Effects of a single message exposure on exercise motivation and behavior among adults aged 30-45

International Journal of Health Promotion and Education ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/rhpe20 Effects of a single message exposure on exercise motivation and behavior among adults aged 30-45 Emily L. Mailey, Deirdre Dlugonski, Gina M. Besenyi, Rebecca Gasper & Stacey Slone To cite this article: Emily L. Mailey, Deirdre Dlugonski, Gina M. Besenyi, Rebecca Gasper & Stacey Slone (2022): Effects of a single message exposure on exercise motivation and behavior among adults aged 30-45, International Journal of Health Promotion and Education, DOI: 10.1080/14635240.2022.2031250 To link to this article: https://doi.org/10.1080/14635240.2022.2031250 Published online: 15 Feb 2022. Submit your article to this journal Article views: 49 View related articles View Crossmark data Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=rhpe20 INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION https://doi.org/10.1080/14635240.2022.2031250 Effects of a single message exposure on exercise motivation and behavior among adults aged 30-45 Emily L. Maileya, Deirdre Dlugonskib, Gina M. Besenyia, Rebecca Gaspera and Stacey Slonec a Department of Kinesiology, Kansas State University, Manhattan, KS, USA; bDepartment of Athletic Training and Clinical Nutrition, University of Kentucky, Lexington, KY, USA; cDepartment of Statistics, University of Kentucky, Lexington, KY, USA ABSTRACT ARTICLE HISTORY Promoting intrinsic affective exercise benefits may facilitate autonomous motivation and exercise behavior. However, most media messages primarily emphasize extrinsic weight and health-related benefits. This study examined whether altering exercise messages would influence individuals’ exercise motivation and behavior. Using a 2 × 2 factorial design, message frames were manipulated on the following dimensions: Intrinsic/Extrinsic exercise goal and Easy/Hard exercise routine. A representative sample of adults aged 30–45 (N = 505) completed measures of leisure-time exercise and motivation and then were randomly assigned to view one of the four messages or a control message. Immediately after viewing the message, participants indicated their primary exercise goal. One week later, they completed the exercise and motivation measures again. An ANCOVA revealed no between-group differences in motivation or exercise behavior. Relative to the extrinsic and control conditions, participants in the intrinsic message conditions were more likely to identify an effective primary exercise goal immediately after viewing the message. Overall, a single message exposure did not significantly affect individuals’ exercise motivation or behavior in this sample. Future studies should consider honing optimal message content, assessing message understanding and determining the minimum dose of message exposure needed for a meaningful impact. Received 7 June 2021 Accepted 15 January 2022 KEYWORDS Physical activity; intrinsic; extrinsic; self-determination theory; message framing Introduction Over the past several decades, the field of exercise science has accumulated an abundance of knowledge regarding the widespread benefits of physical activity. As the evidence base supporting the relationships between physical activity and chronic disease has grown, physical activity guidelines have been developed to encourage the public to engage in sufficient activity to reap these well-established health benefits (USDHHS 2018). In spite of these major advances in our field and the proliferation of knowledge about the benefits of physical activity, physical activity levels have remained discouragingly low in the United CONTACT Emily L. Mailey Ave. Manhattan, KS 66506 emailey@ksu.edu © 2022 Institute of Health Promotion and Education Department of Kinesiology, Kansas State University, 920 Denison 2 E. L. MAILEY ET AL. States and other developed countries. In 2018, about 54% of American adults engaged in recommended amounts of aerobic activity, and only about 24% of American adults met the guidelines for both aerobic and muscle-strengthening activity (CDC 2018). Although the causes of this widespread inactivity are complex, one potential contributor may be the way in which we have typically communicated about physical activity, and in particular exercise, to the public. In general, exercise promotion messages in the popular media, and even those delivered by reputable health organizations, have not targeted theoretical constructs or behavior change techniques known to be associated with exercise behavior (Gainforth et al. 2011). In the popular media and the fitness industry, exercise is most often portrayed as a means to lose weight and/or achieve rapid changes in appearance (Berry and Latimer-Cheung 2013; Brown, Miller, and Palmer 