Personalized audio montage: Impact of a receptive music therapy method-variation on youth experiencing homelessness
Bibliographic record
Abstract
Introduction This quantitative research investigates the impact of a receptive music therapy method-variation, Personalized Audio Montage (called Montage Audio Personnalisé [MAP] in French), on self-reported levels of stress, anxiety, physical tension, fatigue, and mood of youth experiencing homelessness.Method A single-group pretest-posttest design was used to determine the impact of MAP. Participants completed the co-researcher music therapist-developed Visual Analogue Scales (VAS) for five independent variables (i.e. self-reported levels of stress, anxiety, fatigue, physical tension, and mood), before and after participating in individual MAP sessions. Multivariate ANOVAs for repeated measures were used considering time (pretest-posttest), and MAP sessions as within-subjects factors.Results Nine youth (n = 9) participated in one to three MAP sessions. There were 20 pre-tests and post-tests for each independent variable except for anxiety, for which 19 pre-tests and post-tests were completed. Results of quantitative data analysis show a statistically significant decrease in scores for self-reported levels of stress, anxiety and physical tension at post-session as compared to pre-session. No significant effect was observed for fatigue. Finally, mood scores significantly improved from prettest to posttest.Discussion Findings suggest that MAP holds potential to be a valuable part of music therapists’ intervention strategies to support the emotional and physical well-being of youth experiencing homelessness. Limitations and future research recommendations are presented with regard to the small sample size and complexity of conducting research with youth experiencing homelessness.
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 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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".