Using Intensive Longitudinal Data Collected via Mobile Phone to Detect Imminent Lapse in Smokers Undergoing a Scheduled Quit Attempt

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.

Associations between morning affect and later-day smoking urges and behavior

OBJECTIVE

Affective experiences are associated with smoking urges and behavior. Few studies have examined the temporal nature of these associations within a day, such as whether positive and negative affect in the morning are associated with smoking urges and behavior later in the day.

METHOD

Participants (N = 63; MAge = 50 years, 48% female; 60% White) were randomized into one of three smoking cessation interventions and answered up to five daily ecological momentary assessments for 28 days during a quit attempt (M = 21.0 days, SD = 7.1). Before analysis, scores for morning positive and negative affect and later-day smoking urges and behavior were calculated.

RESULTS

On days when individuals' morning positive affect was higher than usual, later-day smoking urges tended to be lower than usual. In contrast, on days when individuals' morning negative affect was higher than usual, later-day smoking urges tended to be higher than usual, and smoking was more likely. Further, individuals who had higher characteristic morning positive affect tended to have less intense later-day smoking urges, whereas those who tended to have higher characteristic morning negative affect tended to have more intense later-day smoking urges.

CONCLUSIONS

Morning positive and negative affect were associated with later-day smoking urges, and morning negative affect was related to later-day smoking behavior. Future research should examine whether interventions that boost positive affect on mornings when it is lower than usual and attenuate negative affect on mornings when it is higher than usual, may reduce the intensity of smoking urges and the likelihood of smoking later in the day. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Reducing tobacco and nicotine use among women in treatment for substance use disorder: evaluation of the knit to quit program

INTRODUCTION

Tobacco and nicotine use are prevalent in residential substance use disorder (SUD) treatment programs that serve pregnant and parenting women. This study evaluated a group intervention that integrates knitting instruction, psychoeducation, and social support to improve readiness to quit and reduce tobacco and nicotine use among this population.

METHODS

Clients and staff in four residential SUD treatment programs were assigned to a six-week group intervention or a wait-list control group. Intervention implementation and preliminary effectiveness were assessed using surveys, interviews, and observational measures.

RESULTS

From pre- to post-test, knowledge related to tobacco and nicotine use increased and number of cigarettes smoked per day and nicotine dependence decreased, on average. Additionally, the intervention group reported lower levels of nicotine dependence relative to the control group. Participants described knitting as an enjoyable replacement for smoking and a strategy to regulate stress and emotions.

CONCLUSIONS

Smoking cessation interventions that include knitting are promising and warrant further testing.

Within-person associations between psychological and contextual factors and lapse incidence in smokers attempting to quit: A systematic review and meta-analysis of ecological momentary assessment studies

AIMS

When attempting to stop smoking, discrete smoking events ('lapses') are strongly associated with a return to regular smoking ('relapse'). No study has yet pooled the psychological and contextual antecedents of lapse incidence, captured in ecological momentary assessment (EMA) studies. This systematic review and meta-analysis aimed to synthesize within-person psychological and contextual predictor-lapse associations in smokers attempting to quit.

METHODS

We searched Ovid MEDLINE, Embase, PsycINFO and Web of Science. A narrative synthesis and multi-level, random-effects meta-analyses were conducted, focusing on studies of adult, non-clinical populations attempting to stop smoking, with no restrictions on setting. Outcomes were the association between a psychological (e.g. stress, cravings) or contextual (e.g. cigarette availability) antecedent and smoking lapse incidence; definitions of 'lapse' and 'relapse'; the theoretical underpinning of EMA study designs; and the proportion of studies with pre-registered study protocols/analysis plans and open data.

RESULTS

We included 61 studies, with 19 studies contributing ≥ 1 effect size(s) to the meta-analyses. We found positive relationships between lapse incidence and 'environmental and social cues' [k = 12, odds ratio (OR) = 4.53, 95% confidence interval (CI) = 2.02, 10.16, P = 0.001] and 'cravings' (k = 10, OR = 1.71, 95% CI = 1.34, 2.18, P < 0.001). 'Negative feeling states' was not significantly associated with lapse incidence (k = 16, OR = 1.10, 95% CI = 0.98, 1.24, P = 0.12). In the narrative synthesis, negative relationships with lapse incidence were found for 'behavioural regulation', 'motivation not to smoke' and 'beliefs about capabilities'; positive relationships with lapse incidence were found for 'positive feeling states' and 'positive outcome expectancies'. Although lapse definitions were comparable, relapse definitions varied widely across studies. Few studies explicitly drew upon psychological theory to inform EMA study designs. One of the included studies drew upon Open Science principles.

CONCLUSIONS

In smokers attempting to stop, environmental and social cues and cravings appear to be key within-person antecedents of smoking lapse incidence. Due to low study quality, the confidence in these estimates is reduced.

Classification of Lapses in Smokers Attempting to Stop: A Supervised Machine Learning Approach Using Data From a Popular Smoking Cessation Smartphone App

INTRODUCTION

Smoking lapses after the quit date often lead to full relapse. To inform the development of real time, tailored lapse prevention support, we used observational data from a popular smoking cessation app to develop supervised machine learning algorithms to distinguish lapse from non-lapse reports.

AIMS AND METHODS

We used data from app users with ≥20 unprompted data entries, which included information about craving severity, mood, activity, social context, and lapse incidence. A series of group-level supervised machine learning algorithms (eg, Random Forest, XGBoost) were trained and tested. Their ability to classify lapses for out-of-sample (1) observations and (2) individuals were evaluated. Next, a series of individual-level and hybrid algorithms were trained and tested.

RESULTS

Participants (N = 791) provided 37 002 data entries (7.6% lapses). The best-performing group-level algorithm had an area under the receiver operating characteristic curve (AUC) of 0.969 (95% confidence interval [CI] = 0.961 to 0.978). Its ability to classify lapses for out-of-sample individuals ranged from poor to excellent (AUC = 0.482-1.000). Individual-level algorithms could be constructed for 39/791 participants with sufficient data, with a median AUC of 0.938 (range: 0.518-1.000). Hybrid algorithms could be constructed for 184/791 participants and had a median AUC of 0.825 (range: 0.375-1.000).

CONCLUSIONS

Using unprompted app data appeared feasible for constructing a high-performing group-level lapse classification algorithm but its performance was variable when applied to unseen individuals. Algorithms trained on each individual's dataset, in addition to hybrid algorithms trained on the group plus a proportion of each individual's data, had improved performance but could only be constructed for a minority of participants.

IMPLICATIONS

This study used routinely collected data from a popular smartphone app to train and test a series of supervised machine learning algorithms to distinguish lapse from non-lapse events. Although a high-performing group-level algorithm was developed, it had variable performance when applied to new, unseen individuals. Individual-level and hybrid algorithms had somewhat greater performance but could not be constructed for all participants because of the lack of variability in the outcome measure. Triangulation of results with those from a prompted study design is recommended prior to intervention development, with real-world lapse prediction likely requiring a balance between unprompted and prompted app data.

Socio-economic status moderates within-person associations of risk factors and smoking lapse in daily life

BACKGROUND AND AIMS

Individuals of lower socio-economic status (SES) display a higher prevalence of smoking and have more diffxiculty quitting than higher SES groups. The current study investigates whether the within-person associations of key risk (e.g. stress) and protective (self-efficacy) factors with smoking lapse varies by facets of SES.

DESIGN AND SETTING

Observational study using ecological momentary assessment to collect data for a 28-day period following a smoking quit attempt. Multi-level mixed models (i.e. generalized linear mixed models) examined cross-level interactions between lapse risk and protective factors and indicators of SES on smoking lapse.

PARTICIPANTS

A diverse sample of 330 adult US smokers who completed a larger study examining the effects of race/ethnicity and social/environmental influences on smoking cessation.

MEASUREMENTS

Risk factors included momentary urge, negative affect, stress; protective factors included positive affect, motivation, abstinence self-efficacy; SES measures: baseline measures of income and financial strain; the primary outcome was self-reported lapse.

