Dear Label_Name,

Greetings! I hope you are well.

I am writing on behalf of an international publishing house, Science and Education Publishing, USA (http://www.sciepub.com).

Science and Education Publishing (SciEP) is a multidisciplinary open access publisher of Journals covering the fields of Science, Technology and Medicine. All SciEP publications are subject to high-quality peer review, editorial and production processes and are freely available online.

Welcome to the April, 2013 edition of SciEP newsletter, providing monthly summaries of articles on science & education related topics of interest to scientist and professionals. The mission of our journals is to provide an open access forum for publishing new findings on issues pertinent to scientific and academic field. We also invite you to submit original research papers, review articles, short reports, or case studies are considered for publication in our Multidisciplinary Journals.

American Journal of Public Health Research
DOI: 10.12691/ajphr-1-1-3

The Implementation of a Tele-Homecare System with Service Oriented Architecture and HL7 Message Transmission Standard
Ching-Sung Wang

American Journal of Medical and Biological Research
DOI: 10.12691/ajmbr-1-1-2

The Influence of Ethanol on Pyruvate Kinases Activity in Vivo, in Vitro, in Silico
Lelevich Sergey Vladimirovich, Khrustalev Vladislav Victorovich, Barkovsky Eugene Victorovich, Shedogubova Tatyana Aleksandrovna

American Journal of Medical Sciences and Medicine
DOI: 10.12691/ajmsm-1-1-1

Clinical and Histological Features in Wegener Granulomatosis
Li Cavoli Gioacchino, Passantino Rita, Bono Luisa, Tortorici Calogera, Ferrantelli Angelo, Giammarresi Carlo, Rotolo Ugo

American Journal of Infectious Diseases and Microbiology
DOI: 10.12691/ajidm-1-1-2

The Curse of Lymphatic Filariasis: Would the Continual Use of Diethylcarbamazine Eliminate this Scourge in Papua New Guinea?
Anne Lanham, Lillian Mwanri

We have released issues of some journals on February 2013.
American Journal of Public Health Research
American Journal of Medical Sciences and Medicine
American Journal of Medical and Biological Research
American Journal of Pharmacological Sciences
American Journal of Clinical Medicine Research
American Journal of Nursing Research
American Journal of Cancer Prevention
American Journal of Medicine Studies
American Journal of Infectious Diseases and Microbiology
American Journal of Cardiovascular Disease Research
American Journal of Biomedical Research
American Journal of Mechanical Engineering
American Journal of Microbiological Research
Journal of Preventive Medicine
American Journal of Food and Nutrition
American Journal of Hypertension Research
American Journal of Sports Science and Medicine
Journal of Cancer Research and Treatment
American Journal of Zoological Research
Journal of Biomedical Engineering and Technology
American Journal of Microbiological Research
Biomedical Science and Engineering

We are pleased to announce that submissions are now being accepted for peer review for all the journals across all our subject areas in SciEP.

Please submit your manuscript via our online submission system:
http://www.sciepub.com/author/signin

To unsubscribe from our mailing list, please click on the following link: unsubscribe

I am looking forward to hearing from you.

Kind regards,

David Rain
Email:join@sciepub.com
Science and Education Publishing (http://www.sciepub.com)

Exercise Causality Orientation, Motivation, and Adherence in an Incentive Walking Program

Katie Helms*, Duston Morris, Sedre’ Auna Griddine

School of Counseling, Human Performance, and Rehabilitation, University of Arkansas at Little Rock, Little Rock, United States

Abstract: Participation incentives are commonly used in organizational and workplace exercise programs to encourage and reward selected participant outcomes. Although this program format is associated with limited positive outcomes such as increased exercise frequency, there remains a need to engage participants and consider intrapersonal motivations within this context. The purpose of the study was to investigate Causality Orientations Theory as it relates to the experiences and outcomes of participants enrolled in an incentivized employee walking program. Participants engaged in a 6-week walking program that offered prizes for targeted outcomes, and then completed the Exercise Causality Orientations Scale (ECOS). Participants walked significantly more during the program, although they did not increase frequencies of exercise behaviors other than walking. They also experienced differences in motivation and walking activity according to different primary exercise causality orientations. In this limited context, incentivized exercise programs can help participants achieve a positive outcome related to a specific type of exercise. Exercise program managers should also consider the exercise causality orientation of participants in creating a more customized program experience.

