Mexican Validation of the MOS Questionnaire on Perceived Social Support in the Context of the COVID-19 Pandemic
Validación mexicana del Cuestionario MOS de Apoyo Social Percibido en contexto de pandemia por COVID-19
Perla Shiomara del Carpio Ovando , Erika Robles Estrada , Yazmín Quintero Hernández , Miguel Gallegos , Lucas G. Gago Galvagno , Tomás Caycho-Rodríguez , Lindsey W. Vilca , Pablo Martino , Mauricio Cervigni , Anastasia Razumovskiy , Nelson Portillo
Suma Psicológica, (2022), 29(2), pp. 100-109.
Received 2 January 2022
Accepted 18 May 2022
Introducción: La pandemia de COVID-19 ha tenido un impacto muy negativo en la salud mental y el bienestar psicosocial general de las personas, pero el estudio del apoyo social disponible para hacer frente a una situación tan adversa como esta ha recibido muy poca atención. Objetivo: Examinar las propiedades psicométricas del Cuestionario MOS de Apoyo Social Percibido en población mexicana en contexto de pandemia por COVID-19. Método: Diseño no experimental transversal. Se aplicó un cuestionario sociodemográfico y el Medical Outcomes Study en una muestra no probabilística por conveniencia. Participaron 898 personas de diferentes regiones de México, 258 hombres y 640 mujeres, durante el contexto de la pandemia por COVID-19. Resultados: El análisis arrojó un modelo Bi-factor de dos factores Apoyo emocional/informacional y Apoyo tangible, con índices de bondad que se ajustaron a los datos. La fiabilidad fue adecuada con un coeficiente de omega jerárquico alto, así como en los factores. Asimismo, el coeficiente H fue adecuado en el factor general y sus dimensiones. Conclusiones: La escala presenta validez y confiabilidad para medir el apoyo social percibido en población mexicana.
Palabras clave:
Análisis factorial confirmatorio, apoyo social percibido, COVID-19, confiabilidad, índices de bondad de ajuste, MOS
Introduction: The COVID-19 pandemic has had a very negative impact on people’s overall mental health and psychosocial well-being, but the study of available social support to cope with such an adverse situation has received hardly any attention. Objective: To examine the psychometric properties of the MOS Perceived Social Support Questionnaire among the Mexican population in the context of the COVID-19 pandemic. Method: Non-experimental cross-sectional study. A sociodemographic questionnaire and the Medical Outcomes Study were applied in a non-probabilistic sample. A total of 898 people from different regions in Mexico, 258 males and 640 females, participated in the study in the context of the COVID-19 pandemic. Results: The analysis yielded a bi-factor model with two factors, Emotional/informational support and Tangible support, with satisfactory goodness of fit indices. Reliability was adequate with a high hierarchical omega coefficient, as well as in the factors. Likewise, the H coefficient was adequate in the general factor and its dimensions. Conclusions: Results showed that the scale is a valid and reliable measure of perceived social support among the Mexican population.
Keywords:
Confirmatory factor analysis, perceived social support, COVID-19, reliability, goodness-of-fit indices, MOS
Ahorsu, D. K., Lin, C. Y., Imani, V., Saffari, M., Griffiths, M. D., & Pakpour, A. H. (2022). The fear of COVID-19 scale: Development and initial validation. International Journal of Mental Health and Addiction, 1-9. https://doi.org/10.1007/s11469-020-00270-8
Aiken, L. S., West, S. G., & Reno, R. R. (1991). Regresión múltiple: prueba e interpretación de interacciones. Publicaciones SAGE.
American Psychological Association (2010). Principios éticos de los psicólogos y Código de Conducta. APA.
Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guilford.
