A systematic review of post-secondary transition interventions for youth with disabilities
Bibliographic record
Abstract
Purpose: Youth with disabilities have lower rates of enrollment and completion of post-secondary education compared with youth without disabilities. The objective of this systematic review is to understand the best practices and components of post-secondary transition programs for youth with disabilities. Method: Systematic searches of six international databases identified 18 studies meeting our inclusion criteria (youth with a disability, aged 15–30; focusing on post-secondary education program or intervention, published from 1997 to 2017). These studies were analyzed with respect to the characteristics of the participants, methodology, results, and quality of the evidence. Results: Among the 18 studies, 2385 participants (aged 13–28, mean 17.7 years) were represented across three countries (US, Canada, and Australia). Although the outcomes of the post-secondary transition programs varied across the studies, all of them reported an improvement in at least one of the following: college enrollment, self-determination, self-confidence, social and vocational self-efficacy, autonomy, social support, career exploration, and transition skills. The post-secondary transition programs varied in duration, length, number of sessions, and delivery format which included curriculum-based, online, immersive residential experience, mentoring, simulation, self-directed, technology-based, and multi-component. Conclusions: Our findings highlight that post-secondary transition programs have the potential to improve self-determination, transition skills, and post-secondary outcomes among youth with disabilities.Implications for rehabilitationPost-secondary education interventions have a beneficial influence on post-secondary and related transition outcomes in youth with disabilities.Clinicians and educators should consider having multiple components, involving several sessions that include a curriculum, immersive college residential experience, mentoring, and/or simulations in their interventions for optimum program outcomes.More research is needed to explore the types of interventions that work best for whom and the optimal age (including exploring the socio-demographic characteristics), setting, and delivery format. Post-secondary education interventions have a beneficial influence on post-secondary and related transition outcomes in youth with disabilities. Clinicians and educators should consider having multiple components, involving several sessions that include a curriculum, immersive college residential experience, mentoring, and/or simulations in their interventions for optimum program outcomes. More research is needed to explore the types of interventions that work best for whom and the optimal age (including exploring the socio-demographic characteristics), setting, and delivery format.
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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 | 0.011 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".