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Enregistrement W4311578224 · doi:10.2196/39672

Behavioral Skills Training for Teaching Safety Skills to Mental Health Clinicians: Protocol for a Pragmatic Randomized Control Trial

2022· article· en· W4311578224 sur OpenAlexaffvenueabout
Elizabeth Lin, Mais Malhas, Emmanuel Bratsalis, Kendra Thomson, Rhonda Boateng, Fabienne Hargreaves, Heba Baig, Mary Benisha Benadict, Louis Busch

Notice bibliographique

RevueJMIR Research Protocols · 2022
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueWorkplace Violence and Bullying
Établissements canadiensBrock UniversityCentre for Addiction and Mental Health
Organismes subventionnairesnon disponible
Mots-clésCompetence (human resources)Mental healthPsychological interventionPsychologyMedical educationBest practiceHarmOccupational safety and healthApplied psychologyMedicineNursingPsychiatrySocial psychology

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Workplace violence is an increasingly significant topic, particularly for staff working in mental health settings. The Centre for Addiction and Mental Health (CAMH), Canada's largest mental health hospital, considers workplace safety a high priority and consequently has mandated staff safety training. For clinical staff, key components of this training are self-protection and team-control skills, which are a last resort when an individual is at an imminent risk of harm to self or others and other interventions are ineffective (eg, verbal de-escalation). For the past 20 years, CAMH's training-as-usual (TAU) has been based on a 3D approach (description, demonstration, and doing), but without any competency-based assessment. Recent staff reports indicate that the acquisition and retention of these skills may be problematic and that staff are not always confident in their ability to effectively address workplace violence. The current literature lacks studies that evaluate how staff are trained to acquire these physical skills and consequently provides no recommendations or best practice guidelines. To address these gaps described by the staff and in the literature, we have used an evidence-based approach from the field of applied behavior analysis known as behavioral skills training (BST), which requires trainees to actively execute targeted skills through instruction, modeling, practice, and feedback loop. As part of this method, competency checklists of skills are used with direct observation to determine successful mastery. OBJECTIVE: Our objectives are to evaluate the effectiveness of BST versus TAU in terms of staff confidence; their competence in self-protection and team-control physical skills; their level of mastery (predefined as 80% competence) in these skills; and their confidence, competency, and mastery at 1 month posttraining. METHODS: We are using a pragmatic randomized controlled trial design. New staff registering for their mandatory safety training are randomly assigned to sessions which are, in turn, randomly assigned to either the BST or TAU conditions. Attendees are informed and consented into the study at the beginning of training. Differences between those consenting and those not consenting in terms of role and department are tracked to flag potential biases. RESULTS: This study was internally funded and commenced in January 2021 after receiving ethics approval. As of May 2022, data collection is complete; half of the baseline, posttraining, and 1-month videotapes have been rated, and three-fourths of the interrater reliability checks have been completed. The analysis is expected to begin in late summer 2022 with results submitted for publication by fall 2022. CONCLUSIONS: The findings from this study are expected to contribute to both the medical education literature as well as to the field of applied behavioral analysis where randomized controlled trial designs are rare. More practically, the results are also expected to inform the continuing development of our institutional staff safety training program. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/39672.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,063
score de la tête « metaresearch » (Gemma)0,004
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Études des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: aucune
GenreSignal candidat: Protocole · Signal consensuel: Protocole
Score de désaccord entre enseignants0,494
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0630,004
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0080,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,213
Tête enseignante GPT0,616
Écart entre enseignants0,403 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeEssai randomisé
Domainenon disponible
GenreProtocole

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2022
Routes d'admission3
Résumé présentoui

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