Teaching Physically Active Ph

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Self-Efficacy Theory and the Theory of Planned Behavior: Teaching Physically Active Physical Education Classes a

Jeffrey J. Martin & Pamela Hodges Kulinna a

b

Division of Kinesiology, Health, and Sport Studies , Wayne State University , USA

b

Department of Physical Education , Arizona State University , USA Published online: 25 Feb 2013.

To cite this article: Jeffrey J. Martin & Pamela Hodges Kulinna (2004) Self-Efficacy Theory and the Theory of Planned Behavior: Teaching Physically Active Physical Education Classes, Research Quarterly for Exercise and Sport, 75:3, 288-297, DOI: 10.1080/02701367.2004.10609161 To link to this article: http://dx.doi.org/10.1080/02701367.2004.10609161

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Pedagogy

Aeseerch Quarterly for Exercise and Sport ©2004 by the American Alliance for Health, Physical Education, Recreation and Dance Vol. 75, No.3, pp. 288-297

Self-Efficacy Theory and the Theory of Planned Behavior: Teaching Physically Active Physical Education Classes

Downloaded by [Arizona State University] at 10:48 03 February 2014

Jeffrey J. Martin and Pamela Hodges Kulinna

The purposeofour investigationwas toexaminedeterminants of teachers' intentions to teach physically activephysicaleducation classes (i.e., spend at least50% ofclass time with thestudents engaged in moderate to vigorous physicalactivity). Basedon the theory ofplanned behavior, a modelwasexaminedhypothesizing that teachers' intentionswere determined l7y subjective norm, attitude, and perceived behavioral control. Groundedin self-efficacy theory, it was hypothesized that program goal importance and hierarchical and barrier self-efficacy would alsopredict intention. Usinga series ofhierarchical regression analyses, the theory ofplanned behaviorwas supported l7y accountingfor 59% of thevariancein intention due to attitude, perceived behavioralcontrol; and subjective norm. Self-efficacy theory based variables received minimal support.

Key words: children, fitness, health, psychology

R

esearch e rs in public health, epidemiology, and physical education have consistently demonstrated the importance ofphysicalactivity in promoting fitness and health (Almond & Harris, 1998; Caspersen, 1989; Dishman & Buckworth, 1996; Kujala, Kaprio, Sarna, & Koskenvuo, 1998; Ross & Gilbert, 1985; Salliset al., 1997). For example, physicallyactive people have a reduced risk of heart disease,live longer, have better quality lives, and are less likely to be depressed (Sallis & Owen, 1999). Most adults, however, are inactive or irregularly active (D. S. Department of Health and Human Services [DSDHHS], 1996). Children and adolescents' physical activity habits are also poor. Many children and adolescents are physically inactive and become even less active as they age (Ross & Gilbert, 1985, DSDHHS, 1996).

Submitted: July 16, 2002 Accepted: December 6, 2003 Jeffrey J. Martin is with the Division of Kinesiology, Health, and SportStudies at Wayne State University. Pamela Hodges Kulinna is with the Department of Physical Education at Arizona State University.

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For instance, virtually 50% of all young people do not participate regularly in vigorous activity, and only 41 % of fifth- to twelfth-grade students obtain enough vigorous activity to derive cardiovascular benefits (Ross & Gilbert, 1985, DSDHHS). Researchers examining relationships among physical activity, youth fitness, and health have suggested that school physical education may be the only institutional setting providing an opportunity for most children to be consistently physically active (Sallis et al., 1997). For instance, most states have physical education programs requiring student participation (National Association for Sport and Physical Education, 1997), and most children and youth attend school (DSDHHS, 1996), although regulations vary according to state (Siedentop, 2001). Representatives ofleading professional health and physical activity organizations have issued numerous position statements emphasizing the importance of providing physical activity in school physical education. The Council on PhysicalEducation for Children stated, "Regular physical education programs (preferably daily) should provide a significant amount of the time in activitynecessary to meet the guidelines in this report" (Corbin & Pangrazi, 1998, p. 14). The Healthy People 2010 objectives for school physical education indicate that students should spend 50% of their class time being physically