Keywords: exercise, causality orientation, exercise incentive programs

Received April 02, 2021; Revised May 05, 2021; Accepted May 14, 2021

Citation: Katie Helms, Duston Morris, Sedre’ Auna Griddine, Exercise Causality Orientation, Motivation, and Adherence in an Incentive Walking Program. Journal of Physical Activity Research, 6 (1). 28-35. January 2021. doi:10.12691/jpar-6-1-5

1. Introduction

Exercise has wide-ranging personal benefits including weight management, health risk reduction, improved cognitive function, and improved quality of life [1]. Unfortunately, only slightly more than half of American adults meet basic physical activity guidelines, with over a quarter reporting no physical activity at all [2]. Consequences associated with a lack of sufficient physical activity have implications beyond individual health. In addition to personal health, exercise has also been identified as a critical factor in healthcare costs, both for individuals and for businesses [3].

In addition to healthcare costs, the association of inadequate physical activity as a risk factor that negatively affects work performance, productivity, and absenteeism has created an interest in the provision of wellness programs in workplaces and organizations [4,5]. Organizational wellness programs have increased, with nearly half of American worksites with over 50 employees having some type of wellness program [6]. While these programs can include a variety of different components such as workplace safety or smoking cessation, increasing physical activity and exercise are common focuses in many programs [7].

Incentivizing participation is a frequently-used technique that has resulted in higher participation rates in wellness and exercise programs [7,8,9,10]. Incentives for program participation might include financial rewards such as discounts on health insurance, or more commonly, gifts or prizes [6]. The use of incentive-based formats is especially common in exercise-specific programs, as they allow for customization, goal-setting, documented outcomes, and camaraderie among participants [11,12]. Such programs might offer payment or prizes when participants reach various milestones, such as a certain number of gym visits, minutes of exercise, or miles walked within a specified time period. Similar to larger-scale wellness programs, exercise-specific incentive programs have varying degrees of success. Financial incentives have been found to result in increased exercise during the program, as well as persisting exercise behavior after the program’s conclusion [13]. Incentivized participants reported improvements in health indicators as well as increased gym attendance compared with non-incentivized participants [8]. However, results regarding various success measures of incentivized exercise programs remain mixed. Reference [14] reported only slight differences in gym attendance when incentivized with cash or prizes, and no differences in continued visits after the incentive period was over.

With so many different considerations for exercise incentive program design, it is worth examining specific program aspects that are associated with greater success. One such consideration is the type of incentive offered. Positive incentives that present something of value to participants if they meet program goals seem to be more successful than punitive incentives that take something away from participants if they don’t meet those goals [15]. Also, exercise incentive program participants can become accustomed to incentives over time [10]. Program administrators can adjust incentive strength or scheduling to address this potential loss of incentive effectiveness [8].

While incentive-based formats are commonly used in organizationally-sponsored exercise programs, [3] identify less than one-third of participants as rating this technique as “effective”. This illustrates a need to consider additional factors that might facilitate exercise incentive program participation, adherence, and enjoyment. In addition to examining program components that may enable greater program success, effective program design must also consider various intrapersonal factors such as motivations, preferences, and attitudes of program participants. These elements of intention and connection with participants are critical for the program administrator to incorporate into exercise program design [15]. Reference [6] especially stresses the importance of making exercise incentive programs attractive to participants, particularly mentioning the consideration of individual motivation. Reference [16] further emphasizes designing exercise programs with individual motivational styles in mind to optimize participation, adherence, and success measures. Incorporating behavioral or motivational theories into exercise incentive program design may provide additional insights regarding the interactions between program design and intrapersonal factors. For example, Self-Determination Theory has been utilized in exercise incentive programs in examining the degree to which externally rewarding exercise behaviors might detract from participants’ own intrinsic motivation to perform those behaviors [17]. Another theory regarding the regulation of behavior that might be relevant to exercise incentive program outcomes is Causality Orientations Theory.

