ArticlePeerJ2023
Clinician motivational interviewing skills in 'simulated' and 'real-life' consultations differ and show predictive validity for 'real life' client change talk under differing integrity thresholds.
Article in PeerJ, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Designing and Conducting Motivational Interviewing Research in Veterinary Clinical Settings: A Practical Guide for Researchers.Animals : an open access journal from MDPI · 2026Review
- From Persuasion to Partnership: Evaluating the Practicalities, Ethics, and Evidence for Implementing Motivational Interviewing in Veterinary Practice.Animals : an open access journal from MDPI · 2026Review
- Enhancing Medical Interview Skills Through AI-Simulated Patient Interactions: Nonrandomized Controlled Trial.JMIR medical education · 2024Article
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accurate and reliable assessment of clinician integrity in the delivery of empirically supported treatments is critical to effective research and training interventions. Assessment of clinician integrity can be performed through recording simulated (SI) or real-life (RL) consultations, yet research examining the equivalence of these data is in its infancy. To explore the strength of integrity assessment between SI and RL samples in Motivational Interviewing (MI) consultations, this article examines whether Motivational Interviewing Treatment Integrity (MITI) assessments differ between SI and RL consultations and reviews the predictive validity of SI and RL MI skills categorisations for RL client response language. Methods: This study first compared MITI coding obtained in SI and RL consultations for 36 veterinary clinicians. Multilevel models of 10 MITI behaviour counts and four MITI global scores were run using MLwiN 3.02 to assess if a significant difference existed between SI and RL MITI data, with consultation within clinician within cohort (A and B) as nested random effects. Second, we investigated the effect of SI and RL MI skills groupings on rate of RL client response talk using three multivariable regression models. Two Poisson regression models, with random intercepts for farm and veterinarian and offset for number of minutes of the recordings, were estimated in the statistical software R using the package glmmTMB for the two response variables Change Talk and Sustain Talk. A logistic regression model, with the same random intercepts, with the response variable Proportion Change Talk was also estimated using the same package. Results: Veterinary clinicians were less MI consistent in RL consultations, evidenced through significantly lower global MITI Cultivating Change Talk ( Conclusions: Findings suggest SI and RL data may not be interchangeable. Whilst both data offer useful insights for specific research and training purposes, differing contextual MI skills thresholds may offer a more equitable assessment of clinician RL client-facing MI integrity. Further research is needed to explore the applicability of these findings across health contexts.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.