Salud Mental

Metric Properties of the Infodemic Signs and Symptoms Scale in Brazilian Older Adults

##plugins.themes.bootstrap3.article.main##

Ricardo Bezerra Cavalcante
Patricia Rodrigues Braz
Altemir José Gonçalves Barbosa
Renata Eloah de Lucena Ferretti-Rebustini
Nadia Shigaeff
Eduarda Rezende Freitas
Luan César Ferreira Simões
Regina Consolação dos Santos

Abstract

Introduction. Infodemics promote disinformation, triggering serious consequences. It is therefore necessary to evaluate the phenomena associated with infodemics and their effects on mental health.

Objective. Construct and analyze the internal structure validity and reliability of the Infodemic Signs and Symptoms Scale (ISSS) in older adults. The ISSS was designed to track signs and symptoms indicative of psychological distress associated with exposure to information on socially critical events.

Method. This is a psychometric study of the construction and validation of a measurement instrument. To conduct the study, the ISSS was administered online (web survey) and by phone to 3,003 older adults from different regions of Brazil.

Results. The instrument has good reliability (Cronbach’s alpha = .97 and McDonald’s omega = .97) and excellent replicability of the construct, as borne out by the GH index (latent = .982 and observed = .884). Evidence of the quality and efficacy of the measures showed high values for both the factor determination index (.991) and the EAP marginal reliability (.982), sensitivity rate (7.452) and expected percentage of actual differences (98%).

Discussion and conclusion. The instrument analyzed in this study fills a gap, as there were no validated instruments for measuring the effects of infodemics on the mental health of older adults. The analyzed evidence indicates that the ISSS has good internal structure validity and reliability for measuring the signs and symptoms of infodemics in older adults. The instrument will assist in screening for the mental distress in older adults caused by infodemics in emergency crisis contexts.

Keywords:
Psychological stress, infodemic, public health, mental health

References

Ahmad, A. R., & Murad, H. R. (2020). The impact of social media on panic during the COVID-19 pandemic in Iraqi Kurdistan: online questionnaire study. Journal of medical Internet research, 22(5), e19556. https://doi.org/10.2196/19556

Almeida, O. P., & Almeida, S. A. (1999). Confiabilidade da versão brasileira da Escala de Depressão em Geriatria (GDS) versão reduzida. Arquivos de Neuro-Psiquiatria, 57(2B), 421–426. https://doi.org/10.1590/s0004-282x1999000300013

Bridgman, A., Merkley, E., Loewen, P. J., Owen, T., Ruths, D., Teichmann, L., & Zhilin, O. (2020). The causes and consequences of COVID-19 misperceptions: Understanding the role of news and social media. Harvard Kennedy School Misinformation Review, 1(3). https://doi.org/10.37016/mr-2020-028

Broche-Pérez, Y., Fernández-Fleites, Z., Jiménez-Puig, E., Fernández-Castillo, E., & Rodríguez-Martin, B. C. (2020). Gender and Fear of COVID-19 in a Cuban Population Sample. International Journal of Mental Health and Addiction, 20(1), 83–91. https://doi.org/10.1007/s11469-020-00343-8

Buja, A., & Eyuboglu, N. (1992). Remarks on Parallel Analysis. Multivariate Behavioral Research, 27(4), 509–540. https://doi.org/10.1207/s15327906mbr2704_2

Costa, B. R. L. (2018). Bola de Neve Virtual: O Uso das Redes Sociais Virtuais no Processo de Coleta de Dados de uma Pesquisa Científica. Revista Interdisciplinar de Gestão Social, 7(1). https://doi.org/10.9771/23172428rigs.v7i1.24649

Costello, A. B., & Osborne, J. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research, and Evaluation, 10(1). https://doi.org/10.7275/jyj1-4868

Czeisler, M. É., Drane, A., Winnay, S. S., Capodilupo, E. R., Czeisler, C. A., Rajaratnam, S. M., & Howard, M. E. (2021). Mental health, substance use, and suicidal ideation among unpaid caregivers of adults in the United States during the COVID-19 pandemic: Relationships to age, race/ethnicity, employment, and caregiver intensity. Journal of Affective Disorders, 295, 1259–1268. https://doi.org/10.1016/j.jad.2021.08.130

De Cassia N., T. (2020). Crises, desastres naturais e pandemias: contribuições da Psicologia Positiva. Ciencias Psicológicas, 14(2), e2161. https://doi.org/10.22235/cp.v14i2.2161