Developed by [18], Causality Orientations Theory poses three different tendencies at work in regulating intentional behaviors. Self-determined, or autonomous behaviors are motivated by one’s self-awareness of needs and goals, and contain a high degree of choice. Control-determined behaviors are also characterized by a degree of individual choice, but are primarily influenced by regulatory external elements such as deadlines, rewards, or consequences. Finally, amotivated, or impersonal behaviors are influenced by external factors and perceptions that outcomes are out of one’s control [18]. Applied to exercise behaviors, the idea that individuals vary in their behavioral regulation tendencies gives insight into different ways that exercise programs could be adjusted to appeal to individual preferences. For example, the use of rewards for exercise program completion milestones might be an important motivator for some orientations, but not others. On one hand, exercise program administrators can adjust program elements to enhance short-term program approach and participation from individuals experiencing various orientations. However, a long-term goal in considering causality orientation in exercise might be to ultimately facilitate exercise environments that promote autonomously-regulated behaviors that might result in lasting adherence [16].

While incentives have been associated with success measures in exercise programs compared to non-incentivized programs, there remains a need to make these programs more inviting to participants. Considering that behavior regulation and motivation vary between individuals, it is important to include these intrapersonal factors in programs that aim to facilitate exercise behaviors. Given that incentives are commonly included in exercise program formats, we hope to identify ways in which these specific types of programs serve individuals with varying levels of causality orientations. This study aims to investigate Causality Orientations Theory as it relates to the experiences and outcomes of participants in an exercise incentive program that offered rewards for a target number of steps walked. Results might be used to enhance exercise incentive program design in optimizing participation and outcomes.

1.1. Research Questions

The exploratory nature of this study resulted in research questions inquiring about exercise program considerations such as exercise frequency, motivation, and adherence. These variables were then compared across the three different exercise causality orientations.

1) Did self-reported walking and other exercise frequency differ before, during, and after the walking challenge program?

2) To what degree did participants report different exercise goal achievement before, during, and after the walking challenge program?

3) To what degree did participants report different levels of motivation to exercise before, during, and after the walking challenge program?

4) How did these three previous test variables differ according to exercise causality orientation of participants?

2. Methods

2.1. Procedure

A 6-week exercise incentive program was administered during the fall academic semester by the Employee Wellness Program at a public higher education institution in the mid-south. Titled the “Fall Step Challenge”, the program invited participants to track and submit the number of steps they walked per week. The program was offered to all university employees, and students were welcomed to participate as well. Participation was voluntary, free of charge, and incentivized by offering various prizes for completing an established number of steps per week. Participants received regular emails that contained various cues to action and motivational messages, encouraging them to complete and record their weekly steps in a Google form. Participants who accumulated 40,000 steps within a week were invited to enter a weekly drawing for small prizes such as fitness bands and exercise mats. The first 100 participants who registered for the program also received a t-shirt.

Prior to data collection, the researcher obtained human subjects research approval through the relevant institutional review board. A web-based survey was administered to program participants immediately after the program’s conclusion. The researcher distributed the survey by sending an invitation via email to all of the participants who registered for the program.

2.2. Instrument

A web-based questionnaire was utilized through Qualtrics Survey Software. The first section contained 4 questions related to demographics. The instrument also contained five items that assessed exercise frequency, exercise goal-achievement, and exercise motivation before, during, and after the exercise incentive program. Retroactively, participants indicated their activity frequency, exercise goal-achievement, and exercise motivation prior to starting the program, during the program, and at the completion of the program.

The second part of the questionnaire included the Exercise Causality Orientations Scale (ECOS). Rose et al. (2001) developed this scale to assess the strength of three different causality orientations (autonomy orientation, control orientation, and impersonal orientation) during various exercise scenarios. Participants were presented with seven different exercise scenarios and then asked about the likelihood of performing a certain behavior based on the three different causality orientations. For example, scenario one asks, “You are beginning a new exercise program. You are likely to: 1) ‘Decide for yourself which type of exercise you would like to complete (autonomy orientation).’, 2) ‘Attend a structured exercise class where an exercise leader is telling you what to do (control orientation).’ and 3) ‘Tag along with your friends and do what they do (impersonal orientation).’” Participants then selected their likelihood of performing each behavioral scenario within the item’s context on a 7-point scale from 1 (very unlikely) to 7 (very likely).

