|Does action planning moderate the intention-habit interaction in the exercise domain? A three-way interaction analysis investigation.|
|Jump to Full Text|
|PMID: 21979328 Owner: NLM Status: MEDLINE|
|Both habit strength and action planning have been found to moderate the intention-exercise behaviour relationship, but no research exists that has investigated how habit strength and action planning simultaneously influence this relationship. The present study was designed to explore this issue in a prospective sample of undergraduate students (N = 415): action planning, habit strength, intention, attitudes, subjective norms and perceived behavioural control were assessed at baseline and exercise behaviour was assessed 2 weeks later. Both habit strength and action planning moderated the intention-exercise relationship, with stronger relationship at higher levels of planning or habit strength. Decomposing a significant action planning × habit strength × intention interaction showed that the strength of the intention-exercise relationship progressed linearly through levels of action planning and habit strength. These novel results show that action planning strengthens the intention-habit strength interaction in the exercise domain: exercise interventions should therefore focus on simultaneously bolstering action planning and habit strength.|
|Gert-Jan de Bruijn; Ryan E Rhodes; Liesbeth van Osch|
Related Documents :
|8990508 - No effect of albumin on the dermal absorption rate of hydrocortisone 21-butyrate, perme...
11772878 - Reversal of angiogenic growth factor upregulation by revascularization of lower limb is...
14734828 - Emetine inhibits glycolysis in isolated, perfused rat hearts.
8079188 - Jejunal responses to absorptive and secretory stimuli in the neurally isolated jejunum ...
2197098 - Effects of single doses of quinapril and atenolol on autonomic nervous function and exe...
22993498 - Development and safety of an exercise testing protocol for patients with an implanted c...
|Type: Journal Article Date: 2011-10-08|
|Title: Journal of behavioral medicine Volume: 35 ISSN: 1573-3521 ISO Abbreviation: J Behav Med Publication Date: 2012 Oct|
|Created Date: 2012-09-12 Completed Date: 2012-11-08 Revised Date: 2013-06-27|
Medline Journal Info:
|Nlm Unique ID: 7807105 Medline TA: J Behav Med Country: United States|
|Languages: eng Pagination: 509-19 Citation Subset: IM|
|Amsterdam School of Communication Research ASCoR, University of Amsterdam, Kloveniersburgwal 48, 1012 CX, Amsterdam, The Netherlands. firstname.lastname@example.org|
|APA/MLA Format Download EndNote Download BibTex|
Exercise / psychology*
Journal ID (nlm-ta): J Behav Med
Journal ID (iso-abbrev): J Behav Med
Publisher: Springer US, Boston
© The Author(s) 2011
Received Day: 7 Month: 1 Year: 2011
Accepted Day: 8 Month: 9 Year: 2011
Electronic publication date: Day: 8 Month: 10 Year: 2011
pmc-release publication date: Day: 8 Month: 10 Year: 2011
Print publication date: Month: 10 Year: 2012
Volume: 35 Issue: 5
First Page: 509 Last Page: 519
PubMed Id: 21979328
Publisher Id: 9380
|Does action planning moderate the intention-habit interaction in the exercise domain? A three-way interaction analysis investigation|
|Gert-Jan de Bruijn1||
|Ryan E. Rhodes2|
|Liesbeth van Osch3|
1Amsterdam School of Communication Research ASCoR, University of Amsterdam, Kloveniersburgwal 48, 1012 CX Amsterdam, The Netherlands
2Behavioural Medicine Laboratory, University of Victoria, Victoria, BC Canada
3Department of Health Education and Health Promotion, Maastricht University, Maastricht, The Netherlands
Engaging in sufficient exercise has various health benefits, including decreased chances for certain cancers (Leitzmann et al., 2008) and overweight (Donnelly et al., 2009; Kromhout et al., 2001). However, exercise participation rates continue to be suboptimal (Haskell et al., 2007). Models focusing on important and modifiable determinants of exercise behaviour are thought to be relevant for exercise intervention development (Rhodes & Pfaeffli, 2010). One of the most commonly applied theoretical models in this development phase is the theory of planned behaviour (Ajzen, 1991), which theorises that intention (a conscious motivation to act) is the primary determinant of any given behaviour. The intention concept is influenced by attitudes (positive and/or negative evaluations of performance), subjective norms (perceptions of social norms to act) and perceived behavioural control (perceptions of controllability and ease of performance).
Even though the theory of planned behaviour proposes that a positive exercise intention is sufficient for exercise behaviour to occur, recent summary evidence has indicated that intentional control of (exercise) behaviour is more limited than assumed in the theory of planned behaviour (Hagger & Chatzisarantis, 2009; Hagger et al., 2002; McEachan et al., 2011; Symons Downs and Hausenblas, 2005; Webb & Sheeran, 2006). For instance, a summary study of 60 physical activity determinant studies reported a medium effect sized average correlation of .42–.51 between intention and physical activity behaviour (Hagger et al., 2002), suggesting that more than half of the variance in exercise behaviour cannot be explained by exercise intentions (Hausenblas et al., 1997; McEachan et al., 2011; Symons Downs & Hausenblas, 2005). This finding is reflected in a recent synthesis of experimental evidence showing that changes in intention lead to only small-sized changes in behaviour (Webb & Sheeran, 2006). Because most people are not engaging in exercise behaviour without positive exercise intentions (Rhodes & Plotnikoff, 2006), it would appear that those who report positive intentions, but do not act in accordance with those intentions, are the main reason for the intention-exercise gap (Orbell & Sheeran, 1998; Rhodes & Plotnikoff, 2006). Identifying post-intentional factors that can bridge this gap is therefore relevant for better exercise interventions.
Two factors that have been proposed to bridge this gap are exercise habit strength (De Bruijn & Rhodes, 2011; Rhodes et al., 2010a) and exercise self-regulation (Sniehotta et al., 2005a, b). Self-regulation refers to the formulation of action plans (the specification of when, how, and/or where to act in accordance with one’s positive exercise intentions) (Sniehotta et al., 2005a, b) and has generally shown beneficiary effects on exercise enactment in diverse samples, including rehabilitation patients (Lippke et al., 2004; Sniehotta et al., 2006), undergraduate students (Milne et al., 2002), and family members (Rhodes et al., 2010b). Furthermore, these interventions have also shown non-significant changes in exercise intention, indicating that self-regulatory strategies indeed act as a post-intentional strategy: they solidify and maintain exercise motivations by providing the how to achieve behavioural performance (Norman & Conner, 2005; Sniehotta, 2009).