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Martin and Kulinns

active (USDHHS, 2(00). The National Center for Chronic Disease Prevention and Health Promotion stated that a substantial portion of children's weekly physical activity should be obtained from physical education classes (USDHHS, 1996). Furthermore, they suggested that physical education teachers should be trained specifically to provide children with moderate to vigorous physical activity during class time. Finally, it has been noted that a comprehensive approach to increasing youth physical activity should have school physical education as a primary component (Sallis et aI., 1992). Investigators have supported the importance of school-based physical education programs in promoting physical activity and health. Sallis and colleagues (1997) reported that a health-based physical education curriculum, implemented by physical education specialists and trained classroom teachers, successfully increased children's physical activity levels. In a review of 19 studies, Almond and Harris (1998) also found that the eight intervention-based studies were successful in increasing physical activity levels in physical education classes. Clearly, school physical education provides an excellent opportunity for children to be active and develop health benefits, despite barriers, such as a lack offacilities (Martin & Kulinna, 2003; McKenzie, et al. 1995) that limit physical activity. Teachers are obviously a major determinant ofwhether children and youth in physical education classes engage in high levels of physical activity. Teachers' intentions to teach physically active classes are critical, because intentions are major behavioral determinants (Ajzen & Madden, 1986). The current study uses social cognitive theory to investigate teachers' intentions to teach physically activeclasses.The social cognitive theory ofhuman behavior stipulates that people have the ability to self-regulate, adopt goals, use anticipatory forethought, and reflect on their thoughts, feelings, and behaviors (Bandura, 1997). As an overarching meta-theory, it provides a broad framework for self-efficacy theory (SET; Bandura, 1997) and the theory of planned behavior (TPB; Ajzen, 1991). According to the TPB, teachers with strong intentions to teach physically active classes are more likely to do so, compared to teachers with weaker intentions (Godin & Shephard, 1986; Wurtele & Maddux, 1987). Intentions, according to the TPB, are influenced by the social setting (i.e., subjective norm) and individual's attitudes. Teachers with positive attitudes toward teaching classes with high physical activity levels and a supportive social environment (e.g., school administrators) are likely to have strong intentions to teach classes with high levels of student participation in physical activity. Finally, because not all behaviors are under people's volition, perceived behavioral control is also an important element of the TPB (Ajzen, 1991). Teachers with a strong sense of control over what and how they teach will develop stron-


ger intentions, compared to teachers who perceive they have little control over their lessons or the curriculum. Self-efficacytheory (Bandura, 1997) also provides a theoretical base for this study. It highlights the importance ofself-efficacy and outcome value or importance (Maddux, 1995). Self-efficacy, in particular, is thought to be the primary determinant ofhuman behavior. According to SET, teachers who feel efficacious about providing students with high physical activity levels in their classes with supportive program goals, such as promoting physical activity, fitness, and health, will be more likelyto do so,compared to teachers who are less efficacious and do not viewphysical activity, fitness, and health program goals as important. Physical activity leading to fitness development has been shown to be the most important outcome goal for physical education teachers, although several other outcome goals were important to teachers (i.e., self-actualization, motor skill development and social development; Kulinna & Silverman, 2000). Although self-efficacy (SE) and perceived behavioral control (PBC) are sometimes considered similar (Ajzen, 1991), their definitions are not identical (Ajzen, 1991; Bandura, 1997), and it is common to assess them separately (Coumeya, 1995; McAuley & Mihalko, 1998). In our study, PBC was defined as how much control teachers have over teaching classes with high levels of student physical activity participation. In contrast, consistent with Bandura (1997), SE refers to how capable teachers feel in their ability to teach lessons that include large amounts (i.e., at least 50% of class time) of physical activity. Thus, in the current study, PBC and SE are conceptually distinct. A variety of research in human movement settings has supported the TPB (Dzewaltowski, 1989; Gatch & Kendzierski, 1990; Godin, 1994; Kimiecik, 1992; Schifter & Ajzen, 1985; Yordy & Lent, 1993). Gatch and Kendzierski (1990), for instance, indicated that subjective norm, attitude, and PBC contributed to predicting female undergraduate students' intentions to participate in aerobics. Godin (1994) reviewed 12 exercisebased studies and reported that intention accounted for 30% of the variance in exercise behavior. Hausenblas, Carron, and Mack (1997) also supported the TPB with a meta-analysis of 31 exercise-based studies. Finally,research in nonsport and exercise settings has also supported the important role that subjective norm and attitude play in predicting intention. For instance, in a meta-analysis of 87 studies, Sheppard, Hartwick, and Warshaw (1988) found the average correlation between attitude/subjective norm and intention was .66. ,SE research is also prolific, and numerous metaanalyses have acknowledged the vital role that SE cognitions play in human behavior (Holden, Moncher, Schinke, & Barker, 1990; Multon, Brown, & Lent, 1991; Stajkovic & Luthans, 1998). Stajkovic and Luthans (1998) examined