FINDINGS

Participants provided 43 297 post-quit observations. Mixed models suggested that income and financial strain moderated the effect of some risk factors on smoking lapse. The within-person association of negative [odds ratio (OR) = 0.967, 95% CI= 0.945, 0.990, P < 0.01] and positive affect (OR = 1.023, 95% CI = 1.003, 1.044, P < 0.05) and abstinence self-efficacy (OR = 1.020, 95% CI = 1.003, 1.038, P < 0.05) on lapse varied with financial strain. The within-person association of negative affect (OR = 1.005, 95% CI = 1.002, 1.008, P < 0.01), motivation (OR = 0.995, 95% CI = 0.991, 0.999, P < 0.05) and abstinence self-efficacy (OR = 0.996, 95% CI = 0.993, 0.999, P < 0.01) on lapse varied by income. The positive association of negative affect with lapse was stronger among individuals with higher income and lower financial strain. The negative association between positive affect and abstinence self-efficacy with lapse was stronger among individuals with lower financial strain, and the negative association between motivation and abstinence self-efficacy with lapse was stronger among those with higher income. The data were insensitive to detect statistically significant moderating effects of income and financial strain on the association of urge or stress with lapse.

CONCLUSION

Some risk factors (e.g. momentary negative affect) exert a weaker influence on smoking lapse among lower compared to higher socio-economic status groups.

A three-arm randomized controlled trial using ecological momentary intervention, community health workers, and video feedback at family meals to improve child cardiovascular health: the Family Matters study design

BACKGROUND

Numerous observational studies show associations between family meal frequency and markers of child cardiovascular health including healthful diet quality and lower weight status. Some studies also show the "quality" of family meals, including dietary quality of the food served and the interpersonal atmosphere during meals, is associated with markers of child cardiovascular health. Additionally, prior intervention research indicates that immediate feedback on health behaviors (e.g., ecological momentary intervention (EMI), video feedback) increases the likelihood of behavior change. However, limited studies have tested the combination of these components in a rigorous clinical trial. The main aim of this paper is to describe the Family Matters study design, data collection protocols, measures, intervention components, process evaluation, and analysis plan.

METHODS/DESIGN

The Family Matters intervention utilizes state-of-the-art intervention methods including EMI, video feedback, and home visiting by Community Health Workers (CHWs) to examine whether increasing the quantity (i.e., frequency) and quality of family meals (i.e., diet quality, interpersonal atmosphere) improves child cardiovascular health. Family Matters is an individual randomized controlled trial that tests combinations of the above factors across three study Arms: (1) EMI; (2) EMI + Virtual Home Visiting with CHW + Video Feedback; and (3) EMI + Hybrid Home Visiting with CHW + Video Feedback. The intervention will be carried out across 6 months with children ages 5-10 (n = 525) with increased risk for cardiovascular disease (i.e., BMI ≥ 75%ile) from low income and racially/ethnically diverse households and their families. Data collection will occur at baseline, post-intervention, and 6 months post-intervention. Primary outcomes include child weight, diet quality, and neck circumference.

DISCUSSION

This study will be the first to our knowledge to use multiple innovative methods simultaneously including ecological momentary intervention, video feedback, and home visiting with CHWs within the novel intervention context of family meals to evaluate which combination of intervention components are most effective in improving child cardiovascular health. The Family Matters intervention has high potential public health impact as it aims to change clinical practice by creating a new model of care for child cardiovascular health in primary care.

TRIAL REGISTRATION

This trial is registered in clinicaltrials.gov (Trial ID: NCT02669797). Date recorded 5/02/22.

Daily adherence to nicotine replacement therapy in low-income smokers: The role of gender, negative mood, motivation, and self-efficacy

BACKGROUND

Low-income smokers may benefit from interventions promoting nicotine replacement therapies (NRTs), particularly for women, as women have worse smoking cessation outcomes than men. Little is known about factors that affect daily NRT adherence, such as negative mood, motivation, and self-efficacy, and whether gender moderates these associations.

METHODS

Secondary analysis of a randomized controlled trial comparing a novel, in session sampling of short-acting combination NRT intervention (In Vivo) to standard care smoking cessation behavioral counseling was performed. Low-income smokers (n = 62; Mage = 47.4; 42 % female; 61 % non-White) completed daily surveys using the Insight™ mHealth platform for 55 consecutive days. Three types of NRT adherence were examined: dose amount of short-acting NRT, nicotine patch wear time, and combination NRT (cNRT) (combined nicotine patch and short-acting NRT).

RESULTS

Generalized multilevel models report same-day negative mood was associated with greater likelihood of nicotine patch adherence in men, but unrelated to women's nicotine patch adherence. Same-day negative mood was associated with greater likelihood of cNRT adherence in men, but less likelihood in women. The relationship between same-day motivation and use of short-acting NRT varied by gender, but simple slope analyses revealed that motivation was unrelated to short-acting NRT use within either group. Same-day self-efficacy was related to an increased likelihood of nicotine patch adherence and cNRT adherence in women but unrelated to men's adherence of either type.

CONCLUSIONS

Future research should focus on gender differences in low-income smokers' same-day negative mood, motivation, and self-efficacy processes on NRT adherence during smoking cessation interventions.

The effect of alcohol use on smoking cessation: A systematic review

Only a small minority of all attempts to stop smoking are successful, especially among smokers who are heavy drinkers and those with an alcohol use disorder. The current systematic review focuses on the negative effects of alcohol use, either before or during attempts to quit smoking, on the success rate of these attempt(s) in alcohol-drinking tobacco smokers. We conducted a systematic review of naturalistic and experimental studies, which included at least 40 tobacco smokers with a recorded drinking status (non-drinking, heavy drinking, alcohol use disorder) and a clearly documented change in alcohol consumption. We could not conduct a meta-analysis and, thus, used consistency across studies to draw conclusions. The evidence presented here shows that alcohol use is associated with lower rates of success in quitting smoking in 20 out of 27 studies. This includes both lapses and relapses. Similarly, in 19 out of 20 long-term follow-up studies, the duration of smoking abstinence was shorter among persons with higher alcohol consumption. Finally, 12 out of 13 experimental studies showed that exposure of smokers to alcohol cues or to drinking of alcohol induce a strong propensity to smoke. It is, therefore, recommended for smokers who drink alcohol and who intend to quit smoking to use an integrated approach, i.e., to stop or substantially reduce their alcohol consumption before and/or during their attempt to quit smoking.

A Smartphone-Based Intervention for Anxiety and Depression in Racially and Ethnically Diverse Adults (EASE): Protocol for a Randomized Controlled Trial

BACKGROUND

Clear health disparities have emerged in the rates of COVID-19 exposure, hospitalization, and death among Black, Hispanic, and American Indian (BHAI) individuals, relative to non-Hispanic White (NHW) individuals. BHAI populations have been disproportionately affected by lower behavioral health access and heightened negative mental health outcomes during the pandemic.

OBJECTIVE

This project directly addresses health disparities in access to behavioral health care during the COVID-19 pandemic among BHAI populations via an adaptation of the established, initially validated, low-cost, mobile app Easing Anxiety Sensitivity for Everyone (EASE) among individuals with symptoms of elevated anxiety or depression or both.

METHODS

The EASE trial is a 2-arm, prospective, randomized, blinded-assessor study with intention-to-treat analysis. Participants (N=800; n=200, 25%, Black; n=200, 25%, Hispanic; n=200, 25%, American Indian; and n=200, 25%, NHW) are randomized to receive either EASE or an active comparison condition for anxiety and depression. Participants compete an online prescreener, an enrollment call to provide informed consent, a baseline survey, a 6-month intervention period, and 3- and 6-month postbaseline assessments. Select participants also complete a 3- and 6-month postbaseline qualitative interview via phone or an online platform (eg, Zoom). Participants complete 2 scheduled daily ecological momentary assessments (EMAs) during the 6-month study period. These twice-daily EMAs guide a just-in-time approach to immediate, personalized behavioral health care.

RESULTS

Outcomes include reductions in anxiety and depressive symptoms and functional impairment at 3 and 6 months postrandomization. We also will examine putative mechanisms (eg, anxiety sensitivity [AS] and COVID-19-specific stress and fear) of the intervention effects. Further, as treatment effects may differ across sociocultural factors, perceived discrimination, social support, and socioeconomic status (SES) will be evaluated as potential moderators of treatment effects on the primary outcomes. Process evaluation using data collected during the study, as well as individual interviews with participants, will complement quantitative data.

