Logo
homeHome
toggle_offCompany ProfilegroupsBoards & Staffsworkspace_premiumMemberships & PartnersschoolAcademy of Journalismperson_addCareerslinkBlog(EN)emailContact Us
list_altOur JournalslightbulbInstruction for AuthorsbookmarkBrieflands PolicieshandshakePublish My Researchplay_circleJournal Management Systemcredit_cardArticle Processing Chargeszoom_inOpen Peer ReviewimagePublishing Services
menu_bookPublish My Book

IJ Psychiatry and Behavioral Sciences

IJPBS is the Official Journal of Mazandaran University of Medical Sciences

homeHome
play_arrowCurrent IssuelistAll Issuesformat_indent_increaseIn PresscheckAccepted ManuscriptssearchSearch
helpInstructions
starJournal InformationgroupsEditors & BoardsshareIndexing and Listing Sourcesshow_chartJournal Metricszoom_inOpen Peer Review (OPR)balancePublication Ethics and Publication Malpractice Statementmenu_bookReviewer and AE Registration FormemailSupportphoneContact Us
format_list_bulletedAPC
Authors GuideSubmit Manuscript

Outlines

https://doi.org/10.5812/ijpbs.12662

Development and Validation of Social Cognitive Theory Based Questionnaire for Physical Activity to Preventing Osteoporosis (PAQ-SCT)

Author(s):
Mahin NematollahiMahin Nematollahi1, Ahmad Ali EslamiAhmad Ali EslamiAhmad Ali Eslami ORCID2,*
1Student Research Center, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
2Department of Health Education, Faculty of Health, Isfahan University of Medical Sciences, Isfahan, Iran
IJ Psychiatry and Behavioral Sciences:Vol. 12, issue 3; e12662
Published online:Aug 01, 2018
Article type:Research Article
Received:May 06, 2017
Accepted:May 04, 2017
How to Cite:Nematollahi M, Eslami AA. Development and Validation of Social Cognitive Theory Based Questionnaire for Physical Activity to Preventing Osteoporosis (PAQ-SCT). Iran J Psychiatry Behav Sci. 2018;12(3):e12662. doi: https://doi.org/10.5812/ijpbs.12662

Abstract

Background:

Social cognitive theory is a suitable model that examines many factors associated with physical activity. Despite the importance of this issue, there is no evidence of a specific questionnaire for assessing physical activity in Iranian women.

Objectives:

This article reports the development and psychometric evaluation process of a physical activity questionnaire among Iranian women.

Methods:

In 2016, this psychometric study was carried out on 400 women aged less than 50 years old from 10 health centers recruited by clustering sampling in Isfahan. After reviewing numerous texts, a questionnaire was developed and necessary reforms, in accordance with the principles of translation and cultural adaptation, were applied in a research committee. Then, content validity confirmed by an expert panel as well as face validity was evaluated in a pilot study. Construct validity was conducted using exploratory and confirmatory factor analysis. Reliability was also measured using Cronbach’s alpha coefficient and internal consistency method. Scales used in this study included self-efficacy, outcome expectations, social support, and self-regulation.

Results:

Internal consistency was found 0.90. In the exploratory factor analysis, four-factor models with a total variance of 80.9% were identified (P < 0.001). The CFA results (CMIN = 276/874, DF = 166, P < 0.001, CFI = 0.967, RMSEA = 0.061) represent the suitability and acceptability of a model based on social cognitive theory.

Conclusions:

Due to good values of validity and reliability, the questionnaire was developed based on social cognitive theory, its use is recommended to assess physical activity in Iranian women.

