Non-suicidal self-injury and suicidal behaviour in children and adolescents accessing residential or intensive home-based mental health services.
Notice bibliographique
Résumé
OBJECTIVE: There is a dearth of Canadian research with clinical samples of youth who self-harm, and no studies could be located on self-harm in children and youth accessing residential or intensive home-based treatment. The purposes of this report were to explore the proportion and characteristics of children and youth identified as self-harming at admission by clinicians compared to youth not identified as self-harming, compare self-harming children to adolescents, and to compare caregiver ratings of self-harm at intake to clinician ratings at admission. METHOD: This report was developed from a larger longitudinal, observational study involving 210 children and youth accessing residential and home-based treatment and their caregivers in partnership with five mental health treatment centres in southwestern Ontario. Agency data were gleaned from files, and caregivers reported on symptom severity at 12 to 18 months and 36 to 40 months post-discharge. RESULTS: Fifty-seven (34%) children and youth were identified as self-harming at admission. The mean age was 11.57 (SD 2.75). There were statistically significant differences on symptom severity at intake between those identified as self-harming and those not so identified; most of these differences were no longer present at follow up. Children were reported to have higher severity of conduct disorder symptoms than adolescents at intake, and there was some consistency between caregiver-rated and clinician-rated self-harm. Children were reported to engage in a wide range of self-harming behaviours. CONCLUSION: These findings suggest that youth who were identified as self-harming at admission have elevated scores of symptom severity, self-harm can occur in young children and while many improve, there remains a concern for several children and youth who did not improve by the end of service. Children engage in some of the same types of self-harm behaviours as adolescents, and they also engage in behaviours unique to children.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».