Programs Promoting Virtual Social Connections and Friendships for Youth with Disabilities: A Scoping Review
Bibliographic record
Abstract
AIMS: This scoping review explores what is known about programs that support youth with physical and developmental disabilities to create virtual social connections as a means toward friendships. METHODS: Peer-reviewed studies were searched in six electronic databases: CINAHL, EMBASE, ERIC, MEDLINE, PsycINFO, and Scopus. Two reviewers screened articles that described programs in which participants, ages 8-20, interacted with others online, and reported outcomes related to virtual social connections and friendships in their personal social networks. Data extraction involved program characteristics (e.g., duration, group members, online platform) plus qualitative description outlining access and participation experiences. RESULTS: After screening 12,605 articles, 9 were determined eligible. Programs followed two approaches: (1) training youth to use the internet and technology to access virtual spaces independently; and (2) designing virtual opportunities and activities that encourage youth interaction and collaboration. Each approach was grounded in the principles of fostering privacy and independence (i.e., socializing with peers without relying on caregivers), safety and self-expression (i.e., communicating authentically), plus confidence and capability (i.e., trying new skills). CONCLUSIONS: This scoping review provides guidance on enhancing access and participation of youth with disabilities in virtual spaces where they can develop social connections that increase chances for friendships.
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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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".