PICKING UP THE PACE: TESTING THE EFFECTS OF THE KOHLER
MOTIVATION GAIN ON AN AEROBIC VIDEO TASK
By
Jennifer A. Scorniaenchi

A THESIS
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE
Kinesiology
2011

ABSTRACT
PICKING UP THE PACE: TESTING THE EFFECTS OF
THE KÖHLER MOTIVATION GAIN ON AN AEROBIC VIDEO TASK
By
Jennifer A. Scorniaenchi
This study investigated the presence and persistence of the Köhler motivation gain effect
on repeated sessions of aerobic exercising using a virtually-presented partner. The Köhler
effect is present when an inferior team member persists at a taxing task longer in a team
situation than one would expect from knowledge of his/her individual performance. The
effect is hypothesized to be most potent in conjunctive task conditions where the team’s
potential productivity is equal to the productivity of its least capable member. Participants
(N = 58) were randomly assigned to either an individual, coactive (performance outcome
was determined irrespective of their more capable partner’s performance) or conjunctive
condition (group performance outcome was determined by the partner who stopped riding
first) where they rode with a moderately more capable virtual partner. In a 3 (conditions)
x 6 (time) factorial design, participants exercised on a stationary bike for as long as they
could at 65% of their maximum heart rate on 6 days over a 2-week period. Results
showed those who cycled with a partner under conjunctive conditions over all sessions
persisted 675.39 s longer (M = 1313.46 s) than individual controls and 127.34 s longer
than those under coactive conditions. The findings demonstrate that exercising with a
virtually-present partner in a conjunctive manner can improve persistence on an aerobic
task that persists across multiple work trials.

Copyright By
JENNIFER A. SCORNIAENCHI
2011

	
  

ACKNOWLEDGMENTS
	
  
A special thank you to my advisor and thesis committee chair Dr. Deborah Feltz. Thank
you to my thesis committee members, Drs. Norbert Kerr and Joe Eisenmann, and Ph.D
Candidate Brandon Irwin for providing guidance and direction on this project.
My appreciation goes to all those who volunteered their time and effort to make this
study possible.

iv	
  

TABLE OF CONTENTS
LIST OF TABLES ………………………………………………………………… ..…..iv
LIST OF FIGURES ………………………………………………………………..….....v
CHAPTER 1
INTRODUCTION ………………………………………………………………………. 1
Nature of the problem …………………………………………………………….1
Background and Theory …………………………………………………………..2
Contextual Factors ………………………………………………………………..8
Purpose of the Study ……………………………………………………………...9
Hypotheses ………………………………………………………………………10
Secondary Research Questions ……………………………………………….....10
Delimitations …………………………………………………………………….11
Definitions …………………………………………………………………….....11
CHAPTER 2
REVIEW OF LITERATURE …………………………………………………………...13
Group Motivation Research and Theory ………………………………………..13
The Köhler Effect ……………………………………………………………….15
Mechanisms Underlying the Köhler Effect ……………………………………..18
Social Comparison Processes …………………………………………...18
Indispensability ………………………………………………………….19
Potential Moderators of Group Motivation Gains ……………………………....21
Task Structure …………………………………………………………...21
Physical Presence ………………………………………………………..22
Gender …………………………………………………………………...24
Availability of partner-related performance information ……………......26
Social Ostracism ………………………………………………………...28
Social Factors Affecting Exercise …………………………………………….....29
Self-Efficacy and Exercise …………………………………………………........30
Summary ………………………………………………………………………...36
CHAPTER 3
METHOD ……………………………………………………………………………….38
Participants ……………………………………………………………………....39
Research Design ………………………………………………………………....39
Task ……………………………………………………………………...39
Measures ………………………………………………………………...39
Demographic Questionnaire and Physical Activity Readiness
Questionnaire …………………………………………………....39
Diet …………………………………………………………........40
Self-Efficacy Measures …………………………………….........40
Intention to Exercise …………………………………….............41
Ratings of Perceived Exertion …………………………..............42
VO2 Max Estimate ………………………………………...........42
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Heart Rate ……………………………………………………….43
RPM …………………………………………………...................43
Power Output ………………………………………………........43
Procedure ……………………………………………………………………......43
CHAPTER 4
RESULTS …………………………………………………………………………….....50
Preliminary Analyses …………………………………………………………....50
Descriptives ………………………………………………………….......50
Assessment of Fitness and Habitual Physical Activity... ………..............50
Outliers and Normality ………………………………………………….51
Power ........................................................................................................52
Heart Rate .................................................................................................52
Main Analyses ………………………………………………………………......53
RPE ……………………………………………………………………...54
Task Self-Efficacy ……………………………………………………....55
Regulatory Self-Efficacy ………………………………………………..56
Intention to Exercise ………………………………………………….....56
CHAPTER 5
DISCUSSION …………………………………………………………………………...57
Limitations ……………………………………………………………………....60
Future Research ………………………………………………………………....61
Conclusion ……………………………………………………………………....64
APPENDICES ………......................................................................................................65
APPENDIX A: Informed Consent ........................................................................66
APPENDIX B: Demographics Questionnaire…………………………………...68
APPENDIX C: Regulatory Self-Efficacy Scale…………………………………70
APPENDIX D: Pre Task Self-Efficacy Scale……………………………………73
APPENDIX E: Post Task Self-Efficacy Scale…………………………………...76
APPENDIX F: Comparative Self-Efficacy Scale………………………………..79
APPENDIX G: Intention to Exercise Scale ……………………………………..81
APPENDIX H: 24-Hour Food and Drink Intake ..................................................83
APPENDIX I: Self-Report Fitness .......................................................................85
APPENDIX J: Resting Heart Rate ........................................................................87

vi	
  

REFERENCES ……….....................................................................................................98

vii	
  

LIST OF TABLES
Table 1. This Shows Descriptive Means of Fitness and Habitual Physical Activity…....89
Table 2. This Shows Means of Main Outcome Measures (Persistence and RPE) ...........90
Table 3. This Shows Means of Measures of Intensity (For Manipulation Check) ...........91
Table 4. This Shows Means of All Self-Efficacy Measures (on a scale of 0-10) .............92

viii	
  

LIST OF FIGURES

Figure 1. Average heart rate across trials. ..............................................................93
Figure 2. Average heart rate across trials between conditions ...............................94
Figure 3. Persistence means across trials between conditions (sec) ......................95
Figure 4. Ratings of perceived exertion across trials ........................................................96
Figure 5. Task self-efficacy across trials 2-6, with trial 1 as a covariate ..........................97

ix	
  

CHAPTER ONE
INTRODUCTION
Nature of the Problem
Many people are either inactive or too seldom active even though the links
between regular physical activity and health are well documented (Chandrashekhar &
Anand, 1991; Jennings, Deakin, Dewar, Laufer, & Nelson, 1989; Lee, 1994; Smith et al.,
1995; Warburton, Nicol, & Bredin, 2006). Of those who are physically active, the quality
of their activity, specifically aerobic exercise, is less than optimal. For instance, they may
not exercise as long, as intense, or as frequently as the U.S. guidelines recommend, which
is at least 30 min a day of moderately intense physical activity on at least 5 days each
week (U.S Department of Health and Human Services, 2008). A number of psychological
factors have been proposed that influence motivation to exercise, including enjoyment
(Hardy & Rejeski, 1989), self-efficacy (McAuley & Courneya, 1993), and social
influence (Carron, Hausenblas & Mack, 1996). For instance, group exercise programs
have been shown to lead to higher exercise adherence than individualized programs
(Dishman & Buckworth, 1996). However, group exercise programs may not be helpful
to people whose time conflicts with scheduled exercise programs, those who do not have
the resources, or those who suffer from social physique anxiety (Bain, Wilson, &
Chiakind, 1989). Thus, there is a need to study how the benefits of group motivation can
be used to improve exercise levels despite the problems of time conflicts and social
physique anxiety.

1	
  

The use of a virtual partner is one strategy that could continue the benefits of
having an exercise partner without the limitations of a structured group exercise program
or the potential social anxiety about one’s physique. Preliminary work using a
conjunctive-goal protocol based on motivation gain theory and the Köhler effect has
shown that the use of a virtual partner leads to longer durations of isometric exercise
bouts than exercising alone (Feltz, Kerr, & Irwin, 2010). There is a need to extend this
study to examine the motivation effects of virtual partners in an aerobic activity and over
an extended period of time to determine if these effects have the potential for a significant
cardiovascular health benefit. Therefore, the purpose of this thesis is to examine if the
Köhler motivation gain phenomenon affects the duration of exercise during an aerobic
task.
Background and Theory
According to the American College of Sports Medicine (ACSM), a cardiovascular
exercise program needs to follow general guidelines to ensure maximum safety and
effectiveness. These characteristics are essential for measurable improvements. This is
commonly referred to as the FITT principle and stands for frequency, intensity, time, and
type of exercise. The Centers for Disease Control and Prevention (CDC), the American
Heart Association, and the ACSM recommend adults accumulate at least 30 min a day of
moderate–intensity physical activity on most, preferably all, days per week (1995), for a
total of at least 150 min a week. In 1996, Physical Activity and Health: A Report of the
Surgeon General supported this same recommendation. In order to track the percentage
of adults who meet this guideline, CDC specified that "most" days per week is 5 days and
2	
  

the ACSM defines “moderate” as an intensity of 40% to 60% of an individual’s VO2
maximum or within the 3-5.9 MET range. For cardiorespiratory fitness the ACSM (2000)
recommends exercise/physical work intensities between 55% and 90% of maximum heart
rate (MHR) for at least 20 min, 3 days a week. The ACSM suggests low-fit or
deconditioned individuals may experience improvements at exercise intensities of only
55% to 65% MHR. Skinner et. al. (2004) remarks, “Because ‘quite unfit’, sedentary
subjects are already doing enough activity in their daily lives to maintain a VO2
ventilatory threshold (at levels that are generally greater than 50% oxygen uptake reserve
(VO2R), it is not necessary to reduce the prescribed intensity to 40% VO2R, as
recommended by the ACSM.” Research has shown that aerobic endurance training of
fewer than 2 days a week, at less than 40% to 50 % of VO2R, and for less than 10 min, is
generally not a sufficient stimulus for developing and maintaining aerobic fitness in
healthy adults (ACSM, 1998). The Physical Activity Guidelines for Americans affirms
that it is acceptable to follow the CDC/ACSM recommendation and similar
recommendations (U.S Department of Health and Human Services, 2008).
The question arises, then, as to why exercisers are not acquiring the quality and/or
quantity of exercise prescribed above and what can be done to increase motivation to do
so? For those who run as a form of cardiovascular exercise, having a running partner can
give them the extra motivation to go for a run when they are not feeling up to it and to
run for a longer duration than they might do on their own. Further, those who exercise
with a partner or group are more likely adhere to it long term (Carron et al., 1996;
3	
  

Dishman, Sallis, & Orenstein, 1985). One might feel less apt to quit because of the
partnership established, thus heightening the value of one’s contribution to the group’s
success. Similarly, runners often use what is referred to as a “pacer” when training in
order to improve their time and running quality. The pacer is someone who runs at a pace
at which the runner should be or hopes to be running, in order to achieve incremental
goals. The pacer is often someone who is a slightly more fit and experienced runner who
can maintain the desired speed for the desired duration. The less experienced runner feels
motivated to keep going and to keep up with the more experienced pacer. The motivation
gains that come from running with a partner or a pacer may be explained, in part, by
motivation gain theories.
One motivation gain phenomenon that has application to simple persistence or
endurance tasks, such as running, is the Köhler effect (Kerr & Tindale, 2004; Karau &
Williams, 2003). The Köhler effect has been shown to be most potent under conjunctive
group task demands (Weber & Hertel, 2006) that are defined as where the group’s
outcome is determined by the weakest member’s performance (Steiner, 1972).
The Köhler effect is named after Otto Köhler (1926, 1927), who found that
weaker group members performed better on a conjunctive physical persistence task (i.e.,
doing bicep curls) when paired with stronger coworkers versus working alone. Further,
the effect is most potent when the stronger partner is only moderately more capable than
the weaker one (Weber & Hertel, 2006). This effect has been shown to occur in both
virtual and face-to-face teams and on both physical and cognitive performance tasks
4	
  

(Feltz et al., 2010; Weber & Hertel, 2006). However, previous research regarding
motivation gains and physical performance tasks has not focused on aerobic performance
but almost exclusively on temporary work groups performing only one or two trials in a
single session. The present study not only examines the effect of the Köhler motivation
gain on an aerobic task but also tests its persistence across a number of days and
conditions.
The Köhler effect highlights both social comparison and indispensability
processes. When paired with a more capable partner on a task, the weaker partner may be
more inclined to work harder or to set more challenging goals (social comparison).
Additionally, when one believes one’s effort on a task is highly instrumental, motivation
to perform increases (indispensability). For instance, in a study by Kerr et al., (2007),
participants performed a simple arm-lifting task for a number of trials, where for each
trial the participant held one arm horizontally for as long as possible while holding a 1.45
kg dumbbell. Results showed that participants in the conjunctive task condition exhibited
a robust motivation gain of 33.4 s (i.e., they persisted 33.4 s longer than the individual
controls) and participants in the coactive task condition also exhibited a significant
motivation gain of 19.9 s. Thus, feedback indicating that an independent coactor was
more capable than the participant was sufficient to produce a reliable motivation gain (cf.
Seta, 1982). Lastly, the motivation gain in the conjunctive condition was significantly
larger than the gain in the coactive condition.