Higher scores on ECOS items indicated that a participant was more likely to perform the specified behavior. The instrument does not categorize a participant in one particular causality orientation, rather it scores the individual strength of each of the 3 causality orientations within their overall personality. The ECOS demonstrated appropriate internal consistency for the seven-scenario model, (α = .59 - .70), as well as convergent validity with measures of similar constructs. The ECOS also demonstrated test-retest reliability for all three orientations, (r = .71 - .77, p = .001) (Rose et al., 2001).

3. Results

Ninety-three out of 174 participants completed the questionnaire, resulting in a response rate of 53%. Seventy-three (78.4%) of the participants were female, and 20 participants (21.5%) were male. Among the racial composition, 51.6% of participants reported as White/Caucasian, 38.7% reported as Black/African-American, 5.4% were Asian, 3.2% were Hispanic/Latino/Spanish, and 1.1% reported as American Indian or Alaska native. Sixty-nine (74.2%) participants were staff, 18 (10.4%) were faculty, and 6 (6.5%) were students. Table 1 illustrates the demographics of respondents.

Table 1. Demographic Characteristics of Participants

3.1. Activity Frequency, Exercise Goal Achievement, and Exercise Motivation Before, During, and After the Exercise Program

Measures of central tendency and variability were calculated for three test variables. These included: 1) walking and other exercise frequency, 2) frequency of achieving exercise goals, and 3) level of motivation to adhere to an exercise plan. Participants were asked to assess and self-report regarding each variable before, during, and after their participation in the Fall Step Challenge incentive program.

3.1.1. Walking and Other Exercise Frequency

Participants self-reported walking frequency for general fitness, as well as the frequency with which they performed other types of exercise. They selected answer choices along a Likert scale from 1 (no activity) to 8 (six times per week or more). Table 2 displays mean scores and standard deviations of walking and other exercise frequency during each time period.

Table 2. Means and Standard Deviations for Walking and Other Exercise Frequency

A repeated measures ANOVA was utilized to compare walking and other exercise frequency before, during, and after the Fall Step Challenge program. Results of the analyses indicated that participants reported significantly different walking frequencies before, during, and after the Fall Step Challenge program, F(2, 274) = 9.99, p < .001. Tukey post-hoc analyses revealed that participants walked significantly more during the program (M = 6.45, SD = 1.63) than before the program (M = 5.22, SD = 2.04), p < .001. Participants also walked significantly more after the program’s completion (M = 5.97, SD = 2.01) than they did before the program (M = 5.22, SD = 2.04), p = .021. Participants were also asked how frequently they performed other types of exercise before, during, and after the Fall Step Challenge program. Although participants reported slightly more frequent exercise during the challenge, there was no significant difference in the frequency of exercise types other than walking before, during, or after the program.

3.1.2. Exercise Goal Achievement

Using a Likert scale from 1 (strongly disagree) to 5 (strongly agree), participants were asked to indicate their level of agreement with statements about exercise goal achievement before, during, and after the Fall Step Challenge program. Higher mean scores indicated higher levels of exercise goal achievement. Table 3 displays mean scores and standard deviations for participants’ level of exercise goal achievement.

Table 3. Means and Standard Deviations for Exercise Goal Achievement

A repeated measures ANOVA was used to compare exercise goal achievement before, during, and after the Fall Step Challenge program. Results of the analyses determined that participants indicated significant differences for exercise goal achievement before, during, and after the Fall Step Challenge program, F (2, 274) = 19.20, p < .001. The Tukey post-hoc analyses found that participants reported significantly higher levels of exercise goal achievement during the challenge (M = 3.98, SD = 1.07) than either before the challenge (M = 2.88, SD = 1.32), p < .001 or after the challenge (M = 3.55, SD = 1.21), p = .046. Additionally, participants reported higher levels of exercise goal achievement following the challenge program than compared to before the challenge program, p = .001.

3.1.3. Exercise Motivation

Participants were also asked to report their exercise motivation before, during, and after the Fall Step Challenge program. Exercise motivation was measured on a Likert scale of 1 (strongly unmotivated) to 5 (strongly motivated), with higher scores indicating higher levels of exercise motivation. Table 4 displays mean scores and standard deviations for exercise motivation during various stages of the Fall Step Challenge program.

