International Music Therapists’ Perceptions and Experiences in Telehealth Music Therapy Provision
Bibliographic record
Abstract
The use of telehealth within music therapy practice has increased through necessity in recent years. To contribute to the evolving evidence base, this current study on Telehealth Music Therapy (TMT) was undertaken to investigate the telehealth provision experiences of music therapists internationally. Participants completed an anonymous online cross-sectional survey covering demographics, clinical practice, telehealth provision, and telehealth perceptions. Descriptive and inferential statistics, in combination with thematic analysis, were used to analyze the data. A total of 572 music therapists from 29 countries experienced in providing TMT took part in this study. The results showed that the overall number of clinical hours (TMT and in-person hours combined) declined due to the pandemic. Participants also reported reduced perceived success rates in utilizing both live and pre-recorded music in TMT sessions when compared to in-person sessions. Although many music therapists rose to the challenges posed by the pandemic by incorporating TMT delivery modes, there was no clear agreement on whether TMT has more benefits than drawbacks; however, reported benefits included increased client access and caregiver involvement. Furthermore, a correlation analysis revealed moderate-to-strong positive associations between respondents who perceived TMT to have more benefits than drawbacks, proficiency at administering assessments over telehealth, and perceived likelihood of using telehealth in the future. Regarding the influence of primary theoretical orientation and work setting, respondents who selected music psychotherapy as a primary theoretical orientation had more experience providing TMT prior to the pandemic while those primarily working in private practice were most inclined to continue TMT services post-pandemic. Benefits and drawbacks are discussed and future recommendations for TMT are provided.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".