26 Supporting the Transition to Postsecondary for Students with Mental Health Conditions: A Scoping Review
Notice bibliographique
Résumé
Abstract Primary Subject area Mental Health Background The transition from high school to postsecondary is a critical milestone for independence and empowerment. This life stage frequently coincides with the emergence of most mental health conditions (MHCs). Without adequate support to assist with the transition to postsecondary education, the mental health of arriving students with existing MHCs is likely to decline or remain unmet. Declining mental health is strongly associated with students withdrawing from both secondary and postsecondary education. However, a scoping review of interventions aiming to support youth with MHCs transition to postsecondary has not been conducted. Objectives The objectives of this scoping review were to identify: (1) researched interventions that support youth with MHCs during the transition to postsecondary; (2) best practices used to support this transition; (3) methods of evaluating these interventions and any limitations; and (4) gaps where future research is warranted. Design/Methods A database search of MEDLINE, PsycINFO, Embase, SocINDEX, ERIC, CINHAL, and Education Research Complete was undertaken. Two reviewers independently screened studies and extracted the data. Thematic analysis and risk-of-bias assessment were conducted on included studies. Results Nine studies were included in this review, describing eight unique interventions (Figure 1). Sixty-two percent of interventions were nonspecific in the MHCs that they were targeting in postsecondary students. These interventions were designed to support students upon arrival to postsecondary. Peer mentorship, student engagement, and interagency collaboration were found to be beneficial approaches to supporting youth transitioning into postsecondary (Table 1). The overall quality and level of evidence in these studies was low. Three knowledge gaps were found: evidence was not generalizable to the diversity of MHCs, intervention studies were mostly cross-sectional in nature and lacked follow-up data, and sustaining intervention funding remained a challenge for postsecondary institutions. Conclusion The volume of research identified was limited but indicated overall that offering support during the transition to postsecondary was beneficial for students with MHCs. Further evidence is needed that is generalizable across the mental health spectrum, and that assesses intervention outcomes in relation to intervention costs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,071 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,006 | 0,007 |
| Bibliométrie | 0,023 | 0,017 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».