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

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.

Statistical methods for predicting e-cigarette use events based on beat-to-beat interval (BBI) data collected from wearable devices

The prevalence of e-cigarette use among young adults in the USA is high (14%). Although the majority of users plan to quit vaping, the motivation to make a quit attempt is low and available support during a quit attempt is limited. Using wearable sensors to collect physiological data (eg, heart rate) holds promise for capturing the right timing to deliver intervention messages. This study aims to fill the current knowledge gap by proposing statistical methods to (1) de-noise beat-to-beat interval (BBI) data from smartwatches worn by 12 young adult regular e-cigarette users for 7 days; and (2) summarize the de-noised data by event and control segments. We also conducted a comprehensive review of conventional methods for summarizing heart rate variability (HRV) and compared their performance with the proposed method. The results show that the proposed singular spectrum analysis (SSA) can effectively de-noise the highly variable BBI data, as well as quantify the proportion of total variation extracted. Compared to existing HRV methods, the proposed second order polynomial model yields the highest area under the curve (AUC) value of 0.76 and offers better interpretability. The findings also indicate that the average heart rate before vaping is higher and there is an increasing trend in the heart rate before the vaping event. Importantly, the development of increasing heart rate observed in this study implies that there may be time to intervene as this physiological signal emerges. This finding, if replicated in a larger scale study, may inform optimal timings for delivering messages in future intervention.

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

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

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).

An Integrated mHealth App for Smoking Cessation in Black Smokers With HIV: Protocol for a Randomized Controlled Trial

BACKGROUND

Black adults who smoke and have HIV experience immense stressors (eg, racial discrimination and HIV stigma) that impede smoking cessation success and perpetuate smoking-related health disparities. These stressors also place Black adults who smoke and have HIV at an increased risk of elevated interoceptive stress (eg, anxiety and uncomfortable bodily sensations) and smoking to manage symptoms. In turn, this population is more likely to smoke to manage interoceptive stress, which contributes to worse HIV-related outcomes in this group. However, no specialized treatment exists to address smoking cessation, interoceptive stress, and HIV management for Black smokers with HIV.

OBJECTIVE

This study aims to test a culturally adapted and novel mobile intervention that targets combustible cigarette smoking, HIV treatment engagement and adherence, and anxiety sensitivity (a proxy for difficulty and responsivity to interoceptive stress) among Black smokers with HIV (ie, Mobile Anxiety Sensitivity Program for Smoking and HIV [MASP+]). Various culturally tailored components of the app are being evaluated for their ability to help users quit smoking, manage physiological stress, and improve health care management.

METHODS

This study is a pilot randomized controlled trial in which Black combustible cigarette smokers with HIV (N=72) are being recruited and randomly assigned to use either (1) the National Cancer Institute's QuitGuide app or (2) MASP+. Study procedures include a web-based prescreener; active intervention period for 6 weeks; smartphone-based assessments, including daily app-based ecological momentary assessments for 6 weeks (4 ecological momentary assessments each day); a video-based qualitative interview using Zoom Video Communications software at week 6 for participants in all study conditions; and smartphone-based follow-up assessments at 0, 1, 2 (quit date), 3, 4, 5, 6, and 28 weeks postbaseline (26 weeks postquitting date).

RESULTS

Primary outcomes include biochemically verified 7-day point prevalence of abstinence, HIV-related quality of life, use of antiretroviral therapy, and HIV care appointment adherence at 26 weeks postquitting date. Qualitative data are also being collected and assessed to obtain feedback that will guide further tailoring of app content and evaluation of efficacy.

CONCLUSIONS

The results of this study will determine whether the MASP+ app serves as a successful aid for combustible cigarette smoking cessation, HIV treatment engagement, and physiological stress outcomes among Black people with HIV infection. If successful, this study will provide evidence for the efficacy of a new means of addressing major mental and physical health difficulties for this high-risk population. If the results are promising, the data from this study will be used to update and tailor the MASP+ app for testing in a fully powered randomized controlled trial that will evaluate its efficacy in real-world behavioral health and social service settings.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05709002; https://clinicaltrials.gov/study/NCT05709002.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/52090.

Variances in Smoking Expectancies Predict Moment-to-Moment Smoking Behaviors in Everyday Life

BACKGROUND

Many policy decisions about tobacco control are predicated on rational choice models, which posit (1) that smokers are aware of the risks of cigarettes and (2) that perceived risks have a consistent influence on continued smoking behavior. However, research shows that beliefs about smoking may be vulnerable to changes in internal and external contexts.

METHODS

Using ecological momentary assessment, we tested this by measuring how smokers' (N = 52) beliefs about smoking varied over time. Four times per day over 1 week, participants responded to measures of smoking intentions, risk perceptions, mood and social outcome expectancies, and internal and external contextual factors.

RESULTS

We analyzed this data using multilevel modeling, finding that both smoking intentions, risk perceptions, and expectancies differed between participants as well as between moments.

CONCLUSION

Risk perceptions and mood expectancies were a significant predictor of intentions to smoke in the next 30 min, illustrating the importance of these beliefs in decisional processes. This study was preregistered at the Open Science Foundation: https://osf.io/wmv3s/?view_only=71ad66d3ce3845fcb3bf2b9860d820c9 . Our analytic plan was not preregistered.

A smoking cessation smartphone app that delivers real-time 'context aware' behavioural support: the Quit Sense feasibility RCT

Background

During a quit attempt, cues from a smoker's environment are a major cause of brief smoking lapses, which increase the risk of relapse. Quit Sense is a theory-guided Just-In-Time Adaptive Intervention smartphone app, providing smokers with the means to learn about their environmental smoking cues and provides 'in the moment' support to help them manage these during a quit attempt.

Objective

To undertake a feasibility randomised controlled trial to estimate key parameters to inform a definitive randomised controlled trial of Quit Sense.

Design

A parallel, two-arm randomised controlled trial with a qualitative process evaluation and a 'Study Within A Trial' evaluating incentives on attrition. The research team were blind to allocation except for the study statistician, database developers and lead researcher. Participants were not blind to allocation.

Setting

Online with recruitment, enrolment, randomisation and data collection (excluding manual telephone follow-up) automated through the study website.

Participants

Smokers (323 screened, 297 eligible, 209 enrolled) recruited via online adverts on Google search, Facebook and Instagram.

Interventions

Participants were allocated to 'usual care' arm (n = 105; text message referral to the National Health Service SmokeFree website) or 'usual care' plus Quit Sense (n = 104), via a text message invitation to install the Quit Sense app.

Main outcome measures

Follow-up at 6 weeks and 6 months post enrolment was undertaken by automated text messages with an online questionnaire link and, for non-responders, by telephone. Definitive trial progression criteria were met if a priori thresholds were included in or lower than the 95% confidence interval of the estimate. Measures included health economic and outcome data completion rates (progression criterion #1 threshold: ≥ 70%), including biochemical validation rates (progression criterion #2 threshold: ≥ 70%), recruitment costs, app installation (progression criterion #3 threshold: ≥ 70%) and engagement rates (progression criterion #4 threshold: ≥ 60%), biochemically verified 6-month abstinence and hypothesised mechanisms of action and participant views of the app (qualitative).

Results

Self-reported smoking outcome completion rates were 77% (95% confidence interval 71% to 82%) and health economic data (resource use and quality of life) 70% (95% CI 64% to 77%) at 6 months. Return rate of viable saliva samples for abstinence verification was 39% (95% CI 24% to 54%). The per-participant recruitment cost was £19.20, which included advert (£5.82) and running costs (£13.38). In the Quit Sense arm, 75% (95% CI 67% to 83%; 78/104) installed the app and, of these, 100% set a quit date within the app and 51% engaged with it for more than 1 week. The rate of 6-month biochemically verified sustained abstinence, which we anticipated would be used as a primary outcome in a future study, was 11.5% (12/104) in the Quit Sense arm and 2.9% (3/105) in the usual care arm (estimated effect size: adjusted odds ratio = 4.57, 95% CIs 1.23 to 16.94). There was no evidence of between-arm differences in hypothesised mechanisms of action. Three out of four progression criteria were met. The Study Within A Trial analysis found a £20 versus £10 incentive did not significantly increase follow-up rates though reduced the need for manual follow-up and increased response speed. The process evaluation identified several potential pathways to abstinence for Quit Sense, factors which led to disengagement with the app, and app improvement suggestions.

Limitations

Biochemical validation rates were lower than anticipated and imbalanced between arms. COVID-19-related restrictions likely limited opportunities for Quit Sense to provide location tailored support.

Conclusions

The trial design and procedures demonstrated feasibility and evidence was generated supporting the efficacy potential of Quit Sense.

Future work

Progression to a definitive trial is warranted providing improved biochemical validation rates.

Trial registration

This trial is registered as ISRCTN12326962.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 17/92/31) and is published in full in Public Health Research; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Automated, tailored adaptive mobile messaging to reduce alcohol consumption in help-seeking adults: A randomized controlled trial

AIMS

To test differential outcomes between three 6-month text-messaging interventions to reduce at-risk drinking in help-seeking adults.

DESIGN

A three-arm single-blind randomized controlled trial with 1-, 3-, 6- and 12-month follow-ups.

