@ 2014 American Psychological Association 0090-5550/14/$ 12.00 DOI: 10.1037/aOO3529O

Rehabililation Psychology 2014, Vol. 59, No. 1, 42-49

Physical Activity Among Adults With Obesity: Testing the Health Action Process Approach Linda Parschau and Milena Barz

Jana Richert

Freie Universität Berlin

Oregon State University

Nina Knoll

Sonia Lippke

Freie Universität Beriin

Jacobs University Bremen

Ralf Schwarzer Freie Universität Berlin and University of Social Sciences and Humanities Objective: This study tested the applicability of the Health Action Process Approach (HAPA) in a sample of obese adults in the context of physical activity. Method: Physical activity was assessed along with motivational and volitional variables specified in the HAPA (motivational self-efficaey, outcome expectancies, risk perception, intention, maintenance self-efficacy, action planning, eoping planning, recovery self-efficacy, soeial support) in a sample of 484 obese men and women (body mass index a 30 kg/m^). Results: Applying structural equation modeling, the fit of the HAPA model was satisfactory— X^(19I) = 569.93, p < .05,x^/àf= 2.98, comparative fit index = .91, normed-fit index = .87, and root mean square error of approximation = .06 (90% CI = .06, .07)—explaining 30% of the variance in intention and 18% of the variance in physical activity. Motivational self-efficaey, outcome expectancies, and social support were related to intention. An association between maintenance self-efficacy and coping planning was found. Recovery self-efficacy and social support were associated with physical activity. No relationships were found between risk perception and intention and between planning and physical activity. The assumptions derived from the HAPA were partly confirmed and the HAPA may, therefore, constitute a theoretical backdrop for intervention designs to promote physical activity in adults with obesity. Keywords: self-efficacy, social support, motivation, volition, overweight

peetancies and motivational self-efficacy facilitate the formation of the intention to be physically active and that, in such a sample, social support may be more relevant than planning for engaging in physical activity. • Different social-cognitive factors need to be addressed in interventions either promoting intention formation or actual engagement in physical activity. To promote physical activity in obese adults, fostering social support may be more effective than focusing only on individuals' planning in interventions.

Impact and Implications • Although the applicability of the Health Action Process Approach (HAPA) has been tested in many distinct contexts referring to various health behaviors, it has not yet been investigated in adults with obesity with regard to their physical activity. The study extends research on this topic by identifying associations between motivational and volitional variables derived from the HAPA in individuals with obesity. • Study findings partly support the applicability of the HAPA concerning physical activity among obese adults. In particular, results confirm the importance of phase-specifie self-efficacy and suggest that outcome ex-

Introduction As a result of unhealthy lifestyles, obesity (body mass index [BMI] > 30 kg/m^) has become a "pandemic" in developed countries (Popkin, Adair, & Ng, 2012). According to the Worid Health Organization, obesity and overweight belong to the five leading risks for global deaths (World Health Organization, 2009). The risk of secondary diseases such as cardiovascular disease. Type 2 diabetes, musculoskeletal disorders, and various forms of cancer, is elevated in obese individuals (Hu, 2008; National Institutes of Health, 1998). Furthermore, individuals with disabilities are more likely to be obese than individuals without disabilities (44.6% vs. 34.2%; National Health & Nutrition Examination Survey, 2013). Consequently, many patients in medical rehabilitation care are obese and need more than only treatments focusing on the recovery from a secondary disease (e.g., coronary heart disease and musculoskeletal disorder). Restoring better health also re-

This article was published Online First January 20, 2014. Linda Parschau and Milena Barz, Department of Health Psychology, Freie Universität Berlin, Berlin, Germany; Jana Richert, School of Psychologieal Science, Oregon State University, Eugene, OR; Nina Knoll, Department of Health Psychology, Freie Universität Berlin, Berlin, Germany; Sonia Lippke, Jacobs Center on Lifelong Learning and Institutional Development, Jacobs University Bremen, Bremen, Germany; Ralf Sehwarzer. Department of Health Psychology, Freie Universität Berlin, Berlin, Germany, and Department of Psychology, University of Social Sciences and Humanities, Warsaw, Poland. Correspondenee concerning this article should be addressed to Linda Parschau, PhD, Freie Universität Berlin, Department of Health Psychology, Habelschwerdter Allee 45, 14195 Berlin, Germany. E-mail; [email protected] 42

