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This is to certify that the
thesis entitled

WOMEN UNDERGOING BREAST MRI:
THE EFFECTIVENESS OF STATE ANXIETY
INTERVENTIONS

presented by

LORI A. HOISINGTON

has been accepted towards fulfillment
of the requirements for the

Master of Arts degree in Family and Child Ecologx

 

 

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5/10/2206

 

 

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WOMEN UNDERGOING BREAST MRI:
THE EFFECTIVENESS OF STATE ANXIETY INTERVENTIONS

By

Lori A. Hoisington

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF ARTS
Department of Family & Child Ecology

2006

ABSTRACT

WOMEN UNDERGOING BREAST MRI:
THE EFFECTIVENESS OF STATE ANXIETY INTERVENTIONS

By

Lori A. Hoisington

The purpose of this experimental study was to compare the effectiveness of three
educational interventions in reducing state-anxiety levels for women undergoing breast
MRI screenings. The primary independent variable for this study was an educational
intervention PowerPoint tool. Other variables included perceived social support network,
claustrophobia, baseline level of knowledge about MRI, marital status, highest level of
education and previous history of breast cancer. The study sample consisted of 128
women scheduled to undergo Breast MRI exams. Data were gathered in a single Midwest
clinic using questionnaires and an inventory over a period of nine months. Kendall tau-b
correlations, One-way and Two-way ANOVA tests and a multivariate regression analysis
were used to identify relationships between variables.

The study showed no significant relationship between methods of intervention
and state anxiety levels. However, the study did show significant reductions in state-
anxiety levels following intervention within all three groups. Results further indicated
significant relationships between pre-intervention state anxiety and trait anxiety, post-
intervention state anxiety and claustrophobia and also between trait anxiety and
claustrophobia. Several interaction effects were also shown between the study variables

and the three intervention groups.

Copyright by
LORI A. HOISINGTON

2006

ACKNOWLEDGMENTS

I offer thanks to many individuals who supported me throughout this project. I am
deeply grateful to my committee members, Dr. David Imig, Dr. Kevin Berger, Dr.
Barbara Given, Dr. Lori Post, and Dr. Thomas Luster, who believed in me, supported me,
and offered advice and assistance on many occasions. I am also gratefiil to fellow
researchers who offered encouragement and provided help when I was in need: Dr. Laura
Symonds, Dr. Jie Huang, Gia Barboza, Ronald Cox, Margaret Meade, and Debra Scherer.
In addition, I express deep gratitude to Sarra Baraily for her thoughtful assistance and
expertise in editing this thesis.

Special thanks to Dr. Charles Spielberger for his generous input and thoughtful
guidance with interpretation of results for the State-Trait Anxiety Inventory. Also special
thanks to Pastor Royce Allen for convincing me that I could produce my best work in the
face of adversity and to my husband and mother for their faithful support and
encouragement. In addition, I’m grateful to Dr. E. James Potchen, Tom Cooper and other
members of the Department of Radiology, MRI, for supporting my efforts and providing
the sample population and location for data collection. But above all, I thank God for

carrying me through this journey!

iv

TABLE OF CONTENTS

Page
LIST OF TABLES .................................................................................................... vii
LIST OF FIGURES ................................................................................................... ix
CHAPTER 1
INTRODUCTION .................................................................................................... 1
Identification of the Problem ........................................................................ 1
Purpose of the Study ..................................................................................... 3
Significance of the Study .............................................................................. 4
Overview of Conceptual Model, Data Analysis, Results and Implications... 4
CHAPTER 2
LITERATURE REVIEW .......................................................................................... 6
Human Ecological Theory ............................................................................ 6
Anxiety and Distress ..................................................................................... 9
Social Support ............................................................................................... 11
Educational Intervention ................................................................................ 12
Multimedia Intervention ............................................................................... 14
CHAPTER 3
METHODOLOGY .................................................................................................... 17
Participants .................................................................................................... 17
Design ........................................................................................................... 18
Procedure ...................................................................................................... 19
Conceptual Definitions .................................................................................. 20
Inclusion Criteria .......................................................................................... 21
Exclusion Criteria .......................................................................................... 21
Development of Educational Intervention Tool ............................................ 21
MRI Standard Verbal Explanation ................................................................ 22
Hypotheses .................................................................................................... 24
Measurement .................................................................................................. 26
Coding ............................................................................................................ 29
Data Analysis ................................................................................................ 29
CHAPTER 4
RESULTS .................................................................................................................. 31
Univariate Analysis ....................................................................................... 32
Bivariate Analysis ......................................................................................... 38
Research Hypotheses .................................................................................... 47
Post-Hoe Analysis .......................................................................................... 57
Multivariate Analysis .................................................................................... 72

CHAPTER 5

DISCUSSION ............................................................................................................ 76
Limitations of Study ..................................................................................... 81
Conclusions ................................................................................................... 81
Implications for Future Research .................................................................. 83

APPENDICES ........................................................................................................... 87
Appendix A: Conceptual and Operational Definitions ................................. 89
Appendix B: Instrument Review —- State Trait Anxiety Inventory for

Adults (Form Y) .................................................................................... 92
Appendix C: Instrument Review - Short Form Social Support Questionnaire
(SSQ6) ................................................................................................... 97
Appendix D: Demographic Survey .............................................................. 101
Appendix E: Patient History Form — Mammography #1 ............................ 105
Appendix F: Patient History Form — Mammography #2 ............................. 107
Appendix G: Patient History Form — MR1 Mammography ......................... 109
Appendix H: State-Trait Anxiety Inventory ................................................ 111
Appendix 1: Short Form Social Support Questionnaire (SSQ6) ................. 114
Appendix J: Powerpoint Educational Intervention Tool ............................ 120
BIBLIOGRAPHY ...................................................................................................... 1 25

vi

Table

Table 1:

Table 2:

Table 3:

Table 4:

Table 5:

Table 6:

Table 7:

Table 8:

Table 9:

Table 10:

Table 1 1:

Table 12:

Table 13:

Table 14:

LIST OF TABLES

Page
Information Included in Standard Verbal Explanation of MRI ............... 23
Descriptive Statistics for Categorical Data: Group A, Group B and
Group C ..................................................................................................... 32
Descriptive Statistics for Interval Data: Group A, Group B and
Group C ..................................................................................................... 33
Comparison of Continuous Variables between Group A, Group B
and Group C using KW One-way ANOVA ................................................ 36
Correlation Between State Anxiety and Trait Anxiety Using Kendall’s
tau b (N = 128) .......................................................................................... 40
Correlations Between Pre-Intervention State Anxiety, Trait Anxiety,
and Variables Measured at the Interval Level using Kendall’s
taub (N=128) ............................................................................................ 41
Comparison of Pre-Intervention State Anxiety Scores and Categorical
Variables using KW One-Way ANOVA .................................................... 43
Comparison of Trait Anxiety Scores and Categorical Variables Using
KW One-Way ANOVA ............................................................................... 44
Comparison of Interventions Between Groups A, B, and C using a
One- Way ANOVA ...................................................................................... 47
Analysis of the Effectiveness of Interventions within Group A, Group B
and Group C using a 3 x 2 Repeated-Measures ANOVA .......................... 48
Analysis of Social Support Number and Effectiveness of Interventions
using a One-Way ANCOVA ...................................................................... 51
Analysis of Claustmphobia and the Eflectiveness of Interventions
using a Two-Way ANCOVA ...................................................................... 52
Analysis of Previous Knowledge about MRI and the Eflectiveness of
Interventions using a Two-Way ANCOVA ............................................... 53
Analysis of Marital Status and the Effectiveness of Interventions using
a Two-Way ANCOVA ............................................................................. 54

vii

Table 15:

Table 16:

Table 17:

Table 18:

Table 19:

Table 20:

Table 21:

Table 22:

Table 23:

Table 24:

Table 25:

Table 26:

Table 27:

Analysis of Highest Level of Education and the Efi‘ectiveness of
Interventions using a Two-Way ANC OVA ............................................ 55

Analysis of Previous Breast Cancer and the Effectiveness of
Interventions using a Two-Way ANC OVA ............................................ 56

Correlations Between Pre/Post Intervention % Change and Social
Support Number using Kendall’s tau b ................................................. 60

Analysis of Claustrophobia and Pre/Post Intervention % Change
Within Group A, B, and C using a One-way ANOVA ........................... 61

Interaction-by-group Eflect for Claustrophobia and Pre/Post
Intervention % Change Between Group A, B, and C, using a
Two- Way ANOVA .................................................................................. 62

Analysis of Previous Knowledge about MRI and Pre/Post Intervention
% Change Within Group A, B, and C using a One-Way ANOVA ......... 64

Interaction-by-group Effect for Previous Knowledge about MRI
and Pre/Post Intervention % Change Between Group A, B, and C
using a Two-Way ANOVA ..................................................................... 65

Analysis of Marital Status and Pre/Post Intervention % Change
within Group A, B, and C using a One-Way ANOVA .......................... 66

Analysis of Marital Status within Group A Showing Significant Pre-
Intervention vs Post-Intervention State-Anxiety Change ...................... 67

Analysis of Highest Level of Education and Pre/Post Intervention %
Change within Group A, B, and C using a One- Way ANOVA .............. 69

Analysis of Previous History of Breast Cancer and Pre/Post
Intervention % Change within Group A, B, and C using a
One-Way ANO VA .................................................................................. 7O

Interaction-by-Group Effect for Previous History of Breast Cancer
and Pre/Post Intervention % Change Between Group A, B, and C
using a Two-Way ANOVA ..................................................................... 71

Analysis of Moderator Variables and Post-Intervention State Anxiety
using Multivariate Analysis ................................................................... 73

viii

Figure

Figure I:
Figure 2:
Figure 3:

Figure 4:

Figure 5:

Figure 6:

LIST OF FIGURES

Page
Healthcare Model Based on Human Ecological Theory ....................... 9
Intervention Model ................................................................................. 19
Conceptual Model of Intervention with Test Variables ......................... 25
Profile Plot Comparing Pre-Intervention vs. Post-Intervention
State-Anxiety Change for Groups A, B, and C ..................................... 49
Post-hoe Model for Analysis of the Relationship between Moderator
Variables and the Effectiveness of Interventions within Group A, B,
and C ...................................................................................................... 58
Interaction-by-Group Effect for Claustrophobia between Group A,
B, and C .................................................................................................. 63

ix

CHAPTER 1

INTRODUCTION

A new trend in healthcare is emerging: an approach to healthcare which involves
increased focus on patients’ emotional and mental well-being with greater emphasis on
social support networks. As a result, patients often realize greater benefits from treatment
with fewer problems while in rehabilitation. One area of healthcare that has not been
adequately explored from this approach, however, is screening cf the breast with
Magnetic Resonance Imaging (MRI). MRI uses radiofrequency waves and a strong
magnetic field to provide clear and detailed pictures of internal organs and tissues within
the body. Breast MRI is a particularly complex specialty because women who have this

procedure often face the possibility of being diagnosed with cancer.

Identification of the Problem

Approximately three million women in the US. today are living with breast
cancer. “Two million have been diagnosed with the disease and one million have the
disease but do not know it yet” (National Breast Cancer Coalition, 2005, p. 3). Breast
cancer is the leading cause of cancer-related death among women in the US, aged 20-59,
and strikes more women in the world than any other type of cancer (International Agency
for Research on Cancer, 2001; National Cancer Institute, 2005; National Breast Cancer
Coalition, 2005). Furthermore, the prevalence of breast cancer is increasing. Since 1986.
rates have increased by 0.6 percent each year in the US. (Weir et al., 2003).

Given these statistics, the focus on breast-cancer screening is increasing in the

medical world. While breast self-exams and routine mammograms are basic preventative

measures that have been in use for decades, some of the newer screening methods include
breast thermography, breast tomo-mammography, and ultrasound.

One of the most recent methods of breast imaging is Magnetic Resonance
Imaging (MRI). This modality offers improved sensitivity for breast cancer detection
with greater definition of local tumor extent (National Cancer Institute, 2005). Results of
MRI trials reveal a 1-4% cancer yield on initial screening with one-third to one-half of
these lesions being occult on physical exams and mammographies (Hylton, 2005). MRI is
also useful for screening women under the age of 40 who are at high risk for developing
breast cancer (Breast MRI, 2004).

In addition to its use as a diagnostic tool, MRI helps determine the size and extent
of cancerous lesions when exams are positive. Surgery is usually recommended with two
options available depending on the extent of the cancer. In most cases, the surgeon
performs a lumpectomy, in which only part of the breast, containing the tumor and some
of the normal tissue surrounding it, is removed. However, in more advanced cases, a
mastectomy is performed with removal of the entire breast along with any affected lymph
nodes.

The risk of breast cancer often brings fear and anxiety to women. These emotions
are frequently heightened at the time when the women have to undergo diagnostic tests to
screen for the disease. A study conducted by Gram and Slenker (1992) revealed that one
in three women in the general population has anxiety about breast cancer. A more recent
survey conducted with 1,005 US. women further showed that breast cancer is now the
single most feared disease among women in the United States (International

Communications Research of Media, Pa., 2005). Those who are the most anxious before

screening are more likely to remain so after the procedure has been completed (Gram &
Slenker, 1992; Meystre-Agustoni, Paccaud, Jeannin, & Dubois-Arber, 2001). This
finding calls attention to potential adverse effects of mammography screening and reveals
the need for intervention to reduce levels of anxiety in women undergoing breast-cancer
screening procedures.

Other factors that are associated with overall quality of life for breast cancer
patients are social support networks. This is especially true for younger women under the
age of 50. Avis, Crawford and Manuel (2005) conducted research on 202 women in this
age-group who were diagnosed with breast cancer. Results of the study revealed that
women who are in poor relationships experience a lower overall sense of well-being
following the diagnosis of breast cancer than do women in good relationships, or women
without partners. Problems for women in poor relationships were related to almost all
quality-of-life domains. This study suggests the need for more research aimed toward
understanding how social support networks affect outcomes for women who are

diagnosed with breast cancer.

Purpose of the Study
The purpose of this research is twofold: the first is to compare the effectiveness of
three different methods of educational intervention in reducing state anxiety levels for
women who are scheduled to undergo breast MRI (which occurs through experimental
research using an educational intervention tool that provides information about the MRI
procedure), and the second is to describe the relationship between several moderator

variables and the effectiveness of the interventions. The primary moderator variable for

this study is perceived social support. Additional moderator variables include
claustrophobia, previous knowledge about MRI, marital status, highest level of education

and previous history of breast cancer.

Significance of the Study
Research, which compares various methods of educational intervention with state
anxiety levels in patients undergoing diagnostic exams, is limited. Information provided
by this study may be used to understand how computer-based interventions differ in
effectiveness from verbal interventions for women who are scheduled to undergo breast
screening procedures in Midwest clinics. In addition, results from this study may be used
to determine the most effective type of intervention for each individual based on his or

her personal characteristics.

Overview of Conceptual Model, Data Analysis, Results and Implications
The conceptual model for this research is presented in Chapter Three, which

introduces the experimental design along with conceptual definitions for the study.
Chapter Three also describes the study participants, who are women scheduled to
undergo breast MRI exams in a Midwest clinic. This section further introduces research
methodology used for this study and presents Operational definitions for independent
variables, the dependent variable, moderator variables and control variables. In addition,
Chapter Three also details the development and application of the educational
intervention tool, and provides information about methods of data collection and

measurement.

Results of the study are presented in Chapter Four with a summary of the
comparison between the three educational interventions and a discussion about the effects
of the other moderator variables. The analysis also considers the relationships between
pre-intervention state anxiety, post-intervention state anxiety, and trait anxiety and
discusses how they relate to the moderator variables and control variables.

Several new research questions were uncovered during the course of this study.
Chapter Five describes these findings and discusses their implications for future research.
This section also includes a summary of research findings and benefits afforded by the
study. As an extension of this research, the women who participated in this study will be
invited to continue in an ancillary longitudinal study. Permission to contact these women
for future research was obtained through informed consent on the original consent form.
The ancillary research will explore the long-term effects of the moderator variables on
the progress and well-being of the patients. Results from the current study will form the

foundation for a longitudinal study.

CHAPTER 2

LITERATURE REVIEW

Recent shifts in healthcare focus include the psychosocial well-being of patients
and their families. This approach adds an important dimension to patient care: namely,
social support. Several studies involving cancer patients and their families reveal strong
correlations between perceived levels of social support and levels of psychosocial distress
for both patients and family members (or other caregivers) (Kurtz M., Given B., Kurtz J.
& Given C., 1994; Cano et al., 2003; Northouse, Dom’s & Charron-Moore, 1995;
Northouse, Mood, Templin, Mellon & George, 2000). This bi-directional influence
between patients and their families demonstrates the need for further research to identify
factors that are associated with anxiety among women who are scheduled for clinical
studies, including breast MRI. These findings also emphasize the need for the
development of educational intervention tools to reduce patient and family anxiety and

distress.

