Mobile phone-based interventions for smoking cessation

Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development Process and Randomized Controlled Trial

BACKGROUND

Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot.

OBJECTIVE

We aim to report results of the user-centered design development process and randomized controlled trial for a novel and comprehensive quit smoking conversational chatbot called QuitBot.

METHODS

The 4 years of formative research for developing QuitBot followed an 11-step process: (1) specifying a conceptual model; (2) conducting content analysis of existing interventions (63 hours of intervention transcripts); (3) assessing user needs; (4) developing the chat's persona ("personality"); (5) prototyping content and persona; (6) developing full functionality; (7) programming the QuitBot; (8) conducting a diary study; (9) conducting a pilot randomized controlled trial (RCT); (10) reviewing results of the RCT; and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot RCT results. The process of adding a QnA function itself involved a three-step process: (1) generating QnA pairs, (2) fine-tuning large language models (LLMs) on QnA pairs, and (3) evaluating the LLM outputs.

RESULTS

We developed a quit smoking program spanning 42 days of 2- to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing Food and Drug Administration-approved cessation medications, coping with triggers, and recovering from lapses and relapses. In a pilot RCT with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT text messaging program, particularly among those who viewed all 42 days of program content: 30-day, complete-case, point prevalence abstinence rates at 3-month follow-up were 63% (39/62) for QuitBot versus 38.5% (45/117) for SmokefreeTXT (odds ratio 2.58, 95% CI 1.34-4.99; P=.005). However, Facebook Messenger intermittently blocked participants' access to QuitBot, so we transitioned from Facebook Messenger to a stand-alone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions led to us develop a core conversational feature, enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT-3.5 (OpenAI) responds to questions that are not within our library of QnA pairs.

CONCLUSIONS

The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03585231; https://clinicaltrials.gov/study/NCT03585231.

The Effects of mHealth Interventions on Quality of Life, Anxiety, and Depression in Patients With Coronary Heart Disease: Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Coronary heart disease (CHD) is the leading cause of death globally. In addition, 20% to 40% of the patients with CHD have comorbid mental health issues such as anxiety or depression, affecting the prognosis and quality of life (QoL). Mobile health (mHealth) interventions have been developed and are widely used; however, the evidence for the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD is currently ambiguous.

OBJECTIVE

In this study, we aimed to assess the effects of mHealth interventions on QoL, anxiety, and depression in patients with CHD.

METHODS

We searched the Cochrane Library, PubMed, Embase, CINAHL, Web of Science, China National Knowledge Infrastructure, and Wanfang databases from inception to August 12, 2023. Eligible studies were randomized controlled trials that involved patients with CHD who received mHealth interventions and that reported on QoL, anxiety, or depression outcomes. We used the Cochrane risk-of-bias tool for randomized trials to evaluate the risk of bias in the studies, ensuring a rigorous and methodologically sound analysis. Review Manager (desktop version 5.4; The Cochrane Collaboration) and Stata MP (version 17.0; StataCorp LLC) were used to conduct the meta-analysis. The effect size was calculated using the standardized mean difference (SMD) and its 95% CI.

RESULTS

The meta-analysis included 23 studies (5406 participants in total) and showed that mHealth interventions significantly improved QoL in patients with CHD (SMD 0.49, 95% CI 0.25-0.72; Z=4.07; P<.001) as well as relieved their anxiety (SMD -0.46, 95% CI -0.83 to -0.08; Z=2.38; P=.02) and depression (SMD -0.34, 95% CI -0.56 to -0.12; Z=3.00; P=.003) compared to usual care. The subgroup analyses indicated a significant effect favoring the mHealth intervention on reducing anxiety and depressive symptoms compared to usual care, especially when (1) the intervention duration was ≥6 months (P=.04 and P=.001), (2) the mHealth intervention was a simple one (only 1 mHealth intervention was used) (P=.01 and P<.001), (3) it was implemented during the COVID-19 pandemic (P=.04 and P=.01), (4) it was implemented in low- or middle-income countries (P=.01 and P=.02), (5) the intervention focused on mental health (P=.01 and P=.007), and (6) adherence rates were high (≥90%; P=.03 and P=.002). In addition, comparing mHealth interventions to usual care, there was an improvement in QoL when (1) the mHealth intervention was a simple one (P<.001), (2) it was implemented in low- or middle-income countries (P<.001), and (3) the intervention focused on mental health (P<.001).

CONCLUSIONS

On the basis of the existing evidence, mHealth interventions might be effective in improving QoL and reducing anxiety and depression in patients with CHD. However, large sample, high-quality, and rigorously designed randomized controlled trials are needed to provide further evidence.

TRIAL REGISTRATION

PROSPERO CRD42022383858; https://tinyurl.com/3ea2npxf.

Evaluation of effectiveness and acceptability of a psychological treatment for smoking cessation combined with a smartphone App: A pilot study

Despite the increasing number of mobile-based interventions to quit smoking over the last years, few studies have investigated the efficacy of smoking cessation interventions blended with smartphone Apps. The present pilot study aims to examine the preliminary effectiveness and acceptability of a cognitive-behavioral treatment combined with a smartphone App, compared to the same psychological treatment without the App. The sample comprised 206 treatment-seeking smokers, who were assigned to: 1) an experimental group receiving a cognitive-behavioral intervention combined with the "Non Fumo" App (n = 102), and 2) a control group receiving only the cognitive-behavioral intervention to quit smoking (n = 104). Results concerning the primary outcomes showed no significant differences between conditions in point-prevalence abstinence rates at 12-month follow-up (35.30 % in the experimental group vs. 31.70 % in the control group) and in treatment acceptability. Regarding the secondary outcomes, both groups obtained similar point-prevalence abstinence rates at the end of treatment (61.80 % vs. 65.40 %), at 3-month (42.20 % vs. 45.20 %, respectively) and 6-month follow-ups (37.30 % vs. 37.50 %). No significant differences were found between conditions in prolonged abstinence rates at 6-month (35.3 % vs. 35.6 %) and 12-month follow-ups (30.4 % vs. 26.9 %). Overall, good abstinence rates and treatment acceptability were obtained, although there were no significant differences between conditions. More research is needed to establish clear conclusions about the efficacy of psychological smoking cessation treatments blended with smartphone Apps.

Effect of Adding Personalized Instant Messaging Apps to a Brief Smoking Cessation Model in Community Smokers in Hong Kong: Pragmatic Randomized Clinical Trial

BACKGROUND

While text messaging has proven effective for smoking cessation (SC), engagement in the intervention remains suboptimal.

OBJECTIVE

This study aims to evaluate whether using more interactive and adaptive instant messaging (IM) apps on smartphones, which enable personalization and chatting with SC advisors, can enhance SC outcomes beyond the provision of brief SC advice and active referral (AR) to SC services.

METHODS

From December 2018 to November 2019, we proactively recruited 700 adult Chinese daily cigarette users in Hong Kong. Participants were randomized in a 1:1 ratio. At baseline, all participants received face-to-face brief advice on SC. Additionally, they were introduced to local SC services and assisted in selecting one. The intervention group received an additional 26 personalized regular messages and access to interactive chatting through IM apps for 3 months. The regular messages aimed to enhance self-efficacy, social support, and behavioral capacity for quitting, as well as to clarify outcome expectations related to cessation. We developed 3 sets of messages tailored to the planned quit date (within 30 days, 60 days, and undecided). Participants in the intervention group could initiate chatting with SC advisors on IM themselves or through prompts from regular messages or proactive inquiries from SC advisors. The control group received 26 SMS text messages focusing on general health. The primary outcomes were smoking abstinence validated by carbon monoxide levels of <4 parts per million at 6 and 12 months after the start of the intervention.

