Implementation of the My Abilities First Tool: A qualitative study on the perceptions of professionals, caregivers, children, and adolescents with disabilities
Bibliographic record
Abstract
OBJECTIVE: To analyze the perceptions of professionals, caregivers, children, and adolescents with disabilities regarding the implementation of the My Abilities First (MAF) tool in Specialized Child Rehabilitation Centers (CERs). METHOD: This is a qualitative research based on Reflexive Thematic Analysis (RTA). The study involved twenty-seven intentionally selected individuals, comprising 12 physiotherapists, 4 occupational therapists, 11 caregivers, 9 children and 2 adolescents. Participants completed sociodemographic and clinical questionnaires and took part in semi-structured online interviews, focusing on two themes: Positive health approaches and the MAF tool. The study was approved by the local ethics committee (opinion 4.779.175). RESULTS: Reflexive Thematic Analysis of the interviews resulted in two themes: (1) Perceptions regarding the MAF tool as an educational and contributory process to enhance the inclusion and participation of children and adolescents with disabilities, and (2) Barriers and facilitators for the implementation process of the MAF tool. The implementation of MAF was identified as a driving factor in promoting equity and increased participation of children and adolescents with disabilities in various settings, including health, education, and leisure. Interviewees highlighted the need to confront attitudinal, communication, and social barriers that may hinder the implementation of the tool. CONCLUSION: The implementation of the MAF tool was perceived as an innovation due to its focus on the abilities of individuals with disabilities. However, there is a need to restructure it to broaden its scope and access to different contexts in order to confront barriers and enhance the inclusion and participation of children and adolescents with disabilities.
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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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".