Health Psychology 2014, Vol. 33, No. 11, 1298 –1308

© 2014 American Psychological Association 0278-6133/14/$12.00 http://dx.doi.org/10.1037/hea0000085

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Sources of Self-Efficacy for Physical Activity Lisa M. Warner

Benjamin Schüz

Freie Universität Berlin and German Centre of Gerontology

University of Tasmania

Julia K. Wolff

Linda Parschau

German Centre of Gerontology

Freie Universität Berlin

Susanne Wurm

Ralf Schwarzer

German Centre of Gerontology and Friedrich-Alexander University Erlangen-Nuremberg

Australian Catholic University and Freie Universität Berlin

Objective: The effects of self-efficacy beliefs on physical activity are well documented, but much less is known about the origins of self-efficacy beliefs. This article proposes scales to assess the sources of self-efficacy for physical activity aims and to comparatively test their predictive power for physical activity via self-efficacy over time to detect the principal sources of self-efficacy beliefs for physical activity. Method: A study of 1,406 German adults aged 16 –90 years was conducted to construct scales to assess the sources of self-efficacy for physical activity (Study 1). In Study 2, the scales’ predictive validity for self-efficacy and physical activity was tested in a sample of 310 older German adults. Results: Short, reliable and valid instruments to measure six sources of self-efficacy for physical activity were developed that enable researchers to comparatively test the predictive value of the sources of self-efficacy. Conclusion: The results suggest that mastery experience, self-persuasion, and reduction in negative affective states are the most important predictors of self-efficacy for physical activity in community-dwelling older adults. Keywords: mastery experience, vicarious experience, verbal persuasion, self-persuasion, affective states

example, around 80% of German adults over the age of 60 years exercise less than the recommended 2.5 hours per week (Krug et al., 2013). Thus, research on individual factors that enable older adults to engage in physical activity is crucial. Beliefs in having the capacity necessary to accomplish a desired goal—self-efficacy beliefs—make people tackle new and challenging tasks (i.e., initiating physical activity), invest effort, and persist in the face of barriers (Bandura, 1997). Moreover, self-efficacy beliefs for health behaviors can be conceptualized as being task-, maintenance-, or recovery-specific, meaning that people can have different levels of self-efficacy in different phases of health-behavior change (Schwarzer, 2008). Once initial successes are experienced, selfefficacy beliefs increase and help to maintain and resume health behaviors, even in the face of challenges. Therefore, self-efficacy beliefs rank among the strongest predictors for initiating and maintaining physical activity (van Stralen, De Vries, Mudde, Bolman, & Lechner, 2009). Even though there are numerous studies on the effects of self-efficacy beliefs on behavior, much less is known about the sources and determinants of self-efficacy. However, to successfully target self-efficacy beliefs in physical activity interventions, systematic research of the sources on which individuals base their self-efficacy beliefs is needed. We, therefore, proposed a new measure to assess the sources of self-efficacy which allows us to examine the impact of differential sources of self-efficacy on self-efficacy and physical activity, here.

Even though physical inactivity ranks among the key modifiable behavioral risk factors in industrialized countries, because it increases the likelihood of cardiovascular diseases, Type-2 diabetes, and certain cancers, self-directed changes in physical activity and maintaining these changes are insurmountable challenges to many people (Lim et al., 2012). Being physically active on a regular basis appears to be increasingly difficult when people age; for

This article was published Online First April 7, 2014. Lisa M. Warner, Department of Psychology, Freie Universität Berlin and German Centre of Gerontology, Berlin, Germany; Benjamin Schüz, University of Tasmania, Hobart, TAS, Australia; Julia K. Wolff, German Centre of Gerontology, Berlin, Germany; Linda Parschau, Department of Psychology, Freie Universität Berlin, Germany; Susanne Wurm, German Centre of Gerontology, Berlin, Germany and Institute of Psychogerontology, Friedrich-Alexander University Erlangen-Nuremberg, Germany; Ralf Schwarzer, Institute for Positive Psychology and Education, Australian Catholic University, Sydney, NSW, Australia and Department of Psychology, Freie Universität Berlin, Germany. We thank the TV show Quarks and Co, which made the recruitment for Study 1 possible. Study 2 was funded by the German Federal Ministry of Education and Research Grant 01ET1001B and supported by the German Centre of Gerontology and a team of highly motivated student assistants. Correspondence concerning this article should be addressed to Lisa M. Warner, Freie Universität Berlin, Gesundheitspsychologie, Habelschwerdter Allee 45, 14195 Berlin, Germany. E-mail: [email protected] 1298

