Measurement of Physical Activity Self-Efficacy in Adults With Obesity: A Latent Variable Approach to Explore Dimensionality, Temporal Invariance, and External Validity

in Journal of Sport and Exercise Psychology

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Nicholas D. MyersDepartment of Kinesiology, Michigan State University, East Lansing, MI, USA

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André G. BatemanDepartment of Kinesiology, Michigan State University, East Lansing, MI, USA

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Adam McMahonOffice of Institutional Culture, University of Miami, Coral Gables, FL, USA

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Isaac PrilleltenskySchool of Education and Human Development, University of Miami, Coral Gables, FL, USA

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Seungmin LeeDepartment of Kinesiology, Michigan State University, East Lansing, MI, USA

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Ora PrilleltenskySchool of Education and Human Development, University of Miami, Coral Gables, FL, USA

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Karin A. PfeifferDepartment of Kinesiology, Michigan State University, East Lansing, MI, USA

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Ahnalee M. BrincksHuman Development and Family Studies, Michigan State University, East Lansing, MI, USA

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DOI:
https://doi.org/10.1123/jsep.2021-0040
Keywords:
physical activity promotion; e-Health; m-Health; latent physical activity self-efficacy; self-efficacy theory
First Published Online:
18 Nov 2021
In Print:
Volume 43: Issue 6
Page Range:
497–513
Restricted access

The objective of this study was to improve the measurement of physical activity self-efficacy (PASE) in adults with obesity. To accomplish this objective, a latent variable approach was used to explore dimensionality, temporal invariance, and external validity of responses to a newly developed battery of PASE scales. Data (Nbaseline = 461 and N30 days postbaseline = 427) from the Well-Being and Physical Activity Study (ClinicalTrials.gov, identifier: NCT03194854), which deployed the Fun For Wellness intervention, were analyzed. A two-dimensional factor structure explained responses to each PASE scale at baseline. There was strong evidence for at least partial temporal measurement invariance for this two-dimensional structure in each PASE scale. There was mixed evidence that the effectiveness of the Fun For Wellness intervention exerted a direct effect on latent PASE in adults with obesity at 30 days postbaseline (i.e., external validity) of this two-dimensional structure.

Supplementary Materials

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    • Supplementary Table 3 (PDF 89 KB)
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  • Ainsworth, B.E., Bassett, D.R., Strath, S.J., Swartz, A.M., O’Brien, W.L., Thompson, R.W., Jones, D.A., Macera, C.D., & Kimsey, D.C. (2000). Comparison of three methods for measuring the time spent in physical activity. Medicine & Science in Sports & Exercise, 32, S457–S464. https://doi.org/10.1097/00005768-200009001-00004

    • Crossref
    • Search Google Scholar
    • Export Citation

  • American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing.

    • Search Google Scholar
    • Export Citation

  • American Psychological Association. (2020). Publication manual of the American Psychological Association (7th ed.).

  • Asparouhov, T., & Muthén, B.O. (2009). Exploratory structural equation modeling. Structural Equation Modeling, 16, 397–438. https://doi.org/10.1080/10705510903008204

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bandura, A. (1977). Self-efficacy: Towards a unifying theory of behavioral change. Psychological Review, 84, 191–215. https://doi.org/10.1037/0033-295x.84.2.191

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.

  • Bandura, A. (1997). Self-efficacy: The exercise of control. Freeman.

  • Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual Review of Psychology, 52, 1–26. https://doi.org/10.1146/annurev.psych.52.1.1

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Bandura, A. (2006). Guide for constructing self-efficacy scales. In F. Pajares, & T.C. Urdan (Eds.), Self-efficacy beliefs of adolescents (pp. 307–337). Information Age Publishing.

