JRHS 2015; 15(4): 223-227        

Copyright© Journal of Research in Health Sciences

Predictors of Physical Activity among Adolescent Girl Students Based on the Social Cognitive Theory

Monasadat Ardestani (MSc)a, Shamsaddin Niknami (PhD)a*, Alireza Hidarnia (PhD)a, Ebrahim Hajizadeh (PhD)b

a Department of Health Education and Health Promotion, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

b Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

* Correspondence: Shamsaddin Niknami (PhD), E-mail: niknamis@modares.ac.ir

Received: 06 June 2015, Revised: 18 August 2015, Accepted: 28 September 2015, Available online: 07 October 2015


Background: The importance of increasing adolescence girls level of physical activity is recognized as a priority for having a healthy lifestyle. However, adolescent girls especially Iranian, are at high risk for physical inactivity. Social Cognitive Theory (SCT) is a successful theory to explain physical activity behavior. The aim of this study was to determine the predictors of physical activity based on the SCT.

Methods: This cross-sectional study was conducted among 400 adolescent girls (15-16 yr old) in Tehran, Iran (2013). The participants were randomly chosen with multistage sampling. The SCT constructs consisted of self-efficacy, self-regulation, social support, outcome expectancy, and self-efficacy to overcoming impediments. Statistical analysis was carried out applying SPSS: 16, LISREL 8.8. Stepwise regression was used to test predictors of behavior. Pearson correlation was assessed.    

Results: Self efficacy to overcoming impediments was the main construct to predict physical activity (Beta=0.37). Other determinants were self-efficacy (Beta=0.29), family support (beta=0.14), outcome expectancy (beta=0.13), friend support (beta=0.12), and self-regulation (beta=0.11), respectively. In general, the SCT questionnaire determined 0.85 variation of physical activity behavior. All of the constructs had direct significant relation to physical activity behavior (P<0.001).

Conclusions: The constructs of SCT provide a suitable framework to perform promoting physical activity programs and self-efficacy to overcoming impediments and self-efficacy are the best predictors of physical activity in adolescent girls.

Keywords: Physical activity, Students, Regression analysis


One of the most important parts of healthy lifestyle is regular Physical Activity (PA). Physical inactivity may lead to overweight and obesity, inflexible muscle, noncommunicable diseases, some cancers, mental and social disorders, and early death1.

Regular physical activity, especially among adolescence is important for promoting their healthy physical and psychological development. However, there are rising concerns about levels of PA among adolescence (aged 1218 yr) especially among girls. Inactivity rises with age and is higher in girls and women than men2,3.

An estimated 80% of adolescents (aged 13 15 yr) are physically active insufficient. Globally, the physical inactivity level was the highest in the Americas and Eastern Mediterranean regions where almost 50% of women were insufficiently active3.

In Iran, the prevalence of insufficient physical activity in females aged 15 yr and above is estimated 46.5 and in male 25.23. In Tehran, Iran, the prevalence of low physical activity in 15-24 yr women was 41%4. Sufficient physical activity in the age group of 517 considered at least 60 min of moderate to vigorous intensity physical activity per day3. Therefore, to promote physical activity behavior, awareness of its determinants is needed5,6.

The best interventions are grounded in theory-based approaches that aim to change behavioral patterns. The complexity of physical activity behavior is needed to use behavior change theories to identify the main factors influencing it.

One of the most theories to understand the framework of physical activity behavior is Social Cognitive Theory (SCT)7,8. It is based on a multi-dimensional model that includes intrapersonal/interpersonal characteristics, behavior, and environmental factors. The most constructs of SCT used in the studies were self-efficacy, self-regulation, social support, outcome expectancy, and self-efficacy to overcoming impediments. Various researches considered these constructs to adherence PA in diverse groups9,10.

Thus, because of the importance of promoting physical activity in adolescent girls as persons who have important role in their family and community in the future, the necessity to determine the effective factors for designing health education programs based on theory11, and lack of researches to assess the individual, behavioral, and environmental factors effect on PA7, this research assessed the power of predicting construct of social cognitive theory to designing PA programs.


This cross sectional study was conducted on 400 high school girl students in Tehran, Iran, 2013. Participants were randomly selected with multistage sampling .We assigned randomly one area among educational districts in Tehran, Iran. Then a number of schools were randomly chosen. The sample size was estimated based on the number of questionnaire items.12.

