Beliefs, attitudes and subjective norms as predictors of preventive behavioral intentions in offspring of people with Type 2 Diabetes Mellitus
DOI:
https://doi.org/10.5020/2355Keywords:
Attitude, Health Promotion, Diabetes Mellitus.Abstract
Objective: To analyze beliefs, attitudes and subjective norms as predictors of preventive behavioral intention in offspring of parents with type 2 diabetes mellitus in two cities in the state of Hidaldo, Mexico. Methods: This is a quantitative, nonexperimental, explanatory and cross-sectional study. Through a two-stage probabilistic sample, 246 subjects (between 15 and 59 years old) whose parents were enrolled in a diabetes program in the social security service were interviewed in a personal manner. Results: It was observed that the reduction in the risk of developing diabetes affects the intent of developing preventive behaviors mediated by attitude toward prevention (p=0.000), which is the most important predictor of that intention (p=0.000). Subjective norms also have a significant impact on the preventive behavioral intention (p=0.000), although the preventive attitude is not affected by beliefs regarding the development (p=0.095) and severity of the disease (p=0.056). Conclusion: The application of the model allowed the identification of relevant aspects to support health promotion, oriented to influence the processes of change in social behavior, in a population at risk of developing type 2 diabetes mellitus in Mexico. doi:10.5020/18061230.2014.p43Downloads
References
Flores, E. ¿Practicas la cultura de la prevención en salud? Su Médico. [acceso en 2012 Sept]. Disponible en: http://www.sumedico.com/nota7276.html.
Organización Mundial de la Salud - OMS. Diabetes,Centro de Prensa nota descriptiva No. 312, 2011 [acceso en 2012 Sept]. Disponible en: http://www.who. int/mediacentre/factsheets/fs312/es/index.html.
Shaw JE, Sicree RA, Zimmet PZ. Global estimates of the prevalence of diabetes for 2010 and 2030. Diabetes Res Clin Pr. 2010;87(1):4-14.
Hernández-Romieu AC, Elnecavé-Olaiz A, Huerta-Uribe N, Reynoso-Noverón N. Análisis de una encuesta poblacional para determinar los factores asociados al control de la diabetes mellitus en México. Salud Pública México. 2011;53(1):34-9.
Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, et al. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia. 2012;55(11):2895-905.
Andrade F. Estimating diabetes and diabetes free life expectancy in Mexico and seven major cities in Latin America and the Caribbean. Rev Panam Salud Pública. 2009;26(1):9-16.
Gonder-Frederick LA, Cox DJ, Ritterband, LM. Diabetes and behavioural medicine: the second decade.J Consult Clin Psych. 2002;70(3):611-25.
Comité de Educación en Diabetes Fundación IMSS,A. C. [CEDFIMSSAC]. El papel del derechohabiente en la prevención y control de la diabetes mellitus. Rev Med IMSS. 2007;45(2):101-03.
Hernández R, Fernández C, Baptista M. Metodología de la Investigación. 5ª ed. México: McGraw Hill; 2010.
Bentler PM, Chou CP. Practical issues in structural modeling. Sociol Meth Res. 1987;16(1):78-117.
Fox J, Byrnes J, Boker S, Neale M. Structural Equation Modeling in R with the sem and OpenMx Packages.En: Hoyle RH, Kaplan D, Marcoulides G, West S,
editores. Handbook of Structural Equation Modeling.
st Ed. New York: Guilford Press; 2012. p. 325-40.
Chin WW. The Partial Least Square Approach to Structural Equation Modeling. En: Marcoulides GA, editor. Modern Methods for Business Research.Mahwah, NJ: Lawrence Erlbaum; 1998. p. 295-336.
Hair JF, Black WC, Babin BJ, Anderson RE.Multivariate data analysis. A global perspective 7a ed.New York: Pearson Education; 2010
Johnson B, Stevens JJ. Exploratory and confirmatory factor analysis of the School Level Environment Questionnaire (SLEQ). Learn Environ Res.2001;4(3):325-44.
Cheah WL, Wan Abdul Manan WM, Zabidi-Hussin ZAMH. A structural equation model of the determinants of malnutrition among children in rural Kelantan, Malaysia. Rural Remote Health. [periódico na internet].2010 [acceso en 2012 Nov 2];10(1):1-12. Disponible en: http://www.rrh.org.au/publishedarticles/article_print_1248.pdf.
Sridharan B, Deng H, Kirk J, Corbitt BJ. Structural Equation Modeling for Evaluating the user perceptions of E-learning effectiveness in Higher Education. En la conferencia: 18th European Conference in Information Systems, ECIS 2010. Pretoria, South Africa.
Edwards MC, Wirth RJ, Houts CR, Xi N. Categorical Data in the Structural Equation Modeling. Handbook of Structural Equation Modeling. New York: Guilford Press; 2012.
Lei P, Wu Q. Estimation in Structural Equation Modeling. En: Hoyle, R, editor. Handbook of StructuralEquation Modeling. 1st Ed. New York: Guilford Press; 2012. p. 165-80.
Byrne BM. Structural Equation Modeling with EQS.Basic concepts, applications and programming. 2nd Ed.New York: Taylor & Francis Group; 2009.
Beran TN, Violsto C. Structural equation modeling in medical research: a primer. BMC Res Notes.2010;3(267):1-5.
Little TD, Bovaird JA, Card NA. Modeling contextual effects in longitudinal studies. Mahwah, NJ: LEA;2007.
Annett RD, Turner C, Brody JL, Sedillo D, Dalen J.Using Structural Equation Modeling to Understand Child and Parent Perceptions of Asthma Quality ofLife. J Pediatr Psychol. 2010;35(8):870-82.
Lee NR, Kotler P. Social Marketing. Influencing behaviors for good. 4th Ed. USA: SAGE; 2011.
Rimer B, Glantz K. Theory at a glance. a guide for health promotion practice. UK: National Cancer Institute U.S.Department of Health and Human Services, National Institutes of Health; 2005.
Hogg M, Vaughan G. Psicología Social. Madrid: Médica Panamericana; 2010.
Garza ME, Calderón C, Salinas AM, Nuñez GM,Villarreal E. Atribuciones y creencias sobre la diabetes mellitus tipo 2. Rev Med IMSS. 2003;41(6):465-72.
Aunchalee E, Palmquist L, Wilkinson AV, Sandoval JM,Koehly LM. Age-Related differences in Biomedical and Folk Beliefs Causes for Diabetes and Heart Disease among Mexican origins adults. J Immigr Minor Health.2012;14(4):596-601.
Ajzen I. The theory of planned behaviour: reactions and reflections. Psychol Health. 2011;26(9):1113-1127.
Alvaro EM, Crano WD, Siegel JT, Hohman Z, Johnson I, Nakawaki B. Adolescents’ attitudes toward antimarijuana ads, usage intentions, and actual marijuana usage. Psychol Addict Behav.2013;27(4):1027-35.
Solomon MR, Polegato R, Zaichkowsky JL.Consumer Behavior: buying, having, and beign. 8ª ed. Upper Saddle River, NJ: Pearson Prentice Hall; 2009.
Garcia MOH. El impacto de los programas de prevención de la diabetes en Mazatlán, Sinaloa, México.Contribuciones a las Ciencias Sociales. [publicación en línea] 2012 Feb. [acceso 2012 Jul. 27];(15):1-13.Disponible en: www.eumed.net/rev/cccss/18/.
Siwik VP, Kutob RM, Ritenbaugh C, Aickin M, Gordon JS. Families United: development and implementation of a family-based group office visit model for the
primary prevention of type 2 diabetes. Diabetes Educ.2012;38(6):811-21.