PHYSICAL ACTIVITY AND OBESITY: TESTING THE HAPA quires an appropriate management of obesity by promoting physical activity. The main reason for obesity is an energy imbalance between calories consumed and calories expended. A lifestyle consisting of physical activity and a balanced diet can lead to weight loss and reduced health risks (Shaw, Gennat, O'Rourke, & Del Mar, 2006). Although physical activity has many benefits for obese individuals, obese persons are typically less active than individuals maintaining a healthy weight (BMI from 18.5 to 25 kg/m^; Colley et al, 2011). Given that regular physical activity is a promising element in obesity treatment (Hill & Wyatt, 2005), it is necessary to develop effective interventions promoting physical activity. This is of particular relevance in the rehabilitative context as physical activity interventions often target obese adults in orthopedic and cardiac rehabilitation (Ades, Savage, & Harvey-Berino, 2010). Compared to the circumstances in everyday life, the motivation to change one's health behavior might be higher after the experience of a health-threatening event, and the adoption of a health behavior might be easier in the structured environment of the rehabilitative context with the support of health professionals. As staying in rehabilitation facilitates the adoption of more physical activity, exercise interventions for individuals with obesity are highly recommended. A meta-analysis (Gourlan, Trouilloud, & Sarrazin, 2011) revealed that physical activity interventions have a moderate effect (d = 0.44) on physical activity in obese individuals, but the impact varies highly between the analyzed interventions. As the total number and the frequency of intervention sessions did not moderate the intervention effect, different techniques used to promote physical activity might be an explanation for the considerable variability in efficacy between interventions. To design and evaluate more effective interventions, it is necessary to know which theoretical constructs are associated with behavior and which corresponding intervention techniques are effective in changing behavior (Michie et al., 2013). Theory-based interventions are claimed to be more effective in changing behavior than interventions not based on theory (Michie & Prestwich, 2010). However, there is a lack of theory-based physical activity interventions targeting obese populations (Sjolin, 2006). The purpose of this study is to contribute to research on physical activity

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in obese adults by testing whether a well-supported theoretical model comprising motivational and in particular volitional components applies to this subgroup.

HAPA HAPA is a theoretical framework that can describe, explain, and predict health behavior change and that is useful for the development of interventions, especially in the area of physical activity promotion (Schwarzer, Lippke, & Luszczynska, 2011). This model makes a distinction between a motivation phase leading to a behavioral intention and a volition phase leading to the actual health behavior. In Figure 1, we display the variables associated with each phase, along with hypothesized relationships among the variables. Outcome expectancies are regarded as being mainly influential in the motivational process. In particular, positive outcome expectancies (e.g., "If I am physically active on a regular basis then I will do something good for my health") contribute to forming an intention for the target behavior. Risk perception addresses the perceived vulnerability for certain diseases (e.g., "If I keep living as I have this far, then my health-related risk will be high") and is seen as a rather distal and weak predictor of intention (Schwarzer et al., 2011). Motivational self-efficacy (e.g., "I am confident that I can be physically active even if it is difficult for me") is defined as the belief in one's capability to perform a desired action and is seen as crucial to develop an intention in the motivation phase (Schwarzer et al., 2011). Contrary to outcome expectancies and risk perception, self-efficacy remains influential after an intention has been formed. A unique characteristic of the HAPA is the assumption of phase-specific self-efficacy beliefs. Individuals already intending to change their behavior should benefit from volitional selfefficacy that comprises maintenance self-efficacy (e.g., "I am confident that I can be physically active permanently and on a regular basis even if I have to overcome barriers") and recovery self-efficacy (e.g., "I am confident that I can resume my physical activity even if I wasn't physically active several times"). Furthermore, prospective self-regulatory strategies facilitating the translation of intentions into action are included in the HAPA. These

Motivation Phase

Figure 1. Hypothesized associations according to the Health Action Process Approach.

