Predicting habit: The case of physical exercise

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Psychology of Sport and Exercise 9 (2008) 15–26 www.elsevier.com/locate/psychsport

Predicting habit: The case of physical exercise$ Bas Verplankena,, Ole Melkevikb a

Department of Psychology, University of Bath, Claverton Down, Bath BA2 7AY, UK b University of Bergen, Norway

Received 31 October 2005; received in revised form 18 December 2006; accepted 2 January 2007 Available online 23 January 2007

Abstract Objectives: Habit has been an undervalued concept in the behavioral sciences during the past few decades. One reason may be that habit has been equated with behavioral frequency. This leaves out an important characteristic of habits, i.e., the fact that repeated behavior may acquire a degree of automaticity. The present study aimed to demonstrate that exercising habit can be reliably measured, can empirically be distinguished from past frequency of exercising, and can thus be adopted as a meaningful criterion. Design and methods: A longitudinal study was conducted with two measurements one month apart among 111 students. Intentions to exercise, perceived behavioral control of exercising, past exercising frequency, and exercising habit were assessed at both measurements through an internet-based questionnaire. Exercising habit was assessed by the Self-Report Habit Index [Verplanken & Orbell (2003). Reflections on past behaviour: A self-report index of habit strength. Journal of Applied Social Psychology, 33, 1313–1330]), which breaks down the habit concept in the subjective experience of repetition and automaticity. Results: The results showed that exercising habit can be reliably measured, is stable over time, and can be distinguished from mere exercising frequency. Conclusions: In addition to frequency of behavior, measuring habit provides information about the way behavior is executed. An important element of exercising behavior is the decision to go

$

This study was conducted while Bas Verplanken was at the University of Tromsø, Norway and at the Norwegian University of Science and Technology, Norway, and Ole Melkevik was an undergraduate student at the Norwegian University of Science and Technology, Norway. Corresponding author. Tel.: +44 1225 384906; fax: +44 1225 386752. E-mail address: [email protected] (B. Verplanken). 1469-0292/$ - see front matter r 2007 Elsevier Ltd. All rights reserved. doi:10.1016/j.psychsport.2007.01.002

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exercise. It is argued that the habit concept is therefore particularly relevant for the initiation of and adherence to exercising. Implications of distinguishing behavioral frequency and habit for interventions are discussed. r 2007 Elsevier Ltd. All rights reserved. Keywords: Physical exercise; Habit; Behavioral frequency

Introduction Because physical exercise is a major ingredient of a healthy life style, it is important to understand and predict this behavior. Social-cognitive models, in particular the theory of planned behavior (TPB; Ajzen, 1985), have been successfully applied for this purpose (e.g., Armitage, 2005; Chatzisarantis & Hagger, 2005; Chatzisarantis, Hagger, Biddle, & Smith, 2005; Courneya & Bobick, 2000; Courneya & McAuley, 1995; Courneya, Plotnikoff, Hotz, & Birket, 2000; Godin, Valois, & Lepage, 1993; Haggar, Chatzisarantis, & Biddle, 2002; Hausenblas, Carron, & Mack, 1997; Jackson, Smith, & Conner, 2003; Johnston, Johnston, Pollard, Kinmonth, & Mant, 2004; Mummery & Wankel, 1999; Norman & Conner, 2005; Palmer, Burwitz, Dyer, & Spray, 2005; Payne, Jones, & Harris, 2002). According to this theory, behavior is driven by intentions, which are founded on attitudes, experienced normative pressure, and perceived control of behavior. However, the TPB, nor other models of health behavior, such as the health belief model (Rosenstock, 1974), social cognitive theory (Bandura, 1986), or the health action process approach (Schwarzer, 2001), take explicitly into account that we repeat most of our behaviors. It is particularly the cumulative effects of repetition, which can make a behavior detrimental (e.g., eating fatty food) or beneficial (e.g., exercising) to health. This realization, together with the lack of attention to repetition in current models of health behavior, provides a strong argument for focusing on the repetitive nature of exercising. Repetition of behavior is not only important in its own right, such as when it has cumulative effects on health, but also forms the basis of habits. A habit is a form of automaticity in responding, which develops as a person repeats a particular behavior in stable circumstances (Aarts & Dijksterhuis, 2000; Betsch, Haberstroh, & Hohle, 2002; Ouellette & Wood, 1998; Triandis, 1980; Verplanken, 2006; Verplanken & Aarts, 1999; Verplanken & Orbell, 2003; Wood, Quinn, & Kashy, 2002; Wood, Tam, & Guerrero Wit, 2005). Whereas new or infrequent behavior requires mental effort and conscious thinking, this is less so when a behavior is repeated. Frequently repeated behavior may be initiated and/or executed efficiently (in the sense of not requiring many mental resources) and may thus be experienced as smooth, natural, or part of the flow of events. As behavior becomes habitual, it gradually comes under the control of the environment, and, while remaining functional and goal dependent (e.g., Aarts & Dijksterhuis, 2000), it may be less guided by conscious attitudes and intentions (Ji Song & Wood, 2005; Ouellette & Wood, 1998; Verplanken, Aarts, van Knippenberg, & Moonen, 1998). For a long time, habit has been equated with frequency of behavior. Most reports on habit in the literature are based on measures of self-reported frequency of past behavior (Ouellette & Wood, 1998). However, there are good reasons to argue against this conceptualization of habit (Ajzen, 2002; Ajzen & Fishbein, 2005; Verplanken, 2006). First and foremost, a high frequency of