CONCLUSIONS

Data from this efficacy trial will determine whether EASE successfully improves symptoms of anxiety and depression and whether these improvements outperform an active comparison control app. If successful, findings from this study have the potential to decrease anxiety and depression symptoms among vulnerable populations determined to be most at risk of exacerbated, long-lasting negative health sequelae. Data from this study may be used to support an implementation and dissemination trial of EASE within real-world behavioral health and social service settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05074693; https://clinicaltrials.gov/ct2/show/NCT05074693.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/40713.

Psychosocial factors influencing smoking relapse among youth experiencing homelessness: A qualitative study

OBJECTIVES

In the United States, up to 70% of youth experiencing homelessness smoke cigarettes. Many are interested in quitting; however, little is known about psychosocial factors influencing smoking relapse in this population. This study, part of a larger project to develop an optimized smoking cessation intervention for youth experiencing homelessness, aimed to describe how psychosocial factors influence smoking relapse in this group.

METHODS

This study describes the smoking relapse experiences of 26 youth tobacco users, aged 14-24 years, who were recruited from a homeless drop-in center in Ohio. We conducted semi-structured interviews to understand how stress, opportunity, and coping contribute to smoking relapse.

RESULTS

Five themes emerged from the data: (1) smoking as a lapse in emotional self-regulation in response to stress; (2) smoking as active emotional self-regulation in response to stress; (3) social opportunities facilitate smoking in the context of emotion-focused stress coping; (4) problem-focused stress coping; and (5) opportunity facilitates smoking relapse.

CONCLUSIONS

Stress was a primary driver of smoking relapse among youth experiencing homelessness, yet social and environmental opportunities to smoke also precipitated relapse. Interventions to improve abstinence among this population should target foundational stressors, coping skills, social supports, and nicotine dependence.

Technology-mediated just-in-time adaptive interventions (JITAIs) to reduce harmful substance use: a systematic review

BACKGROUND AND AIMS

Lapse risk when trying to stop or reduce harmful substance use is idiosyncratic, dynamic and multi-factorial. Just-in-time adaptive interventions (JITAIs) aim to deliver tailored support at moments of need or opportunity. We aimed to synthesize evidence on decision points, tailoring variables, intervention options, decision rules, study designs, user engagement and effectiveness of technology-mediated JITAIs for reducing harmful substance use.

METHODS

Systematic review of empirical studies of any design with a narrative synthesis. We searched Ovid MEDLINE, Embase, PsycINFO, Web of Science, the ACM Digital Library, the IEEE Digital Library, ClinicalTrials.gov, the ISRCTN register and dblp using terms related to substance use/mHealth/JITAIs. Outcomes were user engagement and intervention effectiveness. Study quality was assessed with the mHealth Evidence Reporting and Assessment checklist.

FINDINGS

We included 17 reports of 14 unique studies, including two randomized controlled trials. JITAIs targeted alcohol (S = 7, n = 120 520), tobacco (S = 4, n = 187), cannabis (S = 2, n = 97) and a combination of alcohol and illicit substance use (S = 1, n = 63), and primarily relied on active measurement and static (i.e. time-invariant) decision rules to deliver support tailored to micro-scale changes in mood or urges. Two studies used data from prior participants and four drew upon theory to devise decision rules. Engagement with available JITAIs was moderate-to-high and evidence of effectiveness was mixed. Due to substantial heterogeneity in study designs and outcome variables assessed, no meta-analysis was performed. Many studies reported insufficient detail on JITAI infrastructure, content, development costs and data security.

CONCLUSIONS

Current implementations of just-in-time adaptive interventions (JITAIs) for reducing harmful substance use rely on active measurement and static decision rules to deliver support tailored to micro-scale changes in mood or urges. Studies on JITAI effectiveness are lacking.

Quit Stage and Intervention Type Differences in the Momentary Within-Person Association Between Negative Affect and Smoking Urges

Background

Smoking urges and negative affect play important roles in daily cigarette smoking and smoking lapse during a cessation attempt. Traditionally, laboratory research has considered negative affect as a potential cause of smoking urges. A deeper understanding of momentary associations between negative affect and smoking urges during a smoking cessation attempt can inform treatment development efforts. This study examined whether the within-person association between negative affect and smoking urges differed before and after a quit attempt, and by intervention type.

Methods

Data are from a pilot randomized controlled trial comparing 3 smoking cessation interventions. Participants were randomly assigned to: (1) a novel, smartphone-based just-in-time adaptive intervention that tailored treatment content in real-time (Smart-T2; n = 24), (2) the National Cancer Institute QuitGuide app (n = 25), or (3) a clinic-based tobacco cessation program (TTRP; n = 23) that followed Clinical Practice Guidelines. All participants received up to 12 weeks of nicotine replacement therapy and completed up to 5 assessments per day (M PreQuit = 25.8 assessments, SD = 6.0; M PostQuit = 107.7 assessments, SD = 37.1) of their negative affect and smoking urges during the 7 days (M = 6.6 days, SD = 1.0) prior to their quit-date and the 29 days (M = 25.8 days, SD = 6.4) after their quit-date. Prior to analysis, repeated measures of smoking urges were decomposed into between-person and within-person components.

Results

After accounting for baseline nicotine dependence, Bayesian multilevel models indicated that the extent of within-person association between negative affect and smoking urges was stronger in the post-quit stage of the intervention than the pre-quit stage. Results also indicated that in the post-quit stage of the intervention, the within-person association between negative affect and smoking urges was weaker for those in the Smart-T2 and TTRP groups compared with those in the QuitGuide group. The extent of this within-person association did not differ between those in the Smart-T2 and TTRP groups.

Conclusions

These findings offer preliminary evidence that the momentary within-person association between negative affect and smoking urges increases following a quit attempt, and that the TTRP and Smart-T2 interventions may weaken this association. Research is needed to replicate and expand upon current findings in a fully powered randomized controlled trial.

Clinical Trial Registration

ClinicalTrials.gov NCT02930200; https://clinicaltrials.gov/show/NCT02930200.

New Directions for Motivational Incentive Interventions for Smoking Cessation

Background

Motivational incentive interventions are highly effective for smoking cessation. Yet, these interventions are not widely available to people who want to quit smoking, in part, due to barriers such as administrative burden, concern about the use of extrinsic reinforcement (i.e., incentives) to improve cessation outcomes, suboptimal intervention engagement, individual burden, and up-front costs.

Purpose

Technological advancements can mitigate some of these barriers. For example, mobile abstinence monitoring and digital, automated incentive delivery have the potential to lower the clinic burden associated with monitoring abstinence and administering incentives while also reducing the frequency of clinic visits. However, to fully realize the potential of digital technologies to deliver motivational incentives it is critical to develop strategies to mitigate longstanding concerns that reliance on extrinsic monetary reinforcement may hamper internal motivation for cessation, improve individual engagement with the intervention, and address scalability limitations due to the up-front cost of monetary incentives. Herein, we describe the state of digitally-delivered motivational incentives. We then build on existing principles for creating just-in-time adaptive interventions to highlight new directions in leveraging digital technology to improve the effectiveness and scalability of motivational incentive interventions.

Conclusions

Technological advancement in abstinence monitoring coupled with digital delivery of reinforcers has made the use of motivational incentives for smoking cessation increasingly feasible. We propose future directions for a new era of motivational incentive interventions that leverage technology to integrate monetary and non-monetary incentives in a way that addresses the changing needs of individuals as they unfold in real-time.

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, M_age  = 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.

The mobile assistance for regulating smoking (MARS) micro-randomized trial design protocol

Smoking is the leading preventable cause of death and disability in the U.S. Empirical evidence suggests that engaging in evidence-based self-regulatory strategies (e.g., behavioral substitution, mindful attention) can improve smokers' ability to resist craving and build self-regulatory skills. However, poor engagement represents a major barrier to maximizing the impact of self-regulatory strategies. This paper describes the protocol for Mobile Assistance for Regulating Smoking (MARS) - a research study designed to inform the development of a mobile health (mHealth) intervention for promoting real-time, real-world engagement in evidence-based self-regulatory strategies. The study will employ a 10-day Micro-Randomized Trial (MRT) enrolling 112 smokers attempting to quit. Utilizing a mobile smoking cessation app, the MRT will randomize each individual multiple times per day to either: (a) no intervention prompt; (b) a prompt recommending brief (low effort) cognitive and/or behavioral self-regulatory strategies; or (c) a prompt recommending more effortful cognitive or mindfulness-based strategies. Prompts will be delivered via push notifications from the MARS mobile app. The goal is to investigate whether, what type of, and under what conditions prompting the individual to engage in self-regulatory strategies increases engagement. The results will build the empirical foundation necessary to develop a mHealth intervention that effectively utilizes intensive longitudinal self-report and sensor-based assessments of emotions, context and other factors to engage an individual in the type of self-regulatory activity that would be most beneficial given their real-time, real-world circumstances. This type of mHealth intervention holds enormous potential to expand the reach and impact of smoking cessation treatments.