RESULTS

Of the participants, 505/700 (72.1%) were male, and 450/648 (69.4%) were aged 40 or above. Planning to quit within 30 days was reported by 500/648 (77.2%) participants, with fewer intervention group members (124/332, 37.3%) reporting previous quit attempts compared with the control group (152/335, 45.4%; P=.04). At the 6- and 12-month follow-ups (with retention rates of 456/700, 65.1%, and 446/700, 63.7%, respectively), validated abstinence rates were comparable between the intervention (14/350, 4.0%, and 19/350, 5.4%) and control (11/350, 3.1% and 21/350, 6.0%) groups. Compared with the control group, the intervention group reported greater utilization of SC services at 12 months (RR 1.26, 95% CI 1.01-1.56). Within the intervention group, engaging in chat sessions with SC advisors predicted better validated abstinence at 6 months (RR 3.29, 95% CI 1.13-9.63) and any use of SC services (RR 1.66, 95% CI 1.14-2.43 at 6 months; RR 1.67, 95% CI 1.26-2.23 at 12 months).

CONCLUSIONS

An IM-based intervention, providing support and assistance alongside brief SC advice and AR, did not yield further increases in quitting rates but did encourage the utilization of SC services. Future research could explore whether enhanced SC service utilization leads to improved long-term SC outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03800719; https://clinicaltrials.gov/ct2/show/NCT03800719.

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.

Effectiveness of Applying Green Heart, a Smartphone-Based Self-management Intervention to Control Smoking: A Randomized Clinical Trial

BACKGROUND

Cardiovascular diseases (CVDs) pose a significant global health concern and are the most common cause of death and disability, necessitating preventive interventions targeting modifiable risk factors. Recently, mobile-health technology has been developed to improve the delivery of cardiovascular prevention by risk factor modification. The "Green Heart" mobile application (app) was designed to aid in risk factor control among coronary artery disease (CAD) patients.

METHODS

This parallel-group, single-blinded randomized controlled trial enrolled 1590 CAD patients, including 668 current smokers, randomly assigned to control (paper-based education) and intervention (application-based) groups. The app encompassed three modules targeting smoking cessation, dyslipidemia control, and blood pressure management. This study evaluated the impact of the smoking cessation module on behavioral change among current smokers. Green Heart assesses nicotine dependence, offering personalized quit plans, educational content, motivational messages, and automated progress tracking. The odds of smoking behavior changes during the 24-week follow-up underwent assessment.

RESULTS

The intention-to-treat analysis highlighted significantly elevated rates of smoking cessation and reductions in the intervention group versus the control group. Adherence to the app (per-treatment analysis) also demonstrated significantly more favorable smoking behavior changes among the application users. Logistic regression emphasized higher odds of quitting and reduction in smoking in the application group, showing an odds ratio of 2.14 (95% CI: 1.16-3.97) compared to those not using the app (P=0.015).

CONCLUSION

Our results confirmed that complete adherence to the app for at least 24 weeks was linked to alterations in cigarette smoking behavior among CAD patients. Trial Registration Number: IRCT20221016056204N1.

Reviewing the Potential Role of Artificial Intelligence in Delivering Personalized and Interactive Pain Medicine Education for Chronic Pain Patients

The integration of artificial intelligence (AI) in patient pain medicine education has the potential to revolutionize pain management. By harnessing the power of AI, patient education becomes more personalized, interactive, and supportive, empowering patients to understand their pain, make informed decisions, and actively participate in their pain management journey. AI tailors the educational content to individual patients' needs, providing personalized recommendations. It introduces interactive elements through chatbots and virtual assistants, enhancing engagement and motivation. AI-powered platforms improve accessibility by providing easy access to educational resources and adapting content to diverse patient populations. Future AI applications in pain management include explaining pain mechanisms, treatment options, predicting outcomes based on individualized patient-specific factors, and supporting monitoring and adherence. Though the literature on AI in pain medicine and its applications are scarce yet growing, we propose avenues where AI may be applied and review the potential applications of AI in pain management education. Additionally, we address ethical considerations, patient empowerment, and accessibility barriers.

Comparing the Effectiveness of the Blended Delivery Mode With the Face-to-Face Delivery Mode of Smoking Cessation Treatment: Noninferiority Randomized Controlled Trial

BACKGROUND

Tobacco consumption is a leading cause of death and disease, killing >8 million people each year. Smoking cessation significantly reduces the risk of developing smoking-related diseases. Although combined treatment for addiction is promising, evidence of its effectiveness is still emerging. Currently, there is no published research comparing the effectiveness of blended smoking cessation treatments (BSCTs) with face-to-face (F2F) treatments, where web-based components replace 50% of the F2F components in blended treatment.

OBJECTIVE

The primary objective of this 2-arm noninferiority randomized controlled trial was to determine whether a BSCT is noninferior to an F2F treatment with identical ingredients in achieving abstinence rates.

METHODS

This study included 344 individuals who smoke (at least 1 cigarette per day) attending an outpatient smoking cessation clinic in the Netherlands. The participants received either a blended 50% F2F and 50% web-based BSCT or only F2F treatment with similar content and intensity. The primary outcome measure was cotinine-validated abstinence rates from all smoking products at 3 and 15 months after treatment initiation. Additional measures included carbon monoxide-validated point prevalence abstinence; self-reported point prevalence abstinence; and self-reported continuous abstinence rates at 3, 6, 9, and 15 months after treatment initiation.

RESULTS

None of the 13 outcomes showed statistically confirmed noninferiority of the BSCT, whereas 4 outcomes showed significantly (P<.001) inferior abstinence rates of the BSCT: cotinine-validated point prevalence abstinence rate at 3 months (difference 12.7, 95% CI 6.2-19.4), self-reported point prevalence abstinence rate at 6 months (difference 19.3, 95% CI 11.5-27.0) and at 15 months (difference 11.7, 95% CI 5.8-17.9), and self-reported continuous abstinence rate at 6 months (difference 13.8, 95% CI 6.8-20.8). The remaining 9 outcomes, including the cotinine-validated point prevalence abstinence rate at 15 months, were inconclusive.

CONCLUSIONS

In this high-intensity outpatient smoking cessation trial, the blended mode was predominantly less effective than the traditional F2F mode. The results contradict the widely assumed potential benefits of blended treatment and suggest that further research is needed to identify the critical factors in the design of blended interventions.

TRIAL REGISTRATION

Netherlands Trial Register 27150; https://onderzoekmetmensen.nl/nl/trial/27150.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-doi.org/10.1186/s12889-016-3851-x.

Patient and dentist perspectives on collecting patient reported outcomes after painful dental procedures in the National Dental PBRN

BACKGROUND

Dental Patient Reported Outcomes (PROs) relate to a dental patient's subjective experience of their oral health. How practitioners and patients value PROs influences their successful use in practice.

METHODS

Semi-structured interviews were conducted with 22 practitioners and 32 patients who provided feedback on using a mobile health (mHealth) platform to collect the pain experience after dental procedures. A themes analysis was conducted to identify implementation barriers and facilitators.

RESULTS

Five themes were uncovered: (1) Sense of Better Care. (2) Tailored Follow-up based on the dental procedure and patient's pain experience. (3) Effective Messaging and Alerts. (4) Usable Digital Platform. (5) Routine mHealth Integration.

CONCLUSION

Frequent automated and preferably tailored follow-up messages using an mHealth platform provided a positive care experience for patients, while providers felt it saved them time and effort. Patients thought that the mHealth questionnaires were well-developed and of appropriate length. The mHealth platform itself was perceived as user-friendly by users, and most would like to continue using it.

PRACTICAL IMPLICATIONS

Patients are prepared to use mobile phones to report their pain experience after dental procedures. Practitioners will be able to close the post-operative communication gap with their patients, with little interruption of their workflow.

Community Activities in Primary Care: A Literature Review

Community health promotion activities are a useful tool for a proactive approach to healthy lifestyles. However, the implementation of these types of activities at health centers is not standardized. The aim of this review was to analyse the characteristics of community activities undertaken in the primary care setting and substantiate available evidence on their health impact. We conducted a bibliographic review until November 15th, 2023 in the TRIPDATABASE, MEDLINE, EMBASE, and DIALNET databases. We included original papers on interventions, community activities, and actions and/or social prescriptions which had been implemented in a Primary Care setting, included a group approach in at least one session, and described some type of evaluation of the intervention applied. Studies targeted at professionals and those without involvement of the primary care team were excluded. The search identified 1912 potential studies. We included a total of 30 studies, comprising 11 randomized clinical trials, 14 quasi-experimental studies, 1 cohort study, and 4 qualitative studies. The issues most frequently addressed in community activities were healthy habits, physical activity, cardiovascular diseases and diabetes. Community activities can improve the physical and psychological environment of their participants, as well as their level of knowledge about the issues addressed. That said, however, implementation of these types of interventions is not uniform. The existence of a professional community-activity liaison officer at health centers, who would help integrate the health system with the community sector, could serve to standardize implementation and maximize the health impact of these types of interventions.