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behavior does not necessarily imply the existence of a strong habit. An athlete may have run a marathon frequently, but this can hardly be qualified as a habit. Habit may also vary independently from behavioral frequency. For example, Verplanken (2006, Study 3) manipulated the ease with which a particular word processing task was executed, while keeping frequency of behavior constant, and later found differences on a self-report habit measure. What, then, is habit, aside from a history of behavioral repetition? Most scholars who defined habit added some reference to automaticity to the behavioral frequency element (e.g., Aarts & Dijksterhuis, 2000; Triandis, 1980; Verplanken & Aarts, 1999). Others stressed situational constancy (e.g., Wood et al., 2002). One may thus consider a habit as repeated behavior that has gained a degree of automaticity, and is executed in stable contexts. Bargh (1989) distinguished between three classes of automatic processes, i.e., preconscious, postconscious and goaldependent. Habits such as exercising fall in the latter category (e.g., Aarts & Dijksterhuis, 2000; Bargh, 1990; Bargh & Gollwitzer, 1994). While habits are functional and goal-directed (e.g., feeling fit), repeating this behavior in particular contexts (e.g., jogging after work) may result in automatic associations between situational cues, the goal which the behavior serves, and the actions undertaken to achieve this. For instance, Sheeran et al. (2005) demonstrated that for those with a strong habit of drinking alcohol, activating the habit-related goal of socializing automatically increased the likelihood of drinking-related behaviors. ‘Automaticity’ may include a number of different qualities. Bargh (1994) suggested low awareness, mental efficiency, difficulty to control, and lack of a conscious intention as ‘‘the four horsemen of automaticity.’’ In this perspective, rather than viewing automaticity as a switch that is on or off, it may be broken down into these four switches, each of which may be on or off, and which thus describe variants of automaticity. Depending on the behavior under study, habitual behavior may be characterized by levels of these four elements. Defining habit as a form of automaticity, rather than as merely frequent behavior, thus provides more explanatory value in that it tells more about the way behavior is executed. An important caveat is that some automatic processes, among which many habits, may be subject to metacognitive reflection (e.g., Petty, Brin˜ol, Tormala, & Wegener, in press; Verplanken, 2006; Verplanken & Orbell, 2003). ‘‘The four horsemen of automaticity’’ provide dimensions along which such reflection might occur. Thus, a habitual car user may realize that he chooses to take the car without making a conscious decision; a habitual snacker may notice the difficulty to control her behavior. We will return to this issue when discussing the measurement of habit, as we propose a meta-cognitive instrument that is based on the assumption that people are able to reflect on these features of automaticity. Another issue concerning the conceptualization of habit, one that is mostly ignored in discussions on this issue, is the level of analysis. In other words, what exactly is considered when we label a behavior as habitual? For example, a person who daily runs for exercise may execute this activity consciously and deliberately. Even if she takes the same track at the same time every day, the activity itself can hardly be considered as an automatic act (Maddux, 1997). What can become automatic, and may thus be considered as habitual, is the decision to go running. When this person first decides to take up running, she might go through a phase in which running has to be carefully planned and incorporated into existing routines. During this phase the decision to go running is likely to be taken consciously