Keywords
Physical Activity
Questionnaires
Reliability and Validity

1. Background

Osteoporosis is a major health concern in which bones become weak and fragile, leading to enormous physical, psychological, economic, and social consequence (1). More than half of the women over 45 are affected with this disease (2). The most important way to prevent osteoporosis is physical activity. Physical activity causes strengthened bones, maintained balance, reduced falling, and reduced bone fractures (3, 4). Despite evidence regarding the benefits of exercise, studies have shown that the physical activity rate in women is highly undesirable (5, 6). According to the world health organization in 2010, about 27% of women had no physical activity and a total of 35% of them in high-income countries and 24% of them in low-income countries had physical inactivity (7). The prevalence of sedentary in Iranian women is 76.3% (8). Women’s participation in sports activities is affected by personal, environmental, and behavioral factors (9, 10). Several studies have been conducted to examine the factors explaining the physical activity and different questionnaires have been developed, which is briefly mentioned:
Sechrist et al. (11), developed the exercise benefits/barriers scale (EBBS). It includes two parts: exercise benefits (29 items) and exercise barriers (14 items). It was evaluated in 650 adults and its reliability and validity have been proven. Cronbach’s alpha was obtained as 0.952 for the whole questionnaire. The Internal correlation coefficient was 0.77. In the exploratory factor analysis (EFA); 9 factors with variance of 64/9% were identified (11). A questionnaire was developed by Steinhardt and Dishman known as outcome expectancies scale (OESE) and it was evaluated on 243 students. It includes two parts: exercise benefits (12 items) and exercise barriers (14 items). The Cronbach’s alpha coefficient for the whole questionnaire was 0.78 (12). the stage of exercise change questionnaire (SECQ) was developed by Marcus. It contains the components of balance of decision-making, barriers, benefits, and self-efficacy and it was examined on 778 men and women. Its Cronbach’s alpha coefficient was obtained 0.82 (13, 14). Physical activity-related self-regulation questionnaire (PARS-43) was developed by Petosa. This questionnaire has 43 items used for self-regulation assessment of adults. Its Cronbach’s alpha coefficient was obtained as 0.96 (15). Self-efficacy assessment and outcome expectancy questionnaire was developed by Clark and it was examined in 729 patients. Variance of self-efficacy was 31% and variance of outcome expectation was 13% (16). Outcome Expectancies Scale for Exercise (OEE) was developed to measure the outcome expectations by Resnick and it was evaluated in 182 old individuals. It includes two parts: exercise benefits (5 items) and exercise barriers (4 items). Reliability and the validity of this tool have been proven (17). Self-Efficacy for Exercise Scale (SEE) was developed by Resnick. It includes 9 items and it was evaluated in older people. Its internal validity was obtained as 0.92. The confirmatory factor analysis (CFA) was significant and acceptable (18). An exercise barriers’ questionnaire was developed by Andajani and it was investigated in a community-based study of 445 women. It includes three parts: Personal barriers (3 items), social barriers (3 items), and environmental barriers (5 items). Cronbach’s alpha of the tool was higher than 0.7 (19). Self-efficacy for exercise scale (SSE) was developed by Kroll to assess self-efficacy. It includes 15 items. Cronbach’s alpha of the tool was 0.72 - 0/83 and total variance was 53% (20). Multidimensional outcome expectations for exercise scale (MOES) was developed by Wojcicki. It assesses multi-dimensional expectations of exercise in older people. It includes three parts: physical (6 items), social (4 items), and self-assessment (5 items). Its reliability and the validity were confirmed using EFA and CFA (21).
Studied tools explained limited dimensions of factors related to physical activity. In some studies, reliability and validity stages have not been stated clearly and precisely (12) or the number of questions was high (11) and localization of these tools has not been conducted in Iran (11). Therefore, it is necessary to develop an appropriate tool to assess factors explaining the physical activity. Social-cognitive theory of Bandura is a model with a broad approach, examining many factors related to physical activity. Based on this theory: cognitive, environmental and behavioral factors have three-way interrelationships. The individual’s behavior is shaped by the perception of the environment. The environment influences the individual’s behavior (22).

2. Objectives

The aim of the present study is the development and psychometric assessment of an appropriate questionnaire to assess constructs of Social-cognitive theory in explaining physical activity related to preventing osteoporosis.

3. Materials and Methods

3.1. Design and Sites

This is a psychometric study that was conducted in Isfahan city after gaining ethical approval from the research deputy of Isfahan University of Medical Sciences (Grant NO. 395203) from May to September 2016.