The inclusion criteria in this study were girl students aged 15-16 yr old, interested in participating, not attend in other physical activity programs, lack of disability. The exclusion criteria included disagreement of students or their parents to participate, and medical ban to exercise. First, the purpose of this study was explained to the participants. The participants were assigned informed consent form. Then they completed the questionnaires in about 20 min.

This study was approved by the Ethics Committee of Tarbiat Modares University, Tehran, Iran.   


The demographic variables included age, father and mother job, father and mother education, SCT scale and the short form of the International Physical Activity Questionnaire (IPAQ) were used in this study.

In the quantitative phase of validity, content validity index (CVI) and the content validity ratio (CVR) were assessed. CVR and CVI above 0.62 and 0.79 were accepted, respectively13. The CVI and CVR for the total items were 0.97-1 and 0.93-1. In the quantitative phase, the content validity index (CVI) assessed the simplicity, relevancy and clarity of items of SCT scale. Content validity ratio (CVR) examined the essentiality of items. Quantitative face validity showed that the range of impact score was 4.6-4.9.

The findings of qualitative content validity were appropriate, regarding to grammar, wording, item allocation and scaling. Briefly, grammar, wording, item allocation and scaling of the SCT questionnaire were evaluated qualitatively by an expert panel consisted of 10 health and physical education specialists. In the qualitative face validity all participants acknowledged that they had no problems in reading and understanding the items. Face validity was assessed by 10 students to evaluate the scale for difficulty, irrelevancy or ambiguity in responding to the questionnaire (qualitative method).

The reliability of the SCT scale was evaluated by means of internal consistency and testretest reliability methods. The internal consistency was assessed by Cronbachs alpha coefficient in 30 students. The alpha values of 0/70 and above were satisfactory. The average of Cronbachs alpha for the subscales was 0.9 (0.83-0.97). Students (n= 30) completed the questionnaire twice with two week interval for assessing the stability (test-re-test reliability) by intraclass correlation coefficient (ICC). The ICC was good to excellent (ICC ranged from 0.63 to 0.91).

We specified the construct validity of SCT scale by administering confirmatory factor analysis (CFA). We conducted CFA by means of maximum likelihood estimation. Confirmatory factor analysis confirmed the six factor structure (self-efficacy, self-regulation, family support, friend support, outcome expectancy, self-efficacy to overcoming impediments). All T-values were significant (P<0.05). Fit indices displayed that the SCT model fitted to the data (Table 1).

Self-efficacy scale

Self-efficacy scale was a 10 item instrument. The response range was 0% to 100% (0%=could not to 100%=positively could exercise). Self-efficacy was defined as personal confidence in the ability to perform the given behavior9. (Alpha=0.85, ICC=0.90, CVI=0.99, CVR=0.94)

Self-efficacy to overcoming impediments scale

Self-efficacy to overcoming impediments scale included 4 items with Likert format (1= not at all sure to 5= totally sure). This variable was defined as the confidence that the person has in overcoming barriers while performing a specific behavior10. (Alpha=0.80, ICC=0.81, CVI=1, CVR=1)

Social support scale

Social support structure with 6 items assessed participants perception of their family and friends support for the exercise, separately. This items were measured on a five point Likert format (1= none, 5= very often). Many people believe that the behavior change is easier when they receive family/friend support and it is an incentive for behavior change9. (Family support: Alpha=0.79, ICC=0.80, CVI=1, CVR=0.91, and friend support: Alpha=0.83, ICC=0.63, CVI=1, CVR=0.91)

Outcome expectancy scale

Outcome expectancy indicated the people's level of agreement with negative or positive statements regarding the possible effects of exercise (1 = not at all likely to 5 = extremely likely). Participants indicated the value of each outcome, by ranging from (1= not at all important to 5= extremely important). A person must value the outcomes that she believes will occur as a result of performing a behavior9. Outcome expectancy and the value of outcome expectancy scales were included 10 items, separately. (Alpha=0.78, ICC=0.80, CVI=0.98, CVR=0.93)

Self-regulation scale

Participants respond to 9 item self-regulation construct on a five-point Likert scale (1 = not at all describe; 5 = describe completely). Self-regulation construct is an integral part of an individuals ability to exert control over their external and internal environment14. (Alpha=0.81, ICC=0.75, CVI=0.97, CVR=0.94).

