Episodic Future Thinking in a Fully Remote, Multi-Component Behavioral Intervention for Type 2 Diabetes: A Pilot/Feasibility Trial in Rural and Non-Rural Adults [Preprint]

PsyArXiv (OSF Preprints) · 2026-03-07

Delay discounting (DD), or preference for immediate gratification, is a promising therapeutic target in type 2 diabetes (T2D). This fully-remote, 24-week randomized trial examined the feasibility and efficacy of episodic future thinking (EFT; n=46) compared to control (n=44) for reducing DD and improving T2D outcomes in non-rural and rural adults. All participants received T2D education, coaching, and self-monitoring resources (MyNetDiary). Recruitment, retention, engagement, and acceptability met or exceeded feasibility benchmarks, except for low rural recruitment and declining EFT engagement over time. EFT reduced DD more than control. Although EFT had no overall effect on HbA1c and weight loss, EFT was more effective than control for reducing HbA1c and DD at higher (vs. lower) levels of baseline DD. Together, these findings support targeted implementation of EFT in larger-scale trials based on baseline DD, consistent with a precision medicine framework. Future research, however, should focus on increasing rural recruitment and optimizing EFT engagement.

Episodic Future Thinking as an Intervention for Alcohol Use Disorder: Effects on Delay Discounting and Real-World Alcohol Consumption

Research Square · 2026-04-03

Impact of four tobacco tax policies on tobacco product purchasing patterns across socioeconomic groups

Tobacco Control · 2026-04-01

SIGNIFICANCE: Understanding how integrated tobacco tax policies influence purchasing decisions across socioeconomic groups is critical to advancing tobacco control in an equitable manner in the context of the rapidly evolving tobacco and nicotine product market. Using an Experimental Tobacco Marketplace (ETM), this study examined the effects of four multitiered tax policies on tobacco purchasing among people who smoke cigarettes. Each policy used a different strategy to attain the goal of reducing cigarette purchasing among three socioeconomic groups. The policies were: tobacco parity, nicotine content, harm reduction and modified risk tobacco products. METHODS: A sample representative of the US population (N=481) was recruited from a national survey panel (Prolific). Using a within-subject/between-subject factorial design, participants completed hypothetical purchasing trials in the ETM with products priced under the four multitiered tax policies. Higher tiers equated to higher taxes. RESULTS: Higher taxes consistently reduced relative spending, while relative spending on medium-tax and no-tax tier products varied by tax proposal. The nicotine content tax policy led to the largest reduction in high-tax tier spending and the greatest shift toward no-tax products (eg, nicotine replacement). No socioeconomic differences were observed. CONCLUSIONS: These findings indicate that strategic taxation is a robust and adaptable tool for shifting tobacco purchasing. Integrated tobacco tax policies are likely to be effective at reducing consumption of the highest-risk products without a disproportionate socioeconomic impact. TRIAL REGISTRATION NUMBER: NCT06795997.

Bayesian Clustering Factor Models

Statistics in Medicine · 2026-01-01

We present a novel framework for concomitant dimension reduction and clustering. This framework is based on a novel class of Bayesian clustering factor models. These models assume a factor model structure where the vectors of common factors follow a mixture of Gaussian distributions. We develop a Gibbs sampler to explore the posterior distribution and propose an information criterion to select the number of clusters and the number of factors. Simulation studies show that our inferential approach appropriately quantifies uncertainty. In addition, when compared to two previously published competitor methods, our information criterion has favorable performance in terms of correct selection of number of clusters and number of factors. Finally, we illustrate the capabilities of our framework with an application to data on recovery from opioid use disorder where clustering of individuals may facilitate personalized health care.

The impact of cumulative vulnerabilities on the valuation of cigarettes among veterans seeking to quit smoking

Addictive Behaviors · 2026-03-26

Episodic Future Thinking in a Fully Remote, Multi-Component Behavioral Intervention for Type 2 Diabetes: A Pilot/Feasibility Trial in Rural and Non-Rural Adults [Preprint]

PsyArXiv (OSF Preprints) · 2026-03-24

Delay discounting (DD), or preference for immediate gratification, is a promising therapeutic target in type 2 diabetes (T2D). This fully-remote, 24-week randomized trial examined the feasibility and efficacy of episodic future thinking (EFT; n=46) compared to control (n=44) for reducing DD and improving T2D outcomes in non-rural and rural adults. All participants received T2D education, coaching, and self-monitoring resources (MyNetDiary). Recruitment, retention, engagement, and acceptability met or exceeded feasibility benchmarks, except for low rural recruitment and declining EFT engagement over time. EFT reduced DD more than control. Although EFT had no overall effect on HbA1c and weight loss, EFT was more effective than control for reducing HbA1c and DD at higher (vs. lower) levels of baseline DD. Together, these findings support targeted implementation of EFT in larger-scale trials based on baseline DD, consistent with a precision medicine framework. Future research, however, should focus on increasing rural recruitment and optimizing EFT engagement.

