DETERMINANTS OF SINGLEHOOD SATISFACTION By Jeewon Oh A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Psychology – Doctor of Philosophy 2022 ABSTRACT DETERMINANTS OF SINGLEHOOD SATISFACTION By Jeewon Oh Although everyone experiences singlehood, people’s experiences and satisfaction with singlehood have not been as thoroughly examined as people’s experiences with romantic relationships. However, single people make up a heterogeneous group and the proportion of single people is rising in many places (Jones & Gubhaju, 2009; Lee & Payne, 2010; U. S. Census Bureau, 2020), making it particularly timely to identify predictors of a satisfying single life. Across a series of studies, this dissertation aimed to examine psychological factors underlying a satisfying single life. First, I examined how attitudes about romantic relationships changed and their links to well-being (Study 1). Expectations toward relationships at the societal level and individual level changed over time. Fewer people perceived marriage as a necessity in recent years. However, even among single people, those who perceived marriage as a necessity tended to report higher life satisfaction. Within individuals, people expected fewer benefits and fewer negatives from being in a relationship over time, and expectations had differential links with life satisfaction and singlehood satisfaction. Even though expectations and resulting singlehood satisfaction might be assumed to change because of major life events (e.g., job loss), trajectories of singlehood satisfaction were not moderated by most major life events except experiencing declines in self-rated health was associated with lower levels of singlehood satisfaction (Study 2). Asking long-term single people, I identified events that single people perceived to be influential for their singlehood (Study 3; e.g., experiences that highlighted their independence). Regardless of the actual event, perceiving the event to be positive predicted higher life satisfaction and singlehood satisfaction. I integrated findings across studies and discuss implications, limitations, and future directions. Keywords: singlehood, satisfaction, major life events ACKNOWLEDGEMENTS Special thanks to my wonderful mentor, Bill Chopik for his guidance on this dissertation and his unending support during the past five years. Many thanks to Deborah Kashy, Rich Lucas, and Emily Durbin for their guidance and feedback not only on this dissertation but also on my graduate training. This would not have been possible without you! I would also like to thank Alejandro Carrillo, Katie Leahy, Prachi Solanki, Jenna Harder, Victor Keller, Caitlin Briggs, Mariah Purol, Rebekka Weidmann, Shree Vallabha, Brian Brutzman, Andrew Rakhshani, Chris, and the MSU writing center for providing critical comments to this dissertation, jumping on zoom at night to help me with R, writing with me, and offering much social support. Speaking of writing together, I’m sure the writing group organized by Mark Brandt holds a share of this dissertation as well—thanks for the accountability and encouragement. I am grateful for Yena Song, who has helped tremendously with coding qualitative responses. I am also so grateful to have family and friends who have supported and encouraged me along the way. I thank my parents, grandparents, Seunggee Hong, Christine Chang, Joo Young Han, Jae-eun Choi, HanNa Lee, Andrea Lee, Lucy Kim, Anna Becker, Sunyoung Lee, Sooyeon Lee, Kyungmin Kim, Juna Kim, Jinkyoung Park, Sharon Bahng, Alison Day, Lauren Collier- Spruel, Kali Vitek, Charlotte King, Hollyn Formosa, Cherie Chen, Kasey McDonald, Christine Kang, Peter Bae, Grace, Pastor Bae, Pastor Jeong’s family. Last but not least, I would like to acknowledge the data/funding sources. Study 1a used data collected by The South Korean Ministry of Culture, Sports and Tourism and hosted on Korea Social Science Data Archive (KOSSDA). Study 1b used data from the German Family iv Panel pairfam, coordinated by Josef Brüderl, Sonja Drobnič, Karsten Hank, Franz Neyer, and Sabine Walper. Pairfam is funded as a long-term project by the German Research Foundation (DFG). Study 2 used the LISS panel data, which were collected by CentERdata (Tilburg University, The Netherlands) through its MESS project funded by the Netherlands Organization for Scientific Research. Data collection for Study 3 was generously funded by the Michigan State University Graduate School and the Psychology Department through the Graduate Office Fellowship. v TABLE OF CONTENTS LIST OF TABLES ......................................................................................................................... ix LIST OF FIGURES ....................................................................................................................... xi INTRODUCTION .......................................................................................................................... 1 The State of Single People ........................................................................................................ 2 Possible Explanations for the Rise in Singlehood .................................................................... 3 Theoretical Explanations for the Heterogeneity of Singlehood Experiences ........................... 5 The Present Studies ................................................................................................................... 9 Overview of Dissertation ........................................................................................................ 10 CHAPTER 1 ................................................................................................................................. 12 Study 1 .................................................................................................................................... 12 The Suffocation of Marriage Model and Changing Societal Beliefs about Marriage ...... 13 Why Might Expectations About Romantic Relationships Change Over Time?............... 14 Study 1a .................................................................................................................................. 15 Research Questions and Hypotheses ................................................................................ 16 Do fewer people believe that marriage is necessary over time? ........................... 16 Is marital status associated with beliefs about marriage? ..................................... 16 Does belief in marriage interact with marital status to predict well-being? ......... 17 Method .............................................................................................................................. 19 Participants ............................................................................................................ 19 Measures ............................................................................................................... 20 Attitudes toward marriage......................................................................... 20 Marital status. ............................................................................................ 20 Well-being................................................................................................. 20 Analytic Strategy .................................................................................................. 21 Results ............................................................................................................................... 22 Study 1a Discussion .......................................................................................................... 23 Study 1b .................................................................................................................................. 26 Method .............................................................................................................................. 26 Participants ............................................................................................................ 26 Measures ............................................................................................................... 27 Expectations for partnership. .................................................................... 27 Satisfaction with life. ................................................................................ 27 Satisfaction with singlehood. .................................................................... 28 Neuroticism. .............................................................................................. 28 Analytic Strategy .................................................................................................. 28 Measurement work.................................................................................... 28 Main analyses............................................................................................ 28 Results ............................................................................................................................... 30 Factor analysis of positive and negative expectations .......................................... 30 How do expectations change over time? .............................................................. 31 vi Do expectations predict life satisfaction, singlehood satisfaction, and length of singlehood? ........................................................................................................... 32 Do trajectories of expectations differ across people who are more often single vs. partnered? .............................................................................................................. 33 Study 1b Discussion.......................................................................................................... 34 CHAPTER 2 ................................................................................................................................. 39 Study 2 .................................................................................................................................... 39 Method .............................................................................................................................. 41 Participants ............................................................................................................ 41 Measures ............................................................................................................... 42 Singlehood satisfaction. ............................................................................ 42 Life events. ................................................................................................ 42 Family relationship satisfaction. ............................................................... 43 Analytic Strategy .................................................................................................. 44 Results ............................................................................................................................... 44 Discussion ......................................................................................................................... 46 CHAPTER 3 ................................................................................................................................. 50 Study 3 .................................................................................................................................... 50 Missed Events ................................................................................................................... 50 Events Characteristics ....................................................................................................... 52 Method .............................................................................................................................. 53 Procedure .............................................................................................................. 53 Participants ............................................................................................................ 54 Well-being Measures ............................................................................................ 55 Satisfaction with singlehood. .................................................................... 55 Life satisfaction. ........................................................................................ 55 Depression................................................................................................. 55 Life Event Measures ............................................................................................. 56 Events characteristics. ............................................................................... 56 Attitudinal, Demographic, and Individual Difference Measures .......................... 56 Expectations for partnership. .................................................................... 56 Basic psychological needs. ....................................................................... 56 Sociosexuality. .......................................................................................... 57 Reasons for being single. .......................................................................... 58 Adult attachment. ...................................................................................... 58 Demographic/Descriptive Measures ..................................................................... 58 Analytic Strategy .................................................................................................. 59 Results ............................................................................................................................... 60 What events were perceived as influential for single people’s happiness? .......... 60 What theoretical constructs predict perceptions of events? .................................. 63 What individual and event characteristics predict well-being? ............................ 64 Discussion ......................................................................................................................... 66 What events do single people find influential? ..................................................... 66 Singlehood theories, event characteristics, and well-being .................................. 69 vii Why are most event characteristics not significantly associated with well-being? ............................................................................................................................... 71 CHAPTER 4 ................................................................................................................................. 75 General Discussion ................................................................................................................. 75 Study 1 .................................................................................................................................... 75 Study 2 .................................................................................................................................... 77 Study 3 .................................................................................................................................... 78 Implications and Future Directions ......................................................................................... 79 CONCLUSION ............................................................................................................................. 83 APPENDIX ................................................................................................................................... 85 REFERENCES ........................................................................................................................... 145 viii LIST OF TABLES Table 1. Correlations among Study 1a variables .......................................................................... 86 Table 2. The proportion of marital status in each wave (Study 1a) .............................................. 87 Table 3. Contingency table with expected and observed frequencies of marital attitudes by waves (Study 1a) ...................................................................................................................................... 88 Table 4. Multinomial regression predicting marital attitudes from marital status (Study 1a) ...... 89 Table 5. Linear regression predicting life satisfaction from marital attitudes and marital status (Study 1a) ...................................................................................................................................... 90 Table 6. Model fit indices for factor analyses (Study 1b)............................................................. 92 Table 7. Factor loadings for the chosen model and the initial model for relationship expectations (Study 1b)...................................................................................................................................... 93 Table 8. Model fit indices for latent growth curves for financial, support, and negative expectations (Study 1b)................................................................................................................. 94 Table 9. Latent growth curves for financial, support, and negative expectations (Study 1b) ...... 95 Table 10. Means, SDs, frequencies, and correlations among study variables (Study 2) .............. 98 Table 11. The latent intercepts and slopes of expectations predicting life satisfaction, singlehood satisfaction, and length of singlehood (Study 1b) ....................................................................... 100 Table 12. Trajectory differences in expectations: Relationship status predicting latent intercepts and slopes of expectations (Study 1b) ........................................................................................ 103 Table 13. Percentage of participants who experience major life events in Study 2 ................... 104 Table 14. Model Fit Indices for Latent Growth Curve Models (Study 2) .................................. 105 Table 15. Changes in Singlehood Satisfaction (Study 2) ........................................................... 106 Table 16. Changes in Singlehood Satisfaction in Response to Life Events (Study 2) ............... 107 Table 17. Codes from Qualitative Analyses (Study 3) ............................................................... 109 Table 18. Means, SDs, frequencies, and correlations among study variables (Study 3) ............ 117 ix Table 19. Independent t-tests on whether people who experienced (vs. didn’t experience) an event perceived events differently .............................................................................................. 121 Table 20. Linear regressions predicting event characteristics from individual differences (Study 3) ................................................................................................................................................. 126 Table 21. Linear regressions predicting well-being from event characteristics (Study 3) ......... 135 Table 22. Linear regressions predicting well-being from individual differences (Study 3) ....... 137 x LIST OF FIGURES Figure 1. Hypothesized interaction between marital attitudes and marital status (Study 1a) ..... 141 Figure 2. Interaction between marital status and marital attitudes on well-being (Study 1a) .... 142 Figure 3. Changes in relationship expectations over time by relationship history (Study 1b) ... 143 xi INTRODUCTION Although everyone experiences singlehood, single people and their experiences of singlehood have not been as thoroughly examined as partnered people and their experiences of romantic relationships have been. However, the proportion of single people (e.g., U.S. Census Bureau, 2020) is increasing, making it particularly timely to understand people’s experiences with their singlehood and predictors of a satisfying single life (Oh et al., 2021) just as researchers study the predictors of a satisfying coupled life (e.g., Cobb et al., 2001). Therefore, this study seeks to explain how singlehood is experienced across a series of three studies with a focus on whether singlehood is a chosen lifestyle and the underlying reasons. In the first two studies, I used existing data. In the first study, I examine trends in people’s attitudes toward romantic relationships, which can inform why people choose relationships over being single (or vice versa) and provide descriptive background information to better situate the subsequent studies. But how and why might attitudes about singlehood and relationships change within a person’s life over time? One possibility is that people’s attitudes towards and satisfaction with singlehood might change as they experience significant life events. Thus, in the second study, I examine whether major life events predict changes in singlehood satisfaction. However, pre-defined lists of events measured in existing longitudinal studies might not capture the wide variety of events that influence single people. In the third study, I collected data to examine people’s perceptions of how they came to be single, specifically focusing on which life events are important for singles as well as their perceptions of missed events. To justify the execution of these studies, I start by providing a general overview of the state of single people, some explanations regarding the increase in the number of single people, and the often- 1 overlooked heterogeneity among single people, which will be a core piece of the dissertation studies. The State of Single People Singlehood is a rising global trend. For instance, among people 15 years and older in the United States, approximately 42% of people were single (defined here as not currently married) in 1993; 10 years later in 2003, approximately 44% of people were single; and in 2020, approximately 48% of people were single (U. S. Census Bureau, 2020). In other words, approximately half of the U.S. population is currently single. A similar trend has been shown in other places around the world, including in Asian countries (Jones & Gubhaju, 2009) and European countries (Lee & Payne, 2010). Despite this widespread increase and the call for a “singles studies” research area (DePaulo, 2014), singlehood and single people are still relatively understudied. When single people are examined, they are most often compared to currently married or coupled individuals to study the link between relationship status and health/well-being. These studies have suggested that marriage or marital histories are associated with health and well- being (e.g., Barrett, 2000; Dush & Amato, 2005). However, more properly examining this question and drawing firm causal inferences have been difficult because people cannot be randomly assigned to a certain marital status. As a result—and as a result of a critical examination of the role of marriage on well-being—the conclusion that marriage is universally (and greatly) beneficial for health and well-being has been critiqued and qualified. For example, studies found some evidence for happier people selecting into marital relationships (Lucas et al., 2003), the happiness gap between married and unmarried may be smaller than expected (Purol et al., 2020), and, although happiness levels increase slightly after marriage, they eventually return 2 to pre-marriage levels (Lucas & Clark, 2006). Therefore, more researchers have started to focus on single people and the aspects of their lives that predict their well-being, such as satisfaction with their single status (Lehmann et al., 2015) and sexual satisfaction (Park et al., 2020), rather than assuming all single people are uniformly less happy than all partnered people because of their single status. However, some studies suggest that people tend to view single people as unhappier compared to partnered people (Greitemeyer, 2009), and this perception aligns with research on singlism, such that negative thoughts and stereotypes about single people might marginalize them in social and institutional settings (Morris et al., 2008; Morris & Osburn, 2016). For instance, people judge single people as having lower self-esteem and more problematic personality traits than partnered people (Greitemeyer, 2009). When comparing people who are single by choice and people who are single not by choice, people who are single by choice are judged as lonelier and interpersonally colder (Slonim et al., 2015). This type of stigma has been proposed to account for observed differences in well-being between single people and partnered people (DePaulo, 2006). This raises the following question: if romantic relationships are a normative experience that many people want (Silverio & Soulsby, 2020) and there are negative stereotypes surrounding singlehood, why is the percentage of single people in the population growing over time? Possible Explanations for the Rise in Singlehood There are many possible reasons behind the observed increase in the single population. First, although people had once strongly expected marriage to bring safety and financial stability, especially for women (Edin et al., 2004; Sorensen & McLanahan, 1987), marriage is no longer seen as strong a necessity for women’s financial well-being. The rise in education and economic 3 mobility partially explains lower marriage rates for women in some countries (Jones & Gubhaju, 2009). A related point is that overall, societal expectations for what kind of lives people should live are changing. There is a greater emphasis on freedom, self-actualization, and independence in people’s lives. These increases can have implications for even married individuals. Expectations for marriage fulfilling multiple areas of one’s life are increasing (e.g., helping fulfill individual goals while also being a good parent, partner, caregiver, provider) and unmet expectations are suggested to result in many unhappy marriages in a society (Finkel et al., 2014). As a result, more people might choose to remain single or return to singlehood after forays into relationships because relationships are not as fulfilling as they are believed to be. Third, the age of people’s first marriage has been on the rise in many countries, which means there are simply fewer people who are married at a given moment, although some of those people might eventually be married (Jones & Gubhaju, 2009). One explanation for this is that marriage had once been seen as a developmental task to be achieved to reach adulthood. But marriage now comes after people are somewhat settled personally and financially. Fourth, there are situational and geographical factors that can it difficult for people to find a partner (Chopik, 2020). For example, some men living in rural areas of China want to be married but face difficulties due to unequal sex ratios in their birth cohorts paired with higher female migration away from the countryside (Liu et al., 2014). These reasons suggest that there are societal and structural explanations for the rise of the single population. However, psychological explanations also likely contribute to the rise in singlehood and are important to investigate. For instance, the life satisfaction of unmarried people has been higher in younger cohorts than in older cohorts (Böger, & Huxhold, 2018) as has the number of single people. These forces provide some support for the possibility that people who enjoy being 4 single are more freely choosing to be single. It would be important to understand what kind of attitudes underlie this trend and promote higher life satisfaction and singlehood satisfaction. Importantly, thinking of being single or in a relationship as a choice also underscores the idea that some people are voluntarily single while others are involuntarily single. Studies comparing voluntary vs. involuntary singles find that voluntarily single adults report lower romantic loneliness (Adamczyk, 2017), less negative emotion, and higher life satisfaction (Apostolou et al., 2019) compared to involuntarily single adults. It may be intuitive that the reasons behind and the experiences of voluntary and involuntary singlehood would be different (e.g., involuntary singles want to be in a relationship but are not). Given that outcomes depend on whether people are more voluntarily or involuntarily single, it would be important to consider this distinction when studying the single population. Theoretical Explanations for the Heterogeneity of Singlehood Experiences Many studies that compare people according to relationship status assume singles are a homogenous group. However, there are many different reasons for being single, which can change a person’s perceptions and experiences of being single. One way that some singles differ from others is the degree to which singlehood is a result of a voluntary decision vs. circumstances (Prabhakar, 2011). Other perspectives on ways that singles differ involve personal or social considerations such as perceived personal deficits or self-blame that hinders people from finding a relationship (Austrom & Hanel, 1985). These different categorizations share a common theme: some people may be single by choice, or voluntarily single; other people may be involuntarily single due to external circumstances or more internal reasons. Several theories provide further insight into the diversity that exists in singlehood—Self Determination Theory, evolutionary psychology, and adult attachment theory. 