Delgado, C. E., Silva, E. A., Castro, E. A. B. D., Carbogim, F. D. C., Püschel, V. A. D. A., & Cavalcante, R. B. (2021). COVID-19 infodemic and adult and elderly mental health: a scoping review. Revista da Escola de Enfermagem da USP, 55, e20210170. https://doi.org/10.1590/1980-220x-reeusp-2021-0170

Dsouza, D. D., Quadros, S., Hyderabadwala, Z. J., & Mamun, M. A. (2020). Aggregated COVID-19 suicide incidences in India: Fear of COVID-19 infection is the prominent causative factor. Psychiatry Research, 290, 113145. https://doi.org/10.1016/j.psychres.2020.113145

Elhai, J. D., Yang, H., McKay, D., & Asmundson, G. J. (2020). COVID-19 anxiety symptoms associated with problematic smartphone use severity in Chinese adults. Journal of Affective Disorders, 274, 576–582. https://doi.org/10.1016/j.jad.2020.05.080

Ferrando, P. J., & Lorenzo-Seva, U. (2017). Assessing the Quality and Appropriateness of Factor Solutions and Factor Score Estimates in Exploratory Item Factor Analysis. Educational and Psychological Measurement, 78(5), 762–780. https://doi.org/10.1177/0013164417719308

Fitzpatrick, K. M., Harris, C., & Drawve, G. (2020). Fear of COVID-19 and the mental health consequences in America. Psychological Trauma Theory Research Practice And Policy, 12(S1), S17–S21. https://doi.org/10.1037/tra0000924

Gaskin, C. J., & Happell, B. (2014). On exploratory factor analysis: A review of recent evidence, an assessment of current practice, and recommendations for future use. International Journal of Nursing Studies, 51(3), 511–521. https://doi.org/10.1016/j.ijnurstu.2013.10.005

González-Sanguino, C., Ausín, B., Castellanos, M., Saiz, J., & Muñoz, M. (2021). Mental health consequences of the Covid-19 outbreak in Spain. A longitudinal study of the alarm situation and return to the new normality. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 107, 110219. https://doi.org/10.1016/j.pnpbp.2020.110219

Hair Jr., J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (5th ed.). Prentice Hall.

Hou, F., Bi, F., Jiao, R., Luo, D., & Song, K. (2020). Gender differences of depression and anxiety among social media users during the COVID-19 outbreak in China:a cross-sectional study. BMC Public Health, 20(1), https://doi.org/10.1186/s12889-020-09738-7

Jakovljevic M. (2020). COVID-19 Crisis as a Collective Hero's Journey to Better Public and Global Mental Health. Psychiatria Danubina, 32(1), 3–5. https://doi.org/10.24869/psyd.2020.3

Jungmann, S. M., & Witthöft, M. (2020). Health anxiety, cyberchondria, and coping in the current COVID-19 pandemic: Which factors are related to coronavirus anxiety? Journal of Anxiety Disorders, 73, 102239. https://doi.org/10.1016/j.janxdis.2020.102239

Kitamura, E. S., Faria, L. R. D., Cavalcante, R. B., & Leite, I. C. G. (2022). Depressão e transtorno de ansiedade generalizada em idosos pela infodemia de COVID-19. Acta Paulista de Enfermagem, 35, https://doi.org/10.37689/acta-ape/2022ao03177

Kwiecinski, A. M. (2019). EPININ: Escala Psicométrica para Identificar Níveis de Infoxicação e Nomofobia em Estudantes do Sistema Superior de Ensino [Doctoral dissertation, Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul].

Lorenzo-Seva, U., & Ferrando, P. J. (2019). Robust Promin: A method for diagonally weighted factor rotation. Liberabit: Revista Peruana de Psicología, 25(1), 99–106. https://doi.org/10.24265/liberabit.2019.v25n1.08

Lorenzo-Seva, U., & Van Ginkel, J. R. (2016). Multiple Imputation of missing values in exploratory factor analysis of multidimensional scales: estimating latent trait scores. Anales de Psicología, 32(2), 596. https://doi.org/10.6018/analesps.32.2.215161

Martiny, C., Silva, A. C. D. O. E., Nardi, A. E., & Pachana, N. A. (2011). Tradução e adaptação transcultural da versão brasileira do Inventário de Ansiedade Geriátrica (GAI). Archives of Clinical Psychiatry (São Paulo), 38(1), 8–12. https://doi.org/10.1590/s0101-60832011000100003

Massena, P. N. (2014). Estudo de validação do Inventário de Ansiedade Geriátrica [Dissertation, Universidade Federal de Ciências da Saúde de Porto Alegre].