3.2. Participants

In psychometric studies, the sample size per item is 15 (23, 24) considering the number of questionnaire parameters and the possibility of loss, 25%, 400 samples recruited from women aged less than 50 years. At first, the city centers covered by The Health Center in Isfahan were selected randomly, then, 10 centers from 25 urban centers were selected by clustering sampling and sample size was obtained based on the proportional to size sampling for each center. After familiarization with samples and informed consent, questionnaires were completed. The inclusion criteria for this study were informed consent and ability to respond to the questions. The exclusion criteria were the physical and mental disability as well as unwillingness to complete the questionnaires.

3.3. Measurement Instrument

The questionnaire used in this study (PAQ-SCT) consists of three parts as follows:
1. Tools to assess demographic factors: it consists of 10 questions regarding age, education, marital status, employment status, and income level.
2. PAQ-SCT: Tools to assess social cognitive theory constructs related to physical activity and it includes four parts: self-efficiency: (14 items), outcome expectations (9 items), social support (8 items), and self-regulation (8 items). In total, 39 questions were developed. Scoring range of all of the questions is based on a 10-point Likert.
3. Tools to assess physical activity: standard questionnaire of physical activity was used in this regard. The international physical activity questionnaire (IPAQ) was used to determine appropriate levels of physical activity among adults aged 15 to 69 years (25), and its validity and reliability have been reported (26). According to its instruction, people are classified into three groups in terms of physical activity: low activity (0 - 599 MET-min/week) of moderate activity (600 - 3000 MET-min/week) and intense activity (greater than 3000 MET-min/week) (25).

3.3.1. Process of Development of PAQ-SCT and Evaluation of Validity and Reliability

After reviewing the literature and studying questionnaires used in papers and confirming the research team, 38 questionnaires were selected. Then, it was examined and necessary reforms were applied by 5 experts to adapt it linguistically and culturally with target population by observing the translation principles and cultural adaptation with the Persian language (27). Validity and reliability of the questionnaire were determined in three steps: Step 1: developed items (38 items) were evaluated to determine the content validity index (CVI) and content validity ratio (CVR) was evaluated by a panel of 20 health experts. Acceptance criterion for each item was based on CVI higher than 0.79 and CVR (in accordance with the Lawshe’s CVR) higher than 0.42 (28). At the stage of examining CVI and CVR, 19 items were deleted: 9 items from the structure of self-efficacy, 4 items from the structure of outcome expectations, and 3 items from the structure of social support and self-regulation. Finally, 20 questions were confirmed. Step 2: In a pilot study, questionnaires were given to 20 women similar to the target population to determine the face validity and impact score was calculated that the impact score of all questions was higher than 1.5 and 20 items were selected (Table 1). Step 3: questionnaires were evaluated in a cross-sectional study in a sample of 400 women.
Table 1.Items of the Development and Psychometric of a PAQ-SCT for Iranian Women
Items SubjectItems of Questionnaire
se11.I can do exercises such as walking and jogging twice a week
se22.I can do exercise at least an hour a day
se33.I can do exercise, even if I am tired
se44.I can do exercise, even if I am under stress
se55.I can do exercise, even if I have no exercise facilities
oe16.Exercise can increase my energy, vitality and freshness
oe27.Exercise causes fatigue and pain in the muscles
oe38.Exercise reduces the risk of diseases such as osteoporosis and depression
oe49.Exercise is an impediment to perform my everyday tasks
oe510.Exercise is a waste of time
ss111.My family and friends encourage me to do exercise
ss212.My family provides exercise facilities for me
ss313.My family and friends prevent exercising
ss414.My family and friends do exercise with me
ss515.My family and friends are satisfied with my exercise
sr116.I have a regular weekly program for exercise
sr217.I adjust my exercise program in accordance with my life and career
sr318.I write my exercise program in a notebook
sr419.If there is a problem in the implementation of the exercise program, I change it
sr520.I am diligent and consistent in implementing my exercise program

Abbreviations: (oe1-oe5); outcome expectations, (se1-se5); self-efficacy, (sr1-sr5); self –regulation, (ss1-ss5); social support.