Although some debate exists on the precise development of habituated performance (Ouellette & Wood, 1998; Wood & Neal, 2007), there is general consensus that habit strength emerges from repetition of behaviour in stable contexts: when behaviour is habituated, it is initiated and executed automatically and without much conscious deliberation upon encountering these contexts (Rothman et al., 2009; Verplanken & Orbell, 2003). Importantly, a recent meta-analysis (Gardner et al., 2011) on the habit strength—health behaviour relationship showed that habits have a summary relationship with health behaviour similar to intentions, affect and self-efficacy. However, research on the role of exercise habit strength in the intention-exercise relationship has been relatively limited in number and less univocal than studies employing self-regulatory strategies. In line with theoretical considerations (Triandis, 1977) empirical evidence in health behavioural domains other than exercise (De Bruijn et al., 2007, 2009) have mostly shown that stronger habits lead to weaker intention-behaviour relationships. For instance, in a study on fruit consumption (De Bruijn et al., 2007), the intention-fruit consumption relationship was seven times stronger at low levels of fruit consumption habit strength than at high levels. Likewise, in a study on active travel habits (De Bruijn et al., 2009) the intention-bicycle use relationship was more than six times stronger at lower levels of bicycle use that at higher levels. However, research on this interaction has shown mixed results in the exercise domain. Whereas cross-sectional data have shown the theorised weaker intention—exercise relationships at higher levels of exercise habit strength (De Bruijn & Rhodes, 2011), studies employing prospective designs have been unable to replicate this finding (Rhodes et al., 2010a, b). More importantly, research has also reported stronger intention-exercise relationships at higher levels of exercise habit strength (Maddux, 1997; Rhodes & De Bruijn, 2010). These counter-theoretical findings have been explained by the fact that vigorous exercise may be potentially aversive due to its strenuous nature (Ekkekakis et al., 2008; Maddux, 1997), therefore requiring substantial motivation even if strong exercise habits have developed (Rhodes & De Bruijn, 2010). As such, strong exercise habits may thus reflect action control, with those who have habituated their exercise behaviour also being better able to translate their exercise intentions into exercise behaviour (De Bruijn, 2011). More research on the interaction between exercise intention and habits is needed to ascertain their independent and interactive role in understanding exercise behaviour: such findings would not only be helpful for informing more effective exercise interventions, but also should be beneficiary for theory development on motivation and habit in the exercise domain.
Although behavioural initiation from a self-regulatory perspective partly mimics behavioural initiation from a habit theory perspective (see (Gollwitzer, 1999) for an extended discussion on this issue), effects of self-regulatory planning and habit strength have often been studied separately (Adriaanse et al., 2010; Holland et al., 2006; Verplanken & Faes, 1999), particularly in the exercise domain. Nevertheless, there appears to be merit in the simultaneous consideration of self-regulation and habitual performance. First, both automatic habits and self-regulatory action planning emphasise the role of contextual cues in behavioural initiation (Aarts et al., 1997b; Gollwitzer, 1999): action planning refers to the cognitive orientation needed to identify relevant contextual cues for behavioural enactment, whereas habit theory proposes that a particular behaviour will be automatically set in motion upon encountering situations that have been frequently paired with this behaviour (Bargh & Chartrand, 1999; Ouellette & Wood, 1998). Given the epidemiological evidence linking environmental factors with increased risk for obesity (Goran & Weinsier, 2000; Van Lenthe & Mackenbach, 2002) and decreased engagement in exercise behaviour (Spence & Lee, 2003), identifying causal pathways between the environment and physical activity behaviours should benefit both theory and practice (Baranowski et al., 2003; Owen et al., 2004).
Second, there is also evidence that self-regulatory strategies may be dependent upon automatic routines (Adriaanse et al., 2010; Holland et al., 2006; Verplanken & Faes, 1999, Webb et al., 2009). For instance, in an intervention study on nicotine dependence (as a proxy for habit strength), implementation intentions and smoking (Webb et al., 2009), results showed that smoking behaviour was reduced significantly amongst participants who had weak or moderate smoking habits, but not amongst those who had strong smoking habits. Further, by linking self-regulatory strategies to critical cues in one’s environment, one should be able to suppress the habitual behaviour and instead enact the intended alternative (Adriaanse et al., 2010; Holland et al., 2006; Verplanken & Faes, 1999). In a recent study regarding this idea, it was indeed shown that implementation intentions specifying critical cues were more successful in changing snacking consumption than traditional implementation intentions specifying when and/or where (Adriaanse et al., 2009). At present, however, there is no evidence on how self-regulatory planning and a validated measure of habit strength simultaneously influence the intention-behaviour relationship in the exercise domain.
To summarise, even though the simultaneous investigation of effects of self-regulatory planning and habit strength has proven useful in other behavioural domains, there is a lack of research on this issue in the exercise domain. Given the potential for exercise theory and intervention development, the present study was therefore set up to address the potential three-way interaction between intentions, habits, and self-regulation in the explanation of exercise behaviour. We opted to employ a three-way interaction study rather than a moderated mediation study in order to keep with the theoretical postulations in the theory of planned behaviour and habit theory. That is, whereas some studies have identified circumstances under which planning mediates the intention-behaviour relationship (Wiedemann et al., 2009), habit theory proposes a moderator effect of habit strength on the intention-behaviour relationship (Triandis, 1977). For the purpose of the present study, three hypotheses were formulated. The first two hypotheses related to the singular interaction of planning and habit strength with intention in the explanation of exercise behaviour. Based on prior evidence (Lippke et al., 2004; Milne et al., 2002; Norman & Conner, 2005; Rhodes et al., 2010a, b; Sniehotta et al., 2005a, b), we hypothesised that planning and intention would interact so that the intention-exercise relationship would be stronger at higher levels of self-regulatory planning. Regarding the interaction with habit strength, we expected a significant intention * habit interaction and tentatively hypothesised that the intention-exercise relationship would be stronger at higher levels of exercise habit strength (Rhodes & De Bruijn, 2010). Finally, we hypothesised that a significant three-way habit × planning × intention interaction would emerge and that the strongest intention-exercise relationships would emerge at high levels of both planning and habit strength.
A prospective online study was conducted amongst undergraduate students who were participating for course credits in a social psychology course from a university in a major city in the Netherlands. Course enrolment was registered for 612 students (M = 21.6 (SD = 2.9), 31.7% male) and announcements for participation were made during college hours, course meetings and black board: data were collected via an online survey tool, hosted at the university. Baseline data included measures of planning, habit strength, and variables from the theory of planned behaviour; follow-up data included measures of exercise behaviour. At baseline, data were available from 551 participants (M = 21.4 (SD = 2.8), 29.2% male), whereas data at follow-up were available from 415 participants (M = 21.4 (SD = 2.9), 26.7% male). Dropout analysis (0 = retained; 1 = dropped out) indicated that females were more likely to drop out, OR = .58, 95% CI [OR = .41, .95], but no other demographics and study variables were significantly related with dropout. The Institutional Review Board approved the execution of this study.
