Systematic Review of Arts-Based Interventions to Address Suicide Prevention and Survivorship in Australia, Canada, the United Kingdom, and the United States of America
Bibliographic record
Abstract
Study Objective. Suicide is a serious health problem that is shaped by a variety of social and mental health factors. A growing body of research connects the arts to positive health outcomes; however, no previous systematic reviews have examined the use of the arts in suicide prevention and survivorship. This review examined how the arts have been used to address suicide prevention and survivorship in nonclinical settings in Australia, Canada, the United Kingdom, and the United States of America. Design and Setting. Ten bibliographic databases, five research repositories, and reference sections of articles were searched to identify published studies. Articles presenting outcomes of interventions conducted between 2014 and 2019 and written in English, were included. Primary Results. Nine studies met inclusion criteria, including qualitative, quantitative randomized controlled trials, quantitative nonrandomized, quantitative descriptive, and mixed-methods studies. The programs studied used film and television (n = 3), mixed-arts (n = 3), theatre (n = 2), and quilting (n = 1). All nine interventions used the arts to elicit emotional involvement, while seven also used the arts to encourage engagement with themes of health. Study outcomes included increased self-efficacy, awareness of mental health issues, and likelihood for taking action to prevent suicide, as well as decreases in suicidal risk and self-harming behaviors. Conclusions. Factors that influence suicide risk and survivorship may be effectively addressed through arts-based interventions. While the current evidence is promising with regard to the potential for arts programs to positively affect suicide prevention and survivorship, this evidence needs to be supplemented to inform recommendations for evidence-based arts interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".