SOURCES OF SELF-EFFICACY

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The Sources of Self-Efficacy Social– cognitive theory (Bandura, 1997) proposes four main sources for the development of self-efficacy beliefs. First, mastery experience represents experiences from when a person has been successful in accomplishing a task in the past, and thus constitutes an authentic indicator of one’s ability to accomplish similar tasks in the future. Mastery experience is, therefore, often considered the strongest source of self-efficacy beliefs (Bandura, 1997), and prompting mastery experience in interventions has been found to be an effective way to increase self-efficacy beliefs for physical activity (Ashford, Edmunds, & French, 2010). Second, vicarious experience describes the act of observing other people who successfully perform a difficult task. This observation is assumed to increase individual self-efficacy beliefs via social modeling processes (Bandura, 1997). Previous qualitative research has accordingly revealed that older adults consider the absence of vicarious experience (or role models) to be barriers to regular physical activity (Allender, Cowburn, & Foster, 2006). Similarly, experimental studies have found that self-efficacy for physical activity can be improved by vicarious experience (Ashford et al., 2010). Third, verbal persuasion entails trying to convince someone of his or her abilities to successfully perform a task (e.g., in a pep talk). According to Bandura (1997), this process can be a source of self-efficacy, but it is assumed that its effects are far less substantial than those of mastery experience or vicarious experience. Miller, Lane, Deatrick, Young, and Potts, 2007 suggested that attempts to persuade others of their abilities might even be interpreted as control or pressure. Accordingly, research has found verbal persuasion to be unrelated or even negatively related to physical activity (Stephens et al., 2012) and self-efficacy (Ashford et al., 2010), or only effective if combined with mastery experience (Wise & Trunnell, 2001). This source of self-efficacy can be differentiated into the subsources persuasion by others and positive self-talk or self-persuasion, which has been found to be a reliable source of self-efficacy in various exercise domains (e.g., Chase, Magyar, & Drake, 2005; Hatzigeorgiadis, Zourbanos, Goltsios, & Theodorakis, 2008). Physiological and affective states are considered to be the fourth main source of self-efficacy (Bandura, 1997). They are based upon appraisal processes; for example, if negative affect such as agitation immediately before a difficult task is interpreted as unpreparedness or vulnerability, self-efficacy and performance might be impaired (Conger & Kanungo, 1988). According to Bandura (1997), this goes beyond mere physiological arousal, and people consider their overall physiological state such as feeling exhausted, ill, or injured when considering their confidence in being able to accomplish a task (Bandura, 1997; O’Brien Cousins, 1997). Positive affect might influence self-efficacy if interpreted as sign of readiness and confidence in one’s own capabilities. As such, positive affect prior to a task is thought to activate memories of previous successes and thus fosters self-efficacy beliefs (Bandura, 1997). Even though Bandura (1997) suggested that mastery experience is the most powerful source of self-efficacy beliefs, there are no assumptions about the relative importance of other sources of self-efficacy. As yet, we are aware of only one study that attempted to measure all proposed sources of self-efficacy for phys-

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ical activity concurrently and to test their comparative associations with physical activity self-efficacy beliefs (Warner, Schüz, Knittle, Ziegelmann, & Wurm, 2011). In this study, mastery experience, vicarious experience, and somatic states had significant direct effects on self-efficacy and significant indirect effects on physical activity via self-efficacy. However, this study measured the sources of self-efficacy using proxy measures, which may have limited the reliability and validity of the findings.

Why Is it Important to Measure the Sources of Self-Efficacy for Physical Activity? Scales for the assessment of self-efficacy sources for physical activity would enable researchers to comparatively test the predictive power of each source to detect which is the most powerful. This would allow targeting the most important sources in more parsimonious and potentially more effective behavioral interventions. Reliable and valid measurement of the sources of selfefficacy would further allow investigating the mechanisms of such interventions and conducting conclusive process evaluations. This would enable manipulation checks and examination of the effective ingredients in health-behavior change interventions by analyzing indirect effects of change in self-efficacy sources on behavior via increases in self-efficacy (Michie & Abraham, 2004).

Aims of the Current Studies In our first step, we aimed at developing parsimonious, reliable, and valid scales to assess the sources of self-efficacy for physical activity. In our second step, the scales’ direct and indirect associations with physical activity via self-efficacy beliefs were tested over time. The purpose of Study 1was to select items for the assessment of the sources of self-efficacy for physical activity from an initial item pool and test their factorial structure, internal consistency, and convergent validity in an online sample with a broad age range. Study 2 was conducted to examine the test–retest reliability, measurement invariance, and predictive validity of the new scales, measuring self-efficacy beliefs and physical activity over time in a sample of older adults completing paper–pencil questionnaires.

Hypotheses The initial item pool was constructed to cover the theoryderived sources of mastery experience, vicarious experience, verbal persuasion, self-persuasion, and affective states (negative and positive). Thus, these sources were expected to form separate factors in the final instrument. Considering Bandura’s (1997) postulations and previous empirical findings, mastery experience was expected to emerge as the strongest source of self-efficacy for physical activity, whereas verbal persuasion by others was expected to be the weakest, or even negatively associated with self-efficacy for physical activity (Ashford et al., 2010). Because older adults, especially, consider the lack of role models as a barrier for physical activity, and role models have been shown to be effective in experimental studies, vicarious experience was expected to emerge as a strong source of physical activity self-efficacy in older adults (Ashford et al., 2010). It has been claimed that “physiological indicators of efficacy play

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an especially influential role in . . . activities requiring physical strength” (Bandura, 1997, p. 106), therefore we expected negative affective states to be relevant for physical activity self-efficacy, as well.

Study 1

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Participants and Procedure Participants were recruited through a documentary on a German science TV show about New Year’s resolutions, broadcast on January 10th and 14th, 2012. The link to test physical activityspecific self-efficacy was placed on the show’s website leading to an online questionnaire. The online survey attracted 1,406 individuals who gave informed consent to participate and thereby entered a raffle for 10 €50 media vouchers. The sample consisted of 65% women and had a mean age of 40.32 years (SD ⫽ 12.95, range ⫽ 16 –90 years). The majority reported living with a partner (66%) and graduated from senior high school (80%).