5 First, Self Determination Theory (SDT; Deci & Ryan, 2000) can help us understand why some single people might be happier than others. SDT suggests that autonomous motivation fosters growth and optimal functioning, which is associated with the distinction between voluntary and involuntary singlehood—people who are single by choice will likely report a greater sense of autonomy and agency. This could stem from an understanding that they have relative autonomy over their life decisions—that they can more freely control their leisure and personal time. Likewise, single people might be investing more heavily in other areas of their lives (e.g., work, hobbies, friendships) that instill a sense of competence and relatedness. Altogether, if autonomy, competence, and relatedness reflect the basic psychological needs required to drive motivation and well-being, voluntarily single people likely satisfy these needs through a variety of other sources beyond romantic relationships (e.g., Derrick et al., 2009; Toepoel, 2013). Consistent with this, voluntary single people have higher life satisfaction than involuntary single people (Apostolou et al., 2019). Second, from an evolutionary perspective, Apostolou et al. (2020) summarized three broad reasons for being single that drive more specific and idiosyncratic reasons for people being single: 1) singlehood can increase individual or group fitness under certain circumstances, 2) modern conditions are different from ancestral conditions, and 3) there are practical constraints that hinder people from finding a partner. They have identified an extensive list of reasons for being single (Apostolou et al., 2020). For example, one of the reasons included “not good at flirting,” which the researchers suggested was due to modern conditions being different from ancestral conditions. In ancestral conditions, marriages may have been at least somewhat arranged or coordinated, or mating was forced or otherwise mandated, and flirting skills were not as relevant a factor. Taking an evolutionary perspective, it is important to also consider the 6 effects of sex. Generally, women are known to be more invested in parenting and are thus “choosier” because their investments are more physically and emotionally costly (Trivers, 1972). Men assume relatively fewer physical and emotional costs, which is one reason why they are hypothesized to be oriented toward pursuing more short-term sexual encounters (Buss & Schmitt, 2019). Consistently, single men are more likely to report being single because they are scared of commitment or are “not the family type.” Overall, people who desire a lot of uncommitted sexual activity might have higher well-being when they are single (assuming that those desires are fulfilled) and thus choose to be single (Edelstein et al., 2011). Third, adult attachment theory, and its integration with singlehood research specifically, suggests three subgroups of long-term singles—single by a secure choice, single due to attachment-system deactivation (i.e., attachment avoidance), and single due to attachment- system hyperactivation (i.e., attachment anxiety; Pepping et al., 2018). Attachment orientations—how people tend to view and approach relationships—have been important to consider as they are closely related to various intra- and inter-individual outcomes (Bartholomew & Horowitz, 1991; Bowlby, 1980). Distributions of secure and insecure adults are often relatively similar among single and partnered populations (Schachner et al., 2008). Although the absolute rates of insecurity might be similar among single and partnered people, attachment insecurity is often associated with poor psychosocial adjustment among long-term singles. Specifically, anxiously attached individuals tend to put high levels of effort into finding relationship partners; maladaptive cognitions and behaviors associated with attachment anxiety may lead to unwanted results whether people are single or partnered (Hazan & Shaver, 1987). Highly anxious people may feel more fearful of being single (Spielmann et al., 2013) and more dissatisfied with their single status, which in turn is associated with lower well-being (Lehmann 7 et al., 2015). Therefore, on one hand, singlehood due to attachment-system hyperactivation (i.e., anxiety) seems to overlap with being involuntarily single. On the other hand, people who are single by a secure personal choice are expected to have higher well-being (Pepping et al., 2018), and this may overlap with being voluntarily single. A point of ambiguity is introduced when considering long-term singlehood and its intersection with attachment avoidance. Attachment theory would predict lower well-being due to maladaptive cognitions and behaviors associated with attachment avoidance. Given their general discomfort with emotional and physical intimacy (Brennan et al., 1998), avoidant individuals may also report being voluntarily single and relatively satisfied with that situation. Because singlehood is a choice, they might be quite satisfied with their singlehood, yet if their attachment needs are not fully met—regardless of their efforts to suppress these needs (Fraley et al., 1998), they might still be otherwise dissatisfied with their lives. Therefore, examining singlehood with attention to different theoretical perspectives might be necessary. Schachner et al. (2008) likewise suggested that the assumption that singles and coupled individuals are the same or show similar levels of functioning might be premature—although there are many similarities between singles and coupled people, long-term singles also reported higher levels of loneliness, depression, and general anxiety that was not attributable to a particular form of attachment insecurity. Thus, these authors called for a more direct examination of the determinants of long- term singlehood beyond attachment orientation. In the current study, I take a holistic approach to assessing determinants of well-being from the perspectives of SDT, evolutionary theory, and attachment theory in addition to forming a broader appreciation of how choice is implicated in people’s decisions to stay single. 8 There is also a great deal of heterogeneity among single people over time and across the lifespan. A study focusing on single young adults found that 53.60% of the sample was voluntary single and 46.40% of the sample was involuntary single (Adamczyk, 2017). Interestingly, 67% of the single sample mentioned wanting a partner in the future while only 6.6% mentioned they would not like to have a partner in the future. This raises another question of whether people who are voluntarily single initially or presently could be involuntarily single in the future (i.e., that they desire a relationship but stay single). This may be why some single people have mixed and/or ambivalent feelings toward their singlehood when we only get a snapshot of their lives (Silverio & Soulsby, 2020). An older study had proposed four types of singles—voluntary temporary, voluntary stable, involuntary temporary, involuntary stable—suggesting singlehood is a flexible process that reflects both choice and an evaluation of people’s immediate life circumstances (Stein, 1981). Therefore, I proposed a series of studies to better understand how single people’s perceptions of and experiences with their singlehood change over time. Specifically, I first examined how perceptions toward relationships in two different cultural samples change over time and how those attitudes are related to life/singlehood satisfaction. I then examined whether experiencing major life events changes singlehood satisfaction. Lastly, I examined whether single people perceive traditionally studied major life events to be major players in determining their satisfaction, the characteristics of events that they perceive as most influential, and theoretically important variables explaining variation in these associations (according to SDT, evolutionary theory, and adult attachment theory). The Present Studies Given the increase in the number of singles and the time spent in singlehood (even for people who eventually end up in a relationship), it is important to understand people’s 9 experiences with their singlehood and predictors of a satisfying single life (Oh et al., 2021). Although people have a fundamental need to belong and yearn for close relationships (Baumeister & Leary, 1995), because belonging needs can be met in other ways (e.g., through other close relationships; Sarkisian & Gerstel, 2016), some researchers suggest single people can be happy and thriving (DePaulo & Morris, 2005). However, other researchers suggest singlehood is not as rosy as advocates for singlehood convey—there is some evidence that singles exhibit some difficulty with social and emotional well-being (Schachner et al., 2008; Silverio & Soulsby, 2020). Thus, the broad goal of the present studies is to better understand the experience of singlehood. More specifically, three studies aim to examine psychological factors behind the experiences of singlehood. Overview of Dissertation Study 1 (Chapter 1) examined how necessary and beneficial people think romantic relationships are for their lives and whether this changes over time, using two existing data sets. Study 1a used a Korean data set to look at changes at the societal level (repeated cross-sectional data) and concurrent associations with happiness. Study 1b used a German data set to model how people’s perceptions of relationships change (longitudinal data of individuals) and how changes in perceptions are linked with singlehood satisfaction. A follow-up question from Study 1 is that attitudes and satisfaction with singlehood might have been formed by life experiences or external pressures that occur across the lifespan. One way to address this is by looking at whether experiencing major life events change singlehood satisfaction. Thus, Study 2 (Chapter 2) tested whether satisfaction with one’s singlehood is reactive to major life events in life in a Dutch sample. However, it is unclear why those events would be important and more fundamentally whether those particular life events that were measured are the major players that determine 10 single people’s satisfaction. To address this possibility, Study 3 (Chapter 3) surveyed single people in the United States and asked about their perceptions of change in singlehood satisfaction, which events they found most influential, the characteristics of those events, and associations with theoretically important individual difference variables. Finally, I integrated findings across the three studies (Chapter 4) and discuss people’s perceptions toward singlehood, relationships and life events, and their links with single people’s satisfaction. I end with directions for future research. 11 CHAPTER 1 Study 1 Not only are singles increasing in number, but their average life satisfaction has also been on the rise (Mikucka, 2016). Because people choosing to be single are happier than people who are involuntarily single (Apostolou et al., 2019), it is possible that increases in singles’ life satisfaction could be attributable to more people being voluntarily single. However, voluntary versus involuntary singlehood is thought to be a flexible status that can change over time (Stein, 1981). Some people might be voluntarily single earlier in life but involuntarily single later in life and vice versa. Unfortunately, longitudinal studies on singlehood that examine reasons for singlehood are rare (if not non-existent) making it difficult to test whether a particular subgroup of single people (e.g., voluntary singles) is growing, whether people who are voluntarily single at one point in time continue to stay voluntarily single and whether the stability or change in these decisions matter for people’s well-being. There are some longitudinal and repeated cross- sectional studies on changes in attitudes and beliefs toward marriage and romantic relationships. These reports reflect societal norms and/or personal expectations about romantic relationships (e.g., that being in a relationship is an important part of life), which would be closely related to beliefs around and experiences with singlehood. Thus, examining beliefs and expectations that people hold about marriage (Study 1a) and romantic relationships more broadly (Study 1b) can give us initial insight into people’s attitudes towards their experience with singlehood and the associated links to well-being. Importantly, we can start to infer some of the reasons why people are increasingly single and quite happy with it by examining how these beliefs and expectations can and have changed over time. 12 The Suffocation of Marriage Model and Changing Societal Beliefs about Marriage The Suffocation of Marriage Model (Finkel et al., 2015; Finkel et al., 2014) provides one account of why singlehood is on the rise. It suggests that various movements (e.g., civil rights and feminist movements) brought about a self-expressive era around 1965. Since then, marriage is being held to a higher standard in recent generations—people are expecting their romantic partners to successfully fulfill many areas of their lives and their marriages to be enriching experiences, rather than default states and processes in which everyone participates. In modern marriages, partners are expected to be excellent parents, friends, sexual partners, sources of income, confidants, caregivers, and more. Such high expectations can undermine relationship satisfaction and life satisfaction: despite high expectations to be married, researchers suggest that actual personal investment in most marriages has not correspondingly increased (Finkel et al., 2015). Thus, people likely do not reap the benefits of their relationships as much because their relationships often fall short of these lofty expectations. Therefore, some people might choose to return to singlehood or stay single because they think a comprehensively happy marriage is unrealistic or not worth a heavy investment; others might indefinitely postpone marriage in hopes of someone meeting those expectations (Lee & Payne, 2010). However, whether the Suffocation of Marriage Model is applicable outside a North American context needs to be tested (Finkel et al., 2014). One reason why the model might be different in different cultures is that marital expectations and relational dynamics also function differently in different cultures (Shiota et al., 2010). Further, given that some single people view their single lives to be fulfilling on their own (DePaulo, 2006), it is likely that some people are single for a different reason other than specifically avoiding the disappointing prospect of an unfulfilling marriage. 13 Nevertheless, many people still view marriage positively and/or expect to get married. For instance, in the U.S., 76% of adolescents expected to either probably or definitely marry in the early 2000s (Manning et al., 2007). Korean college students also have a slightly positive attitude toward marriage on average (M = 3.43, SD = .57 on a scale from 1 to 5; Kim & Jung, 2015) as recently as 2013. Although the proportion of Koreans who believed marriage was necessary decreased from 30% to 10% from 1998 to 2014, the decrease was more noticeable for people older than 40 or born before 1970 and generally, younger people tended to believe marriage was necessary (Lee, 2019). Among people who think marriage is necessary or beneficial, those who find themselves married might be happier. Positive attitudes toward marriage have been suggested to increase the odds of having higher life satisfaction for married people living with their families in Korea even after controlling for marital satisfaction (Ho, 2015). Likewise, people who think marriage is necessary (e.g., view it as a norm) but are ultimately unfulfilled in finding a relationship might be unhappier (Wadsworth, 2016). Alternatively, people may similarly settle into their relationship status (either single or partnered) as they grow older, making the choice distinction less relevant. Ultimately though, these studies consider expectations or attitudes toward a relationship status as static constructs. However, like most expectations, attitudes, and psychological characteristics, they likely change over time for at least some people. Why Might Expectations About Romantic Relationships Change Over Time? People’s goals and motivations shift over time and might influence expectations for romantic relationships. Socioemotional selectivity theory suggests that people are motivated to meet knowledge goals and emotional goals, but their relative importance depends on their perception of time (Carstensen et al., 2003). When people perceive time as limited (due to age, 14 illness, impending transitions, or another reason), they tend to focus on fulfilling social and emotional goals (e.g., doing something to enhance or maintain emotional balance) relative to fulfilling knowledge goals (e.g., learning a new skill, networking for career advancement). Because relationships are a good source of meeting emotional goals, people may come to view romantic relationships more favorably and seek them out (Luong et al., 2011). Consistent with this perspective, among voluntarily single people, some may remain single to prioritize their education or work achievements when they are young and seek romantic partners later in life (Stein, 1981). Considering internal (e.g., socioemotional selectivity theory) and external (e.g., Suffocation of Marriage Model) factors both at play, this study examines how people’s attitudes towards relationships change over time. The increase in the number of single people could be because people expect more negative things from a relationship, expect fewer positive things from a relationship, or both. Thus, the first two studies examine these questions. Study 1a Study 1a aims to describe the overall trend in whether people believe in the necessity of marriage in a South Korean sample from 2006 to 2019 and test whether those beliefs interact with marital status to predict well-being. Singlehood (defined in Study 1a as people who are not married) has been rising around the world, especially in developed countries (Kislev, 2019). Similarly in Korea, marriage rates have decreased from 1990 to 2010 (Raymo & Park, 2020), and the mean age of marriage rose from 1970 to 2010 (Jones & Yeung, 2014), while the percentage of single-person households has increased from the 1960s to 2010, and particularly so since 1980 (Park & Choi, 2015). More recently, the number of single-person households has continued to rise (Kim, 2020). Given the cultural norm of young adults living with parents until 15 marriage, the simultaneous increase in the number of young adults who are single and living alone is noteworthy (Ho, 2015). Research Questions and Hypotheses Do fewer people believe that marriage is necessary over time? I hypothesized that the proportion of people who view marriage as necessary has decreased over time (H1). Based on the Suffocation of Marriage Model, people are putting more value on independence and self-actualization values, in line with an increasing realization that marital partners cannot fulfill the long list of roles prescribed to them. Because this model has been developed and tested mostly in the US, there may be cultural differences that change this link. For instance, particularly among educated East Asian women, the rise in singlehood may not be simply due to the emphasis on the individual. Rather there seems to be a growing dissatisfaction as they experience the conflict between individualism in society and remaining faithful to traditionally unequal gender roles within domestic settings (Jones & Yeung, 2014). Nevertheless, one previous study found that the proportion of Koreans who believed marriage is necessary decreased from 30% in 1998 to 10% in 2014 (Lee, 2019). Thus, I likewise expected to also find the proportion of people who believe in the necessity of marriage to decrease over time. However, because the previous study had six response options (vs. three options for the present study), I expected the percentage to be larger in the present study. Is marital status associated with beliefs about marriage? If people are experiencing more negative aspects of marriage, then previously and currently married individuals may be less likely to believe in marriage as a necessity than never- married individuals. In other words, unhappily married people might rate marriage as less of a necessity because of their negative experiences. On the other hand, if married people are 16 unhappy, they could be more motivated to consider marriage as a necessity to reduce dissonance about being married (Festinger, 1957). Ultimately, it might depend on an individual’s marital experience. One study found that Korean women who married and had children came to hold more traditional views about marriage than women who did not, although their views were not significantly different before marriage and motherhood (Kim & Cheung, 2015). This is consistent with the Suffocation of Marriage Model, which suggests that the best marriages become more satisfying (Finkel et al., 2015)—people in good marriages might naturally think everyone else should get married. Lastly, it is also possible that people who believe marriage is necessary select into marriage while people who believe marriage is optional stay single. I, therefore, did not make a directional hypothesis for this particular sample and discuss the results with respect to how the groups differ on average in whether they believe marriage is a necessity. Does belief in marriage interact with marital status to predict well-being? Figure 1 depicts my predictions for whether beliefs in the necessity of marriage and marital status interact to predict well-being. I expected that never-married single individuals who believe marriage is necessary will report being less happy than single individuals who believe marriage is optional (H2). On one hand, never-married single people who believe marriage is necessary may be more likely to be involuntarily single (i.e., they believe marriage is necessary despite being single). This type of pattern may closely resemble singlehood due to attachment system hyperactivation (i.e., anxious attachment), which is associated with lower well-being (Pepping et al., 2018). Also, according to SDT, involuntary single people’s competency needs would not be met as they feel like they do not have autonomy over their decision to be single—ultimately hindering well-being (Deci & Ryan, 2000). Further, because their situation is not meeting their 17 values/expectations, single people who think marriage is necessary might report lower well- being from a lack of fit between their values/expectations and reality (Higgins, 2000, 2005). Similarly, Dutch singles who viewed marriage as a goal in their lives reported lower levels of satisfaction with their singlehood than single people who did not (Lehmann et al., 2015), and singlehood satisfaction has been a positive predictor of life satisfaction (Oh et al., 2021). On the other hand, never-married single people who believe marriage is an option may feel autonomous over their decision to be single and may meet competency needs that promote well-being through other sources (Deci & Ryan, 2000). However, it is less clear to what extent this group of people resembles those who are single by a secure choice (which would promote well-being) vs. single by avoidant attachment (which would hinder well-being). I expected that married people who believe marriage is necessary will report being happier than people who believe marriage is an option (H3). Previous research found that positive attitudes toward marriage predicted higher life satisfaction for married people (Ho, 2015). However, the underlying mechanisms are less clear—this result could be due to people experiencing a fit between their values/expectations and reality (Higgins, 2000, 2005) or by people with weaker beliefs reporting lower marital satisfaction due to their relationships not meeting their expectations (Finkel et al., 2014). Although these explanations cannot be explicitly tested in the present study, these would be important points to consider in future research. Nonetheless, one important contribution of the present study is that it extends a previous study (Kim & Cheung, 2015) that examined attitudes of never-married, married, and to-be-married people by adding a previously-married group and their reports of life satisfaction based on their relationship attitudes. 18 For that group of previously married single people, I expected that those who believe marriage is necessary will report being less happy than previously married people who believe marriage is optional (H4) for the same reasons as single people. However, I also expected that previously married single people who believe marriage is optional will show lower well-being than single people who believe marriage is optional based on previous research showing life satisfaction decreases after a divorce or bereavement (although some show signs of recovery; Qu & de Vaus, 2015). Method Participants The data came from the Survey on Korean Attitudes and Values (Survey on Korean Attitudes and Values, 2006, 2008, 2016, 2019). The South Korean Ministry of Culture, Sports and Tourism repeatedly collected cross-sectional data starting in 1996 on a representative sample of adults in South Korea. I used all publicly available data from the Korea Social Science Data Archive (KOSSDA) except 20131, which resulted in four waves of data collected over 13 years (2006-2019). This study had a total of 15,249 participants, who were on average 45.03 years old (SD =15.06, range 19-90; Mage2006 = 43.23; Mage2008 = 43.51, Mage2016 = 46.08, Mage2019 = 45.68) and 50.42% women, 49.58% men. The median education was having a high school education; 24.70% of the sample were never-married singles, 5.06% were divorced/separated singles/widowed singles, and the rest were married. 1 Data collected in 2013 will be excluded because the number of response options for attitudes toward marriage (only the first two response options) and marital status (only never-married and married were available response options) was restricted and different than other years. 19 Measures Attitudes toward marriage. Attitudes toward marriage were assessed using a single item: “What is your opinion on marriage?” This item was asked in every wave, and participants could select a statement that was closest to their opinion. “Marriage is a must,” “If possible, it is good to marry,” and “If one is unwilling, marriage is unnecessary.” Marital status. Marital status was measured at every wave, but the response options differed. Waves one (2006) and two (2008) had four categories: never-married, married, divorced, and separated/widowed. Wave three (2016) had five categories by separating a category that was combined earlier (i.e., separated/widowed): never-married, married, divorced, separated, and widowed. Wave four (2019) had three categories: never married, currently married, previously married (e.g., widowed, divorced, separated). In wave three (2016), when relationship status was the most fine-grained, the number of people who were divorced, separated and widowed individuals each constituted less than 2% of the sample (less than 100 people). Thus, I combined groups in other waves to have comparable groups across waves. Well-being. Well-being was assessed using a single item (“In general, how happy are you?”2) on a scale from 1 (Very unhappy/dissatisfied) to 10 (Very happy/satisfied). A question on well-being was asked at all but in the first wave (2006). In the last wave (2019), the response 2 The statements have been translated from Korean for the purpose of this dissertation. 20 options/anchors were phrased in terms of satisfaction even though the question asked about happiness. Thus, I treated happiness and satisfaction as interchangeable3. Analytic Strategy First, I used a χ2 test to test whether the frequency of people who think marriage is necessary has decreased over time and presented a contingency table with the proportions of people across three categories: people who think marriage is a must, good if possible, and unnecessary across four waves. Second, I used a hierarchical multinomial logistic regression to test whether the likelihood of believing in marriage further differs depending on the interaction between time and marital status (single v. currently married v. previously married). The reference group for marital attitudes was believing marriage is a must. In the first step, I entered age, gender, year, and education as control variables. In the second step, I entered two dummy coded variables representing marital status. I interpreted the odds ratio from the full model in the results section. Third, I used hierarchical regression to examine how belief in marriage interacts with relationship status to predict happiness (wave one will be excluded because happiness was not measured). In the first step, I entered age, gender, and education as control variables. In the second step, I entered effects coded categorical variables representing marriage attitudes and relationship status (currently married people and marriage as a must were coded as -1). In the third step, I entered variables that represent the attitudes × status interaction. 3 There was an additional single-item measuring life satisfaction (“In general, how satisfied are you with your current life?”) in wave three. This item and the item used for the entire analysis were highly correlated at r =.77 (n = 5000). 