Mobile-health intervention for smoking cessation among Cambodian people living with HIV: A mixed-methods pilot study

Smartphone-Based Survey and Message Compliance in Adults Initially Unready to Quit Smoking: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

Efficacy of smartphone-based interventions depends on intervention content quality and level of exposure to that content. Smartphone-based survey completion rates tend to decline over time; however, few studies have identified variables that predict this decline over longer-term interventions (eg, 26 weeks).

OBJECTIVE

This study aims to identify predictors of survey completion and message viewing over time within a 26-week smoking cessation trial.

METHODS

This study examined data from a 3-group pilot randomized controlled trial of adults who smoke (N=152) and were not ready to quit smoking within the next 30 days. For 182 days, two intervention groups received smartphone-based morning and evening messages based on current readiness to quit smoking. The control group received 2 daily messages unrelated to smoking. All participants were prompted to complete 26 weekly smartphone-based surveys that assessed smoking behavior, quit attempts, and readiness to quit. Compliance was operationalized as percentages of weekly surveys completed and daily messages viewed. Linear regression and mixed-effects models were used to identify predictors (eg, intervention group, age, and sex) of weekly survey completion and daily message viewing and decline in compliance over time.

RESULTS

The sample (mean age 50, SD 12.5, range 19-75 years; mean years of education 13.3, SD 1.6, range 10-20 years) was 67.8% (n=103) female, 74.3% (n=113) White, 77% (n=117) urban, and 52.6% (n=80) unemployed, and 61.2% (n=93) had mental health diagnoses. On average, participants completed 18.3 (71.8%) out of 25.5 prompted weekly surveys and viewed 207.3 (60.6%) out of 345.1 presented messages (31,503/52,460 total). Age was positively associated with overall weekly survey completion (P=.003) and daily message viewing (P=.02). Mixed-effects models indicated a decline in survey completion from 77% (114/148) in the first week of the intervention to 56% (84/150) in the last week of the intervention (P<.001), which was significantly moderated by age, sex, ethnicity, municipality (ie, rural/urban), and employment status. Similarly, message viewing declined from 72.3% (1533/2120) in the first week of the intervention to 44.6% (868/1946) in the last week of the intervention (P<.001). This decline in message viewing was significantly moderated by age, sex, municipality, employment status, and education.

CONCLUSIONS

This study demonstrated the feasibility of a 26-week smartphone-based smoking cessation intervention. Study results identified subgroups that displayed accelerated rates in the decline of survey completion and message viewing. Future research should identify ways to maintain high levels of interaction with mobile health interventions that span long intervention periods, especially among subgroups that have demonstrated declining rates of intervention engagement over time.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03405129; https://clinicaltrials.gov/ct2/show/NCT03405129.

Technology-based interventions for tobacco smoking prevention and treatment: a 20-year bibliometric analysis (2003-2022)

BACKGROUND

Substance abuse, particularly tobacco smoking, is a significant global public health concern. Efforts have been made to reduce smoking prevalence and promote cessation, but challenges, such as nicotine addiction, marketing tactics by tobacco industry, and cultural acceptability hinder progress. Technology has emerged as a potential tool to address these challenges by providing innovative scalable interventions. The objective of the study was to analyze and map scientific literature on technology-based intervention for tobacco prevention and treatment.

METHODS

A bibliometric methodology was conducted. Scopus database was used to retrieve relevant research articles published between 2003 and 2022. The analysis included publication trends, key contributors, research hotspots, research themes, the most impactful articles, and emerging research topics.

RESULTS

A total of 639 articles were found, with a slow and fluctuating growth pattern observed after 2011. The Journal of Medical Internet Research was the most prominent journal in the field. The United States was the leading country in the field, followed up by the United Kingdom, and the Netherlands. Research hotspots included smoking cessation, randomized controlled trials, and technology-based methods such as internet, mHealth, smartphone apps, text messages, and social media. Four primary research themes were identified: development of smartphone applications, efficacy of text messaging interventions, acceptance and effectiveness of smartphone applications, and interventions targeting young adults and students using mobile phone and social media platforms. The top 10 cited articles demonstrated effectiveness of digital interventions in promoting smoking cessation rates and reducing relapse rates. Emerging research topics included the use of virtual reality interventions, interventions for specific populations through personalized tools, and technology-based interventions in non-Western countries.

CONCLUSIONS

The findings of the current study highlight the potential of technology to address the challenges associated with tobacco smoking. Further future research in this area is warranted to continue advancing the field and developing effective and evidence-based interventions to combat tobacco smoking.

