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Journal of Sports Sciences Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rjsp20

Longitudinal relationships between perceived stress, exercise self-regulation and exercise involvement among physically active adolescents a

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Markus Gerber , Magnus Lindwall , Serge Brand , Christin Lang , Catherine Elliot & Uwe a

Pühse a

Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland

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Department of Food and Nutrition, and Sport Science, University of Gothenburg, Gothenburg, Sweden c

Center for Affective, Stress and Sleep Disorders, Psychiatric Hospital of the University of Basel, Basel, Switzerland Published online: 06 Aug 2014.

To cite this article: Markus Gerber, Magnus Lindwall, Serge Brand, Christin Lang, Catherine Elliot & Uwe Pühse (2014): Longitudinal relationships between perceived stress, exercise self-regulation and exercise involvement among physically active adolescents, Journal of Sports Sciences, DOI: 10.1080/02640414.2014.946072 To link to this article: http://dx.doi.org/10.1080/02640414.2014.946072

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Journal of Sports Sciences, 2014 http://dx.doi.org/10.1080/02640414.2014.946072

Longitudinal relationships between perceived stress, exercise selfregulation and exercise involvement among physically active adolescents

MARKUS GERBER1, MAGNUS LINDWALL2, SERGE BRAND3, CHRISTIN LANG1, CATHERINE ELLIOT1 & UWE PÜHSE1 Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland, 2Department of Food and Nutrition, and Sport Science, University of Gothenburg, Gothenburg, Sweden and 3Center for Affective, Stress and Sleep Disorders, Psychiatric Hospital of the University of Basel, Basel, Switzerland

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(Accepted 15 July 2014)

Abstract Stress exposure may undermine exercisers’ capability to self-regulate their exercise behaviour. This longitudinal study examined the interplay between perceived stress, exercise self-regulation (assessment of action and coping planning) and participation in vigorous exercise in vocational students. Moreover, this study examined whether high exercise self-regulation moderates the assumed negative relationship between stress and exercise. A sample of 580 physically active vocational students (x ± s 17.8 ± 1.3 years, 33.8% girls) was assessed. All participants completed two identical validated questionnaires assessing stress, exercise self-regulation and exercise with a span of 10 months in between survey completion periods. The cross-sectional analyses show that high exercise self-regulation attenuated the assumed negative relationship between stress and exercise. In the longitudinal analyses, however, only a non-significant trend was found. Significant longitudinal relationships existed between exercise self-regulation and exercise involvement. Latent difference score models revealed that a drop in the exercise self-regulation was associated with a concurrent decrease in exercise participation. Cross-lagged panel analyses showed that high exercise self-regulation levels positively predicted exercise behaviour, but an inverse relationship was not supported. The findings suggested that higher exercise self-regulation levels were positively associated with future exercise involvement in currently active adolescents. While partial support was found that exercise selfregulation moderated the influence of stress on exercise, the findings demonstrated that higher exercise self-regulation levels had a positive impact on future exercise involvement in already active individuals. Keywords: action planning, coping planning, exercise self-regulation, implementation intentions, stress

Introduction Elucidating the association between stress and exercise is a public health concern from many perspectives (Stults-Kolehmainen, 2013). In most industrialised countries, physically inactive lifestyles and high perceptions of personal stress are highly prevalent (Ramaciotti & Perriard, 2001; WHO, 2011). Physical inactivity and stress are the risk factors for various chronic conditions including cardiovascular diseases (Petersen et al., 2012) and symptoms of psychopathology (Motl, Birnbaum, Kubik, & Dishman, 2004). In turn, exercise has the potential to alleviate the noxious effects of high stress (Gerber, Lindwall, Lindegård, Börjesson, & Jonsdottir, 2013). In the past research, the relationships between stress and exercise have been examined through

various theoretical lenses, employing a plethora of research designs. The majority of cross-sectional studies revealed that regular exercise is associated with decreased levels of perceived stress (e.g. Lindwall, Ljung, Hadžibajramović, & Jonsdottir, 2012). However, not all investigations confirmed this notion (Yin, Davis, Moore, & Treiber, 2005). Some longitudinal investigations indicated that exercise prevents the occurrence of high stress (e.g. Jonsdottir, Rödjer, Hadzibajramovic, Börjesson, & Ahlborg, 2010; Schnohr, Kristensen, Prescott, & Scharling, 2005), and experimental studies showed equivocal findings. Norris, Carroll, and Cochrane (1992) emphasised that after youngsters completed a high intensity exercise programme, they reported significantly lower stress scores during follow-up. In contrast, a 3-week

