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Technostress: how does it affect the productivity and life of an individual? Results of an observational study
Giuseppe La Torre1, Veronica De Leonardis1, Marta Chiappetta1
1Department of Public Health and Infectious Diseases, Sapienza University of Rome, 00185, Rome, Italy.
Objectives:
Technostress is an emergent phenomenon related to the pervasive use of technology and is associated with the increased computerisation and digitalisation seen over recent decades. This cross-sectional observational study aims to investigate the impact that stress from the use of technologies (i.e. technostress) has on the productivity and life of an individual.
Study Design:
Cross-sectional study.
Methods:
Data were collected using a previously proposed and validated questionnaire. The questionnaire was translated into Italian and transformed into an online format with a Google Docs form. The questionnaire was then associated with a link and QR code (also available in paper format) and disseminated manually and through the use of e-mail and social networks, such as Facebook and Twitter.
Results:
The study sample included 313 individuals, 54.6% of whom were women. The mean age of the sample participants was 34.7 years. The dependent variables were technstressors (i.e. techno-overload, techno-invasion, techno-complexity, techno-insecurity and techno-uncertainty), role stressors (i.e. role overload and role conflict) and productivity. In the multivariate analysis, techno-overload was significantly associated with female gender (β = 0.128; P = 0.018) and unemployment (β = -0.303; P < 0.001); techno-invasion was significantly associated with female gender (β = 0.098; P = 0.081) and degree-level education (β = 0.149; P = 0.008); techno-complexity was significantly associated with female gender (β = 0.107; P = 0.057) and being married (β = 0.113; P = 0.046); techno-uncertainty was significantly associated with unemployment (β = 0.337; P < 0.001); role overload was significantly associated with female gender (β = 0.160; P = 0.014) and productivity was significantly associated with degree-level education (β = 0.125; P = 0.057).
Conclusions:
This observational study evaluated the phenomenon of both work-related and non-work-related technostress of 313 individuals aged between 16 and 65 years. The present study investigated the impact of five techno-stressors, two role stressors and productivity. The results indicate that different techno-stressors are significantly associated with female gender, degree-level education and unemployment. Further research in this field is required to better understand and clarify the epidemiology, clinical presentation and determinants of technostress.
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