Casanova-Rodas, L., Rascón-Gasca, M. L., Alcántara-Chabelas, H., & Soriano-Rodríguez, A. (2014). Apoyo social y funcionalidad familiar en personas con trastorno mental. Salud Mental, 37(5), 443-448. https://doi.org/10.17711/SM.0185-3325.2014.052
Caycho-Rodríguez, T., Valencia, P., Vilca, L. W., Cervigni, M., Gallegos, M., Martino, P., Barés, I., Calandra, M., Rey, C., López-Calle, C., Moreta-Herrera, R., Chacón-Andrade, E., Lobos-Rivera, M., Del Carpio, P., Quintero, Y., Robles, E., Panza, M., Gamarra, O., Buschiazzo, A., White, M., & Burgos, C. (2022). Cross-cultural measurement invariance of the fear of COVID-19 scale in seven Latin American countries. Death Studies, 1-15. https://doi.org/10.1080/07481187.2021.1879318
Caycho-Rodríguez, T., Vilca, L. W., Cervigni, M., Gallegos, M., Martino, P., Portillo, N., Barés, I., Calandra, M., & Burgos, C. (2022). Fear of COVID-19 scale: Validity, reliability and factorial invariance in Argentina’s general population. Death Studies, 1-10. https://doi.org/10.1080/07481187.2020.1836071
Ceballos, M., García, M. J., & Lagunes, R. (2017). Adaptación y validación en población mexicana del Cuestionario de personalidad tipo C (PCTC). Universitas Psychologica 16(2), 1-11. https://doi.org/10.11144/Javeriana.upsy16-2.avpm
Chen, F. F., West, S. G., & Sousa, K. H. (2006). A comparison of bifactor and second-order models of quality of life. Multivariate Behavioral Research, 41(2), 189-225. https://doi.org/10.1207/s15327906mbr4102_5
Costa, G., Salamero, M., & Gil, F. (2007). Validación del cuestionario MOS-SSS de apoyo social en pacientes con cáncer. Medicina Clínica, 128(18), 687-691. https://doi.org/10.1157/13102357
Dambi, J. M., Corten, L., Chiwaridzo, M., Jack, H., Mlambo, T., & Jelsma, J. (2018). A systematic review of the psychometric properties of the cross-cultural translations and adaptations of the Multidimensional Perceived Social Support Scale (MSPSS). Health and Quality of Life Outcomes, 16, 1-19. https://doi.org/10.1186/s12955-018-0912-0
Di Renzo, L., Gualtieri, P., Pivari, F., Soldati, L., Attinà, A., Cinelli, G., Leggeri, C., Caparello, G., Barrea, L., Scerbo, F., Esposito, E., & De Lorenzo, A. (2020). Eating habits and lifestyle changes during COVID-19 lockdown: An Italian survey. Journal of Translational Medicine, 18, 1-15. https://doi.org/10.1186/s12967-020-02399-5
Domínguez-Lara, S. (2019). Correlación entre residuales en análisis factorial confirmatorio: una breve guía para su uso e interpretación. Interacciones, 5(3), e207. https://doi.org/10.24016/2019.v5n3.207
Eagle, D. E., Hybels, C. F., & Proeschold-Bell, R. J. (2019). Perceived social support, received social support, and depression among clergy. Journal of Social and Personal Relationships, 36(7), 2055-2073. https://doi.org/10.1177/0265407518776134
Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in SEM. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (pp. 269-314). Information Age Publishing.