Measures The item pool was developed to cover the six theory-derived sources of physical activity self-efficacy, namely mastery experience, vicarious experience, verbal persuasion by others, selfpersuasion, and positive and negative affective states. The initial item pool consisting of 95 items was developed on the basis of Bandura’s (1997) work, qualitative studies investigating the sources of self-efficacy for physical activity (Chase, Feltz, & Lirgg, 2003; Feltz & Riessinger, 1990), scales to assess feelings induced by physical activity (Gauvin & Rejeski, 1993; McAuley & Courneya, 1994), and scales to assess the sources of self-efficacy in other domains (e.g., sources of mathematic or science selfefficacy; Britner, 2008; Lopez & Lent, 1992; Usher & Pajares, 2006). Five experts selected those items that represented the sources of physical activity self-efficacy best. This evaluation resulted in a preselection of 43 items, which were empirically tested in Study 1. The response format was from 1 (strongly disagree) to 4 (strongly agree). Self-efficacy for physical activity was assessed with nine items (Scholz, Sniehotta, & Schwarzer, 2005). Items include (a) “I am confident that I can exercise on a regular basis even if this is difficult for me.” (task self-efficacy), (b) “I am confident that I can be physically active on a long-term basis even though I might encounter difficult situations.” (maintenance self-efficacy), (c) “I am confident that I can resume a physically active lifestyle even if I have relapsed several times” (recovery self-efficacy; all items translated from German). Because Scholz et al. (2005) conceptualized the initiation, maintenance, and recovery of regular physical activity as difficult tasks per se, additional specifications of exact barriers were not necessarily needed to assess self-efficacy for physical activity. In addition, barriers were individual- and taskspecific, thus, an a priori definition of barriers could have posed an overly simplistic one-size-fits-all approach. In the questionnaire, self-efficacy was assessed before the Sources of Self-Efficacy Scales to ensure that reflections about people’s sources of self-efficacy would not bias self-efficacy ratings. Responses ranged from 1 (strongly disagree) to 4 (strongly agree). For manifest analyses, the item scores were averaged to

create one self-efficacy score. For latent analyses, the items were parceled according to their corresponding facet of self-efficacy (two task self-efficacy items, four maintenance self-efficacy items, and three recovery self-efficacy items in one parcel, respectively). We used the German short version of the Support for Exercise Habits Scale to measure received social support for physical activity (Fuchs, 1997; Sallis, Grossman, Pinski, Patterson, & Nader, 1987). Participants rated the frequency with which they received support for physical activity from their network on a 5-point scale from (almost) never to (almost) always within the past week. The three items had the same stem: “Please think of the past week. What has your social network (e.g., partner, kids, friends) done concerning your physical activity?” “Members of my social network have . . . ” followed by “. . . exercised with me,” “. . . reminded me to be physically active,” and “. . . helped me organize my exercise.” To analyze discriminant validity, intentions and outcome expectancies for physical activity were assessed on a 4-point Likert scale, ranging from (1) strongly disagree to (4) strongly agree (Schwarzer, Lippke, & Luszczynska, 2011): Behavioral intentions were assessed using the statement “I strongly intend to . . .” followed by five items: (a) “. . . be physically active several days a week,” (b) “. . . be physically active regularly,” (c) “. . . exercise (e.g., endurance sports and strength training),” (d) “. . . be physically active in my leisure time” and (e) “. . . be physically active performing daily chores (such as strenuous work in household and garden)”. Negative and positive outcome expectancies were assessed with two items each. The item stem “If I am physically active on a regular basis . . .” was followed by (a) “. . . then I have to invest a lot of effort” and (b) “. . . then I do not have enough time left for other activities” (negative) and (a) “. . . then I contribute something to my good health” and (b) “. . . then I spend time with nice people” (positive). For the positive outcome-expectancy items, Cronbach’s alpha was only .08, therefore they were analyzed separately. Table 1 shows Cronbach’s alphas, means, standard deviations and ranges for all measures.

Analytic Procedure Random halves of the sample were generated (n ⫽ 703 for each subsample). Data from the first half (Subsample A) were analyzed to reduce the item pool. Item reduction was based on the following criteria: A principal axis analysis with interrelated factors (oblimin rotation, delta set to 0) was performed over all 43 items in SPSS 20. Items were excluded if their loadings on the assumed factors in the pattern matrix was below .40, if they built separate factors, or cross-loaded higher than .30 on other factors. Items that correlated below .30 with self-efficacy for physical activity were also removed. The second half of the data (Subsample B) was used (a) to conduct a confirmatory factor analysis (CFA) in Mplus 6 on the items that were selected in Subsample A, (b) to calculate reliabilities and descriptive statistics of the resulting factors in SPSS, (c) to test convergent validity on a manifest and latent level with physical activity self-efficacy in Mplus, and (d) to test discriminant validity in SPSS. Missing values were treated via listwise deletion in SPSS and full information maximum likelihood imputation in Mplus. Goodness of fit for all structural equation models was