Effectiveness of the QuitSure Smartphone App for Smoking Cessation: Findings of a Prospective Single Arm Trial

BACKGROUND

Digital therapies, especially smartphone apps for active and continuous smoking cessation support, are strongly emerging as an alternative smoking cessation therapy. In the Indian context, there is a growing interest in the use of app-based smoking cessation programs; however, there is limited evidence regarding their effectiveness in achieving long-term continuous abstinence.

OBJECTIVE

This study aimed to evaluate the long-term abstinence effect (up to 30-d abstinence postprogram completion) of a smartphone app, QuitSure, for smoking cessation in active smokers from India.

METHODS

In this prospective single-arm study, participants who signed up for the QuitSure app were enrolled in this study. The primary end point was the prolonged abstinence (PA) rate from weeks 1 to 4 (day 7 to day 30). Furthermore, data for withdrawal symptoms, relapse reasons, and reasons for not continuing the program were also assessed.

RESULTS

The quit rate was calculated considering only the participants who followed up and completed the survey sent to them (per protocol) at day 7 and at day 30, respectively. The PA rate at day 7 was found to be 64.5% (111/172; 95% CI 56% to 72%), and the PA rate at day 30 was found to be 55.8% (72/129; 95% CI 45% to 65%). Within the 7-day abstinence period, 60.4% (67/111) of the participants did not have any withdrawal symptoms. The most common mild withdrawal symptoms were mild sleep disturbance (21/111, 18.9%), mild digestive changes (19/111, 17.1%), and coughing (17/111, 15.3%). Severe withdrawal symptoms were rare, with only 5.4% (6/111) experiencing them. For those achieving 30-day postprogram abstinence, 85% (61/72) had no mild withdrawal symptoms, and 99% (71/72) had no severe withdrawal symptoms. Among successful quitters at day 7, a total of 72.1% (80/111) reported minimal to no cravings, which increased to 88% (63/72) at day 30. Furthermore, 78% (56/72) of those with PA at day 30 reported no change in weight or reduced weight. Among participants experiencing relapse, 48% (28/58) cited intense cravings, 28% (16/58) mentioned facing a tragedy, and 26% (15/58) reported relapsing due to alcohol consumption. The PA rates as a result of the QuitSure program were found to be better than those reported in the results of other smoking-cessation app programs' studies.

CONCLUSIONS

The QuitSure app yields high PA rates and ameliorates symptoms associated with smoking cessation. In order to obtain conclusive evidence regarding the effectiveness and efficacy of the QuitSure program, future research should include appropriate control measures. Nevertheless, the QuitSure program can serve as a valuable adjunct to a conventional smoking cessation treatment program to aid sustained abstinence.

Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022

BACKGROUND

Mental health problems are the most common morbidities of women during the prenatal period. In LMICs mobile phones have been identified as a good vehicle for monitoring individuals with a high risk of mental health conditions. However, evidence is scarce and the purpose of this study was to assess the intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, Ethiopia 2022.

METHODS AND MATERIALS

An institutional-based cross-sectional study design was conducted from May 20th to June 20th, 2022. A total of 715 prenatal women were included and a systematic random sampling technique was employed. An interviewer-administered structured questionnaire was used. Collected data was exported to SPSS version 25 for the descriptive part, and AMOS 26 structural equation modeling was also used to describe and assess the degree and significance of relationships between variables.

RESULTS

A total of 699 (97.8% response rate) responded to complete all the questionnaires. About 530 (77.3%) 95% CI (74%-80.3%) of women intended to use a mobile phone to receive mental health support. The perceived usefulness has a positive effect on attitude (β = 0.391, p < 0.001) and intention to use (β = 0.253, p < 0.001). The perceived ease of use influences perceived usefulness (β = 0.253, p < 0.001) and attitude β = 0.579, p < 0.001). The intention to use is positively affected by attitude (β = 0.662, p < 0.001).Trust has a positive effect on perceived usefulness (β = 0.580, p < 0.001) and intention to use (β = 0.113, p = 0.005). Subjective norm has a direct positive effect on perceived usefulness (β = 0.248, p < 0.001). Attitude serves as a partial mediator between perceived usefulness and intention to use and a complete mediating role between perceived ease of use and intention to use.

CONCLUSION

The level of intention to use a mobile phone among prenatal women is relatively high and attitude, perceived usefulness, and trust had direct positive effects on intention to use a mobile phone. Therefore, hospitals and healthcare providers should take proactive measures to implement the strategies and policies for providing mobile phone-based mental health support to prenatal women in remote areas.

Design, development and evaluation of a mobile-based self-care application for patients with COVID-19 not requiring hospitalization; a study of Northwest of Iran

BACKGROUND

Given the effective role of a mobile applications in disease management, disease monitoring, and self-care in patients with COVID-19 disease, we aimed to design, development and evaluation of a self-care Mobile app for COVID-19 patients not requiring hospitalization.

METHODS

The design, development and evaluation the usability of the self-care and education mobile app for patients with COVID-19 disease were conducted in two main phases at 2021 in Northwest of IRAN; (1) Determine the features and capabilities and (2) Design, development and evaluation of self-care mobile App. JAVA programming languages and Android Operating System were used and selected to design and development of a mobile app. There were 25 participants who conducted evaluations of the mobile app's usability and impact using the mobile health app usability a Questionnaire of User Interface Satisfaction was administered to assess the usability of the developed application. The results were analyzed via Excel 2013.

RESULTS

The model of developing a mobile app as an Information System was the Waterfall model. The smartphone application based on a set of capabilities and features was designed and consists of two main parts: the login screen for user registration, and the main home menu. The user interface includes three main pages or activities; (a) Main Menu for quick access to all of the pages, (b) Symptom management and monitoring to monitor the signs and symptoms during the illness, and (c) Set Reminders and Alarms to notify patients. The users' mean score of the application usability was calculated as 7.91 out of 9 indicating a good level of satisfaction.

CONCLUSION

This app can be a guideline and a useful tools for managing and monitoring symptoms, reminding medications, and implementing self-care instructions in outpatients. The authors suggest evaluating the efficacy and functionality test of mobile-based applications for COVID-19 in clinical trial studies.

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.

Implementing smoking cessation in routine primary care-a qualitative study

Background

The use of digital tools has been proposed as a solution to some of the challenges of providing preventative services in primary care. Although there is a general acceptance among patients to use digital self-help tools to quit smoking, and healthcare organizations are increasingly urged to incorporate these tools in clinical practice, it is unclear how and for whom these innovations can be incorporated into clinical practice.

Objectives

To explore health care professionals' perceptions about smoking cessation practice in routine primary care and the use of digital tools in this work.

Methods

A qualitative study with nine in-depth telephone interviews with health care professionals working in primary care in Sweden. Convenience sampling and snowball technique was used as recruitment strategy. Informants included registered, district and auxiliary nurses as well as behavioral therapists. All informants were female, between 43 and 57 years old and experience of working with smoking cessation in primary care and possibility to recommend digital interventions to smokers.

Results

Informants described smoking cessation practice in primary care as (i) identifying smoking patients, (ii) pursuing standardized routines for smoking cessation practice and (iii) keeping smoking cessation practice on the agenda. Digital tools were described by informants to be used in different ways: (i) replicating practice, (ii) complementing practice and (iii) enabling access to health care practitioners. Finally, the analysis showed that patients' expectations and behaviors contributed to how and when smoking cessation practice was conducted, including the use of digital tools.