Human Ecological Theory
This study is organized around human ecological theory because it provides a
holistic view of the interdependent relationships between individuals, their social systems,
and the physical and biological environments around them (Bubolz & Sontag, 1993). It is
also applicable when assessing the effectiveness of educational intervention in the
clinical setting. A basic premise of the theory is that individuals and groups are both

biological and social in nature (White & Klein, 2002). Humans depend upon their

environments to provide basic elements for survival. As social beings, humans also
depend upon other human beings for care and support. Families carry out psychosocial
and nurturing functions for the good of themselves, as well as for the good of society.
Severe illness in the family necessitates careful allocation and management of resources
in a manner that meets both the needs of the ill family member and the family as a group.
Human ecological theory is multifaceted and considers interactions from a
system’s perspective (Human Ecology Theory, 2002). Urie Bronfenbrenner’s
Bioecological System’s Theory defines multiple ecological levels that comprise the
structure of the environment: microsystem, mesosystem, exosystem, macrosystem and
chronosystem (Bronfenbrenner, 1990) (See Figure 1 on page 9). Bronfenbrenner’s model
provides a way of looking at interactions between patients and their environments while,
at the same time, considering the natural world or reality as constructed by the patient,
and the social and cultural setting in which the patient exists (McLaren & Hawe, 2005).
In the clinical context, Bronfenbrenner’s microsystem encompasses relationships
and interactions that occur in the patient’s immediate surroundings. This level includes
interactions with the patient’s family, close friends, neighborhood and workplace. Most
social support networks occur at this level. The next level, the mesosystem, represents
interactions among the patient’s different microsystems. Healthcare workers are often
part of a patient’s mesosystem. Physicians and patients rely on other healthcare
professionals to provide necessary medical services. The exosystem encompasses the
larger social system that indirectly affects the patient. This level includes the spouse’s
workplace schedule, healthcare clinic staffing and available resources for medical

information. The outermost level in Bronfenbrenner’s model is the macrosystem. This

level encompasses cultural values, customs and laws (Berk, 2000). The macrosystem
includes government regulations and public policies that provide guidelines for patient
care. Although patients do not interact directly with the macrosystem, guidelines
determined at this level have a cascading effect on patient care. The chronosystem
describes change that occurs over time for the patient, the patient’s social support
network and the environment.

Human ecological theory states that as the distance between the patient and the
external system increases. the influence of the system on the patient’s behavior decreases.
Systems that influence patient behavior in this study include the the patient’s perception
of the disease and her interactions with family, friends, neighbors, co-workers, healthcare
workers, and other community support services. As a general rule, the microsystem has
the greatest influence on patient behavior and the macrosystem has the least influence on
patient behavior.

In situations of severe illness. patients and their families may experience high
levels of stress as the demands for care increase. In order to prevent excessive stress. the
patient’s treatment plan should include provisions for health care. transportation, personal
assistance. and support groups. Effective patient care and treatment must include

coordination of efforts at multiple ecological levels.

Chronosystem —
Adaptation of people
and environment
over time '

 
 
 
  
 
 

  
  

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Figure 1. Healthcare Model (based on Bronfenbrenner’s Ecological Theory)

Anxiety and Distress
Healthcare research findings identify several factors related to anxiety and distress
in patients undergoing diagnosis and treatment for cancer. Variables associated with
anxiety include gender, positive test results, poor self-rated health, and dissatisfying

family support. These factors impact successful diagnosis of disease and patient response

to treatment. Greater understanding of this effect will allow for the development of more
effective treatment.

Interestingly, studies show that women generally report feeling greater levels of
distress than men. Northouse, Mood, Templin, Mellon & George in their study, Couples"
Patterns of Adjustment to Colon Cancer (2000), examined the relationship between
gender and distress. The authors concluded that women experience more stress than men
regardless of whether they are the patient or the wife of the patient.

Another strong predictor of anxiety in women undergoing breast-cancer screening
is a positive test result. Ironically, most positive test results are false. Patients frequently
misinterpret positive results as proof of a serious disease and experience potentially
disabling anxiety until additional testing is completed to reconfirm good health (Neher,
1999). Patients suffer anxiety even in the absence of definitive tests. In his study,
Reducing Anxiety about Positive Tests (1999), Neher stresses the importance of
informing patients before testing begins that most positive results are errors. The author
also describes the importance of informing patients face-to-face when positive results are
confirmed and performing follow-up testing as soon as possible. Regardless of whether
test results are confirmed or refuted, there is a need for further research to develop
educational intervention tools for reducing anxiety in patients undergoing breast MRI.

Other studies reveal relationships among self-rated health, family support, and
psychological distress. Cano, Scaturo, Sprafltin, Lantinga, Fiese & Brand (2003) describe
a negative relationship between combined family support and self-rated health and
psychological symptoms or disorders. Dissatisfying family support is positively

correlated with higher incidences of mood disorders and poor self-rated health is

10

positively correlated with higher incidences of mood and anxiety disorders.” (Cano et al.,
2003, p. 115). The study demonstrates the greatest elevation of psychological symptoms
in participants who report dissatisfying family support combined with poor self-rated
health. Findings suggest that assessment of family support may be used to increase
understanding of psychosocial risk factors in primary care and provide more

comprehensive health care.

Social Support

The importance of psychosocial support extends beyond its relationship with self-
rated health and anxiety disorders. Additional correlations are evident between patients’
perceived levels of social support and their levels of psychological and emotional
distress, as well as in their ability to adjust to disease.

Cano et al. (2003) describe a relationship between patients’ perceived levels of
family social support and their levels of psychological distress. Their study applies three
independent psychological distress measures to show how “quantity and quality of family
support are inversely related to psychological symptoms” (p. 112). The authors report
that patient perception of dissatisfying family social support is significantly related to
elevated psychological distress.

Other studies reveal correlations between perceived levels of social support and
the ability to cope with disease-related changes. Northouse et al. (2000) describe this
relationship for both patients and their spouses. According to the authors, family
functioning, marital satisfaction, and social support are primary social resources that can

affect adjustment. Northouse et al. report that a patient’s early response to disease is an

11

indicator of his or her ability to adjust to disease-related symptoms at a later time. In
addition, the authors identify the strongest predictors of patient role-adjustment problems
as a sense of hopelessness and spousal role problems. Northouse et al. further report that
patient spouses report less social support than the patients themselves.

Patients and their families also experience psychological dysfunction and
depression as they attempt to cope with disease-related changes. Rawl, Given, Given, et
al. (2002) describe these observations in their study, Intervention to Improve
Psychological Functioning for Newly Diagnosed Patients with Cancer. It includes a
computer-based nursing intervention program that provides educational information
about disease and treatment, along with emotional support. Patients in the study who
received the nursing intervention experienced significantly less depression than patients
who did not receive it.

These findings reveal a need for the development of assessment tools to
accurately identify patients and family members at risk for poorer adjustment to illness
(Rawl, et al. 2002, p. 283). Early identification of individuals with a high number of
adjustment problems is essential. Without intervention, the problems are likely to persist

for patients and their families, and cause difficulty with role adjustment at a later time.

Educational Intervention
The current trend to include the family in treatment for disease draws attention to
the need for family-focused intervention. Neher’s 1999 study about positive screening
tests reveals the value of using informational intervention to minimize anxiety for

patients who encounter false-positive test results. The study describes the benefit of

12

educating patients before medical testing begins. Other studies describe the benefits of
including family members in this type of intervention.

Northouse, Dorrin, & Charron-Moore (1995) report on the interrelationship
between patient and spousal adjustment to recurrent breast cancer. Recurrent breast
cancer is defined as one or more new primary breast lesions. Northouse et al.’s (1995)
research is based on findings that indicate both patients and family members experience
excessive stress during the recurrent phase of cancer. The study identifies social support
as a key factor affecting the adjustment of women and their partners to recurrent breast
cancer and identifies a bi-directional relationship in their ability to adjust. “Each partner,
in some way, influences the adjustment of the other” (p. 76). Educational intervention
should be designed to reduce anxiety for not only the patient, but for other family
members as well. Results of Northouse et al.’s study (1995) highlights the need for
family-focused intervention in the treatment of disease.

Northouse, Mood, Templin, Mellon & George (2000) described the importance of
identifying couples at risk for adjustment problems early in the course of illness. Their
study further described increased adjustment problems and emotional distress for patients
and their families during the first year following surgery for colon cancer. These findings
add additional support for development of planned programs of care that include family
caregivers.

While family-focused intervention offers promise for improved healthcare,
educational interventions should also be “culturally sensitive and appropriate for the

target audience” (Miller & Champion, 1997, p. 41). The design of interventional

13

programs should take into consideration variations between patients and address
individual needs.

Rawl et al.’s study (2002) employed a menu-driven, computer-based nursing
intervention program for clinical assessment, problem identification, selection of
intervention, and measurement of outcome for cancer patients and their families. Patients
were assigned on a random basis to participate in the intervention program or receive
standard health care. The program provided patients and family caregivers with
information on symptom management, disease and treatment, and medical resources, as
well as emotional support and counseling. The information was tailored to specific needs
of the patient and family through the use of a menu-driven program that guided clinical
assessment, problem identification, selection of interventions, and measurement of
outcomes (Rawl et al., 2002, p. 970). Results of the study revealed the benefits of tailored
intervention. Patients who received the experimental intervention reported significantly
less depression than patients in the standard care group.

Educational intervention has progressed over the years from a single-patient focus
to a more collective focus that considers other individuals in the patient’s social support
network. As the scope of educational intervention has increased, the technology that
drives it has also become more advanced. Current trends include multimedia technologies

that raise educational intervention to a new level.

Multimedia Intervention

Existing research demonstrates the effectiveness of various multimedia

technologies in reducing anxiety for women undergoing breast-cancer screening.

14

Research by Street, Van Order, Bramson, and Manning (1998) compared the
effectiveness of interactive multimedia intervention versus brochures in reducing anxiety
and increasing breast cancer knowledge. The study revealed that women who received
educational intervention reported less anxiety about cancer screening regardless of the
method employed (p. 152). However, individuals differed in their preferred method of
intervention, with younger women preferring interactive multimedia methods.

Another study by Champion, Skinner, Menon, et al. (2002) described the benefits
of tailored intervention for increasing mammography usage. The study tested three types
of interventions: a mailed letter containing information tailored to breast cancer concerns
and beliefs, a phone call delivering the same information and a combination of the mailed
and phoned information. Results of the study showed that all three groups of women who
received intervention demonstrated improved compliance for mammography usage
compared to women who received just the usual care. Women who received both forms
of intervention demonstrated the highest improvement in their levels of compliance for
mammography usage.

Devine and Westlake (1995) reported similar findings. They conducted a meta-
analysis of 116 intervention studies that evaluated the effectiveness of various types of
psychoeducational care in reducing anxiety and depression for adults with cancer. Results
showed that cancer patients who received psychoeducational care experienced less
anxiety and depression compared to patients who received standard medical care.
However, the meta-analysis did not adequately differentiate between the different types
of psychoeducational care. “Additional research is needed to evaluate the relative

effectiveness of different types of psychoeducational care” (p.1369). Devine and

15

Westlake’s study calls attention to the need for additional research which could provide a
better understanding of the interplay between media, message, and audience
characteristics in promoting healthcare objectives.

In summary, trends in healthcare continue to change as new technology develops
and the focus on treatment planning broadens to include the patient’s social support
network. Although quality care directed toward the individual patient is valuable, the
benefits of tailored and multimedia intervention directed toward the patient, family
members, and other caregivers are now apparent. Information gained through research
underscores the value of early identification of anxiety and adjustment problems and
reinforces the value of considering the patient’s social support network in the treatment
plan. As research continues to build on this foundation of knowledge, patients and their
families, along with other caregivers will realize greater success in adjustment to disease

and improved treatment outcomes.

16

CHAPTER 3

METHODOLOGY

Participants

One-hundred-thirty-three women who were scheduled for breast MRI exams at 3
Midwest clinic were asked to participate in this study. The researcher, or study
representative, explained the study to the women and requested consent for participation
and release of medical records. Of those women, 128 (96.2%) participated throughout the
study, three declined to participate and one withdrew from the study after completing the
survey and questionnaires. Demographics for participants included 122 Caucasians
(95.3%), two African Americans (1.6%), one Asian (.8%) and three Hispanics (2.3%).
The women ranged in age from 32 years to 86 years with a mean age of 51 years.

The marital status of participants included five “single-never married” (3.9%),
seven “single, living with a significant other” (5.5%), 81 “married” (63.3%), three
“married but separated” (2.3%), 17 “divorced” (13.3%), six “remarried” (4.7%) and nine
“widowed” (7%).The highest level of education achieved by the participants included one
“General Education Development” (GED) (.8%), 24 “high school” (18.9%), 25 “attended
college” (19.7%), 25 “college two-year degree” (19.7%), 21 “college four-year degree”
(16.5%), 24 “graduate/professional degree” (18.9%) and seven “other” (5.5%). Eighty-
eight (68.8%) of the women who participated were employed at the time of the study and
21 (19.4%) were retired. Additional demographics for the study are recorded in Appendix

A and descriptive statistics are recorded in Table 2 and Table 3 (pages 32 and 33).

17

Design

A single—site clinical, survey-based study was conducted using an experimental
design with an educational intervention tool. The major dependent variable for this
research was level of state anxiety. Independent variables included the standard verbal
explanation (See Table 1 on p. 23) and an educational intervention tool (See Appendix
J). Based on the literature review for this study, along with additional research findings,
the following moderator variables were included: perceived level of social support,
marital status, previous history of breast cancer, claustrophobia (Murphy & Brunberg,
1997, p. 51) and previous knowledge about MRI (Gollub & Shellock, 2001 , p. 198). The
latter describes participants who previously underwent an MRI exam or whose healthcare
provider explained the procedure to them before they arrived for their exam. Control
variables age, race and gender were also included in this study based on the literature
review.

The study consisted of three experimental groups of subjects. Subjects in Group A
received information about breast MRI through standard verbal explanation. Subjects in
Group B received information about breast MRI by viewing the educational intervention
tool, and subjects in Group C received information by viewing the educational
intervention tool and then receiving the standard verbal explanation afterwards. This
three-group study design ensured correct interpretation of results in case the standard
verbal explanation, rather than the educational intervention tool, was responsible for
changes in state-anxiety levels. The conceptual model for the intervention is depicted in

Figure 2 on the next page.

18

 

Group A
Standard
Explanation

 

 

 

 

Input Variable Gm“? B Outcome Variable
Pre-Intervention Level Educational Post-Intervention
of State Anxiety Interventional T00] Level of State Anxiety

 

 

 

 

 

 

 

 

 

Group C
Standard
Explanation and
Educational
Interventional Tool

 

 

 

Control: gender, race, & age

Figure 2. Intervention model

Procedure

The researcher approached women who were scheduled for breast MRI exams at
a Midwest clinic. After explaining the study to the women, the researcher requested their
consent to participate and to allow the release of their medical records for the study.
Women who agreed to participate completed the State Trait Anxiety Inventory (STAI),
the Short Form Social Support Questionnaire (SSQ-6), and a demographic survey. Each
participant was randomly assigned to one of three intervention groups described in the
design section based on a random number table generated by www.random.org (Haahr,

2004). Participants followed the intervention protocol defined by their group.

19

Conceptual Definitions

This study included several variables that required conceptual definitions in order
to fully understand the relationship between the interventions, the moderator variables,
the control variables, and state anxiety levels. These definitions are provided in the list
that follows.

Dependent variable

State Anxiety. State anxiety is conceptually defined as the “transitory emotional
state or condition of the human organism that is characterized by subjective, consciously-
perceived feelings of tension and apprehension, and heightened autonomic nervous
system activity” (Spielberger et al., 1983, p. 2).

Independent variables

Educational intervention tool. The educational intervention tool is defined as a
computer-based PowerPoint tool that provides information about breast MRI (See
Appendix J). The tool includes 13 informational points that comprise the MRI Standard
Verbal Explanation (See Table l on p. 23).

Standard explanation. The standard explanation is the routine explanation
provided to the respondent about the MRI exam by the researcher or study representative
before the exam begins (See Table 1 on p. 23).

Moderator variables

Perceived social support. The primary moderator variable for this study is
perceived social support (See Appendices C & I). This variable describes the number of
people the respondent can count on for support (on a scale of 1 to 9) in six situations and

the respondent’s overall satisfaction with that network (on a scale of 1 to 6).

20

Additional moderator variables .Additional moderator variables for the study
include marital status, previous knowledge about MRI, claustrophobia, highest level of
education and previous history of breast cancer. Conceptual and operational definitions
for these variables are included in Appendix A.

Control variables.
Control variables for the study include age, race and gender. Conceptual and

operational definitions for these variables are included in Appendix A.

Inclusion Criteria
Inclusion criteria for this study were women, 18 years of age or older who were
scheduled to undergo a breast MRI exam. Additional inclusion criteria were mental

competency and the ability to read and write in the English language.

Exclusion Criteria
Exclusion criteria were women who were less than 18 years of age, or who were
mentally incompetent. Also excluded were women who had previously participated in
this study, women who previously underwent breast MRI, and women who previously

viewed the educational intervention tool.

Development of the Educational Intervention Tool
The objective of the educational intervention tool was to reduce state anxiety in
women who were scheduled for breast MRI procedures. Information used to create the

tool was collected in a professional clinical environment over a period of six months

21

during routine patient interviews. During this time, researchers and study representatives
asked women who were scheduled for a breast MRI to describe factors related to the
exam that made them feel nervous or uneasy. As information was gathered, a pattern of
factors developed. The factors most commonly referenced by these women included: fear
of breast cancer, concern about the IV contrast agent , claustrophobia, concern over the
amount of time that would pass before they would know the results of their exam,
apprehension about the safety of MRI, and concern about their physical position on the
table during the exam. The educational intervention tool was designed to provide
information addressing these concerns, and by doing so, the intervention was expected to
reduce state-anxiety levels. As an added measure to ensure quality of care, the
educational intervention tool also contained the 13 informational points that were
included in the standard verbal explanation. The tool consisted of a computer-based

PowerPoint presentation comprised of 15 slides (See Appendix J).

