The prospective relationship between a-priori intentions for and patterns of e-cigarette use among adults who smoke cigarettes.

BACKGROUND: Electronic (e-)cigarettes may help adult cigarette smokers achieve cigarette cessation, depending on patterns of e-cigarette use. Among cigarette smokers who do not use e-cigarettes, it is unclear if and how a-priori intentions for use are related to uptake patterns. Longitudinal studies have focused on established e-cigarette users or adolescent and young adult populations exclusively. METHODS: Within a nationwide randomized clinical trial (N = 638), adult cigarette smokers not currently using e-cigarettes were randomized (2:1) to receive (or not) one-month sampling of e-cigarettes. An exploratory factor analysis (EFA) was performed on an established 15-item measure assessing a-priori intentions for e-cigarette use to identify latent variables. Among those receiving e-cigarette products, regression models examined relationships between intentions and: 1) uptake (yes/no), 2) frequency (number of days per week), and 3) amount (puffing episodes per day) of e-cigarette use at one-month follow-up. RESULTS: Two factors emerged from the EFA: 1) cigarette-related intentions (e.g., cigarette cessation, no smell) and 2) novel appeal of e-cigarettes (e.g., flavors). Three items remained and were treated as separate intentions: "feels like cigarette smoking", "curiosity", and "affordability". In the final multivariable models, "feel like cigarette smoking" predicted more frequent e-cigarette use (ß = 0.187, SE = 0.086, p = 0.03); however, none of the five factors/intentions were significantly associated with uptake or amount of use. CONCLUSIONS: For adult cigarette smokers not currently using e-cigarettes, a-priori intentions for using e-cigarettes might not be predictive of if or how these products will be used in the future, suggesting that motives may not drive use behavior.

Short-changing the future: The systemic gap between psychology internship stipends and living wages.

Introduction: Providing doctoral internship stipends below living wages may harm interns, the clinical services they provide, and the field of health service psychology as a whole. This study evaluated the extent to which doctoral psychology internship stipends from the 2021-2022 training year for APA-accredited, APPIC-member programs in the US are consistent with living wages in the geographic region where sites are located. Methods: We obtained data reflecting internship sites' geographic location and stipends for the 2021-2022 academic year. Using the Massachusetts Institute of Technology Living Wage Calculator, we computed a living wage for the county in which each internship site is located. Descriptive statistics, discrepancies, ratios, and correlations were calculated to reflect the associations between internship sites' stipends and their local living wages. Results: The average internship stipend was $31,783, which was lower than the average living wage by $2,091. Stipends ranged widely, from a low of $15,000 to a high of $94,595-reflecting a six-fold difference in wages. Although internship sites in higher cost of living areas paid higher stipends, over two-thirds (67.0%) of sites did not pay a stipend that equaled or exceeded a living wage. Ninety-eight sites (15.3%) had deficits of over $10,000 when comparing their stipends to local living wages, with $33,240 as the highest deficit. Discussion: Eliminating obstacles to educating health service psychologists by decreasing the financial burden of training will likely have subsequent critical benefits towards bridging the workforce gap between mental healthcare service needs and available providers, ultimately leading to improved population health.

Cannabis Perceptions and Patterns of Use Among Older Adult Cancer Survivors.

Objectives: To descriptively assess cannabis perceptions and patterns of use among older adult cancer survivors in a state without a legal cannabis marketplace. Methods: This study used weighted prevalence estimates to cross-sectionally describe cannabis perceptions and patterns of use among older (65+) adults (N = 524) in a National Cancer Institute-designated center in a state without legal cannabis access. Results: Half (46%) had ever used cannabis (18% following diagnosis and 10% currently). Only 8% had discussed cannabis with their provider. For those using post-diagnosis, the most common reason was for pain (44%), followed by insomnia (43%), with smoking being the most common (40%) mode of use. Few (<3%) reported that cannabis had worsened any of their symptoms. Discussion: Even within a state without a legal cannabis marketplace, older cancer survivors might commonly use cannabis to alleviate health concerns but unlikely to discuss this with their providers.

Behavioral Activation-Based Digital Smoking Cessation Intervention for Individuals With Depressive Symptoms: Randomized Clinical Trial.