Conclusions

Implementing smoking cessation practice in primary care in Sweden encompass continuous work of reaching smoking patients, building buy-in among peers and keeping tobacco on the practice agenda. Digital interventions are used to replicate, complement and enabling access to care. The findings suggest that poor continuity of staff and negative attitudes towards preventative work may challenge smoking cessation practice. However, societal changes in the awareness of the health risks of tobacco use including shifting social norms regarding the acceptance of smoking may contribute to a normalization of speaking about smoking in primary care practice. Increased knowledge is needed on how, and for whom digital tools can be incorporated in clinical practice.

Estimating the true effectiveness of smoking cessation interventions under variable comparator conditions: A systematic review and meta-regression

BACKGROUND AND AIMS

Behavioural smoking cessation trials have used comparators that vary considerably between trials. Although some previous meta-analyses made attempts to account for variability in comparators, these relied on subsets of trials and incomplete data on comparators. This study aimed to estimate the relative effectiveness of (individual) smoking cessation interventions while accounting for variability in comparators using comprehensive data on experimental and comparator interventions.

METHODS

A systematic review and meta-regression was conducted including 172 randomised controlled trials with at least 6 months follow-up and biochemically verified smoking cessation. Authors were contacted to obtain unpublished information. This information was coded in terms of active content and attributes of the study population and methods. Meta-regression was used to create a model predicting smoking cessation outcomes. This model was used to re-estimate intervention effects, as if all interventions have been evaluated against the same comparators. Outcome measures included log odds of smoking cessation for the meta-regression models and smoking cessation differences and ratios to compare relative effectiveness.

RESULTS

The meta-regression model predicted smoking cessation rates well (pseudo R2  = 0.44). Standardising the comparator had substantial impact on conclusions regarding the (relative) effectiveness of trials and types of intervention. Compared with a 'no support comparator', self-help was 1.33 times (95% CI = 1.16-1.49), brief physician advice 1.61 times (95% CI = 1.31-1.90), nurse individual counselling 1.76 times (95% CI = 1.62-1.90), psychologist individual counselling 2.04 times (95% CI = 1.95-2.15) and group psychologist interventions 2.06 times (95% CI = 1.92-2.20) more effective. Notably, more elaborate experimental interventions (e.g. psychologist counselling) were typically compared with more elaborate comparators, masking their effectiveness.

CONCLUSIONS

Comparator variability and underreporting of comparators obscures the interpretation, comparison and generalisability of behavioural smoking cessation trials. Comparator variability should, therefore, be taken into account when interpreting and synthesising evidence from trials. Otherwise, policymakers, practitioners and researchers may draw incorrect conclusions about the (cost) effectiveness of smoking cessation interventions and their constituent components.

Non-pharmacological interventions for smoking cessation: analysis of systematic reviews and meta-analyses

BACKGROUND

Although non-pharmacological smoking cessation measures have been widely used among smokers, current research evidence on the effects of smoking cessation is inconsistent and of mixed quality. Moreover, there is a lack of comprehensive evidence synthesis. This study seeks to systematically identify, describe, and evaluate the available evidence for non-pharmacological interventions in smoking populations through evidence mapping (EM), and to search for best-practice smoking cessation programs.

METHODS

A comprehensive search for relevant studies published from the establishment of the library to January 8, 2023, was conducted in PubMed, Web of Science, Embase, the Cochrane Library, CNKI, CBM, Wan Fang, and VIP. Two authors independently assessed eligibility and extracted data. The PRISMA statement and AMSTAR 2 tool were used to evaluate the report quality and methodology quality of systematic reviews/meta-analyses (SRs/MAs), respectively. Bubble plots were utilized to display information, such as the study population, intervention type, evidence quality, and original study sample size.

RESULTS

A total of 145 SRs/MAs regarding non-pharmacological interventions for smoking cessation were investigated, with 20 types of interventions identified. The most commonly used interventions were cognitive behaviour education (n = 32, 22.07%), professional counselling (n = 20, 13.79%), and non-nicotine electronic cigarettes (e-cigarettes) (n = 13, 8.97%). Among them, counselling and behavioural support can improve smoking cessation rates, but the effect varies depending on the characteristics of the support provided. These findings are consistent with previous SRs/MAs. The general population (n = 108, 74.48%) was the main cohort included in the SRs/MAs. The total score of PRISMA for the quality of the reports ranged from 8 to 27, and 13 studies (8.97%) were rated as high confidence, and nine studies (6.21%) as moderate confidence, in the AMSTAR 2 confidence rating.

CONCLUSIONS

The abstinence effect of cognitive behaviour education and money incentive intervention has advantages, and non-nicotine e-cigarettes appear to help some smokers transition to less harmful replacement tools. However, the methodological shortcomings of SRs/MAs should be considered. Therefore, to better guide future practice in the field of non-pharmacological smoking cessation, it is essential to improve the methodological quality of SRs and carry out high-quality randomized controlled trials (RCTs).

Use of the Smoking Cessation App Ex-Smokers iCoach and Associations With Smoking-Related Outcomes Over Time in a Large Sample of European Smokers: Retrospective Observational Study

BACKGROUND

Digital interventions are increasingly used to support smoking cessation. Ex-smokers iCoach was a widely available app for smoking cessation used by 404,551 European smokers between June 15, 2011, and June 21, 2013. This provides a unique opportunity to investigate the uptake of a freely available digital smoking cessation intervention and its effects on smoking-related outcomes.

OBJECTIVE

We aimed to investigate whether there were distinct trajectories of iCoach use, examine which baseline characteristics were associated with user groups (based on the intensity of use), and assess if and how these groups were associated with smoking-related outcomes.

METHODS

Analyses were performed using data from iCoach users registered between June 15, 2011, and June 21, 2013. Smoking-related data were collected at baseline and every 3 months thereafter, with a maximum of 8 follow-ups. First, group-based modeling was applied to detect distinct trajectories of app use. This was performed in a subset of steady users who had completed at least 1 follow-up measurement. Second, ordinal logistic regression was used to assess the baseline characteristics that were associated with user group membership. Finally, generalized estimating equations were used to examine the association between the user groups and smoking status, quitting stage, and self-efficacy over time.

RESULTS

Of the 311,567 iCoach users, a subset of 26,785 (8.6%) steady iCoach users were identified and categorized into 4 distinct user groups: low (n=17,422, 65.04%), mild (n=4088, 15.26%), moderate (n=4415, 16.48%), and intensive (n=860, 3.21%) users. Older users and users who found it important to quit smoking had higher odds of more intensive app use, whereas men, employed users, heavy smokers, and users with higher self-efficacy scores had lower odds of more intensive app use. User groups were significantly associated with subsequent smoking status, quitting stage, and self-efficacy over time. For all groups, over time, the probability of being a smoker decreased, whereas the probability of being in an improved quitting stage increased, as did the self-efficacy to quit smoking. For all outcomes, the greatest change was observed between baseline and the first follow-up at 3 months. In the intensive user group, the greatest change was seen between baseline and the 9-month follow-up, with the observed change declining gradually in moderate, mild, and low users.

CONCLUSIONS

In the subset of steady iCoach users, more intensive app use was associated with higher smoking cessation rates, increased quitting stage, and higher self-efficacy to quit smoking over time. These users seemed to benefit most from the app in the first 3 months of use. Women and older users were more likely to use the app more intensively. Additionally, users who found quitting difficult used the iCoach app more intensively and grew more confident in their ability to quit over time.

Integrating the "Quit and Stay Quit Monday" Model into Smoking Cessation Services for Smokers with Mental Health Conditions: A Pilot Randomized Controlled Trial

Introduction

People with mental health conditions (MHCs) are less likely to achieve long-term abstinence than people without MHCs. The Quit and Stay Quit Monday (QSQM) model offers a long-term approach to treating tobacco use by encouraging people to quit, requit, or recommit to quit smoking every Monday.

Aim

To evaluate the efficacy, patient satisfaction, and patient engagement with an intervention that integrated the QSQM model into multicomponent smoking cessation services among people with an MHC.