3.4. Data Analysis

Using statistical SPSS.v20 and Amos Grafic.v23 software, data were analyzed and descriptive tests, Cronbach’s alpha coefficient, correlation, variance, EFA, CFA were calculated. EFA was evaluated by using principal component analysis (PCA) to extract the factors and varimax method to rotate the factors. We also used Kaiser-Meyer-Olkin (KMO) measure and Bartlett test to evaluate the sampling adequacy. The best structure was considered to be the one with the eigenvalue greater than 1 and factor loading equal to or greater than 0.4 (29, 30).
The CFA model using the robust maximum likelihood was used to estimate the model parameter. The model was considered acceptable if CMIN/DF was between 1 and 5, CFI (comparative fit index) was greater than 0.8, parsimonious comparative fit index (PCFI) was more than 0.6, Tucker-Lewis Index (TLI) was more than 0.9, root mean squared error of approximation (RMSEA) was < 0.05 good fit or between 0.05 and 0.08 adequate fit (29, 30).

4. Results

The number of participants in the study was 400 people, 40 of them were excluded due to illness, incapacity, or unwillingness to complete the questionnaires, and finally 360 samples were included. The mean age of participants was 33.67 (mean = 33/67, SD = 8/353), (range = 14 - 50). The main characteristics of participants are shown in Table 2.
Table 2.Characteristics of Women Who Participated in Study (N = 360)
Groups VariablesFrequency (No.)Percent (%)
Years of education
Illiterate51.4
The ability to read and write133.6
Primary school3610
Middle & high school4913.6
Diploma14540.3
Collegiate11231.1
Marriage status
Marriage31487.2
Single3610
Widow61.7
Divorced41.1
Job status
Employed6818.9
Unemployed29281.1
Income status
Little3810.6
Moderate20556.9
Good10027.8
Excellent174.7
The results of the physical activity of participants (mean = 934.33, SD = 1051.598) based on the IPAC questionnaire and MET min/week criterion are shown in Table 3.
Table 3.The Results of the Physical Activity of Women Who Participated in Study (N = 360)
Total Physical ActivityFrequency (No.)Percent (%)
Low16846.7
Intermediate17849.4
High143.9

4.1. Items Analysis

In total, 20 items were considered in the questionnaire. Items 1 to 5 related to self-efficiency, items 6 to 10 related to outcome expectations, items 11 to 15 related to social support, and items 16 to 20 related to self-regulation. Based on the information contained in Table 4 and as a correlation coefficient of items was higher than 0.3 (P ≤ 0.005) and the skewness of items was less than 1.96, items were not deleted.
Table 4.Item’s Total Statistics of PAQ-SCT about Physical Activity of Women Who Participated in Study
Items SubjectMean Score of ItemStd. DeviationSkewnessTotal CorrelationSquared Multiple Correlation
se15.413.1730.1410.6350.721
se24.893.2810.3170.6440.745
se34.032.8620.5760.6300.803
se44.333.0700.5090.6000.783
se55.383.1850.0720.6180.751
oe18.442.516-10.6590.4760.811
oe27.342.383-10.0910.3940.724
oe38.422.606-10.6950.3820.814
oe47.072.386-0.9150.4470.703
oe57.462.533-10.1260.4070.723
ss16.513.086-0.3090.5710.748
ss25.573.1660.0150.5890.739
ss36.582.872-0.2180.5230.676
ss45.082.9040.1230.6350.743
ss55.913.047-0.1040.6530.704
sr14.093.2670.7270.7460.800
sr24.683.3370.4350.6840.765
sr32.892.8311.4150.5050.513
sr44.203.2680.6160.6090.654
sr53.973.1740.7380.6880.755

Abbreviations: (oe1-oe5); outcome expectations, (se1-se5); self-efficacy, (sr1-sr5); self –regulation, (ss1-ss5); social support.

4.2. Reliability

The internal consistency and split-half method were used in order to examine the reliability of the scale. Cronbach’s alpha of the whole questionnaire was 0.919 that reflects the suitability of translation and internal consistency of the questionnaire. The internal consistency of the separate factors was also good and ranged from 0.925 to 0.946 (Table 5).
Table 5.Results of Exploratory Factor Analysis Extracted Factors for Items of a PAQ-SCT of Women Who Participated in Studya
Items SubjectSelf-EfficacyOutcome ExpectationsSocial SupportSelf-Regulation
se10.855.........
se20.856.........
se30.885.........
se40.886.........
se50.882.........
oe1...0.908......
oe2...0.893......
oe3...0.925......
oe4...0.871......
oe5...0.889......
ss1......0.891...
ss2......0.877...
ss3......0.863...
ss4......0.859...
ss5......0.819...
sr1.........0.794
sr2.........0.830
sr3.........0.782
sr4.........0.836
sr5.........0.848
Percentage of variance39.78218.09213.7269.302
Cronbach’s alpha0.9460.9450.9380.925