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and deliberately. Once the running has been satisfactorily established as part of the everyday routines, the decision to go running may gain the qualities that make it a habit; it is taken repeatedly, and characterized by a lack of awareness, mental efficiency, and perhaps even some difficulty to control. The measurement of habit The relationship between behavioral frequency and habit, and habit effects in general, cannot be properly investigated without an independent measure of habit (Ajzen & Fishbein, 2005). Verplanken and Orbell (2003) presented the Self-Report Habit Index (SRHI) for this purpose. The SRHI is a generic 12-item self-report instrument, which taps characteristics of habitual behavior, i.e., the experience of a history of repetition, lack of awareness, difficulty to control, mental efficiency, and a sense of self-description. The measure is reliable and shows content, discriminant, and predictive validity for a variety of habits, including healthy food consumption (Brug, de Vet, Wind, de Nooijer, & Verplanken, 2006; Honkanen, Olsen, & Verplanken, 2005), unhealthy snacking (Verplanken, 2006; Verplanken, Herabadi, Perry, & Silvera, 2005), social chatting (Verplanken, 2004), transportation mode choice (Verplanken, Myrbakk, & Rudi, 2005), leisure activities (Verplanken & Orbell, 2003), as well as ‘‘mental habits’’, such as negative selfthinking (Verplanken, Friborg, Wang, Trafimow, & Woolf, 2007). The availability of the SRHI provides opportunities to test hypotheses that could not be tested by using frequency of past behavior as a measure of habit, in particular hypotheses that involve a distinction between behavioral frequency and habit. Why exercising habit is important to study It goes without saying that frequent exercising has a positive health impact. Frequency of exercising is highly dependent on many factors, such as the type of activity, personal preferences, and physical and social limitations. Given these factors, rather than considering ‘the more the better’, a person may find a particular optimal exercising frequency. This frequency then may form the basis of an exercise habit. If we are interested in understanding the mechanisms behind regular exercise behavior, it is therefore not frequency of exercising per se that is interesting, but rather, the degree to which the decision to exercise has become a habit. By definition, habit is a stable and persistent type of behavior, and it is exactly this quality that makes habit an important object to study. The present study aims to contribute to the extant literature on exercising by theoretically and empirically distinguishing exercising habit from exercising frequency. While the SRHI has been used in a number of behavioral domains, to date no study has been reported that applied this (or any alternative) measure of habit to exercising. This is the more important, since it has been argued that the habit concept is not compatible with behaviors such as exercising (e.g., Ajzen, 2002; Maddux, 1997). The study thus addresses two main questions. The first is whether exercise habit can be reliably measured as a stable construct. We provide two indicators of reliability, i.e., internal consistency of the SRHI when applied to exercising, and test-retest reliability. Whereas good internal reliabilities of the SRHI have been reported for other behaviors (e.g., Verplanken & Orbell, 2003), a demonstration of test-retest reliability over a substantial

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period of time is not available. The second question is whether exercise habit can be empirically distinguished from exercise frequency. Providing evidence of the discriminant validity of habit versus frequency in the exercising domain is important, because it is the habitual component of exercising, and not exercising frequency per se, which may contribute to a healthy life style. In order to provide an adequate test of the relationship between behavioral frequency and habit, these variables are controlled for important other variables. Most notable are behavioral intentions and perceived behavioral control, which have been established as primary antecedents of exercising (e.g., Hagger, Chatzisarantis, & Biddle, 2002; Hausenblas et al., 1997; see also Maddux, 1993). As intention and perceived control can be expected to correlate with habit (i.e., establishing a habit can be assumed to imply positive intentions and perceptions of control), these variables were thus included in the analyses in order to control for confounding effects of these variables with respect to behavioral frequency and habit. A sample of university students were approached twice with a 1-month interval, and responded to a questionnaire about their exercising intentions, perceived behavioral control, the frequency of exercising behavior during the previous month, and habit. Whereas in most studies behavioral frequency is the criterion, in the present study, based on the argumentation provided above, we designated habit as the dependent variable of interest. Two hypotheses were formulated. The first hypothesis is that the SRHI of exercising has sufficient internal reliability and shows a significant test-retest reliability. The second hypothesis is that indicators of habit strength and past frequency of behavior measured in the first wave, as well as behavioral frequency between the first and second wave, account independently for variance in habit strength in the second wave, controlling for possible confounding effects of behavioral intentions and perceived behavioral control. Method Participants and design Participants were recruited among undergraduate students at three universities in Norway. The study consisted of two questionnaires, which were provided through the Internet with a 1-month interval. The two measurements will be referred to as T1 and T2. Participants were recruited at the university campus, and were asked to log into a website to respond to a questionnaire about exercising.1 One hundred and ninety-three participants students responded at T1. Participants were asked to provide a unique code that was meant to identify them at T2. One hundred and forty-five participants responded at T2. From this sample, 34 participants could not be matched to their T1 questionnaire or did not fully complete the questionnaire, leaving 111 usable participants. There were 43 men and 68 women. 1

Although Internet-based studies may raise some concerns, such as potential multiple submissions, lack of control during responding, or dishonest behavior, these tend to be not as problematic as previously considered (e.g., Reips, 2006). Inspection of the data and response patterns did not raise any suspicion of sloppy responding. We excluded participants who could not be positively identified to be the same person in both waves.