2017). Thus, individuals have been socialized to think about exercise in terms of these extrinsic benefits (Smith and Bonfiglioli 2015). Unfortunately, evidence is mounting that appearance and health-related reasons for exercise do not motivate sustained behavior as well as affective benefits (e.g. reduced stress, improved energy) that may contribute more immediately to one’s daily well-being (Gellert, Ziegelmann, and Schwarzer 2012; Mailey et al. 2018; Segar, Eccles, and Richardson 2011). From a Self-Determination Theory perspective, outcomes such as weight loss and appearance are considered extrinsic goals (i.e. outwardly focused on external indicators of success), and focusing on such goals may elicit controlled motivation, or a sense that one should be exercising to meet others’ expectations (i.e. external regulation) or to avoid self-induced guilt or shame (i.e. introjected regulation) (Deci & Ryan, 2000). On the other hand, affective outcomes generally represent intrinsic goals (i.e. inwardly focused on personal growth), which tend to be more strongly associated with autonomous motivation, or a genuine sense that one wants to be active, because they value the benefits (i.e. identified regulation) or derive enjoyment and satisfaction from the experience itself (i.e. intrinsic regulation) (Deci and M 2000). Thus, shifting the exercise promotion narrative to better emphasize affective benefits has been identified as an important public health priority (Segar et al. 2016). In line with these efforts, several studies have examined whether exercise messages that highlight affective benefits have a positive effect on the motivation and behavior of those receiving the messages. Segar and colleagues (2012) found overweight women aged 40–60 who viewed an advertisement emphasizing daily well-being reported greater autonomous motivation than those who viewed an advertisement emphasizing weight loss, but overweight men exhibited the opposite response and reported higher autonomous motivation after viewing the weight loss advertisement. Conner et al. (2011) found college students who received a message highlighting affective outcomes of exercise (e.g. reduced stress) reported significantly more exercise 3 weeks later than participants who received a message highlighting instrumental outcomes (e.g. reduced risk of chronic disease). Recently, Hevel et al. (2019) compared the effects of messages highlighting affective versus physical health benefits on motivation to join an exercise class among adults in a university community and found that the affective messages were associated with greater motivation among active, but not inactive individuals. Together, these studies show some promise for the positive effects of messages emphasizing affective benefits on exercise motivation and behavior, but also reveal some inconsistent effects that warrant further investigation. INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 3 There have also been calls to revise our exercise messages to emphasize that any movement is beneficial (Arena et al. 2018). Women, in particular, have reported negative reactions to ‘typical’ messages that portray exercise as grueling and time-consuming because they do not feel that they represent what they can realistically do (Thai et al. 2019). Evidence is emerging that moving away from ‘no pain, no gain’ type messages may have a positive impact on individuals’ exercise perceptions and behavior. In a sample of UK adults, Knox et al. (2015) compared messages that emphasized physiological aspects of activity (e.g. increased breathing and heart rates) to messages that emphasized an ‘easier’ approach (i.e. walking), and found participants reported greater intentions to be active in the walking message group as a function of more positive affective attitudes towards physical activity. Similarly, a review by Latimer, Brawley, and Bassett (2010) found preliminary evidence that participants report greater confidence to engage in physical activity if the behavior is framed as easy (e.g. moderate intensity, manageable time commitment) as opposed to difficult of complex (e.g. vigorous intensity, substantial time commitment). Willis and Knobloch-Westerwick (2014) recently conducted a scoping review of physical activity messaging, and reported that the existing evidence generally supports the use of gain-framed messages (i.e. emphasizing benefits of physical activity) over loss-framed messages, as well as messages that emphasize short-term mental and emotional benefits. Other recommendations included ground messages in theory, target-specific demographic groups, incorporate ‘how to’ information in messages and use ‘commercial style messages’. The present study sought to incorporate these recommendations and add to the message framing literature in several ways. First, although