MRI Standard Verbal Explanation
Standard care for patients who are scheduled to undergo breast MRI includes an
explanation of the MRI procedure before the scan begins. This explanation describes 13

informational points about the exam (see Table l on the next page).

22

Table 1.

Information Included in the Standard Verbal Explanation of MRI

 

10.

11.

12.

13.

MRI uses a strong magnetic field to acquire information for the
images

All non-implanted metal objects must be removed from the patient
prior to the exam

The patient must change into a gown before entering the scan room
A locker is provided to secure valuables

The MRI breast exam involves an intravenous injection of contrast
material that enhances abnormal tissue

The contrast does not impair the patient’s ability to drive or
participate in normal activity

The MRI exam is very loud and, therefore, ear protection and/or
headphones are provided to protect hearing

The patient is positioned on her stomach atop a device known as a
“coil” that acquires information about the breast tissue

The coil is contoured to fit the chest area and minimize discomfort
The patient enters the magnet feet-first for the exam

The bore of the magnet remains Open throughout the procedure
The patient must remain perfectly still during the exam

The technologist can see and hear the patient throughout the exam

 

23

Hypotheses

Clinical research that compares the effectiveness of multimedia interventions in

reducing state-anxiety levels is limited. However, other research suggests that patients

who receive multiple forms of intervention demonstrate the highest improvement in

outcome measurements (Champion et al., 2002). Based on these findings, the primary

alternative hypothesis (H 1 1) being tested by this research is among women undergoing

Breast MRI, there is a relationship between combined verbal and computer-based

educational intervention and the effectiveness of the interventions. The study further

considers the relationship between moderator variables and the efficacy of the

interventions. The conceptual model used to test hypotheses for this study is illustrated in

Figure 3 on the next page. This model addresses the following null hypotheses: and

further considers the following null hypotheses:

H01

Hoz

H03

H04

H05

H06

Among women undergoing Breast MRI, there is no relationship
between combined verbal and computer-based educational
intervention and the effectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between participants ’ perceived levels of social support and the
efiectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between claustrophobia and the eflectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between previous knowledge about MRI and the effectiveness of the

interventions

Among women undergoing Breast MRI, there is no relationship
between marital status and the eflectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between education and the effectiveness of the interventions

24

H07 Among women undergoing Breast MRI, there is no relationship
between previous history of breast cancer and the effectiveness of
the interventions

 

 

 

Trait Anxiety

ll

 

 

 

 

 

 

ti

 

Intervention-Group A
Standard Explanation

 

 

 

 

 

 

Pre-Intervention
Level of State
Anxiety

 

Intervention-Group B
Educational
Intervention Tool

 

 

 

 

 

Intervention-Group C
Standard Explanation
and Educational

Intervention Tool

 

 

 

 

1
Post Intervention
; v Level of State
Anxiety
a n '

 

 

 

 

 

 

 

 

Control Primary Moderator Variable
Variables 0 Perceived Social

0 Age Support
0 Race 0 Number
0 Gender 0 Quality

 

Additional Moderator Variables
0 C laustrophobia
0 Baseline Level of Knowledge of MRI
0 Marital Status
0 Highest Level of Education
0 Previous History of Breast Cancer

 

Figure 3. Conceptual model of intervention with test variables

In order to better understand and predict characteristics that are associated with

elevated state-anxiety levels, the relationship between the study variables and pre-

intervention state-anxiety levels was also examined during data analysis. Chapter Four

25

 

includes a summary of the relationship between pre-intervention state-anxiety levels and

independent variables, moderator variables and control variables

Measurement

Variables for this study were measured with three routine patient history forms: a
single survey and two questionnaires. A complete list of operational definitions for
variables is included in Appendix A.

The variables state anxiety and trait anxiety were measured with the State Trait
Anxiety Inventory (STAI) (See Appendix H). The STAI is a 40-item, 4-point Likert-type
questionnaire (Spielberger, Gorsuch, Lushene, Vagg & Jacobs, 1983). The Inventory
includes twenty questions that measure the participant’s transitory emotional state (state
anxiety) and twenty questions that measure “relatively stable individual differences in
anxiety proneness. . (trait anxiety) (Spielberger et al., 1983, p.2).

State anxiety is based on the assumption that individuals experience differential
levels of state anxiety as a function of their level of trait anxiety depending on conditions
surrounding the stimulus. The Trait Anxiety Inventory establishes a baseline for
comparing state anxiety levels.

Test-retest correlations for the state anxiety scale range from .16 to .62 and
correlations for the trait anxiety scale range from .65 to .86. Test - retest reliability on the
State Anxiety Inventory is expected to be low since the measures on this scale are
thought to reflect transient situational factors that are present at the time of testing.
Internal consistency for both scales is high. The median Chronbach alpha coefficient for

the state anxiety scale is 0.92 and for the trait anxiety scale, the median alpha is 0.90

26

(Spielberger et al., 1983, p. 29). Similarly, Chronbach’s alpha coefficients for the
research presented in this study were 0.94 for the pre-intervention state anxiety scale,
0.95 for the post-intervention state anxiety scale and 0.93 for the trait anxiety scale.

Correlations between the state-anxiety scale and trait anxiety scale are reported by
Spielberger et al. as 0.65 to 0.75 for males and 0.59 to 0.70 for females. Correlations tend
to be higher in situations that pose a threat to self-esteem or when personal adequacy is
evaluated, and scores tend to be lower in situations characterized by physical danger
(Spielberger et al., p. 31). For the research presented in this study, correlation between
trait anxiety and pre—intervention state anxiety was 0.59 and correlation between trait
anxiety and post-intervention state anxiety was 0.57.

The State Trait anxiety inventory has been used extensively for assessing clinical
anxiety in medical, surgical psychosomatic and psychiatric patients (Spielberger et al.,
1983, p. 4). The scale is cited in more than 2,000 research studies “including research in
medicine, dentistry, education, psychology and other social sciences” (Spielberger et al.,
1983,p.5)

The moderator variable, perceived social support was measured with the Short
Form Social Support Questionnaire (SSQ—6) (See Appendix I). The SSQ-6 provides
information about people the respondent can count on for support in six situations.
Participants in this study described their network size, social support number, based on a
scale of 1 to 9 and satisfaction with the network, social support quality, based on a scale
of 1 to 6. The scores in each category were then added together and divided by nine (for
social support number) and six (for social support quality) to achieve overall average

ratings for each dimension of perceived social support.

27

With this instrument, higher scores indicate higher numbers of supporters and
higher satisfaction with that support. Both dimensions of social support have good
internal reliability ranging from 0.90 to 0.93 (Sarason, Levine, Basham & Sarason, 1987).
Alpha coefficients for the current study were 0.94 for social support number and 0.55 for
social support quality. However, with Question 5, who can you really count on? omitted
from the analysis, alpha coefficients were 0.92 for social support number and 0.98 for
social support quality. Internal reliability for social support is discussed in greater detail
in Chapter Four.

The majority of the remaining moderator variables for this study were self-
reported by respondents on the demographic survey (See Appendix D). These include
claustrophobia, marital status, previous knowledge about MRI and highest level of
education. Information about age, gender, race and previous history of breast cancer was
collected by the healthcare personnel during the routine intake interview and recorded on
Mammography Medical History Forms (See Appendices E & G). Conceptual and
operational definitions for these variables are included in Appendix A.

The educational intervention tool was designed to reduce state anxiety for women
undergoing breast MRI. The success of the tool was determined by calculating the
difference between pre-intervention vs. post-intervention state anxiety scores. Greater
changes in pre-intervention vs. post-intervention state-anxiety scores indicated greater

success of the tool.

28

Coding

In preparation for data analysis, data for the study were coded according to the
scales of measurement used during data acquisition. Variables measured at the nominal
level were coded with dummy variables indicating whether the variables were present (0
= no, 1 = yes). Variables measured at this level included claustrophobia, previous history
of breast cancer, and previous knowledge about MRI (measured as either previous MRI
or MRI explained on the demographic survey [See Appendix D]). The categorical
variables race, marital status and highest level of education were also measured at the
nominal level. However, these variables were first categorized with unique codes for each
categorical level and annotated with unique value labels and then recoded with dummy
variables for analysis.

Variables measured at the interval level were coded with the values reported by
the respondents during data acquisition. Variables measured at this level included state
anxiety, trait anxiety, age and perceived social support (reported as either social support

number or social support quality).

Data Analysis
Data analysis for the study was divided into three stages. The first stage consisted
of univariate analysis. Data for each variable were analyzed with frequency tables and
then graphically plotted using histograms (for interval data) and bar charts (for
categorical data) to assess for shape, frequency distribution, central tendency, and

variability. Data were also analyzed for skewness, kurtosis, outliers, gaps and peaks. In

29

addition, interval data were tested for normal distribution using the Shapiro-Wilk
normality test

The next stage of data analysis consisted of bivariate analysis. During this stage,
analyses were performed to examine relationships between test variables. For interval
data, Kendall’s tau_b was performed to test for significant correlations and for
categorical data, the Kruskall Wallis One-way ANOVA test was used to test for
significant differences between means.

Research hypotheses were tested using One—Way ANOVA, repeated-measures
ANOVA and Kendall’s tau_b. A probability of p50.05 was established as the required
value to reject null hypotheses.

The final stage of data analysis consisted of multivariate analysis using ordinary
least squares regression. During this stage of analysis, a model was created to explain the

variance of post-intervention anxiety levels between groups (See Table 17 on page 59).

30

CHAPTER 4

RESULTS

The primary purpose of this study was to compare the effectiveness of three

interventions in reducing state anxiety levels. The research was based on the H01

hypothesis among women undergoing Breast MRI, there is no relationship between

combined verbal and computer-based educational intervention and state-anxiety levels.

Additional hypotheses were also included in the smdy:

H02

H03

H06

H07

Among women undergoing Breast MRI, there is no relationship
between participants ’ perceived levels of social support and the
efiectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between claustrophobia and the eflectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between previous knowledge about MRI and the effectiveness of the
interventions

Among women undergoing Breast MRI, there is no relationship
between marital status and the eflectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between education and the effectiveness of the interventions

Among women undergoing Breast MRI, there is no relationship
between previous history of breast cancer and the eflectiveness of
the interventions

To ensure consistency in the study, participants were randomly assigned to one of

three groups with approximately equal numbers of participants in each (N = 43 for Group

A and Group C, and N = 42 for Group B). Descriptive statistics for variables are included

in Tables 2 and 3 on the next two pages.

31

Univariate Analysis

statistical analysis software (SPSS Inc, Chicago, IL). The first stage consisted of

Analysis of data for this study was conducted using Mac OS X version 11.0 SPSS

univariate analysis with descriptive statistics. Frequency distributions and percentages for

categorical variables were described using cross tabulations (See Table 2 below).

Categorical variables in this analysis included marital status, race, education, previous

history of breast cancer, previous knowledge about MRI and claustrophobia. In addition,

bar charts were generated to graphically display and analyze frequency counts for these

variables.

Table 2

Descriptive Statistics for Categorical Data: Group A, Group B and Group C

 

 

 

 

 

Category A B C Total %A %B %C
Race Caucasian 39 41 42 122 32.00 33.60 34.40
African American 1 0 1 2 A 50.00 0 50.00
Asian 1 0 0 1 100.00 0
Hispanic 2 1 0 3 66.70 33.30
Marital Status Single—Never Manied l 3 1 5 20.00 60.00 20.00
Single—Living with 1 1 5 7 14.30 14.30 71.40
Significant Other
Manied 29 22 30 81 35.80 27.20 37.00
Married/Separated 1 1 1 3 33.30 33.30 33.30
Divorced 5 10 2 17 29.40 58.80 11.80
Remarried 3 2 1 50.00 33.30 16.70
Widowed 3 3 33.30 33.30 33.30
Highest Level - GED 1 0 0 1 100.00 0 0
Education
High School 8 9 7 24 33.30 37.50 29.20

32

 

 

 

Attended College 9 9 7 25 36.00 36.00 28.00
College 2—Year Degree 9 5 11 25 36.00 20.00 44.00
College 4-Year Degree 6 7 8 21 28.60 33.30 38.10
Graduate/Prof. Degree 6 10 8 24 25.00 41.70 33.30
Other 4 1 2 7 57.10 14.30 28.60
Previous History - No 26 27 15 78 33.30 34.60 32.10
BreaS‘Cance’ Yes 17 15 18 50 34.00 30.00 36.00
Previous No 9 16 12 37 24.30 43.20 32.40
gift/1% Yes 34 26 31 91 37.40 28.60 34.10
Claustro phobia No 30 25 24 79 38.00 31.60 30.40
Yes 13 17 19 49 26.50 34.70 38.80

 

 

Descriptive statistics for continuous variables were calculated and reported as

mean, standard deviation, minimum value and maximum value (See Table 3 below).

Continuous variables for the study included pre-intervention and post-intervention state

anxiety, pre/post intervention % change, trait anxiety, social support number, social

support quality and age.

Table 3.

Descriptive Statistics for Interval Data: Group A, Group B and Group C

 

 

 

Groups N Min. Max. Mean Std.
A B C Dev.
A Pre State Anxiety 43 20 80 38.74 15.39
Trait Anxiety 43 20 73 37.05 12.67
Post-Intervention State Anxiety 43 20 74 36.00 14.15
Pre/Post Intervention % Change 43 -0.46 0.41 -0.06 0.15
Social Support Number 43 0.83 9.00 4.53 2.67
Social Support Quality 43 1.00 6.00 5.17 1.38
Age 43 35 86 50.51 10.55

 

33

 

 

Pre State Anxiety 42 20 70 39.14 11.76
Trait Anxiety 42 20 52 33.37 7.25
Post-Intervention State Anxiety 42 21 67 36.57 11.28
Pre/Post Intervention % Change 42 -0.37 0.32 -0.05 0.15
Social Support Number 42 1.17 9.00 4.15 1.98
Social Support Quality 42 1.00 6.00 5.20 1.47
Age 42 32 78 51.62 1 1.25
Pre State Anxiety 43 20 60 37.54 12.00
Trait Anxiety 43 20 52 33.93 8.28
Post-Intervention State Anxiety 43 20 58 35.14 11.77
Pre/Post Intervention % Change 43 -0.31 0.29 -0.06 0.13
Social Support Number 43 0.67 9.00 4.36 2.43
Social Support Quality 43 1.00 6.00 5.03 1.71
Age 43 32 77 50.98 10.21

 

 

Norrnalcy of distribution for continuous variables was assessed using the Shapiro-
Wilk test and each dataset was analyzed for kurtosis and skewness. Data for pre/pos-
intervention % change passed the normality test at the 95% confidence interval.
However, data for pre-intervention state anxiety, post-intervention state-anxiety, trait
anxiety, social support number, social support quality, and age failed the normality test at
this confidence interval. These data were further analyzed with box and whisker plots to
identify outliers. Questionable values were checked against responses from original
surveys and questionnaires for accuracy. Data sets that failed tests for normality or
produced skewness or kurtosis values S -1 or 2 l were transformed using the natural log
to improve symmetry.

Two variables, trait anxiety and social support quality, produced data sets with

positive kurtosis values 2 1. In addition, social support quality produced a negative

34

skewness value 5 -1 and trait anxiety produced a positive skewness value 2 1. While
natural log transformation of trait-anxiety data effectively reduced skewness and kurtosis,
transformation of social support quality data was not successful in compensating for the
skew or kurtos. Analysis of data for social support quality indicated that a high number of
respondents (111 out of 128) reported average scores 2 5. The resulting bias rendered the
data invalid for use as a moderator variable for this study. Data from social support
quality were omitted from further analysis based on these results. Furthermore, the H02
hypothesis which reads, among women undergoing Breast MRI, there is no relationship
between participants ’ perceived levels of social support and the efiectiveness of the
interventions, was modified to reflect exclusion of social support quality. The new H02
hypothesis used for further analyses was stated, among women undergoing Breast MRI,
there is no relationship between patients ’ social support number and the effectiveness of
the interventions.

Following log transformation, data sets for trait anxiety and age passed normality
tests while data sets for pre-intervention state anxiety, post-intervention state-anxiety,
social support number, and social support quality failed to achieve normalcy. In order to
analyze data comprised of both normal and non-normal distribution, the Kruskal-Wallis
One-way Analysis of Variance (KW One-Way ANOVA) test was used to compare means
within Group A, Group B and Group C for these variables. P values of less than 0.05
were considered significant.

Sample Characteristics
Table 3 (on pages 33 - 34) provides descriptive statistics for continuous variables

in the study. Pre-intervention state-anxiety values ranged from 20 to 80 (M = 38.47, SD =

35

13.08), post-intervention state anxiety values ranged from 20 to 74 (M = 35.90, SD =
12.39) and trait anxiety values ranged from 20 to 73 (M = 34.79, SD = 9.76). Further
analysis using a KW One-way ANOVA revealed no significant difference in the means

for these variables between Group A, Group B and Group C (See Table 4 below).

Table 4.

