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Órgano Oficial del Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz
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2017, Number 1

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Salud Mental 2017; 40 (1)

Effect of substance use on condom use in the Theory of Planned Behavior: Analysis of differential item functioning

Sánchez-Domínguez R, Villalobos-Gallegos L, Felix-Romero V, Morales-Chainé S, Marín-Navarrete R
Full text How to cite this article

Language: English
References: 51
Page: 5-14
PDF size: 429.61 Kb.


Key words:

Condom, substance use, attitudes, self-efficacy, subjective norms, young adults.

ABSTRACT

Introduction. Substance use is one of the factors associated with lower condom use in young adults, which increases the likelihood of HIV infection. The Theory of Planned Behavior (TPB) is one of the most useful models for explaining this phenomenon since it considers the aim of engaging in a behavior based on attitudes, subjective norms and self-efficacy. Objective. To develop a questionnaire and to evaluate the Differential Item Functioning (DIF) caused by substance use in TPB indicators, using the Multiple Indicators Multiple Causes Analysis (MIMIC). Method. The study was conducted in two phases with Mexico City college students age 18 to 25. Results. Adequate goodness of fit was obtained in all three models of the TPB: attitudes χ2 S-B(2) = 3.902, p ‹ .001; CFIs = .999; TLIs = .996; RMSEAs = .037, 90% CI ≤ .001-.095; subjective norms χ2 S-B(7) = 9.103, p ‹ 0.245; CFIs = .999; TLIs = .998; RMSEAs = .022, 90% CI ≤ .001-.056; and self-efficacy χ2 S-B(25) = 65.115, p ‹ .001; CFIs = .982; TLIs = .974; RMSEAs = .050, 90% CI = .036-.066; in one item in attitudes and two items in subjective norms a DIF effect was observed, while no item proved significant regarding self-efficacy. Discussion and conclusion. There is little evidence in the detection of DIF due to substance use in TPB indicators in condom use, and this is the first study to conduct this type of analysis. Items presenting DIF open the door to future research due to the importance of assessing how the indicator behaves with a population displaying a particular trait.


REFERENCES

  1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. http://doi.org/10.1016/0749-5978(91) 90020-T.

  2. Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Prediciting Social Behaviour. Englewood Cliffs: Prentice Hall.

  3. Albarracín, D., Johnson, B. T., Fishbein, M., & Muellerleile, P. a. (2001). Theories of reasoned action and planned behavior as models of condom use: a meta-analysis. Psychological Bulletin, 127(1), 142–161. http://doi.org/10.1037/0033- 2909.127.1.142

  4. Alvarez, C., Villarruel, A. M., Zhou, Y., & Gallegos, E. (2010). Predictors of condom use among Mexican adolescents. Research and Theory for Nursing Practice, 24(3), 187–196. http://doi.org/10.1891/1541-6577.24.3.187

  5. Andrew, B. J., Mullan, B. A., de Wit, J. B. F., Monds, L. A., Todd, J., & Kothe, E. J. (2016). Does the Theory of Planned Behaviour Explain Condom Use Behaviour Among Men Who have Sex with Men? A Meta-analytic Review of the Literature. AIDS and Behavior, 1–11. http://doi.org/10.1007/s10461-016-1314-0

  6. Armitage, C. J., & Conner, M. (2001). Efficacy of the Theory of Planned Behaviour: a meta-analytic review. The British Journal of Social Psychology / the British Psychological Society, 40(Pt 4), 471–499. http://doi.org/10.1348/014466601164939

  7. Beauducel, A., & Herzberg, P. Y. (2006). On the Performance of Maximum Likelihood Versus Means and Variance Adjusted Weighted LEast Squares Estimation in CFA. Structural Equation Modeling, 13(2), 204–228. http://doi.org/10.1207/ s15328007sem1302

  8. Benjamini, Y., & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300. http://doi.org/10.2307/ 2346101

  9. Bennett, P., & Bozionelos, G. (2000). The theory of planned behaviour as predictor of condom use: A narrative review. Psychology, Health & Medicine, 5(3), 307–326. http://doi.org/10.1080/713690195

  10. Calsyn, D. A., Baldwin, H., Niu, X., Crits-Christoph, P., & Hatch-Maillette, M. A. (2011). Sexual risk behavior and sex under the influence: An event analysis of men in substance abuse treatment who have sex with women. American Journal on Addictions, 20(3), 250–256. http://doi.org/10.1111/j.1521- 0391.2011.00123.x

  11. Centers for Disease Control and Prevention [CDC]. (2014). Sexually Transmitted Disease Surveillance 2013.

  12. Centro Nacional para la prevención y el control del VIH/SIDA [CENSIDA]. (2016). “Vigilancia Epidemiológica de casos de VIH/SIDA en México Registro Nacional de Casos de SIDA Actualización al 2do. Trimestre de 2016”.