21 Results Correlations among study variables are presented in Table 1. The proportion of marital status in each wave is presented in Table 2. First, the chi-squared test suggested a significant relationship between marital attitudes and time, χ2 (6) = 230.42, p <.001 (Table 3 presents the expected and observed frequencies). On one hand, the frequency of people who think marriage is a must has generally decreased between 2006 and 2019. On the other hand, the frequency of people who think marriage is unnecessary has generally increased. The frequency of people who think marriage is good if possible has stayed relatively consistent. Second, a multinomial logistic regression examined the effect of time, marital status, and their interactions on marital attitudes while controlling for demographic variables. The upper panel in Table 4 compares people who viewed marriage as good, if possible, with people who viewed marriage as a must. There was a 6% increase in thinking marriage is good, if possible, with each year (i.e., a significant effect of time). Never married singles were 31% less likely to think marriage is good if possible than currently married people. Previously married singles did not differ from currently married people. The lower panel in Table 4 compares people who thought marriage is unnecessary, if unwilling, with people who thought marriage is a must. With a year increase, there was a 7% increase in thinking marriage is unnecessary. Previously married singles were 56% more likely to think marriage is unnecessary than currently married people. Never-married singles did not differ from currently married people. Across two comparisons of three marital attitudes, men were more likely to report stronger attitudes toward marriage than women: particularly, the likelihood of viewing marriage as unnecessary (vs. necessary) decreased by 32% for men than for women. Older people were 22 less likely to report weaker attitudes toward marriage. With education, people were more likely to report weaker attitudes toward marriage. Third, a hierarchical linear regression examined how belief in marriage interacts with relationship status to predict well-being while controlling for demographic variables (results in Table 5). The small but statistically significant change in R2 after adding the interaction variables (ΔR2 = .001, p = .008) suggests that marital status moderated the association between marital attitudes and well-being. Figure 2 depicts the interaction by plotting the predicted well-being scores for all combinations between marital attitudes and marital status (predicted scores listed in figure notes). Contrary to what I expected (H2), never-married people who believe marriage is must reported being just as happy or happier than never-married people who believed marriage is a good if possible or unnecessary, respectively. Married people who believed marriage is necessary reported being happier than married people who believed marriage was optional or unnecessary (H3). Contrary to what I expected (H4), previously married people who believed marriage is necessary reported being just as happy or happier than previously married people who believed marriage was good if possible or unnecessary if unwilling, respectively. Younger people, women, and people with more education reported being happier. Study 1a Discussion Study 1a examined changes in societal trends over time—believing in the necessity of marriage and whether this belief is associated with happiness in a South Korean sample. First, I found support for my hypothesis that the proportion of people who view marriage as necessary would decrease over time. Consistent with a previous study that found the proportion of Koreans who believed marriage was necessary decreased from 1998 to 2014 (Lee, 2019), this study also found that the proportion of Koreans who believed marriage was necessary further decreased 23 from 2006 to 2019. Instead, the proportion of people who thought marriage was unnecessary increased. Second, I explored whether there are marital status differences in attitudes towards marriage. Never married singles were more likely to think marriage is a must (vs. good, if possible) than currently married people, although previously married singles did not differ from currently married people. This is somewhat surprising given a past longitudinal study finding that married women held more traditional views about family formation (which included “Marriage is a must”) than women who did not experience the transition (liken to never-married singles; Kim & Cheung, 2015). One explanation is that among the never-married group in the present study are people who expect to be married (e.g., engaged) and have stronger attitudes toward marriage; then, among the married group in Kim and Cheung (2015) are people who may no longer be married, which is consistent with the present finding that previously married singles were more likely to think marriage is unnecessary, if unwilling (vs. a necessity) than currently married people. In this way, it is possible that the experience of being married, and having that marriage end, was associated with viewing marriage as less necessary consistent with the Suffocation of Marriage Model. Finally, I examined whether belief in marriage interacts with marital status to predict well-being. On one hand, contrary to what I expected, single people (previously married and never-married) who thought marriage is a must were just as satisfied if not more satisfied than single people who viewed marriage as good if possible and unnecessary if unwilling. On the other hand, married people who believed marriage is a must were happier than married people who did not. Further, never-married and previously married single people were generally less satisfied than their currently married counterparts. The pattern of results for married people is 24 consistent with past research that found positive attitudes toward marriage were related to higher life satisfaction for married people (Ho, 2015). For single people, I did not find strong evidence that a fit between values (i.e., marital attitudes) and reality (i.e., marital status) promotes well- being (Higgins 2000, 2005). The pattern of results for single people is inconsistent with past research that found Dutch single people who view marriage as a goal were less satisfied with their lives (Lehmann et al., 2015). Even though the percentage of people who endorsed marriage as a necessity decreased over time, 63.35-72.03% of the sample said at the very least that marriage is at least good, if possible, in any given year. In other words, marriage seems to be a strong norm in South Korea, and people who are fulfilling that by endorsing a societally major expectation or finding a relationship may be happy (Wadsworth, 2016). Although this study provided evidence about the changing trends in marriage beliefs in a non-Western context, there are several limitations. First, even though I examined attitudes towards marriage, all response options reflected a positive attitude toward marriage and a strong assumption that marriage is a life goal for many. Given that the data come from a government organization, this may reflect strong societal values or assumptions about the benefits of marriage. However, an important gap is whether people hold negative attitudes toward marriage. Second, after seeing how many people think marriage is a must and whether this trend is changing, a natural follow-up question is why people might think the way they do, whether those beliefs change within individuals, and if they do change, when and in what ways their beliefs change. Third, Study 1a examined attitudes specifically toward marriage but did not capture attitudes toward romantic relationships more broadly, which would be getting closer to more accurately understanding the attitudes of socially single people, defined as people who are neither married nor partnered (vs. legally single people, which can include people who are 25 partnered but not married). Thus, Study 1b addressed these limitations by modeling people’s changes in positive and negative expectations for romantic relationships more broadly. Study 1b Because marriage is an institution, people’s beliefs about marriage might not solely reflect the social aspects of romantic relationships but also the legal or status benefits that marriage provides, for instance. Therefore, Study 1b is meant to examine single people’s expectations about romantic relationships more broadly to consider also social aspects. I will model average reports of and changes in positive and negative expectations, and whether those expectations predict how long/often they are single, their satisfaction with life, and their satisfaction with singlehood. It would be useful to know whether people are single because they do not see the advantages of a relationship or see many disadvantages of a relationship. This will be one of the first longitudinal studies to examine how levels and changes in expectations about relationships predict single people’s satisfaction over time. Method Participants The data came from the German Panel Analysis of Intimate Relationships and Family Dynamics (PAIRFAM; Brüderl et al., 2019; Huinink et al., 2011). PAIRFAM has collected annual panel data starting in 2008, resulting in up to 11 waves of available data. There were over 12,000 people each year across three cohorts (cohort 1: 1971-1973; cohort 2: 1981-1982; cohort 3: 1991-1993). For the main analyses, I included 7,861 participants who had at least three waves of data on expectations for partnership. These participants were on average 26.05 years old (SD = 8.47, range 14-38), 54.3% women and 45.7% men. The median years of education was 11.50 years. In wave 1, 18.4% of the sample were never-married singles, 13.19% married, 14.02% 26 partnered, 1.1% divorced/separated single, .04% widowed single and the rest had missing data in wave 1 (e.g., they joined the study at wave 2). On average, participants had 1.05 previous partners (SD = 1.26) at the start of the study. Before running the main analyses, I conducted factor analyses. For these analyses, I used two subsamples. The first subsample included all participants who had data on expectations for partnership in wave 1 (N = 12,376). The second subsample included all participants who had data on expectations for partnership in wave 5 (n = 7,233); this sample from wave 5 was used to confirm the chosen factor structure from wave 1. Measures Expectations for partnership. Positive and negative expectations for the partnership were measured every two years (waves 1, 3, 5, 7, 94, 11) for both partnered and single people. Table 7 presents all items. Six items measured positive expectations. Participants were asked how strongly they expect several situations related to having a partner on a scale of 1 (Not at all) to 5 (Very strongly). Four items measured negative expectations. Participants were asked how strongly they worry about several situations that could happen within a relationship on a scale of 1 (Not at all) to 5 (Very strongly). When participants answered 7 (No clear idea), those scores were treated as missing (<1% of the data). Satisfaction with life. Participants responded to the question, “All in all, how satisfied are you with your life at the moment?” on an 11-point scale ranging from 0 (very dissatisfied) to 10 (very satisfied). 4 Wave 9 was excluded from analyses because only 56 participants reported on expectations. 27 Satisfaction with singlehood. Only participants who responded ‘no’ to the following question, “In the following, I’ll ask you about intimate relationships. Do you currently have a partner in this sense?” were asked about satisfaction with singlehood. Participants were asked, “How satisfied are you with your situation as a single?” on an 11-point scale ranging from 0 (very dissatisfied) to 10 (very satisfied). Neuroticism. In models where negative expectations were included as predictors, neuroticism was included as a control variable. Neuroticism was measured in wave 3 using an average of four items (e.g., “I am relaxed and don’t let myself be worried by stress.” – reverse scored). Participants rated each item on a 5-point scale from 1(completely false) to 5(completely true). Analytic Strategy Measurement work. I ran a two-factor confirmatory factor analysis using the first wave of positive and negative expectations to confirm they are indeed separate constructs or a one-dimensional scale. I evaluated the model using indices of model fit (CFI, RMSEA, SRMR, TLI; Hu & Bentler, 1999; Sun, 2005). Because model fit was poor for two or more indices, I compared the two- factor solution with the one-factor solution. Because model fit was still poor, I investigated areas of misfit, and decided on a three-factor solution (financial expectations, expecting support, and negative expectations); these decisions are reported in the results section. Main analyses. For the main analyses, I first explored how expectations for partnership change across 11 years by testing a series of latent growth curve models (no-growth, linear growth, quadratic 28 growth) to find the best fitting growth model. Mean scores for each expectation factor were calculated at each wave. I ran latent growth curve models using these observed mean expectation scores across waves. Expectations were centered at the first wave of data collection so that the estimated intercepts could be interpreted as an average score at wave one. Expectations were scaled so that the estimated linear slopes of expectations could be interpreted as an average unit change per wave (i.e., wave 1 = 0, wave 3 = 1, wave 5 = 2, wave 7 = 3, wave 11 = 5) and estimated quadratic slopes could be interpreted as an average unit change2 per wave (i.e., wave 1 = 0, wave 3 = 1, wave 5 = 4, wave 7 = 9, wave 11 = 25). Although negative expectations had significant associations with support and financial expectations, expectations were modeled separately because the model including all expectations did not converge. Second, I tested whether levels and changes in positive and/or negative expectations predict life satisfaction at wave 11, singlehood satisfaction at wave 11, and how long people are single. Specifically, I modeled the intercept and slopes as predictors of life satisfaction, singlehood satisfaction, and length of singlehood (i.e., for those who are partially partnered during the study duration, the number of waves they are single), while controlling for age, gender, education, and net income. The effect of neuroticism on negative expectations was also controlled for. Third, I explored whether trajectories of expectations differed for single people vs. people who were partnered by running a multi-group analysis on the best fitting model chosen for the entire sample. This analysis tested whether long-term singles’ expectations about relationships change differently from people who have been in relationships for long durations. Participants who report being single most (i.e., at least 60%) of the time (i.e., if participants provided all 10 waves of data, reporting to be single for 6+ waves; if participants provided 3 waves of data, 29 reporting to be single for 2+ waves) will be placed in the long-term single group, and participants who report being partnered for most (i.e., at least 60%) of the time will be placed in the long- term partnered group. If the event that this model did not converge, I planned to create a status indicator (1 = single, -1 = partnered, in the same way as described above) and include it as a predictor of the intercept and slopes of expectations in the context of growth curve analyses for the entire sample. Results Factor analysis of positive and negative expectations I ran a two-factor confirmatory factor analysis using the first wave of positive and negative expectations to confirm they are indeed separate constructs. Model fit was poor but rather than it being due to positive and negative expectations being on opposite ends of one spectrum (i.e., one-dimensional scale), it seemed to be due to items for positive expectations diverging. After examining the item content, factor loadings, and correlations among items I observed that among positive expectation items, items about financial and status benefits were loading strongly on the factor while items related to social support were loading weakly. An exploratory factor analysis further suggested that a three-factor solution fit best (a two-factor solution fit better than a one-factor solution), where there were factors for negative expectations, positive expectations regarding support, and positive expectations regarding financial/status benefits. Because the last item in positive expectations loaded weakly on both positive expectation factors and also changed wording halfway through the study, it was excluded. Examining factor level correlations at wave 1, finance and support expectations were weakly positively correlated (r = .04, p = .017), while negative and support expectations were more strongly negatively correlated (r = -.25, p < .001) and negative and finance expectations were 30 positively correlated (r = .162, p < .001). A confirmatory factor analysis using data from wave 5 further provided support for a three-factor solution. Table 6 presents model fit indices for these models and Table 7 presents factor loadings. How do expectations change over time? I modeled how financial, support, and negative expectations changed over 10 years. Table 8 presents model fit indices for no-growth, linear growth, and quadratic growth. Table 9 presents path coefficients from each model. I interpret coefficients from the most complex model tested for each expectation as they fit significantly better than less complex models (i.e., on Δχ2 tests). Figure 3 plots the mean changes over 11 years. On average, people strongly expected to receive support in a relationship (bintercept = 4.51, 95% CI: [4.50, 4.52]) but weakly expected to receive financial benefits (bintercept = 2.11, 95% CI: [2.08, 2.14]) or experience negatives in a relationship (bintercept = 2.34, 95% CI: [2.32, 2.36]). On average, expectations for support decreased linearly (bslope = -.03, 95% CI: [-.04, -.03]). Expectations for financial benefits did not show significant average linear or quadratic change in the quadratic model, although both slopes significantly varied across individuals. On average, expectations for negative experiences decreased and more so in later waves (bquadratic = .01, 95% CI: [.003, .01]). All intercepts and slopes significantly varied (ps < .001), suggesting individual differences in the levels and changes in expectations. Ultimately, I selected the linear models as final models to use as predictors of outcomes due to problems with model convergence (the support model did not converge with the quadratic slope; financial and negative models did not converge after controlling for covariates). In the linear models, mean slopes for both financial expectations and negative expectations suggested 31 linear decreases over time (bfinance = -.03, 95% CI: [-.04, -.02]; bnegatives = -.02, 95% CI: [-.03, -.02]), and the slopes varied across individuals (ps < .001). Do expectations predict life satisfaction, singlehood satisfaction, and length of singlehood? I next modeled life satisfaction and singlehood satisfaction at wave 11, and length of singlehood during the study duration as a function of intercepts and linear slopes of three types of expectation, while controlling for gender, age, years of education, and income (neuroticism was also controlled for negative expectation). Table 10 presents means, standard deviations, correlations among variables. Table 11 presents results from nine models (three expectations and three outcomes). The first page of the table presents the associations between financial expectations and outcomes, the second page presents the associations between support expectations and outcomes, and the third page presents the associations between negative expectations and outcomes. The intercept of financial expectations predicted lower life satisfaction and singlehood satisfaction 10 years later. The slope of financial expectations had a negative association with singlehood satisfaction. Levels and changes in financial expectation did not predict singlehood duration. In other words, people who had greater expectations for financial benefits from partners were less satisfied with their lives and singlehood. People who showed steeper declines in financial expectations were happier with their singlehood. The intercept of support expectations predicted higher life satisfaction and lower singlehood satisfaction 10 years later and shorter periods of singlehood during the study duration. The slope of support expectations had a positive association with life satisfaction and a negative association with singlehood duration, but no association with length of singlehood. In other words, people who had greater expectations for support from partners were more satisfied 32 with their lives but less satisfied with their singlehood and were single for shorter amounts of time. People who showed steeper declines in support expectations were less satisfied with their lives but more satisfied with their singlehood. The intercept of negative expectations predicted lower life satisfaction and longer periods of singlehood during the study duration but did not predict singlehood satisfaction. The slope of negative expectations had a negative association with life satisfaction and a positive association with singlehood duration. In other words, people who had greater expectations for experiencing negatives in a partnership were less satisfied with their lives and were single for longer periods. People who showed steeper declines in negative expectations were more satisfied with their lives and were single for shorter amounts of time. In general, women, younger people, and people with higher income were more satisfied with their lives but these links disappeared after controlling for negative expectations. Across all three models, older adults were consistently more satisfied with their singlehood. Across all three models, men, younger people, and people with fewer years of education and income were consistently single for a shorter period. Do trajectories of expectations differ across people who are more often single vs. partnered? I had planned to answer this question using a multiple-group approach where I test group differences in factor means, variances, covariances, loadings, and residual variances. Due to model convergence issues, I addressed this question by modeling the latent intercept and slopes as a function of status (participants were defined as long-term singles when they reported being single for more than 60% of the study duration vs. long-term partnered when partnered for more than 60% of the study duration). Table 12 shows the estimates for how being single vs. being partnered for most of the time predicts latent intercepts, and linear and quadratic (when 33 applicable) slopes. Figure 3 plots average trajectories for long-term single, long-term partnered people, and the entire sample. For financial expectations, being a long-term single was negatively associated with the linear slope and positively associated with the quadratic slope. In other words, long-term singles more quickly decreased in financial expectations towards the start of the study but showed a slight increase towards the end of the study, while long-term partnered individuals started to decrease towards the end of the study. For support expectations, being a long-term single was negatively associated with the intercept and positively associated with the linear slope. In other words, long-term singles started with lower expectations for support from a partnership than their long-term partnered counterparts, but their expectations decreased more slowly. For expectations about experiencing negatives in a partnership, being a long-term single was positively associated with the intercept and the linear slope, and negatively associated with the quadratic slope. In other words, long-term singles started expecting more negatives from a partnership than their long-term partnered counterparts, and these expectations increased before starting to decrease. Study 1b Discussion Study 1b examined people’s expectations about romantic relationships more broadly. Expectations are useful to examine because they are often linked with subsequent behavior. For example, young adults’ positive attitudes about marriage are linked with their likelihood of becoming married (Cunningham & Thornton, 2006; Manning et al., 2007). Thus, Study 1b examined how people’s expectations for partnership change over time. Then I tested whether 34 those expectations predict important outcomes such as life satisfaction, the length of singlehood, and singlehood satisfaction. I found that people’s expectations are more complex than a positive-negative dichotomy. Rather, there were three types of expectations—expecting to improve financial status, to receive social support, and to go through negative experiences from being in a partnership. People see that a partner might provide different types of benefits such as social support or doing things together and increasing financial status, and these potential benefits are separate from not having negative experiences. Although all three types of expectations decreased over 10 years, people on average more strongly expected to receive social support than to receive financial benefits or have negative experiences. These trajectories further differed depending on relationship history; in general, people who were single for most of the time expected more negative experiences but less benefits over time. Finally, expecting fewer financial benefits and negative experiences, and more support predicted higher life satisfaction. However, for singlehood satisfaction only expecting benefits mattered—expecting fewer financial benefits and support predicted higher singlehood satisfaction. Expecting more support and fewer negative experiences predicted a shorter singlehood. The Suffocation of Marriage Model suggests that people are holding higher expectations for marriage and that these higher expectations when not matched with high investment can make marriage feel as though it is “suffocating.” However, in contrast to this model, the results of this study suggest that in general, people tend to relax their expectations about romantic relationships over time. In addition, although higher financial expectations predicted lower life satisfaction consistent with the model, higher expectations for support predicted greater life satisfaction, which showed that expectations may function differently depending on exactly what 35 is expected from partners. In fact, people who showed steeper declines in expecting support were less satisfied with their lives. This seems to suggest that having and maintaining higher expectations that relationships will be a source of social support is good for life satisfaction. The benefits of social support have been widely studied and simply perceiving that social support is available has been linked with well-being (Assad et al., 2007). People who expect more support might have traits such as optimism that reflect this positive bias towards perceiving social support in their relationships that is adaptive for well-being (Ho et al., 2010; Srivastava et al., 2006). Or these expectations might be grounded in experiences with having supportive social relationships in general, which would predict higher levels of well-being through meeting relatedness needs (SDT; Deci & Ryan, 2000). People who had greater expectations for financial benefits and social support from partners were also less satisfied with their singlehood. People who expect more benefits may be unhappily single because they are not reaping those benefits as a single person. Although we may think financial stability is a benefit that people perceive to be unique to romantic relationships unlike social support—which can come from other types of social relationships (Edin et al., 2004)—the results of this study suggest that in terms of predicting singlehood satisfaction, positive expectations function similarly regardless of the domain. This is consistent with the general idea that a lack of fit between values and reality is detrimental for well-being (Higgins 2000; 2005). Indeed, people who quickly let go of the expectation that partnerships provide financial benefits and social support were happier singles after 10 years. This finding also puts the Suffocation of Marriage Model in a broader context; holding higher expectations toward a partner might not only have implications for the relationship but also for when people are single. 36 Lastly, people who expected more support and less negative experiences were single for shorter amounts of time. In other words, when people held more favorable views about relationships, they were partnered for longer periods. Even if people started with high negative expectations, people who showed steeper declines in negative expectations were more likely to become partnered. This might mean that reductions in negative expectations motivate people to seek a relationship or that people who experience relationships realize it is not so bad. This uncertainty highlights one limitation of this study, which is the weaker evidence for directionality for the outcome length of singlehood. Unlike the other two outcomes that were measured at the last wave of the study, the length of singlehood measures the percentage of time spent in singlehood vs. partnership and cannot tell us whether people were partnered earlier or later in the study duration. Another limitation of Study 1b is that due to convergence problems, I was unable to model quadratic slopes as a function of outcomes or examine changes in all three expectations in the same model to account for their covariation. Therefore, it is unclear whether levels of and changes in one type of expectation lead to changes in another type of expectation and how that might change associations with well-being (e.g., there could be a compensatory effect where high expectations for support compensate for high negative expectations and people are single for shorter amounts of time because of that). Further, although I identified three types of expectations—some of which were related—this fine graining of positive expectations brings up the possibility that there are perhaps other types of expectations (e.g., positive sexual experiences) that may be important to examine in concert with these other expectations. However, the study still laid the groundwork for addressing these types of questions in the future. 37 All in all, this study suggests that lives and singlehood can be more or less satisfying depending on people’s expectations for relationships but that expectations have differential effects on well-being. In general, long-term partnered people expect more benefits and fewer negatives than long-term single people. Across Studies 1a and 1b, I found that attitudes toward marriage are relaxing at a societal level over time, and expectations for relationships are relaxing at an individual level over time, which may be why more people are remaining single. These attitudes also oftentimes predicted measures of well-being. A follow-up question of this study was why expectations change and what that means for well-being. Although people’s motivations can naturally shift over time with age (Carstensen et al., 2003), their related expectations about relationships might change as they are single/partnered over time or even experiencing other life events as a single person. Indeed, attitudes in Study 1 were different depending on people’s relationship history, suggesting the possibility of various life events that shape people’s attitudes and well-being. The next chapter aims to address these questions and possibilities focusing on well-being. 