Impact of Financial Disclosures and Health Warnings on Youth and Young Adult Perceptions of Pro-E-cigarette Instagram Posts.

INTRODUCTION: We examined the impact of financial disclosures and warning labels on pro-e-cigarette Instagram posts and their association with attitudes toward the ad and product among youth and young adults. METHODS: During March to May 2021, we conducted a factorial experiment using an online convenience sample of youth and young adults (N = 1687, Mage = 21.54). Participants were randomized to one of four conditions: pro-e-cigarette Instagram posts with only a financial disclosure, only a warning label, both a financial disclosure + warning label, or no financial disclosure or warning label. After viewing the posts, participants answered questions regarding their attitude toward the ad and the product. We used one-way ANOVA to estimate the association of condition on outcomes controlling for demographics. RESULTS: Young adults who viewed Instagram posts with only a financial disclosure reported more positive attitudes toward the ad than those who viewed posts with both a financial disclosure + warning label (p < .05). Young adults who viewed posts with only a financial disclosure reported more positive attitudes toward the product than those who viewed posts with only a warning label, both a financial disclosure + warning label, and without either (ps < .05). Differences were not statistically significant for youth. E-cigarette use status was associated with increased positive attitudes toward the ad (p < .001) and product (p < .001) for all participants. CONCLUSIONS: Our results can inform policy interventions to mitigate the effects of e-cigarette social media marketing among youth and young adults. Including financial disclosures may not decrease appeal of e-cigarettes compared to posts without either. IMPLICATIONS: Findings from the study suggest that a warning label may be more effective in reducing the effects of pro-e-cigarette social media posts than a financial disclosure among young adults. Public health officials should examine additional strategies beyond financial disclosures and warning labels (eg, social media peer mentoring program) to offset the persuasive effects of pro-e-cigarette social media marketing posts on young people. Additional policy interventional efforts are needed to limit the impact of e-cigarette social media marketing.

Mobile Health Interventions for Substance Use Disorders.

Substance use disorders (SUDs) have an enormous negative impact on individuals, families, and society as a whole. Most individuals with SUDs do not receive treatment because of the limited availability of treatment providers, costs, inflexible work schedules, required treatment-related time commitments, and other hurdles. A paradigm shift in the provision of SUD treatments is currently underway. Indeed, with rapid technological advances, novel mobile health (mHealth) interventions can now be downloaded and accessed by those that need them anytime and anywhere. Nevertheless, the development and evaluation process for mHealth interventions for SUDs is still in its infancy. This review provides a critical appraisal of the significant literature in the field of mHealth interventions for SUDs with a particular emphasis on interventions for understudied and underserved populations. We also discuss the mHealth intervention development process, intervention optimization, and important remaining questions.

Investigating Best Practices for Ecological Momentary Assessment: Nationwide Factorial Experiment.

BACKGROUND: Ecological momentary assessment (EMA) is a measurement methodology that involves the repeated collection of real-time data on participants' behavior and experience in their natural environment. While EMA allows researchers to gain valuable insights into dynamic behavioral processes, the need for frequent self-reporting can be burdensome and disruptive. Compliance with EMA protocols is important for accurate, unbiased sampling; yet, there is no "gold standard" for EMA study design to promote compliance. OBJECTIVE: The purpose of this study was to use a factorial design to identify optimal study design factors, or combinations of factors, for achieving the highest completion rates for smartphone-based EMAs. METHODS: Participants recruited from across the United States were randomized to 1 of 2 levels on each of 5 design factors in a 2×2×2×2×2 design (32 conditions): factor 1-number of questions per EMA survey (15 vs 25); factor 2-number of EMAs per day (2 vs 4); factor 3-EMA prompting schedule (random vs fixed times); factor 4-payment type (US $1 paid per EMA vs payment based on the percentage of EMAs completed); and factor 5-EMA response scale type (ie, slider-type response scale vs Likert-type response scale; this is the only within-person factor; each participant was randomized to complete slider- or Likert-type questions for the first 14 days or second 14 days of the study period). All participants were asked to complete prompted EMAs for 28 days. The effect of each factor on EMA completion was examined, as well as the effects of factor interactions on EMA completion. Finally, relations between demographic and socioenvironmental factors and EMA completion were examined. RESULTS: Participants (N=411) were aged 48.4 (SD 12.1) years; 75.7% (311/411) were female, 72.5% (298/411) were White, 18.0% (74/411) were Black or African American, 2.7% (11/411) were Asian, 1.5% (6/411) were American Indian or Alaska Native, 5.4% (22/411) belonged to more than one race, and 9.6% (38/396) were Hispanic/Latino. On average, participants completed 83.8% (28,948/34,552) of scheduled EMAs, and 96.6% (397/411) of participants completed the follow-up survey. Results indicated that there were no significant main effects of the design factors on compliance and no significant interactions. Analyses also indicated that older adults, those without a history of substance use problems, and those without current depression tended to complete more EMAs than their counterparts. No other demographic or socioenvironmental factors were related to EMA completion rates. Finally, the app was well liked (ie, system usability scale score=82.7), and there was a statistically significant positive association between liking the app and EMA compliance. CONCLUSIONS: Study results have broad implications for developing best practices guidelines for future studies that use EMA methodologies. TRIAL REGISTRATION: ClinicalTrials.gov number NCT05194228; https://clinicaltrials.gov/study/NCT05194228.