⫺.35ⴱⴱⴱ .18ⴱⴱⴱ

.03 .13ⴱⴱ .09

⫺.11ⴱ

⫺.03

⫺.01

ⴱ

.19ⴱⴱ

.54ⴱⴱⴱ .10ⴱ .33ⴱⴱⴱ

.45ⴱⴱⴱ .12ⴱⴱ .48ⴱⴱⴱ

⫺.08 ⬍⫺.01 .12ⴱⴱ

.03 ⫺.08 ⫺.04

.20ⴱⴱⴱ

⬍⫺.01

⫺.40ⴱⴱⴱ

⫺.40ⴱⴱⴱ

⫺.31ⴱⴱⴱ

.12ⴱ

⫺.08

.06 .46ⴱⴱⴱ

.10ⴱ

4

.18ⴱⴱⴱ .60ⴱⴱⴱ

.61ⴱⴱⴱ .14ⴱⴱ

3

.12ⴱⴱ .03

⫺.03 ⫺.09 ⬍⫺.01

2

⫺.19ⴱⴱⴱ .04

.04 .07 ⫺.19ⴱⴱⴱ

⫺.05

1

Note. Results from Study 1, Split Half Sample B. p ⬍ .05. ⴱⴱ p ⬍ .01. ⴱⴱⴱ p ⬍ .001.

1. Age 2. Gender (1 ⫽ men, 2 ⫽ women) 3. Self-efficacy for physical activity 4. Mastery experience 5. Vicarious experience 6. Verbal persuasion by others 7. Self-persuasion 8. Negative affective states 9. Positive affective states 10. Social support 11. Intentions 12. Negative Outcome Expectancies 13. Positive Outcome Expectancies (Health) 14. Positive Outcome Expectancies (People)

Variable

.15ⴱⴱ

.16ⴱⴱ

⫺.06

.25ⴱⴱⴱ .17ⴱⴱⴱ .21ⴱⴱⴱ

⫺.03

.28ⴱⴱⴱ .27ⴱⴱⴱ

5

.21ⴱⴱⴱ

.07

⫺.05

.03 .46ⴱⴱⴱ .17ⴱⴱⴱ

⫺.03

.22ⴱⴱⴱ

6

.09

.20ⴱⴱⴱ

⫺.32ⴱⴱⴱ

.47ⴱⴱⴱ .14ⴱⴱ .38ⴱⴱⴱ

⫺.35ⴱⴱⴱ

7

⫺.14ⴱⴱ

⫺.04

.33ⴱⴱⴱ

⫺.48ⴱⴱⴱ ⫺.10ⴱ ⫺.14ⴱⴱ

8

.21ⴱⴱⴱ

.10ⴱ

⫺.41ⴱⴱⴱ

.15ⴱⴱ .30ⴱⴱⴱ

9

.34ⴱⴱⴱ

.05

⫺.02

.10

ⴱ

10

.04

.26ⴱⴱⴱ

⫺.23ⴱⴱⴱ

11

⫺.16ⴱⴱⴱ

⬍ .01

12

Table 1 Correlations, Cronbach’s Alphas, Means, Standard Deviations, and Ranges for the Sources of Self-Efficacy for Physical Activity Scales

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.06

13

—

—

.65

.89 .66 .70

.83

.86 .81

.90 .84 .73

—

—

␣

2.56

3.81

2.20

2.62 2.06 3.34

1.83

2.22 3.06

3.11 2.72 2.58

—

40.32

M

1.00

0.45

0.74

0.81 0.92 0.55

0.78

0.86 0.74

0.59 0.77 0.76

—

12.95

SD

1.00–4.00

1.00–4.00

1.00–4.00

1.00–4.00 1.00–5.00 1.00–4.00

1.00–4.00

1.00–4.00 1.00–4.00

1.11–4.00 1.00–4.00 1.00–4.00

65% women

16–90

Range

SOURCES OF SELF-EFFICACY

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evaluated using the Comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the standardized root mean residual (SRMR). A satisfactory model fit is indicated by CFI ⬎ .95, RMSEA ⬍ .06, and SRMR ⬍ .08 (Hu & Bentler, 1999).

analysis with oblimin rotation for the selected 18 items. Note that all items in Table 2 were translated from German into English by two bilingual psychologists. The back translation was performed by two bilingual psychologists, who were ignorant of the original version of the items. Discrepancies between the back-translations and originals were used to adjust the wording of individual items.

Results Confirmatory Factor Analysis

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Factor Structure and Item Reduction The principal axis analysis resulted in nine factors, of which six were identified as sources of self-efficacy, whereas the other three factors represented further differentiations of sources (e.g., one factor represented normative beliefs rather than vicarious experience). The initial item pool of 43 items was reduced to 18 items: 10 items were excluded because of cross-loadings or they built separate factors (five mastery experience, three vicarious experience, two negative affective states). Four items were excluded because their loadings on the assumed factor were lower than .40 (three vicarious experience, one verbal persuasion). Seven items were excluded because they had correlations below .30 with selfefficacy for physical activity (four negative affective states, two verbal persuasion, one vicarious experience), leaving 22 items for six sources of self-efficacy, namely three mastery experience, three vicarious experience, three verbal persuasion by others, three self-persuasion, five negative affective states, and five positive affective states. To yield subscales of equal length to avoid differential reliabilities of the subscales as an artifact of scale length, the two lowest-loading items of negative and positive affective states, respectively, were excluded. This reduction process resulted in the hypothesized six subscales: mastery experience, vicarious experience, verbal persuasion by others, self-persuasion, and negative and positive affective states— each containing three items. Table 2 shows the pattern matrix for a second principal axis

To confirm the factorial structure derived from the reduction process in Subsample A, a confirmatory factor analysis was performed on the six-factor model in Subsample B. The six-factor model resulted in a satisfactory fit with ␹2(120) ⫽ 298.96, p ⬍ .001; RMSEA ⫽ 0.06; CFI ⫽ 0.96; SRMR ⫽ 0.05. Figure 1 illustrates the loading of items onto their scales and scales’ interrelations. All items loaded significantly and highly onto the assumed factors. Moderate associations were found between the Positive Affective States and Mastery Experience Scales, the SelfPersuasion and Negative Affective States Scales, and the Mastery Experience and Self-Persuasion Scales. All other associations between scales were negligible.