adults in general have been a common target of message framing studies, this study aimed to focus on adults aged 30–45 because they are likely to be balancing multiple demands, including work and caring for children and/or aging parents, and thus may find it difficult to prioritize exercise amidst all of their other obligations (Mailey et al. 2014; Welch et al. 2009). Additionally, although previous studies have examined messages promoting intrinsic vs. extrinsic physical activity benefits and depicting exercise as easy vs. hard, to our knowledge, no previous studies have examined the potential interaction between these two approaches. Previous studies have examined the effects of single and multiple message exposures; this study utilized a single exposure to examine the impact, if any, of fleeting encounters with exerciserelated messages that are likely among individuals who seek health and exercise information online. The overall purpose of the present study was to examine whether a single exposure to an exercise message could impact motivation, exercise behavior, or exercise goals among adults aged 30–45. Messages highlighted affective (intrinsic) or instrumental (extrinsic) exercise goals and described exercise as easy or hard. Our primary hypothesis was that individuals exposed to messages depicting intrinsic goals and portraying exercise as easy would report greater autonomous motivation and exercise behavior at one-week followup relative to individuals exposed to messages depicting extrinsic goals and portraying exercise as hard. Our secondary hypothesis was that individuals who viewed an intrinsic message would be more likely to identify an affective primary exercise goal, whereas individuals who viewed an extrinsic message would be more likely to identify a weight/ appearance-related primary exercise goal immediately after viewing the message. Finally, 4 E. L. MAILEY ET AL. we explored the overall frequency of primary exercise goals reported and the extent to which motivation and exercise behavior differed among participants endorsing different goals. Methods Study design This study employed a 2 × 2 factorial design, whereby message frames were manipulated on the following dimensions: Intrinsic/Extrinsic exercise goal and Easy/Hard exercise routine. All participants viewed the exact same image and recommended exercises but were randomly assigned to receive one of the four messages or to a control condition that did not view any image or recommended exercises. The control condition was included to determine whether exposure to any exercise message (regardless of content) would influence exercise motivation or behavior. Participants viewed the exercise ‘advertisement’ immediately following completion of the baseline questionnaires and completed follow-up measures 1 week later. All procedures were approved by the university's Institutional Review Board, and all measures were completed online via Qualtrics. Message development In developing the advertisement and messages, we chose to emphasize weight loss as the extrinsic exercise goal because of the prevalence of weight-related messages in the popular media (Bazzini et al. 2015; Willis and Knobloch-Westerwick 2014). All messages were gain-framed and highlighted the potential benefits of exercise. The specific language used to describe Intrinsic/Extrinsic goals and an Easy/Hard exercise routine was adapted from language commonly observed in popular magazines (Mailey, Gasper, and Dlugonski 2019). The final terms selected were as follows: An immediate boost in your energy and mood (Intrinsic Goal), To blast fat and lose weight fast (Extrinsic Goal), Quick, Easy (Easy Routine) and High-intensity, hard-core (Hard Routine). The advertisement recommended an at-home circuit because it would be feasible for individuals to complete without access to a gym or expensive equipment, and individuals could tailor the workout to their preferred intensity and duration. The suggested exercises included a mix of aerobic and strength-based activities that could, if completed in quick succession, contribute to both the aerobic and muscle strengthening physical activity recommendations. We included photos to make the advertisement visually appealing. The photos selected were intended to be neutral and represented both a man and a woman in exercise attire (Figure 1). Participants Participants were recruited in July 2018 using the Qualtrics Panels service, which facilitates sample recruitment from a national pool of volunteers. The Qualtrics team contacted members of their panels within the designated age range (30–45) and informed them that there was a survey they may be eligible to complete. Individuals who accessed the survey completed a screening question to indicate that they could safely participate in INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 