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PARSCHAU ET AL.

comprise action planning (e.g., "I have planned in detail when, where, and how I will be physically active") and coping plarming (e.g., "I have planned in detail how I could cope with difficult situations to stick to my intentions"). A further assumption of the HAPA is that social support may function as a resource in the health behavior change process (Schwarzer et al., 2011). The availability of social support can constitute a resource, whereas the lack of social support can represent a barrier for the performance of health behaviors. Different intervention studies demonstrated the relevance of social support in the area of physical activity (e.g.. Geliert, Ziegelmann, Warner, & Schwarzer, 2011) and were able to show that physical activity interventions comprising social support strategies can be more effective (Salmon, Bremen, Fotheringham, & Finch, 2000). Enlisting a support partner (e.g., a family member or friend) in behavioral weight loss treatments has been found to be especially useful in improving walking (Hemmingsson, Hellénius, Ekelund, Bergström, & Rössner, 2008) and facilitating weight loss (Gorin et al, 2005; Wing & Jeffery, 1999). Therefore, it is a promising recommendation for obesity treatments to involve social support (British Psychological Society, 2011 ; National Institutes of Health, 1998). The HAPA suggests that these social-cognitive variables predict behavior directly and indirectly, irrespective of participants' age, gender, sociocultural background, or health status. In the context of physical activity, previous studies tested and partly confirmed the relationships between the constructs specified in the HAPA in different age groups (Barg et al., 2012; Caudroit, Stephan, & Le Scanff, 2011; Renner, Spivak, Kwon, & Schwarzer, 2007). Other studies concerning physical activity found evidence for the HAPA for instance in orthopedic and cardiac rehabilitation patients (Fleig, Lippke, Pomp, & Schwarzer, 2011 ; Lippke, Ziegelmann, & Schwarzer, 2005; Scholz, Sniehotta, & Schwarzer, 2005; Sniehotta, Scholz, & Schwarzer, 2005; Ziegelmann, Lippke, & Schwarzer, 2006), in patients with multiple sclerosis (Chiu, Lynch, Chan, & Berven, 2011), in individuals with Type 2 diabetes (Lippke & Plotnikoff, in press), and with physical disabilities (Perrier, Sweet, Strachan, & Latimer-Cheung, 2012). However, more research is required to examine whether the assumptions of the HAPA are applicable for high-risk groups, such as obese individuals (Schwarzer & Luszczynska, 2008). In contrast to other health behavior theories, the HAPA includes more theoretical constructs in a dynamic manner, which means they are conceptually specified in terms of stages of change, and as a hybrid model, it integrates stage with the constructs derived from continuum models, embedded in a broader context of social characteristics (Sutton, 2009).

Aims of the Study The aim is to contribute to research on physical activity in obese individuals by testing whether a generally well-supported theoretical model comprising motivational and volitional components applies to this subgroup as well. In particular, this will be done by testing whether the relationships between the constructs specified in the HAPA are applicable for obese individuals in the domain of increasing physical activity. It was hypothesized that a structural equation model that reflects the pattern of relationships specified in the HAPA would corroborate the theoretical assumptions, which

are as follows; outcome expectancies, motivational self-efficacy, risk perception, and social support are associated with intention; motivational self-efficacy is related to maintenance self-efficacy, which in turn is associated with recovery self-efficacy; and maintenance self-efficacy is related to planning and recovery selfefficacy to physical activity (see Figure 1). Furthermore, it was expected that intention is associated with action planning and coping planning, and both planning strategies are connected with physical activity. There is also evidence that social support is important in promoting physical activity in individuals with obesity. Therefore, we hypothesized that social support is directly related to more physical activity.

