MétaCan
Menu
Back to cohort
Record W2943515047 · doi:10.1093/jmt/thz006

A Sequential Mixed-Methods Study of Pre-Professionals’ Understanding of the Undergraduate Music Therapy Internship

2019· article· en· W2943515047 on OpenAlexaff
Amy Clements-Cortés

Bibliographic record

VenueJournal of Music Therapy · 2019
Typearticle
Languageen
FieldPsychology
TopicMusic Therapy and Health
Canadian institutionsWilfrid Laurier UniversityUniversity of Toronto
Fundersnot available
KeywordsInternshipCLARITYPsychologyMusic therapyMedical educationAnxietyMusicalPedagogyMedicinePsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Despite the importance of the clinical music therapy internship, little research has been conducted to understand the perspectives, perceived musical, clinical, and personal skills, concerns, challenges, and anxieties of pre-professionals prior to and upon completion of the internship. This sequential mixed-methods study aimed to assess the perspectives and experiences of undergraduate students in the United States at two stages in the internship in music therapy practice. In total, 177 pre-professionals from the United States participated in this two-part study: (1) an online survey and (2) individual interviews with 25% (n = 44) of the participants. Survey results indicate statistically significant increases in clinical, musical, and personal skill development from pre- to post-internship. Six broad categories emerged from the interviews: confidence, anxiety, role clarity, professional suitability, loneliness, and boundaries/ethics. The results are encouraging, showing that the internship is a valued clinical experience that fosters improvement in the clinical, musical, and personal skills needed to work as a music therapist. This paper concludes with recommendations and suggestions for educators and supervisors on preparing and supporting pre-professionals in their skill development prior to and during internship.

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)0.004
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.497
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.170
GPT teacher head0.443
Teacher spread0.274 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Music TherapySame topicMusic Therapy and HealthFrench-language works237,207