Efficacy of a Just-in-Time Adaptive Intervention to Promote HIV Risk Reduction Behaviors Among Young Adults Experiencing Homelessness: Pilot Randomized Controlled Trial

BACKGROUND

People experiencing homelessness have higher rates of HIV than those who are stably housed. Mental health needs, substance use problems, and issues unique to homelessness such as lack of shelter and transiency need to be considered with regard to HIV prevention. To date, HIV prevention interventions for young adults experiencing homelessness have not specifically addressed modifiable real-time factors such as stress, sexual or drug use urge, or substance use, or been delivered at the time of heightened risk. Real-time, personalized HIV prevention messages may reduce HIV risk behaviors.

OBJECTIVE

This pilot study tested the initial efficacy of an innovative, smartphone-based, just-in-time adaptive intervention that assessed predictors of HIV risk behaviors in real time and automatically provided behavioral feedback and goal attainment information.

METHODS

A randomized attention control design was used among young adults experiencing homelessness, aged 18-25 years, recruited from shelters and drop-in centers in May 2019. Participants were randomized to either a control or an intervention group. The intervention (called MY-RID [Motivating Youth to Reduce Infection and Disconnection]) consisted of brief messages delivered via smartphone over 6 weeks in response to preidentified predictors that were assessed using ecological momentary assessments. Bayesian hierarchical regression models were used to assess intervention effects on sexual activity, drug use, alcohol use, and their corresponding urges.

RESULTS

Participants (N=97) were predominantly youth (mean age 21.2, SD 2.1 years) who identified as heterosexual (n=51, 52%), male (n=56, 57%), and African American (n=56, 57%). Reports of sexual activity, drug use, alcohol use, stress, and all urges (ie, sexual, drug, alcohol) reduced over time in both groups. Daily drug use reduced by a factor of 13.8 times over 6 weeks in the intervention group relative to the control group (Multimedia Appendix 4). Lower urges for sex were found in the intervention group relative to the control group over the duration of the study. Finally, there was a statistically significant reduction in reports of feeling stressed the day before between the intervention and control conditions (P=.03).

CONCLUSIONS

Findings indicate promising intervention effects on drug use, stress, and urges for sex in a hard-to-reach, high-risk population. The MY-RID intervention should be further tested in a larger randomized controlled trial to further investigate its efficacy and impact on sexual risk behaviors.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03911024; https://clinicaltrials.gov/ct2/show/NCT03911024.

Are Machine Learning Methods the Future for Smoking Cessation Apps?

Smoking cessation apps provide efficient, low-cost and accessible support to smokers who are trying to quit smoking. This article focuses on how up-to-date machine learning algorithms, combined with the improvement of mobile phone technology, can enhance our understanding of smoking behaviour and support the development of advanced smoking cessation apps. In particular, we focus on the pros and cons of existing approaches that have been used in the design of smoking cessation apps to date, highlighting the need to improve the performance of these apps by minimizing reliance on self-reporting of environmental conditions (e.g., location), craving status and/or smoking events as a method of data collection. Lastly, we propose that making use of more advanced machine learning methods while enabling the processing of information about the user’s circumstances in real time is likely to result in dramatic improvement in our understanding of smoking behaviour, while also increasing the effectiveness and ease-of-use of smoking cessation apps, by enabling the provision of timely, targeted and personalised intervention.

Perceived discrimination and smoking lapse among Mexican Americans: An ecological momentary assessment study

OBJECTIVE

Racial/ethnic minorities face unique stressors, including perceived discrimination (PD), that may increase the difficulty of quitting smoking relative to the general population of smokers. The current study examines the impact of acute PD on smoking lapse during a quit attempt, as well as potential mechanisms linking PD to lapse among Spanish-speaking Mexican Americans.

METHOD

Participants (N = 169) were Spanish-speaking Mexican Americans living in the United States who completed ecological momentary assessments (EMAs) multiple times per day for 21 days postquit. A multilevel structural equation model decomposed the effect of PD on smoking lapse into indirect effects through negative affect, positive affect, smoking urge, motivation to quit, and self-efficacy.

RESULTS

Results indicated that PD operated indirectly through negative affect, positive affect, and urge to smoke, above and beyond other mechanisms, to increase risk for smoking lapse.

CONCLUSIONS

Findings have direct implications for intervention development among this population, including the potential for developing strategies to buffer the impact of PD, as well as skills to directly manage increased negative affect and urge to smoke. Just-in-time adaptive interventions (JITAIs) might be particularly useful, given they are designed to deliver treatment in real-time (e.g., delivery of strategies to build resilience and implement coping strategies) that could counter the impact of PD on smoking lapse. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Using machine learning to identify predictors of imminent drinking and create tailored messages for at-risk drinkers experiencing homelessness

Adults experiencing homelessness are more likely to have an alcohol use disorder compared to adults in the general population. Although shelter-based treatments are common, completion rates tend to be poor, suggesting a need for more effective approaches that are tailored to this understudied and underserved population. One barrier to developing more effective treatments is the limited knowledge of the triggers of alcohol use among homeless adults. This paper describes the use of ecological momentary assessment (EMA) to identify predictors of “imminent drinking” (i.e., drinking within the next 4 h), among a sample of adults experiencing homelessness and receiving health services at a homeless shelter. A total of 78 mostly male (84.6%) adults experiencing homelessness (mean age = 46.6) who reported hazardous drinking completed up to five EMAs per day over 4 weeks (a total of 4557 completed EMAs). The study used machine learning techniques to create a drinking risk algorithm that predicted 82% of imminent drinking episodes within 4 h of the first drink of the day, and correctly identified 76% of nondrinking episodes. The algorithm included the following 7 predictors of imminent drinking: urge to drink, having alcohol easily available, feeling confident that alcohol would improve mood, feeling depressed, lower commitment to being alcohol free, not interacting with someone drinking alcohol, and being indoors. The research team used the results to develop intervention content (e.g., brief tailored messages) that will be delivered when imminent drinking is detected in an upcoming intervention phase. Specifically, we created three theoretically grounded message tracks focused on urge/craving, social/availability, and negative affect/mood, which are further tailored to a participant’s current drinking goal (i.e., stay sober, drink less, no goal) to support positive change. To our knowledge, this is the first study to develop tailored intervention messages based on likelihood of imminent drinking, current drinking triggers, and drinking goals among adults experiencing homelessness.

Perceived Impacts, Acceptability, and Recommendations for Ecological Momentary Assessment Among Youth Experiencing Homelessness: Qualitative Study

BACKGROUND

The use of ecological momentary assessment (EMA) to study youth experiencing homelessness (YEH) behaviors is an emerging area of research. Despite high rates of participation and potential clinical utility, few studies have investigated the acceptability and recommendations for EMA from the YEH perspective.

OBJECTIVE

This study aimed to describe the perceived benefits, usability, acceptability, and barriers to the use of EMA from the homeless youth perspective.

METHODS

YEH were recruited from a larger EMA study. Semistructured exit interviews were performed using an interview guide that focused on the YEH experience with the EMA app, and included perceived barriers and recommendations for future studies. Data analyses used an inductive approach with thematic analysis to identify major themes and subthemes.

RESULTS

A total of 18 YEH aged 19-24 years participated in individual and group exit interviews. The EMA was highly acceptable to YEH and they found the app and EMA surveys easy to navigate. Perceived benefits included increased behavioral and emotional awareness with some YEH reporting a decrease in their high-risk behaviors as a result of participation. Another significant perceived benefit was the ability to use the phones for social support and make connections to family, friends, and potential employers. Barriers were primarily survey and technology related. Survey-related barriers included the redundancy of questions, the lack of customizable responses, and the timing of survey prompts. Technology-related barriers included the "freezing" of the app, battery charge, and connectivity issues. Recommendations for future studies included the need to provide real-time mental health support for symptomatic youth, to create individually customized questions, and to test the use of personalized motivational messages that respond to the EMA data in real time.