Correspondence: Markus Gerber, Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland. E-mail: [email protected] Present address of Magnus Lindwall is Department of Psychology, University of Gothenburg, Gothenburg, Sweden and Serge Brand is Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland © 2014 Taylor & Francis

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daily running intervention evoked no change on the perceptions of stress among high school students, although a significant improvement in objectively assessed sleep was observed (Kalak et al., 2012). Stress can also become an obstacle to adopting or maintaining a physically active lifestyle. Studies purport that exercise involvement decreases during times of elevated stress (e.g. Stetson, Rahn, Dubbert, Wilner, & Mercury, 1997). Oaten and Cheng (2005) showed that students reduced their exercise participation when an examination was approaching. Moreover, Lutz, Lochbaum, Lanning, Stinson and Brewer (2007) found that stress perceptions at Time 1 were related to reductions in exercise participation at Time 2 in a sample of blue-collar workers. In contrast, the cross-lagged panel model did not support a relationship between Time 1 exercise and Time 2 stress perception. An accumulation of empirical evidence further suggests that specific forms of self-regulatory strategies such as forming action plans (planning when, where and how often to exercise) (Gollwitzer & Brandstätter, 1997) and coping plans (anticipating and coping consciously with behavioural obstacles) (Sniehotta, Schwarzer, Scholz, & Schüz, 2005) can facilitate the enactment of exercise behaviour intentions (e.g. Arbour & Martin Ginis, 2009; Brickell, Chatzisarantis, & Pretty, 2006; Milne, Orbell, & Sheeran, 2002; Shimon & Petlichkoff, 2009). Nevertheless, whether or not the use of such types of exercise self-regulation can offset the negative impact of perceived stress on exercise behaviour remains obscure. Clarifying this ambiguity is relevant because exercise requires relatively high selfregulation (Sonnentag & Jelden, 2009). Therefore, scholars have argued that adherence to exercise can be strengthened through the appropriate use of selfregulation processes (Hagger, Wood, Stiff, & Chatzisarantis, 2009). In recent years, both action and coping planning have received empirical support as effective self-regulatory strategies. Specifically, studies have shown that action planning (forming concrete action plans) is associated with increased levels of exercise in both healthy and clinical populations (Brickell et al., 2006; Dombrowski & Luszczynska, 2009; Milne et al., 2002; Sniehotta, Scholz, & Schwarzer, 2005). For instance, Shimon and Petlichkoff (2009) found that among seventh- and eighth-grade physical education students in a 5-week pedometer study, those in the action planning group produced 2071 to 4141 more steps than those in the control group. Similarly, prior studies revealed that coping planning (anticipating and coping with behaviour obstacles) contributes to the maintenance of regular exercise involvement (Sniehotta et al., 2005; Ziegelmann & Lippke, 2007). For instance, Simkin and Gross