BACKGROUND: Depression is common among adults who smoke cigarettes. Existing depression-specific cessation interventions have limited reach and are unlikely to improve smoking prevalence rates among this large subgroup of smokers. OBJECTIVE: This study aimed to determine whether a mobile app-based intervention tailored for depression paired with a mailed sample of nicotine replacement therapy (NRT) is efficacious for treating depression and promoting smoking cessation. METHODS: A 2-arm nationwide remote randomized clinical trial was conducted in the United States. Adults (N=150) with elevated depressive symptoms (Patient Health Questionnaire-8≥10) who smoked were enrolled. The mobile app ("Goal2Quit") provided behavioral strategies for treating depression and quitting smoking based on Behavioral Activation Treatment for Depression. Goal2Quit participants also received a 2-week sample of combination NRT. Treatment as usual participants received a self-help booklet for quitting smoking that was not tailored for depression. Primary end points included Goal2Quit usability, change in depression (Beck Depression Inventory-II) across 12 weeks, and smoking cessation including reduction in cigarettes per day, incidence of 24-hour quit attempts, floating abstinence, and 7-day point prevalence abstinence (PPA). RESULTS: In total, 150 participants were enrolled between June 25, 2020, and February 23, 2022, of which 80 were female (53.3%) and the mean age was 38.4 (SD 10.3) years. At baseline, participants on average reported moderate depressive symptoms and smoked a mean of 14.7 (SD 7.5) cigarettes per day. Goal2Quit usability was strong with a mean usability rating on the System Usability Scale of 78.5 (SD 16.9), with 70% scoring above the ≥68 cutoff for above-average usability. Retention data for app use were generally strong immediately following trial enrollment and declined in subsequent weeks. Those who received Goal2Quit and the NRT sample reported lower mean depressive symptoms over the trial duration as compared to treatment as usual (difference of mean 3.72, SE 1.37 points less; P=.01). Across time points, all cessation outcomes favored Goal2Quit. Regarding abstinence, Goal2Quit participants reported significantly higher rates of 7-day PPA at weeks 4 (11% vs 0%; P=.02), 8 (7-day PPA: 12% vs 0%; P=.02), and 12 (16% vs 2%; P=.02). CONCLUSIONS: A mobile app intervention tailored for depression paired with a sample of NRT was effective for depression treatment and smoking cessation. Findings support the utility of this intervention approach for addressing the currently unmet public health treatment need for tailored, scalable depression-specific cessation treatments. TRIAL REGISTRATION: ClinicalTrials.gov NCT03837379; https://clinicaltrials.gov/ct2/show/NCT03837379.

Rationale, design, and protocol for a hybrid type 1 effectiveness-implementation trial of a proactive smoking cessation electronic visit for scalable delivery via primary care: the E-STOP trial.

BACKGROUND: Cigarette smoking remains the leading cause of preventable disease and death in the United States. Primary care offers an ideal setting to reach adults who smoke cigarettes and improve uptake of evidence-based cessation treatment. Although U.S. Preventive Services Task Force Guidelines recommend the 5As model (Ask, Advise, Assess, Assist, Arrange) in primary care, there are many barriers to its implementation. Automated, comprehensive, and proactive tools are needed to overcome barriers. Our team developed and preliminarily evaluated a proactive electronic visit (e-visit) delivered via the Electronic Health Record patient portal to facilitate evidence-based smoking cessation treatment uptake in primary care, with promising initial feasibility and efficacy. This paper describes the rationale, design, and protocol for an ongoing Hybrid Type I effectiveness-implementation trial that will simultaneously assess effectiveness of the e-visit intervention for smoking cessation as well as implementation potential across diverse primary care settings. METHODS: The primary aim of this remote five-year study is to examine the effectiveness of the e-visit intervention vs. treatment as usual (TAU) for smoking cessation via a clinic-randomized clinical trial. Adults who smoke cigarettes are recruited across 18 primary care clinics. Clinics are stratified based on their number of primary care providers and randomized 2:1 to either e-visit or TAU. An initial baseline e-visit gathers information about patient smoking history and motivation to quit, and a clinical decision support algorithm determines the best evidence-based cessation treatment to prescribe. E-visit recommendations are evaluated by a patient's own provider, and a one-month follow-up e-visit assesses cessation progress. Main outcomes include: (1) cessation treatment utilization (medication, psychosocial cessation counseling), (2) reduction in cigarettes per day, and (3) biochemically verified 7-day point prevalence abstinence (PPA) at six-months. We hypothesize that patients randomized to the e-visit condition will have better cessation outcomes (vs. TAU). A secondary aim evaluates e-visit implementation potential at patient, provider, and organizational levels using a mixed-methods approach. Implementation outcomes include acceptability, adoption, fidelity, implementation cost, penetration, and sustainability. DISCUSSION: This asynchronous, proactive e-visit intervention could provide substantial benefits for patients, providers, and primary care practices and has potential to widely improve reach of evidence-based cessation treatment. TRIAL REGISTRATION: NCT05493254.

