Demandas e recursos de tecnologias de informação e comunicação: evidências de validade de um instrumento
DOI:
https://doi.org/10.31211/rpics.2024.10.2.345Palavras-chave:
Demandas, Recursos, Tecnologias de Comunicação e Informação, Avaliação Psicológica, ValidaçãoResumo
Contexto: O modelo Demandas-Recursos em Tecnologias de Informação e Comunicação (TIC) propõe que a tecnologia pode atuar como recurso facilitador ou demanda adicional, influenciando o estresse e saúde ocupacional. Objetivo: Adaptar e validar as Escalas sobre Demandas e Recursos de TIC para o contexto brasileiro, explorando suas propriedades psicométricas. Métodos: Participaram 213 trabalhadores brasileiros que utilizavam TIC no desempenho laboral, a maioria do sexo masculino (64,8%) com média de idade de 35,5 anos e formação superior (92,5%). O instrumento foi administrado online, e os dados foram analisados através de Análise Fatorial Confirmatória (AFC) e coeficiente de fidedignidade Ômega. Resultados: A AFC revelou uma estrutura idêntica à original, com oito fatores para a escala de Demandas e dois para a escala de Recursos, ambos com coeficientes Ômega satisfatórios e índices de ajuste adequados. Conclusão: O instrumento apresenta validade psicométrica adequada para investigar demandas e recursos em ambientes de trabalho com TIC, oferecendo uma ferramenta útil para gestores que busquem avaliar e equilibrar esses aspectos no contexto laboral, prevenindo o estresse ocupacional.
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Referências
Ahmad, A. Y. B. (2024). Firm determinants that influence implementation of accounting technologies in business organizations. WSEAS Transactions on Business and Economics, 21, 1–11. https://doi.org/nqr5
Ahmed, Z., Nathaniel, S. P., & Shahbaz, M. (2021). The criticality of information and communication technology and human capital in environmental sustainability: Evidence from Latin American and Caribbean countries. Journal of Cleaner Production, 286, Artigo 125529. https://doi.org/gjjvng
Asparouhov, T., & Muthén, B. (2010). Simple Second Order Chi-Square Correction. http://bit.ly/3CsI1xZ
Bakker, A. B., Demerouti, E., De Boer, E., & Schaufeli, W. B. (2003). Job demands and job resources as predictors of absence duration and frequency. Journal of Vocational Behavior, 62(2), 341–356. https://doi.org/brhb59
Bakker, A. B., Van Veldhoven, M., & Xanthopoulou, D. (2010). Beyond the Demand-Control Model: Thriving on high job demands and resources. Journal of Personnel Psychology, 9(1), 3–16. https://doi.org/fskc4k
Bakker, A. B., Demerouti, E., & Sanz-Vergel, A. (2023). Job demands–resources theory: Ten years later. Annual Review of Organizational Psychology and Organizational Behavior, 10, 25–53. https://doi.org/gsb4k9
Carlotto, M. S., & Câmara, S. G. (2010). Tradução, adaptação e exploração de propriedades psicométricas da escala de tecnoestresse (RED/TIC). Psicologia em Estudo, 15(1), 171–178. https://doi.org/bp8qwd
Cassepp-Borges, V., Balbinotti, M. A. A. & Teodoro, M. L. M. (2010). Tradução e validação de conteúdo: uma proposta para adaptação de instrumentos. Em L. Pasquali, (Org.), Instrumentação psicológica. Fundamentos e práticas (pp.506–520). Artmed.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. https://doi.org/cc5
Day, A., Scott, N., & Kelloway, E. K (2010). Information and communication technology: Implications for job stress and employee well-being. Em P. L. Perrewé & D. C. Ganster (Eds.), New Developments in Theoretical and Conceptual Approaches to Job Stress (Vol. 8, pp. 317–350). https://doi.org/cshcb7
Day, A., Paquet, S., Scott, N., & Hambley, L. (2012). Perceived information and communication technology (ICT) demands on employee outcomes: The moderating effect of organizational ICT support. Journal of Occupational Health Psychology, 17(4), 473–491. https://doi.org/f4cxj4
Demerouti, E., Bakker, A. B., Nachreiner, F., & Schaufeli, W. B. (2001). The job demands-resources model of burnout. Journal of Applied Psychology, 86(3), 499–512. https://doi.org/ckks28
Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. https://doi.org/f2dpm2
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7.ª ed.). Pearson Education Limited.
Hajal, G. E. (2022). Teleworking and the jobs of tomorrow. Research in Hospitality Management, 12(1), 21–27. https://doi.org/nqsm
Hakanen, J., Bakker, A. B., & Schaufeli, W. B. (2006). Burnout and work engagement among teachers. The Journal of School Psychology, 43(6), 495–513. https://doi.org/bbvw5s
Hernández-Nieto, R. A. (2002). Contributions to statistical analysis. Universidad de Los Andes.