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114studies in their meta-analysis and found SE was a strong predictor ofwork-related performance. Based on a metaanalysis of 68 studies, Multon et al. (1991) found a significant effect size between student SE and academic performance over a 12-year period. Holden et al. (1990) conducted a meta-analysis of 25 studies on the SE of children and adolescents. Similarly, Ross (1994) reported on 87 investigations of teacher efficacy through a meta-analysis. These investigations all supported the beneficial influence of SE on human functioning. Research in education has also supported the critical role of efficacy cognitions, although it has been criticized for its methodological and conceptual shortcomings (Bandura, 1997; Henson, 2001; Tschannen-Moran & Woolfolk Hoy, 2001;Woolfolk & Hoy, 1990). For instance, Ross's (1994) meta-analytic study found that most of the 87 studies examined viewed efficacy as a generalized expectancy, in contrast to the domain and task specificity conceptualization of SE (Bandura, 1997). Many researchers also inadequately assessed SE by using one-item scales and failing to achieve correspondence between the SE measure and the behavior of interest (Bandura, 1997). Regardless, evidence suggests that teacher SE is positively related to perceptions of parental (e.g., home tutoring) involvement (Hoover-Dempsey, Bassler, & Brissie, 1987), administrative attention and support (Ashton & Webb, 1986; Chester & Beaudin, 1996), colleague collaboration (Chester & Beaudin, 1996; Hoy & Woolfolk, 1993), and a rigorous academic climate (Hoy & Woolfolk, 1993). There is still a need, however, for continued research examining teacher efficacy with sound measures based on the theoretical underpinnings ofSE theory as outlined by Bandura (1997). The research efforts in this study mirror current SE research trends in general education (Henson, 2001; Tschannen-Moran & Woolfolk Hoy, 2001). Researchers examining variables from the TPB and SET demonstrated that this approach is fruitful. Yordy and Lent's (1993) research, for instance, found that intention and SE were important predictors of exercise status. DuCharme and Brawley (1995) reported that efficacy cognitions predicted intentions for exercise behavior. Combining key constructs from the TPB and SET is viewed as an excellent method to determine the relative importance ofvarious psychological variables (Dzewaltowski, 1989; Dzewaltowski, Noble, & Shaw, 1990; Hausenblas et aI., 1997). In brief, examining the TPB and SET has empirical and theoretical support as well as the ability to parsimoniously explain physical education teachers' intentions to teach classes with high levels ofstudent participation in physical activity. Understanding the determinants ofteachers' intentions to teach classes in which students engage in high physical activitylevels is an important step in understanding children's physical activity participation. Unfortu-

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nately, little is known about physical education teachers' intentions or, importantly, the determinants of those intentions. In fact, although many researchers have investigated teacher SE, the TPB has received little attention in education research. Thus, there is a need to test the TPB in educational settings. In one of the few studies in this area, Martin, Kulinna, Eklund, and Reed (2001) examined 187 predominately Caucasian physical educators. They found support for the theory of reason action (Ajzen & Madden, 1986), that is, attitude and social influences affecting teachers' intentions, as they accounted for 55% of the variance in teachers' intentions to provide physically active classes. They found little support, however, for SE theory (Bandura, 1997). To address the lack of research in this area, we designed the current study. In summary, the primary purpose of this study was to examine the ability of the TPB and SET to predict teachers' perceived behavioral intention to teach physically active physical education lessons. Another purpose was to extend the work of Martin et al. (2001) by examining the TPB along with two forms of SE and program goal importance. A traditional hierarchical form ofSE was investigated as well as a more recent conceptualization of SE, labeled barrier self-efficacy (McAuley & Mihalko, 1998). Barrier self-efficacyreflects teachers' beliefs about their ability to overcome various barriers that could prevent them from teaching highly active physical education lessons. Finally, because Martin et al. (2001) examined a relatively small (i.e., N = 187) and homogenous (i.e., 97% Caucasian) sample of teachers, this study extends their research efforts with a larger (i.e., N = 342) and more ethnically diverse (i.e., Caucasian, African American) sample of teachers. Repeating studies with different samples in a particular area has been suggested as an important way to improve research in physical education pedagogy (Rink, 2000).

