Understanding the essential components and experiences of youth with autism spectrum disorders in peer mentorship programmes during the transition to adulthood: A qualitative meta‐ethnography
Bibliographic record
Abstract
Youth with an autism spectrum disorder (ASD) often require additional supports during the period of transition to from high school to post-secondary education or career paths. Peer mentorship (PM) programmes create opportunities to support youth with ASD in identifying their personal, academic and career goals after graduating from high school; however, there is limited insight about the components of these programmes that are valued by both participants and peer mentors and that are perceived to contribute to the overall success of a programme in achieving their goals. Our objective was to identify, describe and synthesize the components of PM programmes valued by youth with ASD and their peer mentors, as well as to document their experiences in these transitional support services. A meta-ethnography was conducted to synthesize qualitative and mixed methods studies of PM programmes for youth with ASD. A systematic search of seven databases yielded 142 nonduplicate articles. Data analysis and synthesis involved (1) extraction of raw data; (2) extraction of study authors' interpretations, followed by inductive coding; (3) synthesis of key themes and (4) schematic diagram development to illustrate the relationship of themes. Ten studies of PM programmes from Canada (2), United States (4), Australia (3) and United Kingdom (1) were included. Extracted data reflected experiences of 131 mentees and 82 mentors. The essential programme components identified were (1) mentorship, (2) skill building, (3) peer group and (4) facilitating transition. PM characterized by clear communication and connection between mentors and mentees was valuable to the success of the programme. Peer mentors played an essential role to facilitate the positive experiences that mentees had with programme components, including interactions with peer groups. Successful PM programmes created a safe environment for mentees to practice skills and helped mentees gain confidence to expand their roles to take leadership in their learning.
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 | 0.029 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".