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Record W4285164747 · doi:10.1177/23743735221107241

Group Telehealth Music Therapy With Caregivers: A Qualitative Inquiry

2022· article· en· W4285164747 on OpenAlexaff
Annabelle Brault, Guylaine Vaillancourt

Bibliographic record

VenueJournal of Patient Experience · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsConcordia University
Fundersnot available
KeywordsTelehealthMusic therapyQualitative researchPsychologyMedicinePhysical therapyPsychotherapistTelemedicineSociologyHealth care

Abstract

fetched live from OpenAlex

Informal caregivers of older adults are faced with increased responsibilities as health and social systems fail to respond to the rising demands associated with the aging populations. For many caregivers, the COVID-19 pandemic has severely impacted their access to already sparse supportive resources, highlighting the importance of varying service delivery methods to meet caregivers' needs. This qualitative study explored the experiences of informal caregivers of older adults who took part in group telehealth music therapy. Semi-structured interviews with 5 women caregivers were conducted. Through a thematic analysis process, the following themes were identified: (a) affordances of group telehealth music therapy, (b) challenges of group telehealth music therapy, and (c) music as a health resource. Telehealth considerations, clinical implications, as well as ways to support caregiver agency are discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0080.007
Scholarly communication0.0040.003
Open science0.0020.005
Research integrity0.0020.002
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 head0.086
GPT teacher head0.404
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2022
Admission routes1
Has abstractyes

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