Gallegos, M., Zalaquett, C., Luna, S., Mazo-Zea, R., Ortiz-Torres, B., Penagos-Corzo, J. C., Portillo, N., Torres, I., Urzúa, A., Morgan, M., Polanco, F., Florez, A., & Lopes, R. (2020). Enfrentando la pandemia del coronavirus (Covid-19) en las Américas: recomendaciones y pautas para la salud mental. Revista Interamericana de Psicología, 54(1), e1304. https://doi.org/10.30849/ripijp.v54i1.1304
Gobierno de México (2020). Conferencia 12 de junio. https://coronavirus.gob.mx/2020/06/12/conferencia-12-de-junio-2/
Grey, I., Arora, T., Thomas, J., Saneh, A., Tohme, P., & Abi-Habib, R. (2020). The role of perceived social support on depression and sleep during the COVID-19 pandemic. Psychiatry Research, 293(113452), 1-6. https://doi.org/10.1016/j.psychres.2020.113452
Gupta, S., & Sahoo, S. (2020). Pandemic and mental health of the front-line healthcare workers: A review and implications in the Indian context amidst COVID-19, General Psychiatry, 33(5), e100284. https://doi.org/10.1136/gpsych-2020-100284
Hernández, R., & Mendoza, C. P. (2018). Metodología de la investigación: las rutas cuantitativa, cualitativa y mixta. McGraw Hill.
Herrera, B., Galindo, O., Bobadilla, R., Penedo, F., & Lerma, A. (2021). Propiedades psicométricas del Cuestionario MOS de Apoyo Social en una muestra de pacientes con enfermedades cardiovasculares en población mexicana. Psicología y Salud, 31(2), 225-235. https://doi.org/10.25009/pys.v31i2.2691
Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford.
Lakey, B., & Cronin, A. (2008). Low social support and major depression: Research, theory and methodological issues. In Keith S. Dobson & David J. A. Dozois (Eds.), Risk factors in depression (pp. 385-408). Elsevier. https://doi.org/10.1016/B978-0-08-045078-0.00017-4
Liu, C. H., Zhang, E., Wong, G. T. F., Hyun, S., & Hahm, H. C. (2020). Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: Clinical implications for U.S. young adult mental health. Psychiatry Research, 290(113172), 1-7. https://doi.org/10.1016/j.psychres.2020.113172
Lloyd-Jones, B. (2021). Developing competencies for emotional, instrumental, and informational student support during the COVID-19 pandemic: A human relations/human resource development approach. Advances in Developing Human Resources, 23(1), 41-54. https://doi.org/10.1177/1523422320973287
Londoño, N., Rogers, H., Castilla, J., Posada, S., Ochoa, N., Jaramillo, M., Oliveros, M., Palacio, J., & Aguirre-Acevedo, D. (2012). Validation of the Colombian MOS social support survey. International Journal of Psychological Research, 5(1), 142-150. https://doi.org/10.21500/20112084.770
Martínez, A. E., Sánchez, S., Aguilar, E. J., Rodríguez, V., & Riveros, A. (2014). Adaptation and Validation of the MOS Social Support Questionnaire in HIV + Mexican patients. Latin American Journal of Behavioral Medicine, 4(2), 93-101. http://www.journals.unam.mx/index.php/rlmc/article/view/53611
McDonald, R. P. (1999). Test theory: A unified treatment. Lawrence Erlbaum.
Mueller, R. O., & Hancock, G. R. (2001). Rethinking Construct Reliability Within Latent Variable Systems. In Structural equation modeling: Past and present. A festschrift in Honor of Karl G. Jöreskog (pp. 195-261). Scientific Software International.
