Electronic Mentoring Programs and Interventions for Children and Youth With Disabilities: Systematic Review
Bibliographic record
Abstract
BACKGROUND: Children and youth with disabilities experience many challenges in their development, including higher risk of poor self-esteem, fewer friendships, and social isolation. Electronic mentoring is a potentially viable approach for youth with disabilities to access social and peer support within a format that reduces physical barriers to accessing mentors. OBJECTIVE: Our objective was to synthesize and review the literature on the impact of electronic mentoring for children and youth with disabilities. METHODS: We conducted a systematic review, completing comprehensive searches of 7 databases from 1993 to May 2018. We selected articles for inclusion that were peer-reviewed publications, had a sample of children or youth with disabilities (≤25 years of age), and had empirical findings with at least one outcome focusing on the impact of electronic mentoring. Two reviewers independently applied the inclusion criteria, extracted the data, and rated the study quality before discussing the findings. RESULTS: In the 25 studies meeting our inclusion criteria, 897 participants (aged 12-26, mean 17.4 years) were represented across 6 countries. Although the outcomes varied across the studies, of 11 studies testing significance, 9 (81%) reported a significant improvement in at least one of the following: career decision making, self-determination, self-advocacy, self-confidence, self-management, social skills, attitude toward disability, and coping with daily life. The electronic mentoring interventions varied in their delivery format and involved 1 or more of the following: interactive websites, virtual environment, email, mobile apps, Skype video calls, and phone calls. A total of 13 studies involved one-to-one mentoring, 6 had group-based mentoring, and 6 had a combination of both. CONCLUSIONS: The evidence in this review suggests it is possible that electronic mentoring is effective for children and youth with disabilities. More rigorously designed studies are needed to understand the impact and effective components of electronic mentoring 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 | 0.009 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".