5 Figure 1. Exercise ‘advertisement’ (easy, intrinsic condition). exercise, then provided demographic information, which Qualtrics used to ensure the race/ethnicity of final sample was representative of the US population. Qualtrics employed pre-set gender quotas for each of the conditions, so that the final sample had equal distributions of male and female participants across all conditions. Procedures All participants provided informed consent online before proceeding to the questionnaires. Exercise advertisements were embedded into the baseline Qualtrics survey, and a Randomizer feature was used to randomly assign participants to one of the five conditions: Intrinsic Easy, Intrinsic Hard, Extrinsic Easy, Extrinsic Hard, or control. Qualtrics utilized a number of procedures to screen out invalid responses. Specifically, responses were discarded if response time was faster than a set minimum (determined by the length and complexity of the survey), if they included gibberish responses to openended items or if they selected the same response choice (e.g. strongly agree) on a set of multiple-choice items where different responses would be expected. After these screening procedures had been completed and 500 initial responses were obtained, the primary 6 E. L. MAILEY ET AL. investigator conducted a second inspection of all data to identify other potential issues that may have been missed. An additional 87 responses were discarded because they met at least one of the following criteria: 1) implausible values on the measure of exercise behavior (e.g. single-digit responses to exercise duration questions) or 2) incongruent response patterns on the exercise motivation questionnaire (e.g. selecting ‘strongly agree’ and ‘strongly disagree’ for similarly worded items). These participants were subsequently replaced by Qualtrics with new participants until a total of 500 valid responses were obtained. On the baseline survey, participants completed measures of demographics, exercise behavior, and motivation prior to viewing the exercise advertisement. For all groups, the image was preceded by the following message: We know fitting exercise into your busy life can be challenging! We hope this brief message of motivation will encourage you to try to make exercise a priority. It will be worth it! Immediately after viewing the advertisement, participants responded to one additional question that assessed their primary exercise goal. At the end of the baseline survey, participants were reminded that they would receive an invitation to complete a follow-up survey in 1 week. One week after participants completed the baseline survey, Qualtrics sent them a link to the follow-up survey, which included the same measures of exercise behavior, motivation and primary exercise goal. Individuals who had not completed the follow-up survey after 48 hours received a reminder email. In addition to completing the same measures of exercise behavior, motivation and primary exercise goal as the baseline surveys, participants reported whether they remembered seeing a brief message of motivation related to exercise, and if so, what type of exercise the message recommended and why the message recommended exercising. Measures Motivation The Exercise Self-Regulation Questionnaire is a 12-item measure that assesses quality of motivation and consists of four subscales: external regulation (e.g. Because others like me better when I am in shape), introjected regulation (e.g. Because I’d be afraid of falling too far out of shape), identified regulation (e.g. Because I have a strong value for being active and healthy), and intrinsic regulation (e.g. Because it is fun and interesting). It was originally developed based on guidelines for assessing behavioral regulations from Ryan and Connell (1989). Each item begins with the stem: Why do you (or would you) exercise? Participants reported the extent to which each statement was true for them on a scale from 1 (not at all true) to 7 (very true). For each subscale, responses were averaged to yield a total score. Exercise behavior Exercise was assessed using the Godin Leisure-Time Exercise Questionnaire (GLTEQ), on which participants reported the current frequency of engaging in strenuous, moderate and light intensity exercise for at least 15 minutes per session in the past seven days (Godin and Shephard 1985). A total weekly exercise score was then calculated by multiplying the frequencies of strenuous, moderate and light activities by corresponding metabolic equivalent (MET) intensity values of nine, five and three, respectively, INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 7 and then summing the products. Thus, the GLTEQ total score estimates total leisuretime exercise energy expenditure during the past week in METs. Based on guidelines provided