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Record W2938367515 · doi:10.3917/spub.187.0785

Formation pour une intervention de réadaptation par les arts : un transfert de connaissances

2019· article· fr· W2938367515 on OpenAlexaff
Frédérique Beaudoin-Dion, Christian Dagenais, Kim Archambault, Patricia Garel

Bibliographic record

VenueSanté Publique · 2019
Typearticle
Languagefr
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

OBJECTIVES: To evaluate the implementation, processes and perceived efficacy of a pilot project of knowledge transfer in public health, which involves the training/supervision of new practitioners in an art-based rehabilitation program. This innovative evidence-based intervention seeks to promote the well-being of youth with mental disorders through circus and theater workshops. The purpose of this study is to provide a formative evaluation of this pilot project in order to improve the intervention and the knowledge transfer practices in public health. METHODS: This research is based on a participatory and mixed approach, with a ?triangulation-convergence? design, integrating a thematic analysis of qualitative data (semi-structured interviews and Focus Groups), a descriptive analysis of quantitative data (questionnaire of reaction) and a documentary compliance analysis (grid of activity monitoring). RESULTS: The results show that the knowledge transfer strategy has resulted in the training of practitioners who feel ready to take charge of the project, despite implementation gaps. The main barrier was the prolonged and unforeseen absence of project leaders, for reasons out of their control. Nevertheless, the motivation and commitment of the team members acted as a catalyst in this pilot project, which became a setting for discussion and experimentation of the knowledge transfer strategy. CONCLUSION: This study demonstrates the benefits of adopting a participatory approach and mixed method in the evaluation of knowledge transfer in public health, which would better capture the inherent complexity of social interventions.

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.

How this classification was reachedexpand

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.035
GPT teacher head0.295
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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