CONCLUSIONS

YEH are highly receptive to the use of EMA in studies. Further studies are warranted to understand the impact of EMA on YEH behaviors. Incorporating the YEH perspective into the design and implementation of EMA studies may help minimize barriers, increase acceptability, and improve participation rates in this hard-to-reach, disconnected population.

A time-varying model of the dynamics of smoking lapse

OBJECTIVE

The majority of smokers who make a quit attempt experience their first lapse within the first week of quitting, yet limited research to date has examined how the strength and direction of the relationship between smoking risk factors and lapse may change over longer periods of time. Time-varying effect modeling (TVEM) was used to address this gap.

METHOD

A diverse sample (N = 325) of adult smokers completed ecological momentary assessments of risk factors for lapse for 28 days after quitting. TVEM was used to examine the relationship between risk factors (abstinence self-efficacy, positive affect, positive coping expectancies, smoking expectancies, motivation, negative affect, stress, and urge) and lapse for 28 days postquit.

RESULTS

Some associations were stable (e.g., negative affect, motivation), whereas others varied over time. Abstinence self-efficacy, positive affect, and positive coping expectancies were most strongly associated with lapse between Days 3 and 8 postquit. The association of urge with lapse was strongest between Days 4 and 10, as well as near the end of the quit attempt. Stress was also most strongly associated with lapse near the beginning and end of the postquit period and was the only predictor associated with lapse on quit date. The strength of the association between smoking expectancies and lapse increased over time.

CONCLUSION

There may be periods during a quit attempt when certain risk factors are more strongly related to lapse. This work has relevance for tailoring interventions designed to deliver intervention components in particular contexts or times of need. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Reducing Drinking Among People Experiencing Homelessness: Protocol for the Development and Testing of a Just-in-Time Adaptive Intervention

Background

Adults who are homeless are more likely to have alcohol use disorders (AUDs) compared with domiciled adults. Although AUD treatments are commonly available, many factors (eg, transportation limitations and inability to schedule appointments) contribute to low treatment completion rates and low success rates of these interventions among adults experiencing homelessness. Most adults who are homeless own mobile phones; however, no interventions have been developed that use mobile devices to deliver and support AUD interventions for this population. Mobile phone–based AUD interventions may reduce barriers that have limited the use and utility of traditional interventions.

Objective

The aim of this study is to (1) identify variables (eg, affect, stress, geolocation, and cravings) that predict drinking among homeless adults (phase I), (2) develop a mobile intervention that utilizes an algorithm to identify moments of risk for drinking and deliver treatment messages that are tailored to the individual’s current needs in real time (phase II), and (3) pilot test the intervention app (phase III).

Methods

In phase I, adults experiencing homelessness with an AUD (N=80) will complete baseline, equipment, 2-week, and 4-week follow-up visits in person. Participants will be prompted to complete five daily ecological momentary assessments on a study-provided smartphone for 28 days. The smartphone app will collect GPS coordinates every 5 min for the entire 28-day study period. Participants will wear a transdermal alcohol sensor that will objectively measure alcohol use. In phase II, we will use phase I data to develop an algorithm that identifies moments of heightened risk for drinking and develop treatment messages that address risk factors for drinking. Phase III will pilot test the intervention in 40 adults experiencing homelessness with AUD.

Results

This project was funded in June 2018. IRB approval was obtained in October 2018, and data collection for phase I began in February 2019. Phase III data collection is expected to conclude in 2020. To date, 80 participants have consented to the study, and data analysis for phase I will begin in early 2020.

Conclusions

This research will highlight intervention targets and develop a novel intervention for understudied and underserved adults experiencing homelessness with AUD.

International Registered Report Identifier (IRRID)

DERR1-10.2196/15610

Level of Alcohol Consumption and Successful Smoking Cessation

INTRODUCTION

The negative association between heavy alcohol use and likelihood of successful smoking cessation is well established. However, evidence on the effects of moderate alcohol consumption on smoking cessation is sparse. This analysis evaluated the association between alcohol use and smoking and the interaction of alcohol use and use of pharmacotherapy interventions in relation to smoking cessation.

METHODS

Data from adults (n = 923) recruited through a smoking cessation website between November 2011 and March 2012 were analyzed. Data on past-year alcohol use, tobacco use, and demographics were collected at baseline. Self-reported smoking abstinence and current alcohol use data were collected at 1 and 7 months posttreatment. Chi-square and multivariate logistic regression analyses were conducted.

RESULTS

At 1 month, adjusted odds of continued smoking were 1.54 times greater (95% confidence interval [CI] = 1.05% to 2.23%) for moderate drinkers and 2.59 times greater (95% CI = 1.33% to 4.28%) for heavy drinkers than nondrinkers. At 7 months, adjusted odds of continued smoking were not greater for moderate drinkers than nondrinkers, and were 2.32 times greater (95% CI = 1.35% to 3.96%) among heavy alcohol drinkers than nondrinkers. At 1 month, adjusted odds of smoking cessation were 2.33 times greater (95% CI = 1.04% to 3.09%) for alcohol users assigned to nicotine replacement therapy than for those not assigned to nicotine replacement therapy. This relationship was not observed at 7 months.

CONCLUSIONS

Moderate and heavy drinking might impact smoking cessation efforts. Recent moderate drinking may be associated with short-term continued smoking and heavy drinking associated with relapse in the short and long term.

IMPLICATIONS

This study suggests that moderate drinking may influence the process to quit smoking. Further study is needed to better understand the implications of moderate drinking for smoking cessation. Providing information alone may not be effective in helping people abstain from drinking during smoking cessation, especially if moderate drinkers do not perceive their behavior as reducing their chance for a successful quit attempt. Tailoring smoking cessation interventions to include strategies to reduce moderate-to-heavy alcohol consumption may improve smoking cessation outcomes among alcohol users attempting to quit smoking.

Socioeconomic status, mindfulness, and momentary associations between stress and smoking lapse during a quit attempt

BACKGROUND

Models of health disparities highlight stress among low socioeconomic status (SES) smokers as a barrier to cessation. Recent studies suggest that mindfulness may improve cessation outcomes by reducing stress during a quit attempt. The current study examined associations of SES and mindfulness with ecological momentary assessments (EMAs) of stress and smoking lapse during a quit attempt.

METHODS

EMAs (N = 32,329) were gathered from 364 smokers engaged in a quit attempt. A multilevel structural equation model estimated within person paths from momentary stress to subsequent smoking lapse. Between person paths estimated paths from a latent variable for SES and mindfulness to stress and smoking lapse, the indirect effect of SES and mindfulness on lapse through stress, and moderation of within person stress-lapse associations by SES and mindfulness.

RESULTS

Within person estimates found that momentary increases in stress predicted increased risk of subsequent smoking lapse. Between person estimates found that lower SES was indirectly associated with greater risk for smoking lapse through increased stress; and, higher mindfulness was indirectly associated with lower risk for smoking lapse through reduced stress. Additionally, higher SES participants, who reported lower stress during the quit attempt, showed a stronger relationship between momentary increases in stress and risk for subsequent smoking lapse.

CONCLUSIONS

Among low SES smokers engaged in a quit attempt, both SES and mindfulness uniquely influenced smoking lapse through their influence on stress. Findings support reports that mindfulness presents a promising intervention target to reduce stress and improve cessation outcomes among low SES smokers.

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

Prediction of stress and drug craving ninety minutes in the future with passively collected GPS data

Just-in-time adaptive interventions (JITAIs), typically smartphone apps, learn to deliver therapeutic content when users need it. The challenge is to "push" content at algorithmically chosen moments without making users trigger it with effortful input. We trained a randomForest algorithm to predict heroin craving, cocaine craving, or stress (reported via smartphone app 3x/day) 90 min into the future, using 16 weeks of field data from 189 outpatients being treated for opioid-use disorder. We used only one form of continuous input (along with person-level demographic data), collected passively: an indicator of environmental exposures along the past 5 h of movement, as assessed by GPS. Our models achieved excellent overall accuracy-as high as 0.93 by the end of 16 weeks of tailoring-but this was driven mostly by correct predictions of absence. For predictions of presence, "believability" (positive predictive value, PPV) usually peaked in the high 0.70s toward the end of the 16 weeks. When the prediction target was more rare, PPV was lower. Our findings complement those of other investigators who use machine learning with more broadly based "digital phenotyping" inputs to predict or detect mental and behavioral events. When target events are comparatively subtle, like stress or drug craving, accurate detection or prediction probably needs effortful input from users, not passive monitoring alone. We discuss ways in which accuracy is difficult to achieve or even assess, and warn that high overall accuracy (including high specificity) can mask the abundance of false alarms that low PPV reveals.