  13. Conner, M., Sutherland, E., Kennedy, F., Grearly, C., & Berry, C. (2008). Impact of alcohol on sexual decision making: Intentions to have unprotected sex. Psychology & Health, 23(8), 909–934. http://doi.org/10.1080/08870440701596551

  14. Conrad, K. M., Conrad, K. J., Passetti, L. L., Funk, R. R., & Dennis, M. L. (2015). Validation of the Full and Short-Form Self-Help Involvement Scale Against the Rasch Measurement Model. Evaluation Review, 39(4), 395–427. http://doi.org/ 10.1177/0193841X15599645

  15. Cribbie, R. a. (2007). Multiplicity Control in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 14(1), 98–112. http://doi. org/10.1207/s15328007sem1401_5

  16. Crosby, R. A., Charnigo, R. A., Weathers, C., Caliendo, A. M., & Shrier, L. A. (2012). Condom effectiveness against non-viral sexually transmitted infections: a prospective study using electronic daily diaries. Sexually Transmitted Infections, 88(7), 484–9. http://doi.org/10.1136/sextrans-2012-050618

  17. Davis, K. C., Jacques-Tiura, A. J., Stappenbeck, C. A., Danube, C. L., Morrison, D. M., Norris, J., & George, W. H. (2015). Men’s Condom Use Resistance: Alcohol Effects on Theory of Planned Behavior Constructs. Health Psychology, 35(2), 178–186. http://doi.org/10.1037/hea0000269

  18. Donenber, G. R., Emerson, E., Bryant, F. B., Wilson, H., & Weber-Shifrin, E. (2001). Understanding AIDS-Risk Behavior Among Adolescents in Psychiatric Care: Links to Psychopathology and Peer Relationships. Journal of the American Academy of Child & Adolescent Psychiatry, 40(6), 642–653. http://doi. org/10.1097/00004583-200106000-00008

  19. Donovan, D. M., Bigelow, G. E., Brigham, G. S., Carroll, K. M., Cohen, A. J., Gardin, J. G. et al. (2012). Primary outcome indices in illicit drug dependence treatment research: systematic approach to selection and measurement of drug use end-points in clinical trials. Addiction, 107(4), 694–708. http://doi.org/10.1111/ j.1360-0443.2011.03473.x

  20. Ellickson, P. L., Collins, R. L., Hambarsoomians, K., & McCaffrey, D. F. (2005). Does alcohol advertising promote adolescent drinking? Results from a longi tudinal assessment. Addiction, 100(2), 235–246. http://doi.org/10.1111/j.1360- 0443.2005.00974.x

  21. Encuesta Nacional de Salud y Nutricion [ENSANUT]. (2012). Resultados Nacionales. Mexico: Cuernavaca.

  22. Enders, C. K., & Bandalos, D. L. (2001). The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal, 8(3), 430–457. http://doi.org/10.1207/S15328007SEM0803_5

  23. Fishbein, M. (1980). A theory of reasoned action: some applications and implications. Nebraska Symposium on Motivation. Nebraska Symposium on Motivation, 27, 65–116. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/7242751

  24. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley. http://doi. org/10.1017/CBO9781107415324.004

  25. Fishbein, M., & Ajzen, I. (2010). Predicting and changing behaviour: The reasoned action approach. New York: Psychology Press. http://doi. org/10.4324/9780203937082

  26. Francis, A. J. J., Eccles, M. P. M., Johnston, M., Walker, A., Grimshaw, J., Foy, R., … Francis, J. (2004). Constructing questionnaires based on the theory of planned behaviour: a manual for health services researchers. Direct. Newcastle, UK. http://doi.org/0-9540161-5-7

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

  28. Inmaculada, T., Bermudez, M. P., Ramiro, M. T., & Buela-Casal, G. (2014). Creencias religiosas y actitudes hacia el uso del preserVatiVo en adolescentes peruanos. Revista Mexicana de Psicología, 31(1), 41–49.

  29. Instituto Nacional de las Mujeres[INMUJERES]. (2012). Enfermedades de transmisión sexual y VIH-SIDA.

  30. Krippendorff, K. (1990). Metodología del análisis de contenido. (Paidos, Ed.). España.

  31. Lewis, T. T., Yang, F. M., Jacobs, E. A., & Fitchett, G. (2012). Racial/ethnic differences in responses to the everyday discrimination scale: a differential item functioning analysis. American Journal of Epidemiology, 175(5), 391–401. http:// doi.org/10.1093/aje/kwr287

  32. Maher, L., Phlong, P., Mooney-Somers, J., Keo, S., Stein, E., Couture, M. C., & Page, K. (2011). Amphetamine-type stimulant use and HIV/STI risk behaviour among young female sex workers in Phnom Penh, Cambodia. The International Journal on Drug Policy, 22(3), 203–9. http://doi.org/10.1016/j.drugpo.2011.01.003