Comparison of Continuous Variables between Group A, Group B and Group C using KW
One-way ANOVA

 

 

 

 

Group A Group B Group C
Variable N Mean N Mean N Mean Chi df p
Rank Rank Rank Square
Pre- 43 62.99 42 67.30 43 63.28 0.36 2 0.84
Intervention
State Anxiety
Post- 43 62.62 42 68.04 43 62.93 0.57 2 0.75
Intervention
State Anxiety

Trait Anxiety 43 69.58 42 60.62 43 63.21 1.32 2 0.52

Social Support 43 65.91 42 62.71 43 64.84 0.16 2 0.92
Number

Social Support 43 62.71 42 65.77 43 65.05 0.19 2 0.91
Quality

Age 43 62.19 42 66.57 43 64.79 0.30 2 0.86

 

 

36

Descriptive Statistics for Group A

Additional descriptive statistics were computed to examine the distribution of
variables within Group A, Group B and Group C and determine demographic
characteristics for each group. Pre-intervention state-anxiety scores for Group A ranged
from 20 to 80 (M=38.74, SD = 15 .39) and post-intervention scores ranged from 20 to 74
(M = 36.00, SD = 14.15) indicating a change of -2.74 (-7.1%). Trait anxiety scores for
this group ranged from 20 to 73 (M=37.05, SD = 12.67). In addition, 91% of Group A
participants were Caucasian, 67.4% were married and 79.1% had some level of college
education. The average social support number for the group was 4.53. Claustrophobic
tendencies were reported by 13 respondents (30.2%) and 34 (79.1 %) reported having
previous knowledge about MRI. In addition, 39.6% of Group A respondents reported a
previous history of breast cancer.
Descriptive Statistics for Group B

Group B pre-intervention state-anxiety scores ranged from 20 to 70 (M = 39.14,
SD = 11.76) and post intervention scores ranged from 21 to 67 (M = 36.57, SD = 11.28)
which indicated a change of —2.57 (-6.57%). Trait anxiety scores for this group ranged
from 20 to 52 (M = 33.37, SD = 7.25). In addition, 41 (97.6%) participants were
Caucasian and 22 (52.4%) were married. The ages of Group B participants ranged from
32 to 78 years (M = 51.62, SD=11.25) and their average social support number was 4.15.
Additionally, 33 (78.57%) participants reported some level of college education and 17
(40.5%) indicated claustrophobic tendencies. Furthermore, 22 (61.90%) participants in
Group B reported having previous knowledge about MRI and 15 (35.7%) reported a

previous history of breast cancer.

37

Descriptive Statistics for Group C

Pre-intervention state-anxiety scores for Group C ranged from 20 to 60 (M =
37.54, SD = 12.00) and post-intervention scores ranged from 20 to 58 (M = 35.14, SD =
11.77). Trait anxiety scores for this group ranged from 20 to 52 (M = 33.93, SD = 8.28).
Participants’ ages in Group C ranged from 32 to 77 years (M = 50.98, SD = 10.21). In
addition, 42 (97.7%) respondents in this group were Caucasian, 30 (69.77%) were
married and 36 (83.4%) reported some level of college education. The average social
support number for Group C respondents was 4.36. Furthermore, 19 (44.2%) participants
in this group reported claustrophobic tendencies and 31 (72.10%) reported previous
knowledge about MRI.

Bi variate Analysis

Bivariate analysis was conducted to test for significant relationships between
variables in the study. Specifically, analyses were performed using Kendall’s tau_b
correlation and Kruskal-Wallis One-way Analysis of Variance (KW ANOVA) to
examine the relationships between state anxiety and trait anxiety and between pre-
intervention state anxiety and the other test variables. Additional analyses were
performed using Repeated-Measures Analysis of Variance (Repeated-Measures
ANOVA), One-way Analysis of Variance (One-way ANOVA), Two-way Analysis of
Variance (Two-way ANOVA), Analysis of covariance (ANCOVA) and Two-way
Analysis of covariance (Two-way ANCOVA) to test research hypotheses H01 through

H013.

38

Correlates for State Anxiety and Trait Anxiety

State anxiety is based on the assumption that individuals experience different
levels of state anxiety as a function of their level of trait anxiety. This relationship
depends on conditions surrounding the stimulus such that individuals with high trait-
anxiety scores more often exhibit high state anxiety scores because “they interpret a
wider range of situations as dangerous or threatening” (Spielberger, 1983, p. 3).
Kendall’s tau-b (nonparametric) rank correlations were performed to examine
relationships between pre-intervention state anxiety, post-intervention state anxiety and
trait anxiety for this study. Table 5 presents findings from these analyses.

Results of the analyses show significant positive correlation between pre-
intervention state anxiety and post-intervention state anxiety. This finding indicates that
individuals who experienced higher levels of state anxiety before intervention in response
to their impending breast MRI exam also experienced proportionally higher levels of
state anxiety after the intervention compared to individuals who experienced lower levels
of state anxiety in response to their impending exams. This means that participants who
were more apprehensive, tense, nervous, and wonied when they arrived for their breast
MRI exam continued to be proportionally more apprehensive, tense, nervous and worried
after intervention compared to individuals who were less apprehensive, tense, nervous
and worried when they arrived for their exam.

Results also indicate significant positive correlation between pre-intervention
state anxiety and trait anxiety. In other words, individuals who reported general

tendencies toward higher levels of trait anxiety also experienced higher levels of state

39

anxiety in response to their impending breast MRI compared to individuals who reported
general tendencies toward lower trait anxiety.

Table 5
Correlation Between State Anxiety and Trait Anxiety Using Kendall’s Tau_b (N = 128)

 

 

 

 

Correlations Pre St-Anx. Post Trait
State-Anx. Anx.
Kendall’s
tau_b Pre State Anx. Corr. Coeff. 1.00 0.74** 0.45**
Sig. (2-tailed) . 0.00 0.00
Post State Anx. Corr. Coeff. 0.74** 1.00 0.48**
Sig. (2-tailed) 0.00 . 0.00
Trait Anx. Corr. Coeff. 0.45** 0.48** 1.00
Sig. (2-tailed) 0.00 0.00
** Correlation is significant at the .01 level (2-tailed).
* Correlation is significant at the .05 level (2-tailed).

 

 

Correlates and Comparisons for State Anxiety, Trait Anxiety, and Other Test Variables
When assessing the effectiveness of anxiety-reducing interventions, a basic
understanding of the relationship between pre-intervention state-anxiety levels, trait-
anxiety levels, and other demographic characteristics of the sample is helpful. Additional
bivariate analyses were performed to describe relationships between pre-intervention
state-anxiety levels and the following test variables: age, race, social support number,
claustrophobia, previous knowledge about MRI, and highest level of education and
previous history of breast cancer. Correlations were also computed to describe the

relationship between trait anxiety levels and these test variables.

40

Correlates for Other Continuous Variables

Kendall’s tau_b (non-parametric) correlations were performed to describe
relationships between pre-intervention state anxiety, trait anxiety and the variables
measured at the interval level, age and social support number. Results from these
analyses are presented in Table 6.

In addition to the relationship between pre-intervention state anxiety and trait
anxiety previously described, Kendall’s tau-b correlations also showed significant
negative correlation between social support number and trait anxiety. This means that
participants with higher social support numbers reported lower overall general tendencies
toward anxiety. In other words, participants who indicated that they could count on more
people to provide support when they needed it tended to experience less anxiety.

Table 6
Correlations Between Pre-Intervention State Anxiety, Trait Anxiety, and Variables

Measured at the Interval Level Using Kendall ’s Tau b (N = 128)

 

 

Correlations Pre State Trait SS Age
Anxiety. Anxiety Num

 

Kendall’s tau_b Pre St—Anx. Corr. Coeff. 1.00 0.45** -0.09 -0.04
Sig. (2-tailed) . 0.00 0.13 0.54
Trait Anx. Corr. Coeff. 0.45** 1.00 -0.13* -0.04
Sig. (2-tailed) 0.00 . 0.04 0.52
SS Num Corr. Coeff. -0.09 -0.13* 1.00 -0.07
Sig. (2-tailed) 0.1 3 0.04 . 0.27
Age Corr. Coeff. -0.05 -0.04 -0. 10 1 .00
Sig. (2-tailed) 0.57 0.52 0.26

** Correlation is significant at the .01 level (2-tailed).

* Correlation is significant at the .05 level (2-tai1ed).

 

 

41

Comparisons for Categorical Variables

Additional analyses were performed using a KW One-way ANOVA to examine
relationships between pre-intervention state anxiety and trait anxiety and the remaining
categorical variables race, claustrophobia, previous knowledge about MRI, marital status,
highest level of education, and previous history of breast cancer. Table 7 and Table 8
summarize the results from these analyses.

Findings show a significant difference between mean pre-intervention state-
anxiety scores for participants who were claustrophobia compared to mean pre-
intervention state-anxiety scores for participants who were not claustrophobic. This
means that participants who reported claustrophobic tendencies were more anxious when
they arrived for their Breast MRI exams compared to participants who were not
claustrophobic.

In addition, results also suggest a difference in mean pre-intervention state-
anxiety scores for participants with a previous history of breast cancer compared to
corresponding scores for participants without a previous history of breast cancer (X2 =
2.84, p = 0.09). Although the relationship did not reach the .05 level of significance,
participants who experienced breast cancer in the past tended to be more anxious when
they arrived for their breast MRI exam compared to participants with no previous history
of breast cancer.

Results from analyses that compared trait anxiety and other categorical variables
reveal no significant relationships at the S 0.05 level. However, research findings do
suggest a difference in mean trait-anxiety scores for participants who were claustrophobic

compared to mean trait—anxiety scores for participants who were not claustrophobic.

42

Participants who were claustrophobic tended to be more generally prone to higher levels

of anxiety (x2 = 3.15, p = 0.08).

Table 7.

Comparison of Pre-Intervention State Anxiety Scores and Categorical Variables Using

KW One- Way ANOVA

 

 

Pre-Intervention State Anxiety

 

 

 

 

Variable Category N Mean Chi df p
Rank Square
Marital Status 8.03 6 0.23
Single Never Married 5 47.50
Living with Sig. Other 7 59.71
Married 81 65.85
Married but Separated 3 50.83
Divorced 17 65.79
Remarried 6 37.00
Widowed 9 86.00
Total 128
Race 5.73 3 0.13
Caucasian 122 63.61
African American 2 81.25
Asian 1 17.00
Hispanic 3 105. 17
Total 128
Highest Level of 5.98 6 0.43
Education
Grade School or Less 0
GED 1 117.00
High School 24 71.31
Attended College 25 70.64
College 2-Year Degree 25 62.48

43

 

 

 

 

 

 

 

 

 

College 4-Year Degree 21 64.55
Graduate/Professional 25 53.54
Other 7 57.93
Total 128
Claustrophobia 11.29 1 .001
No 79 55.83
Yes 49 78.48
Total 128
Previous Knowledge 0.11 1 0.74
about MRI
No 37 66.19
Yes 91 63.81
128
Previous History of 2.84 1 0.09
Breast Cancer
No 78 60.08
Yes 50 71.40
128
Table 8.
Comparison of Trait Anxiety Scores and Categorical Variables Using KW One-Way
ANOVA
Pre-Intervention State Anxiety
Variable Category N Mean Chi (if p
Rank Sguare
Marital Status 6.35 6 0.39
Single Never Married 5 83.20
Living with Sig. Other 7 57.43
Married 81 63.27
Manied but Separated 3 74.33

 

 

 

 

Divorced 17 68.26
Remarried 6 37.75
Widowed 9 78.17
Total 128
Race 4.09 3 0.25
Caucasian 122 63.73
African American 2 68.75
Asian 1 33.00
Hispanic 3 103.33
Total 128
Highest Level of 6.59 6 0.36
Education
Grade School or Less 0
GED 1 108.50
High School 24 76.31
Attended College 25 69.44
College 2-Year Degree 25 61.90
College 4-Year Degree 21 58.76
Graduate/Professional 25 57.10
Other 7 53.00
Total 128
Claustrophobia 3.15 1 0.08
No 79 59.92
Yes 49 71.88
Total 128
Previous Knowledge 0.38 1 0.54
about MRI
No 37 61.35
Yes '91 65.78
128

 

45

 

Previous History of 0.02 1 0.88
Breast Cancer

No 78 64.10
Yes 50 65.13
128

 

 

In summary, results of Kendall’s tau_b (nonparametric) correlations and the KW
One-way ANOVA test show several significant relationships between pre-intervention
state anxiety, trait anxiety, and other test variables. Pre-intervention state anxiety
positively related to trait anxiety and post-intervention state anxiety at a significant level.

Furthermore, findings show a significant difference in mean pre-intervention
state-anxiety scores for claustrophobic participants compared to corresponding scores for
non-claustrophobic participants indicating that claustrophobic participants were more
anxious at the time of their breast MRI exams. In addition, although not at a significant
level, results further suggest that participants who reported a previous history of breast
cancer tended to experience higher levels of state anxiety when they arrived for their
breast exams compared to participants who reported no history of breast cancer.

Finally, analysis for trait-anxiety shows significant negative correlation between
social support numbers and trait anxiety scores meaning participants with more
individuals in their social support networks reported overall lower tendencies toward
anxiety compared to participants with fewer individuals in their social support networks.
Additional analysis also suggests that participants who were claustrophobic tended
toward higher levels of trait anxiety compared to participants who were not

claustrophobic, but the relationship did not reach a level of significance.

Research Hypotheses

Primary Hypothesis

The H01 null hypothesis for this study states, among women undergoing Breast
MRI, there is no relationship between combined verbal and computer-based educational
intervention and state-anxiety levels, was tested using a One-way Analysis of Variance
(ANOVA). In preparation for this comparison, mean post-intervention state-anxiety
scores were subtracted from mean pre-intervention state-anxiety scores for each
participant and the differences between the two sets of scores were converted to
percentages. Mean percentages for Group A, Group B and Group C were then compared
using a One-way ANOVA to test for significant differences in state anxiety change
between the three groups. Table 9 presents the results of this analysis. Findings indicate
no significant difference in mean state-anxiety change scores between Group A, Group B
and Group C. Therefore, the null hypothesis is not rejected for this study.

Table 9

Comparison of Interventions Between Groups A, B and C using a One-way ANOVA

 

 

Sum of Squares df Mean Square F Sig.

 

 

Between Groups .001 2 .000 0.02 0.99
Within Groups 2.58 125 .021
Total 2.58 127

 

 

df indicates degrees of freedom

In order to better understand the effectiveness of interventions, further analyses
were performed to examine relationships between the interventions and state-anxiety

levels within each group. The sample data set was split into Groups A, B and C prior to

47

analysis to enable comparison between subjects within each group. A Repeated-Measures
(3 x 2) ANOVA was conducted on the log-transformed data for pre-intervention state
anxiety and post-intervention state anxiety to examine this relationship. Table 10 presents
the results of this analysis.

Findings show a significant difference in mean pre-intervention state-anxiety
scores compared to mean post-intervention state-anxiety scores within Group A, Group B
and Group C. The profile plot presented in Figure 4 shows decreased state-anxiety scores
following intervention within all three groups with no interaction effect between Group
A, Group B and Group C.

Table 10.
Analysis of the Efi‘ectiveness of Interventions within Group A, Group B and Group C
using a 3 x 2 Repeated—measures ANOVA

 

 

Tests of Within-Subjects Contrasts

 

Measure: GROUPS

 

 

 

 

Group A B C Source Anxiety Type III df Mean F Sig.
Sum of Square
Squares
A Anxiety Linear 0.02 1 0.02 7.71 0.008
Anxiety * Group Linear 0.00 0
Error( Anxiety) Linear 0.1 1 42 0.00
B Anxiety Linear 0.02 1 0.02 7.59 0.009
Anxiety * Group Linear 0.00 0
Error(Anxiety) Linear 0.10 41 0.00
C Anxiety Linear 0.02 1 0.02 11.07 0.002
Anxiety* Group Linear 0.00 0
Error(Anxiety) Linear 0.07 42 0.00

 

 

48

Estimated Marginal Means of GROUPS

 

 

 

 

ANXEEII'Y

M

Group AB C

Figure 4. Profile plot comparing pre-interventionl vs. post-intervention2 state-anxiety

change for Group A, Group B and Group C

Secondary Hypotheses

In order to better understand relationships between moderator variables, control

variables, and the efficacy of interventions, several additional hypotheses were tested in

this study. Hypotheses H02 through H07 examined relationships between perceived levels

of social support, claustrophobia, previous knowledge about MRI, marital status, highest

level of education, and previous history of breast cancer while controlling for variables

age, race and gender.

 

' & 2 analysis used transformed log for these variables

49

Since only women were included in this study, as outlined in the inclusion
criteria, further analyses will assume control for gender. In addition, based on descriptive
statistics in Table 2, the study was comprised of 122 Caucasians, two African Americans,
one Asian and three Hispanic participants. The large ratio of Caucasians to African
Americans, Asians and Hispanics precludes the use of race as a moderator variable for
this study. Therefore, further analyses will be conducted using age as the single control
variable.

H02 hypothesis. The second hypothesis for this study was, among women
undergoing Breast MRI, there is no relationship between patients’ social support
numbers and the efiectiveness of interventions. This hypothesis was tested using a One-
way Analysis of Covariance (One-way ANCOVA).This analysis used social support
number as the moderator variable and age as a control variable. Results presented in
Table 11 show no significant difference in mean pre/post intervention % change between
Groups A, B or C.