    • Search Google Scholar
    • Export Citation

  • Bauman, A.E., Reis, R.S., Sallis, J.F., Wells, J.C., Loos, R.J.F., & Martin, B.W. (2012). Correlates of physical activity: Why are some people physically active and others not? The Lancet, 380, 258–271. https://doi.org/10.1016/S0140-6736(12)60735-1

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Beauchamp, M.R., Crawford, K.L., & Jackson, B. (2019). Social cognitive theory and physical activity: Mechanisms of behavior change, critique, and legacy. Psychology of Sport and Exercise, 42, 110–117. https://doi.org/10.1016/j.psychsport.2018.11.009

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Byrne, B.M., Shavelson, R.J., & Muthén, B.O. (1989). Testing for equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456–466. https://doi.org/10.1037/0033-2909.105.3.456

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

  • Craig, C.L., Marshall, A.L., Sjöström, M., Bauman, A.E., Booth, M.L., Ainsworth, B.E., Pratt, M., Ekelund, U., Yngve, A., Sallis, J.F., & Oja, P. (2003). International physical activity questionnaire: 12-country reliability and validity. Medicine & Science in Sports & Exercise, 35, 1381–1395. https://doi.org/10.1249/01.MSS.0000078924.61453.FB

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Cronbach, L.J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. https://doi.org/10.1007/BF02310555

  • de Vries, H.J., Kooiman, T., van Ittersum, M., van Brussel, M., & de Groot, M. (2016). Do activity monitors increase physical activity in adults with overweight or obesity? A systematic review and meta-analysis. Obesity, 24, 2078–2091. https://doi.org/10.1002/oby.21619

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Feltz, D.L., & Chase, M.A. (1988). The measurement of self-efficacy and confidence in sport. In J. Duda (Ed.), Advancement in sport and exercise psychology measurement (pp. 63–78). Fitness Information Technology.

    • Search Google Scholar
    • Export Citation

  • Feltz, D.L., Short, S.E., & Sullivan, P.J. (2008). Self-efficacy in sport: Research and strategies for working with athletes, teams, and coaches. Human Kinetics.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Finney, S.J., & DiStefano, C. (2006). Nonnormal and categorical data in structural equation modeling. In R.C. Serlin (Series Ed.), G.R. Hancock, & R.O. Mueller (Vol. Eds.), Structural equation modeling: A second course (pp. 269–313). Information Age.

    • Search Google Scholar
    • Export Citation

  • Gourlan, M.J., Trouilloud, D.O., & Sarrazin, P.G. (2011). Interventions promoting physical activity among obese populations: A meta-analysis considering global effect, long-term maintenance, physical activity indicators and dose characteristics. Obesity Reviews, 12, e633–e645. https://doi.org/10.1111/j.1467-789X.2011.00874.x

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Graham, J.M., Guthrie, A.C., & Thompson, B. (2003). Consequences of not interpreting structure coefficients in published CFA research: A reminder. Structural Equation Modeling, 10, 142–153. https://doi.org/10.1207/S15328007SEM1001_7

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Guttman, L. (1954). A new approach to factor analysis: The radex. In P.F. Lazarsfeld (Ed.), Mathematical thinking in the social sciences (pp. 258–348). Columbia University Press.

    • Search Google Scholar
    • Export Citation

  • Hancock, G.R. (2001). Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct. Psychometrika, 66, 373–388. https://doi.org/10.1007/BF02294440

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hancock, G.R., & Mueller, R.O. (2001). Rethinking construct reliability within latent variable systems. In R. Cudeck, S.H.C. du Toit, & D. Sörbom (Eds.), Structural equation modeling: Past and present. A festschrift in honor of Karl G. Jöreskog (pp. 195–261). Scientific Software International, Inc.

    • Search Google Scholar
    • Export Citation

  • Hayashi, K., Bentler, P.M., & Yuan, K. (2007). On the likelihood ratio test for the number of factors in exploratory factor analysis. Structural Equation Modeling, 14, 505–526. https://doi.org/10.1080/10705510701301891

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hollis, S., & Campbell, F. (1999). What is meant by intention to treat analysis? Survey of published randomised controlled trials. BMJ, 319, 670–674. https://doi.org/10.1136/bmj.319.7211.670

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Hu, L., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55. https://doi.org/10.1080/10705519909540118

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jackson, B., Beauchamp, M.R., & Dimmock, J.A. (2020). Efficacy beliefs in physical activity settings: Contemporary debate and unanswered questions. In G. Tenenbaum & R.C. Eklund (Eds.), Handbook of sport psychology (4th ed., pp. 57–80). Wiley.