Motives for using electronic nicotine delivery systems (ENDS) as a cessation tool are associated with tobacco abstinence at 1-year follow-up: A prospective investigation among young adults in the United States Air Force.

Introduction: Smokers use electronic nicotine delivery systems (ENDS), including e-cigarettes, as a harm reduction strategy even though the Food and Drug Administration (FDA) has not approved them for tobacco cessation. The limited literature about ENDS use for cigarette cessation is concerning for the U.S. military, which is largely comprised of young adults at increased risk for tobacco use. Thus, the current study aims to evaluate use of ENDS products as a cessation tool in relation to point-prevalence tobacco abstinence at one-year follow-up in a cohort of 8,901 U.S. Air Force personnel attending entry-level job training from March 2016 to April 2019. Methods: A propensity-score adjusted multinomial logistic regression model was used to assess the association between the baseline motives for ENDS use (i.e., for cigarette cessation versus alternative reasons) and tobacco use at the one-year follow-up (cigarette use, non-cigarette tobacco product use, and tobacco abstinence) among those reporting history of cigarette use at baseline. Results: Smokers reporting ENDS use for cigarette cessation were more likely to be abstinent at one-year follow-up (Odds Ratio[OR] = 1.62, 95% CI: 1.06-2.49, P =.03) as well as quit using non-cigarette tobacco products (OR = 2.11, 95% CI: 1.65-2.70, P <.001) than those reporting ENDS use for alternative reasons. Conclusions: Current tobacco users are recommended to use FDA-approved products for smoking cessation, such as nicotine replacement therapy. However, given the high prevalence of cigarette use among military populations, ENDS may provide a useful alternative harm reduction strategy for this high-risk population.

"And then I found $5": Optimizing recruitment efficiency in remote clinical trials.

Introduction: As clinical trials adopt remote methodologies, there is need to optimize efficiency of remote enrollment. Within a remote clinical trial, we aim to (1) assess if sociodemographic factors differ among those consenting via mail vs. technology-based procedures (e-consent), (2) determine if, among those consenting via mail, a small unconditional monetary reward ($5) increases likelihood of subsequent enrollment, (3) economically evaluate additional cost per additional participant enrolled with $5 reward. Methods: In the parent nationwide randomized clinical trial of adult smokers (N = 638), participants could enroll via mail or e-consent. Logistic regression models assessed relationships between sociodemographics and enrollment via mail (vs e-consent). Mailed consent packets were randomized (1:4) to include $5 unconditional reward or not, and logistic regression modeling examined impact of reward on subsequent enrollment, allowing for a randomized study within a study. Incremental cost-effectiveness ratio analysis estimated additional cost per additional participant enrolled with $5 incentive. Results: Older age, less education, lower income, and female sex predicted enrolling via mail vs e-consent (p < .05's). In adjusted model, older age (AOR = 1.02, p = .016) and less education (AOR = 2.23, p < .001) remained predictive of mail enrollment. The $5 incentive (vs none) increased enrollment rate by 9% (AOR = 1.64, p = .007), with estimated cost of additional $59 per additional participant enrolled. Conclusions: As e-consent methods become more common, they have potential to reach many individuals but with perhaps diminished inclusion across all sociodemographic groups. Provision of an unconditional monetary incentive is possibly a cost-effective mechanism to increase recruitment efficiency for studies employing mail-based consenting procedures.

The Impact of Older Age on Smoking Cessation Outcomes After Standard Advice to Quit.