Exercise behaviour was assessed using the relevant items from the International Physical Activity Questionnaire (Craig et al., 2003), which has been validated against doubly labelled water techniques (Maddison et al., 2007). Participants indicated on how many days in the past 2 weeks they were engaging in vigorous exercise behaviours, which was defined as ‘activities that make you breathe deeper and faster and which may make you sweat’. In addition, participants indicated how long they were engaged in these activities on such a day. Multiplying frequency and usual duration computed an average amount of time in exercise activities per week. Concepts from the theory of planned behaviour were assessed regarding ‘exercising on at least 3 days per week and at least 20 min per bout in the next 2 weeks’. Intention was assessed with two items, (1) I intend to exercise on at least 3 days per week and at least 20 min per bout in the next 2 weeks’ and (2) ‘I am sure I will exercise on at least 3 days per week and at least 20 min per bout in the next 2 weeks’ (α = .96). Instrumental attitude was assessed with two items regarding the stem ‘I find to exercise on at least 3 days per week and at least 20 min per bout in the next 2 weeks; anchored by ‘very good (+3)’ and ‘very bad (−3)’ and ‘very healthy (+3)’ and ‘very unhealthy’ (−3) (α = .84) and affective attitude was assessed with three items regarding the same stem; items were anchored by (1) very pleasant (+3) and very unpleasant (−3), (2) very enjoyable (+3) and very unenjoyable (−3), and (3) very relaxing (+3) and very stressful (−3) (α = .93). Subjective norm was assessed with five items reflecting perceived norms towards exercising on at least 3 days per week and at least 20 min per bout in the next 2 weeks from parents, friends, partner, fellow students, and roommates (+3 = they find it very important; −3 = they find it very unimportant) (α = .77), while perceived behavioural control was assessed with two items reflecting ease of performance (+3 = very easy; −3 = very difficult) and controllability (+3 = definitely succeed; −3 = definitely not succeed) (α = .90) regarding exercising on at least 3 days per week and at least 20 min per bout in the next 2 weeks. Planning items (α = .94) were derived from recommendations (Sniehotta et al., 2005b) and previous studies (Rhodes et al., 2006; Van Osch et al., 2009) and questioned respondents about whether they had made detailed plans for the next 2 weeks regarding where to exercise, with whom to exercise, when to exercise, what kindof sport to do for exercise, and how often to exercise (+3 = totally agree; −3 = totally disagree). Habit strength (α = .95) was assessed with the self-reported habit index (Verplanken & Orbell, 2003) that consists of twelve items querying participants about key elements of habit strength, including lack of awareness, uncontrollability, and automaticity (Bargh & Chartrand, 1999). Participants answered whether the following items applied to them (+3 = totally agree; −3 = totally disagree): exercising on at least 3 days per week and at least 20 min per bout in the next 2 weeks is something (1) I do regularly, (2) I have been doing for a long time, (3) I do automatically, (4) I do without having to consciously remember, (5) that makes me feel strange when I do not do it, (6) I do without thinking, (7) that would require effort not to do, (8) that belongs to my routine, (9) I start doing before I realize I am doing it, (10) I would find hard not to do, (11), I have no need to think about doing, and (12) that is typically me.
Basic descriptives and bivariate correlations were calculated for initial data description. The main analysis employed hierarchical multiple regression analysis, with exercise in minutes per week as the dependent variable and intention and perceived behavioural control (step 1), affective attitude, instrumental attitude, subjective norm (step 2), habit strength and planning (step 3), the three two-way interactions (step 4) and the three-way interaction (step 5) as independent variables. Multicollinearity was investigated using variance inflation factors (VIF); VIF scores > 5 were regarded as indicative of multicollinearity (Tabachnick & Fidell, 2000). The constituent variables for the interaction terms were centred before computing the interaction terms. Significant interactions were decomposed by simple slope analyses (Aiken & West, 1991) and, for the three-way interaction, followed up by slope difference tests using recommended formulations (Dawson & Richter, 2006). Effect size r and f (Cohen, 1992) were used to interpret correlations and the amount of explained variance. Statistical significance was set at α = .05.
Mean exercise behaviour per week was 131.86 (SD = 174.78) minutes per week, with 55.4% (n = 230) being active for at least 60 min per week. Mean values for most study variables were around midscale, with more positive mean scores for affective and instrumental attitude. Large effect sized correlations with exercise behaviour were found for exercise habit strength, perceived behavioural control, and intention and medium effect sized correlations for action planning and affective attitude. Regarding exercise intention, large effect sizes were found for the association with habit strength, action planning, perceived behavioural control, and affective attitude and a large effect was found for the intention–action planning association (Table 1).
The initial regression model showed VIF-values exceeding critical thresholds for intention (VIF = 6.19) and perceived behavioural control (VIF = 5.73). Inspection of these variables indicated strong correlations between perceived behavioural control and intention items (range .75–.89). Consequently, given their lowest inter-item correlation (r = .75), the final regression model utilised single items for perceived behavioural control (succeed vs. not succeed) and intention (I intend to exercise) in order to assess more precise partial coefficients (Rhodes & Courneya, 2004; Tabachnick & Fidell, 2000). Table 2 reports standardised regression coefficients, F-change values and R2 for this final regression model. Before the interaction terms were added in the fourth and fifth step, analyses showed that, as predicted, intention, perceived behavioural control, habit strength, and action planning were significant predictors of, and explained 58% variance in, exercise behaviour, indicating a large effect size. Entering the two-way interaction terms showed that the habit*intention and the planning*intention interaction were significant, whereas the habit*planning interaction was not. Entering the three-way interaction in the final step showed that all interaction terms were statistically significant.
The significant habit × intention and planning × intention interactions were decomposed using simple slope analyses. Regarding the habit × intention interaction, these analyses showed that intention was a stronger predictor at high levels (β = .62, p < .001) than at medium (β = .42, p < .001) and low (β = .16, p = .024) level of exercise habit strength. Regarding the planning*intention interaction, a similar pattern was observed with a stronger intention-exercise relationship at high levels (β = .63, p < .001) of action planning than at medium (β = .42, p < .001) and low levels (β = .27, p < .001).
Decomposing the significant habit × intention × planning interaction revealed a nonsignificant intention-exercise relationship at low levels of action planning and habit strength (β = −.08, p = .444) and at high levels of action planning and low levels of habit strength (β = .17, p = .111). Stronger and significant relationships were found at low levels of action planning and high levels of habit strength (β = .25, p = .023) and at high levels of action planning and habit strength (β = .74, p < .001) (see Fig. 1). Follow-up tests revealed significant differences in intention–exercise slopes between low planning–low habit strength and the low planning–high habit strength, t(413) = 3.75, p < .001, between the low planning–low habit strength and the high planning–low habit strength, t(413) = 2.59, p = .010, between the low planning–low habit strength and the high planning–high habit strength, t(413) = 5.79, p < .001, between the low planning–high habit strength and high planning habit strength, t(413) = 4.32, p < .001, between the high planning–low habit strength and high planning–high habit strength, t(413) = 5.20, p < .001, between not between the low planning–high habit strength and high planning–low habit strength slopes, t(413) = −.43, p = .67.
