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Record W3120772459 · doi:10.29173/bsuj494

Raising the Curtain on Drama Therapy: Healing Benefits for Youth and Older Adults

2020· article· en· W3120772459 on OpenAlexaffvenue
Vanessa Boila, Lanette Klettke, Stephanie Quong, Ciara Gerlitz

Bibliographic record

VenueBehavioural Sciences Undergraduate Journal · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicArt Therapy and Mental Health
Canadian institutionsMount Royal UniversityQueen's UniversityUniversity of Alberta
Fundersnot available
KeywordsDramaDrama therapyNormativeStorytellingPsychologyPsychotherapistIntervention (counseling)MedicineDevelopmental psychologyClinical psychologyPsychiatryArtNarrativeVisual artsLiteraturePolitical science

Abstract

fetched live from OpenAlex

The vast majority of people around the world have been exposed to dramatic arts in some way, shape, or form, but only recently has drama therapy been accepted as a therapeutic treatment for individuals across the lifespan. This paper provides a general introduction to drama therapy and some of the techniques (e.g., role playing and storytelling) employed in its delivery and hands-on practice. In addition, the paper explores how drama therapy has been used to treat young people (approximately 10-17 years old) who have autism and/or social, emotional, and behavioural difficulties, and older adults (approximately 60-90 years old) who are experiencing normative or non-normative aging. The findings presented here suggest drama therapy may be an efficacious, healing treatment for a myriad of age groups. For instance, its positive effects on individuals with dementia have been observed, and an assortment of intra- and inter-personal improvements have been documented in youth. Considering drama therapy is still a growing field, less drama therapy research exists in comparison to its alternative treatments.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.359
Threshold uncertainty score0.998

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 studies0.0030.000
Scholarly communication0.0010.000
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 head0.210
GPT teacher head0.318
Teacher spread0.108 · 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 designQualitative
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
Published2020
Admission routes2
Has abstractyes

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