Abbreviations: (oe1-oe5); outcome expectations, (se1-se5); self-efficacy, (sr1-sr5); self –regulation, (ss1-ss5); social support.

a ... Not applicable: is less than 0.3

4.3. Factor Analysis

For statistical analysis, the samples (n = 360) were randomly divided into two. EFA was performed on a calibration sample (n1 = 180) and the CFA was performed on a validation sample (n2 = 180).

4.3.1. EFA

KMO index value (Kaiser-Meyer-Olkin index) was equal to 0.917, indicating the adequacy of the sample and Bartlett’s sphericity test results were (Bartlett’s x2 = 4139, df = 120, P < 0.001), which indicates the factor analysis is appropriate to analyze the data. EFA was performed by Promax method, cutoff point = 0.4, and eigenvalues = 1, and a four-factor model with total variance of 80.9% was detected (Table 5).

4.3.2. CFA

The CFA results showed that the measurement model has a good fit with the assumed model, and indicators are significant within the acceptable range. CFA results showed that self-regulation is the most important factor in predicting physical activity (Figure 1).
Second-order model (CFA) [CMIN = 276.874, DF = 166, CMIN/DF = 1.668, CFI = 0.946, PCFI = 0.967, TLI = 0.962, RMSEA = 0.061 (LO-HI = 0.048 - 0.074)]
Figure 1.

Second-order model (CFA) [CMIN = 276.874, DF = 166, CMIN/DF = 1.668, CFI = 0.946, PCFI = 0.967, TLI = 0.962, RMSEA = 0.061 (LO-HI = 0.048 - 0.074)]

5. Discussion

Analyzing and explaining health-related behaviors and related factors require appropriate instruments for measurement. One of these tools is the questionnaires, which is particularly important in science, health education (31, 32). Several questionnaires have been developed and used so far to measure social cognitive theory constructs to explain physical activity. The results showed the questionnaire developed in this study for psychometric evaluation of social cognitive theory constructs related to physical activity in women has acceptable reliability and validity. The strength of this study is an appropriate number of samples (n = 360) to the target group. The developed questionnaire is based on a theory in which four important constructs of social cognitive theory were used, while in most studies, one or two constructs of one model has been examined (20, 21). In this study, we tried to fully state the validity and reliability of tools stages clearly and completely. Reliability and validity of questionnaires and psychometric evaluation procedures have not been clearly and completely stated, and they reported only the results of previous papers (33, 34). One of the main features of a questionnaire is its compliance with cultural, linguistic, and local conditions of the target population. Accordingly, this study examined questionnaires in terms of observing the translation principles and cultural adaptability with the Persian language in a committee consisting of 5 experts. This issue is usually overlooked in other studies (35, 36). To validate the questionnaire and to assess CVI and CVR in this study, the views of 20 experts from the fields of health education were used. This could increase the scientific validity of the questionnaire, while views of less number of experts have been used in most studied related to physical activity (20, 37). The results of studies conducted by Ievers-Landis and Rovniak have identified social cognitive theory as an appropriate model to explain physical activity (33, 38). Cronbach’s alpha of the PAQ-SCT was equal to 0.919 (0.925 - 0.949), which was very appropriate (39). The results of this study are in line with the results of other studies, that consider Cronbach’s alpha reliability, higher than 0.7 as sign of scientific validity of the questionnaire (36, 40). In this study, four scales of social cognitive theory were examined where Cronbach’s alpha of all was higher than 0.9 (Table 5). The results of similar studies could confirm the reliability of the questionnaire in this study (36, 41). In this study, self-regulation (R2 = 0.97) was the most important predictor of physical activity. In studies conducted by Khani Jeyhuni and Wolfe, self-regulation has been introduced as the most important predictor of physical activity (42, 43). Additionally, the Tan study results showed that self-regulation is one of the most important factors in physical activity (44). Consistency of results of this study with mentioned studies shows that four scales developed to measure physical activity have appropriate and acceptable validity and reliability.
Limitations of the study include the large number of questions in the questionnaire, responding to the questions in the form of self-reporting, and short time of the research.

