Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-25T17:29:36.440Z Has data issue: false hasContentIssue false
  • English
  • Français

Development and Validation of the Theory of Planned Behavior Questionnaire in Physical Activity

Published online by Cambridge University Press:  10 January 2013

Sonia Tirado González ,
Mª Carmen Neipp López ,
Yolanda Quiles Marcos  and
Jesús Rodríguez-Marín
Sonia Tirado González
Affiliation:
Universidad Miguel Hernández (Spain)
Mª Carmen Neipp López*
Affiliation:
Universidad Miguel Hernández (Spain)
Yolanda Quiles Marcos
Affiliation:
Universidad Miguel Hernández (Spain)
Jesús Rodríguez-Marín
Affiliation:
Universidad Miguel Hernández (Spain)
*
Correspondence concerning this article should be addressed to Mª Carmen Neipp López. Departamento de Psicología de la Salud. Universidad Miguel Hernández. Avda. de la Universidad s/n, Edificio Altamira. 03202 Elche – Alicante (Spain). E-mail: neipp@umh.es
Get access Rights & Permissions [Opens in a new window]

Abstract

The Theory of Planned Behavior (TPB) is one of the main theoretical models in the study of the different variables, which influence in the practise of physical activity. The aim in this study was to develop a questionnaire based on TPB in physical activity context providing evidence for the validity of the obtained measures. The instrumental project included three independent studies. The first study entailed the construction and qualitative assessment of the items. In the second study, the analysis of factorial structure was performed by means of exploratory measures, and it showed that the reliability of measures was adequate. The third study provided evidence on the dimensionality of the scale. The confirmatory factorial analysis guaranteed the stability of factorial structure proposed by the TPB and provided evidence for the internal validity of the inventory. Moreover, this study provided evidence of its external validity.

La Teoría de la Conducta Planeada (TCP) es uno de los modelos teóricos más empleados para conocer las diferentes variables que influyen en la realización de ejercicio físico. El objetivo en este trabajo fue elaborar un cuestionario basado en la TCP en el contexto del ejercicio físico y aportar evidencias sobre la validez de sus mediciones. El trabajo instrumental incluyó tres estudios independientes. El primer estudio consistió en la elaboración y evaluación cualitativa de los ítems. En el segundo estudio se analizó la estructura factorial mediante procedimientos exploratorios y se mostró que la fiabilidad de las mediciones era adecuada. El tercer estudio aportó evidencias sobre la dimensionalidad del inventario. El análisis factorial confirmatorio avaló la estabilidad de la estructura factorial propuesta por la TCP, así como aportó evidencias de validez interna del instrumento. También se aportan evidencias de su validez externa.