38 CHAPTER 2 Study 2 In Study 1, I have investigated whether attitudes toward marriage and relationships more broadly show signs of change and whether changes in their levels predict singlehood satisfaction. A following question was why singlehood satisfaction and related attitudes about romantic relationships change. One possibility underlying why singlehood satisfaction and attitudes change is major life events, which are time-discrete transitions that people experience— moving residences, marriage, retirement (Luhmann et al., 2012). For example, going through a difficult experience such as unemployment without a partner who can be expected to provide emotional and financial support might change single people’s perspectives on their satisfaction with singlehood. They might reflect on their singlehood status during these transitions and evaluate how happy they are. Following both affirming and disruptive life events, other single people might reflect on their place in the world, reflect on their lives, and become more or less satisfied with being single. In other words, life events that people experience might influence people’s satisfaction with their singlehood. Study 2 aims to address the possibility that satisfaction with singlehood is reactive to major life events in adulthood. On its own, singlehood satisfaction is both somewhat stable and able to change over time, such that it decreases slightly across young adulthood (Oh et al., 2021). However, life events have yet to be comprehensively examined as predictors of individual differences in change in singlehood satisfaction—addressing why it changes over time. Major life events have been used to test changes in personality (Bleidorn et al., 2018; Specht et al., 2011), health (Cohen et al., 2019), loneliness (Buecker et al., 2020) well-being (Luhmann, Buecker, et al., 2020; Luhmann & Eid, 2009), and other psychological characteristics. Outcomes related to singlehood satisfaction 39 show some signs of change in response to life circumstances. For example, single people’s life satisfaction decreases after moving out of their parents’ house for the first time (Qu & de Vaus, 2015). Experiencing a parental divorce is linked to placing less importance on marriage and weaker beliefs in marital permanence in emerging adulthood (Willoughby et al., 2020). In addition, different components of well-being have been shown to decrease after negative changes in health (e.g., disability; Lucas, 2007b). However, less clear is whether and how singlehood satisfaction changes in response to life events. Intuitively, I might predict that negative events would make people less satisfied with their singlehood, and positive events might make people more satisfied with their singlehood, similar to how life events are ostensibly thought to predict life satisfaction. For example, initially, a single person might be leading a happy and fulfilling single life without a romantic partner and meeting attachment needs from family and/or friends (Sarkisian & Gerstel, 2016). After losing a family member or a friend, who was a primary attachment figure and a source of support, their singlehood might suddenly take on a different meaning—without a partner, they may feel less like they are single by a secure personal choice and their satisfaction with singlehood could drop as a result. Single people who experience success in their careers might show an increase in singlehood satisfaction. According to SDT (Deci & Ryan, 2000), autonomous motivation promotes optimal functioning, and single people who intentionally prioritize their careers over romantic relationships (Simpson, 2016; Stein, 1981) might find the opportunity to focus on those goals and reflect on a particularly satisfying element of their singlehood (i.e., that they had the autonomy to pursue a career). However, it is also possible that ostensibly positive events may not drastically boost singlehood satisfaction if people do not have non-romantic close relationships with whom they can share the good news (i.e., capitalization; 40 Peters et al., 2018). Therefore, it would be important to also consider how satisfied single people are with their non-romantic social connections. Yet another possibility is that satisfaction with singlehood is reactive to only certain major life events. Unlike life satisfaction, which is a global judgment of people’s lives (Diener et al., 1985; Pavot & Diener, 2008), singlehood satisfaction is a judgment about a narrower domain in which people are reflecting on an isolated part of their life rather than a broader evaluative judgment. If people do not perceive particular life events to be related indicators of a satisfying single life, their satisfaction might be unaffected when these events happen. Alternatively, one’s relationship status might color how people experience a wide variety of life events. To test how singlehood satisfaction responds to different major life events, I examined how life events predict the trajectory of singlehood satisfaction. Method Participants I used data from the Longitudinal Internet Studies for the Social Sciences (LISS) panel administered by CentERdata (Tilburg University, The Netherlands). The LISS has collected annual panel data from approximately 7,500 people starting in 2007, resulting in up to 13 waves of publicly available data (portions of the study were administered at different times of the year, so the exact years and number of waves for each variable depends on the variable). Participants who had at least three waves of data on singlehood satisfaction were included in the study and, as a result, the sample consisted of 2,132 participants. On average, participants had 6.14 waves of data on singlehood satisfaction (SD = 3.04). At the start of data collection, participants were on average 46.15 years old (SD = 19.93; range: 12-91). The sample was 59.33% women and 40.66% men, and the median education was high school. At wave 1, 30.72% of the sample were never-married singles, 11.44% were 41 divorced/separated singles, and 6.94% were widowed singles; the remaining 50.89% reflects the number of participants who were missing data at wave 1 or partnered initially but became single over time (joining the panel to complete singlehood questions). Assuming people’s relationship status does not change in times that they did not report relationship status (e.g., 12 months between survey waves or if they had a missing report but were single in the previous and subsequent wave), 86.16% of the sample was consistently single (never-married/widowed/ separated/divorced and not partnered), while the remaining 13.84% were in and out of relationships (but still were single for at least three years). Measures Singlehood satisfaction. Thirteen waves of data on singlehood satisfaction measured from 2008 to 2020 are available. The entire panel was asked, “Do you currently have a partner? We understand a partner to be someone with whom you have been in a relationship for at least 3 months. This includes wedded partners.” Only those who responded ‘no’ were asked a single item about singlehood satisfaction. These participants were asked, “How satisfied are you with your situation as a single?” on a scale ranging from 0 (entirely dissatisfied) to 10 (entirely satisfied). Life events. Several major life events were captured at each wave. Life events were health-related (e.g., experiencing changes in health, new chronic illness[es]), job/career-related (e.g., employment, retirement), housing-related (e.g., moving), or family-related (e.g., death of a parent, birth of a child). Table 13 presents the full list of life events and their frequencies. All life events were coded as 0 (did not occur) or 1 (occurred); life events “occurred” if and only if events happened at least once after the first wave up to and including the final wave. 42 For the major life event of getting a new chronic disease, participants responded to 11 questions that asked whether they had a chronic illness (angina, heart attack, high blood pressure, high cholesterol, stroke, diabetes, lung disease, asthma, arthritis, cancer, ulcer, Parkinson’s disease, and dementia). Responses to 11 questions were summed to compute a total number of chronic illnesses at each wave (i.e., ranging from 0 to 11). Comparing the total number of chronic illnesses across waves, when a participant reported a higher number of total illnesses in a later wave, they were coded as a 1 (e.g., a participant who had 2 chronic illnesses in year 2008 and 4 chronic illnesses in year 2010 would get “new chronic illness” = 1). Positive and negative changes in health were assessed by the question “Can you indicate whether your health is poorer or better, compared to last year?” Participants rated their health on a 5-point scale—1 (considerably poorer), 2 (somewhat poorer), 3 (the same), 4 (somewhat better), and 5 (considerably better). Participants who rated their health as at least somewhat poorer (i.e., < 3) at any point in the study duration were coded as experiencing a decline in subjective health. Participants who rated their health as at least somewhat better (i.e., > 3) at any point in the study duration were coded as experiencing an improvement in subjective health. Some life events may occur (or already have occurred) more than once. Experiencing negative life events more than once can further change people’s satisfaction (Luhmann & Eid, 2009). In the current study, I focused on the life events that occurred once (regardless of their re- occurrence) during the study window. Family relationship satisfaction. Satisfaction with family life measured at the first wave was included as a covariate. Participants were asked to respond to “How satisfied are you with your family life?” on a scale ranging from 0 (entirely dissatisfied) to 10 (entirely satisfied). 43 Analytic Strategy First, I examined descriptive information on the life events, looking at the percentage of single people who have experienced each life event. Then, I used latent growth curve models to test whether trajectories of singlehood satisfaction differ depending on whether people experienced an event or not. Previous work suggested that singlehood satisfaction shows quadratic change over time (Oh et al., 2021), thus singlehood satisfaction was modeled as a function of a latent intercept, linear slope, and quadratic slope to test if this unconditional model was appropriate for the present sample. Singlehood satisfaction was centered at the start of data collection so that the estimated intercept can be interpreted as an average score at wave 1. Singlehood satisfaction was scaled so that the estimated linear slopes can be interpreted as an average unit change in satisfaction per year (i.e., wave 1 = 0, wave 2 = 1, wave 3 = 2, wave 4 = 3, etc.) and estimated quadratic slopes could be interpreted as an average unit change2 per wave (i.e., wave 1 = 0, wave 2 = 1, wave 3 = 4, wave 4 = 9, etc.) Second, I examined life events as predictors of intercepts and slopes to look at whether life events predict singlehood satisfaction over and above demographic factors. I controlled demographic variables as predictors of intercepts and slopes. Specifically, I included age, gender, education, income, family satisfaction, and relationship history (i.e., whether people had been consistently single or partnered during the study period). These analyses provide descriptive information on how the trajectory of singlehood satisfaction is moderated by experiencing major life events. Results I wanted to examine how often single people experience major life events (MLEs) and whether experiencing MLEs predict differences in longitudinal trajectories of singlehood 44 satisfaction. Experiencing MLEs was quite rare (see Table 13 for percentages for each event). Among 11 MLEs, only one event—perceiving negative changes in one’s health—was experienced by more than half of the participants (58.9%). The average frequency across the life events was 17.5%. Aside from health-related events that were experienced by 32.7-58.9% of the sample, other events that were related to one’s career, family, and housing were experienced by 12.4% or less of the sample. Only one person gave birth to a child, so this life event was excluded from the following analyses. To estimate how trajectories of singlehood satisfaction differ depending on experiencing a life event, I had planned to model singlehood satisfaction as a function of a latent intercept, linear slope, and quadratic slope. However, due to convergence issues that emerged once adding in covariates and life events, I modeled singlehood satisfaction as a function of a latent intercept and linear slope only when including covariates and life events, although I interpret the findings of unconditional growth curves for both quadratic and linear models here. The quadratic model and linear model both fit well, but the quadratic model fit better than the linear model (see Table 14 for model fit indices). Looking at the path coefficients from the linear model (Table 15), the mean intercept for singlehood was 6.49 (on a scale from 0 to 10), suggesting people were on the more satisfied side with their singlehood. The mean linear slope was positive, suggesting that singlehood satisfaction increased over time on average. There was significant variability in the intercepts and slopes. Adding in the quadratic factor (presented in the upper panel of Table 15), I observed that there was no longer a significant mean linear slope but still significant variability. The average quadratic slope was not statistically different from 0, but there was significant variability in the quadratic slope, though it (b = .001) was much smaller than the variability for 45 the linear slope (b =.18), which may be why models that tried to predict variability in the quadratic slope resulted in convergence problems. Next, I examined life events as predictors of intercepts and slopes of singlehood satisfaction while controlling for demographic variables (i.e., a conditional model). The upper panel of Table 16 presents links with the intercept factor and the lower panel presents links with the slope factor. Declines in self-rated health were related to lower levels of singlehood satisfaction (can be also interpreted as people with high initial levels of singlehood satisfaction were less likely to experience a decline in health). Declines in self-rated health were also related to slower increases in singlehood satisfaction. Life events were otherwise not significantly associated with the intercept and the slope of singlehood satisfaction. I examined age, gender, education, income, family satisfaction, and relationship history as covariates. Women, people who were more satisfied with their family, and consistently single people (who were not partnered during the study) were more satisfied with their singlehood in the first wave. Older adults increased in their singlehood satisfaction at a faster rate over time, while people who were more satisfied with their family and who were consistently single increased in their singlehood satisfaction at a slower rate over time. Discussion In addition to people’s goals and motivations naturally shifting over time (Carstensen et al., 2003), expectations and happiness might be reactive to changing life circumstances (Lucas, 2007a, 2007b). Study 2 extended this literature by examining whether singlehood satisfaction changes as people experience life events. I found that singlehood satisfaction increased on average. This was different from a decrease observed in a previous study that examined singlehood satisfaction in young adults (Oh et al., 2021), but is consistent with trajectories of 46 global life satisfaction showing a quadratic trend over the lifespan (Baird et al., 2010). Major life events (MLEs) have been a major player in the literature on changes in well-being and personality, at least in terms of how much attention has been dedicated to them, if not reliable effects found (Bleidorn et al., 2018; Lucas, 2007a; Rakhshani et al., 2020). However, I found that only subjective changes in health predicted lower levels and slower increases in singlehood satisfaction. These analyses suggested that the trajectory of singlehood satisfaction is resilient to major life events. One anticipated limitation was that major life events are generally rare in the population could be even rarer for a portion of single people (e.g., never-married singles) as several frequently studied MLEs are often, but not necessarily, linked to a relationship domain (e.g., becoming a parent). Indeed, many events were rare in this sample of single people and the lack of influence of life events could have been more methodological (comparing a small number of people who experienced an event with many others who have not experienced the event). Thus, it is unclear whether there are more frequent life events that are traditionally seen as minor that might be more influential for single people’s satisfaction. In using existing data, Study 2 was constrained to using a pre-selected number and type of major life event. There are likely many other life events that are not assessed in these longitudinal panel studies. For instance, perhaps an MLE of a close other (e.g., a best friend’s marriage) could be considered an important event for single people, making their single status salient and ultimately shifting their satisfaction with singlehood. Thus, it would be important to assess whether other life events would be more predictive of singlehood satisfaction. Likewise, it would also be important to investigate missed events, which are major life events not happening within an expected time frame (Luhmann, Buecker, et al., 2020). For example, some single people might expect to be in a long-term 47 committed relationship at some point during adulthood. However, when a long-term relationship does not happen or materialize (and they “miss” the expected starting of a relationship), they may experience a sense of loss (Jackson, 2018) and as a result experience declines in their satisfaction with single life. Further, another future direction is to examine the heterogeneity in how life events predict singlehood satisfaction and other psychological characteristics across samples: the link between a certain life event and a construct changing may be positive in one sample, negative in another, or yet null in other samples, yielding mixed findings of the consistency of life events’ impacts on psychological characteristics (e.g., Chopik et al., 2020; Bleidorn et al., 2018). This heterogeneity may be partially attributable to the fact that the same life event can be experienced differently by different people, and large panel studies might be missing important nuances when they only assess whether an event has occurred or not. The Events Characteristics Questionnaire (ECQ; Luhmann, Fassbender, et al., 2020) has been developed to better capture the nuances of people’s personal experiences with life events. Examining what an event means for a person (rather than using life events as a categorical predictor as having occurred or not) has been suggested as a valuable alternative when investigating the impact of a life event (Kritzler et al., 2021). Therefore, in Study 3, I surveyed single people about life events (experienced and missed) that they perceived to be particularly important in determining their satisfaction and asked about the characteristics of these events to address these limitations. Despite these limitations, the findings of Study 2 suggest that people on average become happier with their singlehood over 12 years of middle adulthood. The trajectory of singlehood satisfaction was unaffected by major life events examined in this study, except declining health predicting lower levels and slower increases in singlehood satisfaction. Being more satisfied with 48 one’s family and being consistently single was, however, associated with singlehood satisfaction. In sum, there may be other relationship-oriented events or events that are more common for singles that might be more influential for singlehood satisfaction. The next chapter aims to address these questions and possibilities while also considering multiple components of well- being. 49 CHAPTER 3 Study 3 In the previous studies, I examined how well-being in single people could shift with broader changes in society (Study 1a), changes in personal expectations towards relationships (Study 1b), and the impact of major life events (MLEs) on singlehood satisfaction (Study 2). However, it is an open question whether traditionally studied events (such as those assessed in panel studies) are the most influential for single people’s well-being. Maybe it is the MLE of close others that are about romantic relationships that matter more. For example, seeing a lifelong best friend entering a romantic relationship may make one’s single status salient or witnessing a close friend experience heartbreak or bereavement might make one decide relationships are not worth the pain. Maybe it is expecting to reach a career goal or a relationship goal by a certain age, but not being there (i.e., missed events) that makes one reflect more about one’s life. Or maybe it is other events entirely that make people reflect on their singlehood. Study 3 explored what events single people perceive to be particularly important in determining their satisfaction with singlehood, what those events are like, and how those characteristics predict current well-being. Study 3 was a mixed-methods study in which single people provided their own set of life events and rated those events on different event characteristics. I linked those characteristics to singles’ well-being and several attitudinal and individual difference variables. Missed Events Missed events are expected major life events that did not occur within a specified time frame often described as normative (Luhmann, Buecker, et al., 2020). These missed events are found to be more frequent than actually experienced events and are thus especially relevant in 50 the context of never-married single people where many of the major life events previously studied in the psychological literature revolve around romantic relationships (e.g., marriage, divorce, widowhood). One possible missed event that is relatively common is not entering a long-term romantic relationship (broadly defined to include marriage) when there was an opportunity. For instance, events in the domains of romance and parenting are found to be two of the top five domains about which people regret (Roese & Summerville, 2005). This is unsurprising based on an evolutionary perspective that people are motivated to secure a good mate and the costliness of missing out on relationships (Apostolou et al., 2019). According to the opportunity principle, when there are clear chances of corrective action (i.e., ways they could have experienced an event), people feel more regret and dissatisfaction (Roese & Summerville, 2005). In other words, people who voluntarily chose singlehood in the past, but are currently involuntarily single might feel more regret and less satisfied with their singlehood (because they might have passed on the opportunity to find a romantic partner). As a result, they may perceive a missed relationship event to be an important game changer in their singlehood satisfaction. Ambiguous loss theory (Jackson, 2018) provides another related framework for examining the experiences of involuntary never-married single people. This theory suggests that some single people hope to be in a long-term committed relationship based on internal motivations and/or external motivations. As a result, they come to develop an image of an anticipated spouse based on societal norms and idealizations. In this way, single people often mentally hold the space of a potential future to-be spouse in their mind, assuming that they will one day end up in a romantic relationship. However, when this expectation is not met over time, people experience an “ambiguous loss in which the spouse is psychologically present yet physically absent” (Lewis 1994; Sharp & Ganong 2007 as cited in Jackson, 2018, p. 213). Thus, 51 a life event many single people might be coming to terms with is the fact that they have not formed a long-term relationship despite mentally assuming that it would happen. Although this type of loss has been reported to also result in pain and negative emotions (de Jong Gierveld et al., 2006) and can be expected to be a major event for some single people, it does not fit the traditional definition of a major life event: that MLEs are time-discrete transitions (Luhmann et al., 2012). In fact, an ambiguous loss does not have a discrete point of loss; the lack of closure and remaining anticipation have been suggested to make this an especially difficult experience (Jackson, 2018). To date, though, it is unclear how common this perception is if single people would spontaneously offer ambiguous loss as an important (missed) life event and exactly how it might affect people. A critical examination of these factors is important to understand how single people think about life events. Further, previous studies focus on involuntary single people, and a broader study examining missed and experienced events of both involuntary and voluntary single people is needed. Study 3 explored events that single people perceive as meaningful regardless of whether they were actually experienced or missed and the event characteristics that predict single people’s well-being. Events Characteristics After gathering data about influential events for single people’s well-being, it would be important to assess what those events are like. Many studies that examined the effects of life events on psychological outcomes have found heterogeneity across outcomes and samples (e.g., Bleidorn et al., 2018; Chopik et al., 2020). One explanation for this is that studies focus narrowly on a few characteristics that can describe an event (e.g., valence: positive vs. negative event, domain: work vs. family) when there is a need to consider multiple characteristics. The Events Characteristics Questionnaire (ECQ; Luhmann, Fassbender, et al., 2020) proposed considering 52 people’s perceptions of events across nine characteristics: challenge, emotional significance, external control, extraordinariness, impact, predictability, social status change, valence, and change in world views. Beliefs about event-related psychological changes (i.e., I think this event will change me in this way) have been linked with perceptions of life events (i.e., if it is perceived to be a greater challenge, of emotional significance, of greater impact, and triggers a change in world views; Rakhshani et al., 2020). These links suggest that events with these characteristics might also be relevant for singlehood satisfaction. Therefore, in the present study, I explored the links between the characteristics of singles’ most recent influential event and their well-being. I also link perceptions of event characteristics with individual differences that are theoretically linked with how people experience singlehood as outlined in the introduction (SDT characteristics, sociosexuality, and reasons for being single—the latter two which are based on evolutionary perspectives—and adult attachment orientation). Method Procedure I recruited single participants for an online survey through Qualtrics Panels. People who are 30+ years old and have been single for at least five years were invited to participate and were compensated for their participation. These criteria were chosen to ensure that people have been single for an adequate period to have experienced enough life events. There were three sections to the survey. First, participants were asked to rate components of their current well-being. Second, participants were asked to describe at least two moments that made them reflect on their singlehood satisfaction (“Think of a specific time that made you reflect on how happy/unhappy you are with being single. Please describe what happened or did not happen with as many details you feel comfortable giving. Did you become happier or less happy with being single because of 53 the time you just wrote about? Why or why not?”). After each event, participants were asked multiple-choice questions to characterize each event (i.e., the ECQ). Third, participants were asked another series of multiple-choice questions that were used in previous studies of this dissertation (see previous chapters), questionnaires measuring theoretically relevant individual differences, and descriptive/demographic questions. All variables that were measured in Studies 1 and 2 were included so that there would be some continuity in measures across the chapters of this dissertation and that some comparisons could be made. Participants This study had 445 single participants who were on average 52.91 years old (SD =14.70; range: 30-92) and had been single for an average of 20.43 years (SD = 17.31; range: 5-70). Regarding relationship history, 59.33% of the sample were never-married singles (n = 264), 28.09% divorced singles (n = 125), 1.57% separated singles (n = 7), and 11.01% widowed singles (n = 49). On average, participants had been in 3.27 relationships (SD = 3.92) in the past (10.65% of the sample had no past relationship) with an average length of .83 years (SD = 1.72; range: 0-16.67). Participants reported not feeling much pressure to be partnered at the current moment (M = 1.64, SD =1.08, on a scale from 1 to 5). The sample was 63.82% women, 35.96% men, and 0.22% other. Regarding sexual orientation, the sample was 85.85% straight, 4.40% gay/lesbian, 4.72% bisexual, 0.63% asexual, and 4.40% other/unsure. Regarding race/ethnicity, 77.08% of the participants were White, 13.48% Black or African American, 4.04% Hispanic or Latinx, 1.80% Asian or Asian American, 0.67% American Indian or Alaska Native, 2.92% Multiracial or other. On average, participants had 13.62 years of education (SD = 4.99) and, when describing their financial situation, reported to be in between neither easy nor difficult (option 4) and slightly difficult (option 5; M = 4.47 on 54 a 7-point scale). Well-being Measures Satisfaction with singlehood. Singlehood satisfaction was measured in two ways. First, the Satisfaction with Relationship Scale (ReSta; Lehmann et al., 2015) measured satisfaction with singlehood using five items (e.g., “In general, how satisfied are you with your current status?”; α = 87). Participants rated their satisfaction on a 4-point scale ranging from 1 (not at all) to 4 (to a great extent). Second, I also included a single-item measure of singlehood satisfaction that was used in Studies 1b and 2. Participants responded to the following question, “How satisfied are you with your situation as a single?” on a scale ranging from 0 (very dissatisfied) to 10 (very satisfied). Life satisfaction. The Satisfaction with Life Scale (Diener et al., 1985) measured life satisfaction using five items (e.g., “In most ways my life is close to ideal;” α = .92). Participants rated their agreement with each item on a 7-point scale ranging from 1 (disagree strongly) to 7 (agree strongly). All items were averaged to calculate a mean life satisfaction score. Depression. The 10-item Center for Epidemiologic Studies Depression Scale (CES-D; Björgvinsson et al., 2013; Miller et al., 2008; Zhang et al., 2012) measured depressive symptoms using 10 items (e.g., “I was bothered by things that usually don’t bother me;” α = .87). Participants rated each item from the following four response options: Rarely or none of the time (less than a day), Some or a little of the time (1-2 days), Occasionally or a moderate amount of time (3-4 days), and Most or all of the time (5-7 days). All items were averaged to calculate a mean depressive symptoms score. 