Method Participants and Procedure By means of an online survey offered by a German health insurance company, 537 obese adults were recruited during September 2011 and October 2012. Insured individuals were directed to this survey by advertisements through print and online media. In addition, employees of different companies were informed about the survey during events concerning workplace health promotion. Beyond that, the link to the online survey also appeared for the public in health-related magazines and on the website of the health insurance company. After excluding participants with more than 10% missing values (n = 53; 9.9%) the final sample consisted of 484 individuals with 328 women (67.8%) and 156 men. The mean age was 42.3 (SD = 11.3, range 18 to 75) years. More than half of the participants were married (n = 266; 55%), 17.8% were in a relationship (n = 86), 27.3% were singles (n = 132), and 28.3% had children. In addition, 61.4% had graduated from high school (n = 297), 27.2% had a university degree (n = 132), and 80% were employed (n = 387). The BMI ranged from 30 kg/m^ to 60.2 kg/m^ (M = 34.7, SD = 4.7). Also, 62.4% of the sample intended to meet the World Health Organization recommendation of engaging in physical activity for at least 30 min on at least 5 days per week (World Health Organization, 2011). However, merely 92 participants (19%) met this recommendation. More than 250 min per week of physical activity is recommended to reduce overweight (Donnelly et al., 2009), which was met by only 37 participants (7.6%).

Measures The online-based questionnaire assessed demographics (age, gender, education, and employment) and HAPA variables. Selfreported height and weight were used to calculate the BMI (determined by dividing weight in kilograms by squared height in meters) of all participants. Example items given below were translated from German. Self-reported physical activity was measured by using two adapted items of the International Physical Activity Questionnaire (Booth, 2000). Participants were asked to indicate on how many days they were physically active on average during the past week (frequency) and for how long they were physically active on such a day (duration in tninutes). Corresponding to the physical activity measure, behavioral intention was measured with two items. Participants were asked to

PHYSICAL ACTIVITY AND OBESITY: TESTING THE HAPA

think of future bouts of physical activity and to indicate on how many days they intended to be physically active on average during the week and for how long they intended to be physically active on such a day. The following social-cognitive scales (adapted from Schwarzer et al., 2011) had a 6-point response format, ranging from 1 {completely disagree) to 6 {completely agree). Risk perception was measured with three items (Cronbach's alpha = .75) such as "If I keep living as I have this far, then my risk of getting diabetes will be high." Positive outcome expectancies were assessed with four items (Cronbach's alpha = .73). All items had the stem "If I am physically active on a regular basis .. ." followed by positive consequences ". .. then I will feel well-balanced and satisfied," " . . . then I will do something good for my health and my fitness," " . . . then I am more alert," and ".. . then it will favorably affect the way I look." Motivational self-efficacy consisted of two single-item indicators (correlation of the two items, r = .83), namely "I am confident that I can be physically active even if it is difficult for me" and "I am certain that I can live a physically active lifestyle even if it is difficult for me." Maintenance self-efficacy was assessed with the item stem "I am confident that I can be physically active on a regular basis ...". The items then were "even if I have to overcome barriers," and "even if I have sorrows and problems" {r = .73). Recovery self-efficacy consisted of two indicators that were worded: "I am confident that I can resume my physical activity . . . " followed by ".. . even if I have interrupted my routine more than once" and " . . . even if I wasn't physically active for several times" (correlation of these two items, r = .78). Action planning was assessed by four items (Cronbach's alpha = .87). The item stem "For the next time, I have planned in detail . . . " was followed by the items (a) ". .. which physical activities I will perform," (b) ". .. on which days of the week I will be physically active," (c) ". .. for how long I will be physically active," and (d) ". .. where I will be physically active." Coping planning was measured with two items (r = .66), starting with the same item stem as above, followed by " . . . when I have to be extra careful to remain physically active" and " . . .

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how I could cope with difficult situations to stick to my intentions." Social support was assessed with the item stem "My family/ friends .. ." and the following two items ". .. encourage me to be physically active on a regular basis" and " . . . have engaged in physical activity with me" {r = .45). The structural equation model included 10 latent variables (risk perception, positive outcome expectancies, motivational selfefficacy, intention, maintenance self-efficacy, recovery selfefficacy, action planning, coping planning, social support, and physical activity) with respective items (manifest variables that were described above) as multiple indicators. Intercorrelations, factor loadings, means, standard deviations, and ranges of all constructs are displayed in Table 1.

