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Health research concerning Indigenous peoples has been strongly characterised by deficit discourse—a ‘mode of thinking’ that is overly focused on risk behaviours and problems. Strengths‐based approaches offer a different perspective by promoting a set of values that recognise the capacities and capabilities of Indigenous peoples. In this article, we seek to understand the conceptual basis of strengths‐based approaches as currently presented in health research. We propose that three main approaches exist: ‘resilience’ approaches concerned with the personal skills of individuals; ‘social–ecological’ approaches, which focus on the individual, community and structural aspects of a person's environment; and ‘sociocultural’ approaches, which view ‘strengths’ as social relations, collective identities and practices. We suggest that neither ‘resilience’ nor ‘social–ecological’ approaches sufficiently problematise deficit discourse because they remain largely informed by Western concepts of individualised rationality and, as a result, rest on logics that support notions of absence and deficit. In contrast, sociocultural approaches tend to view ‘strengths’ not as qualities possessed by individuals, but as the structure and character of social relations, collective practices and identities. As such, they are better able to capture Indigenous ways of knowing and being and provide a stronger basis on which to build meaningful interventions.

Objective: A history of alcohol and other drug (AoD) use is common among men entering prison and often linked to the crime for which they are imprisoned. This is the first systematic review of prison‐based, behavioural AoD treatment programs for more than a decade and the first that reviews the methodological quality of evaluations. This review aims to create an understanding of the quality of research in this field and identify the most effective AoD use treatment for men in prison. Methods: A PRISMA‐compliant systematic review of international, peer‐reviewed research published between January 1995 and December 2015. The Dictionary for Effective Public Health Practice Project was used to assess the methodological quality of papers. Results: A total of 25 relevant papers were identified, of which 12 were rated as methodologically sound. Four of these measured post‐release AoD use and three reported statistically significant reductions in AoD use. Conclusions: Although there is relatively little methodologically strong evidence of the impact of prison‐based AoD treatment, and no Australian papers studies, current best‐evidence practice is Cognitive behavioural therapy delivered in Therapeutic Community (TC) settings. Implications for public health: Prison‐based TC treatment should be available to people in prison who have a history of AoD use.

Screening and assessment (Chapter 2): screening techniques to identify patients with alcohol problems, and subsequent assessments for clinicians to undertake before providing specific treatments or interventions.• Interventions, treatments, relapse prevention and aftercare (Chapter 3): a range of varying interventions and treatments, including brief interventions, brief e-health interventions, psychosocial interventions, alcohol withdrawal management, pharmacotherapy options, and peer support programs. In the final section of this chapter, relapse prevention, aftercare, and long term follow-up strategies are discussed.• Considerations for specific populations (Chapter 4): the management of alcohol problems and treatment considerations for specific population groups of interest in Australia -genderspecific considerations, adolescents and young people, pregnant and breastfeeding women, Aboriginal and Torres Strait Islander peoples, culturally and linguistically diverse groups, sexually diverse and gender diverse populations, older people, and cognitively impaired people.• Understanding comorbidities (Chapter 5): the importance of considering a range of comorbidities when providing treatment for alcohol problems. Polydrug use, comorbid mental disorders, and physical-related comorbidities are discussed.The content of this supplement is based on the various chapters of the full Guidelines for the Treatment of Alcohol Problems, which were based on reviews of the evidence, including well designed meta-analyses and randomised controlled trials, wherever possible. Where this evidence was not available, recommendations were based on the best available research or clinical experience. Each recommendation in the guidelines is accompanied with a level of evidence based on National Health and Medical Research Council evidence recommendations (Box 2), 21 with "A" representing the most evidence and "GPP" (good practice point) indicating a recommendation with no evidence.For more on the Guidelines for the Treatment of Alcohol Problems, visit https://alcoh oltre atmen tguid elines.com.au/. Acknowledgements:The Guidelines for the Treatment of Alcohol Problems project was funded by the Australian Government, under the Drug and Alcohol Program. We would like to express our gratitude to members of the Guidelines Steering Committee for providing invaluable guidance and advice on this project. We thank Daniel Winter, Sophia Little, Brennan Geiger and James Pham for providing research and administrative support, and Joshua Watt for providing clinical support, across sections of this supplement. Finally, we thank Donna Ah Chee, Kylie Lee, Teagan Weatherall, Craig Holloway and Martin Nean for conversations and work which informed the Aboriginal and Torres Strait Islander peoples section in the guidelines and Chapter 4 of this supplement.Competing interests: Paul Haber has been funded by the Lambert Initiative for Cannabinoid Therapeutics at the University of Sydney to undertake clinical trials of cannabinoid treatment for alcohol withdra...

Abstract. Background: Suicide has been considered an important public health issue for years and is one of the main causes of death worldwide. Despite prevention strategies being applied, the rate of suicide has not changed substantially over the past decades. Suicide risk has proven extremely difficult to assess for medical specialists, and traditional methodologies deployed have been ineffective. Advances in machine learning make it possible to attempt to predict suicide with the analysis of relevant data aiming to inform clinical practice. Aims: We aimed to (a) test our artificial intelligence based, referral-centric methodology in the context of the National Health Service (NHS), (b) determine whether statistically relevant results can be derived from data related to previous suicides, and (c) develop ideas for various exploitation strategies. Method: The analysis used data of patients who died by suicide in the period 2013–2016 including both structured data and free-text medical notes, necessitating the deployment of state-of-the-art machine learning and text mining methods. Limitations: Sample size is a limiting factor for this study, along with the absence of non-suicide cases. Specific analytical solutions were adopted for addressing both issues. Results and Conclusion: The results of this pilot study indicate that machine learning shows promise for predicting within a specified period which people are most at risk of taking their own life at the time of referral to a mental health service.