SETTING

United States. A fully remote trial without human contact, with participants recruited primarily via social media outlets.

PARTICIPANTS

Seven hundred and twenty-three adults (mean = 39.9 years, standard deviation = 10.0; 62.5% female) seeking to reduce their drinking were allocated to 6 months of baseline 'tailored statically' messaging (TS; n = 240), 'tailored adaptive' messaging (TA; n = 239) or 'drink tracking' messaging (DT; n = 244).

INTERVENTIONS

TS consisted of daily text messages to reduce harmful drinking that were tailored to demographics and alcohol use. TA consisted of daily, tailored text messages that were also adapted based on goal achievement and proactive prompts. DT consisted of a weekly assessment for self-reported drinking over the past 7 days.

MEASUREMENTS

The primary outcome measure was weekly sum of standard drinks (SSD) at 6-month follow-up. Secondary outcome measures included drinks per drinking day (DDD), number of drinking days (NDD) per week and heavy drinking days (HDD) at 1-, 3-, 6- and 12-month follow-ups.

FINDINGS

At 6 months, compared with DT, TA resulted in significant SSD reductions of 16.2 (from 28.7 to 12.5) drinks [adjusted risk ratio (aRR) = 0.80, 95% confidence interval (CI) = 0.71, 0.91] using intent-to-treat analysis. TA also resulted in significant improvements in DDD (aRR = 0.84; 95% CI = 0.77-0.92) and drinking days per week (b = -0.39; 95% CI = -0.67, -0.10), but not HDD compared with DT at 6 months. TA was not significantly different from TS at any time-point, except DDD at 6 months. All groups made improvements in SSD at 12-month follow-up compared with baseline with an average reduction of 12.9 drinks per week across groups.

CONCLUSIONS

Automated tailored mobile messaging interventions are scalable solutions that can reduce weekly alcohol consumption in remote help-seeking drinkers over time.

Sequencing conversational turns in peer interactions: An integrated approach for evidence-based conversational agent for just-in-time nicotine cravings intervention

Background

Risky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions.

Methods

In this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior change techniques (BCTs) and speech act (SA) theory to uncover the socio-behavioral and linguistic context embedded within the online social discourse. Further, we uncovered the sequential patterns of BCTs and SAs from social conversations (n = 339,067). We utilized grounded theory-based techniques for extracting the scenarios that best describe individuals' needs and mapped them into the architecture of the virtual CA.

Results

The frequently occurring sequential patterns for BCTs were comparison of behavior and feedback and monitoring; for SAs were directive and assertion. Five cravings-related scenarios describing users' needs as they deal with nicotine cravings were identified along with the kinds of behavior change constructs that are being elicited within those scenarios.

Conclusions

AI-led virtual CAs focusing on behavior change need to employ data-driven and theory-linked approaches to address issues related to engagement, sustainability, and acceptance. The sequential patterns of theory and intent manifestations need to be considered when developing effective behavior change CAs.

The effectiveness of mobile-based ecological momentary motivational enhancement therapy in reducing craving and severity of cannabis use disorder: Study protocol for a randomized controlled trial

Objective

This study aims to investigate the effectiveness of Ecological Momentary Motivational Enhancement Therapy (EM-MET) in reducing craving and severity of Cannabis Use Disorder (CUD) among young adults.

Methods

This multicenter, single-blinded randomized controlled trial (RCT) will be conducted over a period of 11 weeks. Eighty patients with CUD will be randomly assigned to two equal-sized parallel groups, either the Motivational Enhancement Therapy (MET) group or the EM-MET group. All participants will receive four individual face-to-face sessions of MET (twice a week). The MET group will not receive any other treatments after these sessions; however, in the EM-MET group, the top triggers of patients will be assessed using mobile-based Ecological Momentary Assessment (EMA) five times a day within three weeks (after face-to-face sessions) and they will receive a call from the therapist who provides them with EM-MET (in the form of an emergency telephone helpline) as soon as they report experiencing triggers of cannabis use that are assessed using EMA in their everyday lives. Primary outcomes including CUD severity and the severity of craving will be evaluated using the Leeds Dependence Questionnaire and the Self-efficacy and Temptation Scale, respectively. These assessments will be conducted at pre-treatment, post-treatment, and a six-week follow-up.

Discussion

If proven feasible and effective, the results of this study will offer clinicians an evidence-based treatment approach to address craving and dependency in patients with CUD. Moreover, these patients will receive effective treatment in real time and in real life, when and where it is most needed. However, it is important to consider the limitations of this study, such as the specific population studied in Tehran, Iran, which may affect the generalizability of the results. Nevertheless, the implementation of Ecological Momentary Interventions (EMIs) in real-life settings holds promise for timely and effective treatment.Trial registration: This trial was registered in the Iranian Registry of Clinical Trials on 21 February 2023. Registry No. IRCT20221224056908N1.

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

BACKGROUND

Depression is common among adults who smoke cigarettes. Existing depression-specific cessation interventions have limited reach and are unlikely to improve smoking prevalence rates among this large subgroup of smokers.

OBJECTIVE

This study aimed to determine whether a mobile app-based intervention tailored for depression paired with a mailed sample of nicotine replacement therapy (NRT) is efficacious for treating depression and promoting smoking cessation.

METHODS

A 2-arm nationwide remote randomized clinical trial was conducted in the United States. Adults (N=150) with elevated depressive symptoms (Patient Health Questionnaire-8≥10) who smoked were enrolled. The mobile app ("Goal2Quit") provided behavioral strategies for treating depression and quitting smoking based on Behavioral Activation Treatment for Depression. Goal2Quit participants also received a 2-week sample of combination NRT. Treatment as usual participants received a self-help booklet for quitting smoking that was not tailored for depression. Primary end points included Goal2Quit usability, change in depression (Beck Depression Inventory-II) across 12 weeks, and smoking cessation including reduction in cigarettes per day, incidence of 24-hour quit attempts, floating abstinence, and 7-day point prevalence abstinence (PPA).

RESULTS

In total, 150 participants were enrolled between June 25, 2020, and February 23, 2022, of which 80 were female (53.3%) and the mean age was 38.4 (SD 10.3) years. At baseline, participants on average reported moderate depressive symptoms and smoked a mean of 14.7 (SD 7.5) cigarettes per day. Goal2Quit usability was strong with a mean usability rating on the System Usability Scale of 78.5 (SD 16.9), with 70% scoring above the ≥68 cutoff for above-average usability. Retention data for app use were generally strong immediately following trial enrollment and declined in subsequent weeks. Those who received Goal2Quit and the NRT sample reported lower mean depressive symptoms over the trial duration as compared to treatment as usual (difference of mean 3.72, SE 1.37 points less; P=.01). Across time points, all cessation outcomes favored Goal2Quit. Regarding abstinence, Goal2Quit participants reported significantly higher rates of 7-day PPA at weeks 4 (11% vs 0%; P=.02), 8 (7-day PPA: 12% vs 0%; P=.02), and 12 (16% vs 2%; P=.02).

CONCLUSIONS

A mobile app intervention tailored for depression paired with a sample of NRT was effective for depression treatment and smoking cessation. Findings support the utility of this intervention approach for addressing the currently unmet public health treatment need for tailored, scalable depression-specific cessation treatments.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03837379; https://clinicaltrials.gov/ct2/show/NCT03837379.

Varenicline Combined With Oral Nicotine Replacement Therapy and Smartphone-Based Medication Reminders for Smoking Cessation: Feasibility Randomized Controlled Trial

BACKGROUND

Varenicline and oral nicotine replacement therapy (NRT) have each been shown to increase the likelihood of smoking cessation, but their combination has not been studied. In addition, smoking cessation medication adherence is often poor, thus, challenging the ability to evaluate medication efficacy.

OBJECTIVE

This study examined the effects of combined varenicline and oral NRT and smartphone medication reminders on pharmacotherapy adherence and smoking abstinence among adults enrolled in smoking cessation treatment.

METHODS

A 2×2 factorial design was used. Participants (N=34) were randomized to (1) varenicline + oral NRT (VAR+NRT) or varenicline alone (VAR) and (2) smartphone medication reminder messages (REM) or no reminder messages (NREM) over 13 weeks. Participants assigned to VAR+REM received varenicline reminder prompts, and those assigned to VAR+NRT+REM also received reminders to use oral NRT. The other 2 groups (VAR+NREM and VAR+NRT+NREM) did not receive medication reminders. Participants were not blinded to intervention groups. All participants received tobacco cessation counseling. Smartphone assessments of smoking as well as varenicline and NRT use (if applicable) were prompted daily through the first 12 weeks after a scheduled quit date. Descriptive statistics were generated to characterize the relations between medication and reminder group assignments with daily smoking, daily varenicline adherence, and daily quantity of oral NRT used. Participants completed follow-up assessments for 26 weeks after the quit date.