5.1. Conclusion

The present study represents that the reliability and validity of the PAQ-SCT developed to measure physical activity with the application of social cognitive theory is acceptable. Due to cultural and linguistic adaptation and the use of an ecological model to investigate individual, behavioral, and environmental variables, this questionnaire is recommended to assess physical activity, and it is necessary that further psychometric studies be conducted in this regard.

Acknowledgments

Footnotes

References

  • 1.
    Kanis JA, McCloskey EV, Johansson H, Cooper C, Rizzoli R, Reginster JY, et al. European guidance for the diagnosis and management of osteoporosis in postmenopausal women. Osteoporos Int. 2013;24(1):23-57. [PubMed ID: 23079689]. [PubMed Central ID: PMC3587294]. https://doi.org/10.1007/s00198-012-2074-y.
  • 2.
    Khoshnood ZA. comparative survey the effect of education based on health belief model to osteoporotic and non-osteoporotic mothers for the use of osteoporosis preventive behaviors of their daughters [dissertation]. Tarbiat Modarres University Medical Sciences; 2011.
  • 3.
    Tan AM, LaMontagne AD, English DR, Howard P. Efficacy of a workplace osteoporosis prevention intervention: a cluster randomized trial. BMC Public Health. 2016;16(1):859. [PubMed ID: 27552840]. [PubMed Central ID: PMC4995796]. https://doi.org/10.1186/s12889-016-3506-y.
  • 4.
    Yuan LQ, Lin X, Xiong D, Peng YQ, Sheng ZF, Wu XP, et al. Epidemiology and management of osteoporosis in the People’s Republic of China: current perspectives. Clinical Interventions in Aging. 2015:1017. https://doi.org/10.2147/cia.s54613.
  • 5.
    Olsen J, Bertollini R, Victora C, Saracci R. Global response to non-communicable diseases--the role of epidemiologists. Int J Epidemiol. 2012;41(5):1219-20. [PubMed ID: 23045194]. https://doi.org/10.1093/ije/dys145.
  • 6.
    Heinrich KM, Jokura Y, Maddock J. Exercise self-efficacy and social norms as psychological predictors of exercise behavior. Athletic Insight: Online J Sport Psychol. 2008;10.
  • 7.
    World Health Organization. Levels of insufficient physical activity. Physical activity. WHO; 2016. Available from: http://www.who.int/mediacentre/factsheets/fs385.
  • 8.
    Hazavehei SMM, Asadi Z, Hassanzadeh A, Shekarchizadeh P. Comparing the effect of two methods of presenting physical education Π course on the attitudes and practices of female Students towards regular physical activity in Isfahan University of Medical Sciences. Iranian Journal of Medical Education. 2008;8(1):121-31.
  • 9.
    Brochado A, Oliveira-Brochado F, Brito PQ. Effects of personal, social and environmental factors on physical activity behavior among adults. Revista Portuguesa de Saúde Pública. 2010;28(1):7-17.
  • 10.
    Ferreira I, van der Horst K, Wendel-Vos W, Kremers S, van Lenthe FJ, Brug J. Environmental correlates of physical activity in youth ? a review and update. Obesity Reviews. 2007;8(2):129-54. https://doi.org/10.1111/j.1467-789X.2006.00264.x.
  • 11.
    Sechrist KR, Walker SN, Pender NJ. Development and psychometric evaluation of the exercise benefits/barriers scale. Res Nurs Health. 1987;10(6):357-65. [PubMed ID: 3423307].
  • 12.
    Steinhardt MA, Dishman RK. Reliability and validity of expected outcomes and barriers for habitual physical activity. J Occup Med. 1989;31(6):536-46. [PubMed ID: 2786559].
  • 13.
    Marcus BH, Selby VC, Niaura RS, Rossi JS. Self-efficacy and the stages of exercise behavior change. Research quarterly for exercise and sport. 1992;63(1):60-6.
  • 14.
