Burnout as a predictor of depression: a cross-sectional study of the sociodemographic and clinical predictors of depression amongst nurses in Cameroon

Abstract

BackgroundDepression is a debilitating mental health condition which affects an estimated 350 million people worldwide annually. Nurses are twice as likely to suffer from depression than professionals in other professions. This leads to a considerable loss of efficiency and productivity. We sought to determine the prevalence and predictors of depression among nurses in Cameroon.MethodsCross-sectional analysis carried out over 6 months (January – June 2018) using nurses from public and private healthcare institutions sampled consecutively in the two English-speaking regions (North west and South west regions) of Cameroon. The nurses were handed a structured, printed, self-administered questionnaire to fill and hand in at their earliest convenience. Depression and burnout were assessed using the Patient Health Questionnaire – 9 and the Oldenburg Burnout Inventory respectively.ResultsA total of 143 nurses were recruited (mean age: 29.75 ± 6.55 years; age range: 20–55 years, 32.87% male). The overall prevalence of depression was 62.24%. Independent predictors of depression after multivariable analysis were: Number of night shifts a week (adjusted odds ratio: 1.58; p value: 0.045, 95% CI; 1.01, 2.48) and Total Oldenburg Burnout Inventory score (adjusted odds ratio: 1.21, p value: 0.001; 95% CI; 1.08, 1.35). Recreational drug use was also found to perfectly predict the outcome – depression.ConclusionDepression is highly prevalent among nurses in the English-speaking regions of Cameroon. Accurate predictors could prove vital for early detection and management of affected individuals. Predictors presented herein require further investigation via multicentric nationwide studies, to obtain more generalizable results.

Differential aspects of chronic work-related stress predict depression in registered and geriatric nurses

“…Other studies additionally focused on burnout (Duan-Porter et al, 2018;Huang et al, 2018;H. Li et al, 2018;Maharaj et al, 2018;Mbanga et al, 2019;Nantsupawat et al, 2017;Vasconcelos & Martino, 2018;Vasconcelos et al, 2018). To date the concept of burnout is the subject of an ongoing debate and might fail to predict (sub-)clinical states of depression (Bianchi, Schonfeld & Laurent, 2015a, 2015bSchonfeld & Bianchi, 2016).…”

“…Nonetheless, possible predictors of depression and burnout amongst nurses have yet to be fully understood. However, several studies suggest the impact of chronic work stress on the etiology of depression in nurses (Huang, Wu, Ho & Wang, 2018;Mbanga et al, 2019;Vasconcelos & Martino, 2018;Vasconcelos, Martino & Franca, 2018). Surprisingly, only few studies have assessed stress-related factors in the working environment of geriatric nurses.…”

The Relationship between Working Night Shifts and Depression among Nurses: A Systematic Review and Meta-Analysis

“… The included studies’ risk of bias as determined by the Research Triangle Institute Item Bank [ 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ]. …”

“… Forest plot of the summary of odds ratio of comparable studies [ 20 , 23 , 24 , 25 , 29 , 31 , 33 , 36 ]. …”

A Brief Burnout Evaluation Scale (BBES) as a potential tool to prevent collapse of the health care task force during the COVID-19 pandemic

“…Moreover, even when controlling for depression, burnout symptoms result in considerable costs to the individual, the quality of patient care, and to society itself. 1,[4][5][6][7] These studies also reveal that the key dimensions that most clearly characterize patients with burnout are emotional exhaustion (EE) and depersonalization (DP) as defined by the Maslach Burnout Inventory (MBI) and/or the Oldenburg Burnout Inventory. Those two dimensions are also the ones more related to depression and psychological distress.…”