Factors Associated With Successful E-Cigarette Cessation Among a Convenience Sample of Adult Users.

Background: A growing body of literature suggests that many people who use e-cigarettes become dependent and have difficulty quitting. Most people who use e-cigarettes have interest in quitting, yet there is currently a lack of evidence to inform interventions for e-cigarette cessation. Objective: The purpose of this study was to identify factors associated with successful e-cigarette quit attempts among a large sample of people who use e-cigarettes. Methods: Participants (n=586) were people who use e-cigarettes who reported at least one lifetime attempt to quit their e-cigarette use. Adjusted logistic regression models were performed to examine differences in e-cigarette use characteristics and quit methods between people who currently use e-cigarettes and who quit e-cigarettes. Results: Most participants were people who currently use e-cigarettes and only 27.5% reported successfully quitting. Most participants (90.6%) used e-cigarettes that contained nicotine, and over half (54.0%) used closed-system e-cigarette devices with replaceable pre-filled pods or cartridges. The quit method most commonly used overall (63.1%) and for people who quit e-cigarettes (70.8%) was cold turkey. Past 30-day cigarette use and past 30-day other tobacco use was significantly associated with reduced odds of quitting, and there were no e-cigarette characteristics significantly associated with successful cessation. Nicotine replacement therapy was the only e-cigarette cessation method that was significantly associated with increased odds of quitting after adjusting for past 30-day cigarette and other tobacco use. Conclusions: These results suggests that cigarette use, other tobacco use, and quit method used may significantly influence the likelihood of e-cigarette cessation. Future research is needed to determine the effectiveness of interventions for e-cigarette cessation using nicotine replacement therapy.

A Scoping Review and Meta-analysis of the Use of Remote Biochemical Verification Methods of Smoking Status in Tobacco Research.

INTRODUCTION: Increasing digital delivery of smoking cessation interventions has resulted in the need to employ novel strategies for remote biochemical verification. AIMS AND METHODS: This scoping review and meta-analysis aimed to investigate best practices for remote biochemical verification of smoking status. The scientific literature was searched for studies that reported remotely obtained (not in-person) biochemical confirmation of smoking status (ie, combustible tobacco). A meta-analysis of proportions was conducted to investigate key outcomes, which included rates of returned biological samples and the ratio of biochemically verified to self-reported abstinence rates. RESULTS: A total of 82 studies were included. The most common samples were expired air (46%) and saliva (40% of studies), the most common biomarkers were carbon monoxide (48%) and cotinine (44%), and the most common verification methods were video confirmation (37%) and mail-in samples for lab analysis (26%). Mean sample return rates determined by random-effects meta-analysis were 70% for smoking cessation intervention studies without contingency management (CM), 77% for CM studies, and 65% for other studies (eg, feasibility and secondary analyses). Among smoking cessation intervention studies without CM, self-reported abstinence rates were 21%, biochemically verified abstinence rates were 10%, and 47% of individuals who self-reported abstinence were also biochemically confirmed as abstinent. CONCLUSIONS: This scoping review suggests that improvements in sample return rates in remote biochemical verification studies of smoking status are needed. Recommendations for reporting standards are provided that may enhance confidence in the validity of reported abstinence rates in remote studies. IMPLICATIONS: This scoping review and meta-analysis included studies using remote biochemical verification to determine smoking status. Challenges exist regarding implementation and ensuring high sample return rates. Higher self-reported compared to biochemically verified abstinence rates suggest the possibility that participants in remote studies may be misreporting abstinence or not returning samples for other reasons (eg, participant burden, inconvenience). Remote biochemical confirmation of self-reported smoking abstinence should be included in smoking cessation studies whenever feasible. However, findings should be considered in the context of challenges to sample return rates. Better reporting guidelines for future studies in this area are needed.

