# Client Language Analysis in Veterans and Non-Veterans with Low Motivation to Quit Smoking: Identifying Mechanisms of Change > **NIH VA I21** · VETERANS AFFAIRS MED CTR SAN FRANCISCO · 2024 · — ## Abstract Background: Veterans disproportionately suffer cigarette-related disease and death relative to the general population, but Veterans often endorse low motivation to quit. Analysis of client language with unmotivated smokers may provide new insights into how motivation shifts in response to different therapies. Therapies for unmotivated smokers include motivational interviewing (MI), which aims to enhance intrinsic motivation by resolving ambivalence; and health education (HE), which delivers scripted health advice. MI research suggests that increased in-session client “change talk” (CT), or language reflecting commitment to change the target behavior, relative to “sustain talk” (ST), or language reflecting plans to continue the target behavior, is associated with improved treatment outcomes. HE may contain client statements reflecting learning, or “learning talk” (LT), in response to health information, which may lead to improved outcomes through a different therapeutic mechanism. We propose to analyze client language from two randomized controlled trials (RCTs) comparing MI to HE with unmotivated smokers conducted by our Co-Investigators, including 1) a community RCT with 255 unmotivated smokers; and 2) a Veterans Health Administration (VHA) pilot study with 85 Veteran smokers with mental illness, of which a subset reported low motivation to quit. Analysis of client language in MI and HE sessions from these studies with unmotivated smokers will provide insight into the mechanisms underlying MI and HE. Significance/Impact: Given the high prevalence of smoking in Veterans, identifying therapeutic techniques associated with positive outcomes in unmotivated smokers has great potential to improve Veteran health. This project addresses HSR&D priorities of mental health, primary care practice, and quality/safety. Innovation: This mixed methods project is the first of its kind to examine aspects of in-session client language as predictors of treatment outcomes in unmotivated smokers, a population representative of most Veteran smokers in VHA care. Specific Aims: Aim 1 is to code client language in audio recorded MI and HE sessions from two RCTs with unmotivated smokers, including a community sample and a Veteran sample. We hypothesize that in both datasets, proportion of CT will be higher in MI than HE and that LT will be higher in HE than in MI. Aim 2 is to examine the relationship between proportion of CT to ST and proportion of LT to RT and 3- and 6- month treatment outcomes in the community sample. We hypothesize that that a higher proportion of CT relative to ST will be positively associated with treatment outcomes, both in MI and HE; that a higher proportion of LT relative to RT will be positively associated with outcomes, both in MI and HE; and that both high CT and high LT in the same session will be associated with improved outcomes relative to either high CT alone or ST alone irrespective of treatment group. We also hypothesize that proportion ... ## Key facts - **NIH application ID:** 11076619 - **Project number:** 5I21HX003410-03 - **Recipient organization:** VETERANS AFFAIRS MED CTR SAN FRANCISCO - **Principal Investigator:** Ellen Herbst - **Activity code:** I21 (R01, R21, SBIR, etc.) - **Funding institute:** VA - **Fiscal year:** 2024 - **Award amount:** — - **Award type:** 5 - **Project period:** 2021-10-01 → 2023-09-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/11076619 ## Citation > US National Institutes of Health, RePORTER application 11076619, Client Language Analysis in Veterans and Non-Veterans with Low Motivation to Quit Smoking: Identifying Mechanisms of Change (5I21HX003410-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/11076619. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*