Abstract:
Mental health in the workplace is becoming of ever greater importance. General
occupational health surveillance programmes are already in widespread use, with
established referral systems for treatment and rehabilitation, and the same mechanisms
could be expanded to include mental health screening and intervention. This study
aimed to develop a concise composite mental health screening tool, based on analysis
of existing data, for application in routine occupational health surveillance in South Africa.
Data from workplace occupational health surveillance programs from 2,303 participants
were analysed. Participants completed a number of questions/scaled items collated
into a survey format, and partook in an interview with a psychologist. The data was
analysed using frequency of positive self-reports, Chi square to calculate associations
with outcomes, Receiver Operator Characteristic curve analysis to explore predictive
ability, and binomial logistic regression to calculate the relative contribution of markers
to outcomes. An exploratory factor analysis was further conducted on identified items.
A general workplace model with 14 markers (and a maritime workplace model with
17 markers) were identified. The factor analysis suggested their organisation into five
domains (similar for both models), namely neurocognitive health, common mental
disorders, history of adaptation in occupational specific contexts, family-work interface,
and stress overload. The study’s data-driven approach proposed a concise composite
screener with less than 50 items, comprising five domains. This tool appears useful in
identifying employees at risk for workplace injuries or poor mental health outcomes, and
could be applied to related workplace settings in South Africa.