Older adults are a high priority population for smoking cessation. This study observed the influence of older age on the relationship between quitting predictors and cessation. Secondary analysis was conducted of a primary care trial of adults who smoke cigarettes randomized to standard advice to quit or advice plus 2 week supply of nicotine replacement therapy. Logistic regressions assessed interactions of age (<60 vs. ≥ 60 years) by predictors in relation to quit attempts and 6-month cessation controlling for treatment. Predicting quit attempts, there was an interaction of age by motivation (p = .025) and trend of age by nicotine dependence (p = .057). Predicting 6-month cessation, an interaction of age by motivation was observed (p = .020) and a trend of age by dependence (p = .067). For those with high nicotine dependence, older adults had less successful outcomes compared to younger counterparts. Yet among participants unmotivated to quit, older adults had more successful outcomes than those younger.

Examination of Tobacco-Related Messaging and Tobacco Use over Time among U.S. Military Young Adults.

Background: People from minoritized populations have historically been targeted by tobacco companies. Little is known about exposure to tobacco-related messages among military personnel from disadvantaged backgrounds. Objectives: The current study aimed to examine exposure to tobacco-related messaging across many nicotine products and through a variety of mediums (i.e., family, friends, advertisements, event promotions, social media) among diverse military populations and use one year later in a sample of young adults who recently enlisted in the U.S. Air Force. Methods: In this study, 8,901 U.S. Air Force trainees reported on demographics, tobacco use, and exposure to positive tobacco messages from social sources (i.e., friends, family, social media) and environmental sources (i.e., advertisements and promotions). Tobacco use was reported one-year later. Results: Compared to others of the same reported racial/ethnic background, Latino/a/x (Relative Risk Ratio [RRR] = 1.354, 95% CI: [1.145, 1.563]) and multiracial (RRR = 1.594, 95% CI: [1.173, 2.016]) participants who were exposed to positive tobacco messages from social sources were significantly more likely to report tobacco product use at one-year follow-up than those who were not exposed to social messages. Exposure to positive tobacco messages from environmental sources were not significantly associated with tobacco use one year later. Conclusions: Social messages may play an important role in increasing risk of tobacco use among some minoritized populations. Cultural as well as systemic factors could be addressed in future tobacco prevention programs to decrease the potency of positive tobacco-related social messages among Latino/a/x and multiracial communities.

Predictors of Cessation Outcomes Among Older Adult Smokers Enrolled in a Proactive Tobacco Quitline Intervention.

OBJECTIVES: To identify predictors of older adults' likelihood of quitting following engagement in a proactive tobacco quit line. METHODS: Older (>60 years) participants (N = 186) enrolled in a four-session quit line with 8-weeks of nicotine replacement therapy reported demographics, beliefs, and information about tobacco use. Point prevalence abstinence was reported at 3 and 12-months. RESULTS: In final models, endorsement of quitting to take control of one's life and confidence in quitting were positively associated with 3-month cessation (OR = 1.74, 95% CI = 1.16, 2.62; OR = 1.75, 95% CI = 1.21, 2.52, respectively). At 12 months, stronger endorsement of quitting to take control of one's life and decreased nicotine dependence were associated with higher cessation (OR = 1.51, 95% CI = 1.05, 2.17; OR = 0.84, 95% CI = 0.71,0.99, respectively). DISCUSSION: For tobacco cessation among older adults, programs should provide additional support to those with higher nicotine dependence, promote quitting self-efficacy, and encourage quitting as means to gain control of life and health.

Efficacy of a group-based brief tobacco intervention among young adults aged 18-20 years in the US Air Force.

INTRODUCTION: Most smokers begin using tobacco before the age of 25 years, making it important to reduce tobacco use during adolescence and early adulthood. Rates of use are historically higher among military personnel. While 'Tobacco 21' made it illegal for US retailers to sell tobacco to those aged <21 years, the policy did not address cessation for current youth and young adult tobacco users. Additionally, there is limited research on cessation interventions among young adults under 21 years. The current study evaluated the efficacy of a group-based Brief Tobacco Intervention (BTI) among US Air Force trainees, who are predominantly aged 18-20 years and directly impacted by Tobacco 21 legislation. METHODS: Participants were 2969 US Air Force Trainees from April 2017 through January 2018 cluster randomized to three conditions: 1) BTI + Airman's Guide to Remaining Tobacco Free (AG), 2) AG alone, and 3) the National Cancer Institute's Clearing the Air (CTA) pamphlet. To assess the efficacy of the interventions among people aged 18-20 years, a domain analysis (<21 years, n=2117; and ≥21 years, n=852) of a multinomial logistic regression model was run. RESULTS: Mono tobacco users aged <21 years at baseline who received the BTI+AG had higher odds of quitting tobacco at 3 months (OR=2.13; 95% CI: 1.02-4.46). Dual and poly users aged <21 years at baseline who received the BTI+AG intervention had higher odds of reducing the number of tobacco products used at 3 months (OR=2.94; 95% CI: 1.03-8.37). CONCLUSIONS: The BTI was effective for people aged 18-20 years. The current study offers insight into components of interventions that might be successful in helping this age group decrease tobacco use.