Table 4. Means and Standard Deviations for Exercise Motivation

A repeated measures ANOVA was used to compare exercise motivation before, during, and after the Fall Step Challenge program. Results of the analyses showed significant differences in exercise motivation before (M = 3.29, SD = 2.21), during (M = 4.45, SD = .63), and after the Fall Step Challenge program, (M = 4.01, .98), F (2, 274) = 31.92, p < .001. The Tukey post-hoc analyses found that participants reported significantly different levels of exercise motivation during the challenge compared to before, p < .001, or after the challenge program, p = .008. Additionally, participants reported feeling more motivated to exercise after the challenge then before, p < .001.

3.2. Exercise Causality Orientation

The Exercise Causality Orientation Scale (ECOS) was used to assess the strength of 3 causality orientations in 7 different exercise scenarios. The orientations assessed were autonomy, control, and impersonal. Measures of central tendency and variability were calculated for each orientation in each of the 7 exercise scenarios (Table 5). Mean scores and standard deviations were also calculated cumulatively across all 7 scenarios. Cumulatively across all 7 scenarios, participants reported higher levels of autonomy orientation, followed by a control and impersonal orientation (Table 6).

Table 5. Means and Standard Deviations for Exercise Causality Orientation Scale Items

Table 6. Means and Standard Deviations for Primary Causality Orientation Type

We used a T-test to compare means between genders for each exercise scenario on the ECOS. The only exercise causality orientation displaying differences in means between genders was the autonomy orientation in scenario 2. This scenario presented a hypothetical situation in which the participant was asked to keep a record of all the weekly exercise they have completed in an exercise diary. Different viewpoints of the diary represented different exercise causality orientations. Women (M = 6.05, SD = 1.28) were significantly more likely to react to this scenario with an autonomy orientation than men (M = 5.3, SD = 1.38), t (92) = 2.2, p(2-tailed) = .036.

3.3. Exercise Causality Orientation and Exercise Frequency

A one-way ANOVA was performed to analyze differences in walking and other exercise frequency according to the participant’s primary exercise causality orientation. We calculated this by summing the exercise causality orientation scores across all seven items. Walking frequency significantly differed based on exercise causality orientation during the Fall Step Challenge program, F (2, 81) = 4.491, p = .014. Tukey post-hoc tests were used to analyze specific differences between exercise causality orientations. Findings from this analysis demonstrated that participants who scored higher on autonomy orientation had higher levels of walking frequency compared to participants who scored higher on impersonal orientation. No significant differences were found in other exercise frequency between the control, autonomy, and impersonal orientations.

3.4. Exercise Causality Orientation and Exercise Goal Achievement

A one-way ANOVA was used to analyze differences in exercise goal achievement before, during, and after the Fall Step Challenge program. Findings from this analysis demonstrated that participants’ primary exercise causality orientation was not significantly related to exercise goal achievement before, during, or after the Fall Step Challenge program.

3.5. Exercise Causality Orientation and Exercise Motivation

A one-way ANOVA was utilized to measure differences in participants' exercise motivation before, during, and after the Fall Step Challenge program based on exercise causality orientation. Causality orientation was significantly related to higher levels of exercise motivation before the Fall Step Challenge program, F (2, 81) = 3.05, p = .05. The post hoc analysis revealed that participants who primarily exhibit a control orientation reported significantly higher levels of exercise motivation than participants with an impersonal orientation, p = .041.

Exercise motivation during the Fall Step Challenge program also differed according to causality orientation, F (2, 81) = 3.89, p = .024. The Post hoc analysis showed that participants who primarily report a control orientation reported significantly more exercise motivation than participants reporting a primarily impersonal orientation, p = .02.

4. Discussion

4.1. Walking Frequency before, during, and after the Program

Participants reported that while engaged in the Fall Step Challenge program they significantly increased their walking frequency. In this limited context, incentivized exercise programs can help participants achieve a positive outcome related to a specific type of exercise. These findings are congruent with studies which demonstrate positive outcomes related to similarly-formatted exercise incentive programs [8,12,13].

