Information and communication technology demands and resources: Validity evidence of a measure
DOI:
https://doi.org/10.31211/rpics.2024.10.2.345Keywords:
Demands, Resources, Communication and Information Technologies, Psychological Assessment, ValidationAbstract
Background: The Demands-Resources Model in Information and Communication Technologies (ICT) suggests that technology can act as a facilitating resource or add demands, influencing occupational stress and health. Objective: To adapt and validate the ICT Demands and Resources Scales in the Brazilian context, exploring their psychometric properties. Methods: The study involved 213 Brazilian workers who used ICT in their job tasks, mostly male (64.8%), with an average age of 35.5 and higher education (92.5%). The measure was administered online, and the data were analyzed using Confirmatory Factor Analysis (CFA) and the Omega reliability coefficient. Results: The CFA revealed a structure similar to the original, with eight factors for the Demands Scale and two for the Resources Scale, both with satisfactory Omega coefficients and adequate fit indices. Conclusion: The measure shows adequate psychometric validity for investigating demands and resources in ICT work environments, offering a useful tool for managers seeking to assess and balance these aspects in the workplace, thereby helping prevent occupational stress.
Downloads
References
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
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Mary Sandra Carlotto, Sheila Gonçalves Câmara, Lia Severo Vieira, Guilherme Welter Wendt, Arla Day
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The authors retain the copyright and grant the journal right of first publication with the work simultaneously licensed under the Creative Commons Attribution-NonCommercial 4.0 International License that allows the sharing of work and recognition of authorship and initial publication in this journal.