Keywords

theory of planned behaviorphysical exerciseinstrumental studyvalidationteoría conducta planeadaejercicio físicoestudio instrumentalvalidación
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 15 , Issue 2 , July 2012 , pp. 801 - 816
Copyright
Copyright © Cambridge University Press 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In Kuhi, J. & Beckmann, J. (Eds.), Action-control: From cognition to behavior (pp.11–39). Heidelberg, Germany: Springer.CrossRefGoogle Scholar
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. http://dx.doi.org/10.1016%2F0749-5978%2891%2990020-TCrossRefGoogle Scholar
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Nueva York, NY: Prentice Hall.Google Scholar
Anderson, E. S., Wojcik, J. R., Winett, R. A., & Williams, D. M. (2006). 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 Psychology, 25, 510–520. http://dx.doi.org/10.1037%2F0278-6133.25.4.510CrossRefGoogle Scholar
Baessler, J., & Schwarzer, R. (1996). Evaluación de la autoeficacia: Adaptación española de la escala de autoeficacia general [Measuring generalized self-beliefs: A Spanish adaptation of the General Self-Efficacy scale]. Ansiedad y Estrés, 2, 1–8.Google Scholar
Bandura, A. (1997). Self-efficay: Toward a unifying theory of behavioral change. Psychological review, 84, 191–215. http://dx.doi.org/10.1037%2F%2F0033-295X.84.2.191CrossRefGoogle Scholar
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. http://dx.doi.org/10.1037%2F%2F0033-2909.107.2.238CrossRefGoogle ScholarPubMed
Bentler, P. M., & Yuan, K. H. (1999). Structural equation modeling with small samples: Test statistics. Multivariate Behavioral Research, 34, 181–197. http://dx.doi.org/10.1207%2FS15327906Mb340203CrossRefGoogle ScholarPubMed
Biddle, S. J. H., Fox, K. R., & Boutcher, S. H. (2000). Physical activity and psychological wellbeing. Londres, England: Routledge.Google Scholar
Blair, S. N., & Brodney, S. (1999). Effects of physicial inactivity and obesity on morbidity and mortality: Current evidence and research issues. Medicine and Science in Sports and Exercise, 31, 646–662. http://dx.doi.org/10.1097%2F00005768-199911001-00025CrossRefGoogle Scholar
Blanchard, C. M., Courneya, K. S., Rodgers, W. M., Fraser, S. N., Murray, T. C., & Daub, B. (2003). Is the theory of planned behavior a useful framework for understanding exercise adherente during phase II cardiac rehabilitation? Journal of Cardiopulmonary Rehabilitation, 23, 29–39. http://dx.doi.org/10.1097/00008483-200301000-00007CrossRefGoogle Scholar
Bollen, K. A. (1990). Overall fit in covariance structure models: Two types of sample size effects. Psychological Bulletin, 107, 256–259. http://dx.doi.org/10.1037%2F%2F0033-2909.107.2.256CrossRefGoogle Scholar
Browne, M. V. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37, 62–83. http://dx.doi.org/10.1111%2Fj.2044-8317.1984.tb00789.xCrossRefGoogle ScholarPubMed
Browne, M. V., & Cudeck, R. (1992). Alternative ways of assessing model fit. Sociological Methods and Research, 21, 230–258. http://dx.doi.org/10.1177%2F0049124192021002005CrossRefGoogle Scholar
Carmines, E. G., & McIver, J. P. (1981). Analyzing models with unobserved variables: Analysis of covariance structures. In Bohmstedt, G. W. & Borgatta, E. F. (Eds.), Social Measurement (pp. 65–115). Thousand Oaks, CA: Sage Publications.Google Scholar
Chatzisarantis, N., & Hagger, M. (2008). Influences of personality traits and continuation intentions on physical activity participation within the theory of planned behavior. Psychology & Health, 23, 347–367. http://dx.doi.org/10.1080%2F14768320601185866CrossRefGoogle Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral science. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Conner, M., & Norman, P. (1995). The role of social cognition in health behaviors. In Conner, M. & Norman, P. (Eds.), Predicting Health Behavior: Research and practice with social cognition models (pp. 1–22). Buckingham, England: Open University Press.Google Scholar
Conner, M., & Sparks, P. (1996). The theory of planned behavior and health behaviors. In Conner, M. & Norman, P. (Eds.), Predicting Health Behavior: Research and practice with social cognition models (pp. 121–162). Buckingham, England: Open University Press.Google Scholar
Curran, P. S., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1, 16–29. http://dx.doi.org/10.1037%2F%2F1082-989X.1.1.16CrossRefGoogle Scholar
Deci, E. L. (1975). Intrinsic motivation. New York, NY: Plenum Press.CrossRefGoogle Scholar
Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. New York, NY: Plenum Press.CrossRefGoogle Scholar
Deci, E. L., & Ryan, R. M. (2000). The “what” and “why” of goal pursuits: Human needs and the self-determination of behavior, Psychological Inquiry, 11, 227–268. http://dx.doi.org/10.1207%2FS15327965PLI1104_01CrossRefGoogle Scholar