Furthermore, participants also reported an increase in walking frequency following the completion of the Fall Step Challenge program as compared to before they began the program. This suggests that incentive-based exercise programs might help promote and sustain exercise behavior beyond the duration of the prescribed program [8]. Future studies should consider the relationship between incentive-based exercise programs and how long participants continue exercise behavior beyond the prescribed program [13].

While participation in the Fall Step Challenge program was related to increases in walking frequency during and after the program, it did not seem to be related to increases in the frequency of other exercise types besides walking. This could suggest that incentive-based exercise programs might be limited in their applicability beyond program-specific exercise. For example, a walking program might increase walking frequency, but might not be helpful in producing increased frequency among other exercise types such as resistance training. On the other hand, effects occurring relative to the specified program activity might be useful in targeting a featured activity type to which program managers wish to draw attention.

4.2. Exercise Causality Orientation and Walking Frequency

Causality orientation was examined as an intrapersonal variable as it related to participants’ exercise frequency, as well as self-reported exercise goal-achievement and exercise motivation. Findings related to exercise causality orientation and walking frequency demonstrated that walking frequency differed according to orientation, specifically between those reporting a predominantly autonomy orientation and those reporting a predominantly impersonal orientation. In other words, those who felt better able to control or regulate their motivation and behavior walked more frequently. Likewise, those with primarily impersonal orientations may have walked less because of inability to perceive control over exercise behavior. These findings support [13]’s assertions that causality orientations can relate to differences in exercise behaviors. It is helpful for exercise program managers to know that those with autonomy orientation might be more inclined to adhere to exercise programs, so that they can shift efforts to enhance adherence among other causality orientations.

4.3. Exercise Causality Orientation and Exercise Goal Achievement

Participants reported higher agreement with meeting their exercise goals both during and after the walking challenge program than before it. The result that program participation was related to the perception of goal achievement might illustrate the value of feedback in exercise incentive programs. These types of programs provide tangible reinforcement that provide targets for exercise behaviors, and then provide measurable feedback about performance. Exercise program goals and outcomes presented in a quantifiable manner may allow participants to be more aware of their achievements.

However, exercise causality orientation did not have any significant relationship with the degree to which participants felt that they met their exercise goals. This finding seems to contradict the notion that causality orientation provides a context within which participants might attribute their ability to achieve an established goal [18]. The walking challenge program used in the current study utilized pre-established activity goals that were set by the program manager. Perhaps the findings that causality orientation was unrelated to the perception of meeting exercise goals neglects a distinction between self-generated goals versus those set by an external, arbitrary factor.

4.4. Exercise Causality Orientation and Exercise Motivation

Participants reported being significantly more motivated to exercise during the walking challenge program than either before the program or after it. This finding supports previous literature demonstrating an immediate effect of current program participation [8]. However, while participants reported being more motivated to exercise during the program than after, they also reported more exercise motivation after the program’s conclusion than before it. This provides limited support to previous findings that program effects may continue to some degree after the program’s conclusion [13].

Results indicated differences in exercise motivation levels according to predominant exercise causality orientation. Participants who identified primarily with control orientation reported higher levels of exercise motivation before and during the Fall Step Challenge program than participants who identified primarily with impersonal orientation. These findings support [18]’s and [16]’s definition of a control orientation as externally influenced, yet still capable of internal regulation. Those with primarily control orientation might be especially motivated by exercise programs utilizing tangible incentives and deadlines as motivators for participation. It is interesting to note that while those with control orientation reported the most exercise motivation, they did not report the most walking activity. This finding provides another insight for program managers to be aware of in that some participants may report more motivation, but that increased motivation does not necessarily translate to increased exercise activity. Program managers might be better able to address this gap between motivation and behavior by being aware of these differences according to causality orientation among program participants.

5. Conclusions

The current study examines Exercise Causality Orientation as it relates to an exercise program utilizing an incentive-based format to reward participant outcomes. Exercise incentive programs are an effective way to help people increase exercise frequency and exercise behavior [11,12]. Despite demonstrated effectiveness and popularity of this program format among organizationally-sponsored exercise programs, these types of programs still fail to connect with many of their intended participants [6]. In examining ways to improve this specific type of exercise program, participants’ exercise causality orientation might be considered prior to program design and implementation. This approach heeds [6]’s call to involve and engage participants in exercise program design; as well as [16]’s recommendations to consider individual motivations and behavior regulation in order to optimize exercise program participation.