Development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention for adults with alcohol misuse who are experiencing homelessness.

BACKGROUND: Adults experiencing homelessness have much higher rates of alcohol misuse than housed individuals. This study describes the development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention (JITAI) to reduce alcohol use among adults experiencing homelessness. METHODS: We conducted a pilot trial (N = 41; mean age [SD] = 45.2 [11.5]; 19.5% women) of the Smart-T Alcohol JITAI where participants completed brief ecological momentary assessments (EMAs) each day, received personalized treatment messages following each EMA, and accessed on-demand intervention content for 4 weeks. The prediction algorithm and treatment messages were developed based on an independent but similar sample as part of the trial. We examined three drinking outcomes: daily drinking (yes/no), drinks per day, and heavy episodic drinking, controlling for scores on the Alcohol Use Disorders Identification Test (AUDIT) at baseline, age, and sex using quadratic growth curve models. RESULTS: Over the 4-week period, participants showed a decline in all alcohol use outcomes. Participants also reported high levels of satisfaction with the JITAI. CONCLUSIONS: Use of the Smart-T Alcohol JITAI was well received and provided encouraging evidence that it may reduce any drinking, drinks per day, and heavy episodic drinking among adults experiencing homelessness.

Evaluating the feasibility and acceptability of a mobile-based health technology for smoking cessation: Mobile Anxiety Sensitivity Program.

OBJECTIVES: Cigarette smoking is the leading preventable cause of death and disability. Although most US smokers want to quit, more than 95% of cessation attempts end in relapse within 6 months. To improve cessation outcomes, research has turned to targetable mechanisms, such as anxiety sensitivity (AS), which maintain smoking behaviour, impede cessation success, and can be effectively targeted in the context of psychosocial interventions. Although integrated treatment programmes that address AS reduction in the context of smoking cessation have demonstrated promising results, presently, no mobile, technology-based integrated treatment exists to expressly address smoking and AS. The current study evaluated the initial feasibility and acceptability of a mobile smoking cessation intervention, Mobile Anxiety Sensitivity Program for smoking (MASP). METHODS: Participants were 15 daily adult combustible cigarette smokers (females n = 6, Mage = 46.5 years, SD = 13.3) who completed a 6-week total intervention period (baseline visit, 2 weeks pre-quit, 4 weeks post-quit, follow-up visit). RESULTS: Most participants (N = 12) completed the full 6-week intervention, and participant engagement with MASP was high. Participants reported that MASP was acceptable. Biochemical verification of smoking abstinence indicated 25% of smokers were abstinent for at least 24 hr prior to the in-person 4 weeks post-quit follow-up visit. CONCLUSIONS: Findings indicated that MASP has the potential to provide effective assistance to those wanting to quit cigarettes. PRACTITIONER POINTS: Mobile-based smoking cessation interventions may be a promising treatment option, particularly for those of lower socio-economic status. Targeting AS in the context of a mobile-based smoking cessation app may be a viable way to improve smoking cessation success and treatment outcome. Due to the pilot nature of this study, there was no control group. Thus, comparative conclusions and generalizability based on the current study must be made with caution.

Redesigning culturally tailored intervention in the precision health era: Self-management science context.