The present study was set up to integrate empirical knowledge and theoretical considerations in the post-intentional exercise phase by considering habitual and self-regulatory strategies in the explanation of prospective exercise behaviour. The reported main effects of these variables were in line with earlier research: stronger exercise habits and self-regulatory planning were predictive of engaging in more exercise behaviour, even when statistically controlling for the influence of exercise intention and perceived behavioural control. Given that meta-analytical evidence on exercise determinants has shown that intention and perceived behavioural control are the strongest predictors of exercise behaviour (Hagger et al., 2002), constructs that are able to affect exercise behaviour after these two variables have been taken into account should be both theoretically (Ajzen, 1991) and practically (Baranowski et al., 1998) informative. Further, these two constructs also interacted with intention in the explanation of exercise behaviour: decomposing a significant intention × planning interaction revealed stronger intention–exercise relationships at higher levels of action planning than at lower levels of action planning. These findings are in line with theoretical postulations (Sniehotta, 2009) and earlier evidence from exercise determinant studies (Norman & Conner, 2005) and provide further fidelity that self-regulatory action planning does not only promote exercise behaviour in patient samples (Lippke et al., 2004; Sniehotta et al., 2006) and family members (Rhodes et al., 2010a, b), but should also be employed in exercise interventions in young adults (Conner et al., 2010).
When the significant intention–habit strength interaction was decomposed, findings were also in line with our tentatively formulated hypothesis: intention was a stronger predictor of exercise behaviour at higher, rather than at lower, levels of exercise habit strength. This finding is noteworthy, because it counters theoretical considerations (Aarts et al., 1997b; Triandis, 1977) and empirical evidence in other health behavioural domains (De Bruijn et al., 2007, 2008), including more moderate activity behaviours (De Bruijn & Gardner, 2011; De Bruijn et al., 2009; Rhodes & De Bruijn, 2010) that suggest limited intentional control of behaviour at high levels of habit strength. As noted, however, the strenuous and effortfulness nature of exercise behaviour may require strong motivational and automatic components simultaneously, rather than a trade-off between these components (Maddux, 1997; Rhodes & De Bruijn, 2010). Apparently, strenuous behaviours may set some boundary limitation on the intention–habit trade-off observed in more everyday behaviours, such as fruit and fat consumption (De Bruijn et al., 2007, 2008) and transport mode choices (De Bruijn et al., 2009). Alternatively, some considerations (Ajzen, 2002) have also proposed that a distinction should be made between automaticity in executing behaviour and automaticity in the decision to take action. It would seem that, for exercise behaviours, the automatic component of habit strength might be more relevant for behavioural decisions (e.g. going for a mountain bike ride at a specific time and place), rather than the behavioural performance itself (Ajzen, 2002; Ajzen & Fishbein, 2001; Rhodes & De Bruijn, 2010; Verplanken & Melkevik, 2008). For behavioural performance, habit strength measures may reflect the importance for action control, with those who have habituated exercise behaviour demonstrating more success in translating their positive exercise intentions into actual exercise behaviour (De Bruijn, 2011; Rhodes et al., 2010a, b).
The final purpose of the present study was to investigate the three-way interaction between planning, habits, and intention in the prediction of exercise behaviour. The decomposition of a significant interaction term showed that the strength of the intention-exercise relationship progressed linearly across levels of action planning and habit strength: the weakest relationship was found at low levels of planning and habit strength, whereas the strongest relationship was found at high levels of planning and habit strength. Thus, stronger self-regulatory planning and exercise habits do not only independently lead to more exercise behaviour and stronger intention-exercise relationships, but also work in concert to produce or solidify the intention –exercise behaviour relation. These findings counter results from an earlier smoking intervention (Webb et al., 2009), where stronger smoking habits decreased the effectiveness of an implemental planning interventions. Although results similar to this latter study have also been reported in the dietary domain (Adriaanse et al., 2010; Verplanken & Faes, 1999), it should be noted that habit strength and self-regulatory strategies have only been studied relatively recent in health promotional research. Moreover, whereas self-regulatory strategies have been studied between behaviours (i.e. planning and habits related to different behaviours, e.g. fruit consumption and snack intake), studies employing habitual considerations of behaviour have often been conducted within behaviours (i.e. intentions and habits related to the same behaviour). Given that habit theory also considers counter-intentional habits as inhibitors of motivational action, future research should also investigate which behaviours have habitual capacities that inhibit action following from exercise intentions.
Although exercise behaviour in itself it linked with chronic diseases and is plagued by low adherence, the limited research on the simultaneous investigation of habits and self-regulation prohibits definite conclusions regarding the pathways that link these constructs with intention and health behaviour in general. Clearly, replications of the interaction between these variables in other health behavioural domains are needed to identify the universality of the present findings or to ascertain whether this effect is affected by relevant moderator variables, such as behaviour type. For instance, within the physical activity domain, intensity of the activity behaviour (i.e. more moderate activities such as walking vs. more vigorous activities such as exercise) has been found to moderate the effect of habit in the intention-activity relationship (Rhodes & De Bruijn, 2010). Likewise, significant interaction effects between intention and habit have consistently been reported in the dietary domain (De Bruijn, 2011; De Bruijn et al., 2007, 2008) and the travel domain (De Bruijn & Gardner, 2011; De Bruijn et al., 2009), but evidence from other health behaviours, such as binge drinking (Norman, 2011), have failed to find significant interactions. Moreover, mixed findings have also been reported with regard to the effectiveness of action planning, with some studies reporting only limited (De Nooijer et al., 2006; Sniehotta et al., 2005a, b) or no effects (De Vet et al., 2009; Koestner et al., 2006; Rise et al., 2003) on behavioural changes. Evidently, habits do not always set boundary limitations on the intention-health behaviour relationship and self-regulatory strategies do not always guarantee behavioural action. Thus, more research on how habits, planning, intentions and behaviour interrelate is needed to better detail the mechanisms of this interaction in order inform and modify behaviour change theories and intervention strategies.
One particularly relevant way to better detail these mechanisms is to experimentally manipulate action planning, rather than assessing it through survey measures. In this respect, Weinstein (2007) has argued that ongoing behaviours (those that people perform regularly) may lead people to create or strengthen their perception of, and the reasons for, their behaviour based on performing the behaviour. Rooted in dissonance (Festinger, 1957) and self-perception (Bem, 1967) theory, these reasons and perceptions may lead to unjustified claims of causes of behaviour, particularly when assessed with survey measures (Schwarz, 1999). For instance, a recent series of systematic reviews reported limited evidence for the influence of environmental factors on obesogenic behaviours based on observational survey-based studies. In contrast, though, when contextual variables were manipulated in intervention research, much stronger effects on obesogenic behaviours were reported (Brug et al., 2006). These results demonstrate that reliance on observational and/or self-reported survey data may lead to misinforming theory and intervention and emphasize that experiments or quasi-experiments should be prioritized in health promotional research (Weinstein, 2007). Whereas the application of self-regulatory strategies in these experimental settings may be straightforward, the promotion of habituation of exercise behaviour is arguably more challenging. That is, self-regulatory interventions typically require the participant to formulate implementation intentions specifying where and/or when to act, with nonsignificant differences in intervention effectiveness between self-generated or experiment-provided implementation intentions (Armitage, 2009).