Counselor Efficiency at Providing Feedback in a Technology-Based Behavioral Weight Loss Intervention: Longitudinal Analysis.

BACKGROUND: Feedback for participants' self-monitoring is a crucial and costly component of technology-based weight loss interventions. Detailed examination of interventionist time when reviewing and providing feedback for online self-monitoring data is lacking. OBJECTIVE: The aim of this study was to longitudinally examine the time counselors spent providing feedback on participant self-monitoring data (ie, diet, physical activity, weight) in a 12-month technology-based weight loss intervention. We hypothesized that counselors would compose feedback for participants more quickly over time. METHODS: The time the lay counselors (N=10) spent reviewing self-monitoring records and providing feedback to participants via email was longitudinally examined for all counselors across the three years of study implementation. Descriptives were observed for counselor feedback duration across counselors by 12 annual quarters (ie, 3-month periods). Differences in overall duration times by each consecutive annual quarter were analyzed using Wilcoxon-Mann-Whitney tests. RESULTS: There was a decrease in counselor feedback duration from the first to second quarter (mean 53 to 46 minutes; P<.001), and from the second to third (mean 46 to 30 minutes; P<.001). A trend suggested a decrease from the third to fourth quarter (mean 30 to 26 minutes; P=.053), but no changes were found in subsequent quarters. Consistent with the hypothesis, counselors may be increasing their efficiency in providing feedback; across 12 months, counselors spent less time reviewing participant self-monitoring and composing feedback (decreasing from mean 53 to 26 minutes). CONCLUSIONS: Counselors used increasingly less time to review online self-monitoring data and compose feedback after the initial 9 months of study implementation. Results inform counselor costs for future technology-based behavioral weight loss interventions. For example, regardless of increasing counselor efficiency, 25-30 minutes per feedback message is a high cost for interventions. One possibility for reducing costs would be generating computer-automated feedback. TRIAL REGISTRATION: ClinicalTrials.gov NCT02063178; https://clinicaltrials.gov/ct2/show/NCT02063178.

Association between Perceived Discrimination and Vaping among College Students.

BACKGROUND: Perceived discrimination has been associated with a higher prevalence of e-cigarette use among adult samples. However, little is understood about the relationship between discrimination and various vaping behaviors among college students. Methods: College students completed an online survey about e-cigarette use (N = 488; 73.2% women; 52.7% White, 30.5% Black/African American, 6.1% Asian, 5.3% other races, 3.9% Multiracial). Participants completed the Everyday Discrimination Scale and identified which of their identities discrimination was most directed toward. Regressions, controlling for significant covariates of outcomes, examined discrimination in relation to e-cigarette ever use, current use, and frequency of use. Results: A higher discrimination score predicted greater odds of ever vaping compared with never use (OR = 1.21, p=.03). Controlling for race (p=.003), greater discrimination was related to increased likelihood of established vaping (100+ times) versus lighter levels of use (AOR = 1.22, p=.04). Discrimination was not associated with likelihood of current vaping (p>.05). Among e-cigarette users, greater perceived discrimination was related to an increased time spent vaping per day (ß =1.69, SE = 0.204, p=.05). Conclusions/Importance: Greater perceived discrimination was associated with more frequent vaping among college students. Current results extend previous findings by suggesting that among college e-cigarette users, those who experience discrimination are more likely to use these products frequently rather than experimentally. Findings can inform the identification and development of resources for students experiencing discrimination to prevent the uptake of e-cigarette use.

Trends in Tobacco Use among Young Adults Presenting for Military Service in the United States Air Force between 2013 and 2018.