55 Life Event Measures Events characteristics. Participants rated each event they described using the 18-item version of the Events Characteristics Questionnaire (ECQ; Luhmann, Fassbender, et al., 2020). There are two items for each of nine experience characteristics: challenge (e.g., “This experience was stressful.”, α = .83), emotional significance (e.g., “This experience moved me a lot.”, α =.70), external control (e.g., “This experience was in the hands of other people.”, α =.67), (extra)ordinariness (e.g., “Most people like me experience this experience sometime in their lives.”, α =.61), impact (e.g., “This experience had a strong impact on my life.”, α =.71), predictability (e.g., “This experience occurred suddenly.”, α =.80), social status change (e.g., “My reputation suffered from this experience.”, α =.77), valence (e.g., “This experience was joyful.”, α =.68) and change in world views (e.g., “This experience helped me gain new perspectives.”, α =.63). Participants were asked to rate each item on a 5-point scale from 1 (strongly disagree) and 5 (strongly agree). Items were averaged for each event characteristic. Attitudinal, Demographic, and Individual Difference Measures Expectations for partnership. I included 10 items that measured expectations for partnership from Study 1b. Items across each type of expectation were averaged. Four items measured expecting support (α = .89), two items measured expecting financial benefits (α = .79), and four items measured expecting negative experiences from partnerships (α = .81). Items were averaged for each subscale. Basic psychological needs. SDT posits that there are three basic human needs: the need for autonomy, relatedness, and competence. The Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS; 56 Chen et al., 2015) assessed how well participants’ three needs are currently being met. There are eight items for each need with four items measuring satisfaction and four items measuring frustration with each need: autonomy (e.g., “I feel a sense of choice and freedom in the things I undertake,” αsatisfaction = .75; αfrustration =.81), relatedness (e.g., “I feel that the people I care about also care about me,” αsatisfaction = .86; αfrustration =.82), competence (e.g., “I feel confident that I can do things well,” αsatisfaction = .86; αfrustration =.86). Participants rated each item on a 5-point scale ranging from 1 (completely untrue) to 5 (completely true). Items were averaged for each subscale. Sociosexuality. The revised Sociosexual Orientation Inventory (SOI-R; Penke & Asendorpf, 2008) assessed sociosexual orientation with nine items, which reflect evolutionary perspectives on romantic relationships (i.e., the pursuit of uncommitted sexual activity at the expense of longer- term, committed relationships). The SOI-R includes three subscales on the desire, behavioral, and attitudinal facets of sociosexual orientation. The desire subscale (SOI-Desire) reflects an individual's interest in uncommitted sex (e.g., “How often do you have fantasies about having sex with someone with whom you do not have a committed romantic relationship?” α = .89). The sociosexual behavior subscale (SOI-Behavior) reflects an individual's past uncommitted sexual activity (e.g., “With how many different partners have you had sexual intercourse on one and only one occasion?” α = .72). The sociosexual attitudes subscale (SOI-Attitudes) reflects a person’s beliefs about uncommitted sexual activity (e.g., “Sex without love is OK;” α = .68). I used a 5-point scale ranging from 1 to 5 with higher numbers indicating a more unrestricted sociosexual orientation (e.g., more often experiencing sexual arousal outside of a committed relationship, the greater number of casual sexual partners). Items were averaged for each 57 subscale. Reasons for being single. A previous study identified 92 reasons for people’s singlehood that fit under 18 factors, which then fell under four domains: low capacity for courtship, freedom, constraints from previous relationships, and personal constraints (Apostolou et al., 2020). To reduce participant burden, I asked participants to rate their agreement on 18 items based on the factors as provided by the author of the scale. Participants responded to each item using a five-point scale ranging from 1 (Strongly disagree) to 5 (Strongly agree). Then, I combined items to calculate four domain scores: low capacity for courtship (e.g., “I am not good at flirting”; α = .69), freedom (e.g., “I want to be free to do whatever I want”; α = .74), previous constraints (e.g., “I want to devote my attention to my children”; α = .56), and personal constraints (e.g., “Addictions”; α = .67). Items were averaged for each subscale. Adult attachment. The Experiences in Close Relationships-Relationship Structures questionnaire (ECR-RS; Fraley et al., 2011) measured attachment. The scale consists of nine items. Six items measure avoidance (e.g., “I prefer not to show close others how I feel deep down;” α = .70). Three items measure anxiety (e.g., “I often worry that close others don’t really care about me” α = .86). Participants rated each item on a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). Items were averaged for each subscale. Demographic/Descriptive Measures Finally, I asked questions about the participant’s relationship status history: I asked participants how long they have been single, and for participants who have been previously partnered, I asked the total length and number of their past romantic relationships. I also asked 58 about their current feelings toward partnership: “Do you feel pressure to be partnered?” which was rated on a 5-point scale from 1(no pressure at all) to 5(strong pressure). Lastly, demographic questions (age, gender, level of education, race/ethnicity) were asked. Analytic Strategy First, to code qualitative responses for people’s influential events, I read through all participant responses while taking notes of observations and created a preliminary coding scheme by creating categories from the observations (Miles et al., 2018; Woike, 2007). The coding scheme differentiated whether the experience was a traditionally studied personal MLE (if it was, what it was), and what kind of experience it was when it was not a MLE. One research assistant and I separately coded the first 16 responses, discussed discrepancies, and modified the coding scheme (i.e., combining or differentiating categories and re-defining). We repeated these steps four times to reach the final coding scheme, which had 30 codes in total. For every response, each event code received a 0 = event not mentioned, 1 = event mentioned, or -9 = irrelevant response. Participants were asked to write at least two responses, but because several participants wrote that they did not have (or could not remember) a second event to talk about, rewrote their first event, and wrote “nothing” as their second event, responses from second events were only used to develop the coding scheme and not included in quantitative analyses. Thus, all following quantitative analyses are based on codes and ECQs about the first event. Second, I examined the descriptive statistics for events that were mentioned more than 5% of the time (17 codes) to set a minimum threshold for events that were frequent enough to warrant descriptive analyses. Specifically, I examined the means and standard deviations of the characteristics of participants’ first event assuming these were the most influential. Then, I conducted t-tests to examine the characteristics of each event (i.e., if event characteristics 59 differed on whether a response featured the qualitative code or not). Third, I examined the links between event characteristic ratings and individual difference variables that are theoretically linked to the single experience. These associations provided a critical test for whether three existing theoretical frameworks (attachment theory, evolutionary theory, and SDT) were related to how single individuals perceived specific life events. These linear regressions were exploratory in nature given limited theorizing around perceptions of specific experiences in singlehood. Lastly, I tested whether characteristics of the event and individual difference variables predicted various components of well-being using linear regressions. Given the large number of tests for this study, I only interpreted coefficients that were statistically significant at an adjusted threshold of p ≤ .001. Results What events were perceived as influential for single people’s happiness? Across the whole sample, participants wrote about a total of 912 events (22 participants chose to write about a third event). Table 17 presents all codes, definitions, examples, frequencies (frequency of reporting the event and frequency of reporting a positive or negative change in singlehood satisfaction following the event) of experiences that single people perceived to be influential for their happiness as a single person. A large majority of the responses were events that participants personally experienced (17.15%), but 18.86% of the responses were events that others experienced (more than half by close others; the remaining involved acquaintances, celebrities, and strangers). When people described observing others’ events as influential, many of these events were about others’ romantic or family experiences. For example, a participant mentioned that seeing “a friend who is in a terrible marriage” made them “happy to be single.” Often related to observing others’ 60 relationships were missed events—participants described how they were not experiencing aspects of romantic experiences. Some of these reflections were triggered by observing others’ life events or based on their own past experiences. For example, some missed events were related to traditionally studied major life events that others were going through or reflecting on the presence of others in their lives: “My good friend was talking about how he might propose to his girlfriend soon.” Other missed events could be considered more as daily experiences (e.g., “It's lonely trying sleep at night without [the] comfort of another to cuddle with”; “I recently had my parents stay with me for a visit for a full week. I reflected on lucky they are still in my life [sic] and I feel close to them.”). In general, most major life events that are typically accounted for in large panel studies (e.g., moving, getting a new job, becoming sick) were less common (<5%). Participants often described events that would not qualify as a major life event—because they do not have a discrete transitioning time—to be influential for their singlehood satisfaction. Rather, these events described a slow, gradual experience or were marked by the continued presence of something/someone in their lives (e.g., “Happy because of my grandkids”). Among the daily experiences that triggered a change or reflection on people’s singlehood satisfaction, common events were about having a connection to and support from other close relationships (e.g., family and friends). Further, several people reported feeling happy being single because they could choose how to live their lives: “My days are filled with arts and craft projects, reading, baking or spending time with good friends. My home is always clean, laundry caught up and time to spend online. I save money on food and most household essentials. Peaceful.” Most responses that described events related to connections also reported an increase in singlehood satisfaction (71%). However, for other single people, being single meant not having a go-to person to do activities with, which resulted in dissatisfaction: “I want to go out to 61 eat but because I will be alone with no one to join me [I just] forget about it and stay home and have an unsatisfying meal.” Most responses that described events related to lacking connections also reported decrease in singlehood satisfaction (73%). Worth noting, as described in 10% of the events, some participants did not seem to view singlehood as a meaningful part of their identity that they reflect on. Table 18 presents the means, standard deviations, and correlations among all study variables. Examining descriptive statistics of event characteristics (collapsing across the codes), I observed that all characteristics fell around the midpoint (3), with ordinariness and emotional significance showing higher levels and status change having lower levels. Overall, event characteristics were mostly positively correlated with one another. Ordinariness and positive valence of an event were weakly correlated with other characteristics, except that positive valence and challenge showed the strongest (negative) link. Table 19 presents independent samples t-tests on whether each coded event differed on nine event characteristics. Due to the low frequency of some events, I examined characteristics of events that were mentioned at least 5% of the time (n = 17 events; witnessing family members’ and friends’ events were combined into “close others” to increase power and because there was no a priori reason to predict differences). Overall, the 17 events did not differ on levels of predictability, worldview, ordinariness, or status change. Events related to ending/having difficult romantic relationships (relative to events without this code) were characterized by higher levels of challenge, external control, and negative valence. Events related to lacking connection to and support from non-romantic others were characterized by higher levels of negative valence. Events related to experiencing freedom, independence, and a sense of choice in life were characterized by lower levels of challenge and higher levels of positive valence. Events 62 related to bereavement (of non-romantic others) were characterized by higher levels of challenge, emotional significance, impact, and negative valence. Memories of past events were characterized by higher levels of emotional significance. Finally, events related to positive mood and negative mood (e.g., when they were afraid needed comfort) were characterized by higher levels of positive and negative valence, respectively (using the event characteristics questionnaire), suggesting that participants’ written reports of the events and survey rated characteristics of the events corresponded. In short, qualitative responses suggested that there are many events that do not fall under the definition of personal major life events that single people perceive to be influential for their singlehood satisfaction. For instance, there are others’ events, missed events and events without discrete transition periods. What theoretical constructs predict perceptions of events? First, I examined bivariate correlations among event characteristics, theoretically relevant individual differences, and demographic variables (the remainder of Table 18). Sociosexual orientation and attachment avoidance did not show strong correlations with event characteristics. Other individual differences had a statistically significant correlation with at least three event characteristics. For instance, expecting financial benefits and expecting negatives from a relationship were correlated with seeing the event as changing one’s worldview and status, and externally controlled. Satisfaction with autonomy and competence needs were correlated with seeing the event as changing one’s worldview, as more ordinary and positive. Frustration with autonomy, relatedness and competence needs were correlated with seeing the event as more predictable, externally controlled, challenging and changing one’s worldview. Among individual difference variables, constraints from previous relationships (e.g., having children from previous 63 relationships) showed the greatest number of statistically significant associations (rs > .21) with event characteristics—constraints were correlated with perceiving events as more predictable, externally controlled, challenging, and status changing—followed by attachment anxiety and frustration with meeting competence needs. Attachment anxiety and frustration with competence were correlated with perceiving events as more predictable, externally controlled, impactful, negative, challenging, and status changing. Next, Table 20 presents the results of multiple regressions testing whether theoretical individual difference variables predict each event characteristic controlling for demographic predictors and their common variance. Previous constraints were associated with describing a life event as being more predictable, of greater emotional significance, and higher impact. Freedom as a reason for singlehood was associated with higher positive valence. Satisfaction with autonomy needs and feeling inept with courting were associated with lower and higher challenge perceptions, respectively. Personal constraints predicted higher status change. Expectations about romantic relationships, satisfaction/frustration with relatedness and competence needs, sociosexuality, and attachment orientation did not predict event characteristics. Demographic variables except financial difficulty also rarely predicted event characteristics. In sum, most individual differences that were correlated with event characteristics no longer predicted event characteristics after controlling for other individual differences. Feeling like people are single because of previous constraints was the most consistent predictor of how people perceived an event (as more predictable but broadly impactful). What individual and event characteristics predict well-being? I examined the bivariate correlations among event characteristics, theoretically relevant 64 individual differences and four measures of well-being (life satisfaction, multi-item and single- item measures of singlehood satisfaction, depressive symptoms; see Table 18). Perceiving an event as positive and challenging was correlated with higher and lower well-being, respectively. Perceiving an event as status changing was also correlated with lower well-being, but event characteristics were otherwise not significantly correlated with well-being. Satisfaction and frustration with basic needs were correlated with well-being in expected directions (e.g., satisfaction with basic needs was correlated with greater singlehood and life satisfaction and lower depressive symptoms). Attachment anxiety was negatively correlated with all measures of well-being; attachment avoidance was negatively correlated with life satisfaction and positively correlated with depressive symptoms, but not correlated with singlehood satisfaction. I used multiple regressions to test whether event characteristics predicted well-being controlling for demographic predictors (Table 21). Positive valence was associated with higher life satisfaction and both measures of singlehood satisfaction. Status change was associated with lower singlehood satisfaction (only the multi-item measure) and higher depressive symptoms. Table 22 presents the results of multiple regressions testing whether theoretically relevant individual differences predicted well-being controlling for demographic predictors. Meeting autonomy needs was associated with higher life satisfaction. Being single because of the freedom it gives was associated with higher singlehood satisfaction (single-item and multi-item versions). Being single due to previous constraints and attachment anxiety predicted greater depressive symptoms. In summary, across nine event characteristics and 18 individual differences, perceiving events as positive, being satisfied with one’s autonomy, and being single to be independent was associated with higher well-being. Perceiving events as status changing, being single because of 65 constraints and being anxiously attached was associated with lower well-being. Discussion The main aim of Study 3 was to identify events that single people perceive as major determinants of their satisfaction with singlehood and what those events are like. It represents an extension both in terms of the basic description of and enumeration of events that single people think are important and also differentiating information on why they might be impactful. After asking single people about influential events, I found that only a small number of impactful events mentioned by participants were those traditionally studied in panel studies (like in Study 2). Instead of personal MLEs, participants mentioned diverse events ranging from others’ MLEs, missed events, times that made them feel free and independent, and sudden moments that triggered a deep reflection. Participants’ ratings of the characteristics for each event suggested that, while people may experience certain events such as bereavement and difficulties in romantic relationships in a similar way, they may perceive other types of events in unique ways. Reporting higher barriers to getting into a relationship sometimes predicted people’s perceptions of events (more predictable, emotionally significant, impactful, and status changing) but not always. People who reported experiencing more positive events (in valence) and consistency in social status tended to report higher well-being. What events do single people find influential? When asked about moments that led people to reflect on their singlehood satisfaction, participants did mention traditionally studied MLEs, although it was rare. For example, unemployment was experienced in 10% of the sample across 12 years in Study 2, but only 3% of participants in Study 3 mentioned events related to unemployment (including having financial concerns) as being influential for their singlehood satisfaction. Likewise, health-related events, 66 which were experienced by the greatest number of participants in Study 2, were mentioned by less than 5% of the participants in Study 3 as influential events for their singlehood satisfaction. Birth-related events (Study 3: 1.43%) were mentioned at a similar percentage as they were estimated to be experienced (Study 2: 1.22%), but the category in Study 3 also included having grandchildren or hearing about another person’s pregnancy. In other words, if we assume that single participants in this study have experienced these major life events at similar rates as single participants in Study 2, personal MLEs do not seem to be the most salient events that shift people’s satisfaction with being single (i.e., they didn’t mention these events when they were asked what was most important). Instead, participants mentioned diverse events ranging from others’ experiences, to missed events in the relationship domain, to times that made them feel free and independent. The most frequently mentioned kind of event was related to difficulties in romantic relationships. These ranged from people’s reflections on how their relationships ended in the past to seeing others’ relationship conflicts. Many people wrote about how they are glad to not experience negatives in a romantic relationship and attributed an increase in singlehood satisfaction because of this. However, a portion of people also wrote about existing loneliness and attributed a decrease in singlehood satisfaction due to the event. Consistent with these written reports, people who described events about difficulties in romantic relationships rated the events as more challenging, emotionally significant, impactful, negative, and subject to external control. The second most frequently mentioned kind of event was an event that highlighted the freedom and independence afforded by singlehood. Compared to some events that resulted in mixed feelings (e.g., moving), freedom events seemed to be relatively uniform in positive 67 responses (i.e., perceived increases in singlehood satisfaction): 70% of the participants who described a freedom-related event also wrote that they perceived an increase in singlehood satisfaction (vs. 14% who perceived a decrease in singlehood satisfaction). Consistent with their written reports, people who described these events rated the event as more positive and less challenging. As suspected, sometimes participants described others’ major life events in the relationship domain, such as marriage, divorce, and pregnancy—in other words, a missed event that they did not experience. However, many other times, participants described missed experiences coming from not having a partner or more general social connection, such as not experiencing relational conflict/obligation, physical intimacy, or daily companionship (e.g., having a person to go with for a nice meal). Past research that examined missed events including infertility and missed sexual/romantic transitions found that people who experienced missed events were more heterogeneous in how they changed in well-being (i.e., lower rank-order stability in well-being, Luhmann, Buecker, et al., 2020). The findings from this study suggest that people might focus on different aspects of missed events: among people who missed a romantic transition, some people might feel free and autonomous because they are missing relational obligations. Other people might be feeling lonely because of the lack of consistent company or feel a sense of loss (Jackson, 2018). However, some experiences described in this study related to missing relational experiences would not qualify as a missed event because participants said they chose singlehood. Missed events are defined as events that do not happen within an expected timeline (i.e., which implicitly suggests that missing an event is not under a person’s control—yet voluntarily single people chose to miss these events on some level). Overall, many events that were mentioned by the participants were not time-discrete, but rather 68 oftentimes repetitive or idiosyncratic experiences. Future research would therefore be needed to modify definitions of life events and missed events to test whether the types of life events identified in this qualitative study affect singlehood satisfaction. Singlehood theories, event characteristics, and well-being I also examined whether individual differences that were theoretically relevant to the singlehood experience predicted how people perceived events regardless of the specific type of event. Mainly, I wanted to implicate self-determination theory, attachment theory, and evolutionary perspectives (sociosexuality and reasons for being single) with the perceptions of these life events. Reasons for being single (Apostolou et al., 2020), based on evolutionary perspectives, were the most frequent predictors of event characteristics. On one hand, people who felt previous relationships constrained them from being partnered perceived events as being more predictable, of greater emotional significance, and higher impact. People who felt that personal issues were constraining them from being partnered perceived higher status change. In other words, people who may be more involuntarily single were perceiving events related to their singlehood as more impactful (in general, emotionally, for social status). On the other hand, people who reported being single to be independent perceived events as more positive. Similarly, satisfaction with autonomy (SDT; Deci & Ryan, 2000) was the other theoretical variable associated with people’s perceptions of how challenging an event was; people who were meeting their autonomy needs perceived events to be less challenging. Alternatively, people who did not feel much challenge felt more autonomous. The overall pattern of results across four individual difference variables is somewhat consistent with previous findings that show people who are involuntarily single people show greater negative emotion (Apostolou et al., 2019) and more loneliness (Adamczyk, 2017) than voluntarily single people. 69 Given some theorizing about singlehood experiences particularly within the domain of adult attachment theory (Pepping et al., 2018; Pepping & MacDonald, 2019), I was surprised to find limited evidence for links between attachment orientations and event characteristics. Attachment anxiety did show a positive association with perceived challenge, but it did not meet the conservative significance level to reduce type I error probability. In sum, people’s perceptions of events (that were relevant for their singlehood) seem to be linked with individual differences that are directly related to singlehood (i.e., the reasons for being single). Although this was a cross-sectional study that relied on people’s recollection of life events, the lack of consistent individual difference predictors has been seen in other types of studies examining the effects of personality on adaptation to life events (Anusic et al., 2014; Yap et al., 2012). In general, among event characteristics, positive valence was associated with higher well- being while status change was associated with lower well-being. Financial difficulty was associated with lower general well-being (lower life satisfaction and more depressive symptoms) but not singlehood satisfaction. Among the theoretically relevant variables, it was mostly a few individual difference variables based on evolutionary theory—reasons behind singlehood but not sociosexuality—that predicted well-being for singles. People who indicated freedom as their reason for singlehood were more satisfied with singlehood. Based on evolutionary perspectives, not engaging in long-term monogamous relationships can be considered adaptive in some environments and situations, namely those in which having multiple sexual partners can improve fitness and focusing on aspects of one’s life (e.g., career or education) can increase mate value (e.g., wealth; Fisher et al., 2008). In addition, meeting one’s autonomy needs was associated with greater life satisfaction; being single due to personal constraints and attachment anxiety predicted greater depressive symptoms. Although links between theoretical constructs and well-being were 70 in expected directions and intuitive, the overall takeaway from Study 3 is that there were relatively few associations between theoretical variables and perceptions of life events among singles; the lack of links among most theoretical variables and well-being was surprising. Why are most event characteristics not significantly associated with well-being? Study 3 found that most event characteristics were not significantly associated with the measures of well-being. One possibility for the lack of findings is that some people have a relatively stable set-point of well-being (Lucas, 2007). Previous research suggests some events lead to lasting changes in well-being, but there are individual differences in whether people adapt and return to original levels. Consistent with this possibility, one participant who talked about feeling alone as the only non-couple at a friend’s funeral mentioned, “I was less happy at the moment but fine now. I can’t let a temporary circumstance keep me sad.” Likewise, many participants who described moments that made them reflect on their satisfaction with their singlehood satisfaction mentioned stability in their satisfaction (e.g., “Every silent moment I become aware of reminds me of my being content with my single status. My happiness remains the same. I am never changing in and of my mood.”). In other words, for some people, their well-being and particularly singlehood satisfaction may be resistant to change from life events. One insight from this study is that people may have some degree of insight into these adaptation processes—that they acknowledge feeling sad or dissatisfied at one point but that these feelings dissipated over time. A second possibility is that people’s descriptions of the events were complex, and the events often happened over a long time, evoked various emotions, and had implications for concurrent and future events beyond that single experience. For example, a participant wrote, “When I got my dream job at [blinded], [it] was a very happy time. And losing it 4 months later 71 due to COVID-19 was definitely deviating [sic].” As shown in this example, it is unclear whether the perceived characteristics are about the first event (getting the job), the second event (losing the job), the relatively short time of positive feelings, or a combination of these features and others. Even if they were asked to rate characteristics for the first and second events separately, the second event occurring might have changed the perception of the first event. Previous research has found that recent events (within the past 3 months) are more likely to influence well-being (Suh et al., 1996). My study shows that one possible reason behind this phenomenon is that multiple events happen in that same time frame, not just one event. On a slightly different note, even when participants did not experience a separate opposing event afterward, many participants wrote about their mixed reactions that might even change over time. Specifically, they were often said they felt both happier and unhappier as a result. In addition, some people perceived more gradual changes. For instance, a participant mentioned being less satisfied with their singlehood and that they are “just tired of going through life alone.” This suggests a possibility that for some, singlehood satisfaction may have gradually changed without a specific trigger (or that they were relatively satisfied with being single at one point but eventually not satisfied at another point). This points to a third issue that some people may not find singlehood a significant part of their identity. For example, responses like “I rarely think about being single” may suggest that singlehood is not an important part of their identity. This is consistent with work suggesting that in general, singlehood tends to be viewed less as a group (i.e., low entitativity; Fisher & Sakaluk, 2020). “I honestly never think of happiness as it relates to be single or not. I can't measure my hapiness to beinv single or not. I measure my happiness based on my feelings at that moment. I've experined being unhappy while in a relationship. To me, they don't relate. [sic]” Although 72 people who choose singlehood might strongly identify as a single person, people who are expecting to be partnered in the future might not take on the identity as a single person. Future research could examine whether life events change singlehood satisfaction differently across subgroups of single people (e.g., those who hold a strong singlehood identity). All in all, this study had many strengths. It suggested the need to consider different types of life events to better understand singlehood, including not only experienced but missed life events that happen unexpectedly. This study also identified the characteristics of the most common events for singles and individual difference characteristics associated with different components of well-being. However, one noteworthy limitation is that the open-ended life event reports were retrospective, a common limitation when asking people to report on past life events. This means that recall biases are possible because, in hindsight, people tend to re-evaluate the events (Luhmann, Fassbender, et al., 2020). Thus, the event characteristics used to describe an event that individuals have already reflected on and thought about may not have been the best way to quantify their perceptions of a specific event. However, many people acknowledged this in their qualitative responses, (e.g., they were dissatisfied as a single person after a bereavement but have learned to be ok with it). Future research is, therefore, needed to see whether single people revise their recall of important life events. Nonetheless, this study identified several events that single people perceived to be impactful and how people perceived these events (i.e., characteristics of these events). Experiencing events that are perceived to be positive and not status changing was associated with higher well-being. Surprisingly, many individual difference variables that were expected to be associated with singlehood were not associated once they were entered simultaneously into a regression with demographic characteristics. The degree to which people report being single due 73 to constraints from previous relationships was the most consistent predictor of event characteristics and also a predictor of depressive symptoms. Feeling autonomous and being single to be free of obligations was associated with higher life satisfaction and singlehood satisfaction, respectively. 