Identifying psychological distress data available in nationally representative surveys: A scoping review and case study of Australian surveys

Soc Psychiatry Psychiatr Epidemiol. 2025 Aug 11. doi: 10.1007/s00127-025-02981-6. Online ahead of print.

ABSTRACT

PURPOSE: Mental health data are crucial for understanding trends in psychological distress. This scoping review aimed to identify and describe surveys of representative samples of the Australian household population that measured psychological distress, and to provide a case study illustrating how datasets can be systematically summarized to assist researchers to more easily identify available datasets.

METHODS: We systematically searched PubMed and data archives for surveys state or nationally representative of the Australian household population that assessed psychological distress.

RESULTS: We provide a searchable metadata database characterizing 283 identified datasets from 41 studies (25 cross-sectional, 16 longitudinal) conducted between 1989 and 2023. Thirty-nine psychological distress instruments were used, with the Kessler Psychological Distress scale (K10) [1] most common (n = 114 datasets). Surveys also frequently measured demographics, physical health, and socioeconomic information. Stratified random sampling of geographic areas was the most common sampling frame, and adults the most frequently sampled group. There was notably less representation of important subgroups of the population, including youth, Aboriginal and Torres Strait Islander people, and people with disabilities, despite evidence of high distress prevalence in these groups.

CONCLUSIONS: This review provides valuable metadata summarizing available psychological distress datasets, including information on sampling designs, instrumentation, and covariates. This metadata is available to other researchers, enabling efficient identification of relevant datasets, promoting data sharing, and supporting future data integration. This method for systematically compiling metadata can be replicated for data related to other topics important to public health to facilitate greater data utilization.

PMID:40789817 | DOI:10.1007/s00127-025-02981-6