Reliability Analysis Table 1 shows Cronbach’s alphas, means, standard deviations and ranges derived from Subsample B for each of the six subscales. All sources of self-efficacy for physical activity scales had satisfactory internal consistencies.

Validity Analysis Convergent validity is demonstrated by manifest correlations (see Table 1) and correlations between latent variables (see Figure 2). Each subscale of the sources of self-efficacy for physical

Table 2 Rotated Pattern Matrix for the Selected Sources of Self-Efficacy for Physical Activity Scales Factors Item

SP

VPO

NA

ME

PA

VE

ME1: I have mostly been successful in being physically active on a regular basis. ME2: Even if it turned out challenging at times, I have managed to remain active. ME3: It was never difficult for me to be physically active on a regular basis. VE1: I model myself on people who are more active than I am. VE2: I feel more confident in being physically active if I can model myself on somebody else. VE3: I feel motivated to be active if I see people my age being active. VPO1: Others encourage me to be physically active. VPO2: Whenever I lack motivation to be physically active, others encourage me to be. VPO3: The people who are important to me encourage me to resume physical activities when I have quit doing them. SP1: Whenever I struggle to be motivated for physical activity, I tell myself that I can do it. SP2: I tell myself I can manage to be physically active on a regular basis. SP3: I motivate myself to be physically active on a regular basis. NA1: Just before I start physical activities, I feel worn out NA2: Just before I start physical activities, I feel tired. NA3: Just before I start physical activities, I feel tense. PA1: Just before I start physical activities, I feel energetic. PA2: Just before I start physical activities, I feel thrilled in anticipation. PA3: Just before I start physical activities, I feel strong.

.05 .07 ⫺.08 .07 ⫺.09 .06 ⫺.04 .00

⫺.03 .02 .02 ⫺.01 .04 ⫺.01 .66 .83

.00 ⫺.01 ⫺.05 ⫺.04 .03 .00 .06 ⫺.01

.84 .83 .70 .11 ⫺.11 .03 ⫺.09 .09

⫺.01 .00 .13 ⫺.08 .05 .05 .02 .01

⫺.01 ⫺.04 .02 ⴚ.73 ⴚ.56 ⴚ.69 ⫺.04 .01

.05 .61 .87 .80 .00 ⫺.02 .00 ⫺.03 .09 .06

.82 .12 ⫺.01 ⫺.08 ⫺.01 ⫺.01 .02 .00 .02 ⫺.01

⫺.04 ⫺.03 ⫺.04 .05 .87 .94 .57 ⫺.07 .04 ⫺.01

.01 .07 ⫺.08 .05 .02 .08 ⫺.08 ⫺.06 .13 .06

⫺.02 .01 ⫺.01 .11 ⫺.04 ⫺.06 .04 .79 .73 .84

.01 .00 ⫺.03 .01 .01 .03 ⫺.03 ⫺.01 ⫺.03 .01

Note. Data from Study 1, Split Half Sample A; ME ⫽ mastery experience; NA ⫽ negative affect; PA ⫽ positive affect; SP ⫽ self-persuasion; VPO ⫽ verbal persuasion by others; VE ⫽ vicarious experience.

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Figure 1. Confirmatory factor analysis for the sources of self-efficacy for physical activity scales. Note. Data from Study 1, Split Half Sample B; reported are standardized path coefficients; first factor loading always set to 1; solid lines represent significant paths, dashed lines nonsignificant paths; all indicators load significantly (p ⬍ .001) on their factors; ⴱ p ⬍ .05; ⴱⴱ p ⬍ .01; ⴱⴱⴱ p ⬍ .001.

activity correlated significantly with self-efficacy for physical activity, confirming convergent validity. Discriminant validity was tested against social support for physical activity and behavioral intentions, and negative and positive outcome expectancies. As Table 1 indicates, mastery experience was moderately correlated with negative outcome expectancies, r ⫽ ⫺.40, verbal persuasion by others with social support, r ⫽ .46, and positive affective states with negative outcome expectancies, r ⫽ ⫺.41. All other correlations were below .40. This correlation pattern supports the notion of discriminant validity for the sources of self-efficacy.

Study 2 Participants and Procedure A sample of community-dwelling adults aged 64 and older was recruited for the PREFER project via local newspapers, flyers placed in meeting places for older adults, in pharmacies, at general

practitioners’ offices, and via advertisement letters to members of a German health-insurance company. Ethical consent was obtained from the appropriate ethics commission (German Psychological Society, DGPs-SW 02_2012). In total, 310 participants provided informed consent and completed the baseline (T1) paper–pencil questionnaire. Participants were randomized into one of three groups to compare a psychological group intervention for physical activity motivation with an intervention for volunteering motivation and a wait-list control group (not reported here). All groups received follow-up questionnaires in the mail with prepaid return envelopes 7 weeks and 11 weeks after baseline. The first follow-up (T2) was completed by 283 participants and the second (T3) by 271. For the purpose of this study, longitudinal data from all three groups were analyzed jointly while statistically controlling for group allocation in all analyses. At T1, participants were, on average, 70.3 years of age (SD ⫽ 4.86, range ⫽ 64 – 92 years), and 75.2% were women. The majority graduated from senior high school (53%) and 40% lived together with a partner.