5	
  

Research has demonstrated variability in the indispensability and social
comparison explanations of the Köhler effect depending on the type of task group
presented (Hertel, Kerr, Scheffler, Geister, & Messé, 2000; Kerr et al., 2007). Hertel et al.
(2000) compared the performance of a less capable member of a dyad when working
side-by-side at an arm-lifting persistence task under conjunctive task demands (i.e., the
group score was defined by that less capable member’s performance) versus additive task
demands (i.e., the group score was the sum of the dyad’s performances). Researchers
observed a significant motivation gain under conjunctive conditions but not in the
additive conditions.
However, other research has found evidence for the social comparison
explanation (Stroebe et al., 1996). Stroebe et al. (1996) conducted a number of studies
based on their goal comparison approach in which male participants performed a physical
persistence task (turning a hand wheel as fast as possible for 15 min) and received
continuous performance information about a stronger partner during the group trial.
Results showed significant motivation gains in the group trials compared to a workingalone control condition but this effect was unaffected by the structure of the group task.
Whereas Köhler (1926) reported motivation gains in a conjunctive task (the weaker group
member determined the group outcome), Stroebe et al. (1996) reported motivation gains
of inferior group members also during an additive group task (the group outcome is
determined by the sum of the individual contributions) where weaker group members’
performance is not indispensable but can be compensated for by stronger partners. This
result suggests that upward comparison can initiate motivation gains of weaker group

6	
  

members regardless of the relative importance of their individual contribution to the
group outcome.
In terms of the perceived instrumentality of individual effort for the group
outcome, low perceived dispensability of individual contributions to the group leads to a
decrease in effort (Kerr, 1983; Kerr & Bruun, 1983). High perceived indispensability of
personal contributions to the group should lead to additional motivation because this
personal contribution affects not only one’s own outcomes, as during individual work,
but also the outcomes of other group members (Hertel, Niemeyer, & Clauss, 2008). Thus,
motivation gains in a group should be triggered when the consequences of one’s own
performance are perceived as higher or more important in the group when compared to
individual work (Paulus, 1983). This suggests that neither the social comparison
explanation (Seta, 1982; Stroebe et al., 1996) nor the indispensability explanation (Kerr
& Bruun, 1983) alone is sufficient to account for the Köhler motivation gain effect.
However, one can account for the effect by presuming that two mechanisms are at work
separately. It is also important to note that these two mechanisms may work differently in
different task conditions.
Although the Köhler effect has been shown to have an effect on such motor
persistence tasks, little is known about how such motivation gains influence individuals
when presented with an aerobic task and whether or not these gains attenuate over time.
If a participant is always less capable than the partner the participant may be discouraged
about keeping up and lose motivation to try. Lount, Kerr, Messe, Seok, and Park (2008)
examined the persistence of partners on a conjunctive physical persistence task across
multiple trials. They found that working with a single partner who was repeatedly more
7	
  

capable led to smaller motivation gains over time, but still showed motivation gains
compared to the individual control. No research has examined this effect across multiple
days.
Additionally, Feltz et al. (2010) suggested that while exercising conjunctively
with a more capable partner in ad hoc laboratory groups could be motivating, finding an
ideally more capable partner could be difficult and would not be particularly helpful for
the stronger partner. Thus, they investigated the use of a virtual exercise partner to
examine the Köhler motivation gain effect on an abdominal persistence task. Individual
controls were compared to those with a moderately more capable partner in a conjunctive
task condition, a coaction condition, and an additive condition. The researchers found that
motivation gains were significantly greater in all experimental conditions than in the
individual control condition. Thus, results suggested that virtual partners who are
moderately more capable than the exercise participants can improve persistence
motivation. Their finding is practically important because having a virtual partner
overcomes some of the obstacles of finding an optimally-matched partner at a particular
location with whom to exercise.
Contextual Factors
The context chosen for the current investigation was exercise in both individual,
conjunctive, and coactive settings. Individual exercise provides the control condition with
which to study changes in exercise persistence as a result of the presence of others and
the subsequent changes in motivation. Coactive exercise (in dyads) provides a
prerequisite for establishing that a process gain has occurred in a group (Tindale &
Larson, 1992; Todd, Seok, Kerr, & Messé, 2006). When superior group members provide

8	
  

an available comparison standard, upward social comparison should motivate the subject
to exert more effort in the group compared to working alone. Conjunctive exercise
provides a type of interaction where the collective effort of all members is pooled
towards one main goal. Success is dependent on the combined effort of both members in
the dyad.
	
  

Undergraduate women were selected for the purpose of this study for conceptual

reasons and to control for gender differences. While this may limit the generalizability of
the findings, the internal validity is strengthened. Women may also lack motivation to
exercise vigorously compared to men. A longitudinal study conducted based on data
obtained every 2 years from 17,314 men and women who were aged 19 to 26 between
1984 and 2006, examined trends over a 23-year-period in six different health behaviors
(Clarke, O’Malley, Johnston, Schulenberg, & Lantz 2009). One health behavior measured
was how often they exercised vigorously (jogging, swimming, or calisthenics). Results
showed that young women consistently exercised less than young men.
	
  

The current study focuses on an aerobic task because previous research on

motivation gains involving physical tasks has focused almost exclusively on strength
tasks. Unfortunately, little is known about the effects of motivation gains on aerobic
performance. Although thought of as an independent activity, aerobic tasks can be
viewed along a task interdependence continuum with coactive tasks (e.g., running a
marathon) at the low end and highly interactive tasks (e.g., 4x4 track relay) at the high
end.
Purpose of the Study

9	
  

The primary purpose of this study was to examine the effects of the Köhler
motivation gain on the duration of an aerobic task in females using a virtually-presented
partner. This study extends previous research by examining motivation gains on an
aerobic task over several days to understand how exercise duration (at the recommended
intensity) can be increased as a result of changes in motivation.
Hypotheses
Hypothesis 1: Compared to working alone, females increase their effort when working
together with a moderately superior virtual partner under coactive task demands.
H1.a: The benefit (as measured by within-subject duration of exercise) of
exercising with a moderately-more-capable coactor will decline across repeated
exercise sessions.
Hypothesis 2: Compared to working alone, females increase their effort when working
together with a moderately superior virtual partner under conjunctive task demands, and
these motivation gains should be higher than motivation gains under coactive task
demands.
H2.a: The additional benefit of exercising with a moderately-morecapable partner (under conjunctive conditions) will not decline over
sessions.
Secondary Research Questions
In addition, the following exploratory research questions were addressed:
Do ratings of perceived exertion (RPE) in women change in tandem with motivation
gains?

10	
  

Does self-efficacy for aerobic exercise in women change in tandem with motivation
gains?
Does intention to exercise in women change in tandem with motivation gains?
Delimitations
The findings are limited to college women, and thus may not generalize to other
female populations. Additionally, motivation gain effects for women may be different
from effects for men.
Definitions
Borg Scale: a self-selected subjective measurement of an exerciser’s overall level of
intensity- commonly referred to as RPE- described on a scale of 1 to 10 (very easy to
extremely hard).
Coactive Task: individuals work simultaneously without any interdependence or common
outcome (i.e., excluding social loafing).
Conjunctive Task: the group outcome is determined by the least capable member.
FITT Principle: set of guidelines that increase the quality of exercise.
Frequency: how often one exercises.
Intensity: how hard one works during exercise, which is determined by heart rate.
Time: how long one exercises. (i.e., the duration of the task).
Type: the activity that one is doing.
Heart Rate (HR): measured as beats per minute (bpm). HR can be monitored and
measured by taking one’s pulse at the wrist, arm or neck. An approximation of maximum
heart rate (MHR) can also be calculated as follows: MHR = 220 - age. A more accurate
11	
  

method of calculating target heart rate (THR) is using the heart rate reserve (HRR)
method, which takes individual resting heart rate (RHR) into consideration. HRR can be
calculated as follows: HRR = MHR-RHR. For the purpose of this study, RHR for each
subject was calculated using the HRR method prior to Trial 1, in order to find 65% of
their MHR.
Indispensibility: perceived instrumentality of individual effort for the group outcome.
Köhler Effect: when superior group members provide an available comparison standard,
upward social comparison should motivate the subject to exert more effort in the group
compared to working alone.
Self-efficacy: the belief in one’s capabilities to organize and execute the courses of action
required to manage prospective situations (Bandura, 1995, p. 2).
Social Comparison: adjustment of performance to standards provided by their social
environment.

12	
  

CHAPTER TWO
REVIEW OF LITERATURE
The purpose of this chapter is to provide a review of literature that is relevant to
the variables and procedures in this study. This chapter begins with a review of group
motivation research and theory. Next, a review of the Köhler effect as a motivation gain
phenomenon based on conceptual contributions and empirical research is provided. This
is followed by a summary of social factors influencing exercise, including research on
self-efficacy.
Group Motivation Research and Theory
A substantial body of research conducted over the last 30 years has focused on the
consequences for individual task motivation of performing a task collaboratively in a
group. The initial wave of this body of research documented that group performance
contexts are sometimes demotivating (Karau & Williams, 1993). Baron & Kerr (2003)
provide possible causes for this. Compared to individual performers, group members may
(a) feel less personally identifiable and hence, less subject to evaluation; (b) recognize
that in some instances they may be able to free-ride on other group members’ efforts, or
(c) reduce their efforts rather than contribute what they perceive to be more than their fair
share of the collective effort. Although extensive research on motivation losses in groups
is available, empirical demonstrations for the opposite- motivation gains- has only
recently been explored in depth. There is much support for the notion that motivationa
gains can occur in task groups. Hertel et al. (2000) note that the facilitation of
performance of simple, well-learned tasks in the presence of audiences or coactors
13	
  

(Zajonc, 1965) might be counted as a type of group motivation gain if enhanced drive
occurs. There are also a number of studies that suggest that implicit or explicit
competition between members of cooperative task groups can enhance member
motivation and performance (e.g., Erev, Bornstein, & Galili, 1993; Stroebe, Diehl, &
Abakoumkin, 1996). Hertel et al. (2000) states the possibility that the "social facilitation"
effect reported in Triplett's (1897) classic experimental study was due to implicit
competition between children winding fishing reels. Earlier tests of “social facilitation”
by Martens and Landers (1972), found that the debilitating effects of evaluation concerns
on task performance (i.e., a complex motor task) increased as the number of coactors
present increased.
There are a few studies (e.g, Kerr & MacCoun, 1984; Kerr & Sullaway, 1983)
that have suggested that group composition can underlie some group motivation gains. In
these studies, researchers have found higher task motivation by both male and female
participants in mixed-sex groups than in same-sex groups or individual performers. They
attribute this effect to special evaluation concerns arising in mixed-sex interactions. There
is also some evidence that when difficult performance goals have been set, people may
work harder in a group than individually (Matsui, Kakuyama, & Onglatco, 1987).
Two motivation gain phenomena have been studied systematically. The first is the
social compensation effect. When one has reason to doubt that one’s fellow group
members can or will contribute enough to achieve an important group goal, one may
compensate for their low inputs by increasing one’s own effort (Williams & Karau,
1991). Although this effect has been well replicated, it appears to have many necessary
conditions (e.g., collective success must be extremely important, the act of compensating

14	
  

should not be viewed as too inequitable, individual levels of effort must be anonymous).
This suggests that the social compensation effect would be of limited value for enhancing
motivation in aerobic exercise. Therefore, the current study focuses on the second
motivation gain phenomena, the Köhler effect. Köhler’s work is examined in more detail
below.
The Köhler Effect. The Köhler effect was first discovered in the 1920s by the German
industrial psychologist, Otto Köhler. Studying male members of a Berlin rowing club,
Köhler found that dyads could perform a taxing physical task (e.g., doing as many
standing bicep curls as possible) longer than one would expect from knowledge of the
dyad members’ performances at a comparably difficult individual version of the task. The
demands of Köhler’s dyad task meant that the group could persist no longer than its
weaker member and once that weaker member was exhausted and quit, it was impossible
for the stronger member to continue. Such group tasks—where the group’s potential
productivity is equal to the productivity of its least capable member—are commonly
referred to as conjunctive tasks. Köhler demonstrated that weaker members of dyads will
push themselves harder when they are paired with someone stronger in a conjunctive
persistence task. Köhler also found that this motivation gain was moderated by the
discrepancy between partners’ abilities where the motivation gain was largest when this
discrepancy was moderate. When there was either very little discrepancy in the abilities
of the dyad members or a very large discrepancy, the dyads did worse than the average
member, whereas for moderate levels of discrepancy, the dyads did better than the
average member. Köhler took the latter result as evidence for a group motivation gain.