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Table 1 Means, standard deviations, and correlations of the variables included the study at T1 and T2 Variable and range

M

SD

2

3

4

5

6

1. 2. 3. 4. 5. 6.

6.47 4.98 2.49 4.24 2.30 4.26

0.69 1.02 0.83 1.29 0.99 1.24

0.41***

0.42*** 0.29**

0.47*** 0.34*** 0.77***

0.45*** 0.30** 0.69*** 0.51***

0.46*** 0.37*** 0.76*** 0.87*** 0.63***

T1-behavioral intention (1–7) T1-perceived behavioral control (1–7) T1-past behavioral frequency (0–4) T1-habit (1–7) T2-past behavioral frequency (0–4) T2-habit (1–7)

Note: ** ¼ po0.01; *** ¼ po0.001.

Questionnaires At T1, participants were first given a description of exercising, i.e., physical activity for at least half an hour, which leads to a noticeable higher pulse rate or physical tiredness. The constructs that were relevant for the present purposes were past exercising frequency, behavioral intention, perceived behavioral control, and habit. Past exercising frequency. At T1 participants were presented with four items, asking to indicate how often they had exercised during the last week, month, half year, and year, respectively. This was indicated on 5-point scales with response labels ‘‘never’’ (0), ‘‘every now and then’’ (1), ‘‘weekly’’ (2), ‘‘several times a week’’ (3), and ‘‘almost every day’’ (4). The four items formed a reliable scale, coefficient a ¼ 0.80, and were averaged. Habit was measured both at T1 and T2 by using the SRHI (Verplanken & Orbell, 2003). Participants responded to the stem ‘‘Exercising is somethingy,’’ which was followed by the 12 items of the scale. Three sample items are ‘‘yI do automatic,’’ ‘‘yI have no need to think about doing,’’ and ‘‘yI have been doing for a long time.’’ Responses were given on 7-point scales, which were anchored by ‘‘disagree completely’’ (1) to ‘‘agree completely’’ (7). High scores indicate a strong habit. The items showed high internal consistency on both occasions, coefficient a ¼ 0.93 and 0.92 at T1 and T2, respectively. Behavioral intention to exercise was measured at T1. Participants were first asked how many times a week they would like to exercise during the coming month. This number (x) was used in three items: ‘‘I intend to exercise x times per week during the coming month,’’ ‘‘I will try to exercise x times per week during the coming month,’’ and ‘‘I am motivated to exercise x times per week during the coming month.’’ Responses were given on 7-point scales, which were anchored by ‘‘disagree completely’’ (1) to ‘‘agree completely’’ (7). High scores indicate a strong intention. The items showed satisfactory internal consistency, coefficient a ¼ 0.80.2 Perceived behavioral control was measured at T1 by eight items. The items addressed aspects of perceived control as well as perceived difficulty (Trafimow, Sheeran, Conner, & Finlay, 2002). Three sample items were ‘‘It is difficult to execute the exercise activities that I planned,’’ ‘‘It is easy 2

Although a single-item measure of intention is common and has been found valid in the exercise domain (Chatzisarantis et al., 2005; Courneya & McAuley, 1995; Courneya et al., 2000), we added the other two intention items in order to provide a more reliable measure, which thus proved satisfactory.

