In What Contexts, How, and Why Do Transition to Adulthood Interventions Work for Adolescents Living with Disabilities: A Realist Review
Bibliographic record
Abstract
Background Transitioning to adulthood is a demanding phase for youth and more challenging for youth with disabilities. Many transition interventions have been implemented to support transition preparedness for youth with disabilities. However, it is still unclear how these interventions work under different contexts. Objective The aim of this realist review is to review the literature on different interventions aimed to support adolescents transitioning to adulthood. The research question was: How (Mechanism) and in what circumstances (Context) transition to adulthood interventions work to improve education, employment, and community integration skills outcomes for youth with disabilities (Outcome)? Methods This review adhered to the essential steps for realist reviews, employing Context-Mechanism-Outcome Configurations (CMOCs) heuristic tools to formulate realist causal explanations. Results Of the 32 documents that met the inclusion criteria, vocational and educational skills were the most frequently reported outcomes. The review found that transition interventions with inclusive real-life environments that cater specifically to the needs of youth without stigmatization are instrumental in empowering youth's self-advocacy, confidence, and self-determination and enabling active participation and engagement. Conclusions While this review provides actionable insights, future research should explore the long-term sustainability and scalability of transition interventions.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".