    Marcus BH, Rakowski W, Rossi JS. Assessing motivational readiness and decision making for exercise. Health Psychol. 1992;11(4):257-61. [PubMed ID: 1396494].
  • 15.
    Petosa PS. Use of social cognitive theory to explain exercise behavior among adults [dissertation]. The Ohio State University; 1993.
  • 16.
    Clark DO, Nothwehr F. Exercise Self-Efficacy and its Correlates among Socioeconomically Disadvantaged Older Adults. Health Education & Behavior. 2016;26(4):535-46. https://doi.org/10.1177/109019819902600410.
  • 17.
    Resnick B, Zimmerman SI, Orwig D, Furstenberg AL, Magaziner J. Outcome expectations for exercise scale: utility and psychometrics. J Gerontol B Psychol Sci Soc Sci. 2000;55(6):S352-6. [PubMed ID: 11078112].
  • 18.
    Resnick B, Jenkins LS. Testing the reliability and validity of the self-efficacy for exercise scale. Nursing research. 2000;49(3):154-9.
  • 19.
    Andajani-Sutjahjo S, Ball K, Warren N, Inglis V, Crawford D. Perceived personal, social and environmental barriers to weight maintenance among young women: A community survey. Int J Behav Nutr Phys Act. 2004;1(1):15. [PubMed ID: 15462679]. [PubMed Central ID: PMC524367]. https://doi.org/10.1186/1479-5868-1-15.
  • 20.
    Kroll T, Kehn M, Ho PS, Groah S. The SCI Exercise Self-Efficacy Scale (ESES): development and psychometric properties. Int J Behav Nutr Phys Act. 2007;4:34. [PubMed ID: 17760999]. [PubMed Central ID: PMC2034591]. https://doi.org/10.1186/1479-5868-4-34.
  • 21.
    Wojcicki TR, White SM, McAuley E. Assessing outcome expectations in older adults: the multidimensional outcome expectations for exercise scale. J Gerontol B Psychol Sci Soc Sci. 2009;64(1):33-40. [PubMed ID: 19181688]. [PubMed Central ID: PMC2654993]. https://doi.org/10.1093/geronb/gbn032.
  • 22.
    Bandura A. Health Promotion by Social Cognitive Means. Health Education & Behavior. 2016;31(2):143-64. https://doi.org/10.1177/1090198104263660.
  • 23.
    Ghasemi V. Structural Equation Modeling in social researches using Amos Graphics. Tehran Jameeshenasan: SAGE Publications. 2011:76-108. https://doi.org/10.4135/9781526402257.n4.
  • 24.
    Pearson RH, Mundform DJ. Recommended Sample Size for Conducting Exploratory Factor Analysis on Dichotomous Data. Journal of Modern Applied Statistical Methods. 2010;9(2):359-68. https://doi.org/10.22237/jmasm/1288584240.
  • 25.
    Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9 Suppl):S498-504. [PubMed ID: 10993420].
  • 26.
    Deng HB, Macfarlane DJ, Thomas GN, Lao XQ, Jiang CQ, Cheng KK, et al. Reliability and validity of the IPAQ-Chinese: the Guangzhou Biobank Cohort study. Med Sci Sports Exerc. 2008;40(2):303-7. [PubMed ID: 18202571]. https://doi.org/10.1249/mss.0b013e31815b0db5.
  • 27.
    Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine. 2000;25(24):3186-91.
  • 28.
    Hajizadeh E, Asghari M. Statistical methods and analyses in health and biosciences a research methodological approach. Tehran: Jahade Daneshgahi Publications; 2011. Persian.
  • 29.
    Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal. 1999;6(1):1-55. https://doi.org/10.1080/10705519909540118.
  • 30.
    Bentler PM. Comparative fit indexes in structural models. Psychol Bull. 1990;107(2):238-46. [PubMed ID: 2320703].
  • 31.
    Artino AR, La Rochelle JS, Dezee KJ, Gehlbach H. Developing questionnaires for educational research: AMEE Guide No. 87. Med Teach. 2014;36(6):463-74. [PubMed ID: 24661014]. [PubMed Central ID: PMC4059192]. https://doi.org/10.3109/0142159X.2014.889814.
  • 32.
    Glanz K, Rimer BK, Viswanath K. Health Behavior and Health Education: Theory, Research, and Practice. John Wiley & Sons; 2008.
  • 33.