15	
  

Subsequent research suggests that the conjunctive nature of Köhler’s (1926, 1927)
task is a crucial feature of this work context, and, as such, it differentiates his effect from
Triplett’s (1898) social facilitation phenomena, another type of potential motivation gain.
In social facilitation, the mere presence of others (as coactors or an audience) can
motivate individuals to try harder. Research indicates, however, that the motivation gains
that the weaker coworker on a conjunctive task displays are not due to the mere presence
of others and, thus, are not a product of social facilitation. For example, Hertel et al.
(2000) found that the less able worker tried significantly harder under conjunctive task
demands (i.e., the group score was defined by that less capable member’s performance)
than under additive task demands (i.e., the group score was the sum of the dyad’s
performances), even though exactly the same number of people were present in both
conditions. Task conjunctivity, in addition to the coworkers’ differential abilities, also
distinguishes the Köhler effect from social compensation (e.g., Williams & Karau, 1991).
Köhler’s (1926, 1927) original study has been replicated several times in various
domains. Stroebe et al. (1996) successfully replicated the effect using Köhler's original
lifting task. Dyads did better than their average (Köhler's original baseline) and their less
capable member (the appropriate baseline for detecting motivation gains) when there was
a relatively large discrepancy in abilities. As a version of Köhler’s second task, in another
series of experiments, Stroebe et al. (1996) had participants turn a crank (with a
mechanical brake) as fast as possible for 10 min. On all trials, participants worked in
separate rooms. To capture the conjunctive aspect of Köhler's task, participants were told
that unless the turning speeds of the two dyad members were sufficiently close to one
another, a penalty would be assessed. A computer screen continuously displayed the

16	
  

discrepancy in turning speeds between dyad members on dyadic trials. Dyads generally
did better than isolated individuals, and in one study, motivation gains relative to the
weaker-member baseline were positively related to the discrepancy between group
member's individual performances.
More recent attempts to replicate and explain the Köhler effect (Hertel et al.,
2000; Hertel, Kerr, Scheffler, et al., 2000; Lount, Messé, & Kerr, 2000) have yielded
similar findings. In these studies a paradigm was used that incorporated most of the basic
features of Köhler’s original procedure but that was also more efficient and afforded less
risk of pain or injury to participants than did Köhler’s task. In this new procedure,
participants held their arms extended above a trip-alarm device for as long as they felt
they could without experiencing undue distress or risking injury. The researchers made
this task more difficult either by having the workers hold a metal bar or by attaching a
weighted band to their wrist. In the individual condition, the task ended whenever the
participant lowered his or her arm far enough to trigger the alarm. In the group condition,
conjunctive task demands were created where the task was over when either of two
coworkers did so. Hertel et al. (2000) explains the most important advantage of this new
task over Köhler’s original task is that successful performance of the revised task requires
minimal inter-individual coordination and therefore one can assume that effort and output
increase and decrease in the same manner.
Using this paradigm in five studies (Hertel et al., 2000, Experiments 1 and 2;
Hertel, Kerr, Scheffler, et al., 2000, Experiments 1 and 2; Lount et al., 2000), Messé et al.
(2001) examined people’s performance under both individual and conjunctive task
demands (i.e., in which the less able participant’s score determined how well the team

17	
  

did). Across all studies, the researchers consistently found significant motivation gains
for the weaker coworker, with average performance increases in group trials compared
with individual trials ranging between 10% and 50%. Similarly, Weber & Hertel’s (2007)
meta analysis (17 studies, N = 2, 240) results indicated that the overall motivation gain
effect of weaker group members is moderate and significant (g .60). While the Köhler
motivation gain has been examined in motor tasks, such as the ones described previously,
and cognitive tasks (Hertel, Deter & Konradt, 2003; Lount & Phillips, 2008; Wittchen et
al., 2008), the Köhler motivation gain has never been examined in an aerobic task, which
is the goal of the current study.
Mechanisms underlying the Köhler Effect.
Social comparison processes. Recent research (e.g., Kerr et al., 2007) reveals that there
are at least two mechanisms underlying the Köhler effect. The first stresses social
comparison processes. When confronted with a more capable partner or coacter on an
ambiguous but valued task, the weaker partner may revise his/her personal performance
goal upward. An alternative explanation suggests that doing as well or better than the
partner becomes a salient goal. Although there are interesting differences between the
two explanations—goal-setting version and intragroup-competition version—both
explanations hold that it is the opportunity for performance comparison that is critical for
the phenomenon. Such opportunities can arise even when performers are not actually
working together as a group (e.g., when they are coacting, i.e., two people exercising in
one another’s presence). In a recent study, Sambolec, Messé, and Kerr (2007) observed
significant motivation gains in both conjunctive and coactive work conditions but there
was no significant difference in the magnitude of these gains. This pattern implied that

18	
  

social comparison (equally possible in both work conditions) might be sufficient to
explain the Köhler motivation gain effect. However, there is evidence in support of
instrumentality as a mechanism underlying the Köhler effect.
Indispensability. The second mechanism stresses the indispensability of one’s efforts for
one’s group. As instrumentality and value models of motivation suggest (e.g., Karau &
Williams, 1993; Shepperd, 1993; Vroom, 1964), task motivation is likely to be enhanced
when one sees one’s efforts as being highly instrumental—i.e., indispensable—in
achieving highly valued outcomes. This suggests that task conditions that increase
instrumentality will increase motivation. Under conjunctive task conditions, the group’s
performance is highly contingent on the weaker member’s effort—i.e., the weaker
member’s efforts are indispensable for group success. Note that such contingencies
depend largely on the demands of the task—in particular, it is the conjunctive nature of
the group task that makes the weaker member’s efforts particularly indispensable. One
way of competitively testing these two generic explanations is to vary how indispensable
the weaker member’s efforts are (Steiner, 1972). Hertel, Kerr, Scheffler, et al. (2000,
Experiment 2) utilized this approach when they compared the performance of the less
capable member of a dyad when working side-by-side at an arm-lifting persistence task
under conjunctive task demands (i.e., the group score was defined by that less capable
member’s performance) versus additive task demands (i.e., the group score was the sum
of the dyad’s performances). Results indicated that this motivation gain occurred under
conjunctive but not under additive task demands, suggesting that the instrumentality of
one's contribution to valued outcomes is a more likely explanation of the Köhler effect
than social comparison processes.

19	
  

Hertel, et al. (2008) also showed support for the importance of instrumentality. In
a study involving computer-supported dyads without face-to-face contact, based on
previous research on the Köhler effect (Hertel et al., 2000), the researchers expected high
motivation of group members when their individual effort was highly instrumental for the
group’s success. Consistent with their expectations, motivation of the group members
was high and even exceeded the baseline of individual work (thus revealing motivation
gains) when the individual’s contribution was highly instrumental for the dyad’s success
(i.e., weaker coworker under conjunctive task demand). When instrumentality was low
(i.e., weaker coworker under additive task demand), inconclusive results were obtained.
This lends support to the importance of instrumentality as an underlying mechanism of
the Köhler effect and indicates that motivation gains can be produced in computersupported dyads, even without face-to-face interaction. This indication is of particular
relevance to the current study, as two of its conditions are computer-supported dyads. If
motivation gains in groups can be shown on an aerobic task using computer-supported
dyads, the implications for exercisers and the health games industry could be of great
value.
Earlier work often contrasted upward comparison and social indispensability as
alternative explanations for motivation gains of inferior group members (e.g., Hertel et
al., 2000; Hertel, Kerr, Scheffler, et al., 2000). However, recent work has emphasized that
these different motivation mechanisms are not necessarily mutually exclusive but can be
complementary (Hertel et al., 2008; Kerr et al., 2007; Lount, et al., 2000). For instance, a
person might both try to maximize the group outcome (pursuing collectivistic goals) and
try to outperform the coworker (pursuing individualistic goals) at the same time.

20	
  

Therefore, upward comparison and social indispensability processes may be active
simultaneously and the relative strength of the processes being determined both by
situational factors (e.g., norms, task structure) and by the personality of the individual
(e.g., need for achievement, need for affiliation). It is important to note that these two
mechanisms may work differently when moderated by other variables.
Potential moderators of group motivation gains. There are many potential factors that
moderate the effects of group motivation gains discovered in recent research. A metaanalysis (17 studies, N= 2,240) conducted by Weber and Hertel (2007) included a
moderator analysis, which revealed the following moderators: task structure, physical
presence, gender, performance information, and task type. Results indicated that the
overall motivation gain effect of inferior group members observed is moderate and
significant (g .60). Recently, social ostracism has also been explored as a potential
moderator of group motivation gains (Kerr et al., 2008).
Task structure. Additive task conditions (i.e., the group score is the sum of the dyad’s
performances) support the social compensation theory and therefore promotes outcome
interdependence between partners. Kerr et al. (2008) state that “previous failures to
observe significant motivation gains with invidious social comparison under additive task
conditions (e.g., Hertel et al., 2003; Hertel et al., 2000) may plausibly be attributed to
other motivation processes (e.g., free riding on one’s partner) obscuring this social
comparison effect” (p.832). The notion of “free riding on one’s partner” is often referred
to as social loafing. Under additive task conditions, less capable members might
anticipate that stronger members will compensate for their poorer performance and
therefore will “free ride” on the stronger members’ efforts (Kerr, 1983; Williams &

21	
  

Karau, 1991). Kerr et al. (2007) speculates that this social loafing effect could counter
and possibly eliminate any motivation gains due to social comparison. To avoid such
ambiguities, the current study will use a conjunctive condition, where one’s more-capable
peer will be a teammate and the group score will depend entirely on one’s own level of
performance in addition to a coactive condition where social comparison is just as
possible but without the outcome interdependence that occurs with additive task
conditions.
Physical presence. Another potential moderator of motivation gains is the physical
presence of group members. The growing number of computer-mediated forms of group
work (e.g., Hertel et al., 2005) emphasizes the importance of investigating the effects of
physical presence on motivation. Recent studies have demonstrated that working face to
face leads to significantly higher effort increases in the weakest group member compared
to working with physically absent partners (Hertel et al., 2008; Lount et al., 2007). Lount
et al. (2007) examined whether increasing evaluation concerns would increase the
magnitude of the Köhler effect. Evaluation concerns were manipulated by having
participants work in the physical presence or virtual presence of their coworker. Results
showed that motivation gains were significantly greater for participants who worked in
the physical presence of their coworker, which suggests that evaluation concerns can
potentially increase the magnitude of the Köhler effect. It has also been found that a
moderate discrepancy in ability between partners has been shown to be optimal for
producing the motivation gain (Feltz, Irwin, & Kerr, 2010; Koehler, 1927; Messé et al.,
2002). Messé et al. reported that the Köhler motivation gain effect is smaller when one’s
more capable partner is either only slightly more capable or extremely more capable than

22	
  

oneself. Feltz et al. found similar results with a virtually-presented partner in a health
games context.
Apart from the effects of the mere social presence of others (e.g., Zajonc, 1965),
positive effects of physical presence can also be caused by impression management or
self-presentation concerns (Tedeschi & Rosenfeld, 1981; Tedeschi, Schlenker, &
Bonoma, 1971). When other individuals are physically present, the social consequences
of being the weaker person should be more noticeable because evaluative feedback is
more likely (Carron, Burke, & Prapavessis, 2004). These effects are relevant both for
social comparison and for social indispensability processes. Being the weaker person in a
social competition should be more harsh when an individual is visible to others and can
see their reactions as compared to spatially distributed groups (Hertel et al., 2008; Lount
et al., 2000). Similarly, social sanctions (e.g., stigmatization, exclusion) for holding the
group back when personal effort is indispensable should be more aversive with a
physically present, compared to an absent, coworker (Hertel, Kerr, Scheffler, et al.,
2000). Such findings have interesting implications for the use of computer-supported
exercise and virtual exercise partners by those who’s lack of exercise motivation or
aversive feelings towards exercise stem from such things as social physique anxiety or
low self-efficacy.
Moreover, significant motivation gains have been repeatedly demonstrated under
conditions where participants did not meet or know their partner (e.g., Hertel et al.,
2003). In line with these findings, research on social facilitation has reported effort
increases when other people were not physically but electronically present in
brainstorming groups (e.g., Aiello & Kolb, 1995; Aiello & Svec, 1993). Even under

23	
  

conditions in which participants worked together with individuals who were neither
physically nor electronically present, such effort increases have been documented (e.g.,
Dashiell, 1930; Feinberg & Aiello, 2006), and as a result the current study aims to
discover whether the use of a virtual partner during an aerobic task supports such
findings.
Gender. Previous research on motivation gains in groups predominantly pursued a
situation-based approach, exploring factors such as task structure or the presence of
coworkers as determinants of different underlying mechanisms. However, the motivation
impact of these factors might be additionally moderated by personality factors such as a
person’s gender. Past studies suggest that there might be gender differences in the relative
importance of both the indispensability and social comparison explanatory processes. A
recent experiment by Kerr et al. (2007) confirms this suggestion. In one of their
experiments, gender difference was eliminated by priming women with a goal (viz.,
competition) thought to be consistently more important to men. Kerr et al. (2007) argue
that the relative importance of these two motivation processes will depend on the
immediate and chronic importance attached to more personal (viz., to achieve a favorable
social comparison) versus collective (viz., to contribute to one’s group) goals.
Gender has also been proven to be a moderator of motivation losses. For example,
studies on free riding (Brown-Kruse & Hummels, 1993; Nowell & Tinkler, 1994) and the
“sucker effect” (i.e., a particular form of social loafing that stems from the perceptions
that others in the group are withholding, or intend to withhold, effort. Individuals who
hold this perception then withhold effort themselves to avoid being played for a "sucker")
(Kerr, 1983), documented higher motivation losses for male than for female group

24	
  

members. Similarly, Karau and Williams (1993) observed gender as a moderator in their
meta-analysis of social loafing, showing higher levels of social loafing for male
participants than for female. Potential explanations for these gender effects are related to
general differences in social orientations. Women often show a more interdependent,
relational tendency, and attach more value to the welfare of others (Schwartz & Rubel,
2005) while men prove to be more independent, assertive, and attribute more value to
social status and strive to control or dominate other people (e.g., Costa, Terracciano, &
McCrae, 2001; Schwartz & Rubel, 2005, Suh, Moskowitz, Fournier, & Zuroff, 2004).
These gender differences in collectivistic versus individualistic orientations might
explain why women are less likely to reduce their efforts for the group and to engage less
in social loafing (Karau & Williams, 1993, 2001). For similar reasons, these gender
differences might also moderate motivation gains in groups. Given that men are driven
more strongly by individualistic motives, such as being better than others, they should be
more likely to react on the basis of social comparison regardless of the consequences for
the group outcome. In contrast, given that women more often act on the basis of
collectivistic orientations (e.g., maximizing the group outcome), they should be more
sensitive to social indispensability. Recent studies with both female and male participants
provided evidence for both processes (e.g., Hertel et al., 2008; Kerr et al., 2007; Wittchen
et al., 2009). However, contradictory findings on motivation gains of weaker group
members have been found (e.g., Stroebe et al., 1996). The fact that Stroebe et al. found
evidence only for upward comparison effects in their studies might have been due to their
participants being solely male. In contrast, the experiments by Hertel et al., (2000),
providing evidence for social indispensability effects included predominantly female