BACKGROUND: Nurse scientists have significantly contributed to health equity and ensuring cultural tailoring of interventions to meet unique needs of individuals. Methodologies for cultural tailoring of self-mangament interventions among marginalized populations have limitedly accommodated intersectionality and group heterogeneity when addressing health needs. PURPOSE: Identify methodological limitations in cultural tailoring of interventions among priority populations and issue recommendations on cultural elements that researchers can target to ensure valid cultural tailoring approaches. METHODS: Synthesis of literature on health equity, self-management, and implementation and dissemination research. FINDINGS: Among priority populations, intersectionality and group heterogeneity has made group-based cultural tailoring approaches less effective in eliciting desirable health outcomes. Precision health methodology could be useful for cultural tailoring of interventions due to the methodology's focus on individual-level tailoring approaches. DISCUSSION: We offer ways to advance health equity research using precision health approaches in cultural tailoring through targeting unique elements of culture and relevant psychosocial phenotypes.

Ecological Momentary Assessment of Alcohol Consumption and Its Concordance with Transdermal Alcohol Detection and Timeline Follow-Back Self-report Among Adults Experiencing Homelessness.

BACKGROUND: Studies of alcohol use presume valid assessment measures. To evaluate this presumption, we examined the concordance of alcohol use as measured by ecological momentary assessment (EMA) self-reports, transdermal alcohol concentration readings via the Secure Continuous Remote Alcohol Monitor (SCRAM), and retrospective self-reports via the Timeline Follow-Back (TLFB) among adults experiencing homelessness. METHODS: Forty-nine adults who reported alcohol misuse (mean age = 47, SD = 9; 57% Black; 82% men) were recruited from a homeless shelter. For 4 weeks, alcohol use was assessed: (i) 5 times or more per day by EMA, (ii) every 30 minutes by a SCRAM device worn on the ankle, and (iii) by TLFB for the past month at the end of the study period. There were 1,389 days of observations of alcohol use and alcohol use intensity for 49 participants. RESULTS: EMA and SCRAM alcohol use data agreed on 73% of days, with an interrater agreement Kappa = 0.46. A multilevel analysis of concordance of 3 measures for alcohol use yielded statistically significant correlations of 0.40 (day level) and 0.63 (person level) between EMA and SCRAM. Alcohol use was detected on 49, 38, and 33% of days by EMA, SCRAM, and TLFB, respectively. For alcohol use intensity, EMA and SCRAM resulted in statistically significant correlations of 0.46 (day level) and 0.78 (person level). The concordance of TLFB with either EMA or SCRAM was weak, especially at the day level. CONCLUSIONS: This is the first study to examine concordance of alcohol use estimates using EMA, SCRAM, and TLFB methods in adults experiencing homelessness. EMA is a valid approach to quantifying alcohol use, especially given its relatively low cost, low participant burden, and ease of use. Furthermore, any stigma associated with wearing the SCRAM or reporting alcohol use in person may be attenuated by using EMA, which may be appealing for use in studies of stigmatized and underserved populations.

A Mobile Just-in-Time Adaptive Intervention for Smoking Cessation: Pilot Randomized Controlled Trial.

BACKGROUND: Smartphone apps for smoking cessation could offer easily accessible, highly tailored, intensive interventions at a fraction of the cost of traditional counseling. Although there are hundreds of publicly available smoking cessation apps, few have been empirically evaluated using a randomized controlled trial (RCT) design. The Smart-Treatment (Smart-T2) app is a just-in-time adaptive intervention that uses ecological momentary assessments (EMAs) to assess the risk for imminent smoking lapse and tailors treatment messages based on the risk of lapse and reported symptoms. OBJECTIVE: This 3-armed pilot RCT aimed to determine the feasibility and preliminary efficacy of an automated smartphone-based smoking cessation intervention (Smart-T2) relative to standard in-person smoking cessation clinic care and the National Cancer Institute's free smoking cessation app, QuitGuide. METHODS: Adult smokers who attended a clinic-based tobacco cessation program were randomized into groups and followed for 13 weeks (1 week prequitting through 12 weeks postquitting). All study participants received nicotine patches and gum and were asked to complete EMAs five times a day on study-provided smartphones for 5 weeks. Participants in the Smart-T2 group received tailored treatment messages after the completion of each EMA. Both Smart-T2 and QuitGuide apps offer on-demand smoking cessation treatment. RESULTS: Of 81 participants, 41 (50%) were women and 55 (68%) were white. On average, participants were aged 49.6 years and smoked 22.4 cigarettes per day at baseline. A total of 17% (14/81) of participants were biochemically confirmed 7-day point prevalence abstinent at 12 weeks postquitting (Smart-T2: 6/27, 22%, QuitGuide: 4/27, 15%, and usual care: 4/27, 15%), with no significant differences across groups (P>.05). Participants in the Smart-T2 group rated the app positively, with most participants agreeing that they can rely on the app to help them quit smoking, and endorsed the belief that the app would help them stay quit, and these responses were not significantly different from the ratings given by participants in the usual care group. CONCLUSIONS: Dynamic smartphone apps that tailor intervention content in real time may increase user engagement and exposure to treatment-related materials. The results of this pilot RCT suggest that smartphone-based smoking cessation treatments may be capable of providing similar outcomes to traditional, in-person counseling. TRIAL REGISTRATION: ClinicalTrials.gov NCT02930200; https://clinicaltrials.gov/show/NCT02930200.