Data Analyses Reliability and descriptive analyses were performed with SPSS 20. Structural equation modeling with latent variables was used to test the hypothesized models. All model estimations were conducted with AMOS 20 using Full Information Maximum Likelihood, which does not require complete data for parameter estimation. Goodness-of-fit indices to evaluate model fit were the comparative fit index (CFI) and the normed-fit index (NFI), with values greater than .90 indicating reasonably good fit and the root mean square error of approximation (RMSEA), with values lower than .08 indicating adequate fit (Kline, 2005). The structural equation model included the latent exogenous variables risk perception, outcome expectancies, and motivational self-efficacy as well as the latent endogenous variables maintenance self-efficacy, recovery self-efficacy, intention, action planning, coping planning, and physical activity. In addition, social support was added as a further exogenous variable. In order to minimize the number of indicators for latent variables and thereby reducing error variances simultaneously, two parcels of two items each were used as indicators for positive outcome expectancies as well as for action planning (Little, Cunningham, Shahar, & Widaman, 2002). As participants' age was correlated with recovery self-efficacy {r = .13;p < .01), action planning (r = .ll;p < .01) and coping planning {r = .12; p < .05), the manifest variable age

Table 1 Means, Standard Deviations, and Correlations of Variables

1, Physical activity in total minutes per week 2. Intention in total minutes per week 3, Risk perception 4. Outcome expectancies 5, Motivational self-efficacy 6. Maintenance self-efficacy 7, Recovery self-effieacy 8. Action planning 9. Coping planning 10, Social support

M(SD)

Range

1

105.91 (136.51)

0-1080

.56-.65

193.53(120.76) 20-960 4,23(1.18) 1-6 5.17(0.57) 1-6 4,17 (0.93) 1-6 4,04 (0.95) 1-6 4,33 (0,94) 1-6 4,46(1.01) 1-6 3,16(1.28) 1-6 3,51 (1.23) 1-6

2

3

4

5

6

7

8

9

10

.60" .31-.35 -.09* -.02 .55-.85 .06 .10* ,10* .72-.87 .18** ,23" -.07 ,19" .90-.92 .17" ,21" -,07 ,18" ,70" .78-.92 .13" ,16" -.05 .08 .52** .52" .79-.99 .18" ,25" .01 .22" .30" .26" ,27" .90-.92 .12" ,15" -.11* .11* .39" .37" .27" .39** .76-.86 .17" .16" -.05 ,10* .16" .23" .09* .13** ,14** .65-.68

Note. All scores are related to the manifest scales. The range of indicator factor loadings on latent constructs are presented in the diagonal and in boldface. Intercorrelations are presented below the diagonal. N = 484. • p < .05. "p 30 kg/m" form a high-risk group that is in need of being physically active. Therefore, it is important to test if the models that explain physical activity hold true for this population in particular. Only then can one develop interventions that will be effective in this population. The current observational study aimed at testing the relationships between psychological constructs specified in the HAPA to find out whether mechanisms which were previously identified in orthopedic and cardiac reha-