Method Recruitment Participant recruitment began at the district level. The curriculum coordinators for 49 school districts were contacted to request participation by the physical education specialists in our study. Thirty-six districts (73%) agreed to participate. Three methods of teacher recruitment were used. First, for five of the districts, the research team attended an inservice workshop for physical education teachers, and interested teachers completed the research materials during the workshop. Second, in 15 districts, the curriculum coordinator (or another administrator) sent research packets to the teachers.


Martin and KuJinna

Finally, the remaining districts provided a list of teachers and their school contact information, and we sent the packets directly to the teachers with a letter of support from the district. Six hundred ninety packets were distributed, and 342 were returned, for a 50% return rate. The research packets included an informed consent form, demographic sheet, and the 86-item instrument. Teachers returned packets to the second author, and all provided informed consent.


Participants Three hundred forty-two physical education teachers from a midwestern state participated in the current study. Participants ranged in age from 23 to 62 years (M = 43.3 years, SD= 9.9). There was adequate representation from both genders, with 41.1 % female and 58.9% male participants. Ethnic background was mostly reported as Caucasian (70.2%) followed by African American (23.3%) and Hispanic American (5.2%); 1.3% was unreported. Educational degree level varied as follows: bachelor (36.5%), specialist (6.7%), master (56.2%) and doctorate (.6%). Teachers had between 1 and 40 years of teaching experience (M= 16.5 years, SD= 10.8), and almost half of our sample (i.e., 47.7%) taught physical education classes daily. The remaining teachers taught physical education either 1 (21.8%), 2 (23.1 %), or 3 (7.4%) days a week. Many teachers (28.9%) taught classes ranging in length from 51 to 55 min, whereas another significant group of educators (26.2%) taught classes lasting 46-50 min. Another 30% were split fairly evenly (i.e., 10%) over 26-30-,36-40-, or 41-45-min classes. The remaining teachers taught either short (e.g., < 20 min) or long (i.e., > 60 min) classes. Teaching level for our sample was split across the elementary (41.7%) junior high/middle school (23.1 %), and high school (27.5%) levels. The remaining 7.7% taught at two different levels (e.g., elementary and middle school). Teachers averaged 32 students per class ofwhich they reported 50% of their students' ethnic backgrounds were Caucasian, 44% African American, 3% Hispanic American, and 2% Asian American (1% unreported).

Instrument The questionnaire used in this investigation asked participants to report their gender, age, ethnicity, educationallevel, and years of teaching. They also reported the grade level, length, and number of physical education classes taught per week. Participants estimated the average number of students per class and their ethnic background. All questionnaire instructions defined "large amounts of physical activity"as at least 50% ofclass time. The criterion of 50% of class time was used to