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Jöreskog, K.G. (1970). A general method for analysis of covariance structures. Biometrika, 57, 239–251. https://doi.org/10.2307/2334833

  • Lee, S., McMahon, A., Prilleltensky, I., Myers, N.D., Dietz, S., Prilleltensky, O., Pfeiffer, K.A., Bateman, A.G., & Brincks, A.M. (2020). Effectiveness of the fun for wellness online behavioral intervention to promote well-being actions in adults with obesity: A randomized controlled trial. Journal of Sport & Exercise Psychology, 43(1), 83–96. https://doi.org/10.1123/jsep.2020-0049

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Marsh, H.W., Hau, K.T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis testing approaches to setting cutoff values for fit indexes and dangers in overgeneralising Hu & Bentler’s (1999) findings. Structural Equation Modeling, 11, 320–341. https://doi.org/10.1207/s15328007sem1103_2

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Marsh, H.W., Lüdtke, O., Muthén, B., Asparouhov, T., Morin, A.J.S., Trautwein, U., & Nagengast, B. (2010). A new look at the big-five factor structure through exploratory structural equation modeling. Psychological Assessment, 22, 471–491. https://doi.org/10.1037/a0019227

    • Crossref
    • Search Google Scholar
    • Export Citation

  • McAuley, E. (1993). Self-efficacy and the maintenance of exercise participation in older adults. Journal of Behavioral Medicine, 16, 103–113. https://doi.org/10.1007/BF00844757

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Millsap, R.E. (2012). Statistical approaches to measurement invariance. Routledge.

  • Millsap, R.E., & Kwok, O.M. (2004). Evaluating the impact of partial factorial invariance on selection in two populations. Psychological Methods, 9, 93–115. https://doi.org/10.1037/1082-989x.9.1.93

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Millsap, R.E., & Yun-Tien, J. (2004). Assessing factorial invariance in ordered-categorical measures. Multivariate Behavioral Research, 39, 479–515. https://doi.org/10.1207/S15327906MBR3903_4

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Muthén, B.O. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indictors. Psychometrika, 49, 115–132. https://doi.org/10.1007/BF02294210

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Muthén, L.K., & Muthén, B.O. (1998–2017). Mplus user’s guide (8th ed.).

  • Myers, N.D., & Feltz, D.L. (2007). From self-efficacy to collective efficacy in sport: Transitional methodological issues. In G. Tenenbaum, & R.C. Eklund (Eds.), The handbook of sport psychology (3rd ed., pp. 799–819). Wiley. https://doi.org/10.1002/9781118270011.ch36

    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Feltz, D.L., & Wolfe, E.W. (2008). A confirmatory study of rating scale category effectiveness for the coaching efficacy scale. Research Quarterly for Exercise and Sport, 79, 300–311. https://doi.org/10.1080/02701367.2008.10599493

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Jin, Y., Ahn, S., Celimli, S., & Zopluoglu, C. (2015). Rotation to a partially specifed target matrix in exploratory factor analysis in practice. Behavior Research Methods, 47, 494–505. https://doi.org/10.3758/s13428-014-0486-7

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Myers, N.D., McMahon, A., Prilleltensky, I., Lee, S., Dietz, S., Prilleltensky, O., Pfeiffer, K.A., Bateman, A.G., & Brincks, A.M. (2020). Effectiveness of the fun for wellness online behavioral intervention to promote physical activity in adults with obesity: A randomized controlled trial. Journal of Medical Internet Research Formative Research, 4, Article e15919. https://doi.org/10.2196/15919

    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Prilleltensky, I., Hill, C.R., & Feltz, D.L. (2017). Well-being self-efficacy and complier average causal effect modeling: A substantive-methodological synergy. Psychology of Sport & Exercise, 30, 135–144. https://doi.org/10.1016/j.psychsport.2017.02.010

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Prilleltensky, I., Lee, S., Dietz, S., Prilleltensky, O., McMahon, A., Pfeiffer, K.A., Ellithorpe, M.E., & Brincks, A.M. (2019). Effectiveness of the fun for wellness online behavioral intervention to promote well-being and physical activity: Protocol for a randomized controlled trial. BMC Public Health, 19, 737. https://doi.org/10.1186/s12889-019-7089-2

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Prilleltensky, I., McMahon, A., Lee, S., Dietz, S., Prilleltensky, O., Pfeiffer, K. A., Bateman, A.G., & Brincks, A.M. (2020). Effectiveness of the fun for wellness online behavioral intervention to promote subjective well-being in adults with obesity: A randomized controlled trial. Journal of Happiness Studies, 22, 1905–1923. https://doi.org/10.1007/s10902-020-00301-0