bilitation patients (Fleig et al., 2011; Lippke et al., 2005; Scholz et al., 2005; Sniehotta et al, 2005; Ziegelmann et al, 2006), in patients with multiple sclerosis (Chiu et al., 2011), in individuals with Type 2 diabetes (Lippke & Plotnikoff, in press), and with physical disabilities (Perrier et al., 2012) in the context of physical activity may also apply to an obese sample. Most of the hypothesized associations were corroborated. In the motivation phase, outcome expectancies, motivational self-efficacy, and social support were associated with intention. This indicates that improving beliefs that obese individuals hold about beneficial effects of being physically active, and their own capabilities to perform a desired action, is important when motivating this population to become more active. Encouragement by family and friends was also a predictor of intentions. Further studies need to account for more detailed acts of encouragement stemming from different social sources. The strongest relationship was found between motivational self-efficacy and maintenance self-efficacy, attesting convergent validity. In the volition phase, maintenance self-efficacy was related to recovery self-efficacy and coping planning. Recovery self-efficacy in turn was associated with physical activity. Previous studies on the HAPA often omitted the volitional constructs recovery self-efficacy and coping planning. To date, tests concerning associations of maintenance self-efficacy with both recovery self-efficacy and coping planning are rather rare in the context of physical activity and therefore this study makes a contribution by filling this gap. An association between recovery self-efficacy and physical activity was found in other studies before (e.g., Chiu et al, 2011; Luszczynska, Mazurkiewicz, Ziegelmann, & Schwarzer, 2007; Luszczynska & Sutton, 2006). It was also corroborated that intention is associated with action planning and coping planning. These volitional relationships are consistent with previous research on the HAPA in the area of physical activity as well, although most studies did not observe associations separately but summarized the subscales action planning and coping planning to one scale (e.g., Caudroit et al, 2011; Chiu et al, 2011; Perrier et al., 2012). The current study also aimed at testing whether social support can be seen as an additional meaningful predictor in the HAPA. Results demonstrated that social support is not only related to

Figure 2. The Health Action Process Approach with social-cognitive determinants of physical activity in obese individuals. Boldfaced coefficients are statistically significant at least at the .05 level.

PHYSICAL ACTIVITY AND OBESITY: TESTING THE HAPA intention but also to physical activity. The assessment of support referred to encouragement of and active engagement in activity. This raises the question whether future studies should elaborate on these components and design specific measures to assess encouragement for intention formation as opposed to active engagement at the levels of initiation, action, and maintenance of exercise. Moreover, it is important to identify the social sources of selfefficacy improvement (Warner, Schiiz, Knittle, Ziegehnann, & Wurm, 2011). Contrary to our assumption, risk perception was not associated with intention. However, this is in line with other studies on physical activity. Past findings indicate that whereas risk perceptions seem to enable further elaboration of thoughts about consequences and competencies they might not be sufficient to form an intention (Schwarzer et al, 2011). Another possible explanation is that the participants already suffered from sequelae (such as diabetes). Therefore, assessing the risk of typical comorbidities of obesity might not have been adequate but should have been replaced by risk perceptions on further health decline or higher mortality risk. However, previous studies on the HAPA also failed to find risk perceptions associated with intention formation (e.g.. Barg et al., 2012; Chiu et al., 2011; Perrier et al., 2012) and therefore argued for the assumption that risk perception is a rather distal predictor of intention. Furthermore, neither action nor coping planning were related to physical activity. This is a meaningful finding given that social support emerged as being strongly related to physical activity instead. Some previous studies based on the HAPA have demonstrated that planning strategies facilitate physical activity (e.g., Chiu et al., 2011; Parschau et al., 2012; Ziegelmann et al., 2006), but there are also several studies that did not find this relationship (e.g., Caudroit et al., 2011; Perrier et al., 2012; Renner et al., 2007). In the context of dietary behavior of adults with overweight and obesity, a study on the HAPA also demonstrated that social support but not planning predicted behavior (Scholz, Ochsner, Hornung, & Knoll, 2013). A recent intervention study yielded a positive effect of implementation intentions on physical activity among obese individuals but could not confirm that action and coping planning mediated between implementation intention and number of steps a day (Bélanger-Gravel, Godin, Bilodeau, & Poirier, 2013). Even if some intervention studies could show that planning is an effective strategy for obese individuals to be more active and to lose weight (Göhner et al., 2012; Luszczynska, Sobczyk, & Abraham, 2007), these strategies alone might be insufficient for translating intention into behavior in some obese individuals. A possible explanation for this might be that planning is a cognitively demanding self-regulation strategy. However, on average, self-regulation skills were found to be lower in obese than in normal weight individuals (Davis, Patte, Curtis, & Reid, 2010; Nederkoom, Smulders, Havermans, Roefs, & Jansen, 2006), and therefore social facilitation of such skills might be a good idea.