by Godin (2011), participants were classified as ‘active’ if the sum of their strenuous and moderate activities was ≥ 24 METs, and ‘inactive’ if the sum of their strenuous and moderate activities was < 24 METs. Based on the descriptions and examples of strenuous and moderate exercise included in the questionnaire (e.g. strenuous exercise = heart beats rapidly), the GLTEQ is most likely to capture activities that are aerobic in nature. Thus, these activity classifications likely reflect whether or not individuals were meeting the aerobic activity guidelines at the time they participated in the study. Primary exercise goal Primary exercise goal was assessed by a single question: If you were to engage in exercise during the next week, what is the primary motive or goal that would drive you to be active? Participants selected their primary exercise goal from a list of ten options, which were drawn from the Exercise Motivations Inventory-2 (Markland and Ingledew 1997) to reflect common intrinsic and extrinsic goals. For analyses, responses were combined to create four general categories: weight/appearance goal (to lose weight or manage my weight, to enhance my appearance), affective goal (to manage stress, to feel good, to have fun), health goal (to live a healthy lifestyle, to prevent health problems) and other goal (to spend time with friends, to enhance fitness, to accomplish a personal goal). Participants also had the option to write in an ‘other’ goal, which were subsequently classified into one of the four general categories by the primary investigator. Data analysis The raw baseline and follow-up motivation and exercise scores were highly skewed, so univariate comparisons across the groups were conducted using the KruskalWallis test to investigate baseline differences, and change scores were calculated for the primary analyses. Chi-square tests and independent samples t-tests were used to determine whether those who dropped out differed from those who completed the study on any baseline or demographic variables. To determine whether motivation or exercise scores differed by group (primary analyses) after exposure to the messages, analysis of covariance (ANCOVA) was conducted on the change from baseline to follow-up. Baseline scores were added to the models as covariates in addition to gender, parent status and baseline activity level (dichotomous variable based on GLTEQ scores). Each model included three pre-planned comparisons to examine contrasts between treatment vs. control groups, intrinsic vs. extrinsic groups and easy vs. hard groups. To test the secondary hypothesis, chi-square tests were conducted to determine whether the distribution of primary exercise goal differed by group. Finally, we conducted Kruskal–Wallis tests to determine whether motivation or exercise behavior differed according to primary exercise goal at baseline (i.e. immediately after the message exposure). Changes from baseline based on primary exercise goal were tested using ANCOVA adjusting for baseline score, gender, parental status and baseline activity level as in the primary analyses. 8 E. L. MAILEY ET AL. Table 1. Demographic characteristics of the sample by group at baseline (N = 505). Mean (SD)/Frequency (%) Age Gender Female Male Race White Asian Black Native American Other Employment status Full-time Part-time Unemployed/homemaker Student/other Education No high school diploma High school graduate Some college/2-year degree College graduate Graduate/professional degree Annual household income <$35,000 $35,000-$49,999 $50,000-$74,999 $75,000-$99,999 >$100,000 Marital status Married Single/Divorced/Separated Number of children 0 1 2 3+ Physical activity level Active Inactive Control N = 101 37.3 (4.1) Extrinsic Easy N = 101 37.8 (4.7) Intrinsic Easy N = 100 36.6 (4.4) Extrinsic Hard N = 101 37.0 (4.6) Intrinsic Hard N = 102 37.6 (4.2) 51 (50.5%) 50 (49.5%) 50 (49.5%) 51 (50.5%) 50 (50.0%) 50 (50.0%) 50 (49.5%) 51 (50.5%) 51 (50.0%) 51 (50.0%) 59 (58.4%) 19 (18.8%) 18 (17.8%) 1 (1.0%) 5 (5.0%) 56 (55.4%) 14 (13.9%) 20 (19.8%) 5 (5.0%) 11 (10.9%) 56 (56.0%) 17 (17.0%) 22 (22.0%) 2 (2.0%) 6 (6.0%) 57 (56.4%) 11 (10.9%) 21 (20.8%) 3 (3.0%) 13 (12.9%) 59 (57.8%) 15 (14.7%) 22 (21.6%) 3 (2.9%) 7 (6.9%) 74 (73.3%) 8 (7.9%) 13 (12.9%) 6 (5.9%) 75 (74.3%) 9 (8.9%) 12 (11.9%) 5 (5.0%) 71 (71.0%) 10 (10.0%) 14 (14.0%) 5 (5.0%) 78 (77.2%) 5 (5.0%) 13 (12.9%) 5 (5.0%) 72 (70.6%) 12 (11.8%) 16 (15.7%) 2 (2.0%) 0 (0.0%) 13 (12.9%) 34 (33.7%) 22 (21.8%) 32 (31.7%) 0 (0.0%) 14 (13.9%) 33 (32.7%) 26 (25.7%) 28 (27.7%) 1 (1.0%) 13 (13.0%) 31 (31.0%) 32 (32.0%) 23 (23.0%) 4 (4.0%) 11 (10.9%) 33 (32.7%) 30 (29.7%) 23 (22.8%) 0 (0.0%) 13 (12.7%) 36 (35.3%) 28 (27.5%) 25 (24.5%) 22 (21.8%) 16 (15.8%) 18 (17.8%) 10 (9.9%) 33 (32.7%) 20 (19.8%) 14 (13.9%) 17 (16.8%) 13 (12.9%) 35 (34.7%) 23 (23.0%) 12 (12.0%) 28 (28.0%) 16 (16.0%) 21 (21.0%) 27 (26.7%) 14 (13.9%) 22 (21.8%) 13 (12.9%) 24 (23.8%) 24 (23.5%) 19 (18.6%) 21 (20.6%) 8 (7.8%) 30 (29.4%) 53 (52.5%) 48 (47.5%) 57 (56.4%) 44 (43.6%) 49 (49.0%) 51 (51.0%) 43 (42.6%) 58 (57.4%) 59 (57.8%) 43 (42.2%) 52 (51.5%) 21 (20.8%) 20 (19.8%) 8 (7.9%) 45 (44.6%) 19 (18.8%) 24 (23.8%) 13 (12.9%) 47 (47.0%) 17 (17.0%) 17 (17.0%) 19 (19.0%) 56 (55.4%) 20 (19.8%) 16 (15.8%) 9 (8.9%) 42 (41.2%) 17 (16.7%) 27 (26.5%) 16 (15.7%) 56 (55.4%) 45 (44.6%) 68 (67.3%) 33 (32.7%) 58 (58.0%) 42 (42.0%) 63 (62.4%) 38 (37.6%) 59 (57.8%) 43 (42.2%) Results Participant characteristics and retention The final sample included 505 individuals that provided valid baseline data. The demographic characteristics of the sample at baseline are presented in Table 1. There were no significant demographic differences between groups. On average, participants were 37.2 years old, 50% were male, 56.8% were White, 73.3% were working full time, 51.7% were married and 52.1% had children. About 60% of the participants were classified as ‘active’ (i.e. meeting physical activity guidelines) based on their self-reported exercise behavior. INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 9 Of the 505 randomized participants, 382 (75.6%) provided valid follow-up data 1 week later. Completion rates were similar across groups. However, individuals with children were more likely to drop out than those without children (p = .01). Additionally, participants who dropped out reported higher leisure-time exercise at baseline (M (SD) = 46.8 (33.2)) than those who completed the study (M(SD) = 38.7 (28.0); p = .008). Primary analysis Descriptive statistics for the motivation subscales and exercise behavior are presented by the group in Table 2. Exercise behavior differed significantly between groups at baseline (p = 0.004); there were no baseline group differences in the motivation subscales. Figure 2 displays the mean change scores with 95% confidence intervals by group for motivation and exercise behavior. ANCOVA analyses revealed no significant overall group effects for any of the motivation subscales or for exercise behavior, indicating that changes in motivation and exercise behavior were similar across all groups, including the control group. In addition, all pre-planned comparisons yielded non-significant effects. When adding gender, parent status and baseline activity level as covariates, all models remained non-significant. Baseline activity level (active vs. inactive) was significantly associated with changes in all motivation subscales, such that active individuals reported greater increases in intrinsic (B = 0.35, p = 0.001), identified (B = 0.29, p = 0.004), introjected (B = 0.38, p = 0.001) and external regulation (B = 0.28, p = 0.02) than inactive individuals from baseline to follow-up. Secondary analysis Immediately after viewing the advertisement at baseline, the distribution of primary exercise goal in the full sample was as follows: weight/appearance (46%), health (30%), affective (17%), other (7%). We examined the extent to which the distributions of primary goals differed by group. An initial chi-square analysis including all groups and all goals approached significance (X2 = 19.27, p = .08). Among those that viewed an intrinsic message, 22% endorsed an affective primary exercise goal, compared to 15% of those that viewed an extrinsic message and 12% in the control condition. Furthermore, among those that viewed an extrinsic message, 48% endorsed a primary exercise goal related to weight or appearance, compared to 39% of those that viewed an intrinsic message and 54% in the control condition (Figure 3). Because the exercise messages emphasized either weight-related or affective benefits, a secondary chi-square analysis comparing just these two goals revealed a significant immediate difference between groups (X2 = 10.64, p = .03). However, at one-week follow-up, the distribution of primary exercise goal no longer differed by group (X2 = 7.70, p = .10). Next, we examined whether the motivation subscales or exercise behavior differed according to primary exercise goal, regardless of group assignment. Descriptive statistics (median (IQR)) are presented in Table 3. The results revealed significant differences in intrinsic regulation (p < 0.001), identified regulation (p < 0.001), and exercise behavior (p = 0.004) by primary exercise goal at baseline. Specifically, participants with a primary goal related to weight or appearance reported lower intrinsic regulation and exercise behavior than participants with primary affective, health, or other goals. However, changes in motivation and exercise from baseline to follow-up did not differ according to primary exercise goal. 10 E. L. MAILEY ET AL. Table 2. Descriptive statistics [median (IQR)] by group and time point for motivation