Prevalence Estimate for Adjustment Disorders in the South African Navy

Introduction and Aim

Adjustment Disorder is among the most commonly diagnosed mental disorders in the armed forces, with a mean prevalence estimated at 7.4% across military populations. The prevalence in South African military populations is not known. This study aimed to estimate the prevalence of Adjustment Disorders in the South African Navy and to explore potential risk factors.

Methods

In this cross-sectional study, a representative sample of 714 sailors completed the International Adjustment Disorder Questionnaire, and also provided information from their biennial occupational health assessment mental health screening, which included other clinical screeners of mental health and adjustment history.

Results

The estimated prevalence of Adjustment Disorders in the South African Navy was 6.9%, and was proportionally distributed across gender and age categories. Depression and PTSD were the main comorbid conditions. Risk factors included a) history of adjustment difficulties during military deployment or family adjustment difficulties, b) domestic discord (difficulties in relationship with spouse/partner or immediate family), and c) the experience of stress overload (i.e., that the demands of life are overwhelming available resources).

Conclusion

The estimated prevalence was similar to the expectation of military personnel generally, although the self-report data needs to be interpreted cautiously. The contributing risk factors offer possible direction for targeted intervention, e.g., skills training and relationship counselling to enhance coping with military service and family challenges, and cognitive behaviour therapy generally to address sailors' experience of stress overload.

A Concise Occupational Mental Health Screening Tool for South African Workplaces

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.