Limitations and Future Directions By identifying motivational and volitional associations, this study provides a starting point to develop HAPA-based physical activity interventions for obese persons which can be offered and conducted in inpatient medical rehabilitation. However, when interpreting findings of the study, some limitations have to be taken

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into account. First, the majority of the sample were women and working at the time of assessment, which may affect the generalization of study findings. This uneven distribution has to be taken into account when drawing conclusions. Second, using subjective assessments such as online-based questionnaires may lead to validity bias. However, it is difficult to assess social-cognitive constructs in a different way than using self-reports, which represent the most common choice to date. Third, using online-based assessments may also have effects on the generalization of study findings as only computer-literate individuals were able to answer the questionnaires. However, there are many benefits associated with online-based studies, such as the high level of anonymity reducing intentional misreporting as well as economic advantages. A particular concern was the finding that planning did not predict the behavioral outcome. In addition to the explanations provided above, we assume that this could also be an artifact of the crosssectional nature of the data. Planning is a prospective construct, whereas behavior is reported retrospectively for the last week, which means that some participants perhaps did not perform the behavior but planned to do so, resulting in a reverse relationship. Another frequent deficit in planning research that also applies to the present study is that planning is often assessed in a rather diffuse way for instance, without asking in more detail how many plans have been formed (Wiedemann, Lippke, Reuter, Ziegelmann, & Schüz, 2011). In the present study, physical activity was measured without differentiating between low, moderate, or high intensity. An online questionnaire including scales with at least two items to assess nine social-cognitive constructs forced us to minimize the number of items to prevent premature termination of completion. Another limitation might be that some study participants were rather muscular and did not have excess body fat. This is due to the choice of the BMI to identify obese participants. Using waist circumference instead would yield a proxy of the amount of body fat. However, the BMI is the most used population-level measure of obesity (National Obesity Observatory, 2009). In addition, it cannot be precluded that other models also fit the data. However, this study tested a latent structural equation model that is in accordance with the assumptions of the HAPA, and the identified model fit the data in a satisfactory manner. Despite these limitations, future research should build on this guiding work by testing the identified relationships longitudinally and experimentally within a randomized controlled trial conducted in a rehabihtative context. This prospective research should comprise additional facets of social support which might mediate between intention and physical activity (e.g., instrumental or informational received social support). One should also consider planning strategies that do not focus only on when, where and how to be physically active but also on how to improve one's social support (Burkert, Scholz, Gralla, & Knoll, 2011; Prestwich et al., 2012). Also, participants' health status (such as disability, chronic illness conditions) and information about mobility and physical capability should be taken into account, which may moderate the associations found in this study. In addition, future research may focus on age and gender as further relevant moderators of these relationships. Furthermore, action control should be included as another promising volitional strategy. In contrast to planning, action control is an in situ self-regulatory strategy comprising the subfacets of

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awareness of standards, self-monitoring, and self-regulatory effort that specifically contribute to behavior maintenance as well as to relapse prevention (Sniehotta, Scholz, & Schwarzer, 2005; Schwarzer et al, 2011). A recent HAPA study found that action control in addition to social support predicted low-fat dietary behaviors in overweight and obese participants (Scholz et al., 2013).

Conclusion This study tested the HAPA with structural equation modeling in a large sample of obese adults. Results partly confirmed the theoretically assumed associations of the HAPA and contribute to the evidence of its suitability in the context of physical activity in obese populations. Implications exist for theory improvement and practical implementations, especially for interventions in the rehabilitation context. The HAPA appears to provide a theoretical backdrop for motivational and volitional physical activity interventions addressing obese individuals. This is especially relevant for the development of physical activity interventions for obese adults with disability and chronic illness as this high-risk group needs an appropriate management of obesity by promoting physical activity. In particular, study findings suggest that (a) encouraging outcome expectancies, motivational self-efficacy, and social support may help adults with obesity to form an intention to be physically active; (b) targeting social support might be more effective than focusing only on planning to promote physical activity; and (c) considering phase-specific self-efficacy (e.g., maintenance self-efficacy to enhance coping planning and recovery self-efficacy to foster physical activity) might help to develop more effective intervention strategies for medical rehabilitation care.

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Received January 24, 2013 Revision received September 18, 2013 Accepted October 30, 2013

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