(1994) revealed that previously sedentary women who implemented a self-instructed training programme relapsed less often if they created detailed plans about how to cope with ten common and difficult high-risk situations for exercise relapse. Until now, the relationship between stress, exercise self-regulation and exercise behaviour among adolescents remains largely unexplored. However, stress is a common phenomenon during this period of life due to vocational demands, school pressure, identity formation, emotion regulation, parent–child conflicts, etc. (Byrne, Davenport, & Mazanov, 2007). Adolescence is also a period of transition characterised by increased independence, enlarging social networks, changed relationships, experimentation with new behaviours and decreasing levels of physical activity (Gordon-Larsen, Nelson, & Popkin, 2004; Masten, 2004). The present longitudinal study, therefore, provides new information regarding the interplay between perceived stress, exercise self-regulation and exercise participation across two measurement time points in physically active adolescent vocational students. Vocational students were chosen because new job responsibilities (e.g. acting professionally, taking care of customers) and pressures (e.g. performing efficiently, being successful at school and in the workplace) could arise during the transition to a vocational school (Narring et al., 2004), and because vocational students self-reported lower levels of exercise than peers attending academic high schools (Michaud, Jeannin, & Suris, 2006). The primary aim of the present study was to reveal whether exercise self-regulation moderates the assumed negative relationship between perceived stress and exercise involvement in a sample of physically active vocational students. The focus on already active adolescents was due to the difficulty to measure decreases in exercise among adolescents with already low levels of exercise at Time 1. Sniehotta et al. (2005) have argued that the use of self-regulatory strategies can solve persistence problems by producing a memory advantage because the underlying perceptual, attentional and mnemonic mechanisms endure even in cases of low self-control resources. For instance, a person who has formulated tangible action plans regarding when, where and how often to exercise is thought to be less likely to forget his/her planned exercise because the behaviour is more accessible to self-monitoring. Our first hypothesis, therefore, was that high exercise self-regulation assists the ability of youth to overcome stress as an obstacle to exercising (Sonnentag & Jelden, 2009). There were two supplementary goals associated with this study. The first goal was to examine the patterns of change between perceived stress, exercise self-regulation and exercise by using latent difference

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Stress, self-regulation and exercise score models (McArdle, 2009). These analyses examine the change in two or more variables from a between-person perspective. For example, latent difference score models allow for testing whether or not a person who changes in exercise self-regulation relative to others also changes his or her exercise participation relative to others. While the aspect of change tends to be neglected in research (e.g. Hofer & Sliwinski, 2006), this study intends to provide insight regarding the current body of knowledge. Based on the prospective research, we hypothesised that positive change in stress is associated with negative change in exercise (Hypothesis 2a: Lindwall, Gerber, Jonsdottir, Börjesson, & Ahlborg, 2013; Oaten & Cheng, 2005; Schnohr et al., 2005) and that negative change in exercise self-regulation is related to negative change in exercise involvement (Hypothesis 2b: Brickell et al., 2006; Dombrowski & Luszczynska, 2009). Although preliminary evidence exists that stress has a negative influence on selfregulatory control (Oaten & Cheng, 2005), no clear hypothesis emerged concerning how change in stress is associated with change in exercise self-regulation. The second supplementary goal was to examine the reciprocal influence between perceived stress, exercise self-regulation and exercise via cross-lagged panel analyses across two time-point measurements. Based on the work of Lutz et al. (2007), we hypothesised that there would be a stronger effect of Time 1 stress on Time 2 exercise than vice versa (Hypothesis 3a). Based on the research showing that relapses into physically inactive lifestyles are less likely among participants who use self-regulatory strategies (Simkin & Gross, 1994; Sniehotta et al., 2005; Ziegelmann & Lippke, 2007), we expected a unidirectional, yet significant effect from Time 1 exercise self-regulation on Time 2 exercise (Hypothesis 3b). We had no concrete expectations regarding the cross-lagged interplay between stress and exercise self-regulation due to a dearth of evidence. Nevertheless, Muraven and Baumeister (2000) have argued that stress may negatively affect self-regulation because coping with stress requires the constant monitoring of threatening stimuli, the blocking of sensations, overriding negative thoughts, stopping unwanted emotions, shifting attention and reframing. One can, therefore, speculate that stress also influences exercise self-regulation because the ability to maintain exercise might diminish if individuals chronically invest energy for selfregulation in order to manage stress.