However, research on habit formation has shown that habituation of exercise behaviour can take up to 90 days (Lally et al., 2009), suggesting that behavioural recurrence is needed for exercise habituation to occur. Further, models on habit development propose that this recurrence should be accompanied by stable and supporting environmental cues (Aarts et al., 1997a, b; Ouellette & Wood, 1998). While these suggestions are in line with ecological models of health behaviour (Kremers et al., 2006; Spence & Lee, 2003), the often-observed large effect size correlation between affect and habit strength (De Bruijn, 2011; De Bruijn & Rhodes, 2011; Rhodes et al., 2010a, b) indicates that promoting affective evaluations may also be beneficiary to habit formation. In fact, considerations and evidence from not only a habit theory perspective, but also from a self-determination theory perspective, have outlined the potential relevance of positive affective responses in human action. That is, not only has positive affect been found to be an implicit motivator of automatic action (Custers & Aarts, 2005), positive affective responses are also viewed as self-determined intrinsic motivations in self-determination theory (Hagger & Chatzisarantis, 2009). Intrinsic motivation reflects the extent to which action is undertaken based solely on experiential positive rewards, such as enjoyment, pleasure and fun (Hagger & Chatzisarantis, 2009; Rhodes et al., 2009). Moreover, recent evidence has indicated that those affective evaluations are strong predictors of activity behaviours (Rhodes et al., 2009) that may influence behaviour outside of conscious intentions (Keer et al., 2010; Lawton et al., 2009, 2007) in a manner similar to how habits affect behaviour (De Bruijn & Van den Putte, 2009; Verplanken & Orbell, 2003). Although these findings indicate that employing affective strategies and persuasive messages should be preferably included in exercise promotion interventions that aim to develop and/or foster strong exercise habits, there is only limited evidence of those strategies actually being employed in exercise behaviour change interventions (Conner et al., 2011; Parrot et al., 2008) and no evidence exists whether these exercise behaviours are maintained for sufficient periods to reach an acceptable level of automaticity (Lally et al., 2009).
Despite its practical and theoretical informative nature, the present study is subject to limitations. The first limitation relates to the self-report measures of exercise behaviour that were employed in the study, which may have led to measurement errors from recall bias (Prince et al., 2008). The second limitation relates to the study population, which consisted of a convenience sample of undergraduate students. Although studies employing population-based samples (Rhodes & Plotnikoff, 2006; Rhodes et al., 2008b) have reported similar intention-exercise relationships as those presented in the current study and research has indicated that there is little evidence for differences in theoretical relationships between undergraduate and other samples (Rhodes et al., 2008a), there is evidence of a positive link between educational level and physical activity levels (Van Lenthe et al., 2004). Consequently, our study sample may have had an overrepresentation of sufficient exercisers. Another limitation of our study was the use of single items for intention and perceived behavioural control that was deemed necessary in order to deal with multicollinearity issues and conceptual and/or measurement redundancy, also based on earlier studies indicating measurement issues between perceived behavioural control and intention (Rhodes & Courneya, 2004). Future studies may need to consider this potential overlap when assessing perceived behavioural control and intention in order to reduce the potential inflation of coefficients, which are particularly evident when motivation is not held constant (Rhodes & Courneya, 2004), thereby potentially misinforming exercise interventions. Also, although the items that were kept for the final analyses directly addressed the domain of the respective constructs, constructs assessed with single items have limited construct validity and psychometric properties (Streiner & Norman, 2003). A fourth limitation of our study relates to the short time period between assessing intentions, planning items and habit strength and follow-up exercise behaviour. Although short time periods are relatively common in studies on exercise behaviour and habit strength (De Bruijn, 2011; Rhodes et al., 2010a, b) and self-regulatory strategies (Milne et al., 2002) and also suggested for research using the theory of planned behaviour (Ajzen, 1991; Ajzen & Fishbein, 2001) in order to allow for more accurate predictions, this short time lag does not provide evidence on how exercise behaviour, intentions, habits and self-regulatory planning have developed across time: studies using cross-lagged panel data are needed to unravel these potential interrelating pathways. One final limitation relates to our use of action planning as the sole post-intentional strategy. There is, however, evidence that preparatory planning (i.e. formulating preparatory behaviours needed for goal achievement) outperforms action planning in the prediction of fruit consumption (Van Osch et al., 2010). Although determinants of fruit consumption and exercise behaviour may differ, these findings do suggest including multiple self-regulation strategies in determinant and intervention studies in order to detect their surplus value in predicting exercise behaviour.
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
|Aarts H,Paulussen T,Schaalma H. Physical exercise habit: On the conceptualization and formation of habitual health behavioursHealth Education ResearchYear: 19971236337410.1093/her/12.3.36310174219|
|Aarts H,Verplanken B,Knippenberg A. Habit and information use in travel mode choicesActa PsychologicaYear: 19979611410.1016/S0001-6918(97)00008-5|
|Adriaanse MA,Ridder DTD,Wit JBF. Finding the critical cue: Implementation intentions to change one’s diet work best when tailored to personally relevant reasons for unhealthy eatingPersonality and Social Psychology BulletinYear: 200935607110.1177/014616720832561219106078|
|Adriaanse MA,Oettingen G,Gollwitzer PM,Hennes EP,Ridder DTD,Wit JBF. When planning is not enough: Fighting unhealthy snacking habits by mental contrasting with implementation intentionsEuropean Journal of Social PsychologyYear: 2010401277129310.1002/ejsp.730|
|Aiken LS,West SG. Multiple regression: Testing and interpreting interactionsYear: 1991Thousand Oaks, CASage Publications, Inc|
|Ajzen I. The theory of planned behaviourOrganizational Behavior and Human Decision ProcessesYear: 19915017921110.1016/0749-5978(91)90020-T|