We applied Banville et al. method15 to cross culturally translate of the questionnaires. Two independent bilingual health researchers translated the original scales to Persian. Blind to the original questionnaire, the other two bilingual health researchers translated Persian form in English. Finally, an expert team comprising the translators and researchers reviewed all the translation and cultural adaptation processes. Agreement in terms of semantic, idiomatic and conceptual equivalence was reached and a final version of the scale was provided16.

Physical Activity Measure

Physical activity was measured by the short form of the International Physical Activity Questionnaire (IPAQ). The IPAQ assesses exercise intensity and duration based on minutes and days17. This form records the activity of four intensity levels: 1) Vigorous-intensity activity 2) Moderate-intensity activity 3) Walking; and 4) Sitting. There are three levels of physical activity proposed to classify populations: low, moderate and high18.

The validity and reliability of the IPAQ were approved in several studies19,20  and this research (ICC=0.85).

Data Analysis

The power of predicting PA behavior based on SCT constructs was assessed by Multiple Linear Regression and Stepwise Regression. Data were analyzed through SPSS: 16 (Chicago, IL, USA) and LISREL8.8.


Girl students participated in this study were 15-16 yr old. Majority of the parents were low literate. Most of father's jobs were employee and majority of mothers were housekeepers. Besides, 100% of subjects had insufficient physical activity. Demographic characteristics and physical activity rate of participants are provided in Table 2. The SCT accounted for 0.85 variance of physical activity behavior.


Self-efficacy to overcoming impediments was the main predictor of physical activity. This construct had a significant positive effect on physical activity behaviors, and one unit increase in self-efficacy to overcoming impediments led to 4.66% increase in target behaviors (ß=0.37).

Other determinants were self-efficacy (ß=0.29), family support (ß=0.14), outcome expectancy (ß=0.13), friend support (ß=0.12) and self-regulation (ß=0.11), respectively. The items of constructs and detailed results are presented in Table 3 and 4. The correlations of all constructs were significant (Table 5).

Table 1: Fit indices of the measurement model using Social Cognitive Theory (SCT)

Table 2: Demographic characteristics and physical activity rate/ level of the Participants (n=400)

Table 3: Item of construct social cognitive theory

Table 4: Predictors of physical activity behavior based on the Social Cognitive theory (dependent variable: physical activity)

Table 5: Correlations between the constructs of SCT defining physical activity behavior of school students (n=400)


It is of great importance to recognize the effective factors of PA behavior on different groups for designing the efficient health education interventions8 to promote exercise behavior. This study was conducted to determine the factors that lead to promote regular physical activity.

This investigation demonstrated that adolescent girl students were not adequately active. Therefore, it was required to examine the physical activity behavior in this target group. Our findings confirmed to the determined 0/85 variation of physical activity. Generally, range of 0.8< has a good fit indices to model13. Therefore, constructs of SCT can use to designing educational intervention for promoting physical activity behavior as a framework.

Our results showed that all of the constructs of SCT were significantly associated with PA, with self-efficacy to overcoming impediments, self-efficacy, family support, friend support, outcome expectancy, and self-regulation. Self-efficacy to overcoming impediments was the strongest predictor of exercise behavior. This construct is essential to have regular physical activity. Self-efficacy was a significant predictor of PA behavior. This is consistent with the result of Haider et al. 21. In that study, low scores for social support and self-efficacy to overcoming impediments was also found21.

In Dishman et al. study, self-efficacy to overcoming barriers to physical activity was stable across the high school years and was not directly or indirectly related to changes in physical activity. Rather, self-efficacy moderated the relation between changes in PA and social support. Girls who maintained higher perceptions of social support had less decline in PA, but only if they also had high self-efficacy to overcoming barriers to physical activity22. In Solymanian dissertation, the effect of self-efficacy on exercise behavior was mediated by self-regulation. In other words, high self-efficacy increases the use of self-regulation strategies14.

Family and friend support had a moderate effect on exercise behavior. The items of these construct were similar, but with a little different, family support was more important. Rutkowski et al. showed that a statistically significant inverse relationship is found between parental physical activities and the activity levels of adolescents (r=.23, P<.05). Typically, these parents do not share their physical activity time with family members20.