Figure 2. Convergent validity for the sources of self-efficacy for physical activity scales. Note. Data from Study 1, Split Half Sample B; reported are standardized path coefficients; first factor loading always set to 1; correlations between the sources are not displayed for clearer presentation; all indicators load significantly (p ⬍ .001) on their factors and the overall model fit the data well: ␹2(168) ⫽ 368.51, p ⬍ .001, RMSEA ⫽ 0.05, CFI ⫽ 0.96, SRMR ⫽ 0.05; ⴱ p ⬍ .05; ⴱⴱ p ⬍ .01; ⴱⴱⴱ p ⬍ .001.

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Measures The Sources of self-efficacy for physical activity were assessed at T1, T2, and T3 with the final six subscales created in Study 1. The response format was the same as in Study 1, ranging from 1 (strongly disagree) to 4 (strongly agree). Self-efficacy for physical activity was assessed at T2 with six items representing task, maintenance, and recovery self-efficacy (see Study 1; Scholz et al., 2005). Cronbach’s alpha at T2 was .89. Three parcels each containing two items (representing the three facets of self-efficacy) were built to construct the latent factor self-efficacy for physical activity. Physical activity was assessed at T1 and T3 with three different self-report measures. The frequency of moderate and vigorous physical activity was assessed with two items based on the validated Baecke Questionnaire for Habitual Physical Activity (Baecke, Burema, & Frijters, 1982; Pols et al., 1995). The items were (a) “During an average week, how often do you engage in physical activities that make you sweat and breathe hard?” and (b) “In the last four weeks, how often did you engage in physical activities that made you sweat and breathe hard?” Answers were given on a scale from 1 (never) to 5 (always). Exercise frequency has been shown to be related to physical functioning and well-being in older adults (McAuley et al., 2000; Nieuwland et al., 2000). The time frame of one week was chosen to avoid memory biases, which are common in older adults (Rikli, 2000). To assess the intensity and duration of activity, the total Physical activity Index of the validated PRISCUS-PAQ was assessed (Trampisch et al., 2010). In this questionnaire, participants reported the frequency and duration of sitting, resting, cleaning, other household activities, gardening, sports, group exercise, gym exercise, and cycling as means of transportation and walking during the last 7 days. Each rating was transformed into MET minutes (Metabolic Equivalent of Task Minutes; Ainsworth et al., 2000) and summed up, so that the total PRISCUS-PAQ represented each participant’s total activity within the last week in MET minutes. This index has been found to reliably assess physical activity and to be valid as compared with accelerometer data in older German adults (Trampisch et al., 2010, 2012). To increase reliability and reduce bias of physical activity self-reports, physical activity was subsequently operationalized as a latent variable using both Baecke items and the PRISCUS-PAQ index.

model was estimated using the INDIRECT function in Mplus, in which the sources of self-efficacy at T1 predicted change in physical activity from T1 to T3 (by controlling for T1 physical activity) via self-efficacy for physical activity at T2. To account for item-specific variance in the physical activity factor, two method factors were included in the model. To test the magnitude of the indirect effects against one another, a Wald test was performed in Mplus. Model goodness of fit was evaluated with the same criteria as in Study 1. All analyses were controlled for group allocation, gender, and age.

Results Internal Consistency, Retest–Reliability, and Measurement Invariance Cronbach’s alphas for the sources of self-efficacy for physical activity at each of the three points of measurement ranged from .86 –.89 for mastery experience, .83–.86 for vicarious experience, .88 –.93 for self-persuasion, .82–.88 for verbal persuasion by others, .75–.83 for negative affective states, and .87–.92 for positive affective states. The 4-week test–retest reliability (T2–T3) was satisfactory for all six Sources Scales, with .65 (p ⬍ .001) for mastery experience, .66 (p ⬍ .001) for vicarious experience, .68 (p ⬍ .001) for verbal persuasion by others, .65 (p ⬍ .001) for self-persuasion, .59 (p ⬍ .001) for negative affective states, and .65 (p ⬍ .001) for positive affective states. Measurement invariance across time was assumed for all six Sources of Self-Efficacy Scales over all three points in time. Strict measurement invariance (equal factor loading, item intercepts, and measurement errors across time) could be established for vicarious experience and negative affective states, as these models did not fit the data worse than the strong measurement-invariance models. Strong measurement invariance (equal factor loading and item intercepts) could be established for mastery experience, selfpersuasion, verbal persuasion by others, and positive affective states, as these models did not fit the data worse than the weak measurement-invariance models (Meredith, 1993). See Table 3 for model fits and model comparisons. Therefore, it can be assumed that the latent factors represent sufficiently similar constructs over time.