Methods

This was a randomized controlled pilot trial. Eligibility criteria were as follows: (1) ≥18 years old, (2) smoked a cigarette in the past 30 days, (3) diagnosis of an ICD-10 MHC, (4) interest in quitting smoking, (5) able to receive services in English, and (5) had an active email and a cell phone. The intervention group (n = 33) received QSQM-focused telephone coaching, a weekly QSQM email newsletter, a SmokefreeTXT anchored around a Monday quit date, and 4 weeks of nicotine replacement therapy (NRT). The control group (n = 36) received information about contacting their state Quitline for usual services. Primary outcomes were self-reported quit attempts, 7-day abstinence, and intervention satisfaction at 3 months.

Results

Twenty-four participants (73%) in the intervention group began telephone coaching, 26 (79%) enrolled in the QSQM email newsletter, 19 (58%) enrolled in SmokefreeTXT, and 15 (46%) used NRT. Using a penalized intent-to-treat approach, quit attempts in the intervention and control groups were 63.6% and 38.9% (OR 2.75, 95% CI 1.03-7.30), respectively. Seven-day abstinence in the two groups was 12.1% and 5.6% (OR 2.35, 95% CI 0.40-13.74), respectively. Of the 15 intervention group participants who set a quit date during the intervention, 13 (86.7%) selected a Monday quit day. Qualitative interviews revealed positive participant experiences with picking a Monday quit day. On follow-up surveys, 89.5%, 69.3%, and 64.3% of intervention participants reported that the counseling, QSQM email, and text messaging, respectively, were very or somewhat helpful.

Conclusions

The QSQM model was acceptable and potentially efficacious among people with MHCs, but intervention engagement and satisfaction were modest. Future research should adapt or develop new QSQM delivery approaches to improve patient engagement and potential efficacy of the model. This trial is registered with clinicaltrials.gov (NCT04512248).

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.

Effect of Mobile Phone Text Messaging Self-Management Support for Patients With Diabetes or Coronary Heart Disease in a Chronic Disease Management Program (SupportMe) on Blood Pressure: Pragmatic Randomized Controlled Trial

BACKGROUND

Maintaining engagement and support for patients with chronic diseases is challenging. SMS text messaging programs have complemented patient care in a variety of situations. However, such programs have not been widely translated into routine care.

OBJECTIVE

We aimed to examine the implementation and utility of a customized SMS text message-based support program for patients with type 2 diabetes (T2D), coronary heart disease, or both within a chronic disease integrated care program.

METHODS

We conducted a 6-month pragmatic parallel-group, single-blind randomized controlled trial that recruited people with T2D or coronary heart disease. Intervention participants received 4 semipersonalized SMS text messages per week providing self-management support to supplement standard care. Preprogrammed algorithms customized content based on participant characteristics, and the messages were sent at random times of the day and in random order by a fully automated SMS text messaging engine. Control participants received standard care and only administrative SMS text messages. The primary outcome was systolic blood pressure. Evaluations were conducted face to face whenever possible by researchers blinded to randomization. Participants with T2D were evaluated for glycated hemoglobin level. Participant-reported experience measures were evaluated using questionnaires and focus groups and summarized using proportions and thematic analysis.

RESULTS

A total of 902 participants were randomized (n=448, 49.7% to the intervention group and n=454, 50.3% to the control group). Primary outcome data were available for 89.5% (807/902) of the participants. At 6 months, there was no difference in systolic blood pressure between the intervention and control arms (adjusted mean difference=0.9 mm Hg, 95% CI -1.1 to 2.1; P=.38). Of 642 participants with T2D, there was no difference in glycated hemoglobin (adjusted mean difference=0.1%, 95% CI -0.1% to 0.3%; P=.35). Self-reported medication adherence was better in the intervention group (relative risk=0.82, 95% CI 0.68-1.00; P=.045). Participants reported that the SMS text messages were useful (298/344, 86.6%) and easily understood (336/344, 97.7%) and motivated change (217/344, 63.1%). The lack of bidirectional messaging was identified as a barrier.

CONCLUSIONS

The intervention did not improve blood pressure in this cohort, possibly because of high clinician commitment to improved routine patient care as part of the chronic disease management program as well as favorable baseline metrics. There was high program engagement, acceptability, and perceived value. Feasibility as part of an integrated care program was demonstrated. SMS text messaging programs may supplement chronic disease management and support self-care.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12616001689460; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371769&isReview=true.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2018-025923.

Effect of smoking-related COVID-19 risk messaging on smoking cessation in community smokers: A pragmatic randomized controlled trial

INTRODUCTION

Observational and experimental studies have suggested that messaging on smoking-related COVID-19 risk may promote smoking abstinence, but evidence from randomized clinical trials (RCTs) is lacking.

METHODS

This was a pragmatic RCT in Hong Kong, China, to compare the effectiveness of communicating smoking-related COVID-19 risk with generic cessation support on abstinence. Both groups received brief cessation advice at baseline. The intervention group received messaging on smoking-related COVID-19 risk and cessation support via instant messaging for three months (16 messages in total), which highlighted the increased risk of severe COVID-19 and deaths, and potentially higher risk of viral exposure (e.g. due to mask removal) for smokers. The control group received generic text messaging support for three months (16 messages). The primary outcomes were biochemically validated 7-day point prevalence abstinence (PPA) at 3 and 6 months. Intention to treat analyses was used.

RESULTS

Between 13 June and 30 October 2020, 1166 participants were randomly assigned to an intervention (n=583) or control (n=583) group. By intention-to-treat, validated 7-day PPA did not significantly differ between the intervention and control groups at three months (9.6% and 11.8%, relative risk, RR=0.81; 95% CI: 0.58-1.13, p=0.22) or six months (9.3% and 11.7%, RR=0.79; 95% CI: 0.57-1.11, p=0.18). A higher perceived severity of COVID-19 in smokers at baseline was associated with a greater validated 7-day PPA at six months, and a marginally significant intervention effect on changes in perceived severity from baseline through 6 months was found (p for group × time interaction = 0.08).

CONCLUSIONS

Communicating smoking-related COVID-19 risk via instant messaging was not more effective in increasing smoking abstinence than generic cessation support.

TRIAL REGISTRATION

The study is registered on ClinicalTrials.gov Identifier: NCT04399967.

Challenges and perspectives of tobacco cessation in special groups of patients and populations

During the first 2 years of the coronavirus disease 2019 pandemic, health systems worldwide were put under extreme pressure, and healthcare professionals had to manage unprecedented health crises as well as provide healthcare services to an increased number of patients. Therefore, public health policies with respect to smoking and education of the general population regarding the harmful effects of active and second-hand smoking may not have received adequate attention during this period. More specifically, certain subpopulations suffering from chronic diseases may not have received adequate information about the effects of smoking on the course and outcome of their disease; high-level, evidence-based pharmaceutical therapies; and the potential for follow-up. However, adequate education and awareness regarding short- and long-term health benefits from smoking cessation for the general population as well as special subgroups remains of utmost importance. Healthcare professionals should understand that it is only through high-quality evidence and results from independent studies that they will be able to provide their expertise and scientific knowledge concerning newer tobacco products and their effects on human health.

Efficacy of smartphone applications to help cancer patients quit smoking: Protocol of the Quit2Heal randomized controlled trial

Cigarette smoking is highly prevalent among cancer patients in the United States (US), with up to half of cancer patients smoking at the time of their initial cancer diagnosis. However, evidence-based cessation programs are rarely implemented in oncology care, and smoking is not consistently treated in cancer treatment settings. Consequently, there is an urgent need for accessible and efficacious cessation treatments that are uniquely tailored to the needs of cancer patients. Here we describe the design and implementation of a randomized controlled trial (RCT) testing the efficacy of a smartphone app (Quit2Heal) versus a US Clinical Practice Guidelines-based app (QuitGuide) for smoking cessation among a planned sample of 422 cancer patients. Quit2Heal is designed to address cancer-related shame, stigma, depression, anxiety, and knowledge about the consequences of smoking/quitting. Quit2Heal is based on the principles of Acceptance and Commitment Therapy, a behavioral therapy that teaches skills for accepting cravings to smoke without smoking, values-driven motivation to quit, and preventing relapse. The primary aim of the RCT is to determine whether Quit2Heal has significantly higher self-reported 30-day point prevalence abstinence at 12 months relative to QuitGuide. The trial will also determine whether Quit2Heal's effect on cessation is (1) mediated by improvements in cancer-related shame, stigma, depression, anxiety, and knowledge about the consequences of smoking/quitting; and (2) moderated by baseline factors (e.g., cancer type, stage, time since diagnosis). If successful, Quit2Heal will offer a more efficacious, broadly scalable smoking cessation treatment that could be implemented alongside existing oncology care, thereby improving cancer outcomes.

