Residential immersive life skills programs for youth with disabilities: service providers' perceptions of change processes
Bibliographic record
Abstract
BACKGROUND: Residential immersive life skills (RILS) programs are designed to equip youth with physical disabilities with the foundational life skills required to assume adult roles. The objective was to determine RILS service providers' perceptions of the active ingredients of the intervention change process. METHODS: Thirty-seven service providers from various disciplines completed measures to assess expertise status and participated in qualitative interviews. Qualitative themes were derived, and similarities and differences in themes were identified for blinded groups of novices, intermediates, and experts. RESULTS: The three main themes, reflecting change processes, were: (a) creating a supportive program atmosphere with multiple opportunities for learning, (b) using strategies to support, encourage, and engage youth, and (c) intentionally fostering youth experiences of skill development, social interaction, and pride in accomplishment. In contrast to the novices, experts displayed a more holistic perspective and paid attention to higher-order issues such as providing opportunities and enabling youth. CONCLUSION: The findings indicate how RILS service providers work to create a program atmosphere and employ strategies to intentionally foster particular youth experiences. The findings explicate service providers' theories of practice, the intentional design of RILS program environments to bring about client change, and the value of service provider expertise. Implications for Rehabilitation Service providers of youth independence-oriented life skills programs can intentionally create a learning-oriented and supportive program atmosphere by using non-directive, coaching/guiding, and engagement strategies Youth experiences of skill development, shared experience with others, and pride in accomplishment can be cultivated by providing a range of learning opportunities, including choice making, problem-solving, and skill mastery Compared to more novice service providers, experts discussed managing the program conditions and context, creating opportunities for choice and new experiences, and adopting a facilitating and enabling role (coaching and capitalizing on teachable moments).
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".