|Ajzen I. Residual effects of past on later behaviour: Habituation and reasoned action perspectivesPersonality and Social Psychology ReviewYear: 2002610712210.1207/S15327957PSPR0602_02|
|Ajzen I,Fishbein M. Attitudes and the attitude-behavior relation: Reasoned and automatic processesEuropean Review of Social PsychologyYear: 20011113310.1080/14792779943000116|
|Armitage CJ. Effectiveness of experimenter-provided and self-generated implementation intentions to reduce alcohol consumption in a sample of the general population: A randomized exploratory trialHealth PsychologyYear: 20092854555310.1037/a001598419751080|
|Baranowski T,Anderson C,Carmack C. Mediating variable framework in physical activity interventions: How are we doing? How might we do better?American Journal of Preventive MedicineYear: 19981526629710.1016/S0749-3797(98)00080-49838973|
|Baranowski T,Cullen KW,Nicklas T,Thompson D,Baranowski J. Are current health behavioral change models helpful in guiding prevention of weight gain efforts?Obesity ResearchYear: 200311S23S4310.1038/oby.2003.222|
|Bargh JA,Chartrand TL. The unbearable automaticity of beingAmerican PsychologistYear: 19995446247910.1037/0003-066X.54.7.462|
|Bem DJ. Self-perception: An alternative interpretation of cognitive dissonance phenomenaPsychological ReviewYear: 19677418320010.1037/h00248355342882|
|Brug J,Lenthe F,Kremers SP. Revisiting Kurt Lewin: How to gain insight into environmental correlates of obesogenic behavioursAmerican Journal of Preventive MedicineYear: 200631252910.1016/j.amepre.2006.08.01616777539|
|Cohen J. A power primerPsychological BulletinYear: 199211215515910.1037/0033-2909.112.1.15519565683|
|Conner M,Rhodes R,Morris B,McEachan R,Lawton R. Changing exercise through targeting affective or cognitive attitudesPsychology & HealthYear: 20112611710.1080/08870446.2011.537476|
|Conner M,Sandberg T,Norman P. Using action planning to promote exercise behaviorAnnals of Behavioral MedicineYear: 201040657610.1007/s12160-010-9190-820446124|
|Craig CL,Marshall AJ,Sjöström M,Bauman A,Booth ML,Ainsworth BE,Pratt M,Ekelund U,Yngve A,Sallis JF,Oja P. International Physical Activity Questionnaire: 12-country reliability and validityMedicine and Science in Sports and ExcerciseYear: 2003351381139510.1249/01.MSS.0000078924.61453.FB|
|Custers R,Aarts H. Positive affect as implicit motivator: On the nonconscious operation of behavioral goalsJournal of Personality and Social PsychologyYear: 20058912914210.1037/0022-35126.96.36.19916162049|
|Dawson JF,Richter AW. Probing three-way interactions in moderated multiple regressions: Development and application of a slope difference testJournal of Applied PsychologyYear: 20069191792610.1037/0021-9010.91.4.91716834514|
|Bruijn GJ. Exercise habit strength, planning, and the theory of planned behaviour: An action control approachPsychology of Sport and ExerciseYear: 20111110611410.1016/j.psychsport.2010.10.002|
|Bruijn GJ,Gardner B. Active commuting and habit strength: An interactive and discriminant analyses approachAmerican Journal of Health PromotionYear: 201125e27e3710.4278/ajhp.090521-QUAN-17021192741|
|Bruijn GJ,Kremers SPJ,Vet E,Nooijer J,Mechelen W,Brug J. Does habit strength moderate the intention-behaviour relationship in the Theory of Planned Behaviour? The case of fruit consumptionPsychology and HealthYear: 20072289991610.1080/14768320601176113|
|Bruijn GJ,Kremers SPJ,Singh A,Putte B,Mechelen W. Adult active transportation: Adding habit strength to the Theory of Planned BehaviorAmerican Journal of Preventive MedicineYear: 20093618919410.1016/j.amepre.2008.10.01919162430|
|Bruijn GJ,Kroeze W,Oenema A,Brug J. Saturated fat consumption and the Theory of Planned Behaviour: Additive and interaction effects of habit strengthAppetiteYear: 20085131832310.1016/j.appet.2008.03.01218471932|
|Bruijn GJ,Rhodes RE. Exercise, intention and habit strength relationshipsScandinavian Journal of Medicine and Science in SportsYear: 20112148249110.1111/j.1600-0838.2009.01064.x20136755|
|Bruijn GJ,Van den Putte B. Adolescent soft drink consumption, television viewing, and habit strength: Investigating clustering effects in the Theory of Planned BehaviourAppetiteYear: 200953667510.1016/j.appet.2009.05.00819463873|
|Nooijer J,Vet E,Brug J,Vries NK. Do implementation intentions help to turn good intentions into higher fruit intakes?Journal of Nutrition Education and BehaviourYear: 200638252910.1016/j.jneb.2005.11.021|
|Vet E,Oenema A,Sheeran P,Brug J. Should implementation intentions interventions be implemented in obesity prevention: The impact of if-then plans on daily physical activity in Dutch adultsInternational Journal of Behavioural Nutrition and Physical ActivityYear: 200961110.1186/1479-5868-6-11|
|Donnelly JE,Blair SN,Jakicic JM,Manore MM,Rankin JW,Smith BK. Appropriate physical activity intervention strategies for weight loss and prevention of weight regain for adultsMedicine and Science in Sports and ExerciseYear: 20094145947119127177|
|Ekkekakis P,Hall EE,Petruzello SJ. The relationship between exercise intensity and affective responses demystified: To crack the 40-year-old nut, replace the 40-year-old nutcracker!Annals of Behavioral MedicineYear: 20083513614910.1007/s12160-008-9025-z18369689|
|Festinger L. A theory of cognitive dissonanceYear: 1957Evanston, ILRow, Peterson|
|Gardner B,Bruijn GJ,Lally P. A systematic review and meta-analysis of applications of the Self-Report Habit Index to nutrition and physical activity behaviorsAnnals of Behavioral MedicineYear: 20114217418710.1007/s12160-011-9282-021626256|
|Gollwitzer PM. Implementation intentions: Strong effects of simple plansAmerican PsychologistYear: 19995449350310.1037/0003-066X.54.7.493|
|Goran MI,Weinsier RL. Role of environmental vs. metabolic factors in the etiology of obesity: Time to focus on the environmentObesity ResearchYear: 2000840740910.1038/oby.2000.5010968734|
|Hagger MS,Chatzisarantis NLD. Integrating the theory of planned behaviour and self-determination theory in health behaviour: A meta-analysisBritish Journal of Health PsychologyYear: 20091427530210.1348/135910708X37395918926008|
|Hagger MS,Chatzisarantis NLD,Biddle SJH. A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: Predictive validity and the contribution of additional variablesJournal of Sport and Exercise PsychologyYear: 200224332|
|Haskell WL,Lee IM,Pate RR,Powell KE,Blair SN,Franklin BA,Bauman A. Physical activity and public health: Updated recommendation for adults from the American College of Sports Medicine and the American Heart AssociationMedicine and Science in Sports and ExcerciseYear: 2007391423143410.1249/mss.0b013e3180616b27|
|Hausenblas HA,Carron AV,Mack DE,Godin G. Application of the theories of reasoned action and planned behavior to exercise behaviour: A meta-analysisJournal of Sport and Exercise PsychologyYear: 1997193651|