The Craving-Manager smartphone app designed to diagnose substance use/addictive disorders, and manage craving and individual predictors of relapse: a study protocol for a multicenter randomized controlled trial

Background

The rate of individuals with addiction who are currently treated are low, and this can be explained by barriers such as stigma, desire to cope alone, and difficulty to access treatment. These barriers could be overcome by mobile technologies. EMI (Ecological Momentary Intervention) is a treatment procedure characterized by the delivery of interventions (messages on smartphones) to people in their daily lives. EMI presents opportunities for treatments to be available to people during times and in situations when they are most needed. Craving is a strong predictor of relapse and a key target for addiction treatment. Studies using Ecological Momentary Assessment (EMA) method have revealed that, in daily life, person-specific cues could precipitate craving, that in turn, is associated with a higher probability to report substance use and relapse in the following hours. Assessment and management of these specific situations in daily life could help to decrease addictive use and avoid relapse. The Craving-Manager smartphone app has been designed to diagnose addictive disorders, and assess and manage craving as well as individual predictors of use/relapse. It delivers specific and individualized interventions (counseling messages) composed of evidence-based addiction treatments approaches (cognitive behavioral therapy and mindfulness). The Craving-Manager app can be used for any addiction (substance or behavior). The objective of this protocol is to evaluate the efficacy of the Craving-Manager app in decreasing use (of primary substance(s)/addictive behavior(s)) over 4 weeks, among individuals on a waiting list for outpatient addiction treatment.

Methods/design

This multicenter double-blind randomized controlled trial (RCT) will compare two parallel groups: experimental group (full interventional version of the app, 4 weeks, EMA + EMI), versus control group (restricted version of the app, 4 weeks, only EMA). Two hundred and seventy-four participants will be recruited in 6 addiction treatment centers in France.

Discussion

This RCT will provide indication on how the Craving-Manager app will reduce addictive use (e.g., better craving management, better stimulus control) in both substance and behavioral addictions. If its efficacy is confirmed, the app could offer the possibility of an easy to use and personalized intervention accessible to the greatest number of individuals with addiction.

Clinical Trial Registration

ClinicalTrials.gov: NCT04732676.

Smokers' user experience of smoking cessation apps: A systematic review

OBJECTIVES

To explore how smokers view common functions and characteristics of smoking cessation apps.

DESIGN

Systematic review.

SEARCH SOURCES

CINAHL PLUS, MEDLINE, PsycINFO, EMBASE, IEEE Xplore, ACM Digital Library, and Google Scholar.

REVIEW METHODS

Seven digital databases were searched separately using relevant search terms. Search results were uploaded to Covidence. Inclusion and exclusion criteria were identified with the expert team in advance. Titles, abstracts, and full texts were screened by two reviewers independently. Any disagreements were discussed in research meetings. Pertinent data were extracted and analysed using qualitative content analysis. Findings were presented in a narrative approach.

RESULTS

28 studies were included in this review. The overarching themes were app functionality and app characteristics. Under app "functionality", six subthemes emerged: 1) education; 2) tracking; 3) social support; 4) compensation; 5) distraction, and 6) reminding. Under "app characteristics", five subthemes emerged: 1) simplification, 2) personalisation, 3) diverse content forms, 4) interactivity, and 5) privacy and security.

CONCLUSION

Understanding user needs and expectations is crucial for developing a programme theory for smoking cessation app interventions. Relevant needs identified in this review should be linked to broader theories of smoking cessation and app-based intervention.

Effect of mobile interventions with nicotine replacement therapy sampling on long-term smoking cessation in community smokers: A pragmatic randomized clinical trial

INTRODUCTION

Mobile interventions enable personalized behavioral support that could improve smoking cessation (SC) in smokers ready to quit. Scalable interventions, including unmotivated smokers, are needed. We evaluated the effect of personalized behavioral support through mobile interventions plus nicotine replacement therapy sampling (NRT-S) on SC in Hong Kong community smokers.

METHODS

A total of 664 adult daily cigarette smokers (74.4% male, 51.7% not ready to quit in 30 days) were proactively recruited from smoking hotspots and individually randomized (1:1) to the intervention and control groups (each, n=332). Both groups received brief advice and active referral to SC services. The intervention group received 1-week NRT-S at baseline and 12-week personalized behavioral support through SC advisor-delivered Instant Messaging (IM) and a fully automated chatbot. The control group received regular text messages regarding general health at a similar frequency. Primary outcomes were carbon monoxide-validated smoking abstinence at 6 and 12 months post-treatment initiation. Secondary outcomes included self-reported 7-day point-prevalence and 24-week continuous abstinence, quit attempts, smoking reduction, and SC service use at 6 and 12 months.

RESULTS

By intention-to-treat, the intervention group did not significantly increase validated abstinence at 6 months (3.9% vs 3.0%, OR=1.31; 95% CI: 0.57–3.04) and 12 months (5.4% vs 4.5%, OR=1.21; 95% CI: 0.60–2.45), as were self-reported 7-day point-prevalence abstinence, smoking reduction, and SC service use at 6 and 12 months. More participants in the intervention than control group made a quit attempt by 6 months (47.0% vs 38.0%, OR=1.45; 95% CI: 1.06–1.97). Intervention engagement rates were low, but engagement in IM alone or combined with chatbot showed higher abstinence at 6 months (adjusted odds ratios, AORs=4.71 and 8.95, both p<0.05).

CONCLUSIONS

Personalized behavioral support through mobile interventions plus NRT-S did not significantly improve abstinence in community smokers compared to text only messaging. The suboptimal intervention engagement needs to be addressed in future studies.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04001972.

Mobile-phone text messaging to promote ideal cardiovascular health in women

OBJECTIVE

Ideal cardiovascular health (CVH) was developed to promote CVH as a key component of primordial prevention. Mobile short message service (SMS) is useful for improving health behaviours. We aim to test the effectiveness of SMS intervention in women to improve CVH.

METHODS

In a single-blinded, randomised, controlled study, 620 women, aged 35-70 years, without cardiovascular disease, were enrolled in SMS intervention versus no SMS. CVH metrics by self-report, and biochemical laboratory, anthropometric and blood pressure measurements were collected during home visits at baseline and 9 months. Women were categorised as having poor (0-2), intermediate (3-4) or ideal (5-7) CVH according to the number of ideal CVH metrics. Participants were randomised 1:1 to SMS intervention versus control. SMS was sent every 5-6 days for 9 months. The primary outcome was the difference in the proportion of women with ideal CVH between SMS and control groups at 9 months. Rates of intermediate CVH, poor CVH and each of the seven ideal CV health metrics at 9 months were key secondary endpoints.

RESULTS

At 9 months, there was no significant difference between groups for the primary outcome (16.3% at baseline and 13.3% at 9 months, and 10.1% and 11.1%, in SMS and control groups, respectively, adjusted RR 1.0; 95% CI 0.6 to 1.6). Similarly, there were no significant differences between groups for the key secondary endpoints. SMS had an acceptance rate of 94.9%.

CONCLUSIONS

Behavioural SMS intervention did not improve rates of ideal CVH in women, despite being feasible and well received.

TRIAL REGISTRATION NUMBER

6377.

Impact of patient and provider nudges on addressing herpes zoster vaccine series completion

OBJECTIVES

To determine the combined impact of provider-facing and text message-based, patient nudges on herpes zoster vaccine series completion.

METHODS

Following a period during which Kroger Health implemented provider facing nudges, select US patients that initiated herpes zoster vaccination were randomized to receive timed text messages when the second dose was due and available as part of a quality improvement exercise. Main comparisons were between patients intervened by provider nudge only and those intervened by both provider and patient nudges. Data were assessed by GEE-basedlogistic and linear regression, controlling for available patient- and store-level characteristics, and geospatial analyses.

