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Studies that synthesised the pooled prevalence of depressive symptoms and work-related psycho-social factors among HCWs exposed to these factors are scarce. Therefore, this review aimed to synthesise information on pooled prevalence and association with work-related psychosocial factors with depressive symptoms in healthcare workers. Observational studies reporting prevalence and measures of effect sizes for work-related psychosocial factors of depressive symptoms were searched from PubMed, Scopus, CINHAL, Cochrane, PsycINFO, and Psychology and Behavioural Sciences. Primary studies that reported prevalence of depressive symptoms and effect sizes for work-related psychosocial factors (job-strain, workplace social support, effort reward ratio, and overcommitment were included in the review. Healthcare workers. The random-effects model was used due to significant anticipated heterogeneity. Study quality was assessed using the Joanna Briggs Institute. Heterogeneity was evaluated using the Cochran’s Q test and quantified using the I2 statistic. Publication bias was evaluated using funnel plots, Egger’s and Begg’s test. Thirty-one studies with 57,847 participants were included in the review. The pooled prevalence of depressive symptoms was 30.9% (95% CI 22.7–40.6%) with significant heterogeneity of I-Squared = 99.6% with p-value < 0.001. Those healthcare workers who perceived effort-reward imbalance (ERR > 1) had higher odds of experiencing depressive symptoms (pOR 4.11, 95% CI 2.93, 5.77). Similarly, over-commitment (pOR 2.88, 95% CI 1.87, 4.44), higher job strain (pOR 2.47, 95% CI 1.60, 3.80), and lower social support (pOR 2.36, 95% CI 1.58–3.51) were associated with higher odds of depressive symptoms. The review highlights the need to consider workplace interventions that may reduce depressive symptoms among HCWs and enhance rewards, optimising commitments, reducing job strain and improving social support in healthcare settings. Future longitudinal studies and intervention studies for low-income countries are required to establish causal relationships.