In this analysis, social support number, or age or the combination of social
support number and age did not significantly change the relationship between the
interventions and state-anxiety levels. There were no significant differences between the

three interventions in effectiveness.

50

Table 11.

Analysis of Social Support Number and Efi‘ectiveness of Interventions Using a One-Way

ANCOVA

 

 

Tests of Between-Subjects Efiects

 

Dependent Variable: Pre/Post Intervention % Chang

 

 

 

Source Type III df Mean F Sig.
Sum of Square
Squares
Corrected Model 0.13 6 0.02 1.05 0.40
Intercept 0.02 1 0.02 1.18 0.28
Group 0.07 2 0.03 1.60 0.21
Age 0.01 1 0.01 0.44 0.51
Social Supp Num 0.08 l 0.08 3.77 0.06
Group * Social Supp 0.08 2 0.04 1.95 0.15
Num
Error 2.45 121 0.02
Total 2.98 128
Corrected Total 2.58 127

a. . .. R Squared = .050 (Adjusted R

Squared = .003)

 

H03 hypothesis. The third hypothesis for this study was, among women undergoing
Breast MRI, there is no relationship between claustrophobia and the efiectiveness of
interventions. This hypothesis was tested using a Two-way ANCOVA and results are

presented in Table 12. This analysis used claustrophobia as the moderating variable and

age as a control variable.

Findings show no significant difference in mean pre/post intervention % change

scores between Groups A, B and C. In other words, claustrophobia, or age or the

51

combination of claustrophobia and age did not significantly change the relationship
between the interventions and state anxiety levels.

Table 12.
Analysis of Claustrophobia and the Efi‘ectiveness of Interventions Using a Two-way

ANCOVA

 

 

Tests of Between-Subjects [fleas
Dependent Variable: Pre/Post Intervention % Change

 

 

Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 0.11 6 0.02 0.87 0.52
Intercept 0.02 1 0.02 0.76 0.38
Group 0.01 2 0.01 0.26 0.77
Age 0.01 1 0.01 0.41 0.52
Claustro 0.00 1 0.00 0.00 0.95
Group * Claustro 0.10 2 0.05 2.49 0.09
Error 2.47 121 0.02

Total 2.98 128

Corrected Total 2.58 127

 

a. . .R Squared = .041 (Adjusted R Squared = -.006)

 

H04 hypothesis. The fourth hypothesis for the study was among women
undergoing Breast MRI, there is no relationship between previous knowledge about MRI
and the effectiveness of interventions. A Two-way ANCOVA was used to test this
hypothesis. This analysis used previous knowledge about MRI as the moderator variable
and age as a control variable.

Table 13 presents the results showing no significant difference in mean pre/post
intervention % change scores between Groups A, B and C. In other words, previous

knowledge about MRI, or age, or the combination of previous knowledge about MRI and

52

age did not significantly change the relationship between the interventions and state-
anxiety levels.

Table 13.
Analysis of Previous Knowledge about MRI and the Effectiveness of Interventions Using
a Two-way ANCOVA

 

 

Tests of Between-Subjects Effects
Dependent Variable: Pre/Post Intervention % Change

 

Source Type III df Mean F Sig.
Sum of Square
Squares
Corrected Model 0.06 6 0.01 0.50 0.81
Intercept 0.01 1 0.01 0.60 0.44
Group 0.00 2 0.00 0.12 0.89
Age 0.01 1 0.01 0.31 0.58
Basic Know MRI 0.00 1 0.00 0.00 0.95
Group * Basic Know 0.06 2 0.03
MR1 1.38 0.26
Error 2.52 121 0.02
Total 2.98 128
Corrected Total 2.58 127

a..R Squared = .024 (Adjusted R Squared = -.024)

 

H05 hypothesis. The fifth hypothesis for this study, among women undergoing
Breast MRI, there is no relationship between marital status and the effectiveness of
interventions, was also tested using a Two-way ANCOVA. This analysis used marital
status as the moderator variable and age as a control variable.

Table 14 presents the results which show no significant difference in mean

pre/post intervention % change scores between Groups A, B and C. In this analysis,

53

marital status, or age or the combination of marital status and age did not significantly
change the relationship between the interventions and state anxiety levels.

Table 14
Analysis of Marital Status and the Effectiveness of Interventions using a Two-way

ANCOVA

 

 

Tests of Between-Subjects Effects
Dependent Variable: Pre/Post Intervention % Change

 

Source Type III df Mean F Sig.
Sum of Square
Squares
Corrected Model 0.49 21 0.02 1.19 0.28
Intercept 0.02 1 0.02 0.95 0.33
Group 0.07 2 0.03 1.77 0.18
Age 0.02 1 0.02 0.83 0.37
Marital 0.15 6 0.03 1.29 0.27
Group * Marital 0.43 12 0.04 1.83 0.05
Error 2.09 106 0.02
Total 2.98 128
Corrected Total 2.58 127

 

a..R-Squared = .190 (Adjusted R-Squared = .030

 

H06 hypothesis. The sixth hypothesis for this study was among women undergoing
Breast MRI, there is no relationship between highest level of education and the
efiectiveness of interventions. This hypothesis was tested using a Two-way ANCOVA.
This analysis used highest level of education as the moderating variable and age as a
control variable. Findings indicate no significant difference in mean pre/post intervention

% change scores between Groups A, B and C.

54

Table 15 presents the results which show that in this analysis, the highest level of
education, or age or the combination of highest level of education and age did not
significantly change the relationship between the interventions and state anxiety levels.
The relationship between mean scores for the three groups remained about the same.

Table 15
Analysis of Highest Level of Education and the Efiectiveness of Interventions Using a
Two-way ANC OVA

 

 

Tests of Between-Subjects Effects

 

Dependent Variable: Pre/Post Intervention % Change

 

 

Source Type III df Mean F Sig.
Sum of Square
Squares
Corrected Model 0.28 19 0.01 0.69 0.82
Intercept 0.01 l 0.01 0.28 0.60
Group 0.0] 2 0.00 0.16 0.85
Age 0.00 1 0.00 0.14 0.71
Education 0.16 6 0.03 1.27 0.28
Group * Education 0.12 10 0.01 0.54 0.86
Error 2.30 108 0.02
Total 2.98 128
Corrected Total 2.58 127

 

a. . .R Squared = .108 (Adjusted R Squared = -.049)

 

 

H07 hypothesis. Two-way ANCOVA was further used to test the seventh
hypothesis for this study, among women undergoing Breast MRI, there is no relationship
between previous history of breast cancer and the effectiveness of interventions. This
analysis used previous history of breast cancer as the moderator variable and age as a

control variable. Results from the analysis are presented in Table 16.

55

Findings indicate no significant difference in mean pre/post intervention %
change scores between Groups A, B and C. In other words, previous history of breast
cancer, or age or the combination of previous history of breast cancer and age did not
significantly change the relationships between the interventions and anxiety levels.

Table 16
Analysis of Previous Breast Cancer and the Effectiveness of Interventions Using a Two-

way ANCO VA

 

 

Tests of Between-Subjects Effects

Dependent Variable: Pre/Post Intervention % Change

 

Type III Sum of
Source Squares df Mean Square F Sig.
Corrected Model 0.01 6 0.00 0.10 1.00
Intercept 0.01 1 0.01 0.52 0.47
Group 0.00 2 0.00 0.02 0.98
Age 0.01 1 0.01 0.25 0.62
Group* Breast Ca
Hx 0.00 2 0.00 0.09 0.92
Breast Ca Hx 0.00 1 0.00 0.15 0.70
Error 2.57 121 0.02
Total 2.98 128
Corrected Total 2.58 127

a. . .R Squared = .005 (Adjusted R Squared = -.045)

 

In summary, results of analyses testing hypotheses H01 through H07 indicate no
significant relationship between effectiveness in intervention and moderator variables
social support number, claustrOphobia, previous knowledge about MRI, marital status,
highest level of education and previous history of breast cancer. However, analyses do
show significant differences between means for pre/post intervention % change and

effectiveness of intervention within Group A, Group B and Group C. This means all three

56

methods of intervention significantly reduced anxiety levels. Analyses further show that
the significance level for intervention was highest in Group C (0.002) compared to Group

A (0.008) and Group B (0.009).

Post-hoe Analyses
The conceptual model for this study was used to examine relationships between
three types of educational intervention and changes in state-anxiety levels following
intervention. Additionally, the model was used to identify significant relationships
between moderator variables and the efficacy of the three interventions. Based on
findings from these analyses, additional questions were developed to gain a better
understanding about the relationship between moderator variables and the effectiveness
of interventions within each group. Figure 5 illustrates the post-hoe conceptual model for
secondary hypotheses developed in response to these questions:
H03 Among women undergoing Breast MRI, there is no relationship
between participants ’ perceived social support numbers and the
effectiveness of intervention within Group A, Group B or Group C
H09 Among women undergoing Breast MRI, there is no relationship
between claustrophobia and the effectiveness of intervention within
Group A, Group B or Group C
H010 Among women undergoing Breast MRI, there is no relationship
between previous knowledge about MRI and the effectiveness of
intervention within Group A, Group B or Group C
H011 Among women undergoing Breast MRI, there is no relationship
between marital status and the effectiveness of intervention within
Group A, Group B or Group C
H012 Among women undergoing Breast MRI, there is no relationship

between education and the effectiveness of intervention within
Group A, Group B or Group C

57

H013 Among women undergoing Breast MRI, there is no relationship
between previous history of breast cancer and the effectiveness of
intervention within Group A, Group B or Group C

Figure 5 below illustrates the post-hoe conceptual model.

 

0 Moderator Variables

Social Support Number
Claustrophobia

Previous Knowledge about MRI
Marital Status

Highest Level of Education
Previous History of Breast Cancer

OOOOOO

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Input Variable
0 Pre-Intervention
Level of State
Anxiet
y v x Outcome Variable
0 Post-
Intervention
. ’ Level of State
Intervention Group ‘
0 Groups A, B and C

 

 

 

 

 

 

 

 

Figure 5. Post-hoe model for analysis of the relationship between moderator variables

and the effectiveness of interventions within Group A, Group B and Group C

In preparation for analyses to examine relationships between the moderator
variables and the effectiveness of interventions within Group A, Group B and Group C,

data for the study were split based on the three groups. Results of data analyses were

58

further sorted according to groups to enable comparison of mean levels of state-anxiety
change within each group.

Based on results of the Shapiro-Wilk test for normality showing normal
distribution for pre/pos-intervention % change and non-normal distribution for social
support number, Kendall’s tau_b correlation was used to analyze the relationship between
pre/post intervention % change and social support number (hypothesis H03). In addition,
One-way ANOVA and Two-way ANOVA tests were used to analyze relationships
between pre/post intervention % change and other moderator variables included in
hypotheses H09 — H013.

H08 hypothesis. The hypothesis among women undergoing Breast MRI, there is no
relationship between participants ’ social support numbers and the efi'ectiveness of
intervention within Group A, Group B or Group C was tested using Kendall’s tau_b
correlation. Data for pre/post intervention % change was obtained by subtracting post-
intervention scores from pre-intervention scores for each participant and then
transforming the resulting values into percentages. Therefore, lower values for this
variable indicate greater effectiveness in intervention. Table 17 presents the results of this
analysis.

Findings indicate a modest, negative correlation between participants’ social
support numbers and the effectiveness of intervention within Group B, r(40) = 0.26, p =
0.02). In other words, participants in Group B who indicated that they could rely on more
individuals to provide support when they needed it experienced less reduction in anxiety

compared to participants who indicated that they could rely on fewer individuals to

59

provide support when they needed it. Group B intervention was more effective for
participants with fewer individuals in their social support networks.

Table 17
Correlations Between Pre/Post Intervention % Change and Social Support Number
Using Kendall’s Tau b.

 

 

 

 

Correlations
Group A. Group B. Group C
Kendall’s tau_b SS Num Correlation Coeff. -0.002 0.26* 0.03
Sig. (2-tailed) 0.98 0.02 0.80
N 43 42 43

 

*Correlation is significant at the .05 level (2-tailed).

 

H09 hypothesis. The hypothesis among women undergoing Breast MRI, there is no
relationship between claustrophobia and the effectiveness of intervention within Group
A, Group B or Group C was tested using a One-way ANOVA with the sample data split
into groups for comparison. Findings from this analysis revealed no significant difference
in mean pre/post intervention % change scores for participants who were claustrophobic
compared to corresponding scores for participants who were not claustrophobic within

Group A, Group B or Group C (See Table 18).

60

Table 18
Analysis of Claustrophobia and Pre/Pos Intervention % Change Within Group A, Group
B and Group C using a One-way ANOVA

 

 

 

 

Group A B C Sum of df Mean F Sig.
Squares Square
A Between 0.06 1 0.06 2.60 0.16
Groups
Within 0.92 41 0.02
Groups
Total 0.98 42
B Between 0.03 1 0.03 1 .39 0.25
Groups
Within 0.89 40 0.02
Groups
Total 0.92 41
C Between 0.01 1 0.01 0.5 1 0.48
Groups
Within 0.67 41 0.02
Groups
Total 0.68 42

 

 

Although results of the analysis do not show a significant difference between
claustrophobic participants compared to non-claustrophobic participants, additional
analysis using a One-way ANOVA does show a trend suggesting an interaction-by-group
effect for claustrophobia at a significance level of p = 0.10. (See Table 19). This means
the relationship for claustrophobia and efficacy of interventions differs across the three
groups.

Specifically, results suggest a positive relationship between claustrophobia and
efficacy of intervention for Group A and a negative relationship between claustrophobia

and efficacy of intervention for Group B, and to a lesser extent, for Group C. Group A

61

intervention was more effective in reducing anxiety for claustrophobic participants
compared to either Group B or Group C interventions. Figure 6 shows this interaction
effect.

Table 19.
Interaction-by-group Effect for Claustrophobia and Pre/Post Intervention % Change
Between Group A, Group B and Group C using a Two-way ANOVA

 

 

Tests quetween-Subjects Effects

 

Dependent Variable: Pre/Post Intervention % Change

 

 

 

Source Type III Sum of Squares df Mean Square F Sig.
Corrected Model 0.10 5 0.02 0.97 0.44
Intercept 0.41 l 0.41 20.28 0.00
Group 0.01 2 0.01 0.26 0.78
Group * Claustro 0.10 2 0.05 2.39 0.10
Claustro 0.00 1 0.00 0.00 0.97
Error 2.48 122 0.02

Total 2.98 128

Corrected Total 2.58 127

 

a R Squared = .038 (Adjusted R Squared = -.001)

 

62

Est 1m ated Marginal Means of

PrelPost Intervention % Change
0.00 - Group AB C

 

~02 ‘

 

-.08 ‘ \
-.lU ‘
£—

-.12. 1:1

 

 

 

no yes

Claustrophobic

Figure 6. Interaction-by-group effect for claustrophobia between Group A, Group B and

Group C

H010 hypothesis. The hypothesis, among women undergoing Breast MRI, there is
no relationship between previous knowledge about MRI and the eflectiveness of
intervention within Group A, Group B or Group C was tested using a One-way ANOVA.
Table 20 presents the results of this analysis. Findings reveal no significant difference
between mean pre/post intervention % change scores for participants with previous
knowledge about MRI compared to corresponding scores for participants without

previous knowledge about MRI within Group A, Group B or Group C.

63

Table 20.
Analysis of Previous Knowledge about MRI and Pre/Post Intervention % Change Within
Group A, Group B and Group C using a One-way ANOVA

 

 

 

 

 

Group A B C Sum of df Mean F Sig.
Squares Square
A Between 0.002 1 0.002 0.085 0.773
Groups
Within 0.977 41 0.024
Groups
Total 0.979 42
B Between 0.019 1 0.019 0.836 0.366
Groups
Within 0.905 40 0.023
Groups
Total 0.924 41
C Between 0.034 1 0.034 2. 199 0. 146
Groups
Within 0.643 41 0.016
Groups
Total 0.677 42

 

 

Additional analysis was performed using a Two-way ANOVA to test for

interaction effects of pre/post-intervention % change and previous knowledge about MRI

between the three groups. Results of this analysis show no significant interaction effect

between knowledge about MRI and intervention group (See Table 21 on the next page).

Table 21.
Interaction-by-group Effect for Previous Knowledge about MRI and Pre/Post

Intervention % Change Between Group A, Group B and Group C using a Two-way
ANOVA

 

 

Tests of Between-Subjects Efi‘ects

 

Dependent Variable: Pre/Post Intervention % Change

 

 

 

Type III Sum of
Source Squares df Mean Square F Sig.
Corrected Model 0.06 5 0.01 0.54 0.75
Intercept 0.30 1 0.30 14.58 0.00
Group 0.00 2 0.00 0.12 0.89
Prev Know MR 0.00 1 0.00 0.00 0.98
Group * Previous
Know MR 0.06 2 0.03 1.34 0.27
Error 2.53 122 0.02
Total 2.98 128
Corrected Total 2.58 127

 

a R Squared = .022 (Adjusted R Squared = -.018)

 

H011 hypothesis. The hypothesis among women undergoing Breast MRI, there is
no relationship between marital status and the efi‘ectiveness of intervention within Group
A, Group B or Group C was tested using a One-way ANOVA. Results of this analysis are
presented in Table 22. Findings show a significant difference between mean pre/post

intervention % scores among marital categories within Group A.