Using Elastic Net Penalized Cox Proportional Hazards Regression to Identify Predictors of Imminent Smoking Lapse.

Introduction: Machine learning algorithms such as elastic net regression and backward selection provide a unique and powerful approach to model building given a set of psychosocial predictors of smoking lapse measured repeatedly via ecological momentary assessment (EMA). Understanding these predictors may aid in developing interventions for smoking lapse prevention. Methods: In a randomized-controlled smoking cessation trial, smartphone-based EMAs were collected from 92 participants following a scheduled quit date. This secondary analysis utilized elastic net-penalized cox proportional hazards regression and model approximation via backward elimination to (1) optimize a predictive model of time to first lapse and (2) simplify that model to its core constituent predictors to maximize parsimony and generalizability. Results: Elastic net proportional hazards regression selected 17 of 26 possible predictors from 2065 EMAs to model time to first lapse. The predictors with the highest magnitude regression coefficients were having consumed alcohol in the past hour, being around and interacting with a smoker, and having cigarettes easily available. This model was reduced using backward elimination, retaining five predictors and approximating to 93.9% of model fit. The retained predictors included those mentioned above as well as feeling irritable and being in areas where smoking is either discouraged or allowed (as opposed to not permitted). Conclusions: The strongest predictors of smoking lapse were environmental in nature (e.g., being in smoking-permitted areas) as opposed to internal factors such as psychological affect. Interventions may be improved by a renewed focus of interventions on these predictors. Implications: The present study demonstrated the utility of machine learning algorithms to optimize the prediction of time to smoking lapse using EMA data. The two models generated by the present analysis found that environmental factors were most strongly related to smoking lapse. The results support the use of machine learning algorithms to investigate intensive longitudinal data, and provide a foundation for the development of highly tailored, just-in-time interventions that can target on multiple antecedents of smoking lapse.

The Time-Varying Relations Between Risk Factors and Smoking Before and After a Quit Attempt.

Introduction: Intensive longitudinal data (ILD) collected with ecological momentary assessments (EMAs) can provide a rich resource for understanding the relations between risk factors and smoking in the time surrounding a cessation attempt. Methods: Participants (N = 142) were smokers seeking treatment at a safety-net hospital smoking cessation clinic who were randomly assigned to receive standard clinic care (ie, counseling and cessation medications) or standard care plus small financial incentives for biochemically confirmed smoking abstinence. Participants completed EMAs via study provided smartphones several times per day for 14 days (1 week prequit through 1 week postquit). EMAs assessed current contextual factors including environmental (eg, easy access to cigarettes, being around others smoking), cognitive (eg, urge to smoke, stress, coping expectancies, cessation motivation, cessation self-efficacy, restlessness), behavioral (ie, recent smoking and alcohol consumption), and affective variables. Temporal relations between risk factors and smoking were assessed using a logistic time-varying effect model. Results: Participants were primarily female (57.8%) and Black (71.8%), with an annual household income of <$20000 per year (71.8%), who smoked 17.6 cigarettes per day (SD = 8.8). Individuals assigned to the financial incentives group had decreased odds of smoking compared with those assigned to usual care beginning 3 days before the quit attempt and continuing throughout the first week postquit. Environmental, cognitive, affective, and behavioral variables had complex time-varying impacts on smoking before and after the scheduled quit attempt. Conclusions: Knowledge of time-varying effects may facilitate the development of interventions that target specific psychosocial and behavioral variables at critical moments in the weeks surrounding a quit attempt. Implications: Previous research has examined time-varying relations between smoking and negative affect, urge to smoke, smoking dependence, and certain smoking cessation therapies. We extend this work using ILD of unexplored variables in a socioeconomically disadvantaged sample of smokers seeking cessation treatment. These findings could be used to inform ecological momentary interventions that deliver treatment resources (eg, video- or text-based content) to individuals based upon critical variables surrounding their attempt.

