Exploring Caregivers’ Perspectives on Participation in a Therapy-Based Dance Program for Children with Disabilities: A Qualitative Study
Bibliographic record
Abstract
AIM: This study aimed to 1) understand caregiver's perspectives on the facilitators and barriers of participating in a proposed pediatric therapy-based dance program, (2) explore caregivers' perspectives on a therapy-based dance program aimed at achieving individualized occupational therapy and physical therapy goals in a group setting, and (3) understand the impact of the COVID-19 pandemic on prioritization of participation in therapy services. METHODS: Eight caregivers to children with cognitive and/or physical disabilities participated in semi-structured virtual interviews consisting of open-ended questions. Interviews were audio recorded and transcribed verbatim and conventional content analysis was used to analyze the transcripts. RESULTS: Four categories were identified, mapping to the four layers of the Social Ecological Model of Health (Sallis & Fisher, 2008): 1) Child specific factors impact optimal participation in the program, 2) Family-related factors influence the feasibility of the child's participation, 3) Program specific factors should aim to meet each child's individual needs, and 4) Systemic healthcare factors influence the accessibility of services. Key recommendations for the program's re-design were identified from the data: 1) minimize costs and identify funding sources, 2) ensure small provider-to-participant ratios, 3) facilitate effective collaboration between the therapists and caregivers, 4) create a supportive environment of participants' needs. Conclusions: Factors related to the child, family, program and healthcare system offer guidance to the re-design of the proposed therapy-based dance program, and other pediatric therapy programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".