The Impact of Internet Addiction and Job Satisfaction on Mental Health Symptoms among a Sample of Portuguese Workers

Henrique Pereira, Gergely Fehér, Antal Tibold, Graça Esgalhado, Vítor Costa and Samuel Monteiro
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Henrique Pereira: Department of Psychology and Education, Faculty of Social and Human Sciences, University of Beira Interior, Pólo IV, 6200-209 Covilhã, Portugal
Gergely Fehér: Centre for Occupational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary
Antal Tibold: Centre for Occupational Medicine, Medical School, University of Pécs, 7624 Pécs, Hungary
Graça Esgalhado: Department of Psychology and Education, Faculty of Social and Human Sciences, University of Beira Interior, Pólo IV, 6200-209 Covilhã, Portugal
Vítor Costa: Department of Psychology and Education, Faculty of Social and Human Sciences, University of Beira Interior, Pólo IV, 6200-209 Covilhã, Portugal
Samuel Monteiro: Department of Psychology and Education, Faculty of Social and Human Sciences, University of Beira Interior, Pólo IV, 6200-209 Covilhã, Portugal

IJERPH, 2021, vol. 18, issue 13, 1-11

Abstract: Not many studies assessing the impact of internet addiction (IA) and job satisfaction (JS) on mental health symptoms (MHS) among active workers exist. Therefore, the purpose of this study was as follows: (a) to assess the presence of criteria for IA among a sample of active workers; (b) to analyze differences in IA, JS and MHS, by gender; (c) to analyze association levels among IA, JS, and MHS; and (d) to determine the predictive effect of IA and JS on MHS. In total, 1064 participants ( M age = 40.66; SD = 12.02) completed a survey containing four categories of measures: demographic information, internet addiction, job satisfaction, and mental health symptoms (anxiety and depression). Results showed a presence of 13.3% for IA among the sample. Male participants showed higher scores of IA and JS but lower scores of overall MSH than female participants did. Significant positive correlations were found between overall IA and MHS, and significant negative correlations were found between IA and JS, and MHS and JS. Hierarchical linear regression analysis showed that strong predictors of MHS were age (being older), gender (being female), not having enough economic funds, being unsatisfied with the leadership in the job, being unsatisfied with the nature of the job, and having higher scores in salience and excessive use regarding IA. In conclusion, addiction to internet technology is a risk factor with implications for occupational satisfaction and mental health.

Keywords: internet addiction; job satisfaction; mental health (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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