Methods Participants and procedure Adolescents were recruited from two vocational schools in the central, German-speaking part of

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Switzerland. Students from all classes in the two schools participated in the study (n = 70 classes). The following vocational fields were represented: machine engineers, poly-mechanics, constructors, mouldmakers, production mechanics, construction planners, plastics engineers, merchants, retailers, retail trade assistants and hairdressers. The data assessment took place during a physical education lesson in a group setting in the presence of two trained research assistants. The students were informed about the purpose of the study and about the voluntary nature of their participation. Parents’ informed consent was required for those students who were under 18 years of age. Students were assured confidentiality of their responses and gave informed consent. The study was approved by the local ethics committee and was performed according to the ethical standards stated in the Declaration of Helsinki. Participants completed several psychological and exerciserelated questionnaires at Time 1 (October 2010) and again after a 10-month period (Time 2; May 2011; during the same academic year). Complete Time 1 data were available from 1243 students,  x ± s = 18.0 ± 1.4 years, 530 of whom were girls (43%). A total of 378 students (30%) dropped out before Time 2 (161 girls, 43%). These students reported slightly increased baseline stress, F(1,1242) = 5.51, P < .05, and had an older mean age, F(1,1242) = 19.81, P < .001 (see Instruments section for detailed instrument descriptions). Nevertheless, they did not differ with regard to gender, exercise involvement, exercise self-regulation and family financial background, P > .05. In the present analyses, the focus is placed on already active students. Therefore, only students with ≥ 60 min of vigorous physical activity were included. This cut-off corresponds well with the vigorous-intensity exercise recommendations of the American College of Sports Medicine (≥20 min vigorous physical activity on at least 3 days per week; Garber et al., 2011). Compared with the students who were excluded, the final sample (n = 580, 196 girls) reported higher Time 1 exercise, x ± s = 4.18 ± 3.31 vs. .25 ± .28, F(1,864) = 402.38, P < .001, η2 = .32, and stronger Time 1 action planning, x ± s = 8.37 ± 2.51 vs. 5.66 ± 2.08, F(1,864) = 247.79, P < .001, η2 = .22, but did not differ with regard to stress, coping planning and family social background, P > .05. The final sample was younger than students with vigorous exercise .05. On the other hand, a weak positive association occurred for peers with high exercise self-regulation levels, β = .13, P > .05. Finally, our analyses revealed no significant group differences regarding the stability of stress and exercise.

Associations of change in stress, exercise self-regulation and exercise Using a trivariate latent difference score model, we examined how change in one variable was associated with change in the others. Three models were compared: (a) default: χ2/df = 2.010, P < .001, CFI = .944, TLI = .938, RMSEA = .042, CI = .038, .045, (b) testing for invariance of the factor loadings at Time 1 and Time 2: χ2/df = 2.044, P < .001, CFI = .941, TLI = .936, RMSEA = .042, CI = .039, .046, Δχ2 = .000, ΔCFI = –.003 and (c) testing for

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Stress, self-regulation and exercise

Stress T1

Stress T2

Vigorous exercise T1

Vigorous exercise T2

Stress T1

Stress T2

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Vigorous exercise T2

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Figure 2. Factor loadings and regression weights for students with low, moderate and high exercise self-regulation. Notes: T1 = Time 1, T2 = Time 2. e1–e26 = Measurement errors. Measurement errors were allowed to autocovary over time. All factor loadings were significant at P < .001. S1_1/2 = Stress of home life, S2_1/2 = Stress of school performance, S3_1/2 = Stress of school attendance, S4_1/2 = Stress of romantic relationships, S5_1/2 = Stress of peer pressure, S6_1/2 = Stress of teacher interaction, S7_1/2 = Stress of future uncertainty, S8_1/2 = Stress of school-leisure conflict, S9_1/2 = Stress of financial pressure, S10_1/2 = Stress of adult responsibility, E1_1/2 = Exercise frequency, E2_1/ 2 = Exercise duration. *P < .05. **P < .01. ***P < .001.

invariance of the intercepts over time: χ2/df = 2.147, P < .001, CFI = .934, TLI = .930, RMSEA = .045, CI = .041, .048, Δχ2 = .000, ΔCFI = −.007. All fit indices

met the recommended cut-offs, and the final model revealed a good model fit, having no differences when compared to the less constrained models.