  33. Malcolm, S., Huang, S., Cordova, D., Freitas, D., Arzon, M., Jimenez, G. L., … Prado, G. (2013). Predicting condom use attitudes, norms, and control beliefs in Hispanic problem behavior youth: the effects of family functioning and parent- adolescent communication about sex on condom use. Health Education & Behavior, 40(4), 384–391. http://doi.org/10.1177/1090198112440010

  34. Miles, J. N. V, Marshall, G. N., & Schell, T. L. (2008). Spanish and English versions of the PTSD Checklist-Civilian version (PCL-C): testing for differential item functioning. Journal of Traumatic Stress, 21(4), 369–76. http://doi.org/10.1002/ jts.20349

  35. Muthén, B., & Kaplan, D. (1985). A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38(2), 171–189. http://doi.org/10.1111/j.2044-8317.1985. tb00832.x

  36. Muthén, L. K., & Muthén, B. O. (2002). How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power. Structural Equation Modeling: A Multidisciplinary Journal, 9(4), 599–620. http://doi.org/10.1207/S15328007SEM0904_8

  37. Noar, S. M. (2006). A 10-Year Retrospective of Research in Health Mass Media Campaigns: Where Do We Go From Here? Journal of Health Communication, 11(1), 21–42. http://doi.org/10.1080/10810730500461059

  38. Prati, G., Mazzoni, D., & Zani, B. (2014). Perceived behavioural control, subjective norms, attitudes and intention to use condom: A longitudinal cross-lagged design. Psychol Health, 29(10), 1119–1136. http://doi.org/10.1080/08870446.20 14.913043

  39. Rich, A., Mullan, B. A., Sainsbury, K., & Kuczmierczyk, A. R. (2014). The role of gender and sexual experience in predicting adolescent condom use intentions using the theory of planned behaviour. The European Journal of Contraception & Reproductive Health Care, 19(4), 295–306. http://doi.org/10.3109/1362518 7.2014.917624

  40. Robles-Montijo, S., & Díaz-Loving, R. (2011). Validación de la Encuesta Estudiantil sobre salud sexual (EESS). (F. de E. S. Iztacala, Ed.). México.

  41. Rodríguez-Pérez, V., Valencia-Flores, M., Reyes-Lagunes, I., & Lara-Muñoz, M. del C. (2013). Adaptación y validación psicométrica del Cuestionario de Consecuencias Funcionales del Dormir (Functional Outcomes Sleep Questionnaire [FOSQ]) en habitantes de la Ciudad de México. Salud Mental, 36(4), 307–313.

  42. Sacolo, H. N., Chung, M.-H., Chu, H., Liao, Y.-M., Chen, C.-H., Ou, K.-L., … Chou, K.-R. (2013). High risk sexual behaviors for HIV among the in-school youth in Swaziland: a structural equation modeling approach. PloS One, 8(7), e67289. http://doi.org/10.1371/journal.pone.0067289

  43. Satorra, A., & Bentler, P. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514. http://doi.org/10.1007/ bf02296192

  44. 44.Selikow, T.-A., Ahmed, N., Flisher, A. J., Mathews, C., & Mukoma, W. (2009). I am not “umqwayito’’: a qualitative study of peer pressure and sexual risk behaviour among young adolescents in Cape Town, South Africa. Scandinavian Journal of Public Health, 37 Suppl 2(2 suppl), 107–12. http://doi. org/10.1177/1403494809103903

  45. Starosta, A. J., Berghoff, C. R., & Earleywine, M. (2015). Factor structure and gender stability in the multidimensional condom attitudes scale. Assessment, 22(3), 374–84. http://doi.org/10.1177/1073191114547887

  46. Tyson, M., Covey, J., & Rosenthal, H. E. S. (2014). Theory of planned behavior interventions for reducing heterosexual risk behaviors: A meta-analysis. Health Psychology, 33(12), 1454–1467. http://doi.org/10.1037/hea0000047

  47. United Nations Programme on HIV and AIDS [UNAIDS]. (2014). Global statistics 2014.

  48. United Nations Programme on HIV and AIDS [UNAIDS]. (2015). Position statement on condoms and the prevention of HIV, other sexually transmitted infections and unintended pregnancy. Retrieved from http://www.unaids.org/es/resources/ presscentre/featurestories/2015/july/20150702_condoms_prevention

  49. Valle, E. D. V., Canizales, G. M., & Potter, J. E. (2010). Religión e iniciación sexual premarital en México. Revista Latinoamericana de Población, 4(7), 7–30.

  50. Vasilenko, S. A., & Lanza, S. T. (2014). Predictors of multiple sexual partners from adolescence through young adulthood. Journal of Adolescent Health, 55(4), 491–497. http://doi.org/10.1016/j.jadohealth.2013.12.025

  51. Yzer, M. C. (2012). The Integrative Model of Behavior Prediction as a Tool for Designing Health Messages, 21–40.




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