74 CHAPTER 4 General Discussion In this dissertation, I examined single people’s perceptions and well-being to provide a deeper understanding of singlehood which is becoming a more normative experience. The first study tested whether attitudes about relationships change over time and whether attitudes predict well-being. The second study then examined whether singlehood satisfaction changed as a function of major life events. The third study examined people’s perception of change in singlehood satisfaction (as a function of life events) and tested whether characteristics of events were significant predictors of single people’s satisfaction. In the following sections, I summarize the findings of each study and discuss the implications of these findings for and future directions of singlehood research. Study 1 Study 1 examined how necessary and beneficial people think romantic relationships are for their lives and whether this changed over time, using two existing data sets. In Study 1a, I used a South Korean data set to look at changes in marital attitudes at the societal level and concurrent associations with happiness across marital status. This was also testing whether the Suffocation of Marriage Model (Finkel et al., 2015) applied to a non-North American sample. The model suggested that marriages are becoming suffocating because people nowadays are holding higher (and sometimes unrealistic) expectations for their partners without matching levels of investment on their own part. With time, fewer South Koreans viewed marriage as a necessity in life. Never-married single people viewed marriage more as a necessity than currently married individuals. People who were previously married viewed marriage as more unnecessary than currently married individuals, providing some evidence consistent with the Suffocation of 75 Marriage Model. Nonetheless, when examining what holding these attitudes means for well- being, people with stronger marital attitudes tended to report higher well-being regardless of their experience with marriage. Thus, these results may provide evidence for some type of a selection effect, where happier people endorse a societal norm about marriage (Lucas et al., 2003; Wadsworth, 2016). However, it was unclear what people mean when they reported believing marriage was a necessity or not—the beliefs may reflect social aspects of having a partner, children, additional extended family members or legal or status benefits that marriage provides. To better tease out people’s beliefs and expectations about romantic relationships and how those might change within individuals, I conducted Study 1b. I used a 10-year German longitudinal data set to model how people’s perceptions of relationships change and how levels of and changes in perceptions are linked with well-being. There were at least three types of expectations—expecting negatives in the relationship, expecting financial/status gains, and expecting support from the relationship. People who expected romantic relationships to bring fewer financial benefits were satisfied with life and with singlehood. People who expected romantic relationships to bring support were more satisfied with life but less satisfied with their singlehood. People who expected romantic relationships to bring negative experiences were more satisfied with life but no more/less satisfied with singlehood. In other words, missing relationships that are expected to be bad was not associated with a happier single life, but missing relationships that are expected to be good was associated with an unhappier single life. This suggests that single people might be more attuned to the benefits they are missing out on rather than avoiding the negatives. Further, although expectations in this study were about romantic relationships more broadly rather than strictly about marital relationships, links with 76 life satisfaction inform the Suffocation of Marriage Model (Finkel et al., 2014) of the possibility that certain types of expectations might also matter more for the well-being and maintenance of relationships. In sum, attitudes and expectations about marriage and romantic relationships may be changing at both the societal and individual levels, which have different implications for different components of well-being. Study 2 Next, I examined why one’s singlehood satisfaction might change over time and examined major life events as candidate predictors (Luhmann et al., 2012). Using annual panel data, I found that across 11 life events, only declines in self-rated health were related to singlehood satisfaction; people who experienced a decline in health reported lower levels of singlehood satisfaction and slower increases in singlehood satisfaction over time. This is consistent with how other components of well-being have decreased after negative changes in health (e.g., disability; Lucas, 2007b). All other life events did not consistently predict levels or changes in well-being. There are several possible conclusions from these findings: the first is the most straightforward/simplistic interpretation that singlehood satisfaction is resilient to most major life events. Or that at least middle-aged singles are resilient in how satisfied they are. It is possible that singlehood satisfaction shows more stability with age, consistent with findings that suggest increased stability in life satisfaction with time (e.g., Ehrhardt et al., 2000). A second possibility is that the lack of significant associations with most events is a methodological artifact. There was a disproportionately small number of participants who experienced most events, which made testing some events difficult to do (i.e., led to model convergence issues) or, even when tested, might have made it difficult to detect an effect even if it were there. A third more nuanced 77 possibility is that similar to how only positive (but not negative) expectations about romantic relationships mattered for singlehood satisfaction, there may be specific events that are relevant for singlehood. For instance, some studies suggest life satisfaction change after experiencing a parental divorce (Willoughby et al., 2020). Perhaps these types of events in the domain of romantic relationships would be more relevant for singlehood satisfaction, but in a sample of middle-aged adults, such an event was rare (<.05%). Therefore, the finding that most MLEs do not predict singlehood satisfaction needs to be interpreted with caution given these possibilities. Study 3 Motivated to better understand what types of events were influential for singlehood satisfaction, I surveyed long-term single people about their perceptions of change in singlehood satisfaction in Study 3. I found that single people perceived many life experiences as meaningful for their singlehood beyond simply the major life events mentioned in Study 2. Common events mentioned by participants included experiencing difficulties in romantic relationships (e.g., memories of a previous abusive relationship, seeing couples have conflicts). These events were characterized by lower positive valence, which was a significant predictor of lower life satisfaction and singlehood satisfaction. Many people also wrote about times they were glad to miss negative experiences in a relationship and reported a following increase in their singlehood satisfaction. This qualitative finding seems to contradict quantitative findings that expecting negative experiences in a relationship do not predict singlehood satisfaction concurrently (Study 3) or prospectively (Study 1a). It may be that a portion of those people are involuntarily single and reporting increases in singlehood satisfaction from missing negative relationship experiences (i.e., benefit finding) might be an attempt to reduce dissonance (Festinger, 1957) or based on motivations to self-protect (Alicke & Sedikides, 2009). It may also be that people simply think 78 those events are influential because they lack ability to identify the true reason (Nisbett & Wilson, 1977; Wilson, & Nisbett, 1978). Or it may simply be that missing negative relationship experiences may influence singlehood satisfaction in the short term (Suh et al., 1996) but those experiences do not translate long-term links with singlehood satisfaction through negative expectations. Another frequently observed event mentioned experiencing freedom to live life as they wish—pursuing career opportunities, hobbies, and travel as well as meeting up with people they want to when they want to. These events were characterized by greater positive valence, which again was a significant predictor of higher life satisfaction and singlehood satisfaction. These responses were consistent with a perspective that single people are not suffering but rather are happy and thriving (DePaulo & Morris, 2005) and often have satisfying non-romantic close relationships (Sarkisian & Gerstel, 2016). In addition, quantitative models that tested for significant individual difference predictors of event characteristics and well-being found factors related to autonomy, freedom (i.e., satisfaction with meeting autonomy needs, being single to be independent) as well as constraints that limit autonomy and freedom (i.e., having constraints that hinder people from being in a relationship, and financial difficulty) to be important. In other words, this sense of freedom and autonomy was particularly relevant and colors how single people see the world, the events that happen to them, and themselves. Implications and Future Directions Putting everything together, one main finding of this dissertation is that marriage is becoming less and less of a necessity even in non-Western societies. Tracking with this changing norm was an increase in the proportion of never-married singles, consistent with more global trends (Jones & Gubhaju, 2009; Lee & Payne, 2010; U. S. Census Bureau, 2020). Nevertheless, 79 people who held on to the view that marriage is necessary showed higher well-being (after controlling for marital status), single people reported lower well-being than married individuals, and marital status did not moderate marital attitudes on well-being. This may be partially due to the still-present norms in Korea to be married (Lee, 2019; Verbakel, 2012) and the singlism that might marginalize single people in social and institutional settings (Girme et al., 2022; Morris et al., 2008; Morris & Osburn, 2016). With societal expectations toward marriage relaxing, as well as individuals’ expectations changing over time, it is an important question for future research to test whether singlism persists in the context of these changes, and how to mitigate its effects. A second main finding is that single people hold different types of expectations that change over time and prospectively predict well-being. Single people who expected more financial benefits or social support in a relationship were less happy with being single. Interestingly, these two expectations of benefits were weakly correlated, while financial expectations were positively correlated with expecting negative experiences in a relationship and support expectations were negatively correlated with expecting negative experiences. Despite these correlations, I was unable to model change in more than one expectation at a time due to convergence problems. In addition, there are other expectations that may be important to examine in concert with changes in these expectations. For example, sexual satisfaction is associated with singlehood satisfaction, and romantic relationships are one way that people expect to meet desires for sexual satisfaction (Park et al., 2021; Park & MacDonald, 2022). This presents an exciting opportunity for future research—examining whether diverse expectations interact to predict well-being. A third main finding was that most life events, most event characteristics, and most individual difference variables thought to be implicated in the developing theory of singlehood 80 (e.g., Pepping & MacDonald, 2019) did not predict singlehood satisfaction. Starting with life events, one reason why they might be unrelated to singlehood satisfaction is that even time- discrete transitions are messy in establishing how they impact people. Other events may happen before and after an event that change the meaning and experience of the event. People reflect on an event over time, and these reflections may continue to change its impact as people reevaluate (Luhmann, Fassbender, et al., 2020). In addition, many events that participants wrote as influential were missed events but it was unclear whether participants expected those events to happen within a specific timeframe or merely eventually (Luhmann, Buecker, et al., 2020), although occurring during a specific timeframe is part of the definition of a missed event. Rather, events were more closely tied to the concept of an ambiguous loss, where there is no discrete point of loss or point of closure (Jackson, 2018). This is theorized to make the missed experience hard for people who have developed a mental image of an anticipated spouse. These issues imply that the measurement of life events has much room to be improved, particularly when thinking about what events might be influential for singlehood, influencing expectations, perceptions, and satisfaction. In the introduction, I outlined several theories that could help further insight into the diversity that exists in singlehood—Self Determination Theory, evolutionary psychology, and adult attachment theory and tested them directly in Study 3. Even though some of these variables have been shown to predict well-being in past studies (e.g., attachment; MacDonald & Park, 2021), most associations were not significant when I included various theoretical perspectives at once. One reason for the discrepancy may be due to differences in culture (defined broadly) and experience. For example, the sample in MacDonald and Park (2021) represented more countries (vs. a U.S. sample in Study 3), was younger (on average, 31 vs. 53 years old), and had been 81 single for a much shorter period (on average, 3.5 vs. 20 years). It is possible that the role of attachment differs across these groups, although the lack of consistent individual difference predictors on well-being has also been seen elsewhere (Anusic et al., 2014; Yap et al., 2012). A last main finding is that there was a lack of introspection about singlehood even in a sample of long-term singles. This strengthens the idea that singles make up a heterogeneous group. Specifically, one distinguishable dimension is the degree to which singlehood is a result of a voluntary decision. Some singles may hold a stronger identity as a single person. Other singles who feel they are single because of circumstances may not even consider it to be a part of their identity as they view it as a transient status (Prabhakar, 2011). Several participants mentioned that they did not know if there was an event that was meaningful for their singlehood satisfaction. Some studies suggest that sometimes people do not have introspective access to how and why events affect them psychologically (Nisbett & Wilson, 1977; Wilson, & Nisbett, 1978). This may be particularly true for singles who are not actively attending to the fact that they are single. Thus, for people whose singlehood identity is not salient or important, their well-being may respond to life events differently from people those who hold a strong singlehood identity. 82 CONCLUSION This dissertation was motivated by a desire to contextualize the growing proportion of single people across the globe. Societal expectations toward marriage seem to be changing as well as people’s own expectations about romantic relationships more broadly (Study 1). These changing attitudes are important for understanding how to promote a psychologically satisfying singlehood experience, particularly because what predicts a happy life in general did not always predict a happy single life. In other words, we cannot assume factors promoting life satisfaction (global satisfaction) will also promote singlehood satisfaction (domain-specific satisfaction) even though both satisfactions are often positively correlated. More work is needed to identify the determinants of a satisfying single life across different domains of life. The attempt to understand how expectations and singlehood satisfaction are formed was not entirely successful (Study 2). Experiencing a decline in self-rated health, which was a common event in middle- aged adults, predicted lower levels of singlehood satisfaction that increased more slowly compared to their healthy counterparts. Otherwise, major life events did not predict trajectories of singlehood satisfaction. Several long-term single people reported that that they perceived events in the domain of partnership as influential (Study 3). Particularly events related to experiencing ending/deteriorating romantic relationships were characterized by more negativity, which was associated with lower well-being. In contrast, events related to cherishing freedom to live one’s life without a partner were characterized by more positivity, which was associated with higher well-being. Although many theoretically relevant individual differences were not linked with well-being, my data suggested that the sense of independence and autonomy in singlehood may make the singlehood experience seem more positive. 83 In sum, this dissertation aimed to identify the determinants of singlehood satisfaction by examining it from different angles. These studies highlighted the need for future research investigating within-group variability in singles’ well-being by examining relationship histories, expectations, life events, and identification (as a single person). Altogether, a full appreciation of these factors will be influential in developing a unifying theory of and description of the singlehood experience. 84 APPENDIX 85 Table 1. Correlations among Study 1a variables 1 2 3 4 5 6 7 8 9 10 11 1. Never married 2. Previously married 3. Currently married 4. Marriage is a must -0.18 0.06 0.14 5. Good, if possible -0.05 -0.04 0.07 6. Unnecessary 0.22 -0.02 -0.20 7. Happiness 0.02 -0.10 0.03 0.04 0.06 -0.09 8. Age -0.69 0.24 0.54 0.29 -0.02 -0.25 -0.11 9. Gender 0.09 -0.07 -0.05 0.08 0.02 -0.10 -0.03 -0.02 10. Education 0.38 -0.23 -0.26 -0.23 0.07 0.15 0.15 -0.63 0.13 11. Time (years) 0.07 -0.02 -0.06 -0.11 0.04 0.06 -0.02 0.06 0.01 0.08 Note. Bivariate correlations that are statistically significant at p < .05 are bolded. Mhappiness = 6.92, SDhappiness = 1.47. 86 Table 2. The proportion of marital status in each wave (Study 1a) Never married Married Divorced Separated Widowed 2006 20.89 72.33 1.78 5.00 2008 21.95 71.51 1.52 5.02 2016 21.34 75.58 1.24 0.06 1.78 2019 31.31 63.29 5.39 Total 24.70 70.23 5.06 Note. Values in each cell refer to the % of each group at each wave. Divorce, separated, widowed people were combined to a previously married category. 87 Table 3. Contingency table with expected and observed frequencies of marital attitudes by waves (Study 1a) Attitudes toward Marriage Wave Must Good Unnecessary Total 2006 Count 819 1038 721 2578 Expected count 697.30 1067.92 812.78 2578 Count % within a row 31.77% 40.26% 27.97% 100% Expected % within a row 27.05% 41.42% 31.53% 100% 2008 Count 894 950 725 2569 Expected count 694.86 1064.20 809.94 2569 Count % within a row 34.80% 36.98% 28.22% 100% Expected % within a row 27.05% 41.42% 31.53% 100% 2016 Count 1335 2173 1492 5000 Expected count 1352.40 2071.23 1576.38 5000 Count % within a row 26.70% 43.46% 29.84% 100% Expected % within a row 27.05% 41.42% 31.53% 100% 2019 Count 1076 2155 1869 5100 Expected count 1379.45 2112.65 1607.90 5100 Count % within a row 21.10% 42.25% 36.65% 100% Expected % within a row 27.05% 41.42% 31.53% 100% Total 4124 6316 4807 15247 Note. Must = Marriage is a must. Good = Marriage is good, if possible. Unnecessary = Marriage is unnecessary if unwilling. 88 Table 4. Multinomial regression predicting marital attitudes from marital status (Study 1a) b SE Wald p Exp(b) LB UB b SE Wald p Exp(b) LB UB Good Intercept 0.58 0.02 26.44 <.001 1.79 1.72 1.87 0.67 0.03 24.16 <.001 1.95 1.85 2.06 Time 0.05 0.00 12.74 <.001 1.05 1.05 1.06 0.06 0.00 13.46 <.001 1.06 1.05 1.07 Age -0.03 0.00 -17.05 <.001 0.97 0.97 0.97 -0.04 0.00 -16.92 <.001 0.96 0.96 0.97 Gender -0.18 0.02 -8.51 <.001 0.83 0.80 0.87 -0.17 0.02 -7.75 <.001 0.85 0.81 0.88 Edu 0.26 0.04 6.99 <.001 1.30 1.21 1.40 0.24 0.04 6.37 <.001 1.27 1.18 1.37 NM - - - - - - - -0.38 0.07 -5.15 <.001 0.69 0.59 0.79 PM - - - - - - - -0.04 0.09 -0.45 0.655 0.96 0.80 1.15 Unnecessary Intercept 0.22 0.02 9.38 <.001 1.25 1.19 1.31 0.18 0.03 5.93 <.001 1.20 1.13 1.27 Time 0.07 0.00 15.94 <.001 1.07 1.07 1.08 0.07 0.00 15.46 <.001 1.07 1.06 1.08 Age -0.06 0.00 -28.34 <.001 0.94 0.94 0.95 -0.06 0.00 -21.75 <.001 0.95 0.94 0.95 Gender -0.38 0.02 -16.31 <.001 0.68 0.65 0.72 -0.38 0.02 -16.24 <.001 0.68 0.65 0.71 Edu 0.14 0.04 3.31 <.001 1.15 1.06 1.25 0.16 0.04 3.87 <.001 1.18 1.08 1.28 NM - - - - - - - 0.08 0.08 1.02 0.309 1.08 0.93 1.25 PM - - - - - - - 0.44 0.10 4.41 <.001 1.56 1.28 1.90 Note. NM = never-married singles, PM = previously married singles. The reference category for the multinomial outcome is marriage is a must. Must = Marriage is a must. Good = Marriage is good, if possible. Unnecessary = Marriage is unnecessary if unwilling. The reference group for marital status is currently married people. Age and education were grand-mean centered. Education measured the highest level of education obtained across three categories: 1= middle school or below, 2= graduated high school 3 = enrolled in college and above. Gender: 1 = men, -1 = women. LB = lower bound 95% CI for Exp(b), UB = upper bound 95% CI for Exp(b). 89 Table 5. Linear regression predicting life satisfaction from marital attitudes and marital status (Study 1a) 95% CI for b b SE t p β LB UB (Intercept) 6.92 0.01 535.45 <.001 0.00 6.89 6.94 Age -0.002 0.00 -2.11 0.035 -0.02 0.00 0.00 Gender -0.07 0.01 -5.50 <.001 -0.05 -0.10 -0.05 Education 0.30 0.02 12.24 <.001 0.14 0.25 0.35 Good Unnecessary Never-married Previously married Good × Never-married Unnecessary × Never-married Good × Previously married Unnecessary × Previously married Note. Good = Marriage is good, if possible. Unnecessary = Marriage is unnecessary if unwilling. Marital attitudes and marital status were effects coded. Age and education were grand-mean centered. Education measured the highest level of education obtained across three categories: 1 = middle school or below, 2 = graduated high school 3 = enrolled in college and above. Gender: 1 = men, -1 = women. 90 Table 5 (cont’d). 95% CI for b 95% CI for b b SE t p β LB UB b SE t p β LB UB 6.774 0.02 305.92 <.001 0.00 6.73 6.82 6.76 0.02 296.54 <.001 0.00 6.71 6.80 -0.01 0.00 -7.43 <.001 -0.11 -0.01 -0.01 -0.01 0.00 -7.73 <.001 -0.11 -0.01 -0.01 -0.09 0.01 -6.91 <.001 -0.06 -0.12 -0.06 -0.09 0.01 -6.81 <.001 -0.06 -0.11 -0.06 0.277 0.02 11.39 <.001 0.13 0.23 0.32 0.28 0.02 11.37 <.001 0.13 0.23 0.32 0.059 0.02 3.39 <.001 0.03 0.02 0.09 0.04 0.03 1.24 0.214 0.02 -0.02 0.10 -0.29 0.02 -14.84 <.001 -0.15 -0.32 -0.25 -0.26 0.03 -8.05 <.001 -0.14 -0.33 -0.20 -0.02 0.03 -0.50 0.620 -0.01 -0.09 0.05 -0.05 0.04 -1.46 0.144 -0.03 -0.13 0.02 -0.22 0.04 -5.05 <.001 -0.09 -0.31 -0.14 -0.20 0.05 -4.52 <.001 -0.08 -0.29 -0.12 0.05 0.04 1.20 0.232 0.02 -0.03 0.12 0.08 0.04 2.10 0.036 0.04 0.01 0.16 -0.08 0.06 -1.40 0.163 -0.04 -0.19 0.03 -0.02 0.06 -0.30 0.761 -0.01 -0.14 0.10 Note. Good = Marriage is good, if possible. Unnecessary = Marriage is unnecessary if unwilling. Marital attitudes and marital status were effects coded. Age and education were grand-mean centered. Education measured the highest level of education obtained across three categories: 1 = middle school or below, 2 = graduated high school 3 = enrolled in college and above. Gender: 1 = men, -1 = women. 91 Table 6. Model fit indices for factor analyses (Study 1b) Model χ2 df p RMSEA CFI TLI SRMR Δχ2 Δdf Δp CFA: 2 factor 4442.74 34 <.001 .10 [.10,.11] 0.72 0.64 0.08 EFA: 1 factor 7883.05 35 <.001 .14 [.13,.14] 0.51 0.37 0.10 EFA: 2 factor 4011.22 26 <.001 .11 [.11, .11] 0.75 0.57 0.07 3871.84 9 <.001 EFA: 3 factor 336.34 18 <.001 .04 [.03,.04] 0.98 0.95 0.01 3674.88 8 <.001 CFA: 3 factor 682.16 41 <.001 .05 [.04,.05] 0.95 0.93 0.03 Note. All models use data from wave 1 except the last model (CFA: 3 factor) uses data from wave 5. 90% Confidence intervals in brackets. Wave 1: N = 12376, Wave 5: N = 7233. 92 Table 7. Factor loadings for the chosen model and the initial model for relationship expectations (Study 1b) CFA 3-factor (chosen) CFA 2-factor (original) How strongly do you expect… support finance negative positive negative P1 to undertake activities with a partner? 0.45 0.08 P2 to obtain support from a partner if you need help or become ill? 0.51 0.07 P3 to experience an increased social status because of your partner? 0.76 0.81 P4 to have financial advantages in a partnership? 0.77 0.85 P5 to obtain affection and a feeling of safety in a partnership? 0.41 0.00 How strongly do you worry…/How strongly do you expect N1 about experiencing stress in a partnership? 0.62 0.67 N2 about a partnership becoming boring or routine? 0.56 0.68 N3 about family and friends rejecting or disliking a partner? 0.47 0.56 N4 about being constrained by a partner? 0.69 0.75 Note. Factor loadings > .40 and statistically significant at p <.05 are bolded. The last item for negative expectations was added in wave 3. A scale of 1 (Not at all) to 5 (Very strongly). In Study 3, the stem for negative items were revised to “How strongly do you expect…” The last item for positive expectations was rephrased starting in wave 5. 