RESULTS

During the baseline period, 100,627 adults received at least one HZ vaccine dose and 83.9% completed the series within 6 months over 88.6 days (SD: 26.53) on average. In the intervention period, 120,339 adults were vaccinated at least once and series completion was 88.3% (both provider nudges and text messaging) and 85.3% (not texted) during this observation window (both p < 0.0001). Time between doses was shorter for those who received text messages compared to both the baseline period and those in the intervention period that were not texted (both p < 0.001). Controlling for multiple characteristics, the odds of completion improved in the intervention period compared to baseline (OR: 1.07; 95% CI: 1.033-1.111), but a noticeably higher completion odds was observed amongst patients who received a text message in the intervention period (OR: 1.35; 95% CI: 1.286-1.414). Adjusting for patient and pharmacy factors, those who were texted received their second herpes zoster vaccine dose 8.6 days sooner (95% CI: -9.08 - -8.17, p < 0.0001) compared to those intervened by the provider nudge only.

CONCLUSION

The combined use of clinical and patient-focused nudges is a simple mechanism by which pharmacies and other health care access points can address the multi-dose vaccine needs of diverse patient populations.

Personalized Mobile Health for Elderly Home Care: A Systematic Review of Benefits and Challenges

Mobile health as one of the new technologies can be a proper solution to support care provision for the elderly and provide personalized care for them. This study is aimed at reviewing the benefits and challenges of personalized mobile health (PMH) for elderly home care. With a systematic review methodology, 1895 records were retrieved by searching four databases. After removing duplicates, 1703 articles remained. Following full-text examination, 21 articles that met the inclusion criteria were studied in detail, and the output was presented in different tables. The results indicated that 25% of the challenges were related to privacy, cybersecurity, and data ownership (10%), technology (7.5%), and implementation (7.5%). The most frequent benefits were related to cost-saving (17.5%), nurse engagement improvement (10%), and caregiver stress reduction (7.5%). In general, the number of benefits in this study was slightly higher than the challenges, but in order to use PMH technologies, the challenges presented in this study must be carefully considered and a suitable solution must be adopted. Benefits can also be helpful in persuading individuals and health-care providers. This study shed light on those points that need to be highlighted for further work in order to convert the challenges toward benefits.

Intervention targeting and retention, engagement and abstinence outcomes among Latino and White users of Smokefree.gov text messaging programmes: a cross-sectional study

Background

We examined retention, engagement, and abstinence among Latino users of SmokefreeTXT en Español (SFTXTesp), a Latino-targeted text messaging smoking cessation intervention, and Latino and White users of SmokefreeTXT (SFTXT), a non-targeted intervention.

Methods

Data came from 12281 users (1562 Latino SFTXTesp users and 2301 Latino and 8418 White SFTXT users). We conducted time-to-dropout analyses by race/ethnicity. Using logistic regression, we examined associations between intervention targeting, race/ethnicity, and responses to smoking status prompts, an engagement metric, and self-reported abstinence on quit day, intervention end, and one-month follow-up. Age, gender, census region, smoking frequency, cigarettes smoked per day, prequit time, and number of quit attempts were covariates.

Results

Latinos in SFTXTesp (aOR 0.63) and SFTXT (0.88) were less likely to drop out of the intervention than Whites. SFTXTesp Latino users had higher response rates to smoking prompts than SFTXT Latinos users (aORs 1.35, quit day; 1.84, intervention end; 1.82, one-month follow-up). However, SFTXTesp and SFTXT Latino users had lower response rates than Whites (aORs 0.68, 0.45, quit day; 0.60, 0.30, intervention end; 0.64, 0.33, one-month follow-up). Abstinence was equivalent among Latinos in SFTXTesp and SFTXT interventions, but Latinos using SFTXTesp and SFTXT were less likely to be abstinent than Whites (aORs 0.42, 0.41, quit day; 0.45, 0.37, intervention end; and 0.53, 0.35, one-month follow-up).

Conclusion

Linguistic intervention targeting improved retention and engagement among Latinos, but not abstinence. Latinos had higher retention but lower engagement and abstinence rates than Whites. Cultural targeting may engage Latinos in smoking cessation interventions and improve abstinence.

Conversational artificial intelligence interventions to support smoking cessation: A systematic review and meta-analysis

Background

Conversational artificial intelligence (chatbots and dialogue systems) is an emerging tool for tobacco cessation that has the potential to emulate personalised human support and increase engagement. We aimed to determine the effect of conversational artificial intelligence interventions with or without standard tobacco cessation interventions on tobacco cessation outcomes among adults who smoke, compared to no intervention, placebo intervention or an active comparator.

Methods

A comprehensive search of six databases was completed in June 2022. Eligible studies included randomised controlled trials published since 2005. The primary outcome was sustained tobacco abstinence, self-reported and/or biochemically validated, for at least 6 months. Secondary outcomes included point-prevalence abstinence and sustained abstinence of less than 6 months. Two authors independently extracted data on cessation outcomes and completed the risk of bias assessment. Random effects meta-analysis was conducted.

Results

From 819 studies, five randomised controlled trials met inclusion criteria (combined sample size n = 58,796). All studies differed in setting, methodology, intervention, participants and end-points. Interventions included chatbots embedded in multi- and single-component smartphone apps (n = 3), a social media-based (n = 1) chatbot, and an internet-based avatar (n = 1). Random effects meta-analysis of three studies found participants in the conversational artificial intelligence enhanced intervention were significantly more likely to quit smoking at 6-month follow-up compared to control group participants (RR = 1.29, 95% CI (1.13, 1.46), p < 0.001). Loss to follow up was generally high. Risk of bias was high overall.

Conclusion

We found limited but promising evidence on the effectiveness of conversational artificial intelligence interventions for tobacco cessation. Although all studies found benefits from conversational artificial intelligence interventions, results should be interpreted with caution due to high heterogeneity. Given the rapid evolution and potential of artificial intelligence interventions, further well-designed randomised controlled trials following standardised reporting guidelines are warranted in this emerging area.

Changes in attitudes towards smoking during smoking cessation courses for Turkish- and Albanian-speaking migrants in Switzerland and its association with smoking behavior: A latent change score approach

Introduction

Migrant populations usually report higher smoking rates than locals. At the same time, people with a migration background have little or no access to regular smoking cessation treatment. In the last two decades, regular smoking cessation courses were adapted to reach out to Turkish- and Albanian-speaking migrants living in Switzerland. The main aims of the current study were (1) to analyze the effects of an adapted smoking cessation course for Turkish- and Albanian-speaking migrants in Switzerland on attitudes toward smoking and smoking behavior; and (2) to elucidate whether changes in attitudes toward smoking were associated to changes in smoking behavior in the short- and in the long-term.

Methods

A total of 59 smoking cessation courses (Turkish: 37; Albanian: 22) with 436 participants (T: 268; A: 168) held between 2014 and 2019 were evaluated. Attitudes toward smoking and cigarettes smoked per day were assessed at baseline and 3-months follow-up. One-year follow-up calls included assessment of cigarettes smoked per day. Data were analyzed by means of structural equation modeling with latent change scores.

Results

Participation in an adapted smoking cessation course led to a decrease of positive attitudes toward smoking (T: β = -0.65, p < 0.001; A: β = -0.68, p < 0.001) and a decrease of cigarettes smoked per day in the short-term (T: β = -0.58, p < 0.001; A: β = -0.43, p < 0.001) with only Turkish-speaking migrants further reducing their smoking in the long-term (T: β = -0.59, p < 0.001; A: β = -0.14, p = 0.57). Greater decreases in positive attitudes were associated with greater reductions of smoking in the short-term (T: r = 0.39, p < 0.001; A: r = 0.32, p = 0.03), but not in the long-term (T: r = -0.01, p = 0.88; A: r = -0.001, p = 0.99).

Conclusion

The adapted smoking cessation courses fostered changes in positive attitudes toward smoking that were associated with intended behavior change in the short-term. The importance of socio-cognitive characteristics related to behavior change maintenance to further increase treatment effectiveness in the long-term is discussed.

