Complexities during transitions to adulthood for youth with disabilities: person–environment interactions
Bibliographic record
Abstract
PURPOSE: The purpose of this qualitative study was to explore the experiences of youth with different disabilities from across Canada during their transitions from adolescence to adulthood. METHODS: Qualitative methods, using a phenomenological tradition, explored the meaning of the lived experiences of youth with disabilities in transition to adulthood. Purposeful sampling was used to select people with a range of experiences, background, location and demographic characteristics. Individual interviews with key informants and a focus group with an "expert panel" of participants were the methods of data collection. Data analysis was iterative and followed established practices of phenomenology. RESULTS: Over 50 people, including youth with different disabilities, parents/caregivers and service providers from different organizations and systems across Canada participated in individual and/or focus group interviews. An overarching theme of "complexities" emerged from the data analysis. Complexities were related to the interactions between person and environment during transition experiences. Six subthemes about complexities were explored in depth to describe the primary person-environment interactions that were identified by study participants. CONCLUSIONS: The complexities involved in the interactions between person and environment during transitions to adulthood appear to be similar for youth with different types of disabilities. Recommendations are provided to address these complexities using holistic and collaborative approaches in service delivery and future research. Implications for Rehabilitation The complexities involved in transitions to adulthood appear to be similar for youth with different types of disabilities. Rehabilitation service providers can address these complexities using holistic, strengths-based and collaborative approaches. Service providers and researchers in rehabilitation need to acknowledge the interactions between person and environment rather than addressing each component separately. Future research should include youth, families and community members on research teams to ensure that complexities are adequately addressed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.008 |
| 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".