Rettie, H., & Daniels, J. (2021). Coping and tolerance of uncertainty: Predictors and mediators of mental health during the COVID-19 pandemic. American Psychologist, 76(3), 427–437. https://doi.org/10.1037/amp0000710

Riehm, K. E., Holingue, C., Kalb, L. G., Bennett, D., Kapteyn, A., Jiang, Q., Veldhuis, C. B., Johnson, R. M., Fallin, M. D., Kreuter, F., Stuart, E. A., & Thrul, J. (2020). Associations Between Media Exposure and Mental Distress Among U.S. Adults at the Beginning of the COVID-19 Pandemic. American Journal of Preventive Medicine, 59(5), 630–638. https://doi.org/10.1016/j.amepre.2020.06.008

Shanahan, L., Steinhoff, A., Bechtiger, L., Murray, A. L., Nivette, A., Hepp, U., Ribeaud, D., & Eisner, M. (2022). Emotional distress in young adults during the COVID-19 pandemic: evidence of risk and resilience from a longitudinal cohort study. Psychological Medicine, 52(5), 824–833. https://doi.org/10.1017/s003329172000241x

Sigurvinsdottir, R., Thorisdottir, I. E., & Gylfason, H. F. (2020). The Impact of COVID-19 on Mental Health: The Role of Locus on Control and Internet Use. International Journal of Environmental Research and Public Health, 17(19), 6985. https://doi.org/10.3390/ijerph17196985

Sivo, S. A., Fan, X., Witta, E. L., & Willse, J. T. (2006). The Search for "Optimal" Cutoff Properties: Fit Index Criteria in Structural Equation Modeling. The Journal of Experimental Education, 74(3), 267–288. https://doi.org/10.3200/jexe.74.3.267-288

Sun, Y., Li, Y., Bao, Y., Meng, S., Sun, Y., Schumann, G., Kosten, T., Strang, J., Lu, L., & Shi, J. (2020). Brief Report: Increased Addictive Internet and Substance Use Behavior During the COVID‐19 Pandemic in China. The American Journal on Addictions, 29(4), 268–270. https://doi.org/10.1111/ajad.13066

Tang, F., Liang, J., Zhang, H., Kelifa, M. M., He, Q., & Wang, P. (2021). COVID-19 related depression and anxiety among quarantined respondents. Psychology & Health, 36(2), 164–178. https://doi.org/10.1080/08870446.2020.1782410

Timmerman, M. E., & Lorenzo-Seva, U. (2011). Dimensionality assessment of ordered polytomous items with parallel analysis. Psychological Methods, 16(2), 209–220. https://doi.org/10.1037/a0023353

Van Tilburg, T. G., Steinmetz, S., Stolte, E., van der Roest, H., & de Vries, D. H. (2021). Loneliness and Mental Health During the COVID-19 Pandemic: A Study Among Dutch Older Adults. The Journals of Gerontology: Series B, 76(7), e249–e255. https://doi.org/10.1093/geronb/gbaa111

World Health Organization. (2021). Infodemic management: an overview of infodemic management during COVID-19, January 2020–May 2021. https://www.who.int/publications/i/item/9789240035966

Yabrude, A. T. Z., Souza, A. C. M. D., Campos, C. W. D., Bohn, L., & Tiboni, M. (2020). Desafios das Fake News com Idosos durante Infodemia sobre Covid-19: Experiência de Estudantes de Medicina. Revista Brasileira de Educação Médica, 44(suppl 1). https://doi.org/10.1590/1981-5271v44.supl.1-20200381

Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), 676. https://doi.org/10.1016/s0140-6736(20)30461-x

Zwielewski, G., Oltramari, G., Santos, A. R. S., Nicolazzi, E. M. D. S., Moura, J. A. D., Sant’ana, V. L. P., Schlindwein-Zanini, R., & Cruz, R. M. (2020). Protocolos para tratamento psicológico em pandemias: as demandas em saúde mental produzidas pela Covid-19. Debates em Psiquiatria, 10(2), 3–37. https://doi.org/10.25118/2236-918x-10-2-4