Towards a Smart Smoking Cessation App: A 1D-CNN Model Predicting Smoking Events

Nicotine consumption is considered a major health problem, where many of those who wish to quit smoking relapse. The problem is that overtime smoking as behaviour is changing into a habit, in which it is connected to internal (e.g., nicotine level, craving) and external (action, time, location) triggers. Smoking cessation apps have proved their efficiency to support smoking who wish to quit smoking. However, still, these applications suffer from several drawbacks, where they are highly relying on the user to initiate the intervention by submitting the factor the causes the urge to smoke. This research describes the creation of a combined Control Theory and deep learning model that can learn the smoker’s daily routine and predict smoking events. The model’s structure combines a Control Theory model of smoking with a 1D-CNN classifier to adapt to individual differences between smokers and predict smoking events based on motion and geolocation values collected using a mobile device. Data were collected from 5 participants in the UK, and analysed and tested on 3 different machine learning model (SVM, Decision tree, and 1D-CNN), 1D-CNN has proved it’s efficiency over the three methods with average overall accuracy 86.6%. The average MSE of forecasting the nicotine level was (0.04) in the weekdays, and (0.03) in the weekends. The model has proved its ability to predict the smoking event accurately when the participant is well engaged with the app.

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.

Evaluating the influences of social support and smoking cues on daily smoking abstinence among socioeconomically disadvantaged adults

INTRODUCTION

Perceived social support and smoking cues, such as cigarette availability, are important factors that affect smoking cessation outcomes. However, very few studies examine the influences of social support and smoking cues on lapse during a quit attempt.

METHODS

Socioeconomically disadvantaged smokers participating in a smoking cessation program at a safety net hospital completed smartphone-based ecological momentary assessments (EMAs) for two consecutive weeks (1-week pre-quit through 1-week post-quit). A mixed-effects logistic regression model was used to evaluate whether perceived support to quit smoking, perceived pressure to quit smoking, and situational cues (i.e., being offered a cigarette) were related to the likelihood of reporting smoking cigarettes on any EMA within a day.

RESULTS

Perceived social pressure and support to quit were not related to daily smoking status. Participants were more likely to smoke on days when they were offered a cigarette compared to days when no such event occurred (OR = 3.31 [95% CI = 1.21, 9.06]). This effect was also significant after adjusting for perceived social pressure to quit and support to quit (OR = 3.38 [95% CI = 1.23, 9.31]).

CONCLUSION

The results suggest that being offered a cigarette negatively impacts smoking cessation. The results reinforce the need for including cigarette refusal skills in smoking cessation treatment to reduce the likelihood of smoking lapse among socioeconomically disadvantaged adults.

Mobilizing Breast Cancer Prevention Research Through Smartphone Apps: A Systematic Review of the Literature

Background: Breast cancer rates have been increasing worldwide, particularly among young women, suggesting important interactions between genes and health behaviors. At the same time, mobile technology, including smartphones applications (apps), has emerged as a new tool for delivering healthcare and health-related services. As of 2018, there were nearly 600 publicly available breast cancer apps designed to provide disease and treatment information, to manage disease, and to raise overall awareness. However, the extent to which apps are incorporated into breast cancer prevention research is unknown. Therefore, the objective of this review was to determine how mobile applications are being used for breast cancer prevention among women across the cancer control continuum. Methods: Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched PubMed and Web of Science Core Collection databases using the keywords breast cancer, smartphone, mobile application, and phone app. Full-length journal articles available in English that addressed the research question were included. We categorized articles by prevention type (primary, secondary, and tertiary) and phase of research (protocol, development, feasibility, pilot, measurement, and effectiveness), and identified common themes and gaps. Results: Our search yielded 82 studies (69 unique) that used apps in breast cancer prevention research across 20 countries. Approximately half of the named apps were publicly available. The majority (73%) of studies targeted tertiary prevention; 15% targeted secondary and 13% targeted primary prevention. Apps were used across all phases of research with the predominant phase being feasibility in tertiary prevention (34%), effectiveness in secondary prevention (63%), and development (30%) and effectiveness (30%) in primary prevention. Common uses included assessing outcomes relevant to clinical care coordination, quality of life, increasing self-efficacy and screening behaviors, and tracking and managing health behaviors. Conclusions: We identified the following gaps: few effectiveness studies in tertiary prevention, minimal use of apps for breast cancer etiology or early detection, and few interventions in those at average risk of breast cancer. These findings suggest that while mobile apps can inform breast cancer prevention across the continuum, more work is needed to incorporate apps into primary prevention.

Profound alteration in reward processing due to a human polymorphism in CHRNA5: a role in alcohol dependence and feeding behavior

Human genetic variation in the nicotinic receptor gene cluster CHRNA5/A3/B4, in particular the non-synonymous and frequent CHRNA5 variant rs16969968 (α5SNP), has an important consequence on smoking behavior in humans. A number of genetic association studies have additionally implicated the CHRNA5 gene in addictions to other drugs, and also body mass index (BMI). Here, we model the α5SNP, in a transgenic rat line, and establish its role in alcohol dependence, and feeding behavior. Rats expressing the α5SNP consume more alcohol, and exhibit increased relapse to alcohol seeking after abstinence. This high-relapsing phenotype is reflected in altered activity in the insula, linked to interoception, as established using c-Fos immunostaining. Similarly, relapse to food seeking is increased in the transgenic group, while a nicotine treatment reduces relapse in both transgenic and control rats. These findings point to a general role of this human polymorphism in reward processing, and multiple addictions other than smoking. This could pave the way for the use of medication targeting the nicotinic receptor in the treatment of alcohol use and eating disorders, and comorbid conditions in smokers.

Momentary precipitants connecting stress and smoking lapse during a quit attempt

OBJECTIVE

Most attempts at smoking cessation are unsuccessful, and stress is frequently characterized both as a momentary precipitant of smoking lapse and a predictor of subsequent changes in other key precipitants of lapse. The current study examined longitudinal associations among stress, multiple precipitants of lapse, and lapse among smokers attempting to quit.

METHOD

Ecological momentary assessments (EMAs) were gathered from a multiethnic, gender-balanced sample of 370 adults enrolled in a smoking cessation program. EMAs (N = 32,563) assessed smoking lapse and precipitants of lapse, including stress, negative affect, smoking urge, abstinence self-efficacy, motivation to quit, difficulty concentrating, coping outcome expectancies, and smoking outcome expectancies. A multilevel structural equation model simultaneously estimated within-subject paths from stress to multiple precipitants and subsequent smoking lapse. Indirect effects of stress to smoking lapse through precipitants were computed.

RESULTS

Results indicated that increased stress was significantly associated with all precipitants of lapse, consistent with a greater risk for lapse (i.e., increased negative affect, smoking urge, difficulty concentrating, and smoking outcome expectancies and reduced abstinence self-efficacy, motivation to quit, and coping outcome expectancies). All precipitants were significantly associated with subsequent lapse. Indirect effects indicated that stress was uniquely connected to lapse through negative affect, smoking urge, abstinence self-efficacy, coping outcome expectancies, and smoking outcome expectancies.

CONCLUSIONS

Results of this study highlight the broad importance of stress for smoking lapse during a quit attempt. Smoking cessation programs should pay close attention to the role of stress in exacerbating key precipitants of lapse to improve cessation success rates. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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.

Characterizing ENDS use in young adults with ecological momentary assessment: Results from a pilot study

INTRODUCTION

Ecological Momentary Assessment (EMA) allows for assessment of electronic nicotine delivery systems (ENDS) use in real-time. This EMA study aimed to 1) describe study participation rates; 2) evaluate the concordance of EMA and survey items measuring frequency and quantity of ENDS use; and 3) assess the relationships between EMA items measuring frequency and quantity of ENDS use with ENDS dependence, measured at baseline and with saliva cotinine collected at follow-up.