match the Healthy People 201 oobjectives for school physical education programs, which stipulate that students should spend 50% of class time being physically active (USDHHS, 2000). All questionnaires assessing psychological constructs were based on guidelines provided by Bandura (1997) and Ajzen and Madden (1986) and have been used previously in similar research (Kulinna & Silverman, 2000; Martin etal., 2001) to examine physical education teachers' perceptions and produce reliable and valid scores in similar populations. BehavioralIntention (BI). Participants responded to five items on a 7-point Likert-type scale with anchors of "definitely will not/definitely will" for the question, "I will try to teach lessons that provide large amounts of physical activity,"and anchors of"definitely do not/definitely do" for the questions, "I intend to teach..." and "I plan to teach.... " The anchors of "definitely false/definitely true" were used for the questions, "I am determined to teach..." and "I have decided to teach.... " Attitude (Arr). Teachers responded to the question, "Providing large amounts ofphysical activity (i.e., at least 50% of class time) during my lessons is.... " Participants then responded on a 7-point Likert-type scale, with anchors listing opposing affective adjectives as recommended by Ajzen and Madden (1986). The pairs of adjectives used were: bad/good, unpleasant/pleasant, harmful/beneficial, useless/useful, unenjoyable/enjoyable, unhealthy/healthy, and not important/important. Control(CON). Participants were asked three questions with the following three stems: "How much control do you have over whether you include..." (absolutely no control/complete control); "It is mostly up to me whether I include..." (strongly disagree/strongly agree) ; "If! want to, I can have ..." (strongly disagree/strongly agree). Each stem was completed with the following phrase"... large amounts of physical activity (i.e., at least 50% of class time) in my lessons." Subjective Norm(SN). Subjective norm was determined by examining respondents' perceptions of important social groups (i.e., administrators, fellow teachers, parents, and students) beliefs, and their motivation to comply with those beliefs. Based on the four groups noted above (derived from previous research studies, see Chester & Beaudin, 1996; Hoover-Dempsey, et al., 1987; Hoy & Woolfolk, 1993), an eight-item scale was created consisting offour pairs of questions. An example of one pair, with appropriate anchors following, stated, "The parents at my school believe that it is important that I include large amounts of physical activity (i.e., at least 50% of class time) in my lessons"(strongly disagree/ strongly agree}, and, "How motivated are you to comply with the beliefofyour students' parents that you should include large amounts of physical activity (i.e., at least 50% ofclass time) in your lessons?" (not at all motivated/ extremely motivated). Three subsequent pairs of ques-

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tions replaced "parents" with teachers, administrators, and students. Participants responded on a 7-point Likert-type scale. Hierarchical Self-Efficacy (HSE). The HSE scale is a seven-item measure specifically designed to assess teachers' efficacy for teaching physically active physical education classes. Participants were asked to rate, "How confident are you in your ability to teach lessons that provide physical activity for 20% of the class time?" on a 0-100% scale. Six similar questions substituted the numbers 30, 40, 50, 50, 70, and 80% for 20%. Thus, strength of SE was assessedfor seven levelsof increasing difficulty. The final strength of SE score, ranging from 0 to 100, was obtained by adding each strength (0-100) score and dividing by the number of levels (i.e., questions). Our measure ofSE reflects a microanalytical hierarchical task approach to assessing behavioral SE (see Bandura, 1997; Maddux, 1995; McAuley & Mihalko, 1998). Barrier Self-Efficacy (ESE). The BSE scale is a 20-item measure specifically designed to assess teachers' efficacy for overcoming commonly experienced barriers to teaching physically active physical education classes. From a previous study, the 20 top barriers that physical education teachers faced when trying to teach physically activeclasses (Kulinna, Martin, Zhu, & Reed, 2002) were identified. Examples of these barriers are a lack of time (e.g., short classes),little space (e.g., small gyms), limited institutional support (e.g., lack offunds) , and minimal student interest (e.g., students not interested in participating). A Likert-type scale, based on Bandura's (1997) recommendations and similar to other SE instruments, was then developed. The barrier items were transformed into questions addressing teachers' SE for overcoming these barriers to physically activeclasses. Teachers read a header, "Howconfident are you that you can provide large amounts of physical activity (i.e., at least 50% ofclass time) in your lessons under the following conditions," followed by the 20 questions. For example, one question read, "My students do not enjoy spending large amounts of class time being physically active." Each question was placed on a Likert-type scale anchored by 0% and the phrase "not at all confident" and 100% and the phrase "veryconfident." Participants then circled numbers ranging from 0 to 100, in increments oflO. The final strength ofBSE score, ranging from 0 to 100, was obtained by adding each strength (0-100) score and dividing by the number oflevels (i.e., 20 questions). Program Goal Importance (PCI). The PGI scale is a 9item measure designed to assess program goal importance (Kulinna & Silverman, 2000). Teachers rated the importance ofgoals to promote physical activity and fitness in physical education on a 5-point Likert-type scale anchored by 1 (not important) and 5 (extremely important). Two examples ofquestions from this scale are, "To develop components of health related fitness," and "Pro-

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viding large amounts of activity time ....leading to the development of physical fitness in students."