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Stress T1

Stress T2

Vigorous exercise T1

Vigorous exercise T2

Exercise self-regulation T1

Exercise self-regulation T2

Figure 3. Factor loadings, correlations (double-headed arrows) and regression weights (single-headed arrows) of the trivariate latent difference score model. Notes: T1 = Time 1, T2 = Time 2. ESR = Exercise self-regulation e1–e36 = Measurement errors. Measurement errors were allowed to autocovary over time. All factor loadings were significant at P < .001. S1_1/2 = Stress of home life, S2_1/2 = Stress of school performance, S3_1/2 = Stress of school attendance, S4_1/2 = Stress of romantic relationships, S5_1/2 = Stress of peer pressure, S6_1/2 = Stress of teacher interaction, S7_1/2 = Stress of future uncertainty, S8_1/2 = Stress of school-leisure conflict, S9_1/2 = Stress of financial pressure, S10_1/2 = Stress of adult responsibility, E1_1/2 = Exercise frequency, E2_1/ 2 = Exercise duration, A1_1/2 = Plan where to exercise, A2_1/2 = Plan when to exercise, A3_1/2 = Plan how often to exercise, C1_1/2 = Plan what to do if something interferes with my exercise plans, C2_1/2 = Plan how to cope with setbacks, C3_1/2 = Plan what to do in situations, in which it is difficult to exercise regularly. *P < .05. **P < .01. ***P < .001.

Against our expectations formulated in Hypothesis 2a, Figure 3 shows that change in stress was unrelated to change in exercise behaviour, r = –.07, P > .05. In contrast, Hypothesis 2b was supported. Thus, change in exercise self-regulation was paralleled by change in exercise participation, r = .34, P < .001. Finally, no significant association existed between change in stress and change in exercise self-regulation, r = .02, P > .05. Cross-lags between stress, exercise self-regulation and exercise Figure 4 illustrates the findings of the trivariate cross-lagged panel analysis. Two models were compared: (a) default: χ2/df = 1.839, P < .001, CFI = .955, TLI = .949, RMSEA = .038, CI = .034, .042 and (b) testing for invariance of factor loadings over time: χ2/df = 1.814, P < .001, CFI = .955, TLI = .950, RMSEA = .037, CI = .034, .041, Δχ2 = .605, ΔCFI = .000. After testing for factorial invariance over time, the model-fit was good. Hypothesis 3a was not supported. Figure 4 shows that no significant cross-lags emerged between stress

and exercise. In contrast, evidence was found for the validity of Hypothesis 3b. Thus, a weak significant relationship appeared between Time 1 exercise selfregulation and Time 2 exercise, β = .10, P < .05, showing that students with high Time 1 exercise selfregulation scores reported elevated exercise levels at Time 2. The reverse was not true; students with high exercise involvement at Time 1 did not report higher Time 2 exercise self-regulation levels, β = .05, P > .05. Therefore, the findings suggested a non-reciprocal relationship between these variables, with high self-regulation as a predictor of future exercise. Finally, no significant cross-lags were found between stress and exercise self-regulation. Discussion The main findings of this study are that a significant association existed between exercise self-regulation and exercise involvement across all analyses. Exercise self-regulation also operated as a moderator of the stress–exercise relationship at Time 1. Specifically, a negative relationship between stress and exercise was found only among students with