RESULTS

Participants were predominantly White (71%), and half were female (50%). On average, participants were 54.2 (SD 9.4) years of age, they smoked an average of 19.0 (SD 9.0) cigarettes per day and had smoked for 34.6 (SD 12.7) years. Descriptively, participants assigned to VAR+NRT reported more days of smoking abstinence compared to VAR (29.3 vs 26.3 days). Participants assigned to REM reported more days of smoking abstinence than those assigned to NREM (40.5 vs 21.8 days). Participants assigned to REM were adherent to varenicline on more days compared to those assigned to NREM (58.6 vs 40.5 days), and participants assigned to VAR were adherent to varenicline on more days than those assigned to VAR + NRT (50.7 vs 43.3 days). In the subsample of participants assigned to VAR+NRT, participants assigned to REM reported more days where ≥5 pieces of NRT were used than NREM (14.0 vs 7.4 days). Average overall medication adherence (assessed via the Medication Adherence Questionnaire) showed the same pattern as the daily smartphone-based adherence assessments.

CONCLUSIONS

Preliminary findings indicated that smoking cessation interventions may benefit from incorporating medication reminders and combining varenicline with oral NRT, though combining medications may be associated with poorer adherence. Further study is warranted.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03722966; https://classic.clinicaltrials.gov/ct2/show/NCT03722966.

Ecological momentary interventions for smoking cessation: a systematic review and meta-analysis

BACKGROUND AND OBJECTIVES

Tobacco use is an important cause of preventable mortality and morbidity worldwide. Only 7% of smokers successfully quit annually, despite numerous evidence-based smoking cessation treatments. An important reason for failure is barriers to accessing appropriate smoking cessation interventions, which can be minimized by technology-delivered interventions, such as ecological momentary interventions. Ecological momentary interventions provide the right type and intensity of treatment in real time, based on ecological momentary assessments of relevant variables. The aim of this review was to assess the effectiveness of ecological momentary interventions in smoking cessation.

METHODS

We searched MEDLINE, Scopus, CENTRAL, psychINFO, and ProQuest without applying any filters on 19 September, 2022. One author screened search results for obvious irrelevant and duplicate studies. The remaining studies were independently reviewed by two authors to exclude irrelevant studies, and then they extracted data from the included studies. We collated study findings, transformed data into a common rubric, and calculated a weighted treatment effect across studies using Review Manager 5.

FINDINGS

We analyzed 10 studies with a total of 2391 participants. Assessment methods included exhaled CO analyzers, bidirectional SMS, data input in apps, and hand movement detection. Interventions were based on acceptance and commitment therapy and cognitive behavioral therapy. Smoking abstinence was significantly higher in participants of intervention groups compared to control groups (RR = 1.24; 95% CI 1.07-1.44, P = 0.004; I2 = 0%).

CONCLUSION

Ecological momentary intervention is a novel area of research in behavioral science. The results of this systematic review based on the available literature suggest that these interventions could be beneficial for smoking cessation.

Long-Term Outcomes of a Comprehensive Mobile Smoking Cessation Program With Nicotine Replacement Therapy in Adult Smokers: Pilot Randomized Controlled Trial

BACKGROUND

Increased smartphone ownership has led to the development of mobile smoking cessation programs. Although the related body of evidence, gathered through the conduct of randomized controlled trials (RCTs), has grown in quality and rigor, there is a need for longer-term data to assess associated smoking cessation durability.

OBJECTIVE

The primary aim was to compare smoking cessation outcomes at 52 weeks in adult smokers randomized to a mobile smoking cessation program, Pivot (intervention), versus QuitGuide (control). The secondary aims included comparison of other smoking-related behaviors, outcomes and participant feedback, and exploratory analyses of baseline factors associated with smoking cessation.

METHODS

In this remote pilot RCT, cigarette smokers in the United States were recruited on the web. Participants were offered 12 weeks of free nicotine replacement therapy (NRT). Data were self-reported via a web-based questionnaire with videoconference biovalidation in participants who reported 7-day point-prevalence abstinence (PPA). Outcomes focused on cessation rates with additional assessment of quit attempts, cigarettes per day (CPD), self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire, NRT use, and participant feedback. Cessation outcomes included self-reported 7- and 30-day PPA, abstinence from all tobacco products, and continuous abstinence. PPA and continuous abstinence were biovalidated using witnessed breath carbon monoxide samples. Exploratory post hoc regression analyses were performed to identify baseline variables associated with smoking cessation.

RESULTS

Participants comprised 188 smokers (n=94, 50% in the Pivot group and n=94, 50% in the QuitGuide group; mean age 46.4, SD 9.2 years; n=104, 55.3% women; n=128, 68.1% White individuals; mean CPD 17.6, SD 9.0). Several cessation rates were higher in the Pivot group (intention to treat): self-reported continuous abstinence was 20% (19/94) versus 9% (8/94; P=.03) for QuitGuide, biochemically confirmed abstinence was 31% (29/94) versus 18% (17/94; P=.04) for QuitGuide, and biochemically confirmed continuous abstinence was 19% (18/94) versus 9% (8/94; P=.046) for QuitGuide. More Pivot participants (93/94, 99% vs 80/94, 85% in the QuitGuide group; P<.001) placed NRT orders (mean 3.3, SD 2.0 vs 1.8, SD 1.6 for QuitGuide; P<.001). Pivot participants had increased self-efficacy via the Smoking Abstinence Self-Efficacy Questionnaire (mean point increase 3.2, SD 7.8, P<.001 vs 1.0, SD 8.5, P=.26 for QuitGuide). QuitGuide participants made more mean quit attempts (7.0, SD 6.3 for Pivot vs 9.5, SD 7.5 for QuitGuide; P=.01). Among those who did not achieve abstinence, QuitGuide participants reported greater CPD reduction (mean -34.6%, SD 35.5% for Pivot vs -46.1%, SD 32.3% for QuitGuide; P=.04). Among those who reported abstinence, 90% (35/39) of Pivot participants and 90% (26/29) of QuitGuide participants indicated that their cessation program helped them quit.

CONCLUSIONS

This pilot RCT supports the long-term effectiveness of the Pivot mobile smoking cessation program, with abstinence rates durable to 52 weeks.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04955639; https://clinicaltrials.gov/ct2/show/NCT04955639.

Applying the Just-In-Time Adaptive Intervention Framework to the Development of Gambling Interventions

Just-In-Time Adaptive Interventions (JITAIs) are emerging "push" mHealth interventions that provide the right type, timing, and amount of support to address the dynamically-changing needs for each individual. Although JITAIs are well-suited to the delivery of interventions for the addictions, few are available to support gambling behaviour change. We therefore developed GamblingLess: In-The-Moment and Gambling Habit Hacker, two smartphone-delivered JITAIs that differ with respect to their target populations, theoretical underpinnings, and decision rules. We aim to describe the decisions, methods, and tools we used to design these two treatments, with a view to providing guidance to addiction researchers who wish to develop JITAIs in the future. Specifically, we describe how we applied a comprehensive, organising scientific framework to define the problem, define just-in-time in the context of the identified problem, and formulate the adaptation strategies. While JITAIs appear to be a promising design in addiction intervention science, we describe several key challenges that arose during development, particularly in relation to applying micro-randomised trials to their evaluation, and offer recommendations for future research. Issues including evaluation considerations, integrating on-demand intervention content, intervention optimisation, combining active and passive assessments, incorporating human facilitation, adding cost-effectiveness evaluations, and redevelopment as transdiagnostic interventions are discussed.

Bayesian continuous-time hidden Markov models with covariate selection for intensive longitudinal data with measurement error

Intensive longitudinal data collected with ecological momentary assessment methods capture information on participants' behaviors, feelings, and environment in near real-time. While these methods can reduce recall biases typically present in survey data, they may still suffer from other biases commonly found in self-reported data (e.g., measurement error and social desirability bias). To accommodate potential biases, we develop a Bayesian hidden Markov model to simultaneously identify risk factors for subjects transitioning between discrete latent states as well as risk factors potentially associated with them misreporting their true behaviors. We use simulated data to demonstrate how ignoring potential measurement error can negatively affect variable selection performance and estimation accuracy. We apply our proposed model to smartphone-based ecological momentary assessment data collected within a randomized controlled trial that evaluated the impact of incentivizing abstinence from cigarette smoking among socioeconomically disadvantaged adults. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Effectiveness of eHealth Smoking Cessation Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Rapid advancements in eHealth and mobile health (mHealth) technologies have driven researchers to design and evaluate numerous technology-based interventions to promote smoking cessation. The evolving nature of cessation interventions emphasizes a strong need for knowledge synthesis.

OBJECTIVE

This systematic review and meta-analysis aimed to summarize recent evidence from randomized controlled trials regarding the effectiveness of eHealth-based smoking cessation interventions in promoting abstinence and assess nonabstinence outcome indicators, such as cigarette consumption and user satisfaction, via narrative synthesis.

METHODS

We searched for studies published in English between 2017 and June 30, 2022, in 4 databases: PubMed (including MEDLINE), PsycINFO, Embase, and Cochrane Library. Two independent reviewers performed study screening, data extraction, and quality assessment based on the GRADE (Grading of Recommendations, Assessment, Development, and Evaluations) framework. We pooled comparable studies based on the population, follow-up time, intervention, and control characteristics. Two researchers performed an independent meta-analysis on smoking abstinence using the Sidik-Jonkman random-effects model and log risk ratio (RR) as the effect measurement. For studies not included in the meta-analysis, the outcomes were narratively synthesized.

