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Motivational Interviewing

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Motivational interviewing and culture for urban Native American youth (MICUNAY): A randomized controlled trial.

Journal of substance abuse treatment
To date, few programs that integrate traditional practices with evidence-based practices have been developed, implemented, and evaluated with urban American Indians/Alaska Natives (AI/ANs) using a strong research design. The current study recruited u...

A Comparison of Natural Language Processing Methods for Automated Coding of Motivational Interviewing.

Journal of substance abuse treatment
Motivational interviewing (MI) is an efficacious treatment for substance use disorders and other problem behaviors. Studies on MI fidelity and mechanisms of change typically use human raters to code therapy sessions, which requires considerable time,...

"It sounds like...": A natural language processing approach to detecting counselor reflections in motivational interviewing.

Journal of counseling psychology
The dissemination and evaluation of evidence-based behavioral treatments for substance abuse problems rely on the evaluation of counselor interventions. In Motivational Interviewing (MI), a treatment that directs the therapist to utilize a particular...

Experiences of a Motivational Interview Delivered by a Robot: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Motivational interviewing is an effective intervention for supporting behavior change but traditionally depends on face-to-face dialogue with a human counselor. This study addressed a key challenge for the goal of developing social roboti...

Design feasibility of an automated, machine-learning based feedback system for motivational interviewing.

Psychotherapy (Chicago, Ill.)
Direct observation of psychotherapy and providing performance-based feedback is the gold-standard approach for training psychotherapists. At present, this requires experts and training human coding teams, which is slow, expensive, and labor intensive...

Developing Machine Learning Models for Behavioral Coding.

Journal of pediatric psychology
OBJECTIVE: The goal of this research is to develop a machine learning supervised classification model to automatically code clinical encounter transcripts using a behavioral code scheme.

Breaking Barriers in Behavioral Change: The Potential of Artificial Intelligence-Driven Motivational Interviewing.

Journal of glaucoma
Patient outcomes in ophthalmology are greatly influenced by adherence and patient participation, which can be particularly challenging in diseases like glaucoma, where medication regimens can be complex. A well-studied and evidence-based intervention...