Time with friends and physical activity as mechanisms linking obesity and television viewing among youth.

BACKGROUND: Though bivariate relationships between childhood obesity, physical activity, friendships and television viewing are well documented, empirical assessment of the extent to which links between obesity and television may be mediated by these factors is scarce. This study examines the possibility that time with friends and physical activity are potential mechanisms linking overweight/obesity to television viewing in youth. METHODS: Data were drawn from children ages 10-18 years old (M = 13.81, SD = 2.55) participating in the 2002 wave of Child Development Supplement (CDS) to the Panel Study of Income Dynamics (PSID) (n = 1,545). Data were collected both directly and via self-report from children and their parents. Path analysis was employed to examine a model whereby the relationships between youth overweight/obesity and television viewing were mediated by time spent with friends and moderate-to-vigorous physical activity (MVPA). RESULTS: Overweight/obesity was directly related to less time spent with friends, but not to MVPA. Time spent with friends was directly and positively related to MVPA, and directly and negatively related to time spent watching television without friends. In turn, MVPA was directly and negatively related to watching television without friends. There were significant indirect effects of both overweight/obesity and time with friends on television viewing through MVPA, and of overweight/obesity on MVPA through time with friends. Net of any indirect effects, the direct effect of overweight/obesity on television viewing remained. The final model fit the data extremely well (χ2 = 5.77, df = 5, p<0.0001, RMSEA = 0.01, CFI = 0.99, TLI =0.99). CONCLUSIONS: We found good evidence that the positive relationships between time with friends and physical activity are important mediators of links between overweight/obesity and television viewing in youth. These findings highlight the importance of moving from examinations of bivariate relationships between weight status and television viewing to more nuanced explanatory models which attempt to identify and unpack the possible mechanisms linking them.

Nicotine dependence among young adults: Comparing exclusive ENDS users to exclusive cigarette smokers.

PURPOSE: No studies of young adults have compared symptoms of nicotine dependence among exclusive past 30-day (P30D) ENDS users versus exclusive P30D cigarette smokers. METHODS: Participants at Wave 14 (Fall 2021) of The Texas Adolescent and Tobacco Marketing Surveillance System (TATAMS) (n = 2,341; mean age = 20.95 years old) who reported P30D exclusive ENDS use (n = 212) and P30D exclusive cigarette smoking (n = 46). Symptoms of nicotine dependence were measured with the Hooked On Nicotine Checklist (the 10-item HONC scale). An independent samples t-test compared average HONC scores between groups, and a Pearson (or Fisher's Exact) Chi-Square (X2) test compared the prevalence of symptom(s) between groups. RESULTS: The average HONC score was significantly higher for exclusive P30D ENDS users than exclusive P30D cigarette smokers (3.51 vs. 1.91, p ≤ 0.001). Compared to exclusive P30D cigarette smokers, a significantly higher proportion of exclusive P30D ENDS users reported having felt addicted (45.28% vs. 15.22%, p ≤ 0.001), having strong cravings (50.00% vs. 28.26%, p = 0.007), difficulty not using in prohibited places (i.e., school or work) (24.06% vs. 4.35%, p = 0.002), difficulty concentrating (21.23% vs. 6.52%, p = 0.021), and feeling nervous, restless, or anxious (28.77% vs. 10.87%, p = 0.012). CONCLUSIONS: Symptoms of nicotine dependence were elevated among young adults who were exclusive P30D users of ENDS relative to exclusive P30D cigarette smokers.

Towards AI-Driven Healthcare: Systematic Optimization, Linguistic Analysis, and Clinicians' Evaluation of Large Language Models for Smoking Cessation Interventions.