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Stress T1

Stress T2

Vigorous exercise T1

Vigorous exercise T2

Exercise self-regulation T1

Exercise self-regulation T2

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Figure 4. Factor loadings, correlations (double-headed arrows) and regression weights (single-headed arrows) of the trivariate cross-lagged panel model. Notes: T1 = Time 1, T2 = Time 2. e1–e36 = Measurement errors. Measurement errors were allowed to autocovary over time. All factor loadings are significant at P < .001. S1_1/2 = Stress of home life, S2_1/2 = Stress of school performance, S3_1/2 = Stress of school attendance, S4_1/2 = Stress of romantic relationships, S5_1/2 = Stress of peer pressure, S6_1/2 = Stress of teacher interaction, S7_1/2 = Stress of future uncertainty, S8_1/2 = Stress of school-leisure conflict, S9_1/2 = Stress of financial pressure, S10_1/2 = Stress of adult responsibility, E1_1/2 = Exercise frequency, E2_1/ 2 = Exercise duration, A1_1/2 = Plan where to exercise, A2_1/2 = Plan when to exercise, A3_1/2 = Plan how often to exercise, C1_1/2 = Plan what to do if something interferes with my exercise plans, C2_1/2 = Plan how to cope with setbacks, C3_1/2 = Plan what to do in situations, in which it is difficult to exercise regularly. *P < .05. **P < .01. ***P < .001.

low and moderate exercise self-regulation levels. Nevertheless, even though a trend towards the expected pattern of results was found, no significant longitudinal moderation effects emerged. These results add to the extant literature, in that a specific focus was placed on already active adolescents (based on the activity reported at Time 1). Thus, exerting self-regulatory control through action and coping planning was associated with adolescent exercise maintenance over time. Although reaching statistical significance, a unidirectional yet weak relationship was found between exercise self-regulation and future exercise. This research is also novel insofar as it investigates whether high exercise selfregulation moderates the assumed negative relationship between stress and exercise involvement. However, only partial support was found for this hypothesis. While a significant moderation effect occurred on a cross-sectional basis, the longitudinal analyses revealed a non-significant trend. Specifically, among adolescents with low exercise self-regulation levels, higher Time 1 stress was associated with lower Time 2 exercise, whereas an opposite trend was found in adolescents with high

exercise self-regulation levels. This finding elucidates upon the notion that adolescents with high exercise self-regulation levels increase their exercise involvement in times of stress. Although speculative, we assume that adolescents with high exercise selfregulation levels may plan their exercise involvement more consciously because they know that they can leverage exercise as a stress coping strategy. Moreover, this study placed a focus on two specific types of exercise self-regulation (action and coping planning). Thus, future studies can examine whether more general assessments of self-control (e.g. with the dispositional self-control scale [Tangney, Baumeister, & Boone, 2006]) result in a stronger attenuation of the longitudinal relationship between stress and exercise. For example, Crescioni et al. (2011) showed in a 12-week weight loss programme that participants scoring high on dispositional selfcontrol spent more time exercising and lost more weight after controlling for baseline differences. Additionally, at least two further explanations can be proposed as to why exercise self-regulation had no longitudinal moderating influence on the stress– exercise relationship in this study. First, no

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significant association existed between stress and exercise across time; thus, the prerequisites may not have been met for exercise self-regulation to actualise its stress-buffering potential. Second, we did not distinguish between exercise in structured and informal settings. Nevertheless, the practising of exercise self-regulation might be particularly useful for adolescents to engage in informal exercise activities. No support was found for hypothesis 2a. That is, change in stress was not associated with change in exercise. Likewise, no support was found for hypothesis 3a. That is, no significant cross-lags existed between stress and exercise, although a weak, but significant negative cross-sectional association occurred between stress and exercise at Time 1. In a previous study, Lutz et al. (2007) found a unidirectional negative effect originating from perceived stress on future exercise. The divergent findings can be ascribed to different assessments of the stress concept and varying sample characteristics. One can speculate that stress was not a pertinent exercise obstacle in our sample because the reported stress levels were low to moderate. Nevertheless, this is at odds with the notion that vocational students are in a period of transition associated with increased stress (Narring et al., 2004). Alternatively, decreased exercise participation may coincide with adolescent development (e.g. due to alterations in biological, social and psychological factors) and may be independent of their perceived stress levels. Accordingly, Telama and Yang (2000) argued that the decline in exercise results from a process of “desocialisation,” which is typical for this period of life. In contrast, support was found for Hypothesis 2b and Hypothesis 3b. Hypothesis 2b claimed that change in exercise self-regulation and change in exercise involvement are interrelated. Hypothesis 3b supported the notion that high initial exercise self-regulation scores predicted future exercise involvement, and explained variance above that of Time 1 exercise, but not vice versa. This study expands upon prior research in that it used latent difference score analyses to examine between-person changes over time in active adolescents. Past research has tested whether increasing the use of self-regulatory strategies helps inactive individuals to adopt more physically active lifestyles (Arbour & Martin Ginis, 2009; Brickell et al., 2006). Exercise self-regulation can be used to solve persistence problems by producing a memory advantage because the underlying perceptual, attentional and mnemonic mechanisms endure, even in cases of low self-control resources (Sniehotta et al., 2005). For example, Milne et al. (2002) found that the participants who formed action plans were less likely to forget to exercise or to attribute relapses to time constraints.

