Absconsion from forensic psychiatric institutions
Notice bibliographique
Résumé
Background: Absconding from mental health units is referred to as a patient leaving without permission and can have significant consequences for the patient, family, community, and institution. The varying definitions of absconsion involve breaching security of an inpatient unit, accessing grounds or community without permission, gaining liberty during escorted leave or being absent for longer than permitted from authorized or trial leave. While considerable literature exists on absconsion from acute psychiatric units, there is a paucity of literature specific to forensic absconsions, despite inherent differences between patients and systems. Forensic patients are offenders who are found unfit to stand trial, or not criminally responsible on account of mental disorder. The literature indicates the absconding rate within the forensic population is expected to be low, based on the fact that the level of security in forensic units is higher than general psychiatric units. Despite the rates being considered low, the outcomes of absconding in this population can potentially be serious, thus the exploration of factors surrounding these incidents is essential. Purpose: To review the literature regarding absconsion from forensic psychiatric institutions. This review will identify potential risk factors and motivations of forensic patients that have absconded. Methods: Electronic database and hand searches were conducted to locate articles pertaining to absconding specific to forensic psychiatric institutions published from 1969-present. Search terms included “abscond”, “escape”, “AWOL”, “runaway”, “psychiatric inpatient”, “forensic institution”, & variants. All full-text articles meeting inclusion & exclusion criteria were appraised for qualitative themes, limitations, and assessed for risk of bias using appropriate CASP Checklists. The review is structured following the PRISMA checklist and framework. Results: A total of 19 articles meeting literature review criteria were identified. The majority of the articles were of retrospective case-control design (n=12). Three systematic reviews were found on absconsion that included analyses from both forensic and general psychiatric populations. Definitions for absconding were omitted or varied making comparisons between studies difficult. Much research compared demographic, static and dynamic factors. History of previous absconsion, scores on validated risk-of-violence assessment tools, substance-use disorder, acute mental state, and socio-environmental factors were consistently noted as risk-factors. Four distinct motivations for absconding emerged: goal-directed, frustration/boredom, symptomatic, and accidental. Overall, the literature suggested forensic absconsion was a rare event of short duration with low risk to the public and few re-offending incidents. Conclusions: There is a paucity of literature on forensic absconsions. A consistent definition of absconsion and use of standardized reporting protocols across forensic programs would be beneficial in order to be able to compare data on absconding events. Also, prospective studies should be undertaken to better understand the motivations and dynamic risk factors of forensic patients who have absconded and would help inform a forensic absconsion risk assessment protocol.
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 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,011 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
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 ».