Supporting the Transition to Postsecondary Institutions for Students with Mental Health Conditions: A Scoping Review.
Bibliographic record
Abstract
Objective: To conduct a scoping review to identify programs and interventions to support youth with mental health conditions (MHCs) with their transition to postsecondary institution (PSI). Method: A database search of MEDLINE, PsycINFO, Embase, SocINDEX, ERIC, CINHAL, and Education Research Complete was undertaken. In this review, MHC was defined as a mental, behavioural, or emotional condition, or problematic substance use, and excluded neurodevelopmental or physical disorders. Two reviewers independently screened studies and extracted the data. Included studies are described and a risk-of-bias assessment was conducted on included studies. Results: Nine studies were included in this review, describing eight unique interventions. Sixty-two percent of interventions were nonspecific in the MHCs that they were addressing in postsecondary students. These interventions were designed to support students upon arrival to their PSIs. Peer mentorship, student engagement, goal setting, and interagency collaboration were some of the strategies employed. However, the overall quality and level of evidence in these studies was low and the effectiveness of these programs was not established. Conclusion: The volume of research identified was limited, no reliable nor policy informing conclusions can yet be made about the impact of these interventions as the evaluation methods, quality of the research methodologies, and the levels of evidence available were of low-quality. Future randomized control trials are required that are designed to target and improve transitions from secondary education to PSIs for those with MHCs.
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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 | 0.025 | 0.084 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| 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".