and exercise variables (completers only). Intrinsic Regulation Identified Regulation Introjected Regulation External Regulation Exercise Behavior a Time point Baseline Follow-up Baseline Follow-up Baseline Follow-up Baseline Follow-up Baseline Follow-up Intrinsic Easy (n = 79) 4.0 (2.3–5.3) 4.3 (3.0–5.0) 5.2 (4.0–6.5) 5.0 (4.0–6.3) 4.2 (3.3–5.3) 4.0 (3.3–5.0) 4.3 (3.0–5.3) 4.3 (3.0–5.7) 35.0 (12.5–59.0) 31.0 (15.0–53.0) P-values are from the Kruskal–Wallis test at baseline. Extrinsic Easy (n = 70) 4.3 (3.0–5.7) 4.3 (3.3–5.7) 5.7 (4.7–6.7) 5.7 (4.7–6.7) 4.3 (3.3–5.0) 4.3 (3.0–5.0) 4.3 (3.3–5.7) 4.3 (3.7–5.7) 43.0(26.0–61.0) 39.5(23.0–58.0) Intrinsic Hard (n = 79) 4.0 (3.0–5.0) 4.0 (3.0–5.0) 5.3 (4.3–6.3) 5.0 (4.3–6.0) 4.0 (2.7–5.0) 4.0 (3.0–4.7) 4.0 (2.7–5.0) 4.3 (3.0–5.3) 35.0 (17.0–52.0) 30.0 (17.0–48.0) Extrinsic Hard (n = 76) 4.0 (2.7–5.3) 4.3 (2.7–5.7) 5.7 (4.3–6.5) 6.0 (5.0–7.0) 4.3 (3.3–5.3) 4.8 (3.7–5.3) 4.7 (3.7–5.7) 5.0 (3.8–6.0) 43.0 (23.0–63.0) 39.5 (25.0–62.0) Control (n = 78) 3.7 (2.7–5.3) 4.0 (2.3–5.0) 5.3 (4.0–6.3) 5.3 (4.3–6.3) 4.0 (3.0–5.0) 4.3 (3.0–5.0) 4.0 (2.7–5.3) 4.7 (3.0–5.7) 31.0 (17.0–48.0) 34.0 (14.0–49.0) pa 0.22 0.16 0.12 0.08 0.004 INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 11 Figure 2. Mean changes in motivation (2a) and exercise (2b) outcomes by group, with 95% confidence intervals. Figure 3. Distribution of primary exercise goals immediately after viewing the advertisement. Table 3. Descriptive statistics [median (IQR)] for motivation and exercise behavior by primary exercise goal in the full sample. Intrinsic Regulation Identified Regulation Introjected Regulation External Regulation Exercise Behavior a Time point Baseline Followup Baseline Followup Baseline Followup Baseline Followup Baseline Followup Weight/ appearance (N = 231) 3.7 (2.3–5.0) 3.7 (2.3–5.0) Affective (N = 86) 4.3 (3.0–5.3) 4.3 (3.0–5.0) Health (N = 153) 4.7 (3.0–5.5) 4.3 (3.0–5.3) 5.0 (4.0–6.3) 5.3 (4.3–6.3) 5.0 (4.0–6.3) 5.0 (4.0–6.3) 5.7 (5.0–6.7) 6.0 (5.0–7.0) 6.3 (5.0–7.0) 6.3 (4.5–7.0) <0.001 4.3 (3.3–5.0) 4.3 (3.3–5.3) 4.0 (2.7–5.0) 3.7 (2.7–4.3) 4.0 (3.3–5.0) 4.5 (3.3–5.3) 4.3 (3.0–5.3) 4.3 (2.8–5.2) 0.52 4.3 (3.3–5.3) 4.7 (3.7–5.7) 4.0 (3.0–5.0) 4.0 (3.0–5.3) 4.0 (3.0–5.3) 4.3 (3.3–5.7) 4.7 (3.3–5.3) 4.7 (3.3–5.3) 0.55 32.0 (15–52) 31.5 (16–50) 39.5 (23–60) 33.5 (24–53) 42.0 (22–59) 39.0 (23–57) 38.0 (19–56) 37.5 (17–50.5) 0.004 P-values are from the Kruskal–Wallis test at baseline. Other (N = 35) pa 5.0 (3.7–5.7) <0.001 4.7 (3.2–6.2) 12 E. L. MAILEY ET AL. Message recall Of the 304 participants who completed the follow-up survey and viewed one of the advertisements (i.e. not in the control group), 55% said they remembered seeing a motivational message, 17% said they did not remember and 28% were unsure. In terms of the type of exercise recommended, some participants mentioned specific exercises included in the advertisement (e.g. at-home circuit training, bodyweight exercises, push ups), but others referenced more general exercise modes (e.g. cardio, moderate activity). When asked about why the message recommended exercise, a small number of participants recalled specific outcomes from the ads (i.e. energy, mood, weight loss), but a majority said ‘to be healthy’ (or something similar). Discussion The purpose of this study was to determine whether a single exposure to an exercise message depicting intrinsic vs. extrinsic goals and portraying exercise as easy vs. hard would differentially impact autonomous motivation, exercise behavior, or exercise goals among adults aged 30–45. The primary hypothesis was not supported, as changes in exercise motivation and behavior were similar across groups. Results did reveal an immediate effect of message frame on individuals’ primary exercise goal, such that participants were more likely to identify an affective primary exercise goal if they had viewed an advertisement highlighting affective benefits. However, this effect was not evident 1 week later. Overall, there were very few effects of message frame on the outcomes assessed. One potential explanation for these findings was that the exposure to the message was too brief. Latimer, Brawley, and Bassett (2010) found message effects were more consistent in studies with repeated exposures relative to a single exposure. In the present study, participants may have viewed the message for only a few seconds before continuing with the surveys, and likely spent little time processing the content of the message (Berry and Latimer-Cheung 2013). This fleeting exposure was competing against existing automatic associations about exercise that may have accumulated over decades of personal experience and media influence (Berry, McCarville, and Rhodes 2008). Future studies should attempt to determine the minimum dose of message exposure needed to have a meaningful impact on individuals’ motivation and behavior. The lack of message tailoring in this study may also have contributed to the lack of differences between groups. When messages are tailored to match the characteristics of the recipients, individuals may attend to the messages more carefully, ultimately increasing the likelihood that they enact the recommended behavior (Berry and Latimer-Cheung 2013; op den Akker et al. 2015; Pope, Pelletier, and Guertin 2017). In the present study, the motivational message may have been more compelling to individuals if it was tailored to their current activity level, preferred mode of exercise, or gender. The results of this study indicated that nearly half of all participants reported primary exercise goals related to weight or appearance, whereas only 17% of the participants identified an affective outcome as their primary exercise goal. This is concerning considering weight/appearance goals were associated with less intrinsic motivation and exercise behavior, regardless of group. Our secondary analyses did provide some INTERNATIONAL JOURNAL OF HEALTH PROMOTION AND EDUCATION 13 evidence that messages highlighting immediate affective benefits may increase the likelihood that individuals endorse these exercise goals. The novelty of these messages relative to ‘typical’ messages that emphasize weight and appearance outcomes may have captured participants’ attention, albeit briefly (Berry and Latimer-Cheung 2013). Together, these results provide some support for calls to ‘rebrand exercise’ and highlight affective benefits related to daily quality of life (Segar, Eccles, and Richardson 2011). Implementing these communication strategies in contexts beyond the media (e.g. healthcare, worksite wellness) may provide a more sustained and meaningful exposure to the messages. Limitations This study has a number of limitations, which are important to acknowledge. First, the study duration was short, and the follow-up data were collected only 1 week after baseline. However, given the brief nature of the message exposure, it is unlikely that a longer follow-up would have yielded different results, as any immediate effects observed were no longer present even 1 week later. Additionally, although the recruitment strategy yielded a large, demographically representative sample, the study may have been underpowered to detect significant effects given the brief nature of the manipulation. In addition, the extent to which panelists took the time to view/read the advertisement carefully or answer questions thoughtfully is unknown. The follow-up survey demonstrated that though many participants recalled seeing an exercise message on the initial survey, few remembered specific details of the image or message. This may be a function of the brief message exposure or of the sample (i.e. members of survey panels may complete multiple surveys each week). A manipulation check with specific response options that matched the message characteristics may have provided a more reliable and conclusive assessment than the open-ended approach we utilized to assess the extent to which individuals attended to and processed the motivational messages. Furthermore, future studies should pretest the messages to evaluate how they are received by the target audience. In this study, other aspects of the advertisements (e.g. photos, exercises recommended) may have influenced participants’ perceptions of whether the exercises were ‘easy’ or ‘hard’. For example, individuals who have limited exercise experience or are not currently active may perceive exercises such as triceps dips or high knees running to be intimidating or difficult, regardless of whether they are described as ‘easy’ or ‘hard’. Other participant characteristics not assessed in this study could also be explored. For example, individuals of different weight statuses may have different perceptions of whether the proposed exercises are easy or hard and react differently to messages such as ‘blast fat and lose weight fast’. Conclusion In conclusion, the results of this study suggest a single exposure to a motivational message did not have a significant impact on individuals’ exercise motivation or behavior. Because messages emphasizing weight and appearance as primary exercise goals are so pervasive in our society, a more concerted effort that includes multiple message exposures across a variety of contexts is likely needed to effectively ‘rebrand exercise’ 14 E. L. MAILEY ET AL. such that individuals are more cognizant of the immediate affective benefits exercise can provide. Disclosure statement No potential conflict of interest was reported by the author(s). Funding This work was supported by a Kansas State University. The award is a Small Research Grant (USRF) #3574. References Arena, R., A. 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