Efficacy of e-health interventions for smoking cessation management in smokers: a systematic review and meta-analysis

Background

Smoking is one of the major risk factors for shortened lifespan and disability, while smoking cessation is currently the only guaranteed method to reduce the harm caused by smoking. E-health is a field that utilizes information and communication technology to support the health status of its users. The emergence of this digital health approach has provided a new way of smoking cessation support for smokers seeking help, and an increasing number of researchers are attempting to use e-health for a wide range of effective smoking cessation interventions. We conducted a systematic review and meta-analysis of studies that used e-health as a smoking cessation support tool.

Methods

This systematic review and meta-analysis searched the PubMed, Embase, and Cochrane Library databases until December 2022. The included studies were randomized controlled trials (RCTs) comparing the use of e-health interventions and traditional offline smoking cessation care interventions. The primary outcome of the studies was the point smoking cessation rate (7-day and 30-day), and the secondary outcome was sustained smoking cessation rates. Studies were excluded if there was no clear e-health intervention described or if standard-compliant cessation outcomes were not clearly reported. Fixed-effects meta-analysis and meta-regression analyses were performed on the included study data to evaluate the effectiveness of the interventions. The meta-analysis outcome was the risk ratio (RR) and a 95% confidence interval. The study was registered with PROSPERO, CRD42023388667.

Findings

We collectively screened 2408 articles, and ultimately included 39 articles with a total of 17,351 eligible participants, of which 44 studies were included in the meta-analysis. The meta-analysis revealed that compared to traditional smoking cessation interventions, e-health interventions can increase point quit rates (RR 1.86, 95% CI 1.69-2.04) as well as sustained quit rates in the long-term (RR 1.79, 95% CI 1.60-2.00) among smokers. Subgroup analysis showed that text and telephone interventions in e-health significantly improved short-term quit rates for up to 7 days (RR 2.10, 95% CI 1.77-2.48). Website and app interventions also had a positive impact on improving short-term quit rates for up to 7 days (RR 1.74, 95% CI 1.56-1.94). The heterogeneity of the study results was low, demonstrating the significant smoking cessation advantages of e-health interventions.

Interpretation

We have found that personalized e-health interventions can effectively help smokers quit smoking. The diverse remote intervention methods of e-health can provide more convenient options for further customization. Additionally, further follow-up research is needed to evaluate the sustained effectiveness of interventions on smokers' continuous abstinence over a longer period (greater than one year). In the future, e-health can further optimize smoking cessation strategies.

Funding

No funding.

Pilot Testing of an mHealth App for Tobacco Cessation in People Living With HIV: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

An estimated 40% of people living with HIV smoke cigarettes. Although smoking rates in the United States have been declining in recent years, people living with HIV continue to smoke cigarettes at twice the rate of the general population. Mobile health (mHealth) technology is an effective tool for people living with a chronic illness, such as HIV, as currently 84% of households in the United States report that they have a smartphone. Although many studies have used mHealth interventions for smoking cessation, few studies have recruited people living with HIV who smoke.

OBJECTIVE

The objective of the pilot randomized controlled trial (RCT) is to examine the feasibility, acceptability, and preliminary efficacy of the Sense2Quit App as a tool for people living with HIV who are motivated to quit smoking.

METHODS

The Sense2Quit study is a 2-arm RCT for people living with HIV who smoke cigarettes (n=60). Participants are randomized to either the active intervention condition, which consists of an 8-week supply of nicotine replacement therapy, standard smoking cessation counseling, and access to the Sense2Quit mobile app and smartwatch, or the control condition, which consists of standard smoking cessation counseling and a referral to the New York State Smokers' Quitline. The Sense2Quit app is a mobile app connected through Bluetooth to a smartwatch that tracks smoking gestures and distinguishes them from other everyday hand movements. In the Sense2Quit app, participants can view their smoking trends, which are recorded through their use of the smartwatch, including how often or how much they smoke and the amount of money that they are spending on cigarettes, watch videos with quitting tips, information, and distractions, play games, set reminders, and communicate with a study team member.

RESULTS

Enrollment of study participants began in March 2023 and is expected to end in October 2023. All data collection is expected to be completed by the end of January 2024. This RCT will test the difference in outcomes between the control and intervention arms. The primary outcome will be the percentage of participants with biochemically verified 7-day point prevalence smoking or tobacco abstinence at their 12-week follow-up. Results from this pilot study will be disseminated to the research community following the completion of all data collection.

CONCLUSIONS

The Sense2Quit study leverages mHealth so that it can help smokers improve their efforts at smoking cessation. Our research has the potential to not only increase quitting rates among people living with HIV who may need a prolonged, tailored intervention but also inform further development of mHealth for people living with HIV. This mHealth study will contribute significant findings to the greater mHealth research community, providing evidence as to how mHealth should be developed and tested among the target population.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05609032; https://clinicaltrials.gov/study/NCT05609032.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/49558.