Eng, J. J., & Martin-Ginis, K. A. (2007). Using the theory of planned behavior to predict leisure time physical activity among people with chronic kidney disease. Rehabilitation Psychology, 52, 435–442. http://dx.doi.org/10.1037%2F0090-5550.52.4.435CrossRefGoogle Scholar
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4, 272–299. http://dx.doi.org/10.1037%2F%2F1082-989X.4.3.272CrossRefGoogle Scholar
Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling, 6, 56–83. http://dx.doi.org/10.1080%2F10705519909540119CrossRefGoogle Scholar
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior:An introduction to theory and research. Nueva York, NY: Addison-Wesley.Google Scholar
Francis, J. J., Eccles, M. P., Johnston, M., Walker, A., Grimshaw, J., Foy, R., … Bonetti, D. (2004). Constructing questionnaires based on the theory of planned behavior:Amanual for health services researchers. Newcastle, England: Centre for Health Services Research.Google Scholar
Godin, G., & Kok, G. (1996). The theory of planned behavior: A review of its applications to health-related behaviors. American Journal of Health Promotion, 11, 87–98. http://dx.doi.org/10.4278%2F0890-1171-11.2.87CrossRefGoogle ScholarPubMed
Hagger, M. S., Chatzisarantis, N. L. D., & Biddle, S. J. H. (2002). A meta-analytic review of the theories of reasoned action and planned behavior in physical activity: Predictive validity and the contribution to additional variables. Journal of Sport and Exercise Psychology, 24, 3–32.CrossRefGoogle Scholar
Hakstian, A. R., & Muller, V. J. (1973). Some notes on the number of factors problem. Multivariate Behavioral Research, 461–475. http://dx.doi.org/10.1207%2Fs15327906mbr0804_4Google Scholar
Heise, D. R., & Bohrnstedt, G. W. (1970). Validity, invalidity and reliability. In Borgatta, E. F. & Bohrnstedt, G. W. (Eds.), Sociological Methodology (pp. 104–129). San Francisco, CA: Jossey-Bass. http://dx.doi.org/10.2307%2F270785Google Scholar
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. http://dx.doi.org/10.1080%2F10705519909540118CrossRefGoogle Scholar
Hu, L., Bentler, P. M., & Kano, Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychological Bulletin, 112, 351–362. http://dx.doi.org/10.1037%2F%2F0033-2909.112.2.351CrossRefGoogle ScholarPubMed
Humphreys, L. G. (1964). Number of cases and number of factors: An example where N is very large. Educational and Psychological Measurement, 24, 457–466. http://dx.doi.org/10.1177%2F001316446402400302CrossRefGoogle Scholar
Jackson, D. A. (1993). Stopping rules in principal components analysis: A comparison of heuristical and statistical approaches. Ecology, 74, 2204–2214. http://dx.doi.org/10.2307%2F1939574CrossRefGoogle Scholar
Jackson, C., Smith, A., & Conner, M. (2009). Applying an extended version of the theory of planned behavior to physical activity. Journal of Sports Sciences, 21, 119–133. http://dx.doi.org/10.1080%2F0264041031000070976CrossRefGoogle Scholar
Jerusalem, M., & Schwarzer, R. (1992). Self-efficacy as a resource factor in stress appraisal processes. In Schawarzer, R. (Ed.), Self-efficay: Thought control of action. Washington, DC: Hemisphere.Google Scholar
Jiménez, M., Martínez, P., Miró, E., & Sánchez, A. I. (2008). Bienestar psicológico y hábitos saludables: ¿están asociados con la práctica de ejercicio físico? [Psychological well-being and healthy habits: Are they associated with physical exercise practice?]. International Journal of Clinical and Health Psychology, 8, 85–102.Google Scholar
Jöreskog, K., & Sörbom, D. (1993). LISREL8: Structural equation modeling with the SIMPLIS command language. Hillsdale, NJ: Erlbaum.Google Scholar
Kline, R. B. (1998). Principles and practice of structural equation modeling. New York, NY: Guilford Press.Google Scholar
Latimer, A. E., & Martin, A. (2005). The theory of planned behavior in prediction of leisure time physical activity among individuals with spinal cord injury. Rehabilitation Psychology, 50, 389–396. http://dx.doi.org/10.1037%2F0090-5550.50.4.389CrossRefGoogle Scholar
Lawlor, D. A., & Hopker, S. W. (2001). The effectiveness of exercise as an intervention in the management of depression: Systematic review and meta-regression analysis of randomised controlled trials. British Medical Journal, 322, 763–767. http://dx.doi.org/10.1136%2Fbmj.322.7289.763CrossRefGoogle ScholarPubMed
Linn, R. L. (1968). A Monte Carlo approach to the number of factors problem. Psychometrika, 33, 37–71. http://dx.doi.org/10.1007%2FBF02289675CrossRefGoogle Scholar
Maddux, J. E. (2005). Self-efficacy. In Snyder, C. R. & Lopez, S. J. (Eds.), Handbook of Positive Psychology (pp. 277–287). Oxford: Oxford University Press.Google Scholar
Marcus, B. H., Dubbert, P. M., Forsyth, L. H., McKenzie, T. L., Stone, E. J., Dunn, A. L., & Blair, S. N. (2000). Physical activity behavior change: Issues in adoption and maintenance. Health Psychology, 19, 32–41. http://dx.doi.org/10.1037%2F%2F0278-6133.19.Suppl1.32CrossRefGoogle ScholarPubMed
