Adaptation of the Motivational Interviewing Skills Code to Identify Client Language Predicting Reduced Opioid Use Risk and Increased Use of Alternative Pain Care Strategies in Veterans.

Borsari B, Baxley C, Ladd BO, Delacruz J, Jackson KM, Fetterling T, Self KJ, Hassanbeigi Daryani S, Seal KH, Manuel JK. Adaptation of the Motivational Interviewing Skills Code to Identify Client Language Predicting Reduced Opioid Use Risk and Increased Use of Alternative Pain Care Strategies in Veterans. Methods and protocols. 2025 Dec 8; 8(6):DOI: 10.3390/mps8060149.

Related HSR&D Project(s)

• PPO 18-213 – Adaptation of the Motivational Interviewing Skills Code to Identify Clinician and Client Language Predicting Reduced Opioid Use Risk and Increased Use of Alternative Pain Care Strategies in Veterans

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Abstract:

OBJECTIVE: Motivational Interviewing may be an ideal communication style to use in conjunction with Collaborative Care to address opioid risk, as it can facilitate the discussion of alternative pain care strategies (APCSs) that are pharmacological (APCS-P; e.g., the use of non-opioid pain relievers) or non-pharmacological (APCS-NP; e.g., yoga). This study developed and piloted a coding system (MI Skills Code-APCS) for these discussions. METHOD: Sessions ( < i > n < /i > = 119) from a completed randomized controlled trial comparing Collaborative Care Motivational Interviewing (CCMI) or Attention Control Psychoeducation (ACP) delivered by care managers over 12 weeks to veterans with chronic pain and high-risk opioid use enrolled in VA primary care ( < i > N < /i > = 44). RESULTS: Coders were able to reliably code the client utterances related to APCSs in the sessions (ICCs = 0.58-0.81). The APCS-P and APCS-NP codes were positively correlated with each other. There were two significant relationships between the MISC-APCS codes (motivational states) and the pain interference and endorsement of non-pharmacological pain care goals at 20-week follow-up. CONCLUSIONS: The MISC-APCS has promise as a coding system that can reliably record client utterances regarding different types of pain care strategies. These utterances may be associated with post-treatment reports of pain and efforts to reduce opioid risk. The rapid development of artificial intelligence applications to healthcare can utilize this coding system to assist with the assessment and treatment of chronic pain.