93 Table 8. Model fit indices for latent growth curves for financial, support, and negative expectations (Study 1b) Pseudo- χ2 df p Δχ2 Δdf Δp RMSEA CFI TLI SRMR financial R2 intercept 352.77 17 <.001 .05 [.05,.06] 0.94 0.96 0.08 linear 199.56 14 <.001 153.21 3 <.001 .04 [.04,.05] 0.97 0.98 0.08 9.73% quadratic 111.29 10 <.001 88.27 4 <.001 .04 [.03,.04] 0.98 0.98 0.09 4.04% support χ2 df p Δχ2 Δdf Δp RMSEA CFI TLI SRMR Pseudo-R2 intercept 1130.60 17 <.001 .09 [.09,.10] 0.68 0.81 0.51 linear 311.29 14 <.001 819.31 3 <.001 .05 [.05,.06] 0.91 0.94 0.32 15% quadratic (didn't converge) negatives χ2 df p Δχ2 Δdf Δp RMSEA CFI TLI SRMR Pseudo-R2 intercept 600.51 17 <.001 .07 [.06,.07] 0.87 0.92 0.10 linear 173.69 14 <.001 426.82 3 <.001 .04 [.03,.04] 0.96 0.97 0.10 11.70% quadratic 70.49 10 <.001 103.20 4 <.001 .03 [.02,.03] 0.99 0.99 0.09 4.42% Note. 90% Confidence intervals in brackets. N = 7816 94 Table 9. Latent growth curves for financial, support, and negative expectations (Study 1b) financial expectations b SE t p LB UB β b SE t p LB UB I mean 2.08 0.01 250.79 <.001 2.06 2.10 3.29 2.11 0.01 190.56 <.001 2.08 2.13 I variance 0.40 0.01 45.80 <.001 0.38 0.42 1.00 0.51 0.02 32.83 <.001 0.48 0.54 L mean -0.01 0.003 -3.89 <.001 -0.02 -0.01 L variance 0.01 0.001 9.96 <.001 0.01 0.01 Q mean Q variance I and L cov -0.03 0.003 -9.99 <.001 -0.04 -0.02 I and Q cov L and Q cov Residual Variance 0.41 0.01 88.32 <.001 0.38 0.42 0.51 0.37 0.01 68.89 <.001 0.36 0.38 financial expectations b SE t p LB UB β I mean 2.11 0.02 142.33 <.001 2.08 2.14 2.84 I variance 0.55 0.02 24.76 <.001 0.51 0.60 1.00 L mean -0.01 0.01 -1.17 0.24 -0.04 0.01 -0.04 L variance 0.15 0.02 7.05 <.001 0.11 0.19 1.00 Q mean 0.001 0.002 0.30 0.762 -0.003 0.004 0.01 Q variance 0.003 0.001 5.34 <.001 0.002 0.01 1.00 I and L cov -0.14 0.02 -7.33 <.001 -0.18 -0.10 -0.49 I and Q cov 0.02 0.003 5.68 <.001 0.01 0.03 0.44 L and Q cov -0.02 0.004 -6.08 <.001 -0.03 -0.02 -0.98 Residual Variance 0.36 0.01 49.56 <.001 0.34 0.37 - Note. I = intercept, L = linear slope, Q = quadratic slope, cov = covariance. LB = lower bound, UB = upper bound of 95% confidence intervals. Expectations were centered at the first wave of data collection and scaled so that estimated intercepts could be interpreted as an average score at wave 1 and estimated slopes be interpreted as an average unit change per year. 95 Table 9 (cont’d). Support b SE t p LB UB β b SE t p LB UB β I mean 4.42 0 951.6 <.001 4.41 4.428 13.37 4.51 0.01 764.58 <.001 4.50 4.52 14.70 I variance 0.11 0 39.31 <.001 0.10 0.115 1.00 0.09 0.01 20.60 <.001 0.09 0.10 1.00 L mean -0.03 0.00 -19.93 <.001 -0.04 -0.03 -0.48 L variance 0.01 0.00 12.54 <.001 0.00 0.01 1.00 Q mean Q variance I and L cov 0.00 0.00 -2.36 <.001 0.00 0.00 -0.12 I and Q cov L and Q cov Residual Variance 0.18 0 88.32 <.001 0.17 0.182 0.51 0.15 0.00 68.38 <.001 0.15 0.16 Note. I = intercept, L = linear slope, Q = quadratic slope, cov = covariance. LB = lower bound, UB = upper bound of 95% confidence intervals. Expectations were centered at the first wave of data collection and scaled so that estimated intercepts could be interpreted as an average score at wave 1 and estimated slopes be interpreted as an average unit change per year. 96 Table 9 (cont’d). Negatives b SE t p LB UB β b SE t p LB UB β I mean 2.23 0 350.5 <.001 2.21 2.239 4.735 2.31 0.01 264.08 <.001 2.30 2.33 4.24 I variance 0.22 0 42.9 <.001 0.21 0.231 1 0.30 0.01 31.01 <.001 0.28 0.32 1.00 L mean -0.03 0.002 -15.07 <.001 -0.04 -0.03 -0.40 L variance 0.01 0.001 10.68 <.001 0.01 0.01 1.00 Q mean Q variance I and L cov -0.02 0.002 -10.93 <.001 -0.03 -0.02 -0.49 I and Q cov L and Q cov Residual Variance 0.28 0 88.3 <.001 0.28 0.289 0.561 0.25 0.004 69.03 <.001 0.24 0.26 Negatives b SE t p LB UB β I mean 2.34 0.01 195.55 <.001 2.32 2.36 3.99 I variance 0.34 0.01 24.11 <.001 0.32 0.37 1.00 L mean -0.07 0.01 -6.86 <.001 -0.08 -0.05 -0.20 L variance 0.11 0.01 7.63 <.001 0.08 0.14 1.00 Q mean 0.01 0.002 3.74 <.001 0.003 0.01 0.12 Q variance 0.002 <.001 5.92 <.001 0.002 0.003 1.00 I and L cov -0.11 0.01 -8.45 <.001 -0.13 -0.08 -0.57 I and Q cov 0.02 0.002 6.72 <.001 0.01 0.02 0.51 L and Q cov -0.02 0.002 -6.65 <.001 -0.02 -0.01 -0.98 Residual Variance 0.24 0.01 49.83 <.001 0.23 0.25 Note. I = intercept, L = linear slope, Q = quadratic slope, cov = covariance. LB = lower bound, UB = upper bound of 95% confidence intervals. Expectations were centered at the first wave of data collection and scaled so that estimated intercepts could be interpreted as an average score at wave 1 and estimated slopes be interpreted as an average unit change per year. 97 Table 10. Means, SDs, frequencies, and correlations among study variables (Study 2) 1 2 3 4 5 6 7 8 9 10 11 1. Finance 1 2. Finance 3 0.47 3. Finance 5 0.64 0.51 4. Finance 7 0.99 0.10 0.58 5. Finance 11 0.36 0.45 0.52 0.56 6. Support 1 0.06 0.05 0.27 0.45 0.02 7. Support 3 -0.04 0.03 0.11 0.61 -0.01 0.38 8. Support 5 0.55 -0.08 0.04 -0.03 -0.01 0.87 0.27 9. Support 7 0.82 -0.53 0.01 0.04 0.01 0.00 0.00 0.49 10. Support 11 -0.04 -0.02 -0.01 -0.01 0.04 0.23 0.34 0.41 0.47 11. Negative 1 0.10 0.02 -0.45 -0.83 0.05 -0.07 -0.09 0.12 -0.63 -0.04 12. Negative 3 0.07 0.08 -0.30 -0.92 0.10 -0.10 -0.17 -0.19 -0.48 -0.05 0.44 13. Negative 5 -0.25 -0.07 0.14 0.11 0.10 -0.08 -0.20 -0.18 -0.10 -0.09 0.81 14. Negative 7 -0.76 0.54 0.08 0.12 0.08 -0.30 -0.16 -0.13 -0.13 -0.08 0.42 15. Negative 11 0.07 0.05 0.08 0.11 0.16 -0.07 -0.09 -0.12 -0.08 -0.14 0.32 16. Income -0.03 0.04 0.02 0.00 0.03 0.01 0.02 -0.01 -0.02 -0.04 -0.05 17. Men 0.00 0.00 0.02 0.00 0.01 -0.15 -0.13 -0.13 -0.13 -0.12 -0.05 18. Age 0.03 0.12 0.15 0.12 0.11 0.08 -0.01 -0.02 -0.05 -0.11 -0.11 19. Education -0.01 0.01 0.01 0.01 -0.02 0.01 0.04 -0.02 0.02 0.00 -0.01 20. Singlehood satisfaction -0.03 -0.05 -0.05 -0.02 -0.02 -0.09 -0.11 -0.10 -0.12 -0.15 0.09 21. Life satisfaction -0.01 -0.04 0.00 -0.01 -0.01 0.01 0.00 0.03 0.00 0.01 0.02 22. Singlehood length -0.01 -0.09 -0.06 -0.04 -0.03 -0.17 -0.16 -0.14 -0.14 -0.09 0.18 23. Neuroticism 0.05 0.04 0.04 0.04 0.04 0.03 0.03 0.05 0.06 0.06 0.22 M 2.09 2.10 2.12 2.04 2.06 4.57 4.45 4.41 4.38 4.36 2.34 SD 0.96 0.90 0.90 0.88 0.88 0.45 0.52 0.52 0.54 0.57 0.77 Note. Finance = expectations for financial/status benefits; Support = expecting to receive social support; Negative = expecting negative experiences. The number refers to the wave of data collection. Correlations significant at p <.01 were bolded. Some large correlations (e.g., finance 1 and finance 5) were not statistically significant due to small samples (ns < 10). 98 Table 10 (cont’d). 12 13 14 15 16 17 18 19 20 21 22 23 0.43 0.53 0.53 0.40 0.46 0.51 -0.09 -0.10 -0.10 -0.06 -0.01 0.02 0.04 0.05 0.16 -0.14 -0.14 -0.15 -0.11 0.45 -0.04 -0.02 0.03 0.00 0.01 0.06 0.00 -0.04 0.14 0.15 0.22 0.28 -0.11 0.11 -0.16 0.01 0.04 -0.03 -0.03 -0.07 0.03 -0.01 0.02 -0.02 0.04 0.26 0.26 0.30 0.27 -0.21 0.15 -0.38 0.11 0.69 0.01 0.23 0.23 0.23 0.17 -0.10 -0.21 -0.05 -0.02 0.04 -0.03 0.04 2.25 2.25 2.21 2.16 -84.24 -0.09 26.48 -528.04 -780.60 0.97 1.46 2.70 0.71 0.69 0.70 0.69 1251.74 1.00 8.35 503.07 414.56 80.83 1.84 0.80 Note. Finance = expectations for financial/status benefits; Support = expecting to receive social support; Negative = expecting negative experiences. The number refers to the wave of data collection. Correlations significant at p <.01 were bolded. Some large correlations (e.g., finance 1 and finance 5) were not statistically significant due to small samples (ns < 10). 99 Table 11. The latent intercepts and slopes of expectations predicting life satisfaction, singlehood satisfaction, and length of singlehood (Study 1b) Life satisfaction Predictors b SE t p LB UB β Financial intercept -0.11 0.03 -3.10 0.002 -0.17 -0.04 -0.05 Financial slope -0.22 0.50 -0.44 0.660 -1.20 0.76 -0.01 Gender -0.13 0.02 -5.85 <.001 -0.18 -0.09 -0.08 Age -0.02 0.01 -4.70 <.001 -0.03 -0.01 -0.11 Education 0.01 0.01 1.44 0.151 0.00 0.03 0.04 Income 0.02 0.01 4.38 <.001 0.01 0.03 0.12 Singlehood satisfaction Financial intercept -0.51 0.11 -4.67 <.001 -0.73 -0.30 -0.15 Financial slope -4.20 1.59 -2.65 0.008 -7.31 -1.09 -0.17 Gender -0.11 0.07 -1.57 0.117 -0.26 0.03 -0.05 Age 0.06 0.02 3.81 <.001 0.03 0.09 0.20 Education -0.03 0.03 -1.25 0.211 -0.08 0.02 -0.08 Income -0.04 0.02 -2.48 0.013 -0.08 -0.01 -0.17 Singlehood length Financial intercept -0.06 0.04 -1.61 0.108 -0.13 0.01 -0.02 Financial slope 0.94 0.53 1.78 0.074 -0.09 1.97 0.05 Gender 0.35 0.02 15.10 <.001 0.30 0.39 0.19 Age -0.03 0.01 -6.70 <.001 -0.04 -0.02 -0.14 Education -0.05 0.01 -5.62 <.001 -0.06 -0.03 -0.16 Income -0.03 0.01 -7.35 <.001 -0.04 -0.03 -0.18 Note. Gender: 1= men, -1 = women. Education in years. Income: net income (scaled to 1/100) 100 Table 11 (cont’d). Life satisfaction Predictors b SE t p LB UB β Support intercept 0.54 0.10 5.53 <.001 0.35 0.73 0.10 Support slope 4.07 0.61 6.65 <.001 2.87 5.26 0.17 Gender -0.08 0.02 -3.49 <.001 -0.13 -0.04 -0.05 Age -0.01 0.01 -2.70 0.007 -0.02 0.00 -0.07 Education 0.01 0.01 1.21 0.228 -0.01 0.02 0.04 Income 0.02 0.01 3.69 <.001 0.01 0.03 0.10 Singlehood satisfaction Support intercept -0.71 0.26 -2.74 0.006 -1.23 -0.20 -0.09 Support slope -5.82 1.54 -3.79 <.001 -8.83 -2.81 -0.17 Gender -0.22 0.08 -2.92 0.004 -0.36 -0.07 -0.09 Age 0.04 0.02 2.63 0.008 0.01 0.07 0.14 Education -0.04 0.03 -1.73 0.084 -0.09 0.01 -0.11 Income -0.03 0.02 -2.02 0.043 -0.07 0.00 -0.14 Singlehood length Support intercept -1.20 0.11 -11.44 <.001 -1.41 -1.00 -0.20 Support slope -0.69 0.64 -1.08 0.282 -1.93 0.56 -0.03 Gender 0.25 0.02 10.26 <.001 0.20 0.30 0.13 Age -0.04 0.01 -7.85 <.001 -0.05 -0.03 -0.17 Education -0.04 0.01 -4.90 <.001 -0.06 -0.02 -0.14 Income -0.03 0.01 -5.99 <.001 -0.04 -0.02 -0.15 Note. Gender: 1= men, -1 = women. Education in years. Income: net income (scaled to 1/100) 101 Table 11. (Cont’d) Life satisfaction Predictors b SE t p LB UB β Negative intercept -1.73 0.18 -9.89 <.001 -2.07 -1.38 -0.56 Negative slope -23.19 4.76 -4.87 <.001 -32.52 -13.86 -0.76 Gender 0.14 0.08 1.83 0.067 -0.01 0.30 0.09 Age -0.02 0.01 -1.78 0.075 -0.04 0.00 -0.09 Education 0.00 0.02 0.16 0.875 -0.03 0.03 0.01 Income 0.00 0.01 0.39 0.695 -0.02 0.03 0.03 Singlehood satisfaction Negative intercept -0.29 0.15 -1.92 0.055 -0.59 0.01 -0.07 Negative slope 2.69 1.93 1.40 0.162 -1.08 6.46 0.09 Gender -0.17 0.08 -2.25 0.024 -0.32 -0.02 -0.07 Age 0.06 0.02 3.67 <.001 0.03 0.08 0.19 Education -0.04 0.03 -1.64 0.102 -0.09 0.01 -0.11 Income -0.04 0.02 -2.16 0.031 -0.07 0.00 -0.15 Singlehood length Negative intercept 1.20 0.05 23.92 <.001 1.10 1.30 0.36 Negative slope 5.59 0.65 8.66 <.001 4.33 6.86 0.24 Gender 0.29 0.02 11.89 <.001 0.24 0.34 0.16 Age -0.03 0.01 -5.55 <.001 -0.04 -0.02 -0.12 Education -0.05 0.01 -5.48 <.001 -0.06 -0.03 -0.16 Income -0.03 0.01 -5.58 <.001 -0.04 -0.02 -0.13 Note. Gender: 1 = men, -1 = women. Education in years. Income: net income (scaled to 1/100) 102 Table 12. Trajectory differences in expectations: Relationship status predicting latent intercepts and slopes of expectations (Study 1b) Estimated Effect of Status on Financial Expectations b SE t p LB UB β Intercept 0.00 0.02 0.10 0.919 -0.03 0.03 0.00 Linear slope -0.04 0.01 -3.14 0.002 -0.07 -0.02 -0.09 Quadratic slope 0.01 0.00 3.27 0.001 0.00 0.01 0.11 Estimated Effect of Status on Support Expectations Intercept -0.09 0.01 -14.02 <.001 -0.10 -0.08 -0.26 Linear slope 0.01 0.00 3.67 <.001 0.00 0.01 0.09 Estimated Effect of Status on Negative Expectations Intercept 0.13 0.01 10.20 <.001 0.10 0.15 0.20 Linear slope 0.05 0.01 4.36 <.001 0.03 0.07 0.12 Quadratic slope -0.01 0.00 -4.04 <.001 -0.01 0.00 -0.13 Note. Status: 1= Single for most of study duration, -1 = Partnered for most of the study duration. 103 Table 13. Percentage of participants who experience major life events in Study 2 Event % First job 2.2 Retirement 10.8 Unemployment 9.62 Death of a parent 12.4 Birth of a child 1.22 Death of child 0.05 New chronic illnesses 32.7 Subjective health (positive change) 48.6 Subjective health (negative change) 58.9 Moved residences 6.99 Bought a house 9.05 104 Table 14. Model Fit Indices for Latent Growth Curve Models (Study 2) Model χ2 df p RMSEA CFI TLI SRMR Quadratic 369.275 94 <.001 .037 [.033,.041] 0.966 0.972 0.071 Linear 521.399 98 <.001 .045 [.041,.049] 0.948 0.958 0.09 Note. 90% Confidence intervals in brackets. 105 Table 15. Changes in Singlehood Satisfaction (Study 2) b SE t p LB UB β b SE t p LB UB β I mean 6.49 0.06 115.82 <.001 6.38 6.60 3.19 6.53 0.07 97.27 <.001 6.40 6.67 3.14 I variance 4.15 0.20 21.06 <.001 3.76 4.54 1.00 4.34 0.25 17.30 <.001 3.85 4.84 1.00 L mean 0.03 0.01 4.35 <.001 0.02 0.04 0.16 0.01 0.02 0.30 0.765 -0.03 0.04 0.01 L variance 0.03 0.00 11.65 <.001 0.02 0.03 1.00 0.18 0.02 9.14 <.001 0.14 0.22 1.00 Q mean 0.00 0.00 1.36 0.173 0.00 0.00 0.07 Q variance 0.001 0.00 6.54 <.001 0.00 0.00 1.00 I and L cov -0.20 0.02 -10.73 <.001 -0.24 -0.17 -0.59 -0.44 0.06 -7.41 <.001 -0.55 -0.32 -0.49 I and Q cov 0.02 0.00 3.93 <.001 0.01 0.03 0.29 L and Q cov -0.01 0.00 -7.38 <.001 -0.01 -0.01 -0.94 Residual Variance 1.56 0.02 68.01 <.001 1.52 1.61 - 1.48 0.02 64.53 <.001 1.44 1.53 - Note. I = intercept, L = linear slope, Q = quadratic slope, cov = covariance. LB = lower bound, UB = upper bound of 95% confidence intervals. Singlehood satisfaction was centered at the first wave of data collection and scaled so that estimated intercepts could be interpreted as an average score at wave 1 and estimated slopes be interpreted as an average unit change per year. 106 Table 16. Changes in Singlehood Satisfaction in Response to Life Events (Study 2) Intercept b SE t p LB UB β Age 0.00 0.01 0.15 0.884 -0.01 0.01 0.01 Gender -0.15 0.07 -2.09 0.036 -0.29 -0.01 -0.07 Education -0.01 0.05 -0.15 0.882 -0.11 0.09 -0.01 Income 0.00 0.01 -0.46 0.643 -0.02 0.01 -0.05 Family Satisfaction 0.63 0.06 10.78 <.001 0.51 0.74 0.54 Consistency 1.46 0.20 7.47 <.001 1.08 1.84 0.25 First job -0.35 0.34 -1.04 0.297 -1.01 0.31 -0.03 Retirement 0.09 0.18 0.48 0.629 -0.26 0.43 0.01 Unemployment -0.28 0.17 -1.61 0.108 -0.61 0.06 -0.04 Death of a parent 0.18 0.16 1.10 0.270 -0.14 0.49 0.03 Death of a child -0.30 2.28 -0.13 0.896 -4.78 4.18 0.00 New chronic illnesses 0.02 0.13 0.15 0.879 -0.24 0.27 0.00 Subjective health (positive change) -0.05 0.11 -0.44 0.658 -0.27 0.17 -0.01 Subjective health (negative change) -0.25 0.12 -2.06 0.039 -0.48 -0.01 -0.06 Moved residences -0.01 0.22 -0.04 0.971 -0.43 0.42 0.00 Bought a house -0.22 0.20 -1.09 0.274 -0.61 0.17 -0.03 Note. Age and education were grand-mean centered. All life events: 1 = experienced event, 0 = did not experience event. LB = lower bound, UB = upper bound of 95% confidence intervals. Significant results at p < .05 are bolded. Gender: Men = 1, Women = -1. Consistency: Consistently single = 1, Partnered before = 0. 107 Table 16 (cont’d). Slope b SE t p LB UB β Age 0.003 <.001 5.71 <.001 0.002 0.004 0.33 Gender 0.01 0.01 0.90 0.370 -0.01 0.02 0.04 Education 0.00 0.01 0.57 0.568 -0.01 0.01 0.02 Income 0.00 0.00 0.32 0.746 0.00 0.00 0.04 Family Satisfaction -0.04 0.01 -5.79 <.001 -0.06 -0.03 -0.45 Consistency -0.06 0.02 -3.08 0.002 -0.10 -0.02 -0.13 First job 0.03 0.04 0.62 0.538 -0.06 0.11 0.02 Retirement 0.00 0.02 0.20 0.840 -0.03 0.04 0.01 Unemployment 0.03 0.02 1.49 0.136 -0.01 0.06 0.05 Death of a parent -0.01 0.02 -0.47 0.636 -0.04 0.02 -0.02 Death of a child 0.16 0.22 0.73 0.468 -0.27 0.60 0.02 New chronic illnesses 0.01 0.01 0.50 0.619 -0.02 0.03 0.02 Subjective health (positive change) 0.02 0.01 1.71 0.087 -0.003 0.04 0.06 Subjective health (negative change) -0.05 0.01 -3.71 <.001 -0.07 -0.02 -0.14 Moved residences 0.01 0.02 0.30 0.764 -0.04 0.06 0.01 Bought a house 0.02 0.02 0.97 0.335 -0.02 0.06 0.04 Note. Age and education were grand-mean centered. All life events: 1 = experienced event, 0 = did not experience event. LB = lower bound, UB = upper bound of 95% confidence intervals. Significant results at p < .05 are bolded. Gender: Men = 1, Women = -1. Consistency: Consistently single = 1, Partnered before = 0. 108 Table 17. Codes from Qualitative Analyses (Study 3) Code Definition Example % % Less Names % Total Happier happy Whose Personal Personal "Every silent moment I become aware of experience experience reminds me of my being content with my is it? single status." 72.15% 43.73% 41.40% Family Seeing/hearing "My mother had just got off the phone with my about a family older sisters, both have children and one is member's pregnant. Hearing my mother talk about how experience happy she is for my sisters and having grandchildren is disheartening for myself since I am over 30 and have no children even though I do want to have children. Being single is not conducive to being able to have children." 5.48% 44.44% 44.44% Friends Seeing/hearing "Witnessing a loud argument between friends about a friend's about a relatively trivial matter made me feel a experience little glad that I am single." 4.93% 54.55% 81.82% Others Seeing/hearing "When I heard about Gabby Petito being about other killed by her fiance." people's experience (not family or friend) 7.46% 43.59% 35.90% Ex Seeing/hearing "Hearing my ex wife being a pain to her new about ex's boyfriend" experience 0.99% 50.00% 100.00% Note. Bolded codes are codes that mentioned by >5% of the responses. 109 Table 17 (cont’d). Code Definition Example % % Less Names % Total Happier happy What kind Positive Experiences related to "I met someone that I felt very of romance starting/maintaining/impr comfortable with. we had some great experience? oving/benefitting from times, did things together but I was romantic relationships having problems with being intimate. (dates, marriage, I discovered that I was experiencing engagement) a form of ED. Tried VIAGRA but it didn't work. My Dr. purchased a mechanical device for me to try. That became an issue so the relationship slowly fell apart." 8.88% 28.89% 55.56% Negative Experiences related to "Broken relationships have romance ending/deteriorating/strug contributed to my loneliness. gling from romantic Emotional healing taking so long relationships (abuse, adds to my reluctance and conflicts, divorce, procrastination in reaching out for separation, cheating, fear of being devastated again. Being partner passing, and more single for me has more negatives than day-to-day annoyances) positive. Although my basic needs are supplied daily, the emptiness in my heart is constant and continual, unfulfilled." "Felt happy to be single thinking of a friend who is in a terrible marriage that I feel bad for." 18.20% 53.68% 36.84% 110 Table 17 (cont’d). Code Definition Example % % % Less Names Total Happier happy What kind Missing Experience "It's lonely trying sleep at night without rhe of positive related to not comfort of another to cuddle with just the experience? romance having (missing) days go by and you see everyone else so positive happy with their partners making you wish experiences you had one" associated with "My good friend was talking about how he relationships might propose to his girlfriend soon. I got jealous for a moment but then thought about how I will get to do that when the time is right." "I am happy single. I saw a older couple holding hands, I ask them how long they have married? I wish I could have that." 6.14% 25.42% 76.27% Missing Experience "When I see people who are in relationships negative related to not and one person is in a good mood and the romance having (missing) other person isn't a person who is in the negative good mood has to adjust their mood or the experiences person who is in the bad mood and that is associated with the kind of things that I don't want to deal relationships with I would rather just be happy" "Going with my friend to the store at the drop of a hat. Made me very glad I didn't have to get permission or check in to just go" 9.54% 65.00% 12.50% 111 Table 17 (cont’d). Code Definition Example % % Less % Names % Total Happier happy Event 1 What kind Connection Experience "Happy because of my grandkids" of related to "I recently had my parents stay with experience? having other me for a visit for a full week. I non-romantic reflected on lucky they are still in relationships my life and I feel close to them. I felt (feeling very happy to have a family that is connected, financially stable and makes me feel getting support) safe." 5.15% 70.83% 29.17% 5.39% No Experiences "First Christmas holiday when both connection related to of my children were living out of lacking or state -- having grown up in a very losing non- nuclear family environment, that romantic was difficult." company "when i want to go out to eat but because i will be alone with no one to join me i jut forget about it and stay home and have an unsatisfying meal" 11.40% 13.33% 73.33% 10.11% Freedom Experiences "I was working on my main related to being hobby/passion which is very much a free and one person activity, and I felt independent to thankful that I can take time for make decisions, myself whenever I want to." including "My days are filled with arts and prioritzing and craft projects, reading, baking or focusing on self, spending time with good friends. My not having to home is always clean, laundry caregive caught up and time to spend online. I save money on food and most household essentials. Peaceful." 16.78% 70.00% 14.44% 20.22% 112 Table 17 (cont’d). Code Definition Example % % % Less Names Total Happier happy What kind Birth Related to "The birth of my grandson" of pregnancy, birth, experience? and children 1.43% 66.67% 66.67% Death Related to non- "Dealing with the loss of my mother and partner sister alone, I'm still grieving alone with bereavement nobody to lean on for support" 5.59% 36.67% 63.33% Poor Related to poor "I was having health problems and wished i health health could gave a psrtner to talk to but my family provides sufficient support" 3.07% 26.67% 53.33% Good Related to good "My most happy beside the birth of my 3 health health older children was beating cancer. Now the why is is naturally being alive. Life is good." 0.33% 100.00% 100.00% Moving Moving residences, "When I moved to United States 3 years ago country was happy about it but in the same time, it showed what loneliness and being single really feels like when I am far from home, family and friends. It's so challenging" 1.54% 80.00% 60.00% Job Getting a new job, "When I got my dream job at Westport yachts security advancing in career was a very happy time. " 0.66% 100.00% 100.00% Job Losing a job, having "I lost my job last week. I really missed insecurity a bad job, not having having someone who could be there for me. I employment/income, never expected that to happen and, because of money concerns my age (85), my prospects for getting another job are not good. It would have been nice to have some emotional support." 3.07% 21.43% 71.43% 113 Table 17 (cont’d). Code Names Definition Example % % Less % Total Happier happy What kind Other wins Related to meeting goals "Five years ago I bought my first of outside of the career house. About two weeks after moving experience? realm (dream purchase) in I came in from work and it was all dark inside. When I opened the door and turned the light on my first thought was it would be nice to have someone to share it with. Two minutes later I was like nah, it's all mine." 2.41% 42.86% 35.71% Only single Experiences related to "I was tailgating with friends and was being the only single or the only single one there. Even though "non-couple" I was having fun I felt lonely." 2.08% 10.00% 70.00% Idiosyncratic An "Going to the beach and watching idiosyncratic/random the ocean" experience (including "Sitting down to dinner with just sudden realizations) you enjoying the meal, no human contact, no conversation except for the one you have in your mind" "One time I was on my pc doing some work I had to do and all of a sudden I realized how empty my life was" 10.31% 25.00% 41.67% Learning When people talk about "Listened to my iPod for the first time learning to deal with in a number of years to get over being single or getting grieving process of now-deceased used to it (regardless of boyfriend and move on" choice) "I was very unhappy when my husband passed away unexpectantly, but as time went by I learned to deal with it." 1.97% 53.85% 38.46% 114 Table 17 (cont’d). Code Definition Example % % Less Names % Total Happier happy What kind Aging Experiences/recollections "I see other people my age getting of related to aging, divorced and remarried and am happy I experience? normative experiences at am not in that situation." a certain age group "Felt happy at times about being alone & not having no one to answer too but at the same time wanting someone to grow old with." 1.97% 41.18% 64.71% Nothing When people don't "There's no specific time" know or haven't "I had not really reflected on it until reflected on their the survey started asking me about it" singlehood 10.42% 27.03% 18.92% Timing of Present When people are "I was at a doctor appointment and the event reflecting about change had nothing to say about my after an event relationships or family. It was disappointing and discouraging to discuss." 67.11% 47.75% 38.06% Past When people are "I was listening to some music that reflecting about reminded me of a time with my memories of a past deceased wife who I miss very much." event "When i reflect on my friends that are married with children. Most are unhappy all the time." 5.92% 45.95% 45.95% Special Special times (e.g., "My birthday when I was surrounded by holidays, birthdays) my family and friends and it was just joyful and happy" "I went to a Christmas dinner for work and I was the only person that went alone. It made me wish I had someone to share the experience with" 3.62% 35.29% 47.06% 115 Table 17 (cont’d). Code Definition Example % % Less Names % Total Happier happy Valence Positivity Experiences that "I am enjoying my life. I have been married 5 evoked positive times and widowed twice, so I am enjoying mood (including being single." positivity without elaboration) 16.78% 74.75% 22.22% Negativity Experiences that "I was scared and needed comfort" evoked negative mood (including negativity without elaboration) 15.57% 31.13% 68.87% Note. Bolded codes are codes that mentioned by >5% of the responses. 116 Table 18. Means, SDs, frequencies, and correlations among study variables (Study 3) 1 2 3 4 5 6 7 8 9 1. Predictability 2. Worldview 0.31 3. Emotional significance 0.39 0.53 4. External control 0.33 0.33 0.26 5. Ordinary 0.19 0.24 0.28 0.12 6. Impact 0.40 0.57 0.67 0.31 0.15 7. Positive valence -0.29 0.03 -0.20 -0.24 -0.08 -0.22 8. Challenge 0.42 0.28 0.41 0.47 0.14 0.53 -0.63 9. Status change 0.37 0.35 0.27 0.45 0.03 0.46 -0.24 0.54 10. Expect finance 0.04 0.19 0.11 0.19 0.15 0.09 -0.03 0.14 0.26 11. Expect support 0.11 0.14 0.16 0.16 0.19 0.11 -0.18 0.20 0.10 12. Expect negatives 0.12 0.21 0.09 0.22 0.14 0.12 0.00 0.14 0.23 13. Sat: Autonomy 0.00 0.24 0.15 -0.05 0.32 0.04 0.23 -0.19 -0.17 14. Sat: Relatedness 0.03 0.21 0.16 -0.07 0.28 0.02 0.14 -0.10 -0.16 15. Sat: Competence 0.00 0.22 0.11 -0.08 0.24 0.05 0.22 -0.14 -0.11 16. Frus: Autonomy 0.20 0.07 0.07 0.23 0.07 0.14 -0.22 0.28 0.39 17. Frus: Relatedness 0.19 0.11 0.06 0.32 0.00 0.18 -0.15 0.25 0.45 18. Frus: Competence 0.23 0.09 0.10 0.29 0.04 0.21 -0.29 0.36 0.43 19. Soi-r Behavior -0.04 -0.05 -0.07 0.09 -0.01 -0.04 -0.04 0.03 0.04 20. Soi-r Attitude -0.02 -0.07 -0.09 0.06 -0.03 -0.03 -0.01 0.03 0.06 21. Soi-r Desire 0.10 0.04 0.02 0.10 0.03 0.04 -0.06 0.10 0.17 22. Courtship 0.11 0.10 0.02 0.25 0.03 0.17 -0.20 0.29 0.26 23. Freedom -0.03 0.12 -0.06 0.09 0.06 0.01 0.20 -0.07 0.04 24. Previous constraints 0.34 0.27 0.23 0.34 0.21 0.29 -0.22 0.36 0.36 25. Personal constraints 0.22 0.17 0.02 0.32 0.02 0.11 -0.02 0.17 0.41 26. Avoidance -0.05 -0.16 -0.08 -0.01 -0.09 -0.04 -0.08 0.04 0.05 27. Anxiety 0.20 0.14 0.13 0.31 0.09 0.22 -0.29 0.40 0.35 28. Singlehood (1-item) -0.06 0.09 -0.04 -0.13 0.04 -0.09 0.36 -0.31 -0.24 29. Singlehood (ReSta) -0.14 0.08 -0.07 -0.16 -0.04 -0.14 0.39 -0.34 -0.31 30. Depressive symptoms 0.21 0.03 0.09 0.25 0.04 0.22 -0.40 0.46 0.42 31. Life satisfaction -0.09 0.17 0.05 -0.06 0.13 -0.07 0.44 -0.33 -0.22 32. Age -0.09 -0.11 0.02 -0.10 0.04 -0.06 -0.04 -0.08 -0.24 33. Education -0.19 -0.13 -0.04 -0.19 -0.02 -0.11 0.02 -0.04 -0.19 34. Gender -0.10 -0.05 0.00 -0.02 -0.05 -0.01 0.07 -0.07 0.06 35. Finance 0.11 -0.01 0.03 0.08 -0.09 0.05 -0.33 0.23 0.07 36. Relationship number 0.06 0.01 0.09 0.08 0.04 0.00 -0.02 0.06 0.08 37. Relationship length 0.03 -0.03 0.01 0.04 0.07 0.03 -0.06 0.02 -0.06 48. Singlehood length -0.17 -0.11 -0.02 0.02 -0.01 -0.07 0.02 -0.09 -0.10 M or % 3.11 3.23 3.50 2.68 3.62 3.32 2.78 3.07 2.49 SD 1.19 1.09 1.04 1.13 0.88 1.12 1.22 1.29 1.20 Note. Bivariate correlations that are statistically significant at p < .001 are bolded. Singlehood = Singlehood satisfaction. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 117 Table 18 (cont’d). 10 11 12 13 14 15 16 17 18 19 20 21 22 0.55 0.39 0.20 0.08 0.13 0.16 0.03 0.08 0.04 0.64 0.06 0.11 -0.01 0.69 0.57 0.28 0.19 0.34 -0.26 -0.31 -0.24 0.36 0.20 0.37 -0.23 -0.44 -0.29 0.69 0.26 0.18 0.41 -0.29 -0.30 -0.48 0.65 0.71 0.19 0.15 0.19 -0.04 -0.03 -0.02 0.15 0.19 0.19 0.17 0.08 0.16 -0.10 -0.11 -0.07 0.10 0.14 0.11 0.54 0.30 0.25 0.21 -0.04 -0.05 0.00 0.24 0.31 0.26 0.48 0.49 0.07 -0.05 0.26 -0.02 -0.09 -0.20 0.31 0.35 0.47 0.08 0.04 0.08 0.11 -0.11 0.29 0.25 0.17 0.15 0.06 0.09 0.06 0.18 0.19 0.15 0.33 0.18 0.13 0.31 0.02 0.04 -0.08 0.35 0.33 0.48 0.03 -0.07 0.09 0.41 0.22 0.06 0.33 -0.02 -0.07 -0.01 0.34 0.43 0.38 0.21 0.17 0.29 0.42 -0.15 -0.16 0.03 -0.29 -0.50 -0.28 0.18 0.22 0.21 0.04 0.12 -0.01 0.17 0.23 0.27 0.33 -0.19 -0.28 -0.26 0.58 0.64 0.67 0.15 0.03 0.29 0.34 -0.13 -0.22 -0.03 0.33 0.30 0.23 -0.26 -0.31 -0.28 -0.07 -0.04 -0.20 -0.01 -0.18 -0.24 -0.02 0.34 0.32 0.23 -0.34 -0.36 -0.34 -0.06 -0.02 -0.21 -0.05 0.16 0.13 0.16 -0.37 -0.37 -0.42 0.50 0.47 0.58 0.09 0.04 0.21 0.35 0.03 -0.08 0.04 0.49 0.45 0.44 -0.27 -0.29 -0.37 -0.06 -0.01 -0.05 -0.15 -0.21 -0.19 -0.20 0.12 0.11 0.11 -0.29 -0.29 -0.26 -0.23 -0.15 -0.28 0.07 -0.16 -0.10 -0.11 0.00 0.03 0.01 -0.08 -0.15 -0.10 -0.10 0.03 -0.04 -0.09 0.15 0.04 -0.04 -0.07 -0.13 0.01 0.05 0.15 0.02 0.22 0.21 0.41 -0.01 -0.12 -0.01 -0.09 -0.22 -0.18 -0.29 0.10 0.07 0.24 -0.02 -0.03 -0.06 0.16 0.11 0.12 0.07 -0.02 0.00 -0.02 0.09 0.09 0.08 0.24 0.20 0.17 -0.01 -0.12 -0.08 -0.07 0.02 0.02 -0.02 -0.09 -0.12 -0.04 0.06 0.08 -0.10 -0.07 -0.06 -0.06 0.04 0.05 -0.03 0.00 0.00 0.01 -0.01 -0.11 -0.14 -0.09 0.16 2.50 3.20 2.63 3.68 3.68 3.77 2.67 2.34 2.58 1.97 2.69 2.21 2.58 1.24 1.25 1.10 0.88 1.05 0.97 1.08 1.10 1.18 0.93 1.17 1.14 0.98 Note. Bivariate correlations that are statistically significant at p < .001 are bolded. Singlehood = Singlehood satisfaction. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 118 Table 18 (cont’d). 23 24 25 26 27 28 29 30 31 32 33 34 0.18 0.36 0.42 -0.05 0.05 0.03 0.00 0.43 0.27 0.19 0.33 -0.12 -0.10 -0.10 -0.33 0.38 -0.17 -0.15 -0.08 -0.34 0.80 -0.02 0.43 0.25 0.23 0.57 -0.43 -0.46 0.25 -0.10 0.00 -0.28 -0.33 0.55 0.57 -0.51 -0.06 -0.13 -0.19 -0.05 -0.30 0.13 0.10 -0.27 0.09 -0.01 -0.08 -0.14 0.05 -0.13 0.08 0.05 -0.12 0.02 0.19 0.03 -0.24 0.08 0.01 -0.03 -0.10 -0.15 -0.03 -0.11 0.01 0.06 -0.12 0.12 -0.11 0.23 0.22 -0.15 -0.12 0.32 -0.46 -0.06 -0.07 -0.06 0.02 0.07 0.07 -0.01 0.12 -0.06 -0.06 -0.01 -0.01 0.01 -0.13 0.11 -0.05 0.08 -0.13 -0.05 -0.06 0.04 0.02 -0.02 0.02 0.11 0.03 -0.12 0.11 -0.11 0.07 0.04 -0.04 0.08 0.10 -0.09 0.07 0.33 0.08 0.06 2.80 2.81 1.78 4.08 3.87 8.03 2.94 2.38 4.12 52.91 13.62 35.96 0.97 0.98 0.90 1.20 1.90 3.07 0.87 0.71 1.69 14.70 4.99 Note. Bivariate correlations that are statistically significant at p < .001 are bolded. Singlehood = Singlehood satisfaction. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 119 Table 18 (cont’d). 35 36 37 38 - 0.06 0.01 0.10 - - - 0.09 0.16 0.19 4.47 3.28 0.83 20.43 1.89 3.92 1.72 17.31 Note. Bivariate correlations that are statistically significant at p < .001 are bolded. Singlehood = Singlehood satisfaction. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 120 Table 19. Independent t-tests on whether people who experienced (vs. didn’t experience) an event perceived events differently Predictability Challenge Code Code=0 Code=1 t df p Code=0 Code=1 t df p Personal event 2.99 3.13 -1.08 150.77 0.280 3.05 3.06 -0.02 140.64 0.985 Close other's event 3.10 3.15 -0.24 36.15 0.811 3.04 3.27 -1.00 35.18 0.324 Others' event 3.11 3.01 0.62 54.28 0.536 3.08 2.78 1.78 53.18 0.080 Positive romance 3.10 3.11 -0.08 61.86 0.936 3.07 2.96 0.71 65.74 0.479 Negative romance 3.02 3.39 -2.57 139.54 0.011 2.86 3.75 -6.70 171.12 <.001 Missing positive romance 3.09 3.21 -0.62 47.41 0.536 3.06 2.98 0.44 48.66 0.662 Missing negative romance 3.07 3.3 -1.51 84.90 0.135 3.03 3.24 -1.26 82.80 0.211 Connection 3.10 3.06 0.13 24.97 0.895 3.07 2.79 1.01 25.66 0.323 No connection 3.09 3.17 -0.37 53.18 0.713 2.98 3.67 -3.55 56.33 0.001 Freedom 3.11 3.04 0.48 141.41 0.635 3.21 2.50 4.56 134.65 <.001 Death 3.05 3.73 -2.63 32.24 0.013 2.98 4.03 -4.75 34.51 <.001 Idiosyncratic 3.08 3.32 -1.04 40.20 0.306 3.06 3.06 0.00 40.11 0.997 Present event 3.21 3.04 1.38 270.28 0.170 3.19 2.99 1.47 261.02 0.143 Past event 3.08 3.24 -0.75 42.66 0.457 3.00 3.69 -3.15 43.19 0.003 Positivity 3.15 2.92 1.55 148.29 0.124 3.16 2.72 2.87 154.31 0.005 Negativity 3.02 3.33 -2.36 179.65 0.019 2.89 3.56 -4.73 181.36 <.001 Nothing 3.12 2.85 1.44 45.21 0.155 3.10 2.62 2.19 43.44 0.034 Note. Code = 0 (not experienced), Code = 1 (experienced the event. Results significant at p ≤ .001 are bolded. 121 Table 19 (cont’d). Emotional Significance External Control Code Code=0 Code=1 t df p Code=0 Code=1 t df p Personal event 3.17 3.61 -3.46 124.67 0.001 2.94 2.59 2.71 136.08 0.008 Close other's event 3.54 3.27 1.39 34.85 0.174 2.63 3.00 -1.82 35.41 0.077 Others' event 3.55 3.22 2.02 46.94 0.049 2.63 2.92 -1.74 49.18 0.087 Positive romance 3.54 3.36 1.25 57.76 0.215 2.66 2.66 0.02 61.66 0.983 Negative romance 3.44 3.83 -3.44 165.20 0.001 2.55 3.05 -3.80 149.26 <.001 Missing positive romance 3.54 3.38 1.00 48.67 0.321 2.63 2.91 -1.45 46.91 0.153 Missing negative romance 3.48 3.77 -2.17 86.49 0.033 2.64 2.78 -1.06 98.35 0.290 Connection 3.51 3.75 -1.09 25.74 0.288 2.67 2.5 0.80 26.8 0.431 No connection 3.52 3.56 -0.24 57.49 0.814 2.69 2.38 1.84 56.37 0.070 Freedom 3.53 3.50 0.22 132.60 0.825 2.73 2.41 2.25 130.1 0.026 Death 3.47 4.18 -4.31 35.74 <.001 2.66 2.62 0.19 32.76 0.848 Idiosyncratic 3.52 3.51 0.05 39.17 0.962 2.67 2.56 0.51 40.06 0.615 Present event 3.59 3.49 0.91 273.61 0.364 2.61 2.68 -0.66 280.11 0.507 Past event 3.47 4.11 -4.48 48.18 <.001 2.65 2.73 -0.38 42.26 0.708 Positivity 3.5 3.59 -0.71 150.79 0.477 2.69 2.57 0.84 150.42 0.404 Negativity 3.47 3.69 -1.90 178.82 0.059 2.66 2.66 -0.02 186.14 0.987 Nothing 3.56 3.16 2.08 42.06 0.043 2.68 2.49 0.93 42.25 0.359 Note. Code = 0 (not experienced), Code = 1 (experienced the event). Results significant at p ≤ .001 are bolded. 122 Table 19. (Cont’d) Impact Positive Valence Code Code=0 Code=1 t df p Code=0 Code=1 t df p Personal event 2.96 3.4 -3.35 130.73 0.001 2.63 2.82 -1.54 179.55 0.126 Close other's event 3.34 2.95 1.72 34.06 0.095 2.80 2.48 1.77 38.72 0.084 Others' event 3.36 2.82 3.34 49.73 0.002 2.80 2.62 1.09 51.70 0.282 Positive romance 3.35 3.01 2.20 60.06 0.032 2.81 2.56 1.52 60.64 0.133 Negative romance 3.21 3.69 -3.62 146.32 <.001 2.96 2.16 6.30 175.00 <.001 Missing positive romance 3.32 3.21 0.58 46.94 0.564 2.77 2.90 -0.71 50.06 0.479 Missing negative romance 3.29 3.45 -1.10 86.40 0.273 2.85 2.37 3.34 92.22 0.001 Connection 3.31 3.38 -0.28 26.17 0.778 2.75 3.29 -1.85 25.11 0.075 No connection 3.29 3.51 -1.23 53.60 0.224 2.86 2.12 3.97 55.72 <.001 Freedom 3.32 3.27 0.45 151.01 0.650 2.56 3.59 -7.34 137.82 <.001 Death 3.25 4.20 -4.62 33.74 <.001 2.88 1.53 9.29 42.62 <.001 Idiosyncratic 3.32 3.28 0.17 39.14 0.870 2.80 2.56 1.06 40.42 0.297 Present event 3.42 3.26 1.37 258.82 0.173 2.66 2.84 -1.48 276.16 0.140 Past event 3.25 3.93 -3.87 45.07 <.001 2.83 2.28 2.92 45.65 0.005 Positivity 3.29 3.38 -0.75 174.94 0.455 2.59 3.42 -6.18 163.79 <.001 Negativity 3.22 3.60 -2.96 175.92 0.003 3.02 2.07 8.28 227.32 <.001 Nothing 3.35 2.92 2.37 44.27 0.022 2.76 3.00 -1.39 46.26 0.173 Note. Code = 0 (not experienced), Code = 1 (experienced the event). Results significant at p ≤ .001 are bolded. 123 Table 19 (cont’d). Worldview Ordinary Code Code=0 Code=1 t df p Code=0 Code=1 t df p Personal event 2.94 3.30 -2.96 138.86 0.004 3.43 3.68 -2.36 127.79 0.020 Close other's event 3.27 2.76 2.93 37.08 0.006 3.64 3.56 0.43 34.57 0.668 Others' event 3.27 2.82 3.04 51.61 0.004 3.63 3.6 0.23 46.69 0.822 Positive romance 3.26 2.99 2.03 65.95 0.046 3.66 3.42 1.99 60.48 0.052 Negative romance 3.18 3.42 -1.97 158.64 0.050 3.60 3.75 -1.56 167.57 0.121 Missing positive romance 3.22 3.39 -0.95 47.48 0.349 3.64 3.58 0.41 46.22 0.687 Missing negative romance 3.21 3.34 -1.03 97.90 0.303 3.60 3.85 -2.49 93.51 0.015 Connection 3.22 3.40 -0.85 26.71 0.403 3.62 3.77 -0.84 26.13 0.409 No connection 3.28 2.84 2.37 51.88 0.022 3.62 3.69 -0.50 57.20 0.621 Freedom 3.17 3.44 -1.99 134.99 0.048 3.59 3.78 -2.02 155.68 0.045 Death 3.21 3.47 -1.39 35.28 0.172 3.63 3.67 -0.23 33.68 0.820 Idiosyncratic 3.23 3.28 -0.23 39.84 0.819 3.63 3.6 0.24 40.95 0.815 Present event 3.24 3.23 0.08 257.63 0.934 3.58 3.65 -0.81 280.29 0.420 Past event 3.20 3.55 -2.07 44.91 0.044 3.63 3.65 -0.13 42.65 0.894 Positivity 3.15 3.49 -2.71 160.52 0.007 3.62 3.65 -0.26 142.41 0.797 Negativity 3.20 3.31 -0.94 184.35 0.347 3.61 3.70 -0.95 178.21 0.342 Nothing 3.26 2.93 1.71 42.96 0.095 3.66 3.29 2.50 42.31 0.016 Note. Code = 0 (not experienced), Code = 1 (experienced the event). Results significant at p ≤ .001 are bolded. 124 Table 19 (cont’d). Status Change Code Code=0 Code=1 t df p Personal event 2.37 2.35 0.13 131.38 0.895 Close other's event 2.39 1.90 2.13 35.92 0.040 Others' event 2.39 2.08 1.75 53.06 0.086 Positive romance 2.35 2.38 -0.13 60.03 0.898 Negative romance 2.31 2.51 -1.18 144.61 0.238 Missing positive romance 2.36 2.35 0.03 46.78 0.974 Missing negative romance 2.35 2.38 -0.17 81.53 0.865 Connection 2.37 2.21 0.57 25.92 0.575 No connection 2.36 2.36 0.01 52.42 0.995 Freedom 2.41 2.17 1.51 140.72 0.133 Death 2.39 1.90 2.12 34.59 0.041 Idiosyncratic 2.36 2.31 0.24 41.62 0.813 Present event 2.37 2.35 0.13 267.97 0.896 Past event 2.32 2.68 -1.36 41.41 0.180 Positivity 2.38 2.26 0.80 167.58 0.423 Negativity 2.34 2.40 -0.36 177.21 0.719 Nothing 2.33 2.65 -1.38 42.90 0.176 Note. Code = 0 (not experienced), Code = 1 (experienced the event). Results significant at p ≤ .001 are bolded. 125 Table 20. Linear regressions predicting event characteristics from individual differences (Study 3) Predictability 95% CI b β se t p LB UB Intercept 3.06 0.00 0.06 53.37 <.001 2.95 3.18 Expect Benefits -0.13 -0.14 0.06 -2.16 0.031 -0.25 -0.01 Expect Support 0.05 0.06 0.06 0.91 0.363 -0.06 0.16 Expect Negatives 0.03 0.03 0.06 0.49 0.627 -0.10 0.16 Sat: Autonomy 0.00 0.00 0.10 -0.02 0.981 -0.21 0.20 Sat: Relatedness 0.03 0.03 0.09 0.34 0.736 -0.14 0.20 Sat: Competence 0.10 0.08 0.10 1.04 0.301 -0.09 0.29 Frus: Autonomy 0.10 0.09 0.08 1.28 0.202 -0.05 0.25 Frus: Relatedness 0.05 0.04 0.09 0.50 0.620 -0.14 0.23 Frus: Competence 0.08 0.08 0.09 0.88 0.380 -0.10 0.26 Soi-r Behavior -0.18 -0.14 0.08 -2.33 0.020 -0.33 -0.03 Soi-r Attitude 0.02 0.02 0.06 0.33 0.744 -0.11 0.15 Soi-r Desire 0.10 0.10 0.07 1.52 0.130 -0.03 0.24 Courtship -0.06 -0.05 0.08 -0.80 0.422 -0.21 0.09 Freedom -0.12 -0.10 0.07 -1.71 0.088 -0.25 0.02 Previous Constraint 0.27 0.22 0.08 3.48 0.001 0.12 0.42 Personal Constraint 0.19 0.15 0.08 2.41 0.017 0.04 0.35 Avoidance -0.07 -0.07 0.06 -1.25 0.214 -0.18 0.04 Anxiety -0.02 -0.03 0.05 -0.36 0.722 -0.11 0.07 Age 0.01 0.06 0.01 1.11 0.266 0.00 0.01 Education -0.04 -0.16 0.01 -3.21 0.001 -0.06 -0.01 Gender -0.04 -0.03 0.07 -0.58 0.562 -0.17 0.10 Financial Difficulty 0.05 0.08 0.03 1.49 0.137 -0.02 0.11 Relationship Num 0.00 0.01 0.02 0.23 0.821 -0.03 0.03 Relationship Length 0.01 0.02 0.03 0.30 0.763 -0.06 0.08 Singlehood Length -0.01 -0.14 0.00 -2.68 0.008 -0.02 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 126 Table 20 (cont’d). Worldview 95% CI b β se t p LB UB Intercept 3.20 0.00 0.05 59.53 <.001 3.10 3.31 Expect Benefits 0.04 0.05 0.06 0.76 0.448 -0.07 0.16 Expect Support 0.01 0.01 0.05 0.13 0.901 -0.10 0.11 Expect Negatives 0.10 0.10 0.06 1.58 0.115 -0.02 0.21 Sat: Autonomy 0.07 0.06 0.10 0.76 0.448 -0.12 0.27 Sat: Relatedness 0.08 0.07 0.08 0.94 0.346 -0.08 0.24 Sat: Competence 0.17 0.15 0.09 1.93 0.055 0.00 0.35 Frus: Autonomy -0.06 -0.06 0.07 -0.83 0.406 -0.20 0.08 Frus: Relatedness 0.09 0.09 0.09 0.99 0.321 -0.08 0.26 Frus: Competence -0.02 -0.02 0.09 -0.19 0.850 -0.19 0.15 Soi-r Behavior -0.12 -0.10 0.07 -1.70 0.090 -0.26 0.02 Soi-r Attitude -0.01 -0.02 0.06 -0.24 0.813 -0.13 0.10 Soi-r Desire -0.03 -0.03 0.06 -0.47 0.638 -0.16 0.10 Courtship 0.03 0.03 0.07 0.41 0.680 -0.11 0.17 Freedom 0.00 0.00 0.06 -0.01 0.990 -0.13 0.13 Previous Constraint 0.20 0.18 0.07 2.74 0.006 0.06 0.34 Personal Constraint 0.06 0.05 0.08 0.82 0.414 -0.09 0.21 Avoidance -0.08 -0.09 0.05 -1.50 0.136 -0.18 0.02 Anxiety 0.04 0.06 0.04 0.85 0.395 -0.05 0.12 Age 0.00 -0.05 0.00 -0.90 0.370 -0.01 0.01 Education -0.01 -0.07 0.01 -1.35 0.177 -0.04 0.01 Gender 0.05 0.04 0.06 0.77 0.440 -0.08 0.18 Financial Difficulty 0.02 0.04 0.03 0.78 0.437 -0.04 0.08 Relationship Num 0.00 -0.02 0.02 -0.29 0.769 -0.03 0.03 Relationship Length -0.01 -0.01 0.03 -0.15 0.878 -0.07 0.06 Singlehood Length -0.01 -0.09 0.00 -1.69 0.092 -0.01 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 127 Table 20 (cont’d). Emotional Significance 95% CI b β se t p LB UB Intercept 3.50 0.00 0.05 64.56 <.001 3.39 3.60 Expect Benefits 0.00 0.00 0.06 0.03 0.974 -0.11 0.11 Expect Support 0.06 0.08 0.05 1.20 0.232 -0.04 0.17 Expect Negatives 0.01 0.01 0.06 0.15 0.877 -0.11 0.13 Sat: Autonomy 0.08 0.06 0.10 0.77 0.439 -0.12 0.27 Sat: Relatedness 0.16 0.15 0.08 1.91 0.058 -0.01 0.32 Sat: Competence 0.05 0.05 0.09 0.57 0.570 -0.13 0.23 Frus: Autonomy -0.01 -0.01 0.07 -0.14 0.889 -0.15 0.13 Frus: Relatedness 0.02 0.02 0.09 0.24 0.811 -0.15 0.19 Frus: Competence 0.07 0.08 0.09 0.85 0.395 -0.10 0.25 Soi-r Behavior -0.12 -0.10 0.07 -1.62 0.106 -0.26 0.03 Soi-r Attitude 0.00 0.00 0.06 0.04 0.972 -0.12 0.12 Soi-r Desire -0.01 -0.01 0.07 -0.10 0.920 -0.13 0.12 Courtship -0.07 -0.06 0.07 -0.92 0.356 -0.21 0.07 Freedom -0.10 -0.09 0.06 -1.50 0.135 -0.22 0.03 Previous Constraint 0.24 0.23 0.07 3.31 0.001 0.10 0.39 Personal Constraint -0.06 -0.05 0.08 -0.79 0.428 -0.21 0.09 Avoidance 0.00 0.00 0.05 0.06 0.955 -0.10 0.11 Anxiety 0.04 0.07 0.04 0.87 0.383 -0.05 0.12 Age 0.00 0.04 0.00 0.70 0.486 -0.01 0.01 Education -0.01 -0.03 0.01 -0.48 0.631 -0.03 0.02 Gender 0.11 0.10 0.07 1.73 0.085 -0.02 0.24 Financial Difficulty 0.01 0.02 0.03 0.31 0.758 -0.05 0.07 Relationship Num 0.02 0.06 0.01 1.13 0.259 -0.01 0.05 Relationship Length 0.00 0.01 0.03 0.09 0.929 -0.06 0.07 Singlehood Length 0.00 0.02 0.00 0.34 0.731 -0.01 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 128 Table 20 (cont’d). External Control 95% CI b β se t p LB UB Intercept 2.68 0.00 0.05 49.76 <.001 2.57 2.79 Expect Benefits 0.00 0.00 0.06 0.05 0.960 -0.11 0.11 Expect Support 0.08 0.08 0.05 1.41 0.161 -0.03 0.18 Expect Negatives 0.07 0.06 0.06 1.07 0.284 -0.05 0.18 Sat: Autonomy -0.07 -0.06 0.10 -0.73 0.464 -0.26 0.12 Sat: Relatedness 0.02 0.02 0.08 0.23 0.815 -0.14 0.18 Sat: Competence 0.00 0.00 0.09 -0.03 0.977 -0.18 0.17 Frus: Autonomy -0.07 -0.06 0.07 -0.92 0.358 -0.21 0.07 Frus: Relatedness 0.15 0.15 0.09 1.75 0.082 -0.02 0.32 Frus: Competence -0.09 -0.10 0.09 -1.03 0.306 -0.26 0.08 Soi-r Behavior -0.03 -0.02 0.07 -0.39 0.700 -0.17 0.11 Soi-r Attitude 0.09 0.09 0.06 1.52 0.130 -0.03 0.21 Soi-r Desire -0.08 -0.08 0.07 -1.20 0.231 -0.20 0.05 Courtship 0.06 0.06 0.07 0.88 0.380 -0.08 0.20 Freedom -0.03 -0.03 0.06 -0.51 0.610 -0.16 0.09 Previous Constraint 0.22 0.20 0.07 3.07 0.002 0.08 0.37 Personal Constraint 0.18 0.15 0.07 2.45 0.015 0.04 0.33 Avoidance -0.08 -0.09 0.05 -1.51 0.133 -0.18 0.02 Anxiety 0.09 0.16 0.04 2.17 0.031 0.01 0.18 Age 0.00 0.00 0.00 0.03 0.974 -0.01 0.01 Education -0.03 -0.12 0.01 -2.35 0.019 -0.05 0.00 Gender 0.05 0.04 0.06 0.75 0.453 -0.08 0.17 Financial Difficulty 0.02 0.04 0.03 0.77 0.441 -0.04 0.08 Relationship Num 0.00 0.00 0.01 -0.08 0.934 -0.03 0.03 Relationship Length 0.05 0.07 0.03 1.42 0.157 -0.02 0.11 Singlehood Length 0.00 0.06 0.00 1.16 0.248 0.00 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 129 Table 20 (cont’d). Ordinary 95% CI b β se t p LB UB Intercept 3.54 0.00 0.05 75.59 <.001 3.45 3.63 Expect Benefits 0.03 0.03 0.05 0.51 0.609 -0.07 0.12 Expect Support 0.08 0.10 0.05 1.61 0.108 -0.02 0.17 Expect Negatives 0.01 0.01 0.05 0.16 0.877 -0.10 0.11 Sat: Autonomy 0.21 0.19 0.08 2.44 0.015 0.04 0.37 Sat: Relatedness 0.16 0.17 0.07 2.25 0.025 0.02 0.30 Sat: Competence 0.07 0.07 0.08 0.87 0.384 -0.09 0.22 Frus: Autonomy 0.09 0.10 0.06 1.43 0.155 -0.03 0.21 Frus: Relatedness -0.05 -0.05 0.08 -0.61 0.541 -0.19 0.10 Frus: Competence 0.05 0.06 0.08 0.63 0.531 -0.10 0.20 Soi-r Behavior -0.05 -0.05 0.06 -0.74 0.458 -0.17 0.08 Soi-r Attitude 0.03 0.04 0.05 0.55 0.581 -0.07 0.13 Soi-r Desire -0.01 -0.01 0.06 -0.19 0.850 -0.12 0.10 Courtship -0.04 -0.04 0.06 -0.63 0.526 -0.16 0.08 Freedom -0.01 -0.01 0.06 -0.16 0.877 -0.12 0.10 Previous Constraint 0.18 0.18 0.06 2.78 0.006 0.05 0.30 Personal Constraint -0.08 -0.07 0.07 -1.17 0.241 -0.21 0.05 Avoidance 0.06 0.08 0.05 1.33 0.183 -0.03 0.15 Anxiety 0.04 0.09 0.04 1.17 0.242 -0.03 0.12 Age 0.01 0.08 0.00 1.34 0.180 0.00 0.01 Education -0.01 -0.03 0.01 -0.61 0.541 -0.02 0.01 Gender 0.04 0.04 0.06 0.68 0.498 -0.07 0.15 Finance -0.03 -0.07 0.03 -1.25 0.213 -0.09 0.02 Relationship Num 0.00 -0.02 0.01 -0.31 0.755 -0.03 0.02 Relationship Length 0.04 0.07 0.03 1.37 0.173 -0.02 0.09 Singlehood Length 0.00 0.01 0.00 0.18 0.859 -0.01 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 130 Table 20 (cont’d). Impact 95% CI b β se t p LB UB Intercept 3.29 0.00 0.06 57.84 <.001 3.18 3.40 Expect Benefits -0.05 -0.05 0.06 -0.78 0.438 -0.17 0.07 Expect Support 0.04 0.05 0.06 0.73 0.467 -0.07 0.15 Expect Negatives 0.01 0.01 0.06 0.15 0.884 -0.12 0.13 Sat: Autonomy -0.04 -0.03 0.10 -0.36 0.723 -0.24 0.17 Sat: Relatedness -0.03 -0.02 0.09 -0.29 0.771 -0.19 0.14 Sat: Competence 0.21 0.18 0.10 2.16 0.031 0.02 0.39 Frus: Autonomy -0.05 -0.05 0.08 -0.65 0.518 -0.20 0.10 Frus: Relatedness 0.06 0.06 0.09 0.65 0.515 -0.12 0.24 Frus: Competence 0.11 0.12 0.09 1.21 0.226 -0.07 0.29 Soi-r Behavior -0.12 -0.10 0.08 -1.63 0.104 -0.27 0.03 Soi-r Attitude 0.06 0.06 0.06 0.91 0.364 -0.07 0.18 Soi-r Desire -0.05 -0.05 0.07 -0.70 0.484 -0.18 0.09 Courtship 0.10 0.09 0.08 1.38 0.167 -0.04 0.25 Freedom -0.05 -0.05 0.07 -0.77 0.442 -0.19 0.08 Previous Constraint 0.27 0.24 0.08 3.57 <.001 0.12 0.43 Personal Constraint -0.09 -0.07 0.08 -1.09 0.278 -0.24 0.07 Avoidance -0.07 -0.08 0.06 -1.27 0.206 -0.18 0.04 Anxiety 0.05 0.09 0.05 1.22 0.225 -0.03 0.14 Age 0.00 -0.01 0.01 -0.16 0.874 -0.01 0.01 Education -0.02 -0.09 0.01 -1.70 0.090 -0.04 0.00 Gender 0.12 0.10 0.07 1.71 0.089 -0.02 0.25 Financial Difficulty -0.01 -0.02 0.03 -0.30 0.762 -0.07 0.05 Relationship Num -0.01 -0.05 0.02 -0.90 0.371 -0.04 0.02 Relationship Length 0.02 0.04 0.03 0.68 0.495 -0.04 0.09 Singlehood Length 0.00 -0.05 0.00 -0.80 0.425 -0.01 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 131 Table 20 (cont’d). Positive Valence 95% CI b β se t p LB UB Intercept 2.79 0.00 0.06 49.41 <.001 2.68 2.90 Expect Benefits 0.03 0.03 0.06 0.42 0.672 -0.09 0.14 Expect Support -0.16 -0.17 0.06 -2.85 0.005 -0.27 -0.05 Expect Negatives 0.05 0.04 0.06 0.78 0.439 -0.08 0.17 Sat: Autonomy 0.21 0.15 0.10 2.05 0.042 0.01 0.41 Sat: Relatedness -0.01 -0.01 0.09 -0.15 0.878 -0.18 0.16 Sat: Competence -0.02 -0.01 0.09 -0.17 0.865 -0.20 0.17 Frus: Autonomy -0.11 -0.09 0.08 -1.40 0.163 -0.25 0.04 Frus: Relatedness 0.09 0.08 0.09 0.94 0.350 -0.09 0.26 Frus: Competence -0.05 -0.05 0.09 -0.57 0.571 -0.23 0.13 Soi-r Behavior -0.04 -0.03 0.07 -0.57 0.567 -0.19 0.10 Soi-r Attitude -0.02 -0.02 0.06 -0.34 0.735 -0.15 0.10 Soi-r Desire -0.07 -0.07 0.07 -1.03 0.305 -0.20 0.06 Courtship -0.19 -0.15 0.08 -2.54 0.012 -0.34 -0.04 Freedom 0.23 0.19 0.07 3.47 0.001 0.10 0.37 Previous Constraint -0.13 -0.11 0.08 -1.72 0.087 -0.28 0.02 Personal Constraint 0.02 0.02 0.08 0.28 0.781 -0.13 0.18 Avoidance 0.04 0.04 0.06 0.72 0.472 -0.07 0.15 Anxiety -0.05 -0.08 0.05 -1.21 0.229 -0.14 0.03 Age -0.01 -0.13 0.01 -2.26 0.025 -0.02 0.00 Education 0.00 -0.02 0.01 -0.33 0.740 -0.03 0.02 Gender 0.08 0.07 0.07 1.23 0.218 -0.05 0.22 Financial Difficulty -0.14 -0.22 0.03 -4.44 <.001 -0.21 -0.08 Relationship Num 0.00 0.01 0.02 0.21 0.831 -0.03 0.03 Relationship Length -0.04 -0.05 0.03 -1.12 0.266 -0.10 0.21 Singlehood Length 0.00 -0.01 0.00 -0.26 0.793 -0.01 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 132 Table 20 (cont’d). Challenge 95% CI b β se t p LB UB Intercept 3.02 0.00 0.06 51.31 <.001 2.90 3.14 Expect Benefits 0.02 0.02 0.06 0.33 0.740 -0.10 0.14 Expect Support 0.11 0.11 0.06 1.95 0.052 0.00 0.23 Expect Negatives 0.04 0.03 0.07 0.57 0.567 -0.09 0.17 Sat: Autonomy -0.35 -0.24 0.11 -3.30 0.001 -0.56 -0.14 Sat: Relatedness 0.02 0.01 0.09 0.20 0.844 -0.16 0.19 Sat: Competence 0.20 0.15 0.10 2.06 0.040 0.01 0.39 Frus: Autonomy 0.02 0.02 0.08 0.29 0.775 -0.13 0.18 Frus: Relatedness -0.10 -0.08 0.10 -1.04 0.301 -0.28 0.09 Frus: Competence 0.08 0.07 0.10 0.81 0.416 -0.11 0.26 Soi-r Behavior -0.09 -0.06 0.08 -1.10 0.272 -0.24 0.07 Soi-r Attitude 0.08 0.07 0.07 1.19 0.235 -0.05 0.21 Soi-r Desire -0.01 -0.01 0.07 -0.20 0.843 -0.15 0.13 Courtship 0.26 0.20 0.08 3.40 0.001 0.11 0.42 Freedom -0.17 -0.13 0.07 -2.42 0.016 -0.31 -0.03 Previous Constraint 0.23 0.18 0.08 2.90 0.004 0.07 0.39 Personal Constraint 0.03 0.02 0.08 0.30 0.761 -0.14 0.19 Avoidance -0.09 -0.08 0.06 -1.54 0.124 -0.20 0.02 Anxiety 0.15 0.22 0.05 3.14 0.002 0.05 0.24 Age 0.00 0.03 0.01 0.59 0.558 -0.01 0.01 Education 0.01 0.04 0.01 0.76 0.446 -0.01 0.03 Gender -0.01 -0.01 0.07 -0.15 0.878 -0.15 0.13 Financial Difficulty 0.08 0.13 0.03 2.53 0.012 0.02 0.15 Relationship Num 0.01 0.02 0.02 0.32 0.747 -0.03 0.04 Relationship Length 0.02 0.03 0.04 0.56 0.576 -0.05 0.09 Singlehood Length 0.00 -0.05 0.00 -1.07 0.284 -0.01 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 133 Table 20 (cont’d). Status Change 95% CI b β se t p LB UB Intercept 2.44 0.00 0.05 47.12 <.001 2.33 2.54 Expect Benefits 0.12 0.13 0.05 2.19 0.029 0.01 0.23 Expect Support -0.08 -0.09 0.05 -1.63 0.103 -0.18 0.02 Expect Negatives 0.01 0.01 0.06 0.23 0.818 -0.10 0.13 Sat: Autonomy -0.21 -0.15 0.09 -2.23 0.027 -0.39 -0.02 Sat: Relatedness -0.01 -0.01 0.08 -0.15 0.883 -0.17 0.14 Sat: Competence 0.21 0.18 0.09 2.48 0.014 0.04 0.38 Frus: Autonomy 0.06 0.05 0.07 0.85 0.398 -0.08 0.19 Frus: Relatedness 0.11 0.10 0.08 1.32 0.187 -0.05 0.27 Frus: Competence 0.14 0.14 0.08 1.66 0.097 -0.03 0.30 Soi-r Behavior -0.16 -0.13 0.07 -2.33 0.020 -0.29 -0.03 Soi-r Attitude 0.05 0.05 0.06 0.82 0.415 -0.07 0.16 Soi-r Desire -0.04 -0.04 0.06 -0.69 0.493 -0.17 0.08 Courtship 0.07 0.06 0.07 1.09 0.275 -0.06 0.21 Freedom -0.12 -0.10 0.06 -1.97 0.049 -0.24 0.00 Previous Constraint 0.18 0.15 0.07 2.59 0.010 0.04 0.32 Personal Constraint 0.26 0.21 0.07 3.70 <.001 0.12 0.40 Avoidance -0.05 -0.05 0.05 -0.91 0.365 -0.14 0.05 Anxiety 0.01 0.02 0.04 0.32 0.752 -0.07 0.09 Age -0.01 -0.09 0.00 -1.75 0.081 -0.02 0.00 Education -0.02 -0.08 0.01 -1.81 0.071 -0.04 0.00 Gender 0.10 0.08 0.06 1.59 0.113 -0.02 0.22 Financial Difficulty 0.01 0.02 0.03 0.48 0.635 -0.04 0.07 Relationship Num 0.01 0.03 0.01 0.75 0.453 -0.02 0.04 Relationship Length -0.01 -0.01 0.03 -0.28 0.783 -0.07 0.05 Singlehood Length 0.00 -0.06 0.00 -1.23 0.221 -0.01 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 134 Table 21. Linear regressions predicting well-being from event characteristics (Study 3) Life satisfaction 95% CI b β se t p LB UB Intercept 4.04 0.00 0.07 58.49 <.001 3.9 4.2 Predictable 0.02 0.02 0.07 0.31 0.755 -0.1 0.2 Worldview 0.26 0.17 0.08 3.09 0.002 0.1 0.4 Emotional Significance 0.19 0.12 0.09 2.00 0.046 0.0 0.4 External Control 0.12 0.08 0.07 1.63 0.104 0.0 0.3 Ordinary 0.09 0.05 0.08 1.23 0.219 -0.1 0.2 Impact -0.13 -0.09 0.10 -1.34 0.181 -0.3 0.1 Positive Valence 0.36 0.26 0.08 4.62 <.001 0.2 0.5 Challenge -0.15 -0.12 0.09 -1.73 0.084 -0.3 0.0 Status Change -0.19 -0.14 0.08 -2.48 0.013 -0.3 0.0 Age 0.01 0.05 0.01 1.10 0.271 0.0 0.0 Education 0.00 -0.01 0.01 -0.14 0.889 0.0 0.0 Gender -0.23 -0.13 0.07 -3.18 0.002 -0.4 -0.1 Financial Difficulty -0.31 -0.35 0.04 -8.07 <.001 -0.4 -0.2 Relationship Num -0.01 -0.02 0.02 -0.44 0.659 0.0 0.0 Relationship Length 0.02 0.02 0.04 0.46 0.65 -0.06 0.10 Singlehood Length 0.00 0.02 0.00 0.40 0.693 -0.01 0.01 1-item Singlehood Satisfaction 95% CI b β se t p LB UB Intercept 7.86 0.00 0.15 53.31 <.001 7.57 8.15 Predictable 0.26 0.10 0.15 1.79 0.074 -0.03 0.55 Worldview 0.44 0.16 0.18 2.45 0.015 0.09 0.79 Emotional Significance -0.06 -0.02 0.20 -0.28 0.778 -0.45 0.33 External Control 0.00 0.00 0.16 -0.01 0.996 -0.31 0.31 Ordinary 0.07 0.02 0.16 0.44 0.664 -0.25 0.39 Impact -0.02 -0.01 0.21 -0.12 0.908 -0.43 0.38 Positive Valence 0.69 0.27 0.17 4.17 <.001 0.36 1.01 Challenge -0.32 -0.13 0.19 -1.70 0.090 -0.70 0.05 Status Change -0.38 -0.14 0.17 -2.27 0.024 -0.71 -0.05 Age 0.02 0.09 0.01 1.72 0.087 0.00 0.04 Education 0.04 0.06 0.03 1.19 0.234 -0.02 0.09 Gender -0.32 -0.10 0.15 -2.07 0.039 -0.61 -0.02 Financial Difficulty -0.04 -0.03 0.08 -0.52 0.603 -0.20 0.12 Relationship Num -0.02 -0.02 0.04 -0.45 0.653 -0.10 0.06 Relationship Length 0.07 0.04 0.09 0.74 0.46 -0.11 0.24 Singlehood Length 0.01 0.05 0.01 0.93 0.352 -0.01 0.03 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 135 Table 21 (cont’d). ReSta Singlehood Satisfaction 95% CI b β se t p LB UB Intercept 2.87 0.00 0.04 70.86 <.001 2.79 2.95 Predictable 0.02 0.02 0.04 0.40 0.689 -0.06 0.10 Worldview 0.16 0.20 0.05 3.28 0.001 0.06 0.26 Emotional Significance 0.01 0.01 0.05 0.22 0.827 -0.10 0.12 External Control -0.01 -0.01 0.04 -0.19 0.848 -0.09 0.08 Ordinary -0.06 -0.06 0.04 -1.26 0.210 -0.14 0.03 Impact -0.05 -0.07 0.06 -0.94 0.350 -0.16 0.06 Positive Valence 0.22 0.30 0.05 4.78 <.001 0.13 0.31 Challenge -0.04 -0.06 0.05 -0.75 0.456 -0.14 0.06 Status Change -0.17 -0.22 0.05 -3.66 <.001 -0.26 -0.08 Age 0.00 0.03 0.00 0.68 0.500 0.00 0.01 Education 0.00 0.02 0.01 0.32 0.748 -0.01 0.02 Gender -0.13 -0.15 0.04 -3.18 0.002 -0.22 -0.05 Financial Difficulty 0.00 0.00 0.02 0.07 0.944 -0.04 0.05 Relationship Num 0.00 0.00 0.01 -0.03 0.978 -0.02 0.02 Relationship Length 0.02 0.03 0.02 0.72 0.473 -0.03 0.07 Singlehood Length 0.01 0.09 0.00 1.79 0.075 0.00 0.01 Depressive Symptoms 95% CI b β se t p LB UB Intercept 2.38 0.00 0.03 80.01 <.001 2.32 2.44 Predictable -0.01 -0.02 0.03 -0.34 0.733 -0.07 0.05 Worldview -0.09 -0.14 0.04 -2.50 0.013 -0.16 -0.02 Emotional Significance -0.05 -0.07 0.04 -1.20 0.231 -0.13 0.03 External Control 0.01 0.01 0.03 0.25 0.800 -0.05 0.07 Ordinary 0.05 0.07 0.03 1.57 0.117 -0.01 0.12 Impact 0.05 0.08 0.04 1.17 0.243 -0.03 0.13 Positive Valence -0.09 -0.16 0.03 -2.77 0.006 -0.16 -0.03 Challenge 0.11 0.20 0.04 2.80 0.005 0.03 0.18 Status Change 0.14 0.24 0.03 4.30 <.001 0.08 0.21 Age -0.01 -0.20 0.00 -4.41 <.001 -0.01 -0.01 Education 0.00 -0.03 0.01 -0.64 0.525 -0.02 0.01 Gender -0.01 -0.01 0.03 -0.24 0.808 -0.07 0.05 Financial Difficulty 0.07 0.20 0.02 4.47 <.001 0.04 0.11 Relationship Num 0.00 -0.02 0.01 -0.43 0.670 -0.02 0.01 Relationship Length 0.00 -0.01 0.02 -0.13 0.90 -0.04 0.03 Singlehood Length 0.00 0.02 0.00 0.43 0.670 0.00 0.00 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 136 Table 22. Linear regressions predicting well-being from individual differences (Study 3) Life satisfaction 95% CI b β se t p LB UB Intercept 4.07 0.00 0.07 60.83 <.001 3.93 4.20 Expect Benefits 0.11 0.08 0.07 1.58 0.116 -0.03 0.25 Expect Support -0.17 -0.13 0.07 -2.57 0.011 -0.30 -0.04 Expect Negatives 0.00 0.00 0.08 0.02 0.985 -0.15 0.15 Sat: Autonomy 0.50 0.26 0.12 4.16 <.001 0.26 0.74 Sat: Relatedness 0.25 0.16 0.10 2.47 0.014 0.05 0.45 Sat: Competence -0.03 -0.02 0.11 -0.23 0.817 -0.24 0.19 Frus: Autonomy 0.02 0.01 0.09 0.17 0.867 -0.16 0.19 Frus: Relatedness -0.02 -0.02 0.11 -0.21 0.838 -0.23 0.19 Frus: Competence -0.18 -0.13 0.11 -1.67 0.095 -0.39 0.03 Soi-r Behavior -0.13 -0.07 0.09 -1.50 0.136 -0.31 0.04 Soi-r Attitude 0.08 0.05 0.07 1.05 0.293 -0.07 0.22 Soi-r Desire 0.07 0.05 0.08 0.92 0.359 -0.08 0.23 Courtship -0.10 -0.06 0.09 -1.17 0.242 -0.28 0.07 Freedom 0.19 0.11 0.08 2.35 0.020 0.03 0.34 Previous Constraint -0.04 -0.03 0.09 -0.47 0.642 -0.22 0.14 Personal Constraint 0.03 0.02 0.09 0.31 0.759 -0.15 0.21 Avoidance -0.01 -0.01 0.07 -0.21 0.831 -0.14 0.11 Anxiety -0.05 -0.06 0.05 -0.93 0.352 -0.15 0.05 Age 0.00 -0.04 0.01 -0.77 0.441 -0.02 0.01 Education -0.01 -0.02 0.01 -0.55 0.582 -0.03 0.02 Gender -0.21 -0.12 0.08 -2.59 0.010 -0.36 -0.05 Finance -0.27 -0.31 0.04 -7.14 <.001 -0.34 -0.20 Relationship Num 0.01 0.02 0.02 0.55 0.586 -0.03 0.05 Relationship Length 0.01 0.01 0.04 0.29 0.771 -0.07 0.09 Singlehood Length 0.01 0.06 0.00 1.24 0.217 0.00 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 137 Table 22 (cont’d). 1-item Singlehood Satisfaction 95% CI b β se t p LB UB Intercept 7.97 0.00 0.14 56.75 <.001 7.70 8.25 Expect Benefits 0.04 0.02 0.15 0.29 0.774 -0.25 0.33 Expect Support -0.32 -0.13 0.14 -2.27 0.024 -0.59 -0.04 Expect Negatives -0.06 -0.02 0.16 -0.36 0.722 -0.37 0.25 Sat: Autonomy 0.70 0.20 0.25 2.77 0.006 0.20 1.20 Sat: Relatedness 0.26 0.09 0.21 1.22 0.224 -0.16 0.68 Sat: Competence -0.15 -0.05 0.23 -0.64 0.520 -0.61 0.31 Frus: Autonomy 0.01 0.00 0.19 0.06 0.949 -0.35 0.38 Frus: Relatedness -0.28 -0.10 0.23 -1.24 0.217 -0.72 0.17 Frus: Competence 0.07 0.03 0.23 0.32 0.749 -0.37 0.52 Soi-r Behavior 0.01 0.00 0.19 0.04 0.972 -0.36 0.37 Soi-r Attitude 0.04 0.01 0.16 0.24 0.813 -0.27 0.34 Soi-r Desire -0.27 -0.10 0.17 -1.63 0.105 -0.60 0.06 Courtship 0.07 0.02 0.19 0.38 0.704 -0.29 0.44 Freedom 0.98 0.31 0.17 5.85 <.001 0.65 1.31 Previous Constraint -0.17 -0.05 0.19 -0.90 0.367 -0.55 0.20 Personal Constraint -0.32 -0.10 0.19 -1.66 0.098 -0.70 0.06 Avoidance 0.08 0.03 0.14 0.62 0.539 -0.18 0.35 Anxiety -0.21 -0.13 0.11 -1.93 0.055 -0.43 0.01 Age -0.01 -0.03 0.01 -0.56 0.576 -0.03 0.02 Education 0.01 0.02 0.03 0.36 0.720 -0.05 0.07 Gender -0.13 -0.04 0.17 -0.80 0.425 -0.46 0.20 Finance -0.10 -0.06 0.08 -1.27 0.205 -0.26 0.06 Relationship Num 0.00 0.00 0.04 0.09 0.932 -0.07 0.08 Relationship Length 0.00 0.00 0.08 -0.02 0.982 -0.16 0.16 Singlehood Length 0.00 0.02 0.01 0.41 0.680 -0.01 0.02 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 138 Table 22 (cont’d). ReSta Singlehood Satisfaction 95% CI b β se t p LB UB Intercept 2.91 0.00 0.04 79.51 <.001 2.84 2.99 Expect Benefits -0.02 -0.02 0.04 -0.40 0.687 -0.09 0.06 Expect Support -0.08 -0.12 0.04 -2.32 0.021 -0.16 -0.01 Expect Negatives 0.02 0.03 0.04 0.56 0.578 -0.06 0.10 Sat: Autonomy 0.19 0.19 0.07 2.91 0.004 0.06 0.32 Sat: Relatedness 0.09 0.11 0.06 1.70 0.091 -0.02 0.20 Sat: Competence -0.07 -0.08 0.06 -1.17 0.245 -0.19 0.05 Frus: Autonomy -0.06 -0.08 0.05 -1.30 0.194 -0.16 0.03 Frus: Relatedness -0.07 -0.09 0.06 -1.25 0.214 -0.19 0.04 Frus: Competence -0.05 -0.06 0.06 -0.77 0.442 -0.16 0.07 Soi-r Behavior -0.01 -0.01 0.05 -0.19 0.853 -0.10 0.09 Soi-r Attitude 0.04 0.05 0.04 0.92 0.358 -0.04 0.12 Soi-r Desire -0.08 -0.10 0.04 -1.83 0.067 -0.17 0.01 Courtship 0.00 0.00 0.05 -0.07 0.944 -0.10 0.09 Freedom 0.34 0.39 0.04 7.86 <.001 0.26 0.43 Previous Constraint -0.07 -0.08 0.05 -1.46 0.145 -0.17 0.03 Personal Constraint -0.13 -0.14 0.05 -2.60 0.010 -0.23 -0.03 Avoidance 0.04 0.06 0.04 1.21 0.227 -0.03 0.11 Anxiety -0.03 -0.05 0.03 -0.85 0.394 -0.08 0.03 Age -0.01 -0.09 0.00 -1.89 0.060 -0.01 0.00 Education 0.00 -0.01 0.01 -0.29 0.770 -0.02 0.01 Gender -0.07 -0.08 0.04 -1.66 0.098 -0.16 0.01 Finance -0.01 -0.02 0.02 -0.52 0.605 -0.05 0.03 Relationship Num 0.01 0.03 0.01 0.67 0.503 -0.01 0.03 Relationship Length -0.01 -0.02 0.02 -0.42 0.675 -0.05 0.03 Singlehood Length 0.00 0.07 0.00 1.56 0.119 0.00 0.01 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 139 Table 22 (cont’d). Depressive Symptoms 95% CI b β se t p LB UB Intercept 2.37 0.00 0.03 88.86 <.001 2.31 2.42 Expect Benefits 0.03 0.06 0.03 1.14 0.254 -0.02 0.09 Expect Support 0.01 0.02 0.03 0.49 0.625 -0.04 0.07 Expect Negatives -0.05 -0.07 0.03 -1.52 0.130 -0.10 0.01 Sat: Autonomy -0.07 -0.09 0.05 -1.52 0.130 -0.17 0.02 Sat: Relatedness -0.09 -0.14 0.04 -2.30 0.022 -0.17 -0.01 Sat: Competence -0.06 -0.09 0.04 -1.44 0.151 -0.15 0.02 Frus: Autonomy 0.10 0.15 0.04 2.77 0.006 0.03 0.17 Frus: Relatedness -0.06 -0.09 0.04 -1.40 0.164 -0.14 0.02 Frus: Competence 0.05 0.08 0.04 1.14 0.255 -0.04 0.13 Soi-r Behavior -0.02 -0.02 0.04 -0.51 0.613 -0.09 0.05 Soi-r Attitude -0.02 -0.03 0.03 -0.64 0.523 -0.08 0.04 Soi-r Desire 0.06 0.09 0.03 1.72 0.086 -0.01 0.12 Courtship 0.08 0.11 0.04 2.20 0.028 0.01 0.15 Freedom -0.01 -0.01 0.03 -0.26 0.795 -0.07 0.05 Previous Constraint 0.16 0.22 0.04 4.38 <.001 0.09 0.23 Personal Constraint 0.01 0.01 0.04 0.21 0.835 -0.07 0.08 Avoidance 0.00 0.00 0.03 0.04 0.969 -0.05 0.05 Anxiety 0.08 0.22 0.02 3.95 <.001 0.04 0.12 Age 0.00 -0.06 0.00 -1.37 0.171 -0.01 0.00 Education 0.00 -0.03 0.01 -0.82 0.411 -0.02 0.01 Gender 0.00 0.00 0.03 -0.03 0.974 -0.06 0.06 Finance 0.04 0.12 0.02 2.84 0.005 0.01 0.07 Relationship Num -0.01 -0.07 0.01 -1.82 0.069 -0.03 0.00 Relationship Length 0.01 0.01 0.02 0.29 0.771 -0.03 0.04 Singlehood Length 0.00 -0.05 0.00 -1.13 0.260 -0.01 0.001 Note. Results significant at p ≤ .001 are bolded. Relationship number/length = number/length of previous relationships. Gender: 1 = men, -1 = women. 140 Figure 1. Hypothesized interaction between marital attitudes and marital status (Study 1a) Hypothesized interaction between marital attitudes and marital status 12 10 Happiness 8 6 4 2 0 married single previously-married Relationship status Must Good, if possible 141 Figure 2. Interaction between marital status and marital attitudes on well-being (Study 1a) Note. 1 = marriage is a must, 2 = marriage is good, if possible, 3= marriage is unnecessary if unwilling. The top and bottom figures show identical information; the top figure was made to show the deviations from the prediction while the bottom figure was made to more clearly illustrate the interaction. Below are the estimated well-being scores for each combination with 95% confidence intervals in parentheses. Never-married Previously married Married Must 6.80 [6.65,6.95] 6.87 [6.68,7.07] 7.27 [7.21,7.33] Good 6.79 [6.70,6.88] 6.51 [6.31,6.72] 7.09 [7.04,7.13] Unnecessary 6.52 [6.44,6.60] 6.27 [6.06,6.49] 6.69 [6.63,6.75] 142 Figure 3. Changes in relationship expectations over time by relationship history (Study 1b) Expectations for financial benefits 2.20 2.15 2.10 Expectations 2.05 Partnered Single 2.00 Total 1.95 1.90 1 2 3 4 5 6 Waves Expectations for support 4.80 4.70 Expectations 4.60 4.50 Partnered Single 4.40 Total 4.30 4.20 1 2 3 4 5 6 Waves Note. Partnered = participants who were partnered for at least 60% of the study duration. Single = participants who were single for at least 60%o of the study duration. Linear and/or quadratic trajectories for relationship expectations were plotted based on mean expectation scores at each wave. 143 Figure 3 (cont’d). 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