Feasibility, Acceptability, and Preliminary Effects of a Video-Based Intervention for Smoking Cessation Among People with HIV in Kathmandu, Nepal: A Single-Armed Pilot Study

Despite the evidence of the disproportionate burden of tobacco use among people with HIV (PWH), little effort has been made to design and test smoking cessation interventions for PWH in resource-limited countries. We assessed the feasibility, acceptability, and preliminary effects of a video-based smoking cessation intervention consisting of eleven 3-8-minute sessions among PWH in Nepal, a lower-middle-income country. Guided by the phased-based model, our 3-month intervention focused on setting the quit date, smoking cessation, and abstinence maintenance. We screened 103 PWH over three weeks for our single-arm trial, with 53 considered eligible and 48 recruited (91%). Forty-six participants watched all video clips, while two watched 7-9. All participants were retained at a 3-month follow-up. The 1-week point prevalence abstinence (self-report supported with expired carbon monoxide levels < 5ppm) at 3-month follow-up was 39.6%. Most (90%) participants reported "very much" or "much" comfort with watching the videos on their smartphones, and all would recommend the intervention to other PWH who smoke. Overall, our pilot trial demonstrated the feasibility, acceptability, and high-level efficacy of the video-based smoking cessation intervention highlighting its potential for scaling up in Nepal and other resource-limited countries.

Ending Tobacco Use Through Interactive Tailored Messaging for Cambodian People With HIV (Project EndIT): Protocol for a Randomized Controlled Trial

BACKGROUND

The prevalence of smoking remains high in many low- and middle-income countries (LMICs), including the Southeast Asian nation of Cambodia. Smoking is especially hazardous for people with HIV. In Cambodia, approximately 43%-65% of men with HIV and 3%-5% of women with HIV smoke cigarettes. Thus, there is a critical need for cost-effective smoking cessation interventions for Cambodian people with HIV. This paper describes the design, methods, and data analysis plans for a randomized controlled trial assessing the efficacy of a theory-based mobile health smoking cessation intervention in Cambodian people with HIV.

OBJECTIVE

This 2-group randomized controlled trial compares the efficacy of a mobile health-based automated messaging (AM) intervention versus standard care (SC) in facilitating smoking cessation among Cambodian people with HIV.

METHODS

Cambodian people with HIV who currently smoke and are receiving antiretroviral treatment (target, N=800) will be randomized to (1) SC or (2) the AM intervention. SC participants will receive brief advice to quit smoking, written self-help materials, nicotine patches, and will complete weekly app-delivered dietary assessments for 26 weeks. AM participants will receive all SC components (but will complete smoking-related weekly assessments instead of dietary assessments), in addition to a fully automated tailored messaging program driven by the weekly assessments to facilitate smoking cessation. In the Phase-Based Model of smoking cessation, the cessation process is partitioned into 4 phases: motivation, preparation (precessation), cessation (quit date to 2 weeks post quit), and maintenance (up to 6 months post quit). Our AM program targets processes within these phases, including increasing motivation to quit, enhancing self-efficacy, obtaining social support, skills to cope with nicotine withdrawal symptoms and stress, and skills to maintain abstinence. All participants will complete baseline and 3-, 6-, and 12-month in-person follow-up assessments. The primary outcome is biochemically confirmed abstinence at 12 months, with 3- and 6-month abstinence as secondary outcomes. Potential mediators and moderators underlying treatment effects will be explored, and cost-effectiveness will be assessed.

RESULTS

This study was approved by all relevant domestic and international institutional and ethical review boards. Participant recruitment commenced in January 2023. Data collection is expected to conclude by the end of 2025.

CONCLUSIONS

By demonstrating the greater efficacy and cost-effectiveness of AM relative to SC, this study has the potential to transform HIV care in Cambodia and prevent tobacco-related diseases. Furthermore, it may be adapted for use in other Cambodian populations and in other low- and middle-income countries. Ultimately, the AM approach to smoking cessation could greatly improve public health in the developing world and beyond.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05746442; https://clinicaltrials.gov/ct2/show/NCT05746442.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/48923.

Effectiveness and Acceptability of Conversational Agents for Smoking Cessation: A Systematic Review and Meta-analysis

INTRODUCTION

Conversational agents (CAs; computer programs that use artificial intelligence to simulate a conversation with users through natural language) have evolved considerably in recent years to support healthcare by providing autonomous, interactive, and accessible services, making them potentially useful for supporting smoking cessation. We performed a systematic review and meta-analysis to provide an overarching evaluation of their effectiveness and acceptability to inform future development and adoption.

