Technostress and techno-addiction: analysis of the role of work–family balance
Main Article Content
Keywords
Addiction, Work context, Stress, Family, Psychosocial risks, Human talent, Technologies
Abstract
Objective: to analyze the role of work–family balance in technostress and techno-addiction among colombian workers. This objective aligns with the need to study resources that protect workers from emerging psychosocial risks. Method: A non-experimental, cross-sectional study with an associative strategy was conducted, involving 512 participants (326 women and 186 men). A sociodemographic data sheet and RED-Technostress and SWING work–family interaction questionnaires were administered. Univariate and bivariate analyses were performed, and a path model was designed. Results: A significant negative correlation was identified between work–family balance and discomfort (r=-.206, p<.001), compulsive use (r=-.169, p<.000), and excessive use (r=-.233, p<.000). Additionally, the estimated values in the path
model indicate relationships between work–family balance and discomfort (r=-.21, p<.001), compulsive use (r=-.17,
p<.001), and excessive use of technology (r=-.23, p<.001); these are moderate and inversely proportional, whereas
there is no significance with rejection (r=-.02). This means that greater work–family balance results in less discomfort,
compulsive use, and excessive use of technology. Conclusions: It is determined that work–family balance serves as a resource that can mitigate psychosocial risks such as technostress and techno-addiction. There is a negative relationship between work–family balance and discomfort from technology use, suggesting that workers who successfully balance their work and family responsibilities may experience less stress and anxiety related to technology use.
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Bakker, A., & Geurts, S. (2004). Toward a Dual-Process Model of Work-Home Interference. Work and Occupations, 31(3), 345–366. https://doi.org/10.1177/0730888404266349
Braun, A. C., Machado, W., De Andrade, A. L., & De Oliveira, M. Z. (2019). Why work-family conflict can drive your executives away? Revista de Psicología, 37(1), 251–278. https://doi.org/10.18800/psico.201901.009
Bray, J., Hinde, J., Kaiser, D., Mills, M., Karuntzos, G., Genadek, K., Kelly, E., Kossek, E., & Hurtado, D. (2018). Effects of a Flexibility/Support Intervention on Work Performance: Evidence from the Work, Family, & Health Network. American Journal of Health Promotion, 32(4), 963–970. https://doi.org/https://doi.org/10.1177/0890117117696244
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Byun, S., Ruffini, C., Mills, J. E., Douglas, A. C., Niang, M., Stepchenkova, S., Lee, S. K., Loutfi, J., Lee, J. K., Atallah, M., & Blanton, M. (2009). Internet addiction: Metasynthesis of 1996-2006 quantitative research. Cyberpsychology and Behavior, 12(2), 203–207. https://doi.org/10.1089/cpb.2008.0102
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Castillo, J. (2019). El interés de comprender la relación entre salud, demandas ocupacionales y esfuerzo físico relativo en trabajadores activos. Revista Ciencias de La Salud, 17(2), 170–174. https://revistas.urosario.edu.co/xml/562/56259511001/index.html
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De Wet, W., Koekemoer, E., & Nel, J. A. (2016). Exploring the impact of information and communication technology on employees’ work and personal lives. SA Journal of Industrial Psychology, 42(1), 1–11. https://doi.org/10.4102/sajip.v42i1.1330
Delpechitre, D., Black, H. G., & Farrish, J. (2019). The dark side of technology: examining the impact of technology overload on salespeople. Journal of Business and Industrial Marketing, 34(2), 317–337. https://doi.org/10.1108/JBIM-03-2017-0057
Derks, D., van Duin, D., Tims, M., & Bakker, A. B. (2015). Smartphone use and work-home interference: The moderating role of social norms and employee work engagement. Journal of Occupational and Organizational Psychology, 88(1), 155–177. https://doi.org/10.1111/joop.12083
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Jun 28, 2024
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Quiroz-González, E., Espinal-Guevara, L., & Villavicencio-Ayub, E. (2024). Technostress and techno-addiction: analysis of the role of work–family balance. Desarrollo Gerencial, 16(1), 1–20. https://doi.org/10.17081/dege.16.1.6831
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Author Biographies
Eliana Quiroz-González, Universidad Católica de Pereira, Pereira, Colombia.
PhD (s) in Health. Psychology and Psychiatry from the Universidad de Almería. Master’s degree in Human Talent Management from the Universidad de Manizales and Psychologist from the Universidad Católica de Pereira. She is a professor and researcher in the Psychology Program at the Universidad Católica de Pereira and is part of the research group in Communication, Education, and Culture. Recognized by Minciencias as an associate researcher, she has work experience in human resources management, organizational consulting, and university teaching. Her research interests focus on mental health in the workplace, prevention of psychosocial risks, humanization in health services, and the development of healthy organizations.
Luisa Espinal-Guevara, Universidad Católica de Pereira, Pereira, Colombia.
Psychologist from the Universidad Católica de Pereira. She participated in the research seedbed and investigative residence of the research group in Communication, Education, and Culture of the Faculty of Humanities, Social Sciences, and Education at the Universidad Católica de Pereira. She has professional experience in human resources departments. Her areas of interest include psychosocial factors in the workplace, work-family interaction, and the maladaptive use of Information and Communication Technologies.
Erika Villavicencio-Ayub, Universidad Nacional Autónoma de México, Ciudad de México, México.
PhD in Occupational Health Psychology. Master’s degree in Organization Management, and Bachelor's degree in Psychology. She is a full-time researcher and professor at the Faculty of Psychology of the Universidad Nacional Autónoma de México. She served as the coordinator of organizational psychology from 2016 to 2022. Teaches in postgraduate programs at various universities. She is a specialized reference in mental health and strategic human resources management. Her main lines of research include technostress, work addiction, glass ceiling, psychosocial factors, telecommuting, occupational stress, and the impact of mental health on productivity.