Muyor-Rodríguez, J., Caravaca-Sánchez, F., & Fernández-Prados, J. (2021). COVID-19 fear, resilience, social support, anxiety, and suicide among college students in Spain. International Journal of Environmental Research and Public Health, 18(15), 8156. https://doi.org/10.3390/ijerph18158156
Qi, M., Zhou, S. J., Guo, Z. C., Zhang, L. G., Min, H. J., Li, X. M., & Chen, J. X. (2020). The effect of social support on mental health in Chinese adolescents during the outbreak of COVID-19. Journal of Adolescent Health, 67(4), 514-518. https://doi.org/10.1016/j.jadohealth.2020.07.001
R Core Team (2019). A language and environment for statistical computing (R version 3.6.1). R Foundation for Statistical Computing. http://www.r-project.org/
Ransing, R., Dashi, E., Rehman, S., Mehta, V., Chepure, A., Kilic, O., Hayatudeen, N., Orsolini, L., Vahdani, B., Adiukwu, F., González-Díaz, J., Larnaout, A., Pinto da Costa, M., Grandinetti, P., Soler-Vidal, J., Gashi, D., Shalbafan, M., Nofal, M., Pereira-Sánchez, V., & Ramalho, R. (2021). COVID-19 related mental health issues: A narrative review of psychometric properties of scales and methodological concerns in scale development. Australasian Psychiatry, 29(3), 326-332. https://doi.org/10.1177/1039856221992645
Ransing, R., Ramalho, R., Orsolini, L., Adiukwu, F., Gonzalez-Diaz, J., Larnaout, A., Pinto da Costa, M., Grandinetti, P., Gashi Bytyçi, D., Shalbafan, M., Patil, I., Nofal, M., Pereira-Sánchez, V., & Kilic, O. (2020). Can COVID-19 related mental health issues be measured? Brain, Behavior, and Immunity, 88, 32-34. https://doi.org/10.1016/j.bbi.2020.05.049
Reise, S. P. (2012). The rediscovery of bifactor measurement models. Multivariate Behavioral Research, 47(5), 667-696. https://doi.org/10.1080/00273171.2012.715555
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1-36. https://doi.org/10.18637/jss.v048.i02
RStudio Team (2018). RStudio: Integrated Development Environment for R. RStudio, Inc. http://www.rstudio.com/
Saltzman, L. Y., Hansel, T. C., & Bordnick, P. S. (2020). Loneliness, Isolation, and Social Support Factors in Post-COVID-19 Mental Health. Psychological Trauma: Theory, Research, Practice, and Policy, 12(S1), S55-S57. https://doi.org/10.1037/tra0000703
Schumacker, R. E., & Lomax, R. G. (2015). A Beginner’s Guide to Structural Equation Modeling (4th ed.). Routledge.
Sherbourne, C., & Stewart, A. (1991). The MOS Social Support Survey. Social Science & Medicine, 32(6), 705-714. https://doi.org/10.1016/0277-9536(91)90150-B
Sijtsma, K. (2009). On the use, the misuse, and the very limited usefulness of Cronbach’s alpha. Psychometrika, 74(1), 107-120. https://doi.org/10.1007/s11336-008-9101-0
Sociedad Mexicana de Psicología (2007). Código Ético del Psicólogo (4th ed.). Trillas.
Toledo-Fernández, A., Betancourt-Ocampo, D., & González-González, A. (2021). Distress, depression, anxiety, and concerns and behaviors related to COVID-19 during the first two months of the pandemic: A longitudinal study in adult Mexicans. Behavioral Sciences, 11(5), 76. https://doi.org/10.3390/bs11050076
Torres, C., Galindo-Aldana, G., García, I., Padilla-López, L., Alvarez, D., & Espinoza, Y. (2020). COVID-19 voluntary social isolation and its effects in sociofamily and children’s behavior. Salud Mental, 43(6), 263-271. https://doi.org/10.17711/sm.0185-3325.2020.036
Viladrich, C., Angulo-Brunet, A., & Doval, E. (2017). Un viaje alrededor de alfa y omega para estimar la fiabilidad de consistencia interna, Anales de Psicología, 33(3), 755-782. https://doi.org/10.6018/analesps.33.3.268401
Zinbarg, R. E., Revelle, W., Yovel, I., & Li, W. (2005). Cronbach’s, α Revelle’s β and McDonald’s ω H: Their relations with each other and two alternative conceptualizations of reliability. Psychometrika, 70, 123-133. https://doi.org/10.1007/s11336-003-0974-7
Zysberg, L., & Zisberg, A. (2022). Days of worry: Emotional intelligence and social support mediate worry in the COVID-19 pandemic. Journal of Health Psychology, 27(2), 268-277. https://doi.org/10.1177/1359105320949935