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Table 2 A hierarchical multiple regression analysis predicting habit at T2 Predictors at each step

B

SE B

b

R2

R2-change

Final b

Step 1: T1-behavioral intention (1–7) T1-perceived behavioral control (1–7)

0.66 0.27

0.17 0.11

0.37*** 0.22*

0.25

0.25***

0.02 0.06

Step 2: T1-past behavioral frequency (0–4)a

1.00

0.10

0.67***

0.61

0.36***

0.05

Step 3: T1-Habit (1–7)

0.66

0.07

0.68***

0.78

0.17***

0.71***

Step 4: T2-past behavioral frequency (0–4)b

0.28

0.08

0.22***

0.81

0.02***

0.22***

Note: * ¼ po0.05; *** ¼ po0.001. The dependent measure is T2-habit. R2 ¼ 0.81. a Composite measure (i.e., past exercising frequency of previous week, month, half year, year). b Past exercising frequency of previous month.

for me to exercise x times per week during the coming month,’’ and ‘‘I am sure I will be able to exercise x times per week during the coming month.’’ Responses were given on seven-point scales, which were anchored by ‘‘disagree completely’’ (1) to ‘‘agree completely’’ (7). High scores indicate a high level of perceived control. The items showed satisfactory internal consistency, coefficient a ¼ 0.82.

Results In Table 1 means, standard deviations, and correlations are presented. As can be seen, the SRHI showed high test–retest reliability (r ¼ 0.87). Given that the habit scales also showed high internal reliability, these results provide support for the first hypothesis that habit can be reliably measured as a stable construct. In order to address the second research question, a hierarchical multiple regression was conducted. Habit at T2 was regressed on behavioral intention and perceived behavioral control at T1 (step 1), past exercising frequency at T1, which consisted of the composite measure (step 2), habit at T1 (step 3), and past exercising frequency at T2 (step 4). Note that including the latter variable tested the independent effect of exercising frequency during the preceding month. The results are presented in Table 2. The variance inflation factors varied from 1.25 to 3.43, indicating that there were no multicollinearity problems. As can be seen, both habit at T1 and past exercising frequency at T2 obtained significant regression weights on step 4. This suggests that habit at T2 is independently predicted by existing habit at T1 (reflecting the stability of the habit construct), and the frequency of exercising between the two measurements. Whereas behavioral intention and perceived behavioral control correlated significantly with habit at T2, these variables did not obtain significant regression weights. This suggests that while intention and perceived control were both significant predictors of habit

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at T2 (see Table 1), their impact was statistically mediated by T1 habit and frequency of exercising between T1 and T2.3

Discussion The present study demonstrated two things. The first was that exercising habit can be reliably measured. This was shown by high internal reliabilities and, importantly, a high test–retest reliability. Secondly, the regression analysis suggested that habit can empirically be distinguished from mere exercising frequency. This effect was controlled for the potentially confounding effects of behavioral intention and perceived behavioral control. This result is important because it demonstrates that habit should not be equated with mere behavioral frequency. Although repetition of behavior is a necessary condition for habits to develop, and frequency of past behavior thus correlates with habit strength, the defining feature of a habit is (goal-dependent) automaticity. The results of this study thus suggest that habit is a potentially useful construct in addition to the set of variables that have been found important antecedents of exercising behavior, most notably the variables contained in the theory of planned behavior (e.g., Hausenblas et al., 1997). Habit thus contributes as the automatic component which is strengthened when exercising becomes a routine and is incorporated as a repeated activity in everyday life. Taking habit into account seems particularly important when studying temporal effects, such as stability or change in exercise behavior (e.g., Chatzisarantis et al., 2005; Courneya & Bobick, 2000), adherence to exercising or training (Anton et al., 2005; Armitage, 2005; Courneya & McAuley, 1995; Garcia & King, 1991; Mummery & Wankel, 1999), or effects of interventions (e.g., Chatzisarantis & Hagger, 2005). In such temporal contexts, changes in habit strength provide important information about the way exercising is performed over time, independently of the frequency of performance. Whereas the SRHI has been used and validated in other domains (e.g., Verplanken, 2006; Verplanken & Orbell, 2003), the present study demonstrated that it is a reliable measure in the context of exercising behavior, and provided evidence of the discriminant validity with respect to past frequency of exercising. A limitation must be noted here. Although the type of measures of self-reported behavioral frequency (the composite measure at T1 and the single-item measure at T2) are not uncommon in attitude-behavior studies, they do not have the sophistication of behavioral measures that are often used in the domain of physical activity, such as the Seven-Day Physical Activity Recall measure (Blair, 1984) or the Leisure-Time Exercise Questionnaire (Godin & Shephard, 1985). A study that would replicate the present findings with a better measure of behavior would therefore be welcome. 3

Because the SRHI includes some items on the experience of behavioral repetition (based on the idea that frequency is part of the habit concept), it might be argued that an assessment of habit with this scale is inadequate if it is used to test independent effects of frequency. Although the inclusion of the frequency-related items in the SRHI would work against our hypothesis (i.e., it would be more ‘difficult’ to obtain an independent effect of past behavioral frequency), the analyses were repeated using the SRHI without the three frequency-related items. The results were practically identical. Again, a large test–retest reliability of the SRHI was obtained, r ¼ 0.84, po0.001, as well as satisfactory internal consistencies, as ¼ 0.90 and 0.89 at T1 and T2, respectively. Importantly, past behavioral frequency measured at T2 again obtained a significant b weight, b ¼ 0.19, po0.006.