25	
  

participants. Because the current study is not focused on gender differences and the
motivation gain mechanisms separately, only female participants will be included in
order to control for the potential moderator variable.
Availability of partner-related performance information. Another potential moderator
of motivation gains of weaker group members is the information that is available about
the other group members’ performance. This moderator can affect both social comparison
and social indispensability processes. When information about a partner’s current
performance is available continuously during group work, this permanently updated
comparison standard facilitates comparison processes (e.g., Seta, 1982; Stroebe et al.,
1996). This in turn might lead to greater motivation gains compared to conditions in
which such feedback is either not provided at all or only once during or after a group trial
(Hertel et al., 2008; Kerr et al., 2005).
Similarly, partner-related performance information can affect indispensability
perceptions, particularly during conjunctive tasks. When partner-related performance
information is available continuously, weaker group members can constantly verify
whether they are holding the group back or not. This should highlight the indispensability
of their efforts for the group and thus should increase the efforts of the weaker group
members compared to conditions in which partner-related performance information is not
continuously available. Of course, this is true only if the available information indicates
that the weaker group member is indeed holding the group back. Taking this into
consideration, the current study includes a manipulation of the speed of the virtual partner
(viz., the virtual partner will always be riding slightly faster than the subject) in the
conjunctive condition, thus providing the subject with constant partner-related

26	
  

performance feedback by enabling the subject to constantly see their partner riding ahead
of them on the screen. However, in the current study, researchers will not provide the
subject with any actual information regarding their partner’s ability prior to each ride nor
with a means of communicating directly with their partner.
The lack of continuous partner feedback does not necessarily debilitate
continuous upward comparison or indispensability effects because the knowledge that
one might currently be the weaker person or might be holding the group back could be
sufficient to trigger additional effort. Using a short physical persistence task (about 2–3
min each trial), Kerr et al. (2005) found motivation gains when partner-related
performance feedback was given after the group trial even though these gains were
significantly lower than in conditions with continuous partner feedback. However, in a
study using a cognitive maximizing task that lasted somewhat longer (20 min each trial),
motivation gains occurred only when partner feedback was continuously available and
not when partner feedback was promised after the group trials (Hertel et al., 2008). Thus,
motivation gains of weaker group members seem to be rather fragile when partner-related
performance feedback is not continuously available.
While the potential effects of partner-related performance information have been
discussed with respect to implications of information about another person in the group it
is important to note that feedback can be bidirectional- participants not only receive
feedback about other individuals’ performance but also expect that the other individuals
are continuously informed about the participants’ performance level. This permanent
identifiability of personal contributions might also increase efforts and work on social
loafing has documented that the identifiability of individual contributions decreases the

27	
  

tendency to loaf (Karau & Williams, 1993). This could be because the individual has less
opportunity to hide in the crowd (Davis, 1969), so that the risk of being identified for
poor performance is increased, or because the individual feels less lost in the crowd
(Latane´, Williams, & Harkins, 1979), so that high individual efforts are more likely to be
noticed and rewarded. Moreover, research on brainstorming groups documented that
group members reduced their effort and performance if their contributions were not
identifiable and could not be evaluated (Diehl & Stroebe, 1987), while explicit feedback
during the task enhanced performance in electronic brainstorming groups (e.g., Jung,
Schneider, & Valacich, 2005; Paulus, Larey, Putman, Leggett, & Roland, 1996; Roy,
Gauvin, & Limayem, 1996; Shepherd et al., 1996). The current study will not explicitly
state to participants in the conjunctive and coactive conditions that their partner can see
them while riding however, because participants will be able to see their partners on the
screen and monitor their progress it is likely that they will assume that their own progress
is identifiable by their partners thus, motivation gains are expected.
Social ostracism. Kerr et al., (2008) examined the effect of being ostracized by one’s
work partner on the Köhler motivation gain. Such ostracism weakened but did not
eliminate the Köhler motivation gain. Ostracism only had such an effect when subjects
worked in a group and not under coactive work conditions. This finding indicates that
social ostracism does not seem to affect the social comparison mechanism (viz., when the
coactor had previously ostracized the subject, the subject was no more or less willing to
use the ostracizers’ performance as a basis for social comparison). But ostracism did
attenuate the indispensability mechanism, which depends on working together in a group.
Researchers speculate that being ostracized reduced the value that one attached to the

28	
  

group’s success or to teammates’ evaluation. Conclusively, Kerr and his colleagues also
argue that social ostracism can undermine group members’ concern for group success or
for protecting their reputation in the group without affecting the social comparison
processes that also contribute to the Köhler effect.
Social Factors Affecting Exercise
There are a number of social and psychological factors that influence motivation
to exercise (Franzini, Elliott, Cuccaro, & Schuster, 2009; USDHHS, 2008). These include
social support from health professionals, family, and friends (Coleman, Cox, & Roker,
2008; Zakarian, Hovell, Hofstetter, Sallis, & Keating, 1994), social modeling of physical
activity (Feltz & Riessinger, 1990; Fox, Rejeski, & Gauvin, 2000), other exercise
participants (Carron, et al., 1996) group exercise programs (Dishman & Buckworth,
1996), and access to and convenience of exercise facilities (Sallis, Hovell, Hofstetter et
al., 1990). Additionally, enjoyment of physical activity and self-efficacy for overcoming
exercise barriers have consistently been linked to exercise adherence (McArthur &
Raedeke, in press; McAuley, 1993; Sallis, Prochaska, Taylor et al., 1999). However, the
relationship between efficacy beliefs and task effort is not always positive (Bandura &
Jourden, 1991; Eyal, Bar-Eli, Tenebaum, & Pie, 1995). Feltz, Short, and Sullivan (2008)
suggest that a more moderate level of self-efficacy may enhance motivation to practice
motor tasks.
Research also suggests that some social environments are more appropriate for
fostering motivation and quality exercise experiences. For example researchers have
consistently found that group exercise leads to higher exercise adherence than individual
exercise programs (Dishman & Buckworth, 1996). Specifically, group exercise programs

29	
  

are related to higher enjoyment and levels of social support as well as to increase
intentions to continue exercising and opportunities for comparison with others. However,
structured group exercise programs present a problem for those with social physique
anxiety (Bain et al., 1989) and those who lack the time and/or resources to join an
exercise group. Moreover, prior models of group exercise rarely if ever introduce any real
interdependence between exercisers (e.g., create teams whose
progress and or outcomes are mutually determined), which the current study aims to
address.
Self-Efficacy and Exercise
Motivating people to do regular physical exercise depends on several factors; the
belief in one’s capability to perform is an important factor. Perceived self-efficacy has
been found to be a driving force in forming intentions to exercise and in maintaining the
practice for an extended time (Dzewaltowski, Noble, & Shaw, 1990; Feltz & Riessinger,
1990; McAuley, 1992, 1993; Shaw, Dzewaltowski, & McElroy, 1992; Weinberg, Grove,
& Jackson, 1992; Weiss, Wiese, & Klint, 1989). A series of experiments on the role of
self-efficacy on muscular tasks has shown that endurance in physical performance
depended on efficacy beliefs that were created (e.g., Weinberg, Gould & Jackson, 1979;
Weinberg, Gould, Yukelson & Jackson, 1981; Weinberg, Yukelson, & Jackson, 1980).
The relative importance of self-efficacy to exercise motivation is the reason the current
study included self-efficacy as a dependent variable.
Self-efficacy is the “belief in one’s capabilities to organize and execute the courses
of action required to produce given attainments” (Bandura, 1997, p. 3). Given sufficient
motivation to engage in a behavior, it is a person’s self-efficacy beliefs that determine
whether that behavior will be initiated, how much effort will be expended, and how long
30	
  

effort will be sustained in the face of obstacles and aversive experiences (Bandura, 1997).
Moreover, individuals who perceive themselves as highly efficacious activate sufficient
effort that, if well-executed, produces successful outcomes, whereas those who perceive
low self-efficacy are likely to cease their efforts prematurely and fail on the task
(Bandura, 1986, 1997). This assertion was tested in the current study by comparing task
self-efficacy scores with duration at THR.
Research pertaining to self-efficacy and perceived effort has been more imminent.
McAuley and Courneya (1992) examined 88 middle-aged sedentary participants and
measured their perceptions of their ability to ride a cycle ergometer at 70% of agepredicted MHR for gradually increasing periods of time. Results indicated that a strong
sense of self-efficacy resulted in participants perceiving themselves to have exerted less
effort than those with a lower sense of self-efficacy. After controlling for fitness, body
fat, age, gender, and affect, pre-exercise self-efficacy accounted for 3.1% of the variance
in RPE at the conclusion of the protocol. Rudolph and McAuley (1996) reported similar
findings in a sample of 50 young men who ran on a treadmill at 60% VO2 max for 30
min. After controlling for VO2 max, pre-exercise self-efficacy accounted for 14% of RPE
variance in the final minute of the protocol. This finding was later replicated with teenage
girls by Pender, Bar-Or, Wilk, and Mitchell (2002), where pre-exercise self-efficacy
accounted for 13.5% of the variance in average RPE collected at 4-min intervals during a
20-min bout of cycle ergometry at 60% VO2 peak.
McAuley (1991) examined self-efficacy, attributional, and affective responses in
middle-aged adults at the mid-point of a 5-month exercise program. Results showed that
self-efficacy had a significant and direct effect on exercise-related positive affect.

31	
  

Another study conducted by McAuley, Schaffer, and Rudolph (1995) examined the
relationship between self-efficacy and affective responses to 10 min (or less) of acute
exercise in male patients at a Veterans Administration Medical Center. Results indicated
that older subjects’ self-efficacy levels increased pre- to post-exercise, whereas younger
subjects demonstrated no improvement. No changes in positive or negative affect were
found in either group as a function of participation in acute aerobic exercise. Although
exercise did not produce changes in efficacy in the younger group, and the findings for
affective changes were negative, relationships between efficacy and affect emerged.
McAuley et al. (1995) reported that high pre-exercise self-efficacy was significantly
related to increased positive affect and decreased negative affect during exercise.
Researchers also concluded that those individuals who possessed high positive affect and
low negative affect during exercise were more likely to experience increases in postexercise self-efficacy.
In another examination of the influence of self-efficacy on affective responses to
exercise, Bozoian, Rejeski, and McAuley (1994) compared high and low self-efficacy
group's affective responses to an acute bout of exercise consisting of a 7 min warm-up
and 20 min of cycling at 70% of estimated maximal capacity. They reported that females
with high levels of pre-exercise self-efficacy had greater feelings of positive affect both
during and following acute exercise compared to their less efficacious counterparts. Such
results show the important role of efficacy beliefs in how one feels about exercise—both
during and after. This may also imply that enhancing one’s self-efficacy may lead to
more positive feelings about exercise and exercise ability and therefore motivate them to
persist while exercising or engage in exercise more often.

32	
  

Recent research by Hall, Ekkekakis, and Petruzzello (2005) indicated that the
relationship between perceived effort and self-efficacy might be intensity-dependent.
Self-efficacy was measured on a 100-point scale at regular intervals during three 15-min
treadmill runs: one 20% below; one at; and one 10% above the ventilatory threshold
(VT). Results indicated that self-efficacy produced consistently negative correlations with
RPE below and at the VT, but no significant correlations were observed at intensities
above the VT. These findings are consistent with the “dual-mode model” of exerciseinduced affective responses (Ekkekakis, 2003).
According to Ekkekakis’ model, affective responses to exercise are jointly
influenced by two interacting factors: interoceptive cues (e.g., respiratory or muscular)
that can reach the affective centers of the brain directly, via subcortical routes, and
cognitive factors (including self-efficacy) that are mediated by the frontal cortex. The
balance between these two determinants is said to shift as a function of exercise intensity,
with cognitive factors being dominant at low intensities and interoceptive cues gaining
importance as intensity approaches the individual’s functional limits, due to the overriding influence of interoceptive factors (Ekkekakis, 2003). It is possible however, that
certain cognitive cues may be especially salient as intensity increases and interoceptive
cues take over. The current study aims to address whether such cognitive factors as
motivation do emerge and affect duration of an aerobic task when intensity is set at a
moderately vigorous level.
A better understanding of the efficacy belief-effort relationship can be gained
through experimental manipulation of self-efficacy. Weinberg and his associates
(Weinberg et al., 1979; Weinberg et al., 1981; Weinberg et al., 1980) conducted a series

33	
  

of studies designed to test the predictions of self-efficacy theory in a competitive, motorperformance situation. Self-efficacy was manipulated by having participants compete
against a confederate on a muscular leg-endurance task where the confederate was said to
be either a varsity track athlete who exhibited higher performance on a related task (low
self-efficacy group) or an individual who had a knee injury and exhibited poorer
performance on a related task (high self-efficacy group). To create aversive
consequences, the experiment was rigged so that participants lost in competition on the
two muscular leg endurance task trials they performed (Weinberg et al., 1981). The
results of these studies supported self-efficacy predictions with the high self-efficacy
participants tolerating the task significantly longer than low self-efficacy participants.
Differences in self-efficacy and perceptions of aches and exertion was explored in a
study by Hutchinson, Sherman, Martinovic, & Tenenbaum (2008). The results of their
study demonstrated that increased self-efficacy leads to improved tolerance of an exerting
task (viz. hang grip task). Participants in the high efficacy group were able to tolerate the
handgrip task an average of 40s (23%) longer than participants in either the low efficacy
or control group following the manipulation. Researchers concluded that self-efficacy
manipulation lead to differential perceptions of aches, exertion, and affect during acute
exercise bouts. Specifically, increased self-efficacy leads to lower perceptions of aches
and exertion, and an enhanced affective response to exercise. This latter finding is
consistent with McAuley, Talbot, and Martinez’ (1999) findings where participants
assigned to a high-efficacy manipulation condition reported more positive affect and less
negative affect than those assigned to a low-efficacy manipulation condition. Perceptions
of pain and discomfort can act as barriers to exercise initiation and maintenance. In