65

Table 22.

Analysis of Marital Status and Pre/Post Intervention % Change within Group A, Group B
and Group C using a One-way ANOVA

 

 

 

 

 

 

Group A B C Sum of df Mean F Sig.
Squares Square
A Between 0.303 6 0.050 2.69 0.03
Groups
Within 0.677 36 0.019
Groups
Total 0.979 42
B Between 0.104 6 0.017 0.74 0.62
Groups
Within 0.820 35 0.023
Groups
Total 0.924 41
C Between 0.067 6 0.01 1 0.66 0.68
Groups
Within 0.610 36 0.017
Groups
Total 0.677 42

 

 

Further analysis was performed to determine which categories of marital status

within Group A showed significant pre-intervention vs. post-intervention state-anxiety

change. Descriptive statistics were calculated for each marital category within Group A

to provide this information. Table 23 presents the results of this analysis.

66

Table 23.

Analysis of Marital Status within Group A Showing Significant Pre-Intervention vs.

Post-Intervention State-A nxiety Change

 

 

Descriptive Statistics

 

Marital Status

Single Never
Married

Living with Sig

Other

Married

Married but

Separated

Divorced

Remarried

Widowed

Pre/Post Int.
Change

Valid N
(listwise)
Pre/Post Int.
Change
Valid N
(listwise)
Pre/Post Int.
Change
Valid N
(listwise)
Pre/Post Int.
Change
Valid N
(listwise)
Pre/Post Int.
Change
Valid N
(listwise)
Pre/Post Int.
Change
Valid N
(listwise)

Pre/Post Int.
Change

%

%

%

%

°/o

%

%

28

28

3

Min

0.15

0.41

-0.46

-0.15

-0.25

-0.13

-0.33

0.15

0.41

0.26

-0.15

0.10

0.00

0.03

Mean

0.15

0.41

-O.07a

-0.15

-0.02

-0.04

-012"

Std. Dev

0.14

0.14

0.08

0.19

 

 

a indicates a significant difference between the married category and the non-married

category

b indicates a significant difference between the widowed category and the non-

widowed category

67

Results of this analysis indicate a significant difference between mean state-
anxiety outcome scores for participants in Group A who were married compared to
participants who were not married. Results also show near-significant differences
between mean state-anxiety outcome scores for participants in Group A who were
widowed compared to participants who were not widowed. In other words, Group A
intervention was more effective in reducing anxiety for participants who were
married or widowed compared to participants who were divorced or remarried.

H012 Hypothesis. This hypothesis states: among women undergoing Breast
MR1, there is no relationship between highest level of education and the effectiveness
of intervention within Group A, Group B or Group C and was tested using a One-way
ANOVA. Table 24 presents the results of this analysis.

Findings indicate no significant difference between mean pre/post intervention
% change scores for any category of highest level of education within Group A,
Group B or Group C. In other words, there was no significant difference in the
amount of state-anxiety change for individuals with higher levels of education
compared to individuals with lower levels of education following intervention within
Group A, Group B or Group C. Participants experienced similar levels of anxiety

reduction regardless of their educational backgrounds.

68

Table 24.
Analysis of Highest Level of Education and Pre/Post Intervention % Change within
Group A, Group B and Group C using a One-way ANO VA

 

 

 

 

 

 

 

 

Group A B C Sum of df Mean F Sig.
Sflrares Square
A Between 0.07 1 0.07 2.91 0.10
Groups
Within 0.91 41 0.02
Groups
Total 0.98 42
B Between 0.01 1 0.01 0.32 0.58
Groups
Within 0.91 40 0.02
Groups
Total 0.92 41
C Between 0.02 l 0.02 1.22 0.28
Groups
Within 0.66 41 0.02
Groups
Total 0.68 42

 

 

H13 Hypothesis. The hypothesis among women undergoing Breast MRI, there is
no relationship between previous history of breast cancer and the effectiveness of
intervention within Group A, Group B or Group C was also tested using a One-way
ANOVA. Table 25 presents the results of this analysis. Findings show no significant
difference between mean pre/post intervention % change scores for participants with a
previous history of breast cancer compared to corresponding scores for participants

without a previous history of breast cancer within Group A, Group B or Group C.

69

Table 25

Analysis of Previous History of Breast Cancer and Pre/Post Intervention % Change

within Group A, Group B and Group C using a One-way ANOVA

 

 

 

 

 

 

 

 

Group A B C Sum of df Mean F Sig.
Squares Square

A Between 0.0] 1 0.01 0.21 0.65
Groups
Within Groups 0.97 41 0.02
Total 0.98 42

B Between 0.001 1 0.001 0.02 0.88
Groups
Within Grogis 0.92 40 0.02
Total 0.92 41

C Between 0.001 I 0.001 0.04 0.85
Groups
Within Groups 0.68 41 0.02
Total 0.68 42

 

 

Additional analysis was performed using a Two-way ANOVA to determine

whether the relationship between previous history of breast cancer and pre/post

intervention % change varied between Group A, Group B and Group C. Table 26

presents results from this analysis showing no significant interaction effect for previous

histo of breast cancer and re/ ost intervention % chan e between the three rou s.
ry P P g 8 P

70

Table 26
Interaction-by-group Effect for Previous History of Breast Cancer and Pre/Post

Intervention % Change between Group A, Group B and Group C using a Two-way
ANOVA

 

 

Tests of Between-Subjects Effects

 

Dependent Variable: Pre/Post Intervention % Change

 

 

 

Source Type III Sum of df Mean F Sig.
Squares Square

Corrected Model 0.01 5 0.00 0.06 1.00
Intercept 0.39 1 0.39 18.44 0.00
Group 0.00 2 0.00 0.03 0.98
Group * Br_Ca_Hx 0.00 2 0.00 0.10 0.90
Br_Ca_Hx 0.00 1 0.00 0.08 0.78
Error 2.57 122 0.02

Total 2.98 128

Corrected Total 2.58 127

 

a R Sguared = .003 (Adjusted R Squared = -.038)

 

To summarize, analyses for hypotheses H03 through H013 reveal several
relationships between moderator variables and intervention groups in this study. Analysis
of social support shows moderate, negative correlation within Group B such that
participants with higher social support numbers experience lower effectiveness in
intervention compared to participants with lower social support numbers. Additionally,
analysis of claustrophobia shows an interaction-by-group effect. This means Group A
intervention is more effective for claustrophobic participants compared to non-
claustrophobic participants, and Group B and Group C interventions are less effective for

claustrophobic participants compared to non-claustrophobic participants.

71

Analysis further shows that the effectiveness of Group A intervention varied as a
function of marital status. Specifically, results show that married and, to a lesser extent,
widowed participants experience greater reductions in anxiety following intervention

compared to remarried and divorced participant

Multivariate Analysis

Based on findings of univariate and bivariate analyses along with additional
theoretical considerations, multivariate analysis was employed using ordinary least
squares regression to create a model that explains variance of post-intervention state-
anxiety levels. Results of this comparison are listed in Table 27.

Results of this analysis show an overall model that is statistically significant, R-
Squared = 83%, F (9, 118) = 63.66, p = 0.00. The R-squared value indicates that trait
anxiety (log), social support number (log), marital status (widowed and married), highest
level of education (high school, attended college, college 4-year degree and
graduate/professional degree) and pre-intervention state-anxiety levels (log) explain
approximately 83% of the variance of post-intervention state anxiety levels, leaving only
about 17% unexplained.

There does seem to be an overall effect for highest level of education as
participants who attended college but did not earn a degree scored lower average post-
intervention state anxiety scores. Specifically, participants who attended college reported
an estimated average four-point decrease in post-intervention state-anxiety scores
compared to participants with a GED, a 2-year college degree or other, non-collegiate

education. Interestingly there seems to be a similar trend for high school education.

72

Participants who earned a high school education scored an estimated average three points
lower for post-intervention state-anxiety compared to participants with a GED, a 2-year
college degree or other, non-collegiate education. Although this relationship suggests a
trend toward lower scores for high school education, the relationship did not reach a
significance level of p = 0.05.

In addition, analyses show that pre-intervention state-anxiety scores and trait-
anxiety scores are strong predictors of post-intervention state-anxiety scores. Findings
presented in Table 27 indicate that pre-intervention state-anxiety is the strongest
predictor of post-intervention state-anxiety (t = 16.71 . pS0.05), whereas trait anxiety is
the second-most significant predictor (t = 2.75, pS0.05). The latter finding supports
results presented in Table 6 (on page 41) indicating significant correlation between pre-

intervention state-anxiety scores and trait-anxiety scores.

 

 

 

 

 

Table 2 7.
Analysis of Moderator Variables and Post-Intervention State Anxiety using Multivariate
Analysis
Model Summary
R R Adj. R Std. Err. of Change Statistics
Square Square the Estimate
R F de df2
Square Change
Change
0.91a 0.83 0.82 0.06 0.83 63.66 9 118
Sum of df Mean Square F Sig.
Squares
Regression 2.31 9 0.252 63.66 0.00
Residual 0.48 1 18 0.004
Total 2.79 127

 

73

a. Predictors: (Constant), manied, Graduate/Professional Degree, Trait Anxiety,
Attended College, Social Support Number, College 4-Year Degree, Widowed,
High School, Pre-Intervention State Anxiety

b. Dependent Variable: Post-intervention State Anxiety

 

 

 

 

Coeflicients
Unstand. Stand. t Sig. 95 % Confidence
Coef Coef Interval for B
Model B Std. Beta Lower Upper
Error Bound Bound
l .00 (Constant) -0.03 0.08 -0.42 0.68 -0.20 0.13
Attended -0.04 0.02 -0. 12 -2.5 3 0.01 -0.08 -0.01
College"
Trait Anx. 0.18 0.06 0.14 2.75 0.01 0.05 0.30
Social Supp. 0.03 0.02 0.06 1.51 0.13 -0.01 0.08
Widowed’ -0.01 0.03 -0.02 -037 0.71 0.06 0.04
College 4- -0.02 0.02 -0.06 -1.38 0.17 -0.06 0.01
Year Degree"
Pre State Anx. 0.84 0.05 0.84 16.71 0.00 0.74 0.93
High School" 0.03 0.02 -0.08 -1.70 0.09 -007 0.01
Graduate/Prof. -0.01 0.02 -0.03 -0.62 0.54 -0.05 0.02
Degree 1'
Married’ -001 0.01 —0.03 -0.63 0.53 -003 0.02

 

. Control group for marital (married and widowed) was divorced and remarried

” Control group for highest level of education (high school, attended college, college
4—year degree and graduate/professional degree) was GED, College 2-year degree

and other non-collegiate degrees.

 

In summary, findings from this analysis show lower post-intervention state-

anxiety scores for participants with a non-degree college education and a trend toward

lower scores for participants with a high-school education compared to participants with

a GED, a 2-year college degree or other, non-collegiate education. In addition,

74

multivariate regression analysis also shows that pre-intervention state-anxiety scores and

trait-anxiety scores are strong predictors of post-intervention state-anxiety scores.

75

CHAPTER 5

DISCUSSION

The purpose of this study was to compare the effectiveness of three different
methods of educational intervention in reducing state anxiety levels for women who are
scheduled to undergo breast MRI. The study defined three types of intervention with an
experimental design and randomly assigned participants into groups for this comparison.
The main independent variable for this study was an educational intervention tool and the
main outcome variable was the level of state-anxiety change following intervention.

In order to gain a better understanding about relationships between pre-
intervention state anxiety, post-intervention state anxiety, and trait anxiety, analyses were
conducted to examine relationships between these variables. Results from these analyses
reveal significant correlation between pre-intervention state anxiety and post-intervention
state anxiety and also between pre-intervention state anxiety and trait anxiety. In other
words, participants who reported higher levels of anxiety before intervention also
reported higher levels of anxiety after intervention. Furthermore, participants who
reported higher levels of state anxiety in response to their impending breast MRI exam
also reported greater general tendencies toward anxiety (trait anxiety). These results
support findings by Spielberger et al. (1983) indicating “state-trait correlations tend to be
slightly higher when the STAI scales are given in the same testing session” (p. 31). The
Trait-Anxiety Inventory was administered immediately following the State-Anxiety

Inventory in this study.

76

Additional analyses were conducted to examine the relationship between pre-
intervention state anxiety and other variables in the study. Results show a significant
relationship between pre-intervention state anxiety and claustrophobia and also a near-
significant relationship between pre-intervention state anxiety and previous history of
breast cancer. This means participants who were claustrophobic, and, to a lesser extent,
participants with a previous history of breast cancer, were more anxious when they
arrived for their breast MRI exams compared to participants who were not claustrophobic
or participants without a previous history of breast cancer.

Interestingly, results also show a general trend in the relationship between
claustrophobia and trait anxiety. Participants who were claustrophobic seemed to have
higher general tendencies toward anxiety. These correlations may prove useful in the
healthcare setting when tailoring methods of intervention to specific needs of the patient.
Interventions that are most effective in reducing anxiety for claustrophobic patients, or
patients with a previous history of breast cancer, should be considered for patients having
these characteristics. Further discussion will focus on this topic as the strengths and
weakness of each type of intervention are revealed.

The primary working hypothesis for this research was among women undergoing
Breast MRI, there is a relationship between combined verbal and computer-based
educational intervention and state-anxiety levels. Analysis used to test this hypothesis
revealed no significant relationship between the three methods of intervention and levels
of state-anxiety change following intervention. Therefore, the null hypothesis for this

study, among women undergoing Breast MRI, there is no relationship between combined

77

verbal and computer-based educational intervention and state-anxiety levels, was not
rejected.

Although the efficacy of interventions did not significantly differ between groups,
further analysis did indicate that each intervention resulted in significantly lower levels of
state anxiety within its group (Group A = -7.1%, F (1, 42) = 7 .71, p = 0.008; Group B = -
6.6%, F (1, 41) = 7.59, p = 0.009; Group C = -6.5%, F (1, 42) = 11.07, p = 0.002).
Interventions for Group A, Group B and Group C were all effective in reducing state-
anxiety levels for participants. This finding supports Street et al.’s study, Preconsultation
Education Promoting Breast Cancer Screening (1998) which showed that women who
received educational intervention experienced less anxiety about cancer screening
regardless of the method employed.

Additional consideration was given to the question of whether the reductions in
state anxiety levels for each group represented clinically-significant reductions. A
literature review was conducted in order to answer this question. However the research
did not produce relevant information. According to Charles Spielberger, author of the
STAI, designation of clinical significance is “completely arbitrary” (personal
communication, 2006). While all three interventions significantly reduced state—anxiety
levels, measurements of clinical significance for anxiety change do not appear to be
standardized, and therefore, are not measurable.

The second purpose of this study was to determine whether a relationship existed
between perceived social support networks (number and quality) and the effectiveness of

interventions. Because data for social support quality was excessively skewed and

78

transformation of data failed to reduce the skew, this variable was omitted from
additional bivariate or multivariate analyses.

Further analysis for social support number and efficacy of intervention revealed
moderate negative correlation within Group B. In other words, participants in this group
who reported higher social support numbers also reported less reduction in state-anxiety
levels following intervention. Interestingly, analysis also showed significant negative
correlation between social support number and trait anxiety meaning that participants
who reported a higher number of individuals in their social support networks also
reported lower general tendencies toward anxiety.

Questions arise about the relationship between social support number and
effectiveness of intervention within Group B. Because this intervention provided
computer—based intervention without verbal contact, these participants may have
perceived lower levels of social support during intervention compared to participants
within Group A and Group C who received verbal intervention. If so, this perception
would explain the negative correlation between social support number and efficacy of
intervention within this group. Further research is needed to test this hypothesis.

Interestingly, analyses also reveal an interaction effect for claustrophobia between
Group A, Group B and Group C. Specifically, intervention was most effective for
claustrophobic participants within Group A and least effective for claustrophobic
participants within Group B (and, to a lesser extent, within Group C). This means
participants in Group B who were claustrophobic, experienced less reduction in anxiety
following intervention compared to participants who were not claustrophobic. This is an

interesting finding in lieu of results indicating lower effectiveness within this group for

79

participants with higher social support numbers. These results draw attention to a
possible relationship between social support number, claustrophobia and verbal vs. non-
verbal intervention. However, the interaction of these variables was not adequately
examined in this study to make inferences about their relationship and further research is
needed to form relevant conclusions.

Additional analyses examined relationships between other moderator variables
and efficacy of interventions within each group. Findings show a relationship between
marital status and efficacy of intervention within Group A. Specifically, participants in
this group who were married experienced significantly greater reductions in anxiety
levels following intervention compared to participants who were divorced or remarried.
Furthermore, participants within Group A who were widowed experienced near-
significant reductions in anxiety levels compared to participants who were divorced or
remarried. This finding suggests a possible relationship between successful marriage and
effectiveness of verbal intervention. Additional research focused on marital status and
intervention is needed to further explain this finding.

Lastly, multivariate regression analysis for this study identifies predictor variables
that explain approximately 83% of the variance in post-intervention state anxiety levels.
Results indicate that pre-intervention state anxiety levels as well as trait anxiety levels are
strong predictors of post-intervention state-anxiety levels. In addition, multivariate
analysis also indicates an overall effect for highest level of education. Specifically, results
indicate that participants with a non-degree college education and, to a lesser extent,
participants with a high-school education, experience greater reductions in anxiety

compared to participants with a GED, a two-year college degree or another non-

80

collegiate education. These results suggest a curvilinear relationship between education
and intervention such that intervention is most effective for individuals with a moderate
level of education and less effective for individuals with either lower or higher levels of
education.

