Back

Exploration of barriers to providing mental health care and factors supporting access to mental health care in Australian prisons

Comben, C.; Burgess, M.; Rutherford, Z.; Meurk, C.; Rivas, L.; John, J.; Diminic, S.

2026-05-14 health systems and quality improvement
10.64898/2026.05.11.26352849 medRxiv
Show abstract

ObjectiveThis study aimed to understand barriers to providing mental health care in Australian prisons and explore factors supporting access to mental health care. MethodsThis qualitative study used focus groups with people with a lived experience of mental illness in prison or caring for someone in prison with mental illness and people involved in providing mental health care in prisons. Focus group transcripts were thematically analysed. ResultsFocus groups were held with eight participants. Identified barriers to providing and accessing mental health care in prison included perceived stigma, insufficient resourcing, logistics driven care, inconsistent standards, and tension between prison- and health-centred systems. Factors supporting access to mental health care in prisons included equivalence of care, individually tailored care, connection, resourcing, and coordinated care. ConclusionsIdentified barriers make providing mental health care in prisons difficult, resulting in unmet needs. Factors that support access highlight mechanisms available to improve outcomes, but their utility depends on addressing all barriers. Implications for Public HealthIdentified barriers and supporting factors can help guide service design to improve access and promote interagency collaboration across justice and health. Identified barriers can also be used to help inform evidence-based policy making, including workforce development and increased funding.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.