Data Analysis The internal consistencies of the scores produced by the instruments were first examined using Cronbach's alpha (1951). Descriptive statistics were calculated for the scales by summing items on each scale and dividing the sum by the number of items on the scale. This procedure checked the consistency of the values with the Likert-type scale scoring procedures used in each scale and enhanced interpretability. Finally,correlational and regression analyses were performed.

Results Internal Consistency Coefficient alpha (Cronbach, 1951) for each of the seven multi-item scales shared a high level ofinteritem agreement. The alpha coefficients for BI (.96), CON (.93), SN (.87),ATT (.93), HSE (.84), BSE (.92), and PI (.88) were all considered adequate, because they exceeded Nunnally's (1978) minimal criteria of .70.

Descriptive Statistics Means, standard deviations, and range ofscores for all psychological variables assessed are presented in Table 1. It is apparent from the means and standard deviations of teachers' scores that they had strong behavioral intentions toward teaching classes that involved large amounts of physical activity for their students. Teachers also indicated they had positive attitudes toward teaching active classes and were motivated to com-

Table 1. Means, standard deviations, and ranges for all variables in the model Variable BI

An SN PBC HSE BSE PGI

M

SO

Ranges

6.4 6.4 5.7 6.5 88.0 66.8 4.3

.8 .7 1.0 .9 13.0 16.6 .6

1.0-7.0 2.0-7.0 1.8-7.0 1.0-7.0 40.0-100.0 27.0-100.0 1.2-5.0

Note. BI =intention; An =attitude; SN =subjective norm; PBC = perceived behavioral control; HSE = hierarchical self-efficacy; BSE =barrier self-efficacy; PGI =program goal importance.

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ply with important social groups' (e.g., students, parents, etc.) wishes that they teach large amounts of physical activity in their classes. Teachers also reported a strong sense ofcontrol over the ability to teach physical education classes that included high physical activity levels and teach efficaciously. Their barrier efficacy scores, however, were substantially and significantly lower than their hierarchical efficacy scores, as confirmed by a t test, t( 1,341) = 21.49, p « .001. Finally, teachers indicated that physical activity, fitness, and health-based physical education program goals were important.


Group Differences We conducted a multivariate analysis ofvariance to determine if there were differences in the seven psychological variables according to gender, ethnicity, or school location (i.e., urban vs. suburban schools). For ethnicity, we included only teachers (n = 305) who were Caucasian or African American because of the small number of teachers reporting other ethnicities. The main effects for gender, F(7, 291) =.185, p=. 99, ethnicity, F(7, 291) = 1.07, p=. 38, and school location, F(7, 291) = 1.05, P=. 40, and all interactions were not significant. This analysis indicated that men and women, Caucasians and African Americans, and teachers from urban and suburban schools did not differ in BI, ATT, SN, CON, HSE, BSE, or PGI. Correlations Among Variables in the Model Correlations among the variables can be found in Table 2. The pattern ofcorrelations indicates strong and meaningful (e.g., r= .52-70) relationships among the variables from the TPB (i.e., ATT, SN, and PBC). One statistically significant, but less meaningful, correlation

(e.g., r= .26) involving the SE measures was found. The strongest correlation (r= .22) between variables representing the TPB and SET was between BI and HSE. Hierarchical Regression Analyses Two hierarchical regression analyses were conducted to evaluate how well variables representing the TPB and SET predicted perceived BI. First the TPB was evaluated by entering ATT,SN, and PBC as a block. Next, SET was evaluated by entering both SE measures and PGI as a second block. Our second hierarchical regression analysis contrasted the first analysis by entering the SET variables first as a block and then entering the TPB variables as a second block (see Table 4). Comparing how well each block predicted intention when entered first and sec-

Table 2. Correlations among all psychological variables BI

An

SN

PBC

HSE

BSE

.70.60.52** .22.20** .14*

.60.39.15.17.16*

.37.18** .17** .17-

.15** .15** .03

.26* .08

.04

BI

An SN PBC HSE BSE PGI

Note. BI = intention;

An = attitude; SN = subjective norm; PBC

=perceived behavioral control; HSE =hierarchical selfefficacy; BSE =barrier self-efficacy; PGI =program goal importance. *p < .05. -p< .01.

Table 3. Results of hierarchical regression on the prediction of behavioral intention: Entering the theory of planned behavior first followed by social cognitive theory p