RESULTS

A total of 464 studies were identified through an initial database search after removing duplicates. Following screening and full-text assessments, we deemed 39 studies (n=37,341 participants) eligible for this review. Of these, 28 studies were shortlisted for meta-analysis. According to the meta-analysis, SMS or app text messaging can significantly increase both short-term (3 months) abstinence (log RR=0.50, 95% CI 0.25-0.75; I2=0.72%) and long-term (6 months) abstinence (log RR=0.77, 95% CI 0.49-1.04; I2=8.65%), relative to minimal cessation support. The frequency of texting did not significantly influence treatment outcomes. mHealth apps may significantly increase abstinence in the short term (log RR=0.76, 95% CI 0.09-1.42; I2=88.02%) but not in the long term (log RR=0.15, 95% CI -0.18 to 0.48; I2=80.06%), in contrast to less intensive cessation support. In addition, personalized or interactive interventions showed a moderate increase in cessation for both the short term (log RR=0.62, 95% CI 0.30-0.94; I2=66.50%) and long term (log RR=0.28, 95% CI 0.04-0.53; I2=73.42%). In contrast, studies without any personalized or interactive features had no significant impact. Finally, the treatment effect was similar between trials that used biochemically verified or self-reported abstinence. Among studies reporting outcomes besides abstinence (n=20), a total of 11 studies reported significantly improved nonabstinence outcomes in cigarette consumption (3/14, 21%) or user satisfaction (8/19, 42%).

CONCLUSIONS

Our review of 39 randomized controlled trials found that recent eHealth interventions might promote smoking cessation, with mHealth being the dominant approach. Despite their success, the effectiveness of such interventions may diminish with time. The design of more personalized interventions could potentially benefit future studies.

TRIAL REGISTRATION

PROSPERO CRD42022347104; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=347104.

From Computation to Clinic

Theory-driven and data-driven computational approaches to psychiatry have enormous potential for elucidating mechanism of disease and providing translational linkages between basic science findings and the clinic. These approaches have already demonstrated utility in providing clinically relevant understanding, primarily via back translation from clinic to computation, revealing how specific disorders or symptoms map onto specific computational processes. Nonetheless, forward translation, from computation to clinic, remains rare. In addition, consensus regarding specific barriers to forward translation-and on the best strategies to overcome these barriers-is limited. This perspective review brings together expert basic and computationally trained researchers and clinicians to 1) identify challenges specific to preclinical model systems and clinical translation of computational models of cognition and affect, and 2) discuss practical approaches to overcoming these challenges. In doing so, we highlight recent evidence for the ability of computational approaches to predict treatment responses in psychiatric disorders and discuss considerations for maximizing the clinical relevance of such models (e.g., via longitudinal testing) and the likelihood of stakeholder adoption (e.g., via cost-effectiveness analyses).

Testing the Outcomes of a Smoking Cessation Smartphone App for Nondaily Smokers: Protocol for a Proof-of-concept Randomized Controlled Trial

BACKGROUND

Nondaily smoking is a widespread, increasingly prevalent pattern of smoking, particularly in ethnic minority and vulnerable populations. To date, no effective treatment approach for this type of smokers has been identified.

OBJECTIVE

This study aims to use a randomized controlled trial to evaluate proof-of-concept markers of the Smiling instead of Smoking (SiS) app, a smoking cessation smartphone app designed specifically for nondaily smokers. This app was developed iteratively and is now in its third version. Previous studies have demonstrated acceptability and feasibility when participants were onboarded in person (study 1) and remotely (study 2) and showed within-person changes in line with hypothesized mechanisms of change. This is the first randomized test of this app.

METHODS

In total, 225 adult nondaily smokers will be asked to undertake a quit attempt while using smoking cessation support materials for a period of 7 weeks. Participants will be randomized to use the SiS smartphone app, the National Cancer Institute smartphone app QuitGuide, or the National Cancer Institute smoking cessation brochure "Clearing the Air." Participants will take part in a 15-minute scripted onboarding phone call during which study staff will introduce participants to their support materials. Survey links will be sent 2, 6, 12, and 24 weeks after the participants' initially chosen quit date. The primary outcome is self-efficacy to remain abstinent from smoking at treatment end, measured using the Smoking Self-Efficacy Questionnaire. Secondary outcomes cover several domains relevant to treatment development and implementation: treatment acceptability (eg, satisfaction with smoking cessation support, measured using the Client Satisfaction Questionnaire, and app usability, measured using the System Usability Scale); treatment feasibility (eg, measured using the number of days participants used the SiS or QuitGuide app during the prescribed treatment period); and, in an exploratory way, treatment efficacy assessed using self-reported 30-day point prevalence abstinence.

RESULTS

Recruitment began in January 2021 and ended June 2022. The final 24-week follow-up was completed in January 2023. This trial is funded by the American Cancer Society.

CONCLUSIONS

This study is designed to test whether the prescribed use of the SiS app results in greater self-efficacy to abstain from smoking in nondaily smokers than commonly recommended alternative treatments and whether the SiS app treatment is acceptable and feasible. Positive results will mean that the SiS app warrants testing in a large-scale randomized controlled trial to test its effectiveness in supporting smoking cessation in nondaily smokers. The design of this study also provides insights into issues pertinent to smoking cessation smartphone app treatment development and implementation by measuring, in a randomized design, markers of treatment satisfaction, engagement with the technology and content of the treatment, and adherence to the treatment plan.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04672239; https://clinicaltrials.gov/ct2/show/NCT04672239.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/40867.

A systematic scoping review of just-in-time, adaptive interventions finds limited automation and incomplete reporting

OBJECTIVES

To describe the degree of automation in just-in-time, adaptive interventions (JITAIs) assessed in randomized controlled trials (RCTs) in any medical specialty, and to assess the completeness of intervention reporting.

STUDY DESIGN AND SETTING

Systematic scoping review-we searched PubMed, PsycINFO, and Web of Science, from 1 January 2019 to 2 March 2021, for reports of RCTs assessing JITAIs. We assessed whether study reports included the minimum information required to replicate the interventions based on JITAI frameworks. We described JITAIs according to their automation level using an established framework (partially, highly, or fully automated), and care workload distribution (requiring work from patients, health care professionals [HCPs], both, or neither).

RESULTS

We included 88 JITAIs (62%, n = 55 supported chronic illness management and 12%, n = 11 supported health behavior change). Overall, 77% (n = 68) of JITAIs were missing some information required to replicate the intervention (e.g., n = 38, 43% inadequately reported the algorithm used to select intervention components). Only fifteen (17%) JITAIs were fully automated and did not require additional work from HCPs nor patients. Of the remaining JITAIs, 36% required work from both patients and HCPs, and 47% required work from either patients or HCPs.

CONCLUSION

Most JITAIs are not fully automated and require work from the HCPs and patients.

A pilot adaptive trial of text messages, mailed nicotine replacement therapy, and telephone coaching among primary care patients who smoke

INTRODUCTION

Sequential multiple assignment randomized trials (SMART) inform the design of adaptive treatment interventions. We tested the feasibility of a SMART to deliver a stepped-care intervention among primary care patients who smoked daily.

METHODS

In a 12-week pilot SMART (NCT04020718), we tested the feasibility of recruiting and retaining (>80 %) participants to an adaptive intervention starting with cessation text messages (SMS). The study randomly assigned participants (R1) to assessment of quit status, the tailoring variable, after either 4 or 8 weeks of SMS. The study offered continued SMS alone to those reporting abstinence. Those reporting smoking were randomized (R2) to SMS + mailed NRT or SMS + NRT + brief telephone coaching.

RESULTS

During Jan-March and July-Aug 2020, we enrolled 35 patients (>18 years) from a primary care network in Massachusetts. Two (6 %) of 31 participants reported seven-day point prevalence abstinence at their tailoring variable assessment. The 29 participants who continued to smoke at 4 or 8 weeks were randomized (R2) to SMS + NRT (n = 16) or SMS + NRT + coaching (n = 13). Thirty of 35 participants (86 %) completed 12-weeks; 13 % (2/15) of those in 4-week group and 27 % (4/15) of those in 8-week group had CO < 6 ppm at 12-weeks (p = 0.65). Among 29 participants in R2, one was lost to follow-up, 19 % (3/16) of the SMS + NRT group had CO < 6 ppm vs. 17 % (2/12) of SMS + NRT + coaching (p = 1.00). Treatment satisfaction was high (93 %, 28 of 30 who completed 12-weeks).

CONCLUSIONS

A SMART exploring a stepped-care adaptive intervention combining SMS, NRT, and coaching for primary care patients was feasible. Retention and satisfaction were high and quit rates were promising.

