Clinician motivational interviewing skills in 'simulated' and 'real-life' consultations differ and show predictive...

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.

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.

Veterinary clinicians were less MI consistent in RL consultations, evidenced through significantly lower global MITI Cultivating Change Talk (p < 0.001), Partnership (p < 0.001) and Empathy (p = 0.003) measures. Despite lower objective MI skills groupings in RL consultations, ranking order of veterinary clinicians by MI skills was similar between contexts. The predictive validity of SI and RL MI skills groupings for RL client Change Talk was therefore similar, with significantly more RL client Change Talk associated with veterinarians categorised in the highest grouping ('moderate') in both SI (p = 0.01) and RL (p = 0.02) compared to untrained veterinarians in each respective context.

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.