But the result of Duncan et al. research showed the importance of parental support in promoting physical activity among adolescents23. Pirasteh et al. research24 on girls showed that the self-efficacy scale contained a single factor, the social support scale contained two factors: family support and friend support. However, self-efficacy was the most important predictor to PA behavior24. Besides, outcome expectancy had a moderate effect on physical activity behavior.

Ramirez et.al research based on the SCT indicated positive effect of self-efficacy, outcome expectations, and social support on physical activity behavior in children25. In that study, self-regulation had the least significant effect on PA behavior. This finding is consistent with the results of Edmund26, self-regulation is a process that influences motivation and behavioral change. Self-regulation means that the individual needs goal-setting, planning, and problem solving in order to achieve their personal needs. Self-regulation refers to processes that enable individuals to guide their goal-directed activities over time27.

Wolfe in her dissertation showed that using constructs of SCT was successful in increasing the short and long-term exercise rates of the participants9. Self-regulation has the potential to be an important construct to include in future interventions. Self-efficacy increased throughout the study, but was non-significant between groups at post-test. Social support and outcome expectancies appeared to have been the least successful strategies learned in the intervention for exercise adherence9.

But Haider in his dissertation assessed the role of self-efficacy, social support, outcome expectancies, and self-efficacy to overcome barriers as predictors of exercise among college students in South Asia. Only self-efficacy was predictive of exercise behavior10. In Mehta dissertation, self-efficacy, self-regulation, and expectation had effect on PA behavior on middle aged women28.

This research has some limitations: First, the result of physical activity was based on self-report. Therefore, it may be affected on findings. Second, this study was done on a sample of Tehranian adolescent girl students. Therefore, the findings of this study have to be interpreted with some caution. Further studies are needed with regard to larger samples in the other areas. It is suggested to evaluate the effect of an educational intervention based on the findings of this study in the target group. 


Designing interventions based on construct of SCT to promote physical activity behavior must take into consideration the reinforcing the constructs that are stronger predictors of behavior can lead to more effective interventions. Regarding to self-efficacy to overcoming impediments and self-efficacy as the main factors in order to increase PA behavior in adolescent seems effective.   


This research is part of a PhD dissertation in health education and promotion at the Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran. The authors are grateful to the Research Department of Tarbiat Modarres University and all the participants who helped us, especially teachers in schools under research.

Conflict of interest statement

None declared.