A Just-In-Time Adaptive intervention (JITAI) for smoking cessation: Feasibility and acceptability findings

Smoking cessation treatments that are easily accessible and deliver intervention content at vulnerable moments (e.g., high negative affect) have great potential to impact tobacco abstinence. The current study examined the feasibility and acceptability of a multi-component Just-In-Time Adaptive Intervention (JITAI) for smoking cessation. Daily smokers interested in quitting were consented to participate in a 6-week cessation study. Visit 1 occurred 4 days pre-quit, Visit 2 was on the quit day, Visit 3 occurred 3 days post-quit, Visit 4 was 10 days post-quit, and Visit 5 was 28 days post-quit. During the first 2 weeks (Visits 1-4), the JITAI delivered brief mindfulness/motivational strategies via smartphone in real-time based on negative affect or smoking behavior detected by wearable sensors. Participants also attended 5 in-person visits, where brief cessation counseling (Visits 1-4) and nicotine replacement therapy (Visits 2-5) were provided. Outcomes were feasibility and acceptability; biochemically-confirmed abstinence was also measured. Participants (N = 43) were 58.1 % female (AgeMean = 49.1, mean cigarettes per day = 15.4). Retention through follow-up was high (83.7 %). For participants with available data (n = 38), 24 (63 %) met the benchmark for sensor wearing, among whom 16 (67 %) completed at least 60 % of strategies. Perceived ease of wearing sensors (Mean = 5.1 out of 6) and treatment satisfaction (Mean = 3.6 out of 4) were high. Biochemically-confirmed abstinence was 34 % at Visit 4 and 21 % at Visit 5. Overall, the feasibility of this novel multi-component intervention for smoking cessation was mixed but acceptability was high. Future studies with improved technology will decrease participant burden and better detect key intervention moments.

Digital interventions for smoking abstinence: a systematic review and meta-analysis of randomized control trials

OBJECTIVES

Technological advancements have improved patients' health and clinical care through digital interventions. This study investigated the effects of digital interventions on smoking abstinence.

METHODS

PubMed, the Cochrane Library, and Scopus were systematically searched from inception until December 2021. Meta-analysis was carried out using a random-effects model. The degree of heterogeneity, quality, and publication bias of the selected studies was further evaluated.

RESULTS

A total of 43 randomized control trial studies were eligible for this study. 38,814 participants from 18 countries were included in the analysis. Digital interventions on seven-day point prevalence abstinence (1 month) showed increased smoking abstinence. The odds ratio was 2.02 and confidence interval (CI) was 1.67-2.43; p < 0.001; I² = 55.1%) . The result for a 30-day point prevalence abstinence (1 month) was 1.63 (CI 1.09-2.46; p = 0.018; I² = 0%). Digital intervention also had a significant effect on continuous abstinence (odds ratio = 1.68; CI 1.29-2.18; p < 0.001; I² = 70.1%) and prolonged abstinence (odds ratio = 1.60; CI 1.19-2.15; p = 0.002; I² = 53.6%). There was evidence of heterogeneity and publication bias.

CONCLUSIONS

Digital interventions led to increased smoking abstinence and can be a valuable tool in smoking cessation. Further research is required to evaluate the long-term impact of digital interventions on outcomes related to smoking cessation.

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.

Smoking prevalence among Asian Americans: Associations with education, acculturation, and gender

There is evidence that smoking prevalence rates are related to acculturation, education, and gender among Asian Americans. However, no studies have examined how smoking rates among Asian Americans vary based on acculturation, education, and gender together. This study used National Health Interview Survey (NHIS) data (2010-2018) to examine cigarette smoking prevalence among Asian American men and women aged 18 and older (N = 14,680). Multivariate logistic regression models were used to estimate associations between educational attainment (i.e., college graduate or higher vs some college or lower), years spent in the United States (U.S.) as a proxy for acculturation (i.e., less than 10 years (less acculturated) vs 10 years or more (more acculturated) vs U.S.-born), and cigarette smoking prevalence across gender controlling for age, marital status, poverty (at/above vs below poverty threshold), country of origin (Chinese vs Filipino vs Asian Indian vs Other Asian), and the survey year. Current smoking prevalence was 9.0 % among all Asian Americans - 5.0 % among women and 13.5 % among men. Among respective gender-specific subgroups, U.S.-born Asian women without a college degree and more acculturated Asian immigrant men without a college degree had the highest odds of smoking (OR: 4.096 [95 % CI: 2.638, 6.360] and 1.462 [95 % CI: 1.197, 1.774], respectively). Findings indicated that less educated U.S.-born Asian women and less educated Asian immigrant men are at greatest risk for smoking. Smoking prevalence among Asian Americans is highly related to acculturation, education, and gender. Findings may inform development of policies and programs that are targeted toward smoking cessation among Asian Americans.

The effectiveness of smartphone application-based interventions for assisting smoking cessation: A systematic review and meta-analysis (Preprint)

BACKGROUND

Smoking is a leading cause of premature death globally. Quitting smoking reduces the risk of all-cause mortality by 11%-34%. Smartphone app-based smoking cessation (SASC) interventions have been developed and are widely used. However, the evidence for the effectiveness of smartphone-based interventions for smoking cessation is currently equivocal.

OBJECTIVE

The purpose of this study was to synthesize the evidence for the effectiveness of smartphone app-based interventions for smoking cessation.

METHODS

We conducted a systematic review and meta-analysis of the effectiveness of smartphone interventions for smoking cessation based on the Cochrane methodology. An electronic literature search was performed using the Cochrane Library, Web of Science, PubMed, Embase, PsycINFO, China National Knowledge Infrastructure, and Wanfang databases to identify published papers in English or Chinese (there was no time limit regarding the publication date). The outcome was the smoking abstinence rate, which was either a 7-day point prevalence abstinence rate or a continuous abstinence rate.

RESULTS

A total of 9 randomized controlled trials involving 12,967 adults were selected for the final analysis. The selected studies from 6 countries (the United States, Spain, France, Switzerland, Canada, and Japan) were included in the meta-analysis between 2018 and 2022. Pooled effect sizes (across all follow-up time points) revealed no difference between the smartphone app group and the comparators (standard care, SMS text messaging intervention, web-based intervention, smoking cessation counseling, or apps as placebos without real function; odds ratio [OR] 1.25, 95% CI 0.99-1.56, P=.06, I²=73.6%). Based on the subanalyses, 6 trials comparing smartphone app interventions to comparator interventions reported no significant differences in effectiveness (OR 1.03, 95% CI 0.85-1.26, P=.74, I²=57.1%). However, the 3 trials that evaluated the combination of smartphone interventions combined with pharmacotherapy compared to pharmacotherapy alone found higher smoking abstinence rates in the combined intervention (OR 1.79, 95% CI 1.38-2.33, P=.74, I²=7.4%). All SASC interventions with higher levels of adherence were significantly more effective (OR 1.48, 95% CI 1.20-1.84, P<.001, I²=24.5%).

CONCLUSIONS

This systematic review and meta-analysis did not support the effectiveness of delivering smartphone-based interventions alone to achieve higher smoking abstinence rates. However, the efficacy of smartphone-based interventions increased when combined with pharmacotherapy-based smoking cessation approaches.

TRIAL REGISTRATION

PROSPERO CRD42021267615; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=267615.

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.

The current evidence for substance use disorder apps

PURPOSE OF REVIEW

New mHealth (smartphone) apps for substance use disorders (SUD) are emerging at an accelerated rate, with consumer choice typically guided by app-store user ratings rather than their effectiveness. The expansive reach, low-cost and accessibility of mHealth apps have driven their popularity and appeal as alternatives to traditional treatment; as such, rigorously establishing their effectiveness is of paramount importance.

RECENT FINDINGS

Several systematic reviews conclude that the evidence-base for mHealth SUD apps is weak, inconclusive and hampered by substantial heterogeneity in study designs. However, there have been a number of interesting and novel developments in this area in recent years, which have not been synthesised to date.

SUMMARY

Most mHealth apps deliver either multiple-component behaviour change techniques, discrete psychological interventions or cognitive training interventions, or are designed to act as adjuncts to facilitate the delivery of clinical or continuing care. There are promising signals of their feasibility, acceptability and preliminary effectiveness in numerous open-label pilot studies of mHealth apps targeting alcohol and smoking. However, only a handful of sufficiently-powered, well-designed randomised controlled trials have been conducted to date with mixed findings. Furthermore, there has been limited recent attention on mHealth apps aiming to improve outcomes for individuals using other drugs.

An Integrated mHealth App for Smoking Cessation in Black Smokers With Anxiety: Protocol for a Randomized Controlled Trial

BACKGROUND

Black smokers have greater difficulty in quitting and higher rates of smoking-related diseases and disabilities than the general population. The smoking disparities experienced by this group are, in part, a consequence of multiple chronic life stressors (eg, racial discrimination) that engender increased exposure to interoceptive stress symptoms (eg, anxiety), which can ultimately lead to smoking as a means of immediate emotion regulation.

OBJECTIVE

This study aimed to culturally adapt and initially test a novel mobile intervention (ie, Mobile Anxiety Sensitivity Program for Smoking [MASP]) that targets anxiety sensitivity (AS; a proxy for difficulty and responsivity to interoceptive stress) among Black smokers. The MASP intervention is culturally informed to address interoceptive stress management difficulties among Black smokers and is thus hypothesized to facilitate smoking cessation.

METHODS

In phase 1, a total of 25 Black smokers with elevated AS will be administered MASP for 6 weeks. Following the completion of phase 1, we will further refine the MASP based on qualitative and quantitative data from participants to produce the final MASP iteration. In phase 2, a total of 200 Black smokers with elevated AS will be enrolled and randomly assigned to receive nicotine replacement therapy and either the smartphone-based National Cancer Institute QuitGuide app for standard mobile smoking cessation treatment or the MASP intervention. All participants in phases 1 and 2 will be enrolled remotely and will complete a web-based study screener; smartphone-based baseline assessment; daily smartphone-based ecological momentary assessments for 6 weeks; phone-based end-of-treatment qualitative interviews; and smartphone-based follow-up assessments at postbaseline weeks 1, 2 (quit date), 3, 4, 5, 6, 28, and 54 (weeks 28 and 54 follow-ups will be completed by phase 2 participants only). The MASP intervention is intended to offset barriers to treatment and encourage treatment engagement via smartphones.