The current study showed that exercise incentive programs are associated with increased activity frequency, but might not have a carry-over effect for other activity types. Similar to previous findings, the effectiveness of incentivizing specific behaviors can be a useful consideration in designing exercise programs. However, the current study also supports previous findings that these immediate effects are limited. Exercise program administrators should celebrate the achievement of specific program outcomes, but should not assume that these outcomes can be generalized to other exercise types, or persist beyond the program’s conclusion. Considering causality orientation in program design may have implications in improving the generalizability and durability of program effects. For example, an exercise program manager might choose to feature an exercise activity (such as strength training) that they would like to specifically increase. If this activity was deemed to be underutilized by the target population, then a specific incentive program featuring that activity might be effective in increasing that specific behavior. In addition, program managers might consider follow-up measures or activities intended to help participants persist in exercise behaviors after the program’s conclusion, rather than simply allowing the program to end.

Our study also supports the idea that different exercise causality orientations can result in preferences for different exercise program styles and exercise behavior outcomes. This comparison illustrates important differences in perceptions and outcomes of participants in the same program. A program manager might use knowledge of these differences to more directly connect to participants of different causality orientations. By taking causality orientations of participants into account, program developers could customize various program aspects such as self-selection of exercise type, type of incentives, or daily reports of small accomplishments for each of the three orientations. This customization might enhance exercise frequency, motivation, and goal achievement for the various types of exercise causality orientation. For example, the current study showed that those with predominantly control orientation reported the most motivation, while those with primarily autonomy orientation reported the most activity. Knowing that those with control orientation report more motivation but not necessarily more activity might help a program manager to keep fostering motivation within this specific group, but give extra attention to boosting actual activity levels, such as using more frequent communication or reward intervals.

Although our findings shed some light on the relationship between exercise causality orientation and participation in exercise incentive programs, many questions still remain. For example, does a person’s exercise causality orientation have an effect on how much they enjoy and/or participate in different exercise types? Do exercise incentive programs that encourage/promote a specific exercise type (e.g., walking) increase the likelihood of participation in other exercise types or programs? Does the convenience of the exercise type influence participants’ level of participation and exercise frequency rates? Would exercise incentive programs that are aligned with participants’ exercise causality orientation produce better results and have higher participation rates?

Future studies might address the relationship between participants’ exercise causality orientation and types of exercise selected or preferred by those participants. Additional studies could also evaluate the relationship between exercise causality orientation and participation frequency among various exercise types. Determining how exercise causality orientation is related to selection of exercise type and/or exercise frequency may improve participation in exercise incentive programs, and more importantly, improve the health and well-being of those who participate in the programs.

5.1. Limitations

This study presented several limitations. A disproportionate number of women were represented in the sample, resulting in limited applicability of results across genders. However, this gender imbalance in the sample also represented a disproportionate number of women who chose to participate in the voluntary exercise program. This is consistent with women preferring structured exercise programs such as group fitness classes or personal training more than men [19]. Even though the sample reflects a general disproportion between genders who participate in structured exercise programs, this incongruity might not provide a good understanding of exercise causality orientation as it relates to men.

The current study also utilized walking as its primary exercise activity. Considering that exercise motivations differ according to activity preferences, the activity type used in this study may have influenced motivation or adherence without being accounted for [20]. Additionally, examining walking as the only treatment-related activity limits the generalizability of results to other exercise types.

An important assumption in the use of prizes to incentivize participation in exercise programs is that participants find those prizes to be attractive and motivating. The current study offered non-cash prizes that may not have had consistent desirability between participants. While previous research has found that types of incentives offered and the way in which they are presented may affect program outcomes, the current study did not take qualitative aspects of the incentives offered into consideration [15].

Acknowledgements

We would like to thank the staff of the UA-Little Rock Wellness program for granting us permission to collect data resulting from their Fall Step Challenge walking program.