Limitations of the Study

This study had limitations related to the sample group and the geographic
location. Participants in this study were predominantly Caucasian (95.3%), college-
educated (74%) women who were married (63%). In addition, the study was limited to a
single clinical site and included only women who resided in the Midwest and were able
to read and write in the English language. These factors limited the generalizability of the
results to populations with similar demographics.

One additional limitation of the study warrants notation. A high number of
participants expressed fear of needles when they saw the slide depicting the use of
intravenous (IV) fluid in the PowerPoint educational intervention tool. The extent of this
fear factor was not anticipated in the study design and, therefore, not measured during the
study.

Conclusion

This study was designed and carried out with the primary purpose of comparing
the effectiveness of three different educational interventions in reducing state anxiety
levels and a secondary purpose of examining how perceived social support networks
interact with the interventions. Although results of the study reveal no significant
difference in efficacy between the three interventions, results do indicate that all three

methods of intervention were effective in reducing state anxiety levels for participants

81

within their groups. Participants in all three groups reported significantly lower post-
intervention vs. pre-intervention state anxiety scores on the State Trait Anxiety Inventory.

Results of the study also indicate a relationship between social support number
and efficacy of intervention for participants in Group B and also suggest a relationship
between claustrophobia and effectiveness of intervention for this group. Participants in
Group B with higher social support numbers and, to a lesser extent, participants who
were claustrophobic, experienced less reduction in anxiety following intervention
compared to participants with lower social support numbers or participants who were not
claustrophobic. These findings suggest a possible relationship between social support
number, claustrophobia, and efficacy of intervention. Further research is needed to
explain how these variables interact with verbal vs. non-verbal intervention.

Research findings further indicate lower post-intervention state anxiety scores for
select groups of participants. In general, participants with a high-school or non-degree
college education scored lower state anxiety scores overall following intervention,
compared to participants with a GED, a two-year college degree or other, non-collegiate
education.

In summary, this study provides results that lead to valuable conclusions about
interventions in the clinical setting. The research herein not only addresses the question
of efficacy of intervention, but it also exposes new research questions that were
previously unstated. With this focus, future research can continue to build upon this study
and improve the long-term outlook for patients and families who face the possibility of

being diagnosed with cancer.

82

Implications for Future Research

Results from this study generate new questions related to perceived levels of
family and social support, claustrophobia, needle phobia, and tailored intervention. For
perceived levels of social support, questions arise about the significance of the
relationship between higher social support numbers and the efficacy of intervention
within Group B. The interaction effect of claustrophobia must also be considered for this
group as individuals who are claustrophobic report less reduction in state anxiety levels
following intervention compared to non-claustrophobic participants.

Interestingly, participants within this group viewed the educational intervention
tool but did not receive the standard verbal explanation about the MRI procedure before
completing the STAI for the second time. This raises the question of whether verbal
intervention is necessary in order to counterbalance the effects of claustrophobia on state
anxiety levels. Furthermore, this finding also raises a question about possible interaction
of social support number and claustrophobia in relation to non-verbal intervention.
Additional research is needed to explore the relationship between verbal vs. visual
educational intervention and the interactive effects of claustrophobia and social support
number on state anxiety levels. Research focused on the relationship between
claustrophobia and state anxiety levels with social support number as a control should
provide the foundation for this type of study.

Another factor related to the efficacy of verbal intervention in this study is the
researcher’s and study representatives’ levels of professional experience in delivering
verbal explanations in a clinical setting. The researcher and study representatives for this

study had a minimum often years’ experience in delivering verbal explanations about

83

screening exams to clinical patients. Verbal intervention in this study may have been
more effective compared to other Midwest clinics with less-experienced technologists.
Additional research is needed to determine the relationship between researcher
experience and efficacy of verbal interventions.

Findings from this research also reveal a need for measurement of state anxiety
levels at an additional time point. The current study design provided for measurements of
state anxiety levels at two time points. The first measurement occurred when participants
arrived at the MRI department and the second measurement occurred after the
participants received intervention. However, this design did not measure state anxiety
levels for claustrophobic individuals in Group A after they viewed the magnet for the first
time. In order to measure this effect, the study design should have included
administration of the STAI for all three groups at a third time point after participants
entered the MRI exam room and viewed the magnet for the first time. In consideration of
the need to maintain patient throughput in the clinical environment, this procedure could
be simulated in future research by using a non-clinical MRI exam room.

Another consideration related to administration of the STAI includes a possible
learned effect from repeated testing. A question arises from this study about whether the
results of the post-intervention state anxiety inventory would have been the same if the
participants had not just completed the identical inventory twenty minutes before. In
order to test this hypothesis, future research should include a control group that completes
the post—intervention state-anxiety inventory, but does not complete the pre-intervention

state anxiety inventory.

84

The limitation of this study, related to race, also draws attention to the need for
additional research. Miller and Champion addressed tailored intervention in their research
of Attitudes about Breast Cancer (1997) and called for further research that is culturally
sensitive and appropriate for the target audience. While this study attempted to make
advances toward that goal, it contained too few minority participants to draw conclusions
about the efficacy of racially-tailored intervention. Additional research in this area should
include a higher ratio of minorities-to-Caucasians.

Another factor that may influence the results of future educational intervention
relates to the mean age of participants in this study. The average age of participants in
this research sample was 51 years. As medical technology improves, the human lifespan
will undoubtedly continue to increase and will result in a higher mean age with greater
variance for women who undergo breast-cancer screening exams. This increase in
average age for breast-cancer screening will most likely affect the relationship between
interventions and anxiety levels and should be considered in future research designs.

One additional factor that became apparent during the course of the study was
needle phobia. Several participants expressed a fear of needles when they viewed the
image of the IV setup in the educational interventional PowerPoint tool. The extent of
this condition was not anticipated during the design phase of the study and consequently,
its effect was not measured during data acquisition. Future research that is based in a
clinical setting should include measurements of this factor if IVs or injections are
included as a standard part of the procedure.

Finally, in preparation for future research, participants in this study were invited

to participate in a future ancillary longitudinal study that will explore the long-term

85

effects of the moderator variables on their progress and well being. Results from the
current study will form the foundation for the longitudinal study. Participants who

consented will be contacted for continued follow-up based on the ancillary study design.

86

APPENDICES

87

APPENDIX A

CONCEPTUAL AND OPERATIONAL DEFINITIONS

88

 

VARIABLE

CONCEPTUAL DEFINITION

OPERATIONAL DEFINITION

 

Age

Race

Gender

Marital Status

Claustrophobia

Social Support

Number of years since birth

Culturally distinctive group

The sex of an individual based on
reproductive anatomy

Current status in terms of being
legally married to another
individual of the opposite gender.

Abnormal fear of narrow or
enclosed spaces.

The number of individual the
participant can count on for
support in six distinct situations
and the participants overall
satisfaction with that support

89

Measured by respondent during
intake interview and recorded by
healthcare personnel on
Mammography History forms
#1, #2 & #3 (See Appendices E,
F & G)

Measured by healthcare
personnel and recorded on
Mammography history forms as
either “C” (Caucasian), “B”
(African-American), “H”
(Hispanic) or “O” (Other) (See
Appendices E & G). Coded with
indicator variables for analysis.

Measured by healthcare
personnel and recorded on
Mammography history forms as
either “M” (male) or “F”
(female).

Measured by respondent on
demographic survey (See
Appendix D) and coded as “1”-
Single, never married, “2”
Living with Significant Other
“3” — Married, “4” — Married
but Divorced, “5” — Separated,
“6” - Remarried or ‘“7” —
Widowed. Marital status is
coded with indicator variables
for analysis.

Measured by respondent on
Demographic Survey (See
Appendix D) and coded with
indicator variables for analysis.

Measured by respondent on the
Short Form Social Support
Questionnaire (See Appendices
C & I) and coded for analysis as
the average number (on a scale
from 1-9) and average quality
(on a scale from 1-6) of support
for each participant.

Previous History of
Breast Cancer

Previous Knowledge
about MRI

Highest Education

Educational
Intervention Tool

State Anxiety

Trait Anxiety

Prior episode of breast cancer
characterized by a primary lesion
that is different from the current
primary lesion if present.

Either of two conditions: 1.
participant has previously
undergone an MRI exam. 2.
Participant’s healthcare provider
explained the MRI procedure to
participant prior to arrival in MRI
department.

Highest level of education
achieved by the respondent.

PowerPoint tool that provides
information about breast.

“Transitory emotional state or
condition of the human organism
that is characterized by subjective,
consciously-perceived feelings of
tension and apprehension, and
heightened autonomic nervous
system activity” (Spielberger et
al., 1979).

“Relatively stable individual
difference in anxiety

proneness. . (Spielberger et al.,
1979).

90

Measured by researcher on
Mammography history forms
(See Appendices E & G) and
coded as indicator variables for
analysis

Measured by respondent on
Demographic survey (See
Appendix D) and coded with
indicator variables for analysis.
A response of “yes” to either
question indicates a previous
knowledge about MR1

Measured by respondent on
demographic survey (see
Appendix D) and coded as “1”
Grade School or Less, “2” -
General Educational
Development, “3” - High
School, “4” - Attended College,
“5” - 2-Year Degree, “6” — 4-
Year Degree, ”7” —
Graduate/Professional Degree,
or “8” — Other (Please
Describe ).Measured by
respondent on

Measured by researcher or
representative as respondent’s
viewing of educational
intervention PowerPoint tool.

Measured with 20-question, 4-
point Likert—type State Anxiety
Inventory — Form Y and
recorded as average number for
analysis.

Measured with 20—question 4-
point Likert-type Trait Anxiety
Inventory - Form Y and
recorded as average number for
analysis.

APPENDIX B

INSTRUMENT REVIEW
STATE-TRAIT ANXIETY INVENTORY FOR ADULTS (FORM Y)

91

Title:

Authors:

Population:
Score:
Time:
Publisher:

Date:

Concept or Variable:

Description of Items:

Adequacy of Sample
Tested:

State-Trait Anxiety Inventory for Adults (Form Y)

Charles D. Spielberger, Richard L. Gorusch, and Robert E.
Lushene.

Grades 9-16 and adults.

2 Scores: State Anxiety and Trait Anxiety.
1.0-20 minutes.

Mind Garden, Inc.

1983

State Anxiety Level - Conceptual definition — "Transitory
emotional state or condition of the human organism that is
characterized by subjective, consciously perceived feelings
of tension and apprehension, and heightened autonomic
nervous system activity." (Spielberger etal., 1979)

Trait Anxiety Level — Conceptual definition — "relatively
stable individual differences in anxiety proneness. .
(Spielberger et al., 1979)

The State-Trait Anxiety Inventory (ST AI) is a self-report
assessment which consists of two separate subscales that
contain 20 questions each. These two subscales (S-Anxiety
and T—Anxiety) both use a 4 point Likert scale to allow the
subject to show how often or how much each question
applies to them in both situations. The instrument
differentiates between the temporary condition of "state
anxiety" and the more general and long-standing quality of
"trait anxiety”. The essential qualities evaluated by the
scale are feelings of apprehension, tension, nervousness,
and worry. Scores on the scale increase in response to
physical danger and psychological stress, and decrease as a
result of relaxation training. This instrument was originally
designed as a research tool for measuring anxiety levels in
adults and is useful in both research and clinical contexts.

Samples used to test the SSQ6 are adequate.

92

Normative Data:

Level of Measurement:

Discriminability:

Reliability:

Validity:

Normative data are provided for working adults, military
recruits, college and high school students, male
neuropsychiatric patients, male medical patients, and male
prison inmates.

Mean scores for the State-Anxiety Inventory include 35.72
for working men and 35.20 for working women. The mean
scores for the Trait-Anxiety Inventory include 34.89 for
working men and 34.79 for working women.

Ordinal level of measurement.

The State-Trait Anxiety Inventory uses a Likert-type scale
with four categories.

Reliability of the instrument has been widely reported
(Tanaka, Sakamoto, Kijima, & Kitamura, 1998;
Goldenberg & Waddell, 1990; Barnes, Harp & Jung, 2002).

Test-Retest Reliability — STAI scale stability was assessed
on male and female college students for test-retest intervals
ranging from one hour to 104 days. The magnitude of the
reliability coefficients decreased as a function of interval
length. For the Trait-anxiety scale the coefficients ranged
from .65 to .86, whereas the range for the State-anxiety
scale was .16 to .62. The STAI shows that it is very reliable
by it’s two headed approach to measuring anxiety; the tests
high coefficients for the trait anxiety scales shows that it
does indeed measure consistently the trait anxiety levels
among subjects. This low level of stability for the State-
anxiety scale is expected since responses to the items on
this scale are thought to reflect the influence of whatever
transient situational factors exist at the time of testing.

Validity of the instrument has been widely reported
(Tanaka, Sakamoto, Kijima, & Kitamura, 1998;
Goldenberg & Waddell, 1990).

Correlations are presented in the manual between this scale
and other measures of trait-anxiety: the Taylor Manifest
Anxiety Scale, the IPAT Anxiety Scale, and the Multiple
Affect Adjective Check List. These correlations are .80, 75
and .52, respectively.

93

Administration and
Scoring:

Desirable Features:

Undesirable Features:

Construction Validity: Each item was required to have a
higher mean in a number of stressful situations, and a lower
mean in relaxed situations than in non-stressful (neutral)
situations.

Internal Consistency: Internal consistency of the four
subscales was as follows: State Anxiety Absent (0.91),
State Anxiety Present (0.82), Trait Anxiety Absent (0.80),
and Trait Anxiety Present (0.78).

Ease and Brevity: The test was designed with only two,
twenty point scales that can easily be answered in less than
20 minutes. This design helps to reduce the amount of
change that can occur in the subject’s state anxiety level
during the actual time of the test.

The State-Trait Anxiety Inventory is self-administered.
Scores have a direct interpretation: high scores on their
respective scales mean more trait or state anxiety and low
scores mean less. Both percentile ranks and standard (T)
scores are available for male and female working adults in
three age groups (19-39, 40-49, and 50-69), male and
female high school and college students, male military
recruits, male neuropsychiatric patients, male medical
patients, and male prison inmates. Administration times for
the STAI are 10-20 minutes.

The State-Trait Anxiety Inventory is efficient and cost-
effective. The inventory is very easy to administer and
score. The STAI is also portable allowing for
administration in various settings. The availability of the
inventory enables use in both clinical and research settings.

One of the disadvantages of this instrument is its low level
of stability for state-anxiety scale. However, this instability
should be expected since the outcome of the scale is
influenced by the immediate environmental state.

Sources Consulted:

Barnes, LB., Harp, D., Jung, WS. (2002, August).
Reliability Generalization of Scores on the Spielberger
State-Trait Anxiety Inventory, Educational and
Psychological Measurement, 62(4), 603-618.

94

Plunkett, M. State Trait Anxiety Inventory (STAI), ACU
National School of Exercise Science (N SW). Retrieved
January 16, 2005 from
http://dlibrary.acu.edu.au/staffliome/stburke/su02p43.htm

Spielberger, C.D., Gorsuch, R.L., Lushene, R., Vagg, P.R.,
Jacobs, GA. (1983). State-Trait Anxiety Inventory for
Adults, Review Set (Form Y). Redwood City, CA: Mind
Garden Inc.

Spielberger, C. D., Gorsuch, R. L., & Lushene, R. (1979).
Manual of the State-Trait Anxiety Inventory. Palo Alto:
Consulting Psychologists Press.

Spielberger, CD., Gorsuch, RL., and Lushene, RE. State-
Trait Anxiety Inventory, Consulting Psychologists Press,
Inc. Retrieved January 16, 2005 from
http://www.cps.nova.edu/~cpphelp/STAI.htrnl

State-Trait Anxiety Inventory for Adults. Performance
Assessment Network, 2001. Retrieved February 19, 2006
from
http://www.pantesting.com/products/Mindgarden/staxi.asp

95

APPENDIX C

WSTRUMENT REVIEW
SHORT FORM SOCIAL SUPPORT QUESTIONNAIRE (SSQ-6)

96

Title:
Authors:
Population:

Score:

Time:
Publisher:
Date:

Concept or Variable:

Description of Items:

Adequacy of Sample
Tested:

Normative Data:

Level of Measurement:

Discriminability:

Social Support Questionnaire 6 (SSQ-6).
Sarason, Sarason, Shearin, and Pierce (1987).
Adults.

2 Scores: Number of Supports and Satisfaction with
Support.

5 minutes.
Consulting Psychologists Press, Inc.
1987

Social Support — Conceptual definition - Perceived
availability of others to whom one can turn for support and
satisfaction with this perceived available support.

The Short Form Social Support Questionnaire (SSQ-6) is a
six -item self-report questionnaire designed to measure the
number and quality of social supports. Participants list the
initials and relationship of people they can rely on for
support in specific situations. They receive a score based on
the number of individuals in their support network.
Participants then rate their overall satisfaction with support
in each situation using a 6-point Likert scale (from 1 =
‘very dissatisfied’ to 6 = ‘very satisfied’) and a mean
satisfaction score is calculated. The Short Form Social
Support Questionnaire is an abbreviated instrument derived
from the 27-item Social Support Questionnaire developed
by Sarason, Levine, & Sarason (1983) as part of their work
in the area of social support.