RESULTS

This project was funded in September 2020. Phase 1 data collection began in January 2022. Phase 2 data collection is scheduled to begin in July 2022.

CONCLUSIONS

If successful, data from this study will support culturally informed treatment approaches for Black smokers and, pending findings of efficacy, provide an evidence-based mobile intervention for smoking cessation that is ready for dissemination and implementation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04838236; https://clinicaltrials.gov/ct2/show/NCT04838236.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/38905.

Factors Influencing Adherence to mHealth Apps for Prevention or Management of Noncommunicable Diseases: Systematic Review

Background

Mobile health (mHealth) apps show vast potential in supporting patients and health care systems with the increasing prevalence and economic costs of noncommunicable diseases (NCDs) worldwide. However, despite the availability of evidence-based mHealth apps, a substantial proportion of users do not adhere to them as intended and may consequently not receive treatment. Therefore, understanding the factors that act as barriers to or facilitators of adherence is a fundamental concern in preventing intervention dropouts and increasing the effectiveness of digital health interventions.

Objective

This review aimed to help stakeholders develop more effective digital health interventions by identifying factors influencing the continued use of mHealth apps targeting NCDs. We further derived quantified adherence scores for various health domains to validate the qualitative findings and explore adherence benchmarks.

Methods

A comprehensive systematic literature search (January 2007 to December 2020) was conducted on MEDLINE, Embase, Web of Science, Scopus, and ACM Digital Library. Data on intended use, actual use, and factors influencing adherence were extracted. Intervention-related and patient-related factors with a positive or negative influence on adherence are presented separately for the health domains of NCD self-management, mental health, substance use, nutrition, physical activity, weight loss, multicomponent lifestyle interventions, mindfulness, and other NCDs. Quantified adherence measures, calculated as the ratio between the estimated intended use and actual use, were derived for each study and compared with the qualitative findings.

Results

The literature search yielded 2862 potentially relevant articles, of which 99 (3.46%) were included as part of the inclusion criteria. A total of 4 intervention-related factors indicated positive effects on adherence across all health domains: personalization or tailoring of the content of mHealth apps to the individual needs of the user, reminders in the form of individualized push notifications, user-friendly and technically stable app design, and personal support complementary to the digital intervention. Social and gamification features were also identified as drivers of app adherence across several health domains. A wide variety of patient-related factors such as user characteristics or recruitment channels further affects adherence. The derived adherence scores of the included mHealth apps averaged 56.0% (SD 24.4%).

Conclusions

This study contributes to the scarce scientific evidence on factors that positively or negatively influence adherence to mHealth apps and is the first to quantitatively compare adherence relative to the intended use of various health domains. As underlying studies mostly have a pilot character with short study durations, research on factors influencing adherence to mHealth apps is still limited. To facilitate future research on mHealth app adherence, researchers should clearly outline and justify the app’s intended use; report objective data on actual use relative to the intended use; and, ideally, provide long-term use and retention data.

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.

Efficacy and utilization of smartphone applications for smoking cessation among low-income adults: Secondary analysis of the iCanQuit randomized trial

INTRODUCTION

Evidence of digital interventions that are efficacious among low-income populations is scarce. In a secondary analysis, we determined the efficacy and utilization of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) versus a U.S. Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation in low-income adults enrolled in the iCanQuit randomized trial.

METHODS

Participants were randomized to receive iCanQuit (n = 437) or QuitGuide (n = 460) for 12-months. Consistent with the main trial, the primary outcome was self-reported complete-case 30-day point prevalence abstinence (PPA) at 12-months. Secondary outcomes were 7-day PPA, missing-as-smoking and multiple imputation, prolonged abstinence, and cessation of all tobacco products at 12-months. Outcome data retention, utilization, and change in ACT-based processes were compared across arms.

RESULTS

Participants were recruited from 48 U.S. states. Retention rate was 88% at 12-months and did not differ by arm. At 12-months, iCanQuit was 1.46 times more efficacious than QuitGuide for smoking cessation (27% vs. 20%; OR=1.46 95% CI: 1.04, 2.06). Findings were similar for missing-as-smoking imputation (23% vs. 18%; OR=1.41 95% CI: 1.01, 1.97) and multiple imputation at 12-months (27% vs. 20%; OR=1.51 95% CI: 1.07, 2.14). Treatment utilization was significantly higher among iCanQuit than QuitGuide participants. Increased acceptance of cues to smoke mediated the effect of treatment on cessation.

CONCLUSIONS

The iCanQuit smartphone application was more efficacious and engaging for smoking cessation among low-income adults than a USCPG-based smartphone application. A nationwide dissemination trial of iCanQuit is warranted to determine whether iCanQuit may alleviate cessation-related disparities among low-income adults.

You Don't Need an App-Conducting Mobile Smoking Research Using a Qualtrics-Based Approach

With the increasing availability of smartphones, many tobacco researchers are exploring smartphone-delivered mobile smoking interventions as a disseminable means of treatment. Most effort has been focused on the development of smartphone applications (apps) to conduct mobile smoking research to implement and validate these interventions. However, developing project-specific smartphone apps that work across multiple mobile platforms (e.g., iOS and Android) can be costly and time-consuming. Here, using a hypothetical study, we present an alternate approach to demonstrate how mobile smoking cessation and outcome evaluation can be conducted without the need of a dedicated app. Our approach uses the Qualtrics platform, a popular online survey host that is used under license by many academic institutions. This platform allows researchers to conduct device-agnostic screening, consenting, and administration of questionnaires through Qualtrics's native survey engine. Researchers can also collect ecological momentary assessment data using text messaging prompts with the incorporation of Amazon Web Services' Pinpoint. Besides these assessment capabilities, Qualtrics has the potential for delivering personalized behavioral interventions through the use of JavaScript code. By customizing the question's web elements in Qualtrics (e.g., using texts, images, videos, and buttons), researchers can integrate interactive web-based interventions and complicated behavioral and cognitive tasks into the survey. In conclusion, this Qualtrics-based methodology represents a novel and cost-effective approach for conducting mobile smoking cessation and assessment research.

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.

Daily use of nicotine replacement medications is related to daily smoking status: An ecological momentary assessment study

BACKGROUND

Few studies have examined how daily adherence to nicotine replacement therapy (NRT) impacts daily smoking abstinence.

METHODS

Data from a pilot randomized controlled trial of a smartphone-based smoking cessation intervention were used. Separate, generalized linear mixed models examined the association between ecological momentary assessments of NRT use and same-day and next day smoking status. Separate models examined the relationship between daily smoking status and (1) any use of NRT, (2) quantity of nicotine gum used, and (3) nicotine patch wear time. Reasons for medication non-adherence were also examined.

RESULTS

Participants (n = 77) were predominantly White (66.2%) and female (50.6%), 50.4 years old (SD=11.6) on average, and they smoked an average of 21.8 cigarettes per day (SD=11.0) at baseline. Daily NRT use was significantly associated with a lower likelihood of smoking both within that same day and the following day. While using the gum and patch together, and using the patch alone were associated with reduced odds of same-day and next-day smoking, using the gum alone was not significantly associated with reduced odds of smoking. The most commonly cited reasons for not using the patch or gum was "other" (43.3%), followed by "side effects" (27.1%), and "forgot" (18.9%).

CONCLUSION

Daily use of the patch or both the patch and gum was associated with a lower risk of daily smoking. Low levels of nicotine gum use alone may not be an effective cessation strategy. Future studies should further explore reasons for NRT non-compliance, and ways to increase NRT adherence.

Challenges in Participant Engagement and Retention using Mobile Health Apps: A Literature Review (Preprint)

Background

Mobile health (mHealth) apps are revolutionizing the way clinicians and researchers monitor and manage the health of their participants. However, many studies using mHealth apps are hampered by substantial participant dropout or attrition, which may impact the representativeness of the sample and the effectiveness of the study. Therefore, it is imperative for researchers to understand what makes participants stay with mHealth apps or studies using mHealth apps.

Objective

This study aimed to review the current peer-reviewed research literature to identify the notable factors and strategies used in adult participant engagement and retention.

Methods

We conducted a systematic search of PubMed, MEDLINE, and PsycINFO databases for mHealth studies that evaluated and assessed issues or strategies to improve the engagement and retention of adults from 2015 to 2020. We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Notable themes were identified and narratively compared among different studies. A binomial regression model was generated to examine the factors affecting retention.

Results

Of the 389 identified studies, 62 (15.9%) were included in this review. Overall, most studies were partially successful in maintaining participant engagement. Factors related to particular elements of the app (eg, feedback, appropriate reminders, and in-app support from peers or coaches) and research strategies (eg, compensation and niche samples) that promote retention were identified. Factors that obstructed retention were also identified (eg, lack of support features, technical difficulties, and usefulness of the app). The regression model results showed that a participant is more likely to drop out than to be retained.