Hobfoll, S. E. (1989). Conservation of resources: A new attempt at conceptualizing stress. American Psychologist, 44(3), 513–524. https://doi.org/fj2csj
Hu, L.-T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/dbt
International Test Commission. (2017). The ITC guidelines for translating and adapting tests (2.ª ed.). https://bit.ly/48EKzFk
Kumar, P. S. (2024). Technostress: A comprehensive literature review on dimensions, impacts, and management strategies. Computers in Human Behavior Reports, 16, Artigo 100475. https://doi.org/nqtx
Kupang, G. B., Ballangan, M. G., Carantes, F. T., & Yanes, P. S. (2024). Unpacking technostress: A systematic review on its effects and mitigation. Cognizance Journal of Multidisciplinary Studies, 4(4), 11–21. https://doi.org/nq6n
Mahapatra, M., & Pati, S. P. (2018, June). Technostress creators and burnout: A job demands-resources perspective. Proceedings of the 2018 ACM SIGMIS conference on computers and people research (pp. 70–77). https://doi.org/nqts
Marôco, J. (2014). Análise de equações estruturais: Fundamentos teóricos, software & aplicações (2.ª ed.). ReportNumber.
Miles, J., & Shevlin, M. (2005). Applying regression and correlation: A guide for students and researchers. Sage.
Pansini, M., Buonomo, I., De Vincenzi, C., Ferrara, B., & Benevene, P. (2023). Positioning technostress in the JD-R model perspective: A systematic literature review. Healthcare, 11(446), 1–23. https://doi.org/nqr7
Parts, V. (2024). From technostress to digital well-being. Em S. Durst & A. Pevkur (Eds.), Digital transformation for entrepreneurship (pp. 95–116). World Scientific Publishing Co Pte Ltd. https://doi.org/nqr8
Rahman, H., & Singh, T. (2024). Technostress and work exhaustion: unravelling the mediating role of work-family conflict in post-pandemic remote workers. International Journal of Applied Management Science, 16(3), 261–277. https://doi.org/nqsp
Rani, U., & Furrer, M. (2021). Digital labour platforms and new forms of flexible work in developing countries: Algorithmic management of work and workers. Competition & Change, 25(2) 212–236. https://doi.org/ggmxmn
Rosseel, Y. (2012). Lavaan: An R package for structural equation Modeling. Journal of Statistical Software, 48, 1–36. https://doi.org/f3r4v8
Salanova, M., Llorens, S., Cifre, E., & Nogareda, C. (2007). El tecnoestrés: concepto, medida e intervención psicosocial. https://bit.ly/3NTTfhI
Salanova, M., Llorens, S., & Cifre, E. (2012). The dark side of technologies: Technostress among users of information and communication technologies. International Journal of Psychology, 48(3), 422–436. https://doi.org/ghdwsh
Scholze, A., & Hecker, A. (2024). The job demands-resources model as a theoretical lens for the bright and dark side of digitization. Computers in Human Behavior, 155, Artigo 108177. https://doi.org/gtkjcc
Stadin, M., Nordin, M., Anders Broström, Hanson, L. L. M., Westerlund, H., & Fransson, E. I. (2021). Technostress operationalised as information and communication technology (ICT) demands among managers and other occupational groups – Results from the Swedish Longitudinal Occupational Survey of Health (SLOSH). Computers in Human Behavior, 114, Artigo 106486. https://doi.org/ghhfb5
Stich, J-F, Farley, S., Cooper, C., & Tarafdar, M. (2015). Information and communication technology demands: Outcomes and interventions. Journal of Organizational Effectiveness: People and Performance, 2(4), 327–345. https://doi.org/gk4thb
Tabachnick, B. G., & Fidell, L. S. (2012). Using multivariate statistics (6.ª ed.). Pearson Education.
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/ctx6h7
Vieira, L. S., & Carlotto, M. S. (2021). Demandas e recursos de trabalho como preditores de tecnoestresse em trabalhadores que utilizam as tecnologias de informação e comunicação. Revista Gestão & Tecnologia, 21(3), 148–167. https://bit.ly/3AEGK6r
Wang, H., Ding, H., & Kong, X. (2023). Understanding technostress and employee well-being in digital work: The roles of work exhaustion and workplace knowledge diversity. International Journal of Manpower, 44(2), 334–353. https://doi.org/nqsq
Yıkılmaz, S., K. Yikilmaz, I., Bekmezci, M., Surucu, L., & Cetinkaya, B. (2024). Exploring the moderating effect of musculoskeletal pain on technostress-induced burnout: A cross-sectional study of bank employees. Healthcare, 12, 20, Artigo 2064. https://doi.org/nqsn
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Direitos de Autor (c) 2024 Mary Sandra Carlotto, Sheila Gonçalves Câmara, Lia Severo Vieira, Guilherme Welter Wendt, Arla Day
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