|Holland RW,Aarts H,Langendam D. Breaking and creating habits on the working floor: A field-experiment on the power of implementation intentionsJournal of Experimental Social PsychologyYear: 20064277678310.1016/j.jesp.2005.11.006|
|Keer M,Putte B,Neijens P. The role of affect and cognition in health decision makingBritish Journal of Social PsychologyYear: 20104914315310.1348/014466609X42533719358744|
|Koestner R,Horberg EJ,Gaudreau P,Powers T,Di Dio P,Bryan C,Jochum R,Salter N. Bolstering implementation intention plans for the long haul: The benefits of simultaneously boosting self-concordance or self-efficacyPersonality and Social Psychology BulletinYear: 2006321547155810.1177/014616720629178217030894|
|Kremers, S. P. J., de Bruijn, G. J., Visscher, T. L. S., Van Mechelen, W., de Vries, N. K., & Brug, J. (2006). Environmental influences on energy balance-related behaviors: A dual-process view. International Journal of Behavioral Nutrition and Physical Activity, 3.|
|Kromhout D,Bloemberg B,Seidell JC,Nissinen A,Menotti A. Physical activity and dietary fiber determine population body fat levels: The Seven Country StudiesInternational Journal of Obesity and Related Metabolic DisordersYear: 20012530130610.1038/sj.ijo.080156811319625|
|Lally P,Jaarsveld CHM,Potts HWW,Wardle J. How are habits formed: Modelling habit formation in the real worldEuropean Journal of Social PsychologyYear: 200940998100910.1002/ejsp.674|
|Lawton R,Conner M,McEachan R. Desire or reason: Predicting health behaviors from affective and cognitive attitudesHealth PsychologyYear: 200928566510.1037/a001342419210018|
|Lawton R,Conner M,Parker D. Beyond cognition: Predicting health risk behaviors from instrumental and affective beliefsHealth PsychologyYear: 20072625926710.1037/0278-6188.8.131.52917500612|
|Leitzmann MF,Moore SC,Peters TM,Lacey JV,Schatzkin A,Schairer C,Brinton LA,Albanes D. Prospective study of physical activity and postmenopausal breast cancerBreast Cancer ResearchYear: 200810R9210.1186/bcr219018976449|
|Lippke S,Ziegelmann JP,Schwarzer R. Behavioral intentions and action plans promote physical exercise: A longitudinal study with orthopedic rehabilitation patientsJournal of Sport and Exercise PsychologyYear: 200426470483|
|Maddison R,Ni Mhurchu C,Jiang Y,Vander Hoorn S,Rodgers A,Lawes C,Rush E. International Physical Activity Questionnaire (IPAQ) and New Zealand Physical Activity Questionnaire (NZPAQ): A doubly labelled water validationInternational Journal of Behavioral Nutrition and Physical ActivityYear: 200746210.1186/1479-5868-4-6218053188|
|Maddux JE. Habit, health, and happinessJournal of Sport and Exercise PsychologyYear: 199719331346|
|McEachan, R. R. C., Conner, M., Taylor, N. J., & Lawton, R. J. (2011). Prospective prediction of health-related behaviours with the theory of planned behaviour: A meta-analysis. Health Psychology Review, 5.|
|Milne S,Orbell S,Sheeran P. Combining motivational and volitional interventions to promote exericse participation: Protection motivation theory and implementation intentionsBritish Journal of Health PsychologyYear: 2002716318410.1348/13591070216942014596707|
|Norman P. The theory of planned behaviour and binge drinking among undergraduate students: Assessing the impact of habit strengthAddictive BehaviorsYear: 20113650250710.1016/j.addbeh.2011.01.02521310540|
|Norman P,Conner M. The theory of planned behavior and exercise: Evidence for the mediating and moderating roles of planning on intention-behavior relationshipsJournal of Sport and Exercise PsychologyYear: 200527488504|
|Orbell S,Sheeran P. Inclined abstainers: A problem for predicting health related behaviourBritish Journal of Social PsychologyYear: 19983715116510.1111/j.2044-8309.1998.tb01162.x9639861|
|Ouellette JA,Wood W. Habit and intention in everyday life: The multiple processes by which past behavior predicts future behaviorPsychological BulletinYear: 1998124547410.1037/0033-2909.124.1.54|
|Owen N,Humpel N,Leslie E,Bauman A,Sallis JF. Understanding environmental influences on walking: Review and research agendaAmerican Journal of Preventive MedicineYear: 200427677610.1016/j.amepre.2004.03.00615212778|
|Parrot MW,Tennant LK,Olejnik S,Poudevigne MS. Theory of planned behaviour: Implications for an email-based physical activity interventionPsychology of Sport and ExerciseYear: 2008951152610.1016/j.psychsport.2007.07.002|
|Prince, S., Adamo, K., Hamel, M., Hardt, J., Connor Gorbor, S., & Tremblay, M. (2008). A comparison of direct versus self-report measures for assessing physical activity in adults: A systematic review. International Journal of Behavioral Nutrition and Physical Activity, 5.|
|Rhodes RE,Blanchard CM,Blacklock RE. Do physical activity beliefs differ by age and gender?Journal of Sport & Exercise PsychologyYear: 20083041242318648113|
|Rhodes RE,Blanchard CM,Matheson DM,Coble J. Disentangling motivation, intention and planning in the physical activity domainPsychology of Sport and ExerciseYear: 20067152710.1016/j.psychsport.2005.08.011|
|Rhodes RE,Courneya K. Differentiating motivation and control in the Theory of Planned BehaviourPsychology, Health & MedicineYear: 2004920521510.1080/13548500410001670726|
|Rhodes R,Bruijn GJ. Automatic and motivational correlates of physical activity: Does intensity moderate the relationship?Behavioral MedicineYear: 201036445210.1080/0896428100377490120497942|
|Rhodes RE,Bruijn GJ,Matheson DH. Habit in the physical activity domain: Integration with intention temporal stability and action controlJournal of Sport and Exercise PsychologyYear: 201032849820167953|
|Rhodes R,Fiala B,Conner M. Affective judgments and physical activity: A review and meta-analysisAnnals of Behavioral MedicineYear: 20093818020410.1007/s12160-009-9147-y20082164|
|Rhodes R,Naylor P-J,McKay HA. Pilot study of a family physical activity planning intervention among parents and their childrenJournal of Behavioural MedicineYear: 2010339110010.1007/s10865-009-9237-0|
|Rhodes R,Pfaeffli L. Mediators of physical activity behaviour change among adult non-clinical populations: A review updateInternational Journal of Behavioral Nutrition and Physical ActivityYear: 201073710.1186/1479-5868-7-3720459781|
|Rhodes RE,Plotnikoff RC. Understanding action control: Predicting physical activity intention-behavior profiles across six months in a Canadian sampleHealth PsychologyYear: 20062529229910.1037/0278-6184.108.40.206216719600|
|Rhodes RE,Plotnikoff RC,Courneya KS. Predicting the physical activity intention-behavior profiles of adopters and maintainers using three social cognition modelsAnnals of Behavioral MedicineYear: 20083624425210.1007/s12160-008-9071-619057976|