Analytical Procedure The longitudinal data set of Study 2 was used to test whether the scales assess the sources reliably across time. First, internal consistency was tested using Cronbach’s alpha. Then test–retest analyses were conducted from T2 to T3 to avoid the time period containing the intervention (between T1 and T2). Studying the development of the sources across time in future studies requires at least strong measurement invariance across time. In accordance with Meredith (1993), configural, weak, strong, and strict measurement-invariance models were established for every scale in Mplus 6. The more restrictive models were then tested against the less restrictive ones using chi-square difference tests. Once the more restrictive model fits the data worse than the less restrictive model, the scale’s level of measurement invariance is identified. To test the associations of the sources of self-efficacy and self-efficacy as well as physical activity over time, a mediation

Prediction of Physical Activity by the Sources of Self-Efficacy via Self-Efficacy Over Time To test whether the sources of self-efficacy for Physical Activity do not only relate to self-efficacy for physical activity but also to actual physical activity over time, a structural equation model was specified, which aimed to test whether the sources of self-efficacy (T1) predict change in physical activity (T1–T3) through selfefficacy as the mediator (T2; see Figure 3). The model fit the data satisfactorily, ␹2(356) ⫽ 557.60, RMSEA ⫽ 0.04, CFI ⫽ 0.96, SRMR ⫽ 0.06. Self-efficacy was significantly and positively predicted by mastery experience and self-persuasion, whereas negative affective states predicted self-efficacy negatively. Physical activity was significantly and positively predicted by self-efficacy, vicarious experience and negatively by verbal persuasion by others, after controlling for baseline activity (for coefficients, see

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Table 3 Model Fit and Model Comparisons for Measurement Invariance Across Time (T1, T2, T3) for the Sources of Self-Efficacy for Physical Activity Scales Source

Measurement invariance

␹2

Mastery experience Vicarious experience Verbal persuasion by others Self-persuasion Negative affective states Positive affective states

strong strict strong strong strict strong

42.68 29.82 61.19 53.69 37.41 41.80

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Note.

p

CFI

RMSEA

SRMR

Compared with

⌬␹2

⌬df

p(⌬␹2)

29 .05 35 .72 29 ⬍ .01 29 ⬍ .01 35 .36 29 .06

0.99 1.00 0.98 0.99 1.00 0.99

0.04 0.00 0.06 0.05 0.02 0.04

0.04 0.03 0.04 0.03 0.04 0.03

weak strong weak weak strong weak

1.41 ⫺12.86 3.63 1.68 6.56 6.95

4 6 4 4 6 4

.84 .23 .46 .80 .36 .14

df

Data from Study 2.

Figure 3). Indirect effects of the sources of self-efficacy via selfefficacy on physical activity were significant for mastery experience (standardized indirect effect ⫽ .09, p ⫽ .03), self-persuasion (standardized indirect effect ⫽ .12, p ⫽ .01) and negative affective states (standardized indirect effect ⫽ ⫺.09, p ⫽ .02). To test the relative magnitude of these indirect effects, they were contrasted against one another. The Wald test of parameter constraints was nonsignificant for each of the contrasts, implying that the three indirect effects were comparable in magnitude. Vicarious experience and verbal persuasion by others thus seemed to directly relate to physical activity without being mediated by self-efficacy, whereas mastery experience, self-persuasion, and negative affective states were indirectly associated with physical activity

by relating to self-efficacy in this sample of older German adults.

General Discussion There is good evidence to suggest that self-efficacy beliefs are among the most important predictors of health-behavior change, and most health-behavior change theories assume a crucial role of self-efficacy. However, an up-to-date comprehensive assessment of the sources of self-efficacy for physical activity was lacking. Therefore this study had two aims: (a) to develop scales to assess the sources of self-efficacy for physical activity that are reliable and valid and (b) to test those sources’ relative importance in the

Figure 3. Prediction of physical activity by the sources of self-efficacy for physical activity via self-efficacy for physical activity over time. Note. Data from Study 2; reported are standardized path coefficients; all constructs except from group, age and gender are latent factors; method factors, indicators and indicator loadings are not displayed for clearer presentation; all indicators load significantly on their factors (p ⬍ .001); ⴱ p ⬍ .05; ⴱⴱ p ⬍ .01; ⴱⴱⴱ p ⬍ .001.

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prediction of sources of self-efficacy for physical activity in a sample of older adults—a population in special need for effective health-behavior interventions.

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Validation of the Sources of Self-Efficacy Scales In Study 1, the final six subscales were found to be distinct from each other. The only sources that correlated above .50 were mastery experience and positive affective states. Further, all six scales were internally consistent and correlated well with self-efficacy for physical activity in this sample of broad age range, suggesting convergent validity. The scales’ correlations with social support, behavioral intentions, as well as positive and negative outcome expectancies were moderate, suggesting discriminant validity. In Study 2, test–retest reliability was satisfactory and at least strong measurement invariance could be established for all of the six Sources of Self-Efficacy Scales. Even though the proposed scales contain the sources of selfefficacy suggested by Bandura (1997), recent research has suggested that self-efficacy beliefs might be based on additional sources. Most important, and contrary to social– cognitive theory, positive outcome expectancies were found to positively affect self-efficacy (Williams, 2010), but factors such as feedback (Ashford et al., 2010), mental imagery (Chase et al., 2005; Maddux & Gosselin, 2012; Wesch, Milne, Burke, & Hall, 2006), positive experience (Fleig, Pomp, Schwarzer, & Lippke, 2013; Parschau et al., 2013), and physiological barriers or perceived fitness (O’Brien Cousins, 1997; O’Brien Cousins & Tan, 2002) might also play roles. Future researchers might therefore want to extend the scales to create a broader picture of the sources of self-efficacy for physical activity. Furthermore, the scales were validated by using exercisespecific, self-efficacy items (Scholz et al., 2005). Studies on different specific physical activity behaviors (e.g., competitive sports), barriers (e.g., setbacks after illness), risk situations (e.g., vacation), and populations (e.g., children) might require the construction of efficacy source scales that differ from the ones developed in this article to meet the microanalytic principle of maximum correspondence between self-efficacy and behavior (Bandura, 2006).