    Rovniak LS, Anderson ES, Winett RA, Stephens RS. Social cognitive determinants of physical activity in young adults: A prospective structural equation analysis. Ann Behv Med. 2002;24(2):149-56. https://doi.org/10.1207/s15324796abm2402_12.
  • 34.
    Awadalla NJ, Aboelyazed AE, Hassanein MA, Khalil SN, Aftab R, Gaballa ,I, et al. Assessment of physical inactivity and perceived barriers to physical activity among health college students, south-western Saudi Arabia. East Mediterr Health J. 2014;20(10):596-604. [PubMed ID: 25356690].
  • 35.
    Shahbo GMAEM, El-Rahman MA, El-Mowafy R. Evaluation of Knowledge and Self-Efficacy about Osteoporosis Perception among Females in the Faculty of Nursing in Port-Said, Egypt. International Journal of Caring Sciences. 2016;9(1):72.
  • 36.
    Ardestani M, Niknami S, Hidarnia A, Hajizadeh E. Predictors of Physical Activity among Adolescent Girl Students Based on the Social Cognitive Theory. J Res Health Sci. 2015;15(4):223-7. [PubMed ID: 26728907].
  • 37.
    Soleymanian A, Niknami S, 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. [PubMed ID: 24581300]. [PubMed Central ID: PMC3996026]. https://doi.org/10.1186/1471-2474-15-61.
  • 38.
    Ievers-Landis CE, Burant C, Drotar D, Morgan L, Trapl ES, Kwoh CK. Social support, knowledge, and self-efficacy as correlates of osteoporosis preventive behaviors among preadolescent females. J Pediatr Psychol. 2003;28(5):335-45. [PubMed ID: 12808010].
  • 39.
    Tavakol M, Dennick R. Making sense of Cronbach's alpha. Int J Med Educ. 2011;2:53-5. [PubMed ID: 28029643]. [PubMed Central ID: PMC4205511]. https://doi.org/10.5116/ijme.4dfb.8dfd.
  • 40.
    Evenson AL, Sanders GF. Determination of the validity and reliability of a modified osteoporosis health belief scale and osteoporosis self-efficacy scale to include vitamin D. Calif J Health Promot. 2015;13(2):85-96.
  • 41.
    Anderson ES, Wojcik JR, Winett RA, Williams DM. Social-cognitive determinants of physical activity: the influence of social support, self-efficacy, outcome expectations, and self-regulation among participants in a church-based health promotion study. Health Psychol. 2006;25(4):510-20. [PubMed ID: 16846326]. https://doi.org/10.1037/0278-6133.25.4.510.
  • 42.
    Khani Jeihooni A, Hidarnia A, Kaveh MH, Hajizadeh E, Gholami T. Survey of osteoporosis preventive behaviors among women in Fasa: The Application of the Health Belief Model and Social Cognitive Theory. ISMJ. 2016;19(1):48-62.
  • 43.
    Wolfe ME. An Evaluation of an Exercise Adherence Intervention Using the Social Cognitive [dissertation]. The Ohio State University; 2008.
  • 44.
    Tan AM, LaMontagne AD, Sarmugam R, Howard P. A cluster-randomised, controlled trial to assess the impact of a workplace osteoporosis prevention intervention on the dietary and physical activity behaviours of working women: study protocol. BMC Public Health. 2013;13(1). https://doi.org/10.1186/1471-2458-13-405.
Import into EndNoteImport into BibTex
Indexed in
logoScopus
Crossmark
Crossmark
Checking
Share on
Comments
Number of Comments:0
Cited by
Metrics
Licensing and reuse information

Ordering Reprints

Articles are published under the Creative Commons license stated on each article. No permission or royalty fee is required for uses permitted by that license. CCC handles optional bulk and customized reprint orders. Any quotation covers production and delivery services only, not copyright permission. > Request Reprints from CCC 

Search Relations

Author(s):

Related Articles

Related Article in PubMed

Related Article in Google Scholar

Create Citation Alert via Google Reader