The Forensic Supplement to the interRAI Mental Health Assessment Instrument: Evaluation and Validation of the Problem Behavior Scale
Notice bibliographique
Résumé
Background: Numerous validation studies support the use of the interRAI Mental Health (MH) assessment system for inpatient mental health assessment, triage, treatment planning, and outcome measurement. However, there have been suggestions that the interRAI MH does not include sufficient content relevant to forensic mental health. We address this potential deficiency through the development of a Forensic Supplement (FS) to the interRAI MH system. Using three forensic risk assessment instruments (PCL-R; HCR-20; VRAG) that had a record of independent cross validation in the forensic literature, we identified forensic content domains that were missing in the interRAI MH. We then independently developed items to provide forensic coverage. The resulting FS is a single-page, 19-item supplementary document that can be scored along with the interRAI MH, adding approximately 10–15 min to administration time. We constructed the Problem Behavior Scale (PBS) using 11 items from the interRAI MH and FS. The Developmental Sample, 168 forensic mental health inpatients from two large mental health specialty hospitals, was assessed with both an earlier version of the interRAI MH and FS. This sample also provided us access to scores on the PCL-R, the HCR-20 and the VRAG. To validate our initial findings, we sought additional samples where scoring of the interRAI MH and the FS had been done. The first, the Forensic Sample (N = 587), consisted of forensic inpatients in other mental health units/hospitals. The second, the Correctional Sample (N = 618) was a random, representative sample of inmates in prisons, and the third, the Youth Sample (N = 90) comprised a group of youth in police custody. Results: The PBS ranged from 0 to 11, was positively skewed with most scores below 3, and had good internal consistency (Cronbach's Alpha = 0.80). In a test of concurrent validity, correlations between PBS scores and forensic risk scores were moderate to high (i.e., r with PCL-R Factor two of 0.317; with HCR-20 Clinical of 0.46; and with HCR-20 Risk of 0.39). In a test of convergent validity, we used Binary Logistic Regression to demonstrate that the PBS was related to three negative patient experiences (recent verbal abuse, use of a seclusion room, and failure to attain an unaccompanied leave). For each of these three samples, we conducted the same convergent validity statistical analyses as we had for the Developmental Sample and the earlier findings were replicated. Finally, we examined the relationship between PBS scores and care planning triggers, part of the interRAI systems Clinical Assessment Protocols (CAPs). In all three validity samples, the PBS was significantly related to the following CAPs being triggered: Harm to Others, Interpersonal Conflict, Traumatic Life Events, and Control Interventions. These additional validations generalize our findings across age groups (adult, youth) and across health care and correctional settings. Conclusions: The FS improves the interRAI MH's ability to identify risk for negative patient experiences and assess clinical needs in hospitalized/incarcerated forensic patients. These results generalize across age groups and across health care and correctional settings.
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 | 0,019 | 0,063 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».