  1. Farsad h. Regular physical activity and exercise. Tehran: Ministry of Health and Medical Education; 2010. [Persian]
  2. Lester Coleman, Louise Cox, Debi Roker. Girls and young womens participation in physical activity: psychological and social influences. Health Educ Res. 2008;23(4):633-647.
  3. World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: WHO: 2011.
  4. Asgari F, Rafei A, Azimi S, Rezanejad-Asl P, Heidarian-Miri H. I.R. Iran non-communicable diseases risk factors surveillance provincial report; 2009 [updated 24 May 2009; cited 4 March 2015]; Available from:   http://www.ncdinfobase.ir/files/docs/NCD_RFs_Provincial_report_2009-final(3).pdf .
  5. Coleman L, Cox L, Roker D. Girls and young womens participation in physical activity: psychological and social influences. Health Educ Res. 2008;23(4):633-647.
  6. Meester FD, Dyck DV, Bourdeaudhuij ID, Deforche B, Cardon G. Do psychosocial factors moderate the association between neighborhood walkability and adolescents physical activity? Soc Sci Med. 2013;81:1-9.
  7. Plotnikoff RC, Costigan SA, Karunamuni N, Lubans DR. Social cognitive theories used to explain physical activity behavior in adolescents: A systematic review and meta-analysis. Prev Med. 2013;56:245-253.
  8. Buchan D S, Ollis S, Thomas N E, Baker J S. Physical Activity Behaviour: An Overview of Current and Emergent Theoretical Practices. J Obes. 2012;2012:546459.
  9. Wolfe ME. An evaluation of an exercise adherence intervention using the social cognitive theory [PhD thesis]. Ohio: The Ohio State University; 2008.
  10. Haider T. Using social cognitive theory to predict exercise behavior among college students of south Asian descent at two large Midwestern universities [PhD thesis]. University of Cincinnati; 2011.
  11. Brochado AO, Brochado FO, Brito PO. Effects of personal, social and environmental factors on physical activity behavior among adults. Rev Port Saude Publica. 2010;28(1):7-18.
  12. Waltz CF, Strickland O, Lenz ER. Measurement in nursing and health research. Springer; 2010.
  13. Hajizadeh E, Asghari M. Statistical methods and analyses in health and biosciences: a research methodological approach using SPSS practical guide. Tehran: Publications of Academic Jihad Organization; 2011. [Persian]
  14. Soleymanian A. Evaluation of Theory-based Educational Intervention for Increasing Exercise to Prevent Osteoporosis in Women between 30 and Premenopause Age [PhD thesis]. Tehran: Tarbiat Modares University of Medical Sciences; 2014. [Persian]
  15. Banville D, Desrosiers P, Genet-Volet Y. Translating questionnaires and inventories using a cross-cultural translation technique. J Teach Phys Educ. 2000;19(3):374-387.
  16. Bazarganipour F, Ziaei S, Montazeri A, Faghihzadeh S, Frozanfard F. Psychometric properties of the Iranian version of modified polycystic ovary syndrome health-related quality-of-life questionnaire. Hum Reprod. 2012;27(9):2729-2736.
  17. IPAQ. Guidelines for data processing and analysis of the International Physical Activity Questionnaire (IPAQ)-short and long forms 2005 [updated April, 2014; cited 2 Aug, 2014]; Available from: http://www.ipaq.ki.se/scoring.pdf .
  18. Lee PH, Macfarlane DJ, Lam T, Stewart SM. Validity of the international physical activity questionnaire short form (IPAQ-SF): a systematic. Int J Behav Nutr Phys Act. 2011;8:115.
  19. Gholamnia Shirvani Z, Ghofranipour F, Gharakhanlou R, Kazemnejad A. Determinants of physical activity based on the theory of planned behavior in Iranian Military Staff's Wives: a path analysis. Glob J Health Sci. 2015:7(3):203-239.
  20. Rutkowski EM, Connelly CD. Obesity risk knowledge and physical activity in families of adolescents. J Pediatr Nurs. 2011;26:51-57.
  21. Haider T, Sharma M, Bernard A. Using social cognitive theory to predict exercise behavior among south Asian college students. J Community Med Health Educ. 2012;2:155.
  22. Dishman RK, Saunders RP, Motl RW, Dowda M, Pate RR. Self-efficacy moderates the relation between declines in physical activity and perceived social support in high school girls. J Pediatr Psyc. 2009;34(4):441-451.
  23. Duncan SC, Seeley JR, Gau JM, Strycker LS, Farmer RF. A latent growth model of adolescent physical activity as a function of depressive symptoms. Ment Health Phys Act. 2012;5:57-65.
  24. Pirasteh A, Hidarnia A, Asghari A, Faghihzadeh S, Ghofranipour F. Development and validation of psychosocial determinants measures of physical activity among Iranian adolescent girls. BMC Public Health. 2008;8(1):150.
  25. Ramirez E, Kulinna PH, Cothran D. Constructs of physical activity behaviour in children: The usefulness of Social Cognitive Theory. Psychol Sport Exerc. 2012;13(3):303-310.
  26. Edmonds ET. Osteoporosis knowledge, beliefs and behaviors of college students: utilization of the health belief model [PhD thesis]. University of Alabama; 2009.
  27. Soleymanian A, Niknami SH, Hajizadeh E, Shojaeizadeh D, Montazeri A. Development and validation of a health belief model based instrument for measuring factors influencing exercise behaviors to prevent osteoporosis in pre-menopausal women (HOPE). BMC Musculoskelet Disord. 2014:15:61.
  28. Mehta P. Social Cognitive theory as a predictor of dietary behavior and leisure time physical activity in middle aged Asian Indian women [MSc thesis]. University of Cincinnati; 2009.

JRHS Office:

School of Public Health, Hamadan University of Medical Sciences, Shaheed Fahmideh Ave. Hamadan, Islamic Republic of Iran

Postal code: 6517838695, PO box: 65175-4171

Tel: +98 81 38380292, Fax: +98 81 38380509

E-mail: jrhs@umsha.ac.ir