METHODS

Fifty young adult ENDS users completed baseline surveys, EMAs (i.e., random, event-based, daily diaries), and follow-up questionnaires over a 14-day period. Spearman correlations were conducted to determine concordance of survey items. Linear regression models assessed the relationships between EMA ENDS use characteristics (e.g., puffs, number of days used, quantity of e-liquid) with dependence items at baseline and saliva cotinine at follow-up.

RESULTS

Overall completion for the prompted EMAs (random and daily diaries) was 68%. Correlations between EMA measures assessing ENDS use ranged from weak (ρ = -0.02; NS) to strong (ρ = 0.69, p < .001); EMA to follow-up items ranged from weak (ρ = 0.16; p < .05) to moderate (ρ = 0.54; p < .001). Significant associations were found between ENDS use measured via random and daily diary EMAs and saliva cotinine at follow-up after controlling for cigarette smoking (B = 0.70-1.76; p < .01), but not for event-based EMAs. Items measuring frequency/quantity of use from random EMAs were consistently associated with ENDS dependence at baseline (B = 0.74-1.58; p < .01).

CONCLUSION

EMA represents a promising methodology to capture real-time ENDS use behaviors, primarily through daily diary and random EMAs.

Identifying Behaviors Predicting Early Morning Emotions by Observing Permanent Supportive Housing Residents: An Ecological Momentary Assessment

BACKGROUND

Behavior and emotions are closely intertwined. The relationship between behavior and emotions might be particularly important in populations of underserved people, such as people with physical or mental health issues. We used ecological momentary assessment (EMA) to examine the relationship between emotional state and other characteristics among people with a history of chronic homelessness who were participating in a health coaching program.

OBJECTIVE

The goal of this study was to identify relationships between daily emotional states (valence and arousal) shortly after waking and behavioral variables such as physical activity, diet, social interaction, medication compliance, and tobacco usage the prior day, controlling for demographic characteristics.

METHODS

Participants in m.chat, a technology-assisted health coaching program, were recruited from housing agencies in Fort Worth, Texas, United States. All participants had a history of chronic homelessness and reported at least one mental health condition. We asked a subset of participants to complete daily EMAs of emotions and other behaviors. From the circumplex model of affect, the EMA included 9 questions related to the current emotional state of the participant (happy, frustrated, sad, worried, restless, excited, calm, bored, and sluggish). The responses were used to calculate two composite scores for valence and arousal.

RESULTS

Nonwhites reported higher scores for both valence and arousal, but not at a statistically significant level after correcting for multiple testing. Among momentary predictors, greater time spent in one-on-one interactions, greater time spent in physical activities, a greater number of servings of fruits and vegetables, greater time spent interacting in a one-on-one setting as well as adherence to prescribed medication the previous day were generally associated with higher scores for both valence and arousal, and statistical significance was achieved in most cases. Number of cigarettes smoked the previous day was generally associated with lower scores on both valence and arousal, although statistical significance was achieved for valence only when correcting for multiple testing.

CONCLUSIONS

This study provides an important glimpse into factors that predict morning emotions among people with mental health issues and a history of chronic homelessness. Behaviors considered to be positive (eg, physical activity and consumption of fruits and vegetables) generally enhanced positive affect and restrained negative affect the following morning. The opposite was true for behaviors such as smoking, which are considered to be negative.

Before and after: craving, mood, and background stress in the hours surrounding drug use and stressful events in patients with opioid-use disorder

RATIONALE

Ecological momentary assessment (EMA) of specific events usually focuses more on antecedents and concomitants than on aftermaths.

OBJECTIVES

To examine mental state both before and after discrete episodes of stress and drug use.

METHODS

For up to 16 weeks, outpatients on opioid-agonist treatment carried smartphones on which they initiated entries for stressful events (SEs) or lapses to drug use (DUs), and thrice daily when randomly prompted (RPs). Participants rated their stress, opioid craving, cocaine craving, and moods. RP entries within 5 h of an event were analyzed and compared to other RPs.

RESULTS

Stress, negative mood, and craving were generally higher before and after DUs and SEs compared to background levels in participants with at least one DU (n = 149) or SE (n = 158). Before DUs, there were increases in negative mood, opioid craving, and cocaine craving, but not background stress. Before SEs, there were increases in background stress, opioid craving, and cocaine craving, but not negative mood. These changes were more variable after events than before. Neither DUs nor SEs were significantly related to positive mood.

CONCLUSIONS

Stress increased before stressful-event entries, but was less evident before drug use. Craving increased in the hours before drug use and stressful events-and remained elevated in the hours after either event. These results suggest a stronger link between drug use and craving than between drug use and stress. Lapses to drug use did not improve mood or reduce stress, at least not at our 1-h-bin time resolution, suggesting that if such benefits exist, they are brief.

Using mHealth to Increase Treatment Utilization Among Recently Incarcerated Homeless Adults (Link2Care): Protocol for a Randomized Controlled Trial

Background

There is a significant revolving door of incarceration among homeless adults. Homeless adults who receive professional coordination of individualized care (ie, case management) during the period following their release from jail experience fewer mental health and substance use problems, are more likely to obtain stable housing, and are less likely to be reincarcerated. This is because case managers work to meet the various needs of their clients by helping them to overcome barriers to needed services (eg, food, clothing, housing, job training, substance abuse and mental health treatment, medical care, medication, social support, proof of identification, and legal aid). Many barriers (eg, limited transportation, inability to schedule appointments, and limited knowledge of available services) prevent homeless adults who were recently released from incarceration from obtaining available case management, crisis management, substance abuse, and mental health services.

Objective

The aim of the Link2Care study is to assess the effectiveness of a smartphone app for increasing case management and treatment service utilization, and in turn reduce homelessness and rearrest. The goals of this research are to (1) assess the impact of an innovative smartphone app that will prompt and directly link recently incarcerated homeless adults to community-based case management services and resources and (2) utilize in-person and smartphone-based assessments to identify key variables (eg, alcohol or drug use, social support, psychological distress, and quality of life) that predict continued homelessness and rearrest.

Methods

Homeless adults (N=432) who enroll in a shelter-based Homeless Recovery Program after release from the Dallas County Jail will be randomly assigned to one of the three treatment groups: (1) usual case management, (2) usual case management plus smartphone, and (3) usual case management with a study-provided smartphone that is preloaded with an innovative case management app (smartphone-based case management). Those assigned to smartphone-based case management will receive smartphones that prompt (twice weekly) connections to shelter-based case managers. The app will also offer direct links to case managers (available during normal business hours) and crisis interventionists (available 24 hours a day, 7 days a week) with the touch of a button.

Results

Recruitment began in the spring of 2018, and data collection will conclude in 2021.

Conclusions

This research represents an important step toward integrated service connection and health care service provision for one of the most underserved, high need, and understudied populations in the United States.

Trial Registration

ClinicalTrials.gov NCT03399500; https://clinicaltrials.gov/ct2/show/NCT03399500 (Archived by WebCite at http://www.webcitation.org/6zSJwdgUS)

Registered Report Identifier

RR1-10.2196/9868

An ecological momentary intervention for smoking cessation: The associations of just-in-time, tailored messages with lapse risk factors

BACKGROUND

Smartphone apps can provide real-time, tailored interventions for smoking cessation. The current study examines the effectiveness of a smartphone-based smoking cessation application that assessed risk for imminent smoking lapse multiple times per day and provided messages tailored to current smoking lapse risk and specific lapse triggers.

METHODS

Participants (N=59) recruited from a safety-net hospital smoking cessation clinic completed phone-based ecological momentary assessments (EMAs) 5 times/day for 3 consecutive weeks (1week pre-quit, 2weeks post-quit). Risk for smoking lapse was estimated in real-time using a novel weighted lapse risk estimator. With each EMA, participants received messages tailored to current level of risk for imminent smoking lapse and self-reported presence of smoking urge, stress, cigarette availability, and motivation to quit. Generalized linear mixed model analyses determined whether messages tailored to specific lapse risk factors were associated with greater reductions in these triggers than messages not tailored to specific triggers.