34	
  

addition, positive affect plays an important role in the motivation for exercise (Scanlan &
Simons, 1992). Thus, self-efficacy interventions that improve the affective experience of
the exerciser are likely to also have the potential to enhance exercise adherence. Although
the current study did not manipulate self-efficacy, in order to test such assertions, the
variables of task, comparison, and regulatory self-efficacy were included in addition to an
exercise intention measure at the end of the study.
Although previous research has shown that participants with high self-efficacy
tolerate certain tasks for longer, have more positive affect, and have lower perceptions of
aches and exertion than participants with low self-efficacy, there is also a possibility that
high self-efficacy participants could show a poorer performance than low self-efficacy
participants. High self-efficacy participants might feel complacency or overconfidence
for their task performance (Stone, 1994; Vancouver, Thompson, Tischner, & Putka,
2002) and, as a result, they might not increase their effort substantially. Additionally, low
self-efficacy participants might show greater motivation gains than their high selfefficacy counterparts to prove their capability. For example, high self-efficacy
participants may not feel the need to prove themselves because of the favorable
performance feedback given to them through the self-efficacy manipulation while low
self-efficacy participants may feel that they have something to prove being the weaker
link or because they did not receive favorable performance feedback.
In an unpublished thesis by Seok (2004), subjects performed a task twice on their
own and then worked in a dyad with conjunctive task demands in subsequent trials and
were given feedback on partner’s performance during the preceding two trials (suggesting
partner slightly, moderately, or much superior to subject). Self-efficacy was manipulated

35	
  

via feedback about the subjects first two solo performances where high self-efficacy
feedback indicated that it was very likely that the subject could perform well on the
upcoming trials and low self-efficacy feedback indicated that is was not likely that the
subject could perform well on the upcoming trials. Results suggested that participants
showed greater motivation gains when they had low self-efficacy than when they had
high self-efficacy and this effect was strongest under a moderate level of perceived
discrepancy. However, even though there were significant motivation gains in all the high
self-efficacy conditions and all the low self-efficacy conditions, researchers concluded
that low self-efficacy participants exerted extra effort when they had a moderate
discrepancy (and, to a lesser degree, when they had a large discrepancy). The researchers
note that these results do not indicate that high self-efficacy is a detrimental factor of task
performance but rather; low self-efficacy could have motivating effects on task
performance.
Summary
Köhler’s (1926, 1927) early experimental work documented a genuine group
motivation gain effect. Both Köhler’s experimental work and subsequent research have
shown motivation gains in physical motor tasks. Köhler found that weaker group
members performed better on a conjunctive physical persistence task (i.e., doing bicep
curls) when paired with stronger coworkers versus working alone. Further, the effect is
most potent when the stronger partner is only moderately more capable than the weaker
one (Weber & Hertel, 2006). The Köhler effect highlights both social comparison and
indispensability processes. When paired with a more capable partner on a task, the
weaker partner may be more inclined to work harder or to set more challenging goals

36	
  

(social comparison). Additionally, when one believes one’s effort on a task is highly
instrumental, motivation to perform increases (indispensability). The relative importance
of self-efficacy to exercise motivation is the reason the current study included selfefficacy as a dependent variable. A series of experiments on the role of self-efficacy on
muscular tasks has shown that endurance in physical performance depended on efficacy
beliefs (e.g., Weinberg, Gould & Jackson, 1979; Weinberg, Gould, Yukelson & Jackson,
1981; Weinberg, Yukelson, & Jackson, 1980).
With current research indicating that most American adults do not meet the
recommendations for physical activity, it is important to understand whether such
influences as motivation gains and variables as self-efficacy can enhance exercise
adherence and persistence and under what conditions.

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CHAPTER THREE
METHOD
Participants
Fifty-eight female students from Michigan State University participated in the
study; some participants received extra credit, an excused absence, or a class absence
erased, while others participated simply on a volunteer basis. Subjects were 75.9%
Caucasian, and the majority of the subjects rated their current fitness level as average
(44.8%) or good (32.9%). Sample size was determined from a power analysis conducted
by the researchers, which followed f index recommendations and suggested that a
moderate (f=.30) Köhler effect with probability > .80 could be observed with this sample
size.
Participants were recruited through various kinesiology classes. After an
explanation of what would be expected of them, researchers gave female students the
opportunity to sign up for the study by providing their names and email addresses.
Students were later contacted and asked to complete the Physical Activity Readiness
Questionnaire (PARQ) if they were still interested in participating in the study. Exclusion
from the study was based on answers to the PARQ and current fitness level. Current
fitness level was included in the demographics questionnaire and was assessed with two
items: “How would you rate your personal fitness level?” and “How many times per
week do you exercise for 30 continuous minutes or more at a moderate to high intensity.”
Seven students who were categorized as “highly active” (continuous minutes or more of
exercise at a moderate to high intensity more than 7 times a week) were excluded from
the study because it was assumed that if they were highly active individuals it was likely

38	
  

that they were highly motivated in regards to exercise, which was not the specific target
group the study was designed to address.
Research Design
There were two experimental conditions (coaction and conjunctive) in addition to
an individual control condition. Participants were randomly assigned to one of the three
conditions after their baseline Trial 1. The research design was a 3 x 6 (Groups x Time)
factorial design with repeated measures on the second factor.
Task. The Expresso Fitness Bike is an innovative stationary bike that provides interactive
workouts with its computer-supported screen that enables participants to ride various
outdoor terrains virtually. Personalized training features help individualize programs,
courses, races, and intensity while tracking progress and storing individual information
such as time, calories burned, average power output, average HR, etc. For the purpose of
the study, duration, power output, and HR were the main features of importance. All
subjects rode the same course for all trials. For all three conditions—individual control,
conjunctive, and coactive—each individual rider’s intensity level was predetermined on
the Expresso fitness bike based on the bike gear they were able to ride at and reach 65%
MHR while maintaining 70 RPMs during a specified amount of time (3 min)
Measures
Demographic Questionnaire and Physical Activity Readiness Questionnaire (PARQ).
A demographic questionnaire was used to collect background information from all
participants. Participants were asked to complete the demographics questionnaire and the
PARQ using Surveymonkey at least 24 hours prior to Time 1. General information, such
as age and year in school, was collected. In addition, participants were asked to provide

39	
  

information about their perceived aerobic fitness level with the question, “How would
you rate your personal fitness level?” on a 5-point scale (poor, below average, average,
good, excellent); their exercise habits with the question, “How many times per week do
you exercise for 20 minutes or more doing an activity that makes you sweat/breath
hard?”; and whether or not they cycle for regular exercise. They were also asked to report
their RHR, which was explained to them in the demographics questionnaire. The PARQ
consisted of seven items regarding any physical health condition (e.g., heart condition,
joint problems, or medication) that may prevent them from safely participating in the
study. This was used as a screening instrument for participation. If a participant answered
“yes” to any one of the seven items on the PARQ they were automatically excluded from
the study.
Diet. At the beginning of each trial, each participant completed a one-item questionnaire
asking her to recall, to the best of her ability, what she ate and drank in the past 24 hours.
In order to control for diet/nutrition, participants received instructions/reminders not to
modify their eating patterns every time they were notified of an upcoming trial for which
they were signed up. In addition, during each trial, participants were provided water by
the researchers. All participants received the same size water bottle with the same amount
of water for each trial.
Self-efficacy measures. Three measures of self-efficacy were assessed: task self-efficacy,
comparison self-efficacy, and regulatory self-efficacy. Task self-efficacy and comparison
self-efficacy were measured according to Bandura’s (2006) guidelines and included
efficacy ratings for persistence at the task and persistence in comparison to one’s partner.
Specifically, the task self-efficacy measure consisted of 12 items that asked participants

40	
  

to assess the degree of confidence they have in their ability to cycle at the intensity
determined at baseline, for 10 hierarchically ordered number of minutes. In order to avoid
floor and ceiling effects, intervals were 5 min increments as determined from pilot
testing. Each question included the use of the stem, “Rate your confidence right now that
you can cycle for…” Because task self-efficacy was measured both before and after the
subject cycled, the post task self-efficacy differed slightly; each question included the use
of the stem, “Rate your confidence that the next time you cycle, you could cycle for…”
Responses were made on an 11-point scale, ranging from 0 (not at all confident) to 10
(completely confident). Efficacy scores for each individual were computed by averaging
each participant’s responses to the 12-items. Additionally, for comparison self-efficacy,
for each time period, participants rated how confident they were that they could cycle at
their set intensity for longer than their partner (in the coactive and conjunctive task
conditions) using the same response scale.
The regulatory Self-Efficacy Scale consisted of a 7-item frequency scale that
assessed how confident participants were that over the next 3 months they could keep up
an exercise program at a moderately fast pace for a minimum of 20 min continuous
exercise for one day up to 7 days per week. The stem was, “Over the next 3 months, I can
exercise for…” Responses were made on the same 11-point scale as the task selfefficacy scale.
Intention to exercise. Intention, adapted from the scale used by Mohiyeddini, Pauli and
Bauer (2009), was measured with two items: "My goal is to exercise tomorrow for at
least 20 minutes" and "I intend to exercise tomorrow for at least 20 minutes." Ratings

41	
  

were made on a 7-point scale, from -3 (not at all true for me) to +3 (completely true for
me). The two items were added together for an intention score.
Ratings of perceived exertion (RPE). Perceived exertion was measured using the Borg
(1998) Ratings of Perceived Exertion (RPE) scale during each cycling trial. The Borg
Scale (1998) is a self-selected subjective measurement of an exerciser’s overall level of
intensity. The rating category scale used in this study was a 1 to 10 scale (very easy to
extremely hard). An explanation of the scale was given prior to each ride to ensure
participants understood the numerical meaning. This scale appeared on a large poster
posted to the wall in direct sight of the participant while riding. When asked to report
their level of perceived exertion, the participants told the experimenter which number
corresponded with how hard they felt they were working, and that number was recorded
every 3 min. The average of all ratings during a trial were computed for a perceived
exertion score.
VO2 max estimate. Subjects were led through an online VO2 max estimate test
(http://www.brianmac.co.uk/vo2maxnd.htm). After inputting gender, height, and weight,
subjects were asked to rate their physical activity by selecting “the appropriate "radio
button" that indicates the overall physical activity in the past six months.” They were then
asked to rate their perceived functional ability by selecting “the appropriate "radio
button" that indicates your perceived ability to maintain a steady pace (not too easy or not
too hard) on an indoor track for one mile”, and by selecting “the appropriate "radio
button" that indicates your perceived ability to maintain a steady pace to cover 3 miles
without becoming breathless or over fatigued.” The purpose of this estimate was to have

42	
  

a measure of aerobic fitness level to examine if aerobic fitness level modified any effects
found.
Heart Rate (HR). Subjects wore a two-part HR monitor, which automatically
synchronized with the Expresso fitness bike computer and appeared on the screen.
Subjects wore both wristwatch and a chest strap for each trial. HRs were monitored
continuously, with average HR (excluding the warm-up period) recorded at the end of
each trial.
RPM. A bandwidth of 66-74 RPMs was chosen based on pilot testing of subjects’ ability
to maintain a relatively steady pace at a moderate intensity of work within this
bandwidth. The ideal RPM was 70, which subjects were told to try to maintain. During
each trial, RPM on the Expresso fitness bike screen was monitored closely.
Power output. After each trial was completed, the subject’s power output was recorded
from the reading on the Express fitness bike screen. Power was the average of the
instantaneous power output throughout the session (rather than an estimate of total work
performed). The power output gave researchers a measure of the actual intensity of work.
Procedure
Permission to conduct this study was obtained from the Institutional Review
Board for Human Subjects Research. Following approval, instructors were contacted via
email requesting permission for their students to participate in this study. An explanation
of the purpose and procedure of the research was provided to teachers who agreed to
participate in this study. Upon agreement with the instructors, females students were
given the option to sign up for the study- most in exchange for extra credit, and erased
absence, or a “free” absence, by their teacher. Students were told that while participation

43	
  

was strictly voluntary and that they could drop out of the study at any point, they would
not be awarded the aforementioned “incentive” from their teacher unless they completed
all six trials within the given time frame. A PARQ was obtained from all subjects who
signed up for the study as a health screening precaution. Only those who answered yes to
all questions on the PARQ were allowed to participate in the study. Those who were
eligible to participate were able to sign up for a 60 min time slot on 6 days during a 4
week time frame with the maximum number of sessions a week limited to three and the
minimum time between sessions being 24 hours.
Data collection involved six time points for all 58 participants. Time 1 data for all
subjects was collected to provide a baseline physiological measure. At Time 1, prior to
riding, subjects were provided an informed consent form. Next, their VO2 Max score was
calculated using the online resource. Their 24-hour food and beverage intake recall, the
regulatory Self-Efficacy for Exercise scale, and the Intention to Exercise scale were then
administered. Based on the specific demographic information collected prior to Time 1
(e.g., participant age and RHR), 65% of HRR for each participant was calculated using
the Karvonen formula: HRR ( (220-age) – RHR) x Intensity % + RHR. Prior to Trial 1,
subjects were instructed to report their RHR in the demographics survey. Directions
given to subjects on how to take their RHR can be found in Appendix J. Setting the
intensity at 65% of their HRR surpasses the ACSM recommendations for the average
healthy adult to maintain health and reduce the risk for chronic disease (40% to 60% of
MHR) and satisfies the recommended intensity for aerobic fitness (between 55% and
65% to 90% of MHR). Previous studies assessing self-efficacy and aerobic exercise have
also used 65% MHR as the set-intensity level (Bozoian et al., 1994).