Celebrating each success: proportion of remission as a measure of recovery from polysubstance use disorder proportion of remission; a recovery measure

Harm Reduction Journal · 2026-02-28

BACKGROUND AND AIMS: History of multiple substance use disorders (SUDs) or polysubstance use is highly prevalent, associated with worse treatment outcomes and higher mortality rates compared to single substance use. Although a few longitudinal studies have measured recovery progress over time, no metric explicitly quantifying recovery from polysubstance use is available. Here, we introduce the concept of proportion of remission (PrR) that provides a more granular and nuanced measure of recovery in individuals with polysubstance use and investigate its association with various Quality of Life (QoL) domains. We also report on individual SUD's contribution to QoL. DESIGN: Cross-sectional study design. SETTING: Remote study. PARTICIPANTS: 2,406 participants with polysubstance use (polySUD; i.e., a history of two or more substance use disorders). MEASUREMENTS: Participants completed DSM-5 questionnaires regarding their lifetime and past 12-month substance use, Quality of Life measures, and demographics. Remission status was determined for each SUD based on meeting the DSM-5 criteria (excluding craving) in the past 12 months. Proportion of remission was quantified as the number of SUDs in 12-month remission divided by the total number of lifetime SUDs. RESULTS: PrR was significantly positively associated with environmental (B = 12.13, 95% CI: [9.68, 14.59], f = 0.2), physical (B = 10.75, 95% CI: [8.23, 13.26], f = 0.17), psychological (B = 7.73, 95% CI: [5.93, 9.52], f = 0.17), and social (B = 6.69, 95% CI: [3.45, 9.93], f = 0.08) QoL, after adjusting for covariates. Across SUDs, individuals not in remission exhibited significantly lower QoL compared to those in remission, with stimulants having the largest effect sizes (f = 0.39-0.42). CONCLUSIONS: We propose a novel construct of polySUD recovery: proportion of remission. Our results indicate the potential of PrR to capture gradual improvements in quality of life and reflect recovery progress.

Episodic Future Thinking in a Fully Remote, Multi-Component Behavioral Intervention for Type 2 Diabetes: A Pilot/Feasibility Trial in Rural and Non-Rural Adults [Preprint]

2026-03-08

Delay discounting (DD), or preference for immediate gratification, is a promising therapeutic target in type 2 diabetes (T2D). This fully-remote, 24-week randomized trial examined the feasibility and efficacy of episodic future thinking (EFT; n=46) compared to control (n=44) for reducing DD and improving T2D outcomes in non-rural and rural adults. All participants received T2D education, coaching, and self-monitoring resources (MyNetDiary). Recruitment, retention, engagement, and acceptability met or exceeded feasibility benchmarks, except for low rural recruitment and declining EFT engagement over time. EFT reduced DD more than control. Although EFT had no overall effect on HbA1c and weight loss, EFT was more effective than control for reducing HbA1c and DD at higher (vs. lower) levels of baseline DD. Together, these findings support targeted implementation of EFT in larger-scale trials based on baseline DD, consistent with a precision medicine framework. Future research, however, should focus on increasing rural recruitment and optimizing EFT engagement.

Effects of menthol cigarette and e-cigarette flavour restrictions on tobacco product purchasing: insights from the Experimental Tobacco Marketplace

Tobacco Control · 2026-03-18

AIM: Government regulations can control the design features of tobacco products, including flavours. Understanding how cigarette and e-cigarette flavour availability affects purchasing behaviour among adults who smoke menthol cigarettes can help determine the impact of such policies. Conducted in Roanoke, Virginia, USA, this study investigated how restrictions on menthol cigarettes and non-tobacco e-cigarette flavours affect purchases in the Experimental Tobacco Marketplace (ETM), a simulated environment designed to mimic real-world tobacco purchasing behaviour. METHODS: In a within-subject design, 25 individuals who smoke menthol cigarettes completed purchasing trials with increasing cigarette prices in the ETM under different scenarios: (1) cigarette flavour restricted and e-cigarette flavour restricted, (2) cigarette flavour unrestricted and e-cigarette flavour restricted, (3) cigarette flavour restricted and e-cigarette flavour unrestricted and (4) cigarette flavour unrestricted and e-cigarette flavour unrestricted. RESULTS: Menthol cigarette flavour restrictions significantly decreased cigarette purchases (p<0.001) and increased substitution with e-cigarettes (p<0.002). E-cigarette flavour restrictions were associated with increased purchasing of nicotine replacement therapy (NRT) products (p<0.001). These findings suggest differential impacts of flavour restrictions across product types, highlighting complex substitution patterns among individuals who smoke menthol. CONCLUSION: This study experimentally demonstrated that menthol cigarette bans reduce cigarette purchases. Additionally, flavour restrictions on cigarettes and e-cigarettes distinctly influence substitution patterns, with a menthol cigarette ban encouraging switching to e-cigarettes, while an e-cigarette flavour restriction increases NRT purchasing. As policymakers consider strategies to reduce tobacco-related harms, these findings highlight the need to carefully evaluate broader impacts of flavour restrictions on consumer behaviour.

What is in the model? A Comparison of variable selection criteria and model search approaches

ArXiv.org · 2025-10-03

For many scientific questions, understanding the underlying mechanism is the goal. To help investigators better understand the underlying mechanism, variable selection is a crucial step that permits the identification of the most associated regression variables of interest. A variable selection method consists of model evaluation using an information criterion and a search of the model space. Here, we provide a comprehensive comparison of variable selection methods using performance measures of correct identification rate (CIR), recall, and false discovery rate (FDR). We consider the BIC and AIC for evaluating models, and exhaustive, greedy, LASSO path, and stochastic search approaches for searching the model space; we also consider LASSO using cross validation. We perform simulation studies for linear and generalized linear models that parametrically explore a wide range of realistic sample sizes, effect sizes, and correlations among regression variables. We consider model spaces with a small and larger number of potential regressors. The results show that the exhaustive search BIC and stochastic search BIC outperform the other methods when considering the performance measures on small and large model spaces, respectively. These approaches result in the highest CIR and lowest FDR, which collectively may support long-term efforts towards increasing replicability in research.