Creating intervention messages for smoking cessation is a labor-intensive process. Advances in Large Language Models (LLMs) offer a promising alternative for automated message generation. Two critical questions remain: 1) How to optimize LLMs to mimic human expert writing, and 2) Do LLM-generated messages meet clinical standards? We systematically examined the message generation and evaluation processes through three studies investigating prompt engineering (Study 1), decoding optimization (Study 2), and expert review (Study 3). We employed computational linguistic analysis in LLM assessment and established a comprehensive evaluation framework, incorporating automated metrics, linguistic attributes, and expert evaluations. Certified tobacco treatment specialists assessed the quality, accuracy, credibility, and persuasiveness of LLM-generated messages, using expert-written messages as the benchmark. Results indicate that larger LLMs, including ChatGPT, OPT-13B, and OPT-30B, can effectively emulate expert writing to generate well-written, accurate, and persuasive messages, thereby demonstrating the capability of LLMs in augmenting clinical practices of smoking cessation interventions.

Does the Relationship between Affect and Social Interactions among Adults Experiencing Homelessness Differ during Moments when at a Shelter versus Not?

The prevalence of alcohol use disorders is higher amongst adults experiencing homelessness (AEH) compared with domiciled adults. Greater exposure to heavy drinkers increases personal risk for heavy alcohol use. AEH spend substantial periods of time at shelters and report greater pressure to use alcohol when near shelter locations, as well as greater negative affect when near a shelter. It is unclear if the relationship between affect and 1) interacting with people and 2) being near someone AEH drank alcohol with before differs when AEH are at a shelter versus not. AEH reporting alcohol misuse (n = 72, Mage= 47, 85% Male, 68% Non-White) completed five daily smartphone-based ecological momentary assessments (EMAs) over 28 days. Generalized multilevel modeling revealed that when AEH were interacting with someone they drank with before, they had significantly lower positive affect when at a shelter (b = -0.17, p = 0.05), versus when not (b = 0.00, p = 0.99). AEH are likely to interact with previous drinking partners while at shelters. It may be important to deliver real-time treatment messages targeting affect in these moments, as well as deliver alcohol reduction/abstinence messages.

Project phoenix: Pilot randomized controlled trial of a smartphone-delivered intervention for people who are not ready to quit smoking.

BACKGROUND: Most people who smoke cigarettes report they want to quit in the future, but only 20 % are ready to quit within the next 30 days. This 3-arm pilot randomized controlled trial examined the feasibility and initial efficacy of a novel smartphone-based intervention that aimed to induce smoking cessation attempts among adults not initially ready to quit. METHODS: Participants randomized into the two intervention groups (Group 1: Phoenix App Only; Group 2: Phoenix App + Nicotine Replacement Therapy) received daily smoking cessation messages via smartphone application that were tailored to their current readiness to quit, while the attention control group (i.e., Factoid) received messages not related to smoking cessation. All participants completed a weekly survey for 26 weeks and used the app to set quit dates when/if desired. RESULTS: Participants (N=152) were female (67.8 %), White (75.7 %), 50.0 years old (SD=12.5), and smoked 20.4 cigarettes per day (SD=10.5). Results indicated that the Phoenix interventions were feasible (e.g., participants viewed ~185 messages over 26 weeks; 74.8 % of weekly surveys were completed; 85.5 % completed the 26-week follow-up assessment). Phoenix participants set more quit dates, set quit dates sooner, were abstinent for more days, and used smoking cessation medications on more days than those assigned to the Factoid group. CONCLUSIONS: This low-burden, smartphone-based smoking cessation induction intervention may increase smoking cessation attempts, and may reduce barriers that are encountered with traditional in-person or call-based interventions. TRIAL REGISTRATION: Clinicaltrials.gov number: NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129.

Financial Incentives for Smoking Cessation Among Socioeconomically Disadvantaged Adults: A Randomized Clinical Trial.