44	
  

At Time 1, subjects were shown how to wear the HR monitor properly and were
given the opportunity to use the restroom to properly secure the chest strap. The bike was
then adjusted to the appropriate height and distance from the handles, which were then
recorded. Subjects were given 2 min to warm up at the lowest gear and were told to keep
their RPMs between 66 and 74- ideally at 70. The RPM indicator, which was set at 70
RPMs, was then turned on so that the subject could match the rhythm. Subjects were also
told that they could monitor their RPMs on the Expresso Fitness Bike screen. At the end
of the 2-min warm-up the subject’s HR was checked. If they were not at 65% of their
HRR, researchers increased the gear by one level every 10 s, for up to 3 min, until they
reached 65% of their HRR. Once the subject reached 65% HRR the gear was not
increased any further. If the subjects HR continued to rise past 65% of their HRR during
the 3 min period the gear was decreased by one level every 10 s until they stayed
consistent at 65% of their HRR. Subjects were reminded that they must stay within the
bandwidth of 66-74 RPMs at all times. The gear that the subject ended with was recorded
and represented their intensity level or “working” gear that would remain the same for all
trials. When subjects returned for subsequent trials, they were given a 5 min warm up at a
gear that was half of their working gear before starting the time for their trial.
After their working gear was determined, subjects were given a 3 min rest period
before their Trial 1 ride actually started. Once their 3 min rest period was over, subjects
returned to the bike, and were told to ride the bike for as long as they could at their set
intensity while maintaining between 66-74 RPMs. The researcher explained to the subject
that she/he would closely monitor the subject’s RPMs, and if she dropped below 66
RPMs for longer than 5 s she would be notified “Strike One.” If it happened a second

45	
  

time she would be notified “Strike Two,” and if it happened a third time she would be
notified “Strike Three, Your Trial Is Over.” Subjects were also told that they could
choose to stop riding at any point during their trial, regardless of whether they had any
strikes at all, by saying “I’m done.” Once all the subjects were clear of the conditions and
instructions, their intensity was set, the RPM indicator was turned on, and the time was
started. RPE was recorded every 3 min during the ride using the Borg Scale. At the end of
their ride, their time, average HR, average power output, and whether or not the
researcher stopped the subject (RSS) or the subject stopped herself (SSS) was
immediately recorded. The subject was asked to remove the HR monitor and complete
the intention to exercise scale and the pre task Self-Efficacy scale. After Time 1 was
completed, subjects were randomly assigned to either Group A: Individual, Group B:
Conjunctive, or Group C: Coactive and would remain in those groups for the subsequent
five trials.
Those who were selected to be in the Individual group rode the Expresso fitness
bike under the same conditions and instructions as they did during Trial 1 with the only
difference being a 5 min warm-up at half of their working gear occurring before the start
of their actual trial. Subjects in the Individual group completed the task Self-Efficacy
scale prior to and immediately following their trial.
Subjects assigned to the Conjunctive group were assigned a “virtual partner” as
their teammate for the ride and were told that their partner was scheduled to ride at the
same time as they were, on another Expresso fitness bike in another lab. The subject then
"met" her partner through a brief skype session that was pre-recorded using a
confederate. The subject was told that her partner was riding under the same conditions as

46	
  

she was and that the team’s score would be the time of the partner who stopped riding
first or who was stopped due to dropping below 66 RPMs for longer than 5s over three
instances, at which point the trial would end for both partners. The subject was then asked
to complete the task Self-Efficacy scale and the comparative Self-Efficacy scale prior to
riding. Subjects were able to track their virtual partner’s progress by watching their
partner ride on a “live” video feed. The confederate video was previously recorded and
looped so that the virtual partner never stopped riding. Subjects in the Conjunctive group
had the same virtual partner (recorded in several different clothing outfits and hair-styles)
on this conjunctive task for all trials. In addition to RPE being recorded every 3 min, just
as in Trial 1, their time, average HR, average power output, and whether or not the
researcher stopped the subject (RSS) or the subject stopped self (SSS) was immediately
recorded upon cessation. The subject was asked to remove the HR monitor and asked to
complete the post task Self-Efficacy scale.
Subjects in the Coactive group were assigned a “virtual partner” and were told
that their partner was scheduled to ride at the same time as they were, on another
Expresso fitness bike. The subject "met" her partner through a brief skype session that
was pre-recorded using a confederate. The subject was told that her ride was strictly
individual and that each person’s score was based on how many minutes she rode under
the specific stipulations. The subject was then told that if her partner stops herself or is
stopped by the researcher first, they could continue to ride. They were then asked to
complete the task Self-Efficacy scale and the comparative Self-Efficacy scale prior to
riding. Subjects were able to track their virtual partner’s progress by watching their
partner ride on a “live” video feed. The confederate video was previously recorded and

47	
  

looped so that the virtual partner never stops riding, even after the subject stopped riding.
When the subject returned for their next session she was informed of how long her
partner rode during the previous session. The time that was provided to subjects was
moderately longer than their time in order to create the illusion of a moderately more
capable partner, with subjects being told different “approximate times” that their partner
rode longer than them; 1.4 times the subject’s baseline persistence score was a parameter
for the researchers. Subjects in the Coactive group had the same virtual partner on this
coactive task for all trials with the virtual partner appearing in different clothes and
hairstyles across trials. In addition to RPE being recorded every 3 min, just as in Trial 1,
their time, average HR, average power output, and whether or not the researcher stopped
the subject (RSS) or the subject stopped self (SSS) was immediately recorded upon
cessation. The subject was asked to remove the HR monitor and complete the post task
Self-Efficacy scale.
Although subjects in both the Conjunctive and Coactive groups were led to
believe their stationary bikes were linked to other bikes and they could see their partner
riding, they were not provided with any means to communicate with their supposed
teammates or coactors. For all groups, at the beginning of Trials 1-6, the 24-hour food
and beverage intake recall questionnaire was administered. Task self-efficacy for all
groups was assessed at the beginning and end of Trials 2-6 with baseline taken at the end
of Trial 1. Comparison self-efficacy for the Conjunctive and Coactive group was assessed
at the beginning (after manipulation) of Trials 2 to 6. The regulatory Self-Efficacy scale
and the Intention to Exercise scale were administered to all subjects at the beginning of
Trial 1 and at the end of the Trial 6.

48	
  

Subjects were asked and reminded at the end of each trial not to talk about the
trials outside of the testing lab to protect subject confidentiality and the integrity of the
study. The experimenter was responsible for administering the questionnaires to the
subjects, and subjects were guaranteed confidentiality of their responses. At the
beginning of the study, subjects created a subject code that was used to identify them
instead of their names or student numbers on each survey. The surveys were taken in the
lab, on a secured computer, and were be submitted by the subjects. Their names would
only appear on the sign up sheet for the purpose of reporting back to instructors which of
their students showed up for all trials. Their names also appeared on the experiment log
but were blacked out following data input.

49	
  

CHAPTER FOUR
RESULTS
Preliminary Analyses
Descriptives. There were a total of 58 female participants (M = 20.54 yrs, SD =
1.86), with relatively equal numbers in all conditions (coactive = 18, conjunctive = 20,
individual = 20). Of the 58 participants that were selected, 2 subjects were not included;
one subject was not included because she sustained an injury outside of the study and the
other subject was not included because she raised concerns about the confederate being
an unrealistic match for her because the partner appeared to be much younger, and did
not wish to continue.
Assesment of fitness and habitual physical activity. Prior to engaging in the
study, fitness and habitual physical activity levels, were assessed with two self-report
items: “How would you rate your personal fitness level?” on a 5-point scale (1 = poor,3
= average 5 = excellent) and “How many times per week do you exercise for 30
continuous minutes or more at a moderate to high intensity?” on a scale from 0 to 7+.
The majority of the subjects rated their current fitness level as average (44.8%) or good
(32.9%). Seven students who were categorized as “highly active” (at least 20 continuous
minutes or more of exercise at a moderate to high intensity more than 7 times a week)
were excluded from the study because it was assumed that if they were highly active
individuals it was likely that they were highly motivated in regards to exercise, which
was not the specific target group for this study. Subjects also completed an online
VO2max estimate test (http://www.brianmac.co.uk/vo2maxnd.htm). The purpose of this
estimate was to have a measure of aerobic fitness level to examine if aerobic fitness level

50	
  

modified any effects (see Table 1 for means of fitness and habitual physical activity).
Finally, participants were provided instructions on determination of RHR (i.e. after they
wake up in the morning while still in bed, and preferably the average of 2 different days).
RHR and age were used to calculate 65% of individual participant heart rate reserve
(HRR) using the Karvonen formula: HRR ( (220-age) – RHR) x Intensity % + RHR.
Outliers and normality. The performance data were screened for outliers and
violations of normality. Outliers were defined as values that were +3 SD from the mean.
Four outliers were found for persistence scores and four for HR. Subsequent data
analyses were performed both with and without outliers and the same results were found
for both analyses. Thus, the analyses were conducted with outliers included in the data
and those results are reported below.
An assessment of fatigue effects was calculated among the individual control
group. A one-way repeated measures ANCOVA was performed with Trial as the within
subjects factor and Trial 1 persistence used as the covariate. There was neither a
significant Trial effect nor a linear trend across trials, suggesting that performance in the
individual condition remained relatively stable across time. This curve served as the
baseline for comparison for persistence scores across trials and between groups. As a
follow up, a repeated measures ANCOVA was conducted without the use of Trial 1
persistence and VO2max as covariates. No significant differences were found, indicating
that without controlling for individual differences in ability, as assessed at trial 1, there
was too much error variance to detect any trial effects. A one-way ANOVA was
performed across conditions on Trial 1 persistence scores in order to confirm successful
randomization. No differences were found (p >.16) and thus randomization was

51	
  

successful. The means and standard deviations for all variables from Trial 1-6 are
provided in Table 2.
Power. To verify that there were no differences in power output (intensity of
effort), a 3 (condition) x 5 (time) RM ANCOVA was run with Time (Trial 2, 3, 4, 5, and
6) as the within Ss factor and condition as the between-subjects factor. Baseline power
output was used as the covariate. No condition differences were found. Thus, after
controlling for individual differences in ability (i.e. baseline power output), there were no
differences in power between Ss across trials. Thus, the manipulation was successful.
	
  

HR. As a second indicator of our manipulation of intensity of effort, we analyzed

HR. A 3 (Condition) x 5 (Time) RM ANCOVA was run with Trial 1 (i.e. Baseline) HR
as a covariate. If our manipulation of intensity of effort worked, we would expect to see
no differences in HR across trials, nor differences between groups after controlling for
individual differences (i.e. baseline HR at Trial 1). A significant Trial effect was found (F
= 2.454, p = 0.047, ηp2 = 0.043; see Figure 1). The within subjects contrasts verify the 4th
order trend seen in Figure 2 (F = 4.151, p = 0.047, ηp2 = 0.071). There was neither a
condition main effect nor a significant Condition x Trial interaction. As for the trial effect
and linear trend, it appeared that the trend was negative where average HR decreased
across trials. This could be due to the accumulation of a “training effect”. That is, as a
participant’s fitness improves over the course of the six trials, their HR would decrease
(i.e. their heart would become more efficient) at performing at the same intensity. The
lack of a Condition x Trial interaction, though, suggests that the training effect was
similar across conditions (see Table 3 for means of HR and Power).
Main Analyses

52	
  

A 3x5 (condition x trial) mixed ANCOVA of persistence scores was conducted,
with Trial as the within subjects factor and Trial 1 persistence and VO2max as the
covariates. While it was originally thought that Trial 1 performance would capture most
of the variance due to differences in fitness, the lack of a significant correlation between
Trial 1 performance and VO2max justified the use of both as covariates for this analysis.
First, there was a significant Trial x Condition interaction effect F(8, 216)= 5.15; p <
.001, ηp2 =.163, suggesting that performance across trials was different between
conditions. There was a significant linear trend for the Trial x Condition effect (p < .001,
ηp2=.339). A visual examination of persistence scores across trials, between groups
provides an initial indication of the nature of these trends (see Figure 3). Particularly,
there appears to be a negative linear trend in the individual condition and a positive linear
trend in the conjunctive condition. Lastly, there was a significant Condition (between
groups) effect for persistence, F(2, 54)= 18.68; p < .001, ηp2 =.41, indicating that, across
all trials, some groups performed better than others (see Table 1). An examination of
estimated marginal means (see Table 2 using a 95% confidence interval revealed
significant differences between all groups such that the individual condition (M =
638.07s, SD=350.39) was lower than the coactive condition (M=1186.12, SD=539.77),
which was lower than the conjunctive condition (M=1313.46s, SD=604.60). Thus, the
findings support Hypothesis 1 and 2 that compared to working alone, females work
longer when working together with a moderately superior partner under coactive task
demands and work even longer with a partner under conjunctive task demands than under
coactive demands. Follow up analyses were conducted to specifically target Hypotheses
1a and 2a.

53	
  

To examine Hypothesis 1a (the benefit of exercising with a moderately-morecapable coactive partner will decline over repeated sessions), a polynomial trend analysis
was conducted with the coactive condition, only, and no significant trend was found,
suggesting that performance remained relatively stable across trials (i.e. did not increase
or decrease). To reduce the error term, the same analysis was run with the individual
condition included, and still no significant trend was found. Hypothesis 1a was
disconfirmed- the benefit of exercising with a moderately more capable coactor remains
stable across repeated sessions.
As a follow up, and to answer Hypothesis 2a (the additional benefit of exercising
with a moderately more capable partner under conjunctive conditions will not decline
over repeated sessions) a polynomial trend analysis was conducted for the conjunctive
group, only. There was no significant Trial main effect, nor a significant linear trend.
However, given the large error term (SD = 604.60) and the convincingly steep curve seen
in Figure 3 for the conjunctive condition, I ran the same analysis again, but included the
individual condition, which had a relatively lower SD (350.39). However, the analysis
yielded the same result, there was no significant trend.. Therefore, hypothesis 2a was
confirmed.
RPE. To test Research Question 1, RPE was assessed throughout each trial by
asking participants to rate their level of exertion every 3 minutes. If the participant did
not ride for at least 3 minutes they were asked to rate their RPE for the last 30 seconds
that there were riding the bike. Those scores were then averaged within trials to yield an
average RPE score for each Trial. To assess differences in subjective effort, a 3
(Condition) x 5 (Time) RM ANCOVA was run with Trial 1 (i.e. Baseline) RPE as a

54	
  

covariate. A significant trial effect was found F = 2.835, p = 0.025, ηp2 = 0.051. There
was neither a Condition main effect nor Condition x Trial interaction . The trial effect
showed that RPE scores actually decreased over time (see Table 2, Figure 4). Thus,
although there were significant condition differences in performance across trials, they
were not accompanied by parallel increases/decreases in subjective effort.
Task Self-Efficacy. To test Research Question 2- Does self-efficacy for aerobic
exercise in women change in tandem with motivation gains? a 3 (Condition) x 5 (trial)
RM ANCOVA was run with Baseline TSE as the covariate and post TSE as the
dependent variable, the last factor being the within subjects factor. If self-efficacy
changes as a result of motivation gains, one would see condition differences in selfefficacy (since we already know there are motivation differences). First, there was a
significant trial effect, F (4, 196) = 2.809, p =.027, ηp2 = .054 (see Table 4, Figure 5).
Second, there was a Condition main effect, F (2, 54) = 3.21, p =.049, ηp2 = 0,12). Using
a 95% CI, I found that the Individual condition (M = 4.55, SD = 2.43) was less than
Coactive (M = 5.48, SD = 2.26), which was equal to the Conjunctive condition (M = 6.00,
SD = 2.26). Although there was no significant interaction, within-subjects contrasts
yielded a significant 4th order trend for the overall Trial effect, F (1, 56) = 5.27, p = .026,
ηp2 = .097, suggesting that the average change in post TSE across groups was non-linear
(see Figure 5).
Given that there was a similar pattern of group differences in TSE as there was in
persistence, it was plausible that TSE mediated the effect of condition on persistence. To
test this possibility, a 3 (condition) x 5 (Trial) RM ANCOVA was run with VO2max, Trial
1 performance and Baseline and Post TSE from each trial as covariates. The inclusion of

55	
  

TSE as a covariate eliminated the Trial effect from the previous analysis, but the
Condition x Trial interaction, F (4, 53) = 3.34, p = .001, ηp2 = 0.13, and Condition main
effect , F (2, 55) = 14.06, p < .001, ηp2 = 0.37, were both preserved. Thus, TSE did not
mediate these effects. 	
  