Conclusions

Retaining participants is an omnipresent challenge in mHealth studies. The insights from this review can help inform future studies about the factors and strategies to improve participant retention.

Smartphone-Delivered Ecological Momentary Interventions Based on Ecological Momentary Assessments to Promote Health Behaviors: Systematic Review and Adapted Checklist for Reporting Ecological Momentary Assessment and Intervention Studies

Background

Healthy behaviors are crucial for maintaining a person’s health and well-being. The effects of health behavior interventions are mediated by individual and contextual factors that vary over time. Recently emerging smartphone-based ecological momentary interventions (EMIs) can use real-time user reports (ecological momentary assessments [EMAs]) to trigger appropriate support when needed in daily life.

Objective

This systematic review aims to assess the characteristics of smartphone-delivered EMIs using self-reported EMAs in relation to their effects on health behaviors, user engagement, and user perspectives.

Methods

We searched MEDLINE, Embase, PsycINFO, and CINAHL in June 2019 and updated the search in March 2020. We included experimental studies that incorporated EMIs based on EMAs delivered through smartphone apps to promote health behaviors in any health domain. Studies were independently screened. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. We performed a narrative synthesis of intervention effects, user perspectives and engagement, and intervention design and characteristics. Quality appraisal was conducted for all included studies.

Results

We included 19 papers describing 17 unique studies and comprising 652 participants. Most studies were quasi-experimental (13/17, 76%), had small sample sizes, and great heterogeneity in intervention designs and measurements. EMIs were most popular in the mental health domain (8/17, 47%), followed by substance abuse (3/17, 18%), diet, weight loss, physical activity (4/17, 24%), and smoking (2/17, 12%). Of the 17 studies, the 4 (24%) included randomized controlled trials reported nonstatistically significant effects on health behaviors, and 4 (24%) quasi-experimental studies reported statistically significant pre-post improvements in self-reported primary outcomes, namely depressive (P<.001) and psychotic symptoms (P=.03), drinking frequency (P<.001), and eating patterns (P=.01). EMA was commonly used to capture subjective experiences as well as behaviors, whereas sensors were rarely used. Generally, users perceived EMIs to be helpful. Common suggestions for improvement included enhancing personalization, multimedia and interactive capabilities (eg, voice recording), and lowering the EMA reporting burden. EMI and EMA components were rarely reported and were not described in a standardized manner across studies, hampering progress in this field. A reporting checklist was developed to facilitate the interpretation and comparison of findings and enhance the transparency and replicability of future studies using EMAs and EMIs.

Conclusions

The use of smartphone-delivered EMIs using self-reported EMAs to promote behavior change is an emerging area of research, with few studies evaluating efficacy. Such interventions could present an opportunity to enhance health but need further assessment in larger participant cohorts and well-designed evaluations following reporting checklists. Future research should explore combining self-reported EMAs of subjective experiences with objective data passively collected via sensors to promote personalization while minimizing user burden, as well as explore different EMA data collection methods (eg, chatbots).

Trial Registration

PROSPERO CRD42019138739; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=138739

Smoking Cessation Apps: A Systematic Review of Format, Outcomes, and Features

Smoking cessation interventions are effective, but they are not easily accessible for all treatment-seeking smokers. Mobile health (mHealth) apps have been used in recent years to overcome some of these limitations. Smoking cessation apps can be used in combination with a face-to-face intervention (FFSC-Apps), or alone as general apps (GSC-Apps). The aims of this review were (1) to examine the effects of FFSC-Apps and GSC-Apps on abstinence, tobacco use, and relapse rates; and (2) to describe their features. A systematic review was conducted following the internationally Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Of the total 6016 studies screened, 24 were included, of which nine used GSC-Apps and 15 FFSC-Apps. Eight studies reported significant differences between conditions in smoking cessation outcomes, with three of them being in favor of the use of apps, and two between different point-assessments. Concerning Apps features, most GSC-Apps included self-tracking and setting a quit plan, whereas most of the FFSC-Apps included self-tracking and carbon monoxide (CO) measures. Smartphone apps for smoking cessation could be promising tools. However, more research with an adequate methodological quality is needed to determine its effect. Nevertheless, smartphone apps’ high availability and attractiveness represent a great opportunity to reach large populations.

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.

Prediction of Smoking Risk From Repeated Sampling of Environmental Images: Model Validation

Background

Viewing their habitual smoking environments increases smokers’ craving and smoking behaviors in laboratory settings. A deep learning approach can differentiate between habitual smoking versus nonsmoking environments, suggesting that it may be possible to predict environment-associated smoking risk from continuously acquired images of smokers’ daily environments.

Objective

In this study, we aim to predict environment-associated risk from continuously acquired images of smokers’ daily environments. We also aim to understand how model performance varies by location type, as reported by participants.

Methods

Smokers from Durham, North Carolina and surrounding areas completed ecological momentary assessments both immediately after smoking and at randomly selected times throughout the day for 2 weeks. At each assessment, participants took a picture of their current environment and completed a questionnaire on smoking, craving, and the environmental setting. A convolutional neural network–based model was trained to predict smoking, craving, whether smoking was permitted in the current environment and whether the participant was outside based on images of participants’ daily environments, the time since their last cigarette, and baseline data on daily smoking habits. Prediction performance, quantified using the area under the receiver operating characteristic curve (AUC) and average precision (AP), was assessed for out-of-sample prediction as well as personalized models trained on images from days 1 to 10. The models were optimized for mobile devices and implemented as a smartphone app.

Results

A total of 48 participants completed the study, and 8008 images were acquired. The personalized models were highly effective in predicting smoking risk (AUC=0.827; AP=0.882), craving (AUC=0.837; AP=0.798), whether smoking was permitted in the current environment (AUC=0.932; AP=0.981), and whether the participant was outside (AUC=0.977; AP=0.956). The out-of-sample models were also effective in predicting smoking risk (AUC=0.723; AP=0.785), whether smoking was permitted in the current environment (AUC=0.815; AP=0.937), and whether the participant was outside (AUC=0.949; AP=0.922); however, they were not effective in predicting craving (AUC=0.522; AP=0.427). Omitting image features reduced AUC by over 0.1 when predicting all outcomes except craving. Prediction of smoking was more effective for participants whose self-reported location type was more variable (Spearman ρ=0.48; P=.001).

Conclusions

Images of daily environments can be used to effectively predict smoking risk. Model personalization, achieved by incorporating information about daily smoking habits and training on participant-specific images, further improves prediction performance. Environment-associated smoking risk can be assessed in real time on a mobile device and can be incorporated into device-based smoking cessation interventions.

Feasibility of a Smoking Cessation Smartphone App (Quit with US) for Young Adult Smokers: A Single Arm, Pre-Post Study

While smartphone applications (apps) have been shown to enhance success with smoking cessation, no study has been conducted among young adult smokers aged 18-24 years in Thailand. Quit with US was developed based on the 5 A's model and self-efficacy theory. This single arm, pre-post study was conducted aiming to assess results after using Quit with US for 4 weeks. The primary outcome was a biochemically verified 7-day point prevalence of smoking abstinence. The secondary outcomes included smoking behaviors, knowledge and attitudes toward smoking and smoking cessation, and satisfaction and confidence in the smartphone app. A total number of 19 young adult smokers were included; most participants were males (68.4%) with the mean (SD) age of 20.42 (1.46) years. After 4 weeks of study, the primary outcome demonstrated a smoking cessation rate of 31.6%. All 19 participants expressed better smoking behaviors and better knowledge and attitudes toward smoking and smoking cessation. Further, they were satisfied with the smartphone app design and content and expressed confidence in using it. These findings provided preliminary evidence that Quit with US was found to be a potentially effective smoking cessation smartphone app for young adult smokers.

Usability and Acceptability of Two Smartphone Apps for Smoking Cessation Among Young Adults With Serious Mental Illness: Mixed Methods Study

BACKGROUND

Young adults with serious mental illness (SMI) have higher smoking rates and lower cessation rates than young adults without SMI. Scalable interventions such as smartphone apps with evidence-based content (eg, the National Cancer Institute's [NCI's] QuitGuide and quitSTART) could increase access to potentially appealing and effective treatment for this group but have yet to be tested in this population.

OBJECTIVE

The goal of this user-centered design study is to determine the user experience (including usability and acceptability) of 2 widely available apps developed by the NCI-QuitGuide and quitSTART-among young adult tobacco users with SMI.

METHODS

We conducted usability and acceptability testing of QuitGuide and quitSTART among participants with SMI aged between 18 and 35 years who were stable in community mental health treatment between 2019 and 2020. Participants were randomly assigned to use QuitGuide or quitSTART on their smartphones. App usability was evaluated at baseline and following a 2-week field test of independent use via a video-recorded task completion protocol. Using a mixed method approach, we triangulated 4 data sources: nonparticipant observation, open-ended interviews, structured interviews (including the System Usability Scale [SUS]), and backend app use data obtained from the NCI. Quantitative data were analyzed using descriptive statistics, and qualitative data were analyzed using thematic analysis.