To the best of our knowledge, this is the first study to use (1) a latent difference score model to show that decreasing levels of exercise self-regulation were related to decreased exercise levels and (2) a crosslagged panel analyses to examine the relationship between exercise self-regulation and exercise. In support of Hypothesis 3b, students with high Time 1 exercise self-regulation levels had higher exercise levels after 10 months than did peers with low baseline levels. We acknowledge that there might be redundancy between exercise self-regulation and exercise participation because adolescents who participate in group exercise, for example, need a certain amount of planning to attend the exercise sessions. Nevertheless, our findings reveal that this longitudinal relationship is unidirectional. Further, our results accord with those of Karoly et al. (2005) who discovered differences between regular and irregular exercisers regarding perceived capacity to self-regulate an exercise-related goal compared with an attractive, interfering goal. Their findings suggest that irregular exercisers favoured the interfering goal, while regular exercisers did not have a preference. Some limitations in the present study are worth noting and provide direction for future research. First, all data were gathered via self-report. Second, the stress measure was relatively unspecific and did not place an emphasis on perceptions of exerciserelated barriers. Third, there was no random sample, and participants comprised students in vocational education and training. We also emphasised that the present study includes only two waves of data and therefore cannot address long-term associations. Fourth, exercise self-regulation was used as a categorical variable in the multiple-group comparisons, but this allowed for identifying students with relatively low, moderate or high exercise self-regulation across the duration of the study. Finally, the findings of this research only generalise to active students with vigorous exercise levels ≥60 min/week. The findings of the present study are of practical relevance for two reasons. First, the results show that exercise self-regulation is positively associated with current and future exercise involvement. On the other hand, adolescents only reported low to moderate levels of exercise self-regulation. Hence, training programmes have the potential to trigger positive effects. Second, training of exercise self-regulation may have favourable cross-over effects into other domains of health prevention. Previous research has shown that physical exercise may foster self-regulatory control (Oaten & Cheng, 2006), and studies have shown that exerting self-control is associated with profound positive outcomes across nearly every major life domain (Duckworth, Grant, Loew, Oettingen, & Gollwitzer, 2011; Moffitt et al., 2011; Oaten & Cheng, 2006).

Stress, self-regulation and exercise Conclusion This investigation examined the interplay between exercise self-regulation, perceived stress and exercise involvement. As emphasised previously (Hagger et al., 2009; Sonnentag & Jelden, 2009), adherence to various health-related behaviours requires the appropriate use of self-regulation processes. While the moderating influence of self-regulation processes was only weak in the present study, the findings demonstrated that higher exercise self-regulation levels had a positive impact on future exercise involvement in already active individuals.

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Acknowledgement We thank Mirjam Lüthy and Anne Karina Feldmeth for their contribution to the recruitment of participants, data collection and processing. We also thank all the participants for their valuable time and effort to the study.

Funding Funding for this study was provided by the Swiss Federal Office of Sport [grant number 10-05]. The Federal Office of Sport had no further role in study design, collection, analysis, interpretation of data and writing of this report. All authors declare no conflict of interests. All authors have read and approved the manuscript.

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Longitudinal relationships between perceived stress, exercise self-regulation and exercise involvement among physically active adolescents.

Stress exposure may undermine exercisers' capability to self-regulate their exercise behaviour. This longitudinal study examined the interplay between...
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