	
  

Regulatory SE. A one-way ANCOVA with Post intervention Regulatory SE as

the dependent variable was run to assess condition differences using pre-intervention
RSE as the covariate. No significant effects were found, which suggests that Regulatory
SE does not change (for better or for worse) according to whether one works with a
partner or by themselves (see Table 4).
Comparative self efficacy. A 2 (Condition) x 5 (Trial) RM ANCOVA was run
with Trial as the within subjects factor and Baseline CSE as the covariate. There was no
significant trial or condition x trial effect. There was also no significant trend.
Intention to exercise. In order to answer Research Question 3 (“Does intention to
exercise in women change in tandem with motivation gains?”) a one-way RM ANOVA
was run with Intent as the dependent variable. First, there was a significant Trial effect F
(2, 55) = 11.51, p =.001, ηp2 = 0.17, such that intend decreased from pre (M = 1.75, SD =
1.63) to post (M = 0.97, SD = 1.90).There was also a significant condition main effect, F
(2, 55) = 3.55, p = .035, ηp2 = 0.11. An estimate of these differences using the 95% CI
showed that the Individual condition (M = 0.73, SD = 1.64) was less than the Coactive
condition (M = 1.47, SD = 1.13), which was then equal to the Conjunctive condition (M
= 1.36, SD = 1.47)

56	
  

CHAPTER FIVE
DISCUSSION
The primary aim of this thesis was to examine the presence and persistence of the
Köhler motivation gain effect on repeated sessions of aerobic performance using a
virtually-presented partner. Additionally, the study compared the underlying mechanisms
(social comparison and indispensability) of the Köhler effect on an aerobic task over
multiple sessions. Results showed that those who cycled with a more-capable virtuallypresented partner under coactive task demands persisted 548.05 s longer on average
across sessions (M = 1186.12 s) than individuals cycling alone (M = 638.07 s). This
represents almost a 9 min increase, a 86% improvement on individual exercise. Further,
those who cycled with a partner under conjunctive conditions (M = 1313.46 s) persisted
675.39 s longer than individual controls and 390.47 s longer than those under coactive
conditions. This represents an additional 2 min increase beyond those in the coactive
condition, and a 106 % improvement on individual exercise. Being able to increase one’s
aerobic persistence by over 11 min on average is a substantial gain for those trying to
increase their physical activity.

The observed effect sizes (Conjunctive, d = 1.37;

Coactive, d = 1.20) represent a substantial improvement over other interventions, for
examlple…
	
  

Higher levels of physical activity and fitness appear to reduce all-cause mortality

and cardiovascular disease (CVD) mortality (Blair, Kohl, & Paffenbarger, et al., 1989;
Farrell, Kampert, & Kohl, et al.,1998; Jolliffe, Rees, & Taylor, et al., 2001). Physical
exercise is thus strongly recommended in both primary and secondary prevention of CVD

57	
  

(ACSM, 1994; Fletcher, Balady, & Blair, et al., 1996; Fletcher, Balady, & Amsterdam, et
al., 2001; Shephard & Balady, 1999). Because the majority of Americans do not exercise
as long, as intense, or as frequently as the U.S. guidelines recommend, which is at least
30 min a day of moderately intense physical activity on at least 5 days each week (U.S
Department of Health and Human Services, 2008), the findings of the current study are of
particular value in an effort to meet these guidelines. Moreover, such increases in
exercise duration at the appropriate intensity level also enables people to satisfy the
ACSM’s

recommendation

for

cardiovascular

fitness

which

is

described

as

exercise/physical work intensities between 55% and 90% of MHR for at least 20 min, 3
days a week. The ACSM suggests low-fit or deconditioned individuals may experience
improvements at exercise intensities of only 55% to 65% MHR.
Furthermore, the superiority of the conjunctive task condition supports a number
of prior studies that have shown a significant indispensibilty effect (see Weber & Hertel,
2007). The current study supports research by Hertel, Kerr, and Messe´ (2000) and Lount
et al. (2000), suggests that the overall Köhler motivation gain effect is more likely due to
less able participants’ sense that their efforts are particularly crucial to team success than
to some goal-comparison mechanism, as Stroebe et al. (1996) proposed. Consistent with
Hertel, Kerr, and Messe´ (2000) and Lount et al. (2000) the current study showed that
significant motivation gains were greater when task demands were conjunctive than when
they were coactive (where one teammate can continue to perform after the other has
stopped). Both coactive and conjunctive conditions showed significantly greater
motivation gains than their individual condition counterpart.
However, within the goal-comparison perspective, one would expect equivalent

58	
  

motivation gains across conditions of task demands, as it always was the case that
coworkers could observe each other perform and, thus, use this information as a basis for
setting their own performance goals. Moreover, past work has yielded evidence from
responses to a brief post-trial questionnaire that weaker coworkers are aware that their
efforts matter more under conjunctive task demands (see Hertel, Kerr, & Messe´, 2000;
Lount et al., 2000). Past research has supported a significant indispensability effect with
isometric tasks, but the current study is the first to show this effect with an aerobic task.
Not only was cycling with a virtual partner under conjunctive conditions
significantly superior to cycling under coactive and individual condition; conjunctive task
condition actually increased (although non-significantly) over the six sessions by 997.3s
compared to coactive task participants, who showed little improvement and 209.78s
compared to individual controls, who decreased their times. Unlike Lount et al. (2008)
the social comparison mechanism did not attenuate with repeated group interaction.
Consistent with Lount et al. (2008), the findings of the current study provide support for
the persistence of motivation gains in small performance groups.
While these results provide encouraging evidence to suggest that the Köhler effect
can occur in longer-term groups with stable membership (i.e. the same partner), it is
important to consider that it is not known whether the same effect can be found over a
greater number of sessions. It is possible that the participants’ performance could begin to
decrease as a result of boredom with their partner because of always being the weakest
member. Lount et al. (2008) found, although motivation gains were still present in groups
with stable membership, these gains in effort were even larger when one’s coworker
changed every two trials. They reasoned that people are less likely to continue to compare

59	
  

themselves with a partner or to take the partner’s level of performance as an achievable
performance goal if that partner consistently outperforms them. However, with a new
partner, one has less experience, suggesting that the partner’s superiority is unassailable,
and one may therefore continue to strive to match or exceed that new partner.
As Feltz et al. (2010a) found, the motivation gains achieved with a more capable
partner did not come at the expense of aversion to the task. Although those in partnered
conditions cycled longer than individual controls, they did not perceive that they worked
any harder. The RPE means represented a moderate intensity level of effort (somewhat
hard to hard categories). Given that a sense of high intensity effort can have negative
effects on motivation to exercise (Andrew, Oldridge, Parker, Cunningham, Rechnitzer et
al., 1981), this finding is encouraging for continued participation at the task.
Similar to Feltz et al. (2010a), it was found that although self-efficacy was
significantly correlated with persistence at the task, the motivation-enhancing effect of
working with others was not mediated by changes in self-efficacy—the effect of task
conditions was significant even when self-efficacy was controlled. However, subjects in
the individual condition, on average across trials, have significantly lower self-efficacy
than those in the coactive and conjunctive condition. I speculate that subjects may have
been aware, albeit vaguely, that their performance in the task was improving across
repeated sessions.
Limitations
The findings of the current experiment, although providing encouraging results
regarding the persistence of the Köhler effect in dyads, are not without limitations.
Because the current study focused on female dyads working at a particular aerobic

60	
  

persistence task, it is possible, that the findings could be moderated by gender, group
size, or task features. Moreover, although experimental studies on the Köhler effect have
primarily been conducted in dyads or triads, it is important to note that research in field
settings has demonstrated that, regardless of group size, increased perceptions of
indispensability are associated with increased levels of group performance (Hertel,
Konradt, & Orlikowski, 2004). Also, the motivation gains that were found over time were
only for six sessions. These gains may dissipate over longer periods of time. In addition,
the failure to find a significant linear trend in any of the conditions is surprising, given
the rather steep curves depicted in Figure 2. Failure to find significant trends could
largely be due to the high error terms and relatively low sample sizes. Lastly, subjects in
the coactive condition were given feedback on their partner’s previous performance (e.g.
“your partner persisted ______ longer than you after you quit”; This number was
determined by multiplying the subject’s Trial 1 persistence score by 1.4) each time they
came back to the lab. Subjects in the conjunctive condition, however, received feedback
only after their first trial, just before performing the second trial with their partner for the
first time. Insofar as the experience of receiving feedback is related to one’s motivation,
this is a potential confound in the study.
Future Research
Virtually-presented partners were presented as moderately more capable (i.e.,
persisted 1.4 times longer) than participants because a moderate discrepancy in ability
between partners has been shown to be optimal for producing the motivation gain (Feltz,
Irwin, & Kerr, 2010; Koehler, 1927; Messé et al., 2002). Messé et al. reported that the
Köhler motivation gain effect is smaller when one’s more capable partner is either only

61	
  

slightly more capable or extremely more capable than oneself. Feltz et al. (2010) found
similar results with a virtually-presented partner in a health games context. Future
research should examine the discrepancy in ability between partners over multiple
sessions where partners who set a pace may change over time (from slightly more
capable to increasingly more capable or vice versa). As Feltz et al. (2010a) note
additional promising areas for investigation include the effects of encouragement from
the partner, similarity in appearance and age of the partner, and the degree to which the
partner is a live vs. completely virtual.
Future research also might compare females and males on this particular task.
Although no robust gender difference in the Köhler effect has been reported (cf. Weber &
Hertel, 2006), group gender-composition can moderate the effect (Lount et al.,2000;
Lount, Park, Seok, Kerr, & Messé 2003). There is considerable evidence that men are
more concerned than women with achieving favorable outcomes relative to others (social
comparison process). For example, men tend to be more competitive in many settings,
including athletic competition (e.g., Gill, 1993), the workplace (e.g., Browne, 2002),
learning contexts (e.g., Light, Littleton, Bale, Joiner, & Messer, 2000), and laboratory
groups (e.g., Schopler et al., 2001). Whereas, the indispensability process, presumes that
the most important goal is to contribute to the group’s success; evidence shows that
women are more concerned than men with a variety of communal goals. For example,
women are more likely to have prosocial social value orientations (van Lange, de Bruin,
Otten, & Joireman, 1997), to be inclusive in coalition formation (Vinacke, 1959), to favor
ingroup members (Gaertner & Insko, 2000), to react more negatively to social exclusion
(Leary, Tambor, Terdal, & Downs, 1995), to provide more emotional support (e.g., Fritz,

62	
  

Nagurney, & Helgeson, 2003) and to use less confrontational or coercive means of social
influence (Carli, 1999).
Kerr et al. (2007) found that, for men, simply having the opportunity to compare
with a superior coactor can be sufficient to produce their full Köhler effect, and making
that coactor into a coworker who is wholly dependent on their efforts (under conjunctive
task demands) did not reliably enhance the effect. On the other hand, being indispensable
to one’s performance group boosted effort above the level observed in coacting pairs for
women but not for men. In another experiment, Kerr et al. (2007) primed their female
subjects with competitive goals that would normally be salient to men and made them
salient to women in order to increase the accessibility of the competitive goal among
them. They found that making goals more salient to women in a competitive-comparison
context can increase motivation. Because it is known that men experience increased
motivation gain effects when presented with coactive task demands rather than
conjunctive, it would be interesting to see if such findings hold true with an aerobic task.
If so, it would be interesting to see whether priming male subjects with goals that would
normally be salient to women (which have yet to be clearly defined) but made salient to
them can increase the accessibility of the conjunctive goal and therefore help boost
motivation gains in conjunctive tasks.
Lastly, the current study was conducted in a laboratory setting. While recent
researchers have observed motivation gains in sequential group tasks in the field using
archival data (e.g. swimming relays; Hueffmeier & Hertel, in press), there are no known
studies or interventions that intentionally harness the Kohler effect to increase motivation
in real world tasks and environments. Although research in this area is relatively young,

63	
  

future research should examine the utility and feasibility of implementing such strategies. 	
  
Conclusion
The current study provides encouraging results regarding the persistence of the
Kohler motivation gain phenomenon in task groups. Whereas prior work has examined
how to reduce motivation losses in groups, the current findings contribute to a growing
body of research on the existence and persistence of motivation gains in experimental
groups, and the likely utility of these gains, in this case, in aerobic exercise tasks. These
findings lend support to the notion that motivation gain effects can influence exercise
persistence (most potently under conjunctive task demands with a moderately more
capable partner) over several trials, and as a result, increase self-efficacy (regardless of
task demands). Even though the effects were not mediated by self-efficacy, research
indicates that higher self-efficacious individuals are more likely to engage and persist in
their physical activities; therefore this can have important implications for those looking
to increase their physical activity. Finally, the current study lends support for the use of
virtual partners to achieve such motivation and performance gains.