Association of the Sources of Self-Efficacy With Self-Efficacy and Health Behavior To investigate the sources associations with physical activity over time in a high-risk population, Study 2 was conducted in a sample of older adults. Indirect effects of mastery experience, self-persuasion and negative affective states on physical activity via self-efficacy beliefs over time were found. These findings support the important role of mastery experience and selfpersuasion in the exercise domain and the special relevance of negative affective states as an impediment of self-efficacy in older adults (Lim & Taylor, 2005). Contrary to Bandura’s (1997) proposed hierarchy, the indirect effects on physical activity were similar in magnitude for mastery experience, self-persuasion and negative affective states. Therefore, we suggest that these three sources be addressed in future interventions to promote physical activity self-efficacy in older adults. Vicarious experience was assumed to be an important source of self-efficacy in this population (Warner et al., 2011), but was

found to have no association with subsequent self-efficacy beliefs. Instead, vicarious experience predicted physical activity directly over time. This direct effect could be due to the fact that most older adults report a lack of social models for physical activity (Lee, Arthur, & Avis, 2008), and that only those who exercise regularly and have high self-efficacy beliefs might have the opportunity to observe social models (e.g., in exercise groups), rendering vicarious experience an indicator of regular physical activity rather than a source of self-efficacy. Although verbal persuasion is one of the most frequently used behavior-change techniques in physical activity interventions, it is assumed to be a weak source of self-efficacy and to bear the risk of backfiring (Ashford et al., 2010). In our study, verbal persuasion by others was not associated with later self-efficacy for physical activity, but showed a direct negative association with change in physical activity. On the one hand, this ambiguous effect of verbal persuasion by others might be caused by the recipient’s interpretation of persuasive messages as attempts to be controlled or manipulated in the exercise domain (Miller et al., 2007). On the other hand, a mobilization effect might have occurred, as those older adults, who are sedentary, evoke more social support by their social network, eventually causing a negative association between verbal persuasion by others and physical activity.

Limitations The samples of both studies were convenience samples of community-dwelling volunteers who participated in unpaid surveys. As they were recruited by means of a science TV show and newspaper articles, both samples were likely to be biased toward individuals with higher education, better health behaviors, and better health status. Our results should therefore not be generalized to less educated, younger, or less healthy populations. Furthermore, the sample of Study 1 might have been more familiar with self-efficacy, as the TV show that served as recruitment platform included a feature on self-efficacy, among other constructs. Therefore, the proposed items might have had a low difficulty score in this sample. However, the analyses in Study 2 in a sample without previous knowledge of the construct confirmed the good reliabilities. All measures in this study were self-reports, implying the potential for social desirability and memory bias, especially in the assessment of physical activity. Even though self-reports of physical activity can be valid indicators of actual behavior in adults, future researchers might want to consider more objective measures, for example, using diaries or accelerometers (Slootmaker, Schuit, Chinapaw, Seidell, & van Mechelen, 2009; Trampisch et al., 2012). The exclusive use of self-reports brings about another conceptual problem, as our items for mastery experience can be considered retrospective formulations of the utilized self-efficacy items (French, 2013), which might have produced the high correspondence between mastery experience and self-efficacy. Even though mastery experience and self-efficacy are theoretically and empirically closely related, future studies might reveal formulations of more distinct mastery-experience items or use more objective measures (Bandura, 1997; Moritz, Feltz, Fahrbach, & Mack, 2000). Furthermore, discriminant validity of the developed scales should be tested in more detail in future studies, to ensure their distinct contribution to self-efficacy beliefs above and beyond

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SOURCES OF SELF-EFFICACY

cognitions such as subjective and descriptive norms that might be related to verbal persuasion by others and vicarious experience (Courneya & McAuley, 1995) or depressive symptoms that might bias participants’ ratings of affective states in relation to health behaviors (Rejeski, Reboussin, Dunn, King, & Sallis, 1999). As mentioned earlier, the designs of both studies preclude ruling out reverse causation. Whether the sources of self-efficacy always precede self-efficacy beliefs or whether self-efficacy also promotes the occurrence and frequency of certain sources, therefore, needs further investigation. To guide the construction of future interventions, studies with either frequently repeated assessments of sources and self-efficacy beliefs or experimental designs that manipulate, measure and compare specific sources of self-efficacy against one another are needed to draw more valid conclusions about the relevance of the sources of self-efficacy in different health behavior domains.

Conclusion The short and valid instruments to measure six sources of self-efficacy for physical activity presented in this article enable researchers to identify the differential effects of self-efficacy sources. Further, the scales might be used for manipulation checks and to unravel the mechanisms behind intervention effects. This short instrument can be used to identify the most powerful sources of self-efficacy for physical activity and inform evidence-based interventions. Our first results using the newly developed scales suggest targeting mastery experience, self-persuasion, and a reduction of negative affective states in future physical activity interventions for community-dwelling older adults.

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Received August 1, 2013 Revision received December 14, 2013 Accepted January 31, 2014 䡲