Background: The US military has historically higher tobacco use compared to civilians, and tobacco use increases following enlistment. While the military is vulnerable to tobacco use, current surveillance of tobacco among this high-risk population is lacking. Methods: Recently enlisted Airmen (N = 43,597) between 2013 and 2018 were asked about tobacco use prior to enlistment across ten products: (1) cigarettes/roll your own tobacco, (2) smokeless tobacco/snus, (3) cigars, cigarillos/little cigars, (4) hookah/pipe, and (5) e-cigarettes. Results: Hookah/pipe use, cigarettes/roll your own, smokeless tobacco/snus, and cigars/little cigars/cigarillos use decreased significantly between 2013 and 2018, while the prevalence of e-cigarette use increased (p's < 0.0001). The relationships between the time and each tobacco product(s) use outcomes were influenced differently by different age, race, education and marital status. Conclusion: While e-cigarette use has increased in the civilian sector, the use of e-cigarettes among new recruits increased much more drastically (i.e. prevalence 15.3% in 2018). Further, demographic characteristics influenced tobacco trends; specifically, recruits of racial minorities increased their use of e-cigarettes over the past five years faster than Whites. Of concern is what impact this dramatic increase in e-cigarette use will have on overall health and later initiation of combustible tobacco products in the military.

Dissemination of a Universally Delivered Brief Alcohol Intervention in United States Air Force Technical Training.

OBJECTIVES: Heavy alcohol use is a particular problem in the US military, prompting the Institute of Medicine to identify it as a public health crisis. Developing prevention programs aimed at reducing problematic drinking during military service would be useful. Thus, the purpose of the current study, was to broadly disseminate and assess the effectiveness of a brief alcohol intervention (BAI) + random breathalyzer (RB) intervention to reduce alcohol related incidents (ARIs), to all incoming Air Force trainees. METHODS: The BAI was administered to all incoming Airmen (N = 15,898) across 4 major training Air Force bases. Additionally, underage Airmen were subject to RB tests. A quasi-experimental pre-test post-test design compared the rate of ARIs, per 100,000 training days, during the year prior and the year after the intervention was delivered. RESULTS: A Poisson model indicated that the BAI + RB intervention was associated with a decrease in ARIs across all bases. Overall, the intervention lowered the ARI rate by 16% (ß = -0.178, standard error  = 0.0742, P = 0.016). For every 100,000 training days, annual ARIs decreased from 30.8 to 25.5 after implementation. CONCLUSIONS: A universally administered brief alcohol intervention, coupled with RB targeting underage drinkers, was associated with a reduction in the rate of ARIs. Results of this large-scale prevention study indicate that a brief alcohol intervention can be widely disseminated during US Air Force training and can perhaps reduce costs and make a public health contribution by decreasing alcohol related incidents.

When, How, & Where Tobacco Initiation and Relapse Occur During U.S. Air Force Technical Training.

INTRODUCTION: Military personnel are at high risk for tobacco use, particularly during the first year of military service. Technical Training follows an 8½ week tobacco ban during basic military training and is a vulnerable time for personnel to both reinitiate and initiate tobacco use. Thus, this can be a crucial time to promote tobacco policies and interventions. However, there is limited research examining when, how, and where personnel access tobacco during the first year of service, particularly among users of newer products (eg, electronic cigarettes[e-cigarettes]). Thus, the purpose of the current study is to explore the timing, source, and location of tobacco use during Technical Training across all types of products. Furthermore, this study will examine differences in demographic characteristics and prior tobacco history in relationship to these tobacco behaviors. MATERIALS AND METHODS: Participants were U.S. Air Force recruits completing Technical Training (2017-2018). Protocol was approved by the Institutional Review Board at the 59th Medical Wing of the U.S. Air Force. During the first week of Technical Training, Airmen were consented to participate in the study and completed a questionnaire about demographics and tobacco use history. Next, Airmen were randomized to receive one of three tobacco prevention interventions as part of military training. At a 3-month follow-up, during the last week of Technical Training, consented participants completed a questionnaire about current tobacco use. Airmen reported when (ie, first month vs. after), how (ie, "bummed" from another airman, bought on or off base, received from the internet or event), and where (ie, designated smoking areas on base, off base, bar or club, friend's house, cigar lounge, hookah bar, or vape shop) they used tobacco during Technical Training. Descriptive statistics were used to examine these behaviors across all tobacco products. Additionally, Wilcoxon-Mann-Whitney and Kruskal-Wallis tests compared differences in demographic characteristics and baseline tobacco use in relationship to these tobacco behaviors. RESULTS: No significant differences were found when comparing prior users and first-time users in relationship to tobacco behaviors during Technical Training; however, significant differences in educational background and age were found in regard to the source and location of tobacco use. Additionally, how and where Airmen first used tobacco during Technical Training differed across products. Cigarettes and smokeless tobacco were equally likely to be bought on or off base and most commonly first used at a designated smoking area on base. However, e-cigarettes, cigarillos/little cigars, and hookah were more likely to be bought off base, and first used at a specialty store (ie, vape shop, hookah bar, or cigar lounge). CONCLUSIONS: Tobacco use behaviors during Technical Training differed depending on the type of product. Specifically, new and emerging products were more likely to be bought off base and first used at a specialty store. Thus, military polices regulating on base tobacco pricing might not reduce the growing prevalence of e-cigarettes. Future policies might consider addressing the density of off-base tobacco retailers to reduce the high rates of tobacco use in this population.

