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Enregistrement W7024959478

Therapist Emotional Reactivity and Performance Following a Motivational Interviewing Workshop With and Without Deliberate Practice

2023· other· en· W7024959478 sur OpenAlexaff

Notice bibliographique

RevueYork University Digital Library (York University) · 2023
Typeother
Langueen
DomaineEarth and Planetary Sciences
ThématiqueTree-ring climate responses
Établissements canadiensYork University
Organismes subventionnairesnon disponible
Mots-clésMotivational interviewingContext (archaeology)AmbivalenceTherapeutic relationshipInterpersonal communicationResistance (ecology)Interview
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Some individuals are more reactive to emotional stimuli than others, and this is particularly relevant to psychotherapists due to their frequent interaction with emotionally evocative material. Therapist reactivity can be particularly triggered during challenging clinical moments such as resistance, leading to negative therapy process which can be detrimental to client outcome. Motivational Interviewing (MI) is a therapeutic approach that specifically focuses on exploring ambivalence about change and minimizing resistance in psychotherapy, and therefore is a beneficial strategy to address many challenging interpersonal moments in psychotherapy. Therapists would benefit from training in MI to specifically address these challenging clinical moments, and this may be especially important for therapists who are highly emotionally reactive. Deliberate Practice (DP) has shown promise as a training approach that may result in greater maintenance of skill, and therefore may be explored as a more impactful and long-lasting way to train therapists in MI. The present study involved both traditional and DP training in the context of a continuing education workshop. The impact of training type on therapist reactivity to challenging clinical moments was examined immediately following training, and four months later. The relationship between therapist reactivity, performance, and type of training was also investigated. Eighty-eight community therapists participated in training to use MI principles to effectively manage client ambivalence and resistance. Therapists were randomly assigned to receive a 2-day training workshop based on DP principles, or to receive a 2-day traditional didactic workshop. Self-reported arousal to video vignettes of difficult scenarios was collected prior to the workshop, immediately following the workshop, and 4 months later, and therapists participated in 20-minute interviews with ambivalent volunteers at both post-workshop and follow-up. Therapist dynamic Respiratory Sinus Arrhythmia (dynamic RSA) was measured during these interviews as a psychophysiological measure of emotional reactivity, and interviews were coded for resistance to measure therapist performance. Results demonstrated a decrease in self-reported arousal only for those who engaged in DP training, though this was not maintained at follow-up. There was a difference in dynamic RSA between groups at post-treatment, where the DP group uniquely demonstrated quadratic change, indicating the training had a differing effect. Despite this differing trajectory, RSA showed an overall increase at both post-workshop and follow-up in both groups. This suggests that regardless of training type, therapists were regulating their emotions and possibly having a compassionate response, rather than a stress response, to these interviews. Dynamic RSA between workshop groups was unable to be assessed at follow-up due to a smaller sample size for psychophysiological assessment. In the investigation of the impact of training on performance, greater self-reported arousal was found to predict less resistance in interviews, but there was no relationship observed between psychophysiological arousal and resistance. This study supports the efficacy of DP training in reducing therapist arousal to difficult clinical scenarios, and the importance of continued DP in order to maintain one’s skills. Clinical and training implications are discussed.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,003
Score d'incertitude au seuil0,017

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,017
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,018
Tête enseignante GPT0,186
Écart entre enseignants0,168 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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