Samples used to test the SSQ—6 are adequate.

Normative data are provided for adults.
Ordinal level of measurement is used

The Short Form Social Support Questionnaire uses a
Likert-type scale with six categories.

97

Reliability & Validity:

Administration and
Scoring:

Desirable Features:

Undesirable Features:

Internal consistency reliability coefficients for the SSQ-6
span from .90 to .93 for both the number of supportive
individuals and satisfaction with support (Sarason et al.,
1987). Sarason et al. reported the alpha coefficient of
internal reliability for ‘perceived availability of support’ at
.97 and a test-retest reliability of .90; the alpha coefficient
of internal reliability for ‘satisfaction with support’ was
reported at .94 with test-retest reliability at .83; a modest
correlation of .34 was found between ‘perceived
availability of support’ and ‘satisfaction with support’.

The Short Form Social Support Questionnaire is self-
administered. Given the two-part approach to the

SSQ-6, each item is rated as follows: The first part,
perceived availability of support, is calculated by summing
the total number of support persons listed and dividing it by
six (the total number of items) with a possible range of 0—9,
where a higher score indicates a higher perceived
availability of support; the second part, satisfaction with
support, is calculated by summing the total score and
dividing it by six (the total number of items) with a
possible range of 1-6, where a higher score indicates a
higher satisfaction with support.

The Short Form Social Support Questionnaire is easy to
administer and score. The SSQ-6 is also portable allowing
for administration in various settings. The availability of
the inventory enables use in both clinical and research
settings.

One of the disadvantages of this instrument is its modest
correlation between perceived availability of support and
satisfaction of support.

Sources Consulted:

Plunkett, M. State Trait Anxiety Inventory (STAI) ACU
National School of Exercise Science (NSW). Retrieved
February 19, 2006 from
http://dlibrary.acu.edu.au/staffliome/stburke

Sarason 1., Levine, H., Basham, R., & Sarason, B.:
Assessing Social Support: The social support questionnaire.
Journal of Personality and Social Psychology 1983, 44: 127-
139.

98

Trehame, Gareth J., Lyons, Antonia C., Tupling, Rachel E.
(2001, December).The Effects of Optimism, Pessimism,
Social Support, and Mood on the Lagged Relationship
Between Daily Stress and Symptoms. Current Research in
Social Psychology, 7(5).

Shenoy, Uma A. (1996, December) In Moving to a New
Country: Children and Adolescent’s Adaptation. Master’s
Thesis Submitted to the Faculty of the Virginia Polytechnic
Institute and State University. Retrieved February 19, 2006
from

http://scholar.lib.vt.edu/theses/available/etd-

4491525 1972550/unrestricted/etd.pdf.

Steffen, Patrick R., Hinderliter, Alan L., Blumenthal, James
A., & Sherwood, Andrew. (2001). Religious Coping,
Ethnicity, and Ambulatory Blood Pressure. Psychosomatic
Medicine, 63, 523-530. Retrieved February 19, 2006 from
http://www.psychosomaticmedicine.org/cgi/content/full/63/
4/523.

99

APPENDIX D

DEMOGRAPHIC SURVEY

100

Al Case ID Number _ _ _

We would like you to tell us about you and your family to help us develop
educational tools for women with breast disease. Please circle the best
answer for each question or fill in the blanks with your answer.

A2 Did your doctor or healthcare provider explain the MRI procedure to you?
1 No
2 Yes

A3 Have you ever had an MRI exam before?
1 No
2 Yes

A4 Do small spaces make you feel uncomfortable?
I No
2 Yes

A5 What is the highest level of education you’ve completed?
Grade School or less

General Educational DeveIOpment (GED)

High School

Attended College

College 2-year degree

College 4-year degree

Graduate/Professional degree

Other (please describe)

OO\IO\UI-§UJN'-‘

 

A6 How do you describe your marital status?

Single (never married)

Living with a significant other, not married
Married

Married but Separated

Divorced

Remarried

Widowed

\IGM-hWNH

101

A7 Do you live alone?

 

 

 

1 No
2 Yes
A8 If you do not live alone, how many -
individuals live in yOur home besides
you? _ “
Number ' ' Relationship
2 ~ _ two
‘3 , three .
4 four .,
5 five or more 1'
In this section, we’d like you to describe your occupation J

 

A9 Are you currently employed?
1 No
2 Yes

—__1

A10

A11

A12

A13

A14

If yes, do you work part time or full
time?
1 Part time (29
hrs/week or less
2 Full time (30 or more
hrs/week)
Are you the primary financial
supporter for your family?
1 No
2 Yes

What is the name of your employer?
1

What type of industry do you work in
(education, health, etc)?
1
9 Not sure
What is your job in this occupation?
1
9 Not sure

Please skip to question A18

102

A15 Are you a housewife?
No
2 Yes

A16 Are you retired?
I No
2 Yes

A17 Are you on currently on disability?
1 No
2 Yes

 

In this section, we’d like you to describe your healthcare coverage

 

A18 Do you currently have healthcare coverage?
1 No
2 Yes

A19 If yes, please describe your coverage

1 Private

2 Paid by Employer
3 Medicare

4 Medicaid

A20 Does your insurance limit coverage
for your condition?
1 No
2 Yes

Thank you for participating in this study; we appreciate your input.

103

APPENDIX E

PATIENT HISTORY — MAMMOGRAPHY #1

104

 

 

PATIENT HISTORY

 

ID#: SS#: Xray#:

Last: First: MI: DOB:

Estrogen : Lump : Tenderness :

Birth Ctrl : Pain : Caffeine :

Thyroid : Discharge : Outside Films :

Race : PREGNANCY HISTORY

Height : ft: inches : # Pregncy : Live Births :
Age @ 1St :

FAMILY BREAST CANCER HX Last : Ever Nursed?

Who : pre/pst: Age : MENSTRUAL HISTORY
Age @ Menarche yrs
Last :

Irreg Menses :

OTHER CANCERS

Description :

Date Diag:
SURGERIES Side : Ext : Age : Date :
Mastectomy :
Oophorectomy :

Bx : Mal : Description :

Breast Surgery :
HORMONE HISTORY Date Began : Date Ceased :
Estrogen :
Birth Control :

 

 

105

APPENDIX F

PATIENT HISTORY — MAMMOGRAPHY #2

106

 

 

MAMMOGRAPHY HISTORY

 

 

ID#: SS#: Xray#:
Last: First: MI: DOB:
Time : Exam : Symptomatic :
Weight :

Powder/Deoderant : [H]igh, [M]od, or [L]? Pregnant Now :
Caffeine User : Date Last Period :
Self Referred : Baseline : Screening : Follow-up : Diagnostic :
Outside Films : Exam Date : Location : Avail.
HORMONE HISTORY
Birth Ctrl : yrs : Pain : Estrogen : yrs Now :
Began/Ceased
SYMPTOMS Ext : Age : Date :
Discharge : Color :

Side : Frequency : Length : Loc’n : Comments :
Lumps :
Pain :
FEATURES
Comment :

 

 

107

APPENDIX G

PATIENT HISTORY — MRI MAMMOGRAPHY

108

 

 

MRI PATIENT HISTORY

 

ID# :
XRay# :

Exam Date :
Chart #

 

Name :
Sex : Wt :
BD :
Ph :

Exam Time :
Insurance :
S. Security :

 

Exam :

Diagnosis :
Symptoms :
Prev Here :

 

Physician :
Specialty :
Phone:
Pvt Line :
Comments :

 

MEDICAL HISTORY

Diabetes : Trauma : Cancer :

Kidney Dis. : Pacemaker : AIDS :
PREVIOUS EXAMS
CT Scan :

X-Ray :

Myelogram :
Angiogram :
Ultrasound :
Nuclear Med :

MRI :

Other :

Brought Films :
PROBLEMS LIST
Pain :

Vision :

Hearing :
Headaches :
Balance/Vertigo :
Memory Loss :
Seizures :

Muscle Weakness :
Tingling/Numb. :
Stroke :

Sedation :

Hypertension : Arthritis :
CT Alrgy : M. Implants :

 

Surgeries :
Medications :
Comments :

 

109

APPENDIX H

STATE-TRAIT ANXIETY INVENTORY

110

(SAMPLE)

SELF-EVALUATION QUESTIONNAIRE

STAI Form Y-1

Please provide the following information:

Name Date

Age

Gender (Circle) M F

DIRECTIONS:

A number of statements which people have used to describe themselves are given
below. Read each statement and then circle the appropriate value to the right of

the statement to indicate how you feel right now, that is, at this moment. There are
no right or wrong answers. Do not spend too much time on any one statement but
give the answer which seems to describe your present feelings best.

 

4’0

 

 

 

 

 

 

o ’3
t «to f it»
0 air.» a.
'1) {)1 Q?
a I) 0
1. lfeel calm ..................................................................................... 1 2 3 4
2. lfeel secure .................................................................................. 1 2 3 4
3. lam tense .................................................................................... 1 2 3 4
4. lfeel strained ................................................................................ 1 2 3 4
5. lfeel at ease ................................................................................. 1 2 3 4

 

111

 

(SAMPLE)

SELF-EVALUATION QUESTIONNAIRE
STAlFormY-2

Name Date

DIRECTIONS:

A number of statements which people have used to describe themselves are
given below. Read each statement and then circle the appropriate value to the
right of the statement to indicate how you generally feel. There are no right or
wrong answers. Do not spend too much time on any one statement but give the
answer which seems to describe how you generally feel.

 

 

ll}, (9
e
t e «l is
21.1 feel pleasant ............................................................................... 1 2 3 4
22.1 feel nervous and restless ........................................................... 1 2 3 4
23.1 feel satisfied with myself ............................................................ 1 2 3 4
24.1 with I could be as happy as others seem to be .......................... 1 2 3 4
25.1 feel like a failure ......................................................................... 1 2 3 4

 

 

 

 

 

 

112

 

APPENDIX I

SHORT FORM SOCIAL SUPPORT QUESTIONNAIRE (SSQ-6)

113

Short Form Social Support Questionnaire (SSQ-6)

Please think about people in your life who provide you with help or support. You will
read about some situations, and for each situation you read, tell us all of the people you
know, besides yourself, who you can depend upon / go to for help or support. Please
write each person’s initials plus their relationship to you and whether they are male or
female. Do not list more than nine people per question. After you list the people you
count on for help and support in each situation, then describe your overall level of
satisfaction/ happiness with the help or support you are currently receiving as a whole
from all these people. For any given situation you may tell us that you have no support. If
so, please circle “0”, but still rate your level of satisfaction.

1a. Whom can you really count on to distract you from your worries when you are
worried? (If no one, circle “0” and rate your level of satisfaction) Please list
each person’s initials, his/her relationship to you and whether the person is male
or female.

Person’s Initials Relationship to you Male or Female
0. (No one)

99089999930:-

lb. How satisfied / happy are you with the support / help these people provide, that
is with their helping you when you need help? (Please circle one of the

following)

1 very dissatisfied
2 fairly dissatisfied
3 a little dissatisfied
4 a little satisfied

5 fairly satisfied

6 very satisfied

114

2a

2b.

3a

Whom can you really count on to help you feel more relaxed when under pressure
or tense? (If no one, circle “0” and rate your level of satisfaction) Please list each
person’s initials, his/her relationship to you and whether the person is male or
female.

Person’s Initials Relationship to you Male or Female
0. (No one)

WWSQMPPN!‘

How satisfied / happy are you overall with the support/help these people provide,
that is with their helping you when you need help? (Please circle one of the
following)

1 very dissatisfied

2 fairly dissatisfied
3 a little dissatisfied
4 a little satisfied

5 fairly satisfied

6 very satisfied

Who accepts you totally, including your worst and best points? (If no one, circle
“0” and rate your level of satisfaction) Please list each person’s initials, his/her
relationship to you and whether the person is male or female.

Person’s Initials Relationship to you Male or Female
0. (No one)

FWSQMPPNI‘

115

3b.

4a.

4b.

How satisfied / happy are you overall with the support/help these people provide,
that is with their helping you when you need help? (Please circle one of the
following)

1 very dissatisfied

2 fairly dissatisfied
3 a little dissatisfied
4 a little satisfied

5 fairly satisfied

6 very satisfied

Whom can you really count on to care about you, regardless of what is happening
to you? (If no one, circle “0” and rate your level of satisfaction) Please list each
person’s initials, his/her relationship to you and whether the person is male or
female.

Person’s Initials Relationship to you Male or Female
0. (N 0 one)

PWNP‘S‘PPNT‘

How satisfied / happy are you overall with the support/help these people provide,
that is with their helping you when you need help? (Please circle one of the
following)

1 very dissatisfied
2 fairly dissatisfied
3 a little dissatisfied
4 a little satisfied

5 fairly satisfied

6 very satisfied

116

5a.

5b.

Whom can you really count on to help you feel better when you are feeling
generally sad or down in the dumps? (If no one, circle “0” and rate your level of
satisfaction) Please list each person’s initials, his/her relationship to you and
whether the person is male or female.

Person’s Initials Relationship to you Male or Female
0. (No one)

PWSP‘MPP’NT‘

How satisfied / happy are you overall with the support/help these pe0ple provide,
that is with their helping you when you need help? (Please circle one of the
following)

1 very dissatisfied

2 fairly dissatisfied
3 a little dissatisfied
4 a little satisfied

5 fairly satisfied

6 very satisfied

117

6a

6b.

Whom can you count on to console you / make you feel better when you are very
upset? (If no one, circle “0” and rate your level of satisfaction) Please list each
person’s initials, his/her relationship to you and whether the person is male or
female.

Person’s Initials Relationship to you Male or Female
0. (No one)

99°99‘MPP’N7‘

How satisfied / happy are you overall with the support/help these people provide,
that is with their helping you when you need help? (Please circle one of the
following)

very dissatisfied
fairly dissatisfied
a little dissatisfied
a little satisfied
fairly satisfied
very satisfied

ONU'IALfiNt-t

118

APPENDIX .1

POWERPOINT EDUCATIONAL INTERVENTION TOOL

119

 

Breast AIR]

 

Understanding Your
Exam

 

 

Your Exam

Your doctor has scheduled
a breast exam for you
using Magnetic Resonance
Imaging (MRI). MRI is a
highly sensitive technique
that can detect breast
abnormalities that other
procedures sometimes
miss. The MRI exam lasts
approximately one hour.

 

 

 

 

How is Breast MRI Different

from other Exams?
MRI is a non-invasive procedure that uses a
magnetic field and radio waves to produce cross-
sectional images of the breast. Unlike standard
Mammography, MRI does not use X-Rays.

X-Ray Ultrasound

”v“

           

 

120

 

 

 

When you arrive at
the clinic for your
exam, you will be
asked to complete a
brief medical
history
questionnaire. This
information is necessary to aid in the
interpretation of your MRI exam. It is
important that you record this information as
accurately as possible

 

 

 

The technologist who
performs the MRI exam will
review your medical history
with you and explain the
procedure. She will answer
any questions you might
have about the exam. Please
inform the technologist if
you are pregnant or nursing

 

 

 

 

Before entering the exam

room, you must first W
change into a gown and

remove all metallic objects

including jewelry, watches

and hairpins. MRI uses a

very strong magnet, so you w m m
are not permitted to bring

' . = m
metal artlcles into the scan 13.. fig;- ”5+1“..-
room. A locker is provided W”
- - ~° ‘°°".:'.'::::':..-
1n the dressrng area to ® 55.35:; m - .

 

secure you valuables

 

121

 

 

The MRI magnet is
cylinder-shaped with a
bore through the center.
During the procedure, the
examination table slides
into the middle of the

bore

 

 

 

As part of the Breast
MRI exam, the
technologist will insert
an IV tube into the vein
of your arm. This is
usually done just prior to
the exam. The IV allows
the technologist

 

to administer a clear contrast fluid into your vein
at a precise time during the procedure. The
contrast is necessary to help identify small
lesions and determine the type of tissue they are
made of.

 

 

 

 

The contrast agent used in MRI
will not affect your ability to drive
or perform any other activity. You
can carry on with your normal
routine alter the exam.

  

 

 

122

 

 

Breast MRI uses a special device
called a “coil” to receive information
about your body. The technologist will
place the padded coil on the
examination table in preparation for
your exam.

 

 

 

 

The technologist will
help you onto the
table and position you
correctly for the
exam. Because MRI
produces loud sounds,
you must wear ear
protection during the
procedure. You may listen to music through the
headphones if you’d like. You will still hear the
technologist talk to you through the headphones.

 

 

 

 

The technologist will
raise the table and slide
it into the center of the
magnet. Because MRI is
extremely sensitive to
motion, you must
remain as still as
possible throughout the
exam.

 

 

123

 

 

 

 

After you are
comfortably positioned
in the magnet, the
technologist will
proceed to the
scanning workstation a
to operate the system.

The technologist will continue to communicate
with you through an intercom and observe you
through a large window.

  

 

 

 

    

tu=, . -....

Your exam will be monitored
and interpreted by a radiologist
to ensure that all necessary
images are obtained before you
leave.

 

 

 

 

After the exam is complete, you are free to
collect your belongings and leave. The
radiologist will forward a report to your
referring physician within a few days. You
will review the test results with your doctor.

 

124

 

 

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