References

[1]   | Centers for Disease Control and Prevention. (2021b). Physical activity basics. https://www.cdc.gov/physicalactivity/basics/pa-health/index.htm.
[2]   | Centers for Disease Control and Prevention. (2020). 2019 National Health Interview Survey.
[3]   | Centers for Disease Control and Prevention. (2021a). Fact Sheets and At-a-Glances: Lack of Physical Activity. https://www.cdc.gov/chronicdisease/resources/publications/factsheets/physicalactivity.htm#:~:text=Low%20 levels%20of%20physical%20activity,annually%20in%20health% 20care%20costs.
[4]   | Kirkham, H.S., Clark, B.L., Bolas, C.A., Lewis, G.H., Jackson, A.S., Fisher, D., & Duncan, I. (2015). Which modifiable health risks are associated with changes in productivity costs? Population Health Management, 18(1), 30-38.
[5]   | Wagner S., White M., Schultz I., Murray E., Bradley S.M., Hsu V., McGuire L., Schulz W. (2014). Modifiable worker risk factors contributing to workplace absence: A stakeholder-centered best-evidence synthesis of systemic reviews. Work, 49(4), 541-58.
[6]   | Linnan, L., Cluff, L., Lang, J.E., Penne, M., & Leff, M.S. (2019). Results of the Workplace Health in America Survey. American Journal of Health Promotion, 33(5), 652-665.
[7]   | Pollitz, K., & Rae, M. (2016, May 19). Workplace wellness programs characteristics and requirements. Kaiser Family Foundation. https://www.kff.org/private-insurance/issue-brief/workplace-wellness-programs-characteristics-and-requirements/.
[8]   | Charness, G., & Gneezy, U. (2009). Incentives to exercise. Econometrica, 77(3), 909-931.
[9]   | Mattke, S., Kapinos, K., Caloyeras, J.P., Taylor, E.A., Batorsky, B., Liu, H., Van Busum, K.R., & Newberry, S. (2015). Workplace wellness programs: Services offered, participation, and incentives. Rand Health Quarterly, 5(2).
[10]   | Pope, L.,Harvey-Berino, J. (2013) Burn and earn: A randomized controlled trial incentivizing exercise during fall semester for college first-year students. Preventive Medicine, 56 (3-4), 197-201.
[11]   | Haugen, K. (2009). Creating incentive campaigns. ACSM’s Health & Fitness Journal, 13(2), 22-26.
[12]   | Smith-McLallen, A., Heller, D., Vernisi, K., Gulick, D., Cruz, S., & Snyder, R.L. (2016). Comparative effectiveness of two walking interventions on participation, step counts, and health. American Journal of Health Promotion, 31(2), 119-127.
[13]   | Mitchell, M.S., Goodman, J.M., Alter, D.A., John, L.K., Oh, P.I., Pakosh, M.T., Faulkner, G.E. (2013). Financial incentives for exercise adherence in adults: Systematic review and meta-analysis. American Journal of Preventive Medicine, 45(5), 658-667.
[14]   | Carrera,M., Royer, H., Stehr, M., Sydnor, J. (2017). Can financial incentives help people trying to establish new habits? Experimental evidence with new gym members. IZA Institute of Labor Economics. Discussion Paper Series No. 10874.
[15]   | Berry, L.L., Mirabito, A.M., & Baun, W.B. (2010). What’s the hard return on employee wellness programs? Harvard Business Review, 88(12), 104-112.
[16]   | Rose, E.A., Markland, D., & Parfitt, G. (2001). The development and initial validation of the Exercise Causality Orientations Scale. Journal of Sports Sciences, 19, 445-462.
[17]   | Jeffery, R., Thorson, C., Wing, R., & Burton, L. (1998). Use of personal trainers and financial incentives to increase exercise in a behavioral weight-loss program. Journal of Consulting and Clinical Psychology, 66(5), 777-783.
[18]   | Deci, E. & Ryan, R. (1985). Intrinsic motivation and self-determination in human behaviour. New York: Plenum Press.
[19]   | Helms, K. (2018). Sources of influence in exercise planning among college students. Applied Recreational Research and Planning Annual, 7, 1-20.
[20]   | Box, A.G., Feito, Yo, Brown, C., & Petruzzello, S.J. (2019). Individual differences influence exercise behavior: how personality, motivation, and behavioral regulation vary among exercise mode preferences. Heliyon, 5(4), 1-22.