Markland, D., & Tobin, V. (2004). A modification to the behavioral regulation exercise questionnaire to include and assessment of amotivation. Journal of Sport & Exercise Psychology, 26, 191–196.CrossRefGoogle Scholar
Martínez Arias, M. R. (1996). Psicometría: Teoría de los tests psicológicos y educativos [Psicometry: Theory of psychological and educational tests]. Madrid, Spain: Síntesis.Google Scholar
McAuley, E., Mihalko, S. L., & Bane, S. M. (1997). Exercise and self-esteem in middle-aged adults: Multidimensional relationships and physical fitness and self-efficacy influences. Journal of Behavioral Medicine, 20, 67–83. http://dx.doi.org/10.1023/A:1025591214100CrossRefGoogle ScholarPubMed
Moreno, J. A., Cervelló, E. M., & Martínez, A. (2007). Measuring self-determination motivation in a physical fitness setting: Validation of the Behavioral Regulation in Exercise Questionnaire-2 (BREQ-2) in a Spanish sample. The Journal of Sport Medicine and Physical Fitness, 47, 366–378.Google Scholar
Mote, T. A. (1970). An artifact of the rotation of too few factors: Study orientation vs. trait anxiety. Revista Internacional de Psicología, 37, 61–91.Google Scholar
Netz, Y., Wu, M. J., Becker, B. J., & Tenebaum, G. (2005). Physical activity and psychological well-being in advanced age: A meta-analysis of intervention studies. Psychology and Aging, 20, 272–284. http://dx.doi.org/10.1037%2F0882-7974.20.2.272CrossRefGoogle ScholarPubMed
Neupert, S. D., Lachman, M. E., & Whitbourne, S. B. (2009). Exercise self-efficacy and control beliefs: Effects on exercise behavior after an exercise intervention for older adults. Journal of Aging and Physical Activity, 17, 1–16.CrossRefGoogle ScholarPubMed
Nevitt, J., & Hancock, G. R. (2000). Improving the root mean square error of approximation for nonnormal conditions in structural equation modeling. The Journal of Experimental Education, 68, 251–268. http://dx.doi.org/10.1080%2F00220970009600095CrossRefGoogle Scholar
Rhodes, R., Blanchard, C., Matheson, D., & Coble, J. (2006). Disentangling motivation, intention and planning in the physical activity domain. Psychology of Sport and Exercise, 7, 15–27. http://dx.doi.org/10.1016%2Fj.psychsport.2005.08.011CrossRefGoogle Scholar
Ruiz, M. A., & San Martín, R. (1992). Una simulación sobre el comportamiento de la regla K1 en la estimación del número de factores [A simulation about the behaviour of K1 rule in the estimation of factor numbers]. Psicothema, 4, 543–550.Google Scholar
Shumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation modeling. Mahwah, NJ: Erlbaum.Google Scholar
Sjöström, M., Oja, P., Hagströmer, M., Smith, B. J., & Bauman, A. (2006). Health-enhancing physical activity across European Union countries: The Eurobarometer study. Journal of Public Health, 14, 291–300. http://dx.doi.org/10.1007%2Fs10389-006-0031-yCrossRefGoogle Scholar
Sniehotta, F. F., Scholz, U., & Schwarzer, R. (2005). Brindging the intention-behavior gap: Planning, self-efficacy, and action control in the adoption and maintenance of physical exercise. Psychology and Health, 20, 143–160. http://dx.doi.org/10.1080/08870440512331317670CrossRefGoogle Scholar
Sugawara, H. M., & MacCallum, R. C. (1993). Effect of estimation method on incremental fit indexes for covariance structure models. Applied Psychological Measurement, 17, 365–377. http://dx.doi.org/10.1177%2F014662169301700405CrossRefGoogle Scholar
Taras, H. (2005). Physical activity and student performance at school. The Journal of School Health, 75, 214–218. http://dx.doi.org/10.1111%2Fj.1746-1561.2005.00026.xCrossRefGoogle ScholarPubMed
Terry, D. J., & O'Leary, J. E. (1995). The theory of planned behavior: The effects of perceived behavioral control and self-efficacy. British Journal of Social Psychology, 34, 199–220. http://dx.doi.org/10.1111%2Fj.2044-8309.1995.tb01058.xCrossRefGoogle Scholar
WHO (2002). The world heatlh report 2002-Reducing risks, promoting healthy life. Geneva, Switzerland: WHO.Google Scholar
WHO (2004). World strategy about daily diet, physical activity and heatlh. Geneva, Switzerland: WHO.Google Scholar
WHO (2006). Physical activity and health in Europe: evidence for action. Copenhagen, Denmark: WHO Regional Office for Europe.Google Scholar
Yu, C. Y. (2002). Evaluating cutoff criteria of model fit indices for latent variable models with binary and continuous outcomes. (Doctoral dissertation). University of California, Los Angeles, CA. Retrieved from http://statmodel.com/download/Yudissertation.pdf.Google Scholar
Yuan, K.-H., & Bentler, P. M. (1998). Normal theory based test statistics in structural equation modelling. British Journal of Mathematical and Statistical Psychology, 51, 289–309. http://dx.doi.org/10.1111%2Fj.2044-8317.1998.tb00682.xCrossRefGoogle ScholarPubMed
Zwick, W. R., & Velicer, W. F. (1986). A comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432–442. http://dx.doi.org/10.1037%2F%2F0033-2909.99.3.432CrossRefGoogle Scholar