Evaluating the Effects of a Brief Tobacco Intervention in the US Air Force.

INTRODUCTION: Military personnel have among the highest rates of tobacco use in the United States. Unfortunately, there are few interventions aimed at reducing tobacco use among this vulnerable population. The current study addresses this need by evaluating the short-term effectiveness of a Brief Tobacco Intervention (BTI), a 40-min group-based intervention designed to reduce contemporary patterns of tobacco use among a sample of US military enlistees during an 11-week period of involuntary tobacco abstinence. AIMS AND METHODS: Participants were 2999 US Air Force Technical Trainees at Joint Base San Antonio-Lackland Air Force Base in San Antonio, Texas from April 2017 through January 2018. Participants were cluster randomized to three conditions: (1) BTI + Airman's Guide to Remaining Tobacco Free (AG), (2) AG intervention, or (3) standard smoking cessation intervention. The primary analysis was a comparison of the interventions' efficacies in preventing tobacco use during Technical Training, conducted using a generalized estimating equations logistic regression model controlling for covariates. Multiple imputation was used to account for loss to follow-up. RESULTS: There was not a significant difference by condition in the use of tobacco products at follow-up (p = .454). The BTI + AG condition did produce short-term changes in perceived harm, intentions to use tobacco, knowledge about tobacco products, and normative beliefs. CONCLUSIONS: These findings suggest that while the intervention was effective in the short term, it was not potent enough over a 12-week period to prevent Airmen from initiating tobacco use. Future studies should examine whether adding a booster session or media campaign enhances the effectiveness of the intervention. IMPLICATIONS: Despite the fact that most Airmen believe they will remain tobacco free following the ban in Technical Training, a large percentage of these Airmen resume and initiate tobacco use during this high-risk period. As a result, there is a need for interventions targeting the range of tobacco available to military trainees during a teachable moment when they report intentions to remain tobacco free. The current study shows that a BTI has promise in reducing long-term tobacco use, when coupled with additional interventions, such as a booster session or a media campaign.

Seasonal fluctuations in weight and self-weighing behavior among adults in a behavioral weight loss intervention.

PURPOSE: The current study aimed to observe potential seasonal fluctuations in weight and self-weighing behavior among a diverse sample of adults engaged in a behavioral weight loss intervention. METHODS: Active duty personnel (N = 248) were randomized to either a counselor-initiated or self-paced 12-month behavioral weight loss intervention promoting daily self-weighing. Body weight and self-weighing frequency were collected from electronic scales (e-scales) provided at baseline. RESULTS: Overall, participants lost weight from winter to spring (p = 0.02) and gained weight from fall to winter (p < 0.001). No demographic differences in weight changes were observed. Participants self-weighed less frequently during summer compared to spring (p < 0.0001), less in fall compared to summer (p < 0.0001), and less in winter compared to fall (p < 0.0001). In multivariate models, weight change and self-weighing frequency during the previous season, as well as days since randomization and intervention intensity were associated with seasonal weight changes. CONCLUSIONS: This study is the first to observe seasonal fluctuations of weight and self-weighing behavior among adults actively engaged in a weight loss intervention, consistent with research in the general population. Findings highlight the importance of acknowledging seasonal influence within weight loss programs and trials. LEVEL OF EVIDENCE: Level I, randomized controlled trial.