Technology-Based Smoking Cessation for Youth Exiting Foster Care: A Pilot Randomized Trial

Despite high rates of cigarette use, little attention has been paid to screening and cessation services for youth in foster care. Study aims were to test the feasibility, acceptability, and preliminary efficacy of a technology-based smoking cessation intervention. Study enrollment, satisfaction, and engagement were high in the intervention arm, where readiness to change also significantly increased over time. Intervention and control participants significantly reduced cigarette use at 6-month follow up, though groups did not differ. Technology-based interventions appear to be attractive and offer a potentially scalable link to health care that this vulnerable population may not otherwise seek.

A Text-Based Smoking Cessation Intervention for Sexual and Gender Minority Groups: Protocol for a Feasibility Trial

BACKGROUND

Smoking among sexual and gender minority (SGM) groups, which include lesbian, gay, bisexual, transgender, and queer individuals, has been reported to be highly prevalent. This is attributed to several factors, including minority-specific stress and targeted tobacco marketing. Therefore, this population is at an increased risk for tobacco-related diseases. SMS text messaging programs have been found to be effective for smoking cessation and appeal to traditionally hard-to-reach populations over other interventions. It has also been suggested that targeted and tailored interventions could be more effective among SGM smokers because they can be designed to assure a safe, validating health care environment that enhances receptivity to cessation.

OBJECTIVE

The aim of this study is to develop SmokefreeSGM, a text-based smoking cessation program tailored to and tested among SGM smokers.

METHODS

The study consists of three phases, culminating in a feasibility trial. In Phase 1, our research team will collaborate with a Community Advisory Board to develop and pretest the design of SmokefreeSGM. In Phase 2, the tailored text messaging program will be beta tested among 16 SGM smokers. Our research team will use a mixed-methods approach to collect and analyze data from participants who will inform the refinement of SmokefreeSGM. In Phase 3, a feasibility trial will be conducted among 80 SGM smokers either enrolled in SmokefreeSGM or SmokefreeTXT, the original text-based program developed by the National Cancer Institute for the general population. Our research team will examine recruitment, retention, and smoking abstinence rates at 1-, 3-, and 6-month follow-up. Additionally, a qualitative interview will be conducted among 32 participants to evaluate the feasibility and acceptability of the programs (SmokefreeSGM and SmokefreeTXT).

RESULTS

This study received approval from The University of Texas Health Science Center at Houston Committee for the Protection of Human Subjects to begin research on August 21, 2020. Recruitment for the beta testing of SmokefreeSGM (Phase 2) began in January 2022. We estimate that the feasibility trial (Phase 3) will begin in September 2022 and that results will be available in December 2023.

CONCLUSIONS

Findings from this research effort will help reduce tobacco-related health disparities among SGM smokers by determining the feasibility and acceptability of SmokefreeSGM, an SGM-tailored smoking cessation intervention.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05029362; https://clinicaltrials.gov/ct2/show/NCT05029362.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/42553.

Let's decide what would be convincing, conduct randomized trials with rigorous comparison conditions, and report tests of moderation and publication bias in meta-analyses

We appreciate Jacobson and colleagues' thoughtful commentary on our meta-review of mobile phone-based interventions for mental health. In this response, we address two issues raised: requiring low to moderate heterogeneity (I²<50%) and requiring no evidence of publication bias for evidence to be classified as "convincing." While we agree these represent a high bar, we disagree that these requirements are destined to fail. Other effect sizes reported in the literature, including effect sizes related to mental health interventions and effect sizes related to mobile health (mHealth) interventions (although not their combination) have met requirements for convincing evidence. Jacobson and colleagues argue that features of the mHealth interventions may produce heterogeneity when meta-analyses combine across intervention types. However, several of the effect sizes we reviewed were based on relatively homogeneous portions of the literature and many of the effect sizes we reviewed showed low to moderate heterogeneity. Ideally, future meta-analyses will examine intervention features as moderators of treatment effects. While an absence of publication bias may be a stringent criterion, all but two of the 34 effect sizes we reviewed did not report formal tests of publication bias. Clearly there is a need to reach consensus on how the strength of evidence for mHealth interventions can be evaluated. From our perspective, convincing evidence will ultimately come from large-scale randomized controlled trials employing rigorous comparison conditions along with meta-analyses that do not combine across control condition types, that examine theoretically important moderators, and report formal tests of publication bias. It is this kind of evidence that the public, clinicians, and the scientific community may need to encourage adoptions of mHealth interventions for mental health treatment and prevention.

A general health promotion approach to helping smokers with non-communicable diseases quit smoking: A pilot randomized controlled trial

Background

Despite evidence showing that continued smoking in patients with non-communicable diseases can reduce treatment efficacy and increase the risk of disease progression and multimorbidity, many smoker patients either have no intention to quit or have had failed attempts at quitting.

Objective

To examine the feasibility of a general health promotion approach that uses instant messaging to deliver brief motivational interviewing to help smokers with non-communicable diseases quit smoking.

Methods

In total, 60 participants who had medical follow-up in a special out-patient clinic were randomized into two groups, 30 in the intervention group received brief motivational interviewing to assist them with their chosen behavioral changes, and 30 in the control group received only a smoking cessation booklet. The outcome measures included self-reported 7-day point prevalence of smoking abstinence and any behavioral change reported by the participants at 6 and 12 months. Biochemical validation was performed for those who verbally reported a 7-day point prevalence of smoking abstinence at 12 months.

Results

The majority (95%) of smokers who attended the out-patient clinic owned a smartphone. The response rate was 73.2%. Retention rates at 6-month and 12-month follow-up were 83.3 and 71.7%, respectively. The process evaluation indicated that participants were satisfied with the content of the brief MI messages and appreciated the use of instant messaging as a way to provide them with professional advice and support for managing their health-related lifestyles. The intervention group had a higher biochemically validated abstinence rate than the control group at 12 months (16.7 vs. 6.7 P = 0.23) although the difference was not statistically significant (Adjusted odd ratio 2.4, 95% confidence interval, 0.43-13.75; P = 0.32.), In addition, the proportion of participants reporting a behavioral change was higher in the intervention group at 6 and 12 months.

Conclusion

This study suggested the potential efficacy and feasibility of a general health promotion approach that uses instant messaging to deliver brief motivational interviewing to help smokers with non-communicable diseases quit smoking. The findings can be used to create a new smoking cessation service model that implements a flexible, proactive and personalized approach to help smokers quit smoking.

Clinical trial registration

ClinicalTrials.gov, identifier: NCT03983330.

Adaptive interventions to optimise the mobile phone-based smoking cessation support: study protocol for a sequential, multiple assignment, randomised trial (SMART)

BACKGROUND

Mobile health (mHealth) is promising in developing personalised smoking cessation interventions. By using an adaptive trial design, we aim to evaluate the effectiveness of personalised mHealth intervention in increasing smoking cessation.

METHODS

This study is a two-arm, parallel, accessor-blinded Sequential Multiple-Assignment Randomised Trial (SMART) that randomises 1200 daily cigarette smokers from 70 community sites at two timepoints. In the first phase, participants receive brief cessation advice plus referral assistance to smoking cessation services and are randomly allocated to receive personalised instant messaging (PIM) or regular instant messaging (RIM). In the second phase, PIM participants who are non-responders (i.e. still smoking at 1 month) are randomised to receive either optional combined interventions (multi-media messages, nicotine replacement therapy sampling, financial incentive for active referral, phone counselling, and family/peer support group chat) or continued-PIM. Non-responders in the RIM group are randomised to receive PIM or continued-RIM. Participants who self-report quitting smoking for 7 days or longer at 1 month (responders) in both groups continue to receive the intervention assigned in phase 1. The primary outcomes are biochemical abstinence validated by exhaled carbon monoxide (< 4 ppm) and salivary cotinine (< 10 ng/ml) at 3 and 6 months from treatment initiation. Intention-to-treat analysis will be adopted.

DISCUSSION

This is the first study using a SMART design to evaluate the effect of adaptive mHealth intervention on abstinence