64	
  

APPENDICES

65	
  

APPENDIX A
Informed Consent

66	
  

Informed Consent
This study is being conducted by Professor Deborah Feltz of the MSU Department of
Kinesiology.
In this study, you will be asked to perform aerobic exercise (riding a stationary bike) for
as long as you feel comfortable at a predetermined intensity. You will also be asked to
wear a heart rate monitor and, at the end, report your reactions to the task.
There are two foreseeable risks to participating in this study. It is possible that you will
become fatigued or experience some muscle soreness as a result of performing the
experimental tasks. And, if you already have respiratory problems or heart conditions,
performing the task could aggravate those problems and conditions. For that reason, if
you have any such issues, you may not participate in this study.
Your responses will be kept strictly confidential (to the maximum extent allowable by
law). All your responses will be used for research purposes only. Your name will not be
associated with any report of research findings. Within these restrictions, results of the
study will be made available to you at your request.
Participation in this research project is completely voluntary. You may choose not to
answer specific questions or to stop participating at any time. Participation in this study
will require no more than 40 minutes on six separate occasions.You can participate in the
study only if you feel healthy, are in normal or good bodily constitution, and have no
cardiorespiratory illness or heart conditions.Your participation in the study does not
guarantee any beneficial results to you.
You may address any questions or concerns about this research, including the results
obtained, to Dr. Deborah Feltz (phone: 355-4730, e-mail: feltz@msu.edu) at the MSU
Kinesiology Department. If you are a minor (under the age of 18), you cannot participate
in this study.
If you have questions or concerns about your role and rights as a research participant,
would like to obtain information or offer input, or would like to register a complaint
about this study, you may contact, anonymously if you wish, the Michigan State
University’s Human Research Protection Program at 517-355-2180, Fax 517-432-4503,
or e-mail "mailto:irb@msu.edu" irb@msu.edu or regular mail at 202 Olds Hall, MSU,
East Lansing, MI 48824..
Your signature below indicates your voluntary agreement to participate in this study.
Signature:_____________________________

Date: ______________________

Please provide your permanent mailing address:
Printed Name & PID:______________________________________
Street/Apt #______________________________________________
City, State, ZIP____________________________________________
67	
  

APPENDIX B
Demographics Questionnaire

68	
  

Demographics Questionnaire
1. Age _____
2. Class
1st year _____
2nd year _____
3rd year _____
4th year _____
5th year _____
> 5 years _____
3. Major _______________
4. Race
Caucasian
_____
African American _____
Hispanic
_____
Asian
_____
Mixed
_____
Other
_____

69	
  

APPENDIX C
Regulatory Self-Efficacy Scale

70	
  

Regulatory Self-Efficacy Scale
Directions: Indicate below how confident you are that over the next 3 months you could
keep up an exercise program AT A MODERATE TO VIGOROUS PACE FOR A
MINIMUM OF 20 MINUTES continuous exercise for the number of days listed below.
Over the next 3 months, I can exercise for:
1 day a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

1 day a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

2 days a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

3 days a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

4 days a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

5 days a week for 20 continuous minutes
0

1

2

3

4

5

Not at all Confident

6

7

8

9

10

Absolutely Confident

71	
  

6 days a week for 20 continuous minutes
0

1

2

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

7 days a week for 20 continuous minutes
0

1

2

3

4

5

Not at all Confident

6

7

8

9

10

Absolutely Confident

72	
  

APPENDIX D
Pre Task Self-Efficacy Scale

73	
  

Pre Task Self-Efficacy Scale
Directions: Rate your confidence right now that you can cycle at 65% of your Heart Rate
Reserve (HRR) for…
5 minutes
0

1

2

3

4

5

6

7

Not at all Confident
10 minutes
0

1

2

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

8

9

10

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident
25 minutes
0

10

Absolutely Confident

Not at all Confident
20 minutes
0

9

Absolutely Confident

Not at all Confident
15 minutes
0

8

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

30 minutes
0

1

2

3

4

5

6

7

Not at all Confident
35 minutes
0

1

2

8

9

10

Absolutely Confident

3

4

5
74	
  

6

7

8

9

10

Not at all Confident
40 minutes
0

1

2

Absolutely Confident

3

4

5

6

7

Not at all Confident
45 minutes
0

1

2

1

2

3

4

5

6

7

1

2

10

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident
55 minutes
0

9

Absolutely Confident

Not at all Confident
50 minutes
0

8

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

60 minutes
0

1

2

3

4

5

Not at all Confident

6

7

8

9

10

Absolutely Confident

75	
  

APPENDIX E
Post Task Self-Efficacy Scale

76	
  

Post Task Self-Efficacy Scale
Directions: Rate your confidence that the next time you cycle, you could cycle at 65% of
your Heart Rate Reserve (HRR) for…
5 minutes
0

1

2

3

4

5

6

7

Not at all Confident
10 minutes
0

1

2

1

2

3

4

5

6

7

1

2

3

4

5

6

7

1

2

8

9

10

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident
25 minutes
0

10

Absolutely Confident

Not at all Confident
20 minutes
0

9

Absolutely Confident

Not at all Confident
15 minutes
0

8

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

30 minutes
0

1

2

3

4

5

6

7

Not at all Confident
35 minutes
0

1

2

8

9

10

Absolutely Confident

3

4

5
77	
  

6

7

8

9

10

Not at all Confident
40 minutes
0

1

2

Absolutely Confident

3

4

5

6

7

Not at all Confident
45 minutes
0

1

2

1

2

3

4

5

6

7

1

2

10

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident
55 minutes
0

9

Absolutely Confident

Not at all Confident
50 minutes
0

8

8

9

10

Absolutely Confident

3

4

5

6

7

Not at all Confident

8

9

10

Absolutely Confident

60 minutes
0

1

2

3

4

5

Not at all Confident

6

7

8

9

10

Absolutely Confident

78	
  

APPENDIX F
Comparative Self-Efficacy Scale

79	
  

Comparative Self-Efficacy Scale
Directions: Rate your confidence right now that you can cycle at 65% heart rate reserve
(HRR) for longer than your partner...
0
1
2
3
4

5

Not at all Confident

6

7

8

9

10

Absolutely Confident

80	
  

APPENDIX G
Intention To Exercise Scale

81	
  

Intention To Exercise Scale
Directions: Please respond to the following statement:
“I intend to exercise tomorrow, AT A MODERATE TO VIGOROUS PACE, for at least
20 minutes”.
-3= not at all true for me, 3= completely true for me
-3

-2

-1

0

1

2

82	
  

3

APPENDIX H
24-Hour Food and Drink Intake

83	
  

24-Hour Food and Drink Intake
To the best of your memory, please report everything you have eaten or drank in the past
24 hours.

84	
  

APPENDIX I
Self-Report Fitness

85	
  

Self-Report Fitness
How would you rate your personal fitness level?
Poor
Below Average
Average
Good
Excellent

How many times per week do you exercise for 30 continuous minutes or more at a
moderate to high intensity?

0
1
2
3
4
5
6
7
More than 7

86	
  

APPENDIX J
Resting Heart Rate

87	
  

Resting Heart Rate
When you wake up in the morning and are still in bed:

1. Count your pulse for one minute (use a stop watch) by placing your two fingers on
your neck (carotid artery) until you feel the pulse. Then as soon as you start the watch,
begin counting starting at ZERO (0,1,2,3,4,etc...).
2. Instead of counting for one minute you can also count for 30 seconds and multiply that
number by 2 to get the full minute resting heart rate.
3. It would be best to do this two mornings in a row to obtain your average resting heart
rate (RHR). Add the two readings together, and divide that number by two to get the
RHR. For example: (76 + 80)= 156/2= 78 You can save and resubmit this form once you
have calculated your resting heart rate.

88	
  

Table 1.
Means of fitness and habitual physical activity.

SRPA (d/wk)

Individual
M (SD)
3.00 (1.56)

Coactive
M (SD)
2.72 (1.13)

Conjunctive
M (SD)
3.85* (1.57)

SRF

3.30 (1.13)

3.38 (0.61)

3.30 (0.73)

VO2max (ml/kg/m)

37.46 (8.01)

3.30 (0.73)

42.67 (6.06)

	
  
Note: SRPA = Self-Reported Physical Activity, SRF = Self-Reported Fitness (1 = poor, 3
= average, 5 = excellent)
* p < .05

89	
  

Table 2.
Means of main outcome measures (Persistence and RPE).
Variable

Individual
M (SD)

Coactive
M (SD)

Conjunctive
M (SD)

Time 1
Time 2
Time 3
Time 4
Time 5
Time 6
Total

633.05 (399.87)
682.05 (447.59)
670.8 (409.80)
686.45 (417.30)
608.1 (347.88)
548.0 (326.30)
638.07 (350.39)*

910.11 (626.62)
1272.11 (649.47)
1372.61 (564.06)
1217.78 (568.20)
1224.22 (546.93)
1119.89 (541.10)
1186.12
(539.77)*

689.85 (324.40)
1177.15 (486.22)
1394.1 (673.80)
1425.25 (847.92)
1507.3 (744.83)
1687.15 (889.00)
1313.46
(604.60)*

Time 1
Time 2
Time 3
Time 4
Time 5
Time 6

5.00 (1.15)
5.32 (1.34)
5.28 (1.38)
5.32 (1.00)
5.02 (0.71)
4.80 (1.02)

5.68 (1.30)
5.36 (1.08)
5.23 (1.12)
5.30 (1.02)
5.05 (1.25)
4.83 (0.56)

5.66 (1.09)
5.17 (1.12)
5.44 (1.23)
5.26 (1.00)
5.20 (0.90)
4.80 (0.77)

Pre
Post
Average

1.80 (1.64)
-0.35 (2.16)
0.73 (1.64)*

1.50 (1.38)
1.44 (1.29)
1.47 (1.13)

1.95 (1.85)
1.85 (1.35)
1.36 (1.47)

Persistence (s)

RPE (1-10)

Intention (-3 to
+3)

* p < .05

90	
  

Table 3.
Means of measures of intensity (for manipulation checks).
Individual
M (SD)
Power (watts)
Trial 1
Trial 2
Trial 3
Trial 4
Trial 5
Trial 6
Total
HR (bpm)
Trial 1
Trial 2
Trial 3
Trial 4
Trial 5
Trial 6
Total

Coactive
M (SD)

Conjunctive
M (SD)

89.90 (18.47)
85.60 (18.45)
86.65 (18.38)
87.60 (18.00)
86.40 (19.03)
80.85 (17.20)
86.16 (16.79)

88.78 (13.18)
85.94 (13.94)
86.89 (16.40)
84.89 (13.31)
85.22 (14.47)
78.89 (21.77)
85.10 (12.16)

94.05 (18.40)
91.45 (17.28)
90.05 (18.27)
89.80 (16.38)
88.45 (15.12)
88.95 (14.95)
90.46 (15.10)

151.35 (11.85)
150.50 (15.10)
145.55 (15.00)
147.75 (11.70)
149.45 (11.57)
147.05 (10.97)
148.60 (9.71)

157.61 (10.24)
156.17 (6.26)
153.72 (6.27)
153.50 (8.69)
153.17 (5.55)
153.06 (5.43)
154.54 (5.37)

149.20 (11.13)
150.50 (9.00)
149.50 (9.10)
148.70 (13.42)
147.85 (11.47)
149.63 (9.36)
149.15 (8.35)

91	
  

Table 4.
Means of all self-efficacy measures (all on a scale of 0-10).
Individual
M (SD)

Coactive
M (SD)

Conjunctive
M (SD)

Pre Trial Task SE
Trial 1
Trial 2
Trial 3
Trial 4
Trial 5
Trial 6
Total

4.13 (2.53)
4.21 (2.36)
4.61 (2.82)
5.20 (2.70)
4.61 (2.60)
4.55 (2.68)
4.63 (2.30)

4.17 (2.96)
4.90 (2.61)
5.20 (2.60)
5.29 (2.48)
5.19 (2.29)
5.78 (1.85)
5.45 (2.06)

4.48 (2.63)
4.73 (2.50)
5.45 (2.27)
5.56 (1.97)
5.81 (2.16)
5.88 (2.26)
5.49 (2.01)

Post Trial Task SE
Trial 1
Trial 2
Trial 3
Trial 4
Trial 5
Trial 6
Total

4.34 (2.63)
5.00 (2.78)
4.91 (2.67)
4.51 (2.78)
4.37 (2.77)
4.56 (2.43)

5.41 (2.69)
5.76 (2.56)
5.50 (2.42)
5.19 (2.30)
5.52 (2.42)
5.48 (2.26)

5.13 (2.27)
5.75 (2.42)
6.11 (2.30)
5.80 (1.88)
6.29 (2.09)
5.99 (1.93)

5.83 (1.98)
4.72 (2.08)
4.94 (2.21)
4.28 (1.96)
4.22 (1.86)
4.80 (1.60)

6.45 (1.79)
4.65 (1.69)
5.70 (2.66)
5.05 (2.16)
5.25 (2.55)
5.42 (1.74)

7.33 (2.05)
6.46 (1.98)

8.44 (1.26)
6.93 (1.94)

Competitive SE
Trial 2
Trial 3
Trial 4
Trial 5
Trial 6
Total
Regulatory SE
Pre
Post

7.36 (2.12)
5.92 (2.73)

92	
  

Figure 1. Average heart rate over trials.

93	
  

Figure 2. Average heart rate across trials between conditions (bpm) with Trial 1 HR as
covariate.

94	
  

	
  

Figure 3. Persistence means across trials between conditions (sec).

95	
  

Figure 4. Ratings of perceived exertion over trials.

96	
  

Figure 5. Task self-efficacy across trials 2-6, with trial 1 as a covariate.

97	
  

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