Publications

BACKGROUND

People in substance use disorder (SUD) treatment have a smoking prevalence that is five times higher than the national average. California funded the Tobacco Free for Recovery Initiative, designed to support programs in implementing tobacco-free grounds and increasing smoking cessation services. In the first cohort of the initiative (2018-2020) client smoking prevalence decreased from 54.2% to 26.6%. The current study examined whether similar findings would be replicated with a later cohort of programs (2020-2022).

METHOD

Cross-sectional survey data were collected from clients in 11 residential SUD treatment programs at baseline (n = 185) and at post intervention (n = 227). Multivariate logistic regression assessed change over time in smoking prevalence, tobacco use behaviors, and receipt of cessation services across the two timepoints.

RESULTS

Client smoking prevalence decreased from 60.3 % to 40.5 % (Adjusted Odds Ratio [AOR] = 0.46, 95 % CI = 0.27, 0.78; p = 0.004). Current smokers and those who quit while in treatment reported an increase in nicotine replacement therapy (NRT)/pharmacotherapy from baseline to post intervention (31.9 % vs 45.6 %; AOR = 2.22, 95 % CI = 1.08, 4.58; p = 0.031).

CONCLUSIONS

Like the first cohort, the Tobacco Free for Recovery initiative was associated with decreased client smoking prevalence and an increase in NRT/pharmacotherapy. These findings strengthen the evidence that similar initiatives may be effective in reducing smoking prevalence among people in SUD treatment.

Coronary artery calcium (CAC) is a powerful tool to refine atherosclerotic cardiovascular disease (ASCVD) risk assessment. Despite its growing interest, contemporary public attitudes around CAC are not well-described in literature and have important implications for shared decision-making around cardiovascular prevention. We used an artificial intelligence (AI) pipeline consisting of a semi-supervised natural language processing model and unsupervised machine learning techniques to analyze 5,606 CAC-related discussions on Reddit. A total of 91 discussion topics were identified and were classified into 14 overarching thematic groups. These included the strong impact of CAC on therapeutic decision-making, ongoing non-evidence-based use of CAC testing, and the patient perceived downsides of CAC testing (e.g., radiation risk). Sentiment analysis also revealed that most discussions had a neutral (49.5%) or negative (48.4%) sentiment. The results of this study demonstrate the potential of an AI-based approach to analyze large, publicly available social media data to generate insights into public perceptions about CAC, which may help guide strategies to improve shared decision-making around ASCVD management and public health interventions.