RESULTS

Overall, messages tailored to smoking urge, cigarette availability, or stress corresponded with greater reductions in those triggers than messages that were not tailored to specific triggers (p's=0.02 to <0.001). Although messages tailored to stress were associated with greater reductions in stress than messages not tailored to stress, the association was non-significant (p=0.892) when only moments of high stress were included in the analysis.

CONCLUSIONS

Mobile technology can be used to conduct real-time smoking lapse risk assessment and provide tailored treatment content. Findings provide initial evidence that tailored content may impact users' urge to smoke, stress, and cigarette availability.

Effects of smoking and paroxetine on stress-induced craving and withdrawal symptoms

Background

When smokers relapse, many cite stressful circumstances as the cause. Most smoking cessation medications do not prevent stress induced increases in craving and withdrawal symptom severity; however the effect of smoking prior to stress exposure on symptom severity is unclear.

Methods

We examined how smoking a cigarette immediately prior to a stressful task affects craving and withdrawal symptom severity by analyzing data from a double-blind, crossover study assessing paroxetine's effects on the physiological response to the combination of stress and smoking. Measures were obtained prior to and following smoking / stress exposure and following a subsequent 30 minute period at two laboratory sessions (i.e., after one month each of paroxetine and placebo).

Results

Among study completers (n=63), severity of craving decreased from the beginning of the session to immediately following the smoking / stress exposure (p<0.01) and severity of smoking urges decreased from the beginning to the end of the laboratory session (p<0.001). Withdrawal symptoms were less severe while taking paroxetine vs. placebo (p<0.05) but no treatment x time effects were observed.

Conclusions

Additional research is needed to identify interventions that could similarly decrease stress induced craving in order to determine if smoking cessation rates can be increased.

Real Time Assessment of Young Adults' Attitudes toward Tobacco Messages

Objectives

We used ecological momentary assessment (EMA) to examine young adults' attitudes towards pro-tobacco messages encountered in real time and their association with intentions to use tobacco.

Methods

Young adults (N = 92, ages 18-29) recorded sightings of marketing or social media related to tobacco in real time via mobile app for 28 days. Participants reported message characteristics, their attitudes towards the message, and intentions to use the depicted product for each submission. We used generalized linear mixed models to examine factors related to attitude towards message and intentions to use tobacco.

Results

Messages depicting e-cigarettes (p < .001) or hookah (p < .05) were associated with significantly more favorable attitudes compared with traditional cigarettes. Positive attitude towards the message was significantly associated with intention to use the depicted product (p < .001). Messages depicting e-cigarettes and hookah were significantly associated with higher intention to use. Message source was not significantly related to attitudes towards the message or product use intentions.

Conclusions

Marketing featuring e-cigarettes and hookah is an important target for future regulation. Given that pro-tobacco and e-cigarette messages are prevalent online, future research should consider the Internet and social media as important venues for counter-marketing and intervention efforts.

MapMySmoke: feasibility of a new quit cigarette smoking mobile phone application using integrated geo-positioning technology, and motivational messaging within a primary care setting

Background

Approximately 11,000 people die in Scotland each year as a result of smoking-related causes. Quitting smoking is relatively easy; maintaining a quit attempt is a very difficult task with success rates for unaided quit attempts stubbornly remaining in the single digits. Pharmaceutical treatment can improve these rates by lowering the overall reward factor of nicotine. However, these and related nicotine replacement therapies do not operate on, or address, the spatial and contextual aspects of smoking behaviour. With the ubiquity of smartphones that can log spatial, quantitative and qualitative data related to smoking behaviour, there exists a person-centred clinical opportunity to support smokers attempting to quit by first understanding their smoking behaviour and subsequently sending them dynamic messages to encourage health behaviour change within a situational context.

Methods

We have built a smartphone app—MapMySmoke—that works on Android and iOS platforms. The deployment of this app within a clinical National Health Service (NHS) setting has two distinct phases: (1) a 2-week logging phase where pre-quit patients log all of their smoking and craving events; and (2) a post-quit phase where users receive dynamic support messages and can continue to log craving events, and should they occur, relapse events. Following the initial logging phase, patients consult with their general practitioner (GP) or healthcare provider to review their smoking patterns and to outline a precise, individualised quit attempt plan. Our feasibility study consists of assessment of an initial app version during and after use by eight patients recruited from an NHS Fife GP practice. In addition to evaluation of the app as a potential smoking cessation aid, we have assessed the user experience, technological requirements and security of the data flow.

Results

In an initial feasibility study, we have deployed the app for a small number of patients within one GP practice in NHS Fife. We recruited eight patients within one surgery, four of whom actively logged information about their smoking behaviour. Initial feedback was very positive, and users indicated a willingness to log their craving and smoking events. In addition, two out of three patients who completed follow-up interviews noted that the app helped them reduce the number of cigarettes they smoked per day, while the third indicated that it had helped them quit. The study highlighted the use of pushed notifications as a potential technology for maintaining quit attempts, and the security of collection of data was audited. These initial results influenced the design of a planned second larger study, comprised of 100 patients, the primary objectives of which are to use statistical modelling to identify times and places of probable switches into smoking states, and to target these times with dynamic health behaviour messaging.

Conclusions

While the health benefits of quitting smoking are unequivocal, such behaviour change is very difficult to achieve. Many factors are likely to contribute to maintaining smoking behaviour, yet the precise role of cues derived from the spatial environment remains unclear. The rise of smartphones, therefore, allows clinicians the opportunity to better understand the spatial aspects of smoking behaviour and affords them the opportunity to push targeted individualised health support messages at vulnerable times and places.

Trial registration

ClinicalTrial.gov, NCT02932917.

An Ecological Momentary Intervention for Smoking Cessation: Evaluation of Feasibility and Effectiveness

BACKGROUND

Despite substantial public health progress in reducing the prevalence of smoking in the United States overall, smoking among socioeconomically disadvantaged adults remains high.

OBJECTIVE

To determine the feasibility and preliminary effectiveness of a novel smartphone-based smoking cessation app designed for socioeconomically disadvantaged smokers.

METHODS

Participants were recruited from a safety-net hospital smoking cessation clinic in Dallas, Texas, and were followed for 13 weeks. All participants received standard smoking cessation clinic care (ie, group counseling and cessation pharmacotherapy) and a smartphone with a novel smoking cessation app (ie, Smart-T). The Smart-T app prompted 5 daily ecological momentary assessments (EMAs) for 3 weeks (ie, 1 week before cessation and 2 weeks after cessation). During the precessation period, EMAs were followed by messages that focused on planning and preparing for the quit attempt. During the postcessation period, participant responses to EMAs drove an algorithm that tailored messages to the current level of smoking lapse risk and currently present lapse triggers (eg, urge to smoke, stress). Smart-T offered additional intervention features on demand (eg, one-click access to the tobacco cessation quitline; "Quit Tips" on coping with urges to smoke, mood, and stress).

RESULTS

Participants (N=59) were 52.0 (SD 7.0) years old, 54% (32/59) female, and 53% (31/59) African American, and 70% (40/57) had annual household income less than US $16,000. Participants smoked 20.3 (SD 11.6) cigarettes per day and had been smoking for 31.6 (SD 10.9) years. Twelve weeks after the scheduled quit date, 20% (12/59) of all participants were biochemically confirmed abstinent. Participants responded to 87% of all prompted EMAs and received approximately 102 treatment messages over the 3-week EMA period. Most participants (83%, 49/59) used the on-demand app features. Individuals with greater nicotine dependence and minority race used the Quit Tips feature more than their counterparts. Greater use of the Quit Tips feature was linked to nonabstinence at the 2 (P=.02), 4 (P<.01), and 12 (P=.03) week follow-up visits. Most participants reported that they actually used or implemented the tailored app-generated messages and suggestions (83%, 49/59); the app-generated messages were helpful (97%, 57/59); they would like to use the app in the future if they were to lapse (97%, 57/59); and they would like to refer friends who smoke to use the Smart-T app (85%, 50/59). A minority of participants (15%, 9/59) reported that the number of daily assessments (ie, 5) was "too high."

CONCLUSIONS

This novel just-in-time adaptive intervention delivered an intensive intervention (ie, 102 messages over a 3-week period), was well-liked, and was perceived as helpful and useful by socioeconomically disadvantaged adults who were seeking smoking cessation treatment. Smartphone apps may be used to increase treatment exposure and may ultimately reduce tobacco-related health disparities among socioeconomically disadvantaged adults.