RESULTS

Participants were 17 smokers who were not interested in quitting, with a mean age of 29 (SD 4) years; 41% (n=7) presented with psychotic disorders. Participants smoked an average of 15 (SD 7) cigarettes per day. The mean SUS scores for QuitGuide were similar at visits one and two (mean 64, SD 18 and mean 66, SD 18, respectively). The mean SUS scores for quitSTART numerically increased from visit one (mean 55, SD 20) to visit two (mean 64, SD 16). Acceptability scores followed the same pattern. Observed task completion rates were at least 75% (7/9 for QuitGuide, 6/8 for quitSTART) for both apps at both visits for all but 2 tasks. During the 13-day trial period, QuitGuide and quitSTART users interacted with their assigned app on an average of 4.6 (SD 2.8) days versus 10.8 (SD 3.5) days, for a mean total of 5.6 (SD 3.8) interactions versus 41 (SD 26) interactions, and responded to a median of 1 notification (range 0-8) versus 18.5 notifications (range 0-37), respectively. Qualitative comments indicated moderate to high satisfaction overall but also included concerns about the accuracy of the apps' feedback.

CONCLUSIONS

Both QuitGuide and quitSTART had acceptable levels of usability and mixed levels of acceptability among young adults with SMI. The higher level of engagement with quitSTART suggests that quitSTART may be a favorable tool for young adult smokers with SMI. However, clinical support or coaching may be needed to overcome initial usability issues.

Personalized mobile technologies for lifestyle behavior change: A systematic review, meta-analysis, and meta-regression

Given that the one-size-fits-all approach to mobile health interventions have limited effects, a personalized approach might be necessary to promote healthy behaviors and prevent chronic conditions. Our systematic review aims to evaluate the effectiveness of personalized mobile interventions on lifestyle behaviors (i.e., physical activity, diet, smoking and alcohol consumption), and identify the effective key features of such interventions. We included any experimental trials that tested a personalized mobile app or fitness tracker and reported any lifestyle behavior measures. We conducted a narrative synthesis for all studies, and a meta-analysis of randomized controlled trials. Thirty-nine articles describing 31 interventions were included (n = 77,243, 64% women). All interventions personalized content and rarely personalized other features. Source of data included system-captured (12 interventions), user-reported (11 interventions) or both (8 interventions). The meta-analysis showed a moderate positive effect on lifestyle behavior outcomes (standardized difference in means [SDM] 0.663, 95% CI 0.228 to 1.10). A meta-regression model including source of data found that interventions that used system-captured data for personalization were associated with higher effectiveness than those that used user-reported data (SDM 1.48, 95% CI 0.76 to 2.19). In summary, the field is in its infancy, with preliminary evidence of the potential efficacy of personalization in improving lifestyle behaviors. Source of data for personalization might be important in determining intervention effectiveness. To fully exploit the potential of personalization, future high-quality studies should investigate the integration of multiple data from different sources and include personalized features other than content.

Using e-diaries to investigate ADHD - State-of-the-art and the promising feature of just-in-time-adaptive interventions

Attention-deficit/hyperactive disorder (ADHD) is characterized by symptoms which are dynamic in nature: states of hyperactivity, inattention and impulsivity as core symptoms, and emotion dysregulation as associated feature. Although tremendous work has been done to investigate between-subject differences (how patients with ADHD differ from healthy controls or patients with other disorders), little is known about the relationship between symptoms with triggers and contexts, that may allow us to better understand their causes and consequences. Understanding the temporal associations between symptoms and environmental triggers in an ecologically valid manner may be the basis to developing just-in-time adaptive interventions. Fortunately, recent years have seen advances in methodology, hardware and innovative statistical approaches to study dynamic processes in daily life. In this narrative review, we provide a description of the methodology (ambulatory assessment), summarize the existing literature in ADHD, and discuss future prospects for these methods, namely mobile sensing to assess contextual information, real-time analyses and just-in-time adaptive interventions.

Randomised controlled trial of a just-in-time adaptive intervention (JITAI) smoking cessation smartphone app: the Quit Sense feasibility trial protocol

INTRODUCTION

A lapse (any smoking) early in a smoking cessation attempt is strongly associated with reduced success. A substantial proportion of lapses are due to urges to smoke triggered by situational cues. Currently, no available interventions proactively respond to such cues in real time. Quit Sense is a theory-guided just-in-time adaptive intervention smartphone app that uses a learning tool and smartphone sensing to provide in-the-moment tailored support to help smokers manage cue-induced urges to smoke. The primary aim of this randomised controlled trial (RCT) is to assess the feasibility of delivering a definitive online efficacy trial of Quit Sense.

METHODS AND ANALYSES

A two-arm parallel-group RCT allocating smokers willing to make a quit attempt, recruited via online adverts, to usual care (referral to the NHS SmokeFree website) or usual care plus Quit Sense. Randomisation will be stratified by smoking rate (<16 vs ≥16 cigarettes/day) and socioeconomic status (low vs high). Recruitment, enrolment, baseline data collection, allocation and intervention delivery will be automated through the study website. Outcomes will be collected at 6 weeks and 6 months follow-up via the study website or telephone, and during app usage. The study aims to recruit 200 smokers to estimate key feasibility outcomes, the preliminary impact of Quit Sense and potential cost-effectiveness, in addition to gaining insights on user views of the app through qualitative interviews.

ETHICS AND DISSEMINATION

Ethics approval has been granted by the Wales NHS Research Ethics Committee 7 (19/WA/0361). The findings will be disseminated to the public, the funders, relevant practice and policy representatives and other researchers.

TRIAL REGISTRATION NUMBER

ISRCTN12326962.

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.

Identifying mechanisms that link pain to smoking relapse during a quit attempt

OBJECTIVE

Emerging evidence suggests that adults with chronic pain have poor smoking cessation outcomes, but the exact mechanisms are less understood. This study examined whether depression, anxiety, stress, and then, positive outcome expectancy for smoking mediated the association between pain and smoking relapse during a quit attempt.

METHODS

This study is a secondary data analysis of a three-armed randomized clinical trial that compared in-person and smartphone-based smoking cessation interventions. Participants (N = 81) self-reported the amount of bodily pain they experienced in the past 4 weeks at baseline. Depression, anxiety, stress, and positive outcome expectancy for smoking were measured daily, via a smartphone app, throughout the first week of the quit attempt, and were aggregated to the week level for analyses. Biochemically verified smoking abstinence was assessed 4 weeks postquit date.

RESULTS

Sequential mediation analyses showed that pain was indirectly associated with smoking relapse through greater feelings of stress and then higher expectations that smoking would improve mood (B = 0.22 [95% CI = 0.03, 0.65]). The pathways for depression and anxiety were not significant mediators of pain and smoking relapse.

CONCLUSION

Findings from this study indicate that pain is indirectly associated with smoking relapse through feelings of stress and then positive outcome expectancy for smoking. Smoking cessation treatment for adults who experience high levels of bodily pain should include psychoeducation that teaches adaptive coping responses, such as mindfulness, to manage stress, and challenge expectations about the ability of smoking to improve mood. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

What differs former, light and heavy smokers? Evidence from a post-conflict setting

BACKGROUND

Evidence suggests that people who live in regions affected by the armed conflict are more likely to smoke.

OBJECTIVE

The purpose of this study was to assess factors associated with smoking status in a sample of students in the northern Kosovo province.

MATERIALS AND METHODS

A total of 514 students enrolled in University in Kosovska Mitrovica, Kosovo, were recruited between April to June 2015 at Student Public Health Center during mandatory health checks. Participants filled in socio-demographic and behavioral questionnaire and Beck Depression Inventory (BDI). Based on responses about smoking, students were categorized in non-smokers, former smokers, light smokers (1-13 cigarettes/day) and heavy smokers (> 13 cigarettes/day).

RESULTS

Of 514 students, 116 (22.6%) classified themselves as smokers. Higher education level of fathers (Odds ratio [OR]=2.89, 95% confidence interval [CI] 1.30-6.44, p=0.009), not living with smokers (OR=0.42, 95%CI 0.15-0.97, p=0.017) and longer exposure to second hand smoke (OR=1.07, 95%CI 1.01-1.13, p=0.036) was associated with former smoking. Studying medical and natural sciences (OR=2.07, 95%CI 1.05-4.18, p=0.040), consuming alcohol (OR=2.98, 95%CI 1.19-10.03, p=0.020), living with smokers (OR=2.88, 95%CI 1.49-5.56, p=0.002), longer exposure to second hand smoke (OR=1.06, 95%CI 1.01-1.11, p=0.019) and having a more intense depressive symptoms (OR=1.08, 95%CI 1.03-1.13, p=0.002) was associated with light smoking. Being male (OR=0.22, 95%CI 0.07-0.41, p=0.001), older (OR=1.47, 95%CI 1.21-1.78, p=0.001), living with smokers (OR=3.78, 95%CI 1.69-8.07, p=0.001), longer daily exposure to second-hand smoke (OR=1.10, 95%CI 1.04-1.16, p=0.001), and having more severe depressive symptoms (OR=1.12, 95%CI 1.07-1.18, p=0.001) were associated with heavy smoking.

CONCLUSION

Smoking prevention and cessation programs should include the entire community, because exposure to environmental second hand smoke may facilitate initiation and more intense smoking. Screening of student smokers for depression should be prioritized in the process of rebuilding the framework for primary and secondary prevention in the post-conflict period.