Effective ingredients of verbal de‐escalation: validating an English modified version of the ‘De‐Escalating Aggressive Behaviour Scale’
Notice bibliographique
Résumé
WHAT IS KNOWN ON THE SUBJECT?: Verbal de-escalation is an intervention aimed at calmly managing an agitated client to prevent violence. Effective de-escalation can help reduce the use of seclusion and restraint in psychiatric settings. Despite its importance in practice, there is little agreement on the necessary techniques of de-escalation and most of the research on the topic is based on expert opinion. To our knowledge, only one attempt at quantifying de-escalation skill has been pursued through the German-language De-Escalating Aggressive Behaviour Scale (DABS). While the DABS identified seven qualities necessary for de-escalation, it has not been validated in English and may lack important descriptors. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: The present study enhanced the original DABS with best, acceptable and least desirable staff de-escalation practice descriptions for each of the seven items. This enhancement of the DABS lead to the creation of the English modified DABS (EMDABS). The EMDABS was psychometrically validated for use in research and practice: raters could use the EMDABS with a high level of agreement and consistency. Also, the scale appeared to measure a single cohesive construct - de-escalation. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: With further validation, the EMDABS has potential to be the first English quantitative measure of de-escalation. The EMDABS offers seven items, with associated best practice descriptions, that may be used to inform de-escalation practice. The EMDABS can be used to evaluate training and education programmes and inform how these programmes and independent de-escalation practice may be improved. ABSTRACT: Introduction Verbal de-escalation is crucial to a non-coercive psychiatric environment. Despite its importance, the literature on de-escalation is sparse and mostly qualitative. To address this, Nau et al. (2009) quantified de-escalation by creating the German-language De-Escalating Aggressive Behaviour Scale (DABS). The DABS provides seven skills necessary for de-escalation, however it has not been validated in English and lacks the necessary anchor descriptions to make it useful. Aim To modify the DABS to include descriptions of best, acceptable and least desirable staff practice and to validate the English modified DABS (EMDABS). Method To develop item descriptions for the EMDABS, 50 conflictual staff-patient interactions were reviewed, summarized and cross-referenced with the literature (n = 19). Three raters then used the EMDABS to evaluate 272 simulations depicting these interactions. Results The EMDABS demonstrated very good inter-rater reliability [ICC (3, 1) = 0.752] and strong internal consistency (α = 0.901). A factor analysis revealed that the seven items were best represented by a single factor. Discussion The EMDABS was validated for future use in research and practice. Additional validation and future research directions are discussed. Implications for practice The EMDABS holds promise as a quantitative measure of de-escalation. Its seven items and best practice guidelines have clinical implications for improving practice and training.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».