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Perhaps as a heritage from the behaviorist tradition, most social scientists nowadays equate past behavioral frequency and habit. This is not only unfortunate for conceptual reasons. The habit construct we propose is richer than behavioral frequency in that it encompasses information about how behavior is executed. We believe that both pieces of information—frequency and habit—are important for understanding physical exercise behavior. For instance, frequency information is important when norms for physical exercise are considered. In particular if there are certain thresholds for obtaining measurable positive health effects, it is important to work with frequency information, e.g., in communicating desired exercising frequency levels to the general public. Habit is especially important when considering how exercise behavior is or can be implemented in people’s lives. For example, although a health campaign promoting physical exercise may result in higher exercise frequencies, behavioral changes often do not last. One reason might be that the decision to exercise is not automated, and is thus not embedded as part of one’s everyday activities. Habit is therefore an important construct when it comes adherence to behavior and relapse prevention (cf., Biddle & Nigg, 2002). Distinguishing between behavioral frequency, representing the ‘density’ of behavior, and habit, representing how behavior is executed, may thus have implications for interventions aimed at changing behavior, such as engaging more people in physical exercising (e.g., Chatzisarantis & Hagger, 2005). We may consider two sides of the habit coin. One is that if old, undesired, behavior (e.g., sedentary behavior) is habitual, this may be hard to change. Habits have been found associated with a ‘tunnel vision’, i.e., a lack of interest for new information (e.g., Verplanken, Aarts, & van Knippenberg, 1997), and information use that is biased toward maintaining the existing habit (e.g., Betsch, Haberstroh, Glo¨ckner, Haar, & Fiedler, 2001). In addition, habits have been found associated with attenuated relations between intentions and behavior (e.g., Ji Song & Wood, 2005; Ouellette & Wood, 1998; Verplanken et al., 1998). Given these consequences of habituation, the presence of a habit poses a contraindication to the use of informational campaigns that aim at changing attitudes and intentions, and thus behavior, through providing information about pros and cons of the desired new behavior. Only when an existing habits are broken (e.g., because a person moves to another place), may information-based intervention expected to have some effects (Verplanken & Wood, 2006). The other side of the habit coin is that the very characteristics that make habits form barriers to change (e.g., its automatic qualities), are exactly the characteristics that are very much wanted when new, desired, behavior has been established. Interventions to promote sport and exercise activities may thus explicitly adopt habituation as intervention goal. Verplanken and Wood (2006) argued that in order to accomplish this, structural changes are often needed, which change or form an environment in which habits are encouraged and supported. For instance, when organizations create time and space for employees to work out, exercising at work may turn into a healthy habit. In this example, whereas motivation (i.e., intention) is a necessary condition to get such behavior started, the ease with which such behavior is executed is highly dependent on structural characteristics of the environment. Habit is not an easy concept. It has been argued that habit has no relevance for the behaviors that are of interest to exercise and sport psychologists (Maddux, 1997). Many of these behaviors involve conscious and deliberate enjoyment of physical activity, which is at odds with the habit concept. Insofar this argument is used with respect to the execution of activities such as exercising, we fully agree. The pleasure of exercising and sporting very much consists of the mindful

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experience of these activities, which differs from the typical mindless states we associate with habits. However, our focus of attention and the application of the habit concept is on the decision to exercise. It seems to us that the success of establishing regular exercising lies in the way these activities are built into a person’s everyday life. If one has to think and deliberate whether or not to exercise, one is vulnerable to the many ad-hoc rationalizations, hassles, and moods that may lead to a decision not to exercise that day or that week. We thus would argue that the habit concept is particularly relevant for the initiation of and adherence to exercising. A strong habit to exercise, in our view, thus implies the fact that regular exercising is self-evident, does not require thought or deliberation to initiate, and is incorporated as part of a person’s daily or weekly activities. The activity of exercising itself, then, is hopefully executed with full awareness and enjoyment, perhaps under conditions of flow (e.g., Nakamura & Csikszentmihalyi, 2002), which may thus contribute to health, subjective well-being, and happiness.

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