AIMS AND METHODS

PsycInfo, Web of Science, ACM Digital Library, IEEE Xplore, Medline, EMBASE, Communication and Mass Media Complete, and CINAHL Complete were searched for studies examining the use of CAs for smoking cessation. Data from eligible studies were extracted and used for random-effects meta-analyses.

RESULTS

The search yielded 1245 publications with 13 studies eligible for systematic review (total N = 8236) and six studies for random-effects meta-analyses. All studies reported positive effects on cessation-related outcomes. A meta-analysis with randomized controlled trials reporting on abstinence yielded a sample-weighted odds ratio of 1.66 (95% CI = 1.33% to 2.07%, p < .001), favoring CAs over comparison groups. A narrative synthesis of all included studies showed overall high acceptability, while some barriers were identified from user feedback. Overall, included studies were diverse in design with mixed quality, and evidence of publication bias was identified. A lack of theoretical foundations was noted, as well as a clear need for relational communication in future designs.

CONCLUSIONS

The effectiveness and acceptability of CAs for smoking cessation are promising. However, standardization of reporting and designing of the agents is warranted for a more comprehensive evaluation.

IMPLICATIONS

This is the first systematic review to provide insight into the use of CAs to support smoking cessation. Our findings demonstrated initial promise in the effectiveness and user acceptability of these agents. We also identified a lack of theoretical and methodological limitations to improve future study design and intervention delivery.

Estimates of prevalence, time-trend, and association of smoking in adults living with HIV, HBV, and HCV (NHANES 1999-2018)

Although the smoking rate of human immunodeficiency virus (HIV), hepatitis B virus (HBV) or hepatitis C virus (HCV) infected people was much higher than that of the general population, smoking cessation interventions have long been ineffective. We aimed to examine the estimates of prevalence, time-trend, and association of smoking among people living with HIV, HBV, or HCV. This cohort was composed of 32,115 individuals from the NHANES database (1999-2018) and they were collected in the US. The time trend analysis of smoking and quitting rates was conducted using different years of survey follow-up and different infected groups. Multivariable logistic regression analysis was used to identify the risk factors related to smoking behavior of these infected people. Compared to non-infected smokers, infected smokers were more likely to be older (aged 30-39, OR = 9.92, CI 6.07-16.21; aged 40-49,OR = 3.51, CI 2.49-4.94), males (1.99, 1.54-2.55), lower education and economic level (1.78, 1.39-2.29; 2.05, 1.59-2.65), unemployed (1.63, 1.21-2.20), suffering depression (1.35, 1.05-1.72), and drug users (7.65, 5.04-11.59). Taken together, our study showed that these complex psychosocial characteristics and unhealthy behavioral factors might be major independent risk factors for increasing smoking rate and decreasing smoking cessation rate among these infected people.

Use of research electronic data capture (REDCap) in a COVID-19 randomized controlled trial: a practical example

BACKGROUND

Randomized controlled trials (RCT) are considered the ideal design for evaluating the efficacy of interventions. However, conducting a successful RCT has technological and logistical challenges. Defects in randomization processes (e.g., allocation sequence concealment) and flawed masking could bias an RCT's findings. Moreover, investigators need to address other logistics common to all study designs, such as study invitations, eligibility screening, consenting procedure, and data confidentiality protocols. Research Electronic Data Capture (REDCap) is a secure, browser-based web application widely used by researchers for survey data collection. REDCap offers unique features that can be used to conduct rigorous RCTs.

METHODS

In September and November 2020, we conducted a parallel group RCT among Indiana University Bloomington (IUB) undergraduate students to understand if receiving the results of a SARS-CoV-2 antibody test changed the students' self-reported protective behavior against coronavirus disease 2019 (COVID-19). In the current report, we discuss how we used REDCap to conduct the different components of this RCT. We further share our REDCap project XML file and instructional videos that investigators can use when designing and conducting their RCTs.

RESULTS

We reported on the different features that REDCap offers to complete various parts of a large RCT, including sending study invitations and recruitment, eligibility screening, consenting procedures, lab visit appointment and reminders, data collection and confidentiality, randomization, blinding of treatment arm assignment, returning test results, and follow-up surveys.

CONCLUSIONS

REDCap offers powerful tools for longitudinal data collection and conduct of rigorous and successful RCTs. Investigators can make use of this electronic data capturing system to successfully complete their RCTs.

TRIAL REGISTRATION

The RCT was prospectively (before completing data collection) registered at ClinicalTrials.gov; registration number: NCT04620798 , date of registration: November 9, 2020.