A scoping review of mental health literacy in performing and creative artists: identifying current gaps and future directions
Bibliographic record
Abstract
Introduction: Mental health literacy is a multifaceted construct that consists of helping individuals recognize the early warning signs of mental health conditions, understanding the concept of stigma and misconceptions associated with mental illness, encouraging appropriate help-seeking behaviors, and facilitating access to mental health services. However, mental health literacy remains a largely unexplored topic in artists' health literature. This scoping review examines the conceptualization, operationalization, and measurement of mental health literacy in performing and creative artists. Methods: We conducted a comprehensive search across multiple databases, including MEDLINE, CINAHL, PubMed, EMBASE, PsycINFO, Web of Science, and Cochrane. Our search was designed to identify articles relevant to mental health literacy among artists, encompassing aspects related to the understanding, identification, and education of mental health conditions. Two independent reviewers conducted both abstract and full-text screenings. Our findings are synthesized using the four components of mental health literacy as a framework for organization. Results: Of the 669 unique citations, 26 articles met the inclusion criteria; of these, 23 focused on performing artists. The articles were published between 1997 and 2024, with at least 4,710 participants from nine countries. Only one study included a definition of mental health literacy. Sixteen articles included one of the four components of mental health literacy, nine included two, four included three, and one had all four components. Discussion: Despite the high prevalence of mental health challenges among performing and creative artists, there is a disproportionately low number of interventions aimed at increasing mental health literacy compared to other fields, such as sports medicine and education. This highlights the need for more comprehensive efforts to increase awareness and understanding of mental health issues among artists. Furthermore, the lack of consensus on the conceptualization, operationalization, and measurement of mental health literacy in this field prompts further research. A standardized definition and validated instrument could facilitate more robust research on mental health literacy in the artists' health literature and help identify effective interventions. Future research can build on this review to develop and evaluate interventions aiming to improve mental health literacy in artists.
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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 | 0.023 | 0.101 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.031 | 0.027 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".