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Record W4397014563 · doi:10.1080/17533015.2024.2355134

Exploring uses of visual arts-based interventions for mental health of marginalized populations: a scoping review

2024· review· en· W4397014563 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueArts & Health · 2024
Typereview
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMcGill University
Fundersnot available
KeywordsPsychological interventionMental healthThe artsPsychologySociologyVisual artsPsychotherapistArtPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The intentions of this scoping review are to determine current uses of visual arts-based interventions for mental health and trauma support of marginalized populations, and to identify current gaps in knowledge in this emergent field. METHOD: Six databases (MEDLINE, Embase, CINAHL, Web of Science, PsycINFO, JSTOR) were searched for relevant studies. Following the PRISMA guidelines, 38 articles met the inclusion criteria. RESULTS: Most interventions focused on improving the mental health of participants, or to provide opportunities for participants to process their experiences of mental health. Participants reported increased well-being, experiences of relaxation and/or distraction, and processing of mental health experiences. They perceived arts-based interventions as helpful and developed mutual social support with other participants. CONCLUSION: Arts-based interventions have the potential to inform the development of culturally safe and relevant mental health care for marginalized populations beyond current mainstream mental health practices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.511
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.753
GPT teacher head0.571
Teacher spread0.182 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it