Risk assessment for job burnout with a mobile health web application using questionnaire data: a proof of concept study

Abstract

BackgroundJob burnout has become a rampant epidemic in working societies, causing high productivity loss and healthcare costs. An easy accessible tool to detect clinically relevant risk may bear the potential to timely avert the dire sequelae of burnout. As a start, we performed a proof of concept study to test the utilization of a mobile health web application for a free and anonymous burnout risk assessment with established questionnaires.MethodsWe designed a client-side javascript web application for users who filled out demographic and psychometric data forms over the internet. Users were recruited through social media, back links from hospital websites, and search engine optimization. Similar to population-based studies, we used the Maslach Burnout Inventory-General Survey (MBI-GS) to calculate a burnout risk index (BRIX). As additional mental health burden indices, users filled out the Perceived Stress Scale, Insomina Severity Index, and Profile of Mood States.ResultsWithin six months, the MBI-GS was completed by 11,311 users (median age 33 years, 85 % women) of whom 20.0 % had no clinically relevant burnout risk, 54.7 % had mild-to-moderate risk, and 25.3 % had high risk. In the 2947 users completing all questionnaires, female sex (B = -0.03), cohabiting (B = -0.03), negative affect (B = 0.46), positive affect (B = -0.20), perceived stress (B = 0.18), and insomnia symptoms (B = 0.04) explained 56.2 % of the variance in the continuously scaled BRIX. The reliability was good to excellent for all psychometric scales. The weighting of the BRIX with mental health burden indices primarily modified the risk in users with mild-to-moderate burnout risk.ConclusionsA low-threshold web application can reliably assess the risk of job burnout. As the bulk of users had clinically relevant burnout scores, a web application may be useful to target employees at risk. The clinical value of the BRIX and its modification with coexistent/absent mental health burden awaits evaluation with work and health outcomes.

<p>Recovery Experience: A Concept for Maintaining Quality of Life and Its Mediating Effect Among Female Nurses in China</p>

“…48,49 Job burnout may lead to helplessness, despair, sleep problems, and exhaustion and ultimately affect physical and mental health, which are highly associated with QOL. 50 Analysis of data in this study showed that nurses' QOL was lower when they reported a higher level of burnout, which is consistent with Suner's study. 48 The higher the job burnout was, the lower the QOL the nurses experienced, which was in agreement with Khamisa's study that showed nurses had high levels of job burnout and poor general health.…”

Relationship between job burnout and somatic diseases: a network analysis

“…A campaign was launched via Medinside, Winsider AG, Winterthur, Switzerland, an open access portal for the health care sector, particularly recruiting physicians, as they show high prevalence of burnout 14 . Data were collected with Burnout Protector, a previously described mobile health web application 13 . Age below 18 was the only exclusion criterion.…”

“…Nevertheless, all data was collected in accordance with scientific standards specified by Switzerland’s Federal Act on Research Involving Human Beings 15 and in compliance with the national ethical guidelines on the handling of personal data in the field of medicine issued by the Federal Data Protection Commissioner of Switzerland 16 . All respondents provided informed consent to their anonymized data being used for research 13 .…”

“…For network analysis and following logistic regression, categorical variables for high vs. low scores of each burnout dimension, clinically relevant vs. non-relevant depressive symptoms and high versus low educational level were used 13 . Age was dichotomized at a threshold of 45 years, as EX was shown to be predictive of increased all-cause mortality in employees under 45 years of age 23 .…”

“…We investigated the association of high EX, high CYN and low PE with somatic diseases in users of a mobile health web application 13 performing network analysis, a novel approach in this field of research. The used network analytical method allows to investigate the association of two variables, while simultaneously controlling for the effect of all other variables in datasets with multiple variables.…”