|Rise J,Thompson M,Verplanken B. Measuring implementation intentions in the context of the theory of planned behaviourScandinavian Journal of PsychologyYear: 200344879510.1111/1467-9450.0032512778976|
|Rothman AJ,Sheeran P,Wood W. Reflective and automatic processes in the initiation and maintenance of dietary changeAnnals of Behavioral MedicineYear: 200938S4S1710.1007/s12160-009-9118-319787308|
|Schwarz N. Self-reports: How the questions shape the answersAmerican PsychologistYear: 1999549310510.1037/0003-066X.54.2.93|
|Sniehotta FF. Towards a theory of intentional behaviour change: Plans, planning, and self-regulationBritish Journal of Health PsychologyYear: 20091426127310.1348/135910708X38904219102817|
|Sniehotta FF,Scholz U,Schwarzer R. Bridging the intention-behaviour gap: Planning, self-efficacy, and action control in the adoption and maintenance of physical exercisePsychology & HealthYear: 20052014316010.1080/08870440512331317670|
|Sniehotta FF,Scholz U,Schwarzer R. Action plans and coping plans for physical exercise: A longitudinal intervention study in cardiac rehabilitationBritish Journal of Social PsychologyYear: 2006112337|
|Sniehotta FF,Schwarzer R,Scholz U,Schuz B. Action planning and coping planning for long-term lifestyle change: Theory and assessmentEuropean Journal of Social PsychologyYear: 20053556557610.1002/ejsp.258|
|Spence JC,Lee RE. Toward a comprehensive model of physical activityPsychology of Sport and ExerciseYear: 2003472410.1016/S1469-0292(02)00014-6|
|Streiner DL,Norman GR. Health measurement scales: A practical guide to their development and useYear: 2003New YorkOxford University Press|
|Symons Downs D,Hausenblas HA. Exercise behavior and the theories of reasoned action and planned behavior: A meta-analytic updateJournal of Physical Activity and HealthYear: 200527697|
|Tabachnick BG,Fidell LS. Using multivariate statisticsYear: 20004New YorkAllyn & Bacon, Inc.|
|Triandis H. Interpersonal behaviorYear: 1977Montery, CABrooks/Cole|
|Lenthe FJ,Mackenbach JP. Neighbourhood deprivation and overweight: The GLOBE studyInternational Journal of Obesity and Related Metabolic DisordersYear: 20022623424010.1038/sj.ijo.080184111850756|
|Lenthe FJ,Schrijvers CT,Droomers M,Joung IM,Louwman MJ,Mackenbach JP. Investigating explanations of socio-economic inequalities in health: The Dutch GLOBE studyEuropean Journal of Public HealthYear: 200414637010.1093/eurpub/14.1.6315080394|
|Osch L,Beenackers M,Reubsaet A,Lechner L,Candel M,Vries H. Action planning as predictor of health protective and health risk behavior: An investigation of fruit and snack consumptionInternational Journal of Behavioral Nutrition and Physical ActivityYear: 200966910.1186/1479-5868-6-6919825172|
|Osch L,Reubsaet A,Lechner L,Beenackers M,Candel M,Vries H. Planning health behaviour change: Comparing the behavioural influence of two types of self-regulatory planningBritish Journal of Health PsychologyYear: 20101513314910.1348/135910709X43672319454143|
|Verplanken B,Faes S. Good intentions, bad habits, and effects of forming implementation intentions on healthy eatingEuropean Journal of Social PsychologyYear: 19992959160410.1002/(SICI)1099-0992(199908/09)29:5/6<591::AID-EJSP948>3.0.CO;2-H|
|Verplanken B,Melkevik O. Predicting habit: The case of physical exercisePsychology of Sport and ExerciseYear: 20089152610.1016/j.psychsport.2007.01.002|
|Verplanken B,Orbell S. Reflections of past behavior: A self-report index of habit strengthJournal of Applied Social PsychologyYear: 2003331313133010.1111/j.1559-1816.2003.tb01951.x|
|Webb TL,Sheeran P. Does changing behavioral intentions engender behavior change? A meta-analysis of the experimental evidencePsychological BulletinYear: 200613224926810.1037/0033-2909.132.2.24916536643|
|Webb TL,Sheeran P,Luszczynska A. Planning to break unwanted habits: Habit strength moderates implementation intention effects on behaviour changeBritish Journal of Social PsychologyYear: 20094850752310.1348/014466608X37059118851764|
|Weinstein ND. Misleading tests of health behaviour theoriesAnnals of Behavioral MedicineYear: 20073311010.1207/s15324796abm3301_117291165|
|Wiedemann AU,Schuz B,Sniehotta FF,Scholz U,Schwarzer R. Disentangling the relation between intentions, planning, and behaviour: A moderated mediation analysisPsychology & HealthYear: 200924677910.1080/0887044080195821420186640|
|Wood W,Neal DT. A new look at habits and the habit-goal interfacePsychological ReviewYear: 200711484386310.1037/0033-295X.114.4.84317907866|
[Figure ID: Fig1]
Slopes for intention-exercise relationship across levels of action planning and habit strength
Mean scores, standard deviations, and intercorrelations between study variables and demographics
|1. Exercise (minutes per week)||–||131.86||174.78|
|5. Instrumental attitude||.15**||.23***||.22***||.23***||–||2.26||.92|
|6. Affective attitude||.36***||.62***||.65***||.46***||.46***||–||1.39||1.42|
|7. Subjective Norm||.06||.22***||.19***||.20***||.19***||.18***||–||.25||.95|
|8. Perceived behavioural control||.54***||.86***||.78***||46***||.18***||.59***||.13**||–||.51||1.82|
|10. Gender (0 = female; 1 = male)||−.25*||−.17***||−.18**||−.06||.03||−.12*||−.04||−.17**||−.13*|
Scores for theory of planned behaviour concepts ranged from −3 (most negative) to +3 (most positive)
* p < .05; ** p < .01; *** p < .001
Unstandardized and standardized regression coefficients and R2 and F-value for exercise in minutes per week
|Step||Predictor||b (SE)||β||R2||F||Δ R2||ΔF|
|Instrumental attitude||6.85 (8.90)||.04|
|Affective attitude||2.66 (7.08)||.02|
|Subjective norm||−9.30 (7.87)||−.05|
|Instrumental attitude||7.11 (8.66)||.04|
|Affective attitude||−9.17 (7.33)||−.08|
|Subjective norm||−13.37 (7.77)||−.08|
|Habit strength||23.22 (7.25)||.23**|
|Instrumental attitude||.94 (8.43)||.01|
|Affective attitude||.79 (7.26)||.01|
|Subjective norm||−10.03 (7.42)||−.06|
|Habit strength||15.15 (7.10)||.15*|
|Habit strength × planning||−7.14 (3.72)||−.13|
|Habit strength × intention||11.50 (2.68)||.22**|
|Planning × intention||10.61 (3.20)||.20**|
|Instrumental attitude||1.07 (8.35)||.01|
|Affective attitude||−1.38 (7.24)||−.01|
|Subjective norm||−9.86 (7.36)||−.05|
|Habit strength||9.49 (7.31)||.10|
|Habit strength × planning||−7.64 (3.70)||−.15*|
|Habit strength × intention||13.67 (2.76)||.24***|
|Planning × intention||11.95 (3.20)||.25***|
|Planning × intention × habit strength||3.47 (1.20)||.15**|
PBC perceived behavioural control
* p < .05; ** p < .01; *** p < .001
Keywords: Keywords Exercise behaviour, Intention-exercise relationship, Habit strength, Action planning, Interaction.
Previous Document: Sodium chloride improves photosynthesis and water status in the succulent xerophyte Zygophyllum xant...
Next Document: GENETIC MARKERS TO DISCRIMINATE BENIGN AND MALIGNANT THYROID NODULES WITH UNDETERMINED CYTOLOGY IN A...