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Myers, N.D., Prilleltensky, I., Prilleltensky, O., McMahon, A., Dietz, S., & Rubenstein, C.L. (2017). Efficacy of the fun for wellness online intervention to promote multidimensional well-being: A randomized controlled trial. Prevention Science, 18, 984–994. https://doi.org/10.1007/s11121-017-0779-z

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Raykov T, & Marcoulides G.A. (2019) Thanks coefficient alpha, we still need you. Educational and Psychological Measurement, 79, 200–210. https://doi.org/10.1177/0013164417725127

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Reis, R.S., Salvo, D., Ogilvie, D., Lambert, E.V., Goenka, S., & Brownson, R.C. (2016). Scaling up physical activity interventions across the globe: Stepping up to larger and smarter approaches to get people moving. The Lancet, 388, 1337–1348. https://doi.org/10.1016/S0140-6736(16)30728-0

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Rubenstein, C.L., Duff, J., Prilleltensky, I., Jin, Y., Dietz, S., Myers, N.D., & Prilleltensky, O. (2016). Demographic group differences in domain-specific well-being. Journal of Community Psychology, 44, 499–515. https://doi.org/10.1002/jcop.21784

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Saris, W.E., Satorra, A., & van der Veld, W. (2009). Testing structural equation models or detection of misspecifications? Structural Equation Modeling, 16, 561–582. https://doi.org/10.1080/10705510903203433

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Scarpa, M.P., Prilleltensky, I., McMahon, A., Myers, N.D., Prilleltensky, O., Lee, S., Pfeiffer, K.A., Bateman, A.G., & Brincks, A.M. (2021). Is fun for wellness engaging? Evaluation of user experience of an online intervention to promote well-being and physical activity. Frontiers in Computer Science, 3, Article 690389. https://doi.org/10.3389/fcomp.2021.690389

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Sörbom, D. (1974). A general method for studying differences in factor means and factor structure between groups. British Journal of Mathematical and Statistical Psychology, 27, 229–239. https://doi.org/10.1111/j.2044-8317.1974.tb00543.x

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Stuart, E.A., Perry, D.F., Le, H-N., & Ialongo, N.S. (2008). Estimating intervention effects of prevention programs: Accounting for noncompliance. Prevention Science, 9, 288–298. https://doi.org/10.1007/s11121-008-0104-y

    • Crossref
    • Search Google Scholar
    • Export Citation

  • Tudor-Locke, C., Brashear, M.M., Johnson, W.D., & Katzmarzyk, P.T. (2010). Accelerometer profiles of physical activity and inactivity in normal weight, overweight, and obese U.S. men and women. International Journal of Behavioral Nutrition and Physical Activity, 7, 60. https://doi.org/10.1186/1479-5868-7-60

    • Crossref
    • Search Google Scholar
    • Export Citation

  • U.S. Department of Health and Human Services. (2013). Managing overweight and obesity in adults: Systematic evidence review from the obesity expert panel.  https://www.nhlbi.nih.gov/sites/default/files/media/docs/obesity-evidence-review.pdf

    • Search Google Scholar
    • Export Citation

  • U.S. Department of Health and Human Services: 2018 Physical activity guidelines advisory committee. (2018). 2018 Physical activity guidelines advisory committee scientific report. https://health.gov/paguidelines/second-edition/report/

    • Search Google Scholar
    • Export Citation

  • U.S. Preventive Services Task Force. (2018). Behavioral weight loss interventions to prevent obesity-related morbidity and mortality in adults: United States preventive services task force recommendations. Journal of the American Medical Association, 320, 1163–1171. https://doi.org/10.1001/jama.2018.13022

    • Search Google Scholar
    • Export Citation

  • World Health Organization. (2018). Obesity and overweight fact sheet. http://www.who.int/mediacentre/factsheets/fs311/en/

  • Yates, A. (1987). Multivariate exploratory data analysis: A perspective on exploratory factor analysis. State University of New York Press.

    • Search Google Scholar
    • Export Citation

  • Yuan, K.H., & Bentler, P.M. (2004). On chi-square difference and z tests in mean and covariance structure analysis when the base model is misspecified. Educational and Psychological Measurement, 64, 737–757. https://doi.org/10.1177/0013164404264853

    • Crossref
    • Search Google Scholar
    • Export Citation
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