Importance: Socioeconomically disadvantaged individuals (ie, those with low socioeconomic status [SES]) have difficulty quitting smoking and may benefit from incentive-based cessation interventions. Objectives: To evaluate the impact of incentivizing smoking abstinence on smoking cessation among adults with low SES. Design, Setting, and Participants: This study used a 2-group randomized clinical trial design. Data collection occurred between January 30, 2017, and February 7, 2022. Participants included adults with low SES who were willing to undergo smoking cessation treatment. Data were analyzed from April 18, 2023, to April 19, 2024. Interventions: Participants were randomized to usual care (UC) for smoking cessation (counseling plus pharmacotherapy) or UC plus abstinence-contingent financial incentives (UC plus FI). Main Outcomes and Measures: The primary outcome was biochemically verified 7-day point prevalence smoking abstinence (PPA) at 26 weeks after the quit date. Secondary outcomes included biochemically verified 7-day PPA at earlier follow-ups, 30-day PPA at 12 and 26 weeks, repeated 7-day PPA, and continuous abstinence. Multiple approaches were employed to handle missing outcomes at follow-up, including categorizing missing data as smoking (primary), complete case analysis, and multiple imputation. Results: The 320 participants had a mean (SD) age of 48.9 (11.6) and were predominantly female (202 [63.1%]); 82 (25.6%) were Black, 15 (4.7%) were Hispanic, and 200 (62.5%) were White; and 146 (45.6%) participated during the COVID-19 pandemic. Overall, 161 were randomized to UC and 159 were randomized to UC plus FI. After covariate adjustment with missing data treated as smoking, assignment to UC plus FI was associated with a greater likelihood of 7-day PPA at the 4-week (adjusted odds ratio [AOR], 3.11 [95% CI, 1.81-5.34]), 8-week (AOR, 2.93 [95% CI, 1.62-5.31]), and 12-week (AOR, 3.18 [95% CI, 1.70-5.95]) follow-ups, but not at the 26-week follow-up (22 [13.8%] vs 14 [8.7%] abstinent; AOR, 1.79 [95% CI, 0.85-3.80]). However, the association of group assignment with smoking cessation reached statistical significance at all follow-ups, including 26 weeks, with multiple imputation (37.37 [23.5%] in the UC plus FI group vs 19.48 [12.1%] in the UC group were abstinent; AOR, 2.29 [95% CI, 1.14-4.63]). Repeated-measures analyses indicated that participants in the UC plus FI group were significantly more likely to achieve PPA across assessments through 26 weeks with all missing data estimation methods. Other secondary cessation outcomes also showed comparable patterns across estimation methods. Participants earned a mean (SD) of $72 ($90) (of $250 possible) in abstinence-contingent incentives. Participation during the COVID-19 pandemic reduced the likelihood of cessation across assessments. Conclusions and Relevance: In this randomized clinical trial, incentivizing smoking cessation did not increase cessation at 26 weeks when missing data were treated as smoking; however, the UC plus FI group had greater odds of quitting at follow-ups through 12 weeks. Cessation rates were higher for the UC plus FI group at all follow-ups through 26 weeks when multiple imputation was used to estimate missing outcomes. Trial Registration: ClinicalTrials.gov Identifier: NCT02737566.

Impediments and facilitators to physical activity and perceptions of sedentary behavior among urban community residents: the Fair Park Study.

INTRODUCTION: Insufficient physical activity is an established risk factor for numerous chronic diseases and for premature death. Accumulating evidence reveals that prolonged sedentary time is detrimental, independent of the protective effects of physical activity. Although studies have explored correlates of physical activity among ethnic minority populations, few have examined factors related to sedentary behavior. Therefore, we conducted a preliminary investigation into urban adults' perceptions of sedentary behavior alongside perceived barriers and enablers to physical activity. METHODS: In-depth semi-structured interviews were used to evaluate perceptions of physical activity and sedentary behavior in a sample of low-income, ethnic minority adults. The framework approach guided researchers in analyzing the qualitative data. RESULTS: Participants were well aware of the positive health benefits of physical activity. However, most admitted not regularly engaging in physical activity and cited numerous barriers to activity, such as lack of time, insufficient finances, and neighborhood crime. Enablers included weight loss, the presence of social support, and the availability of safe parks conducive to exercise. In comparison, participants were primarily unfamiliar with the term "sedentary behavior" and did not perceive a relationship between sedentary behavior and health outcomes. CONCLUSION: Our findings illustrate the need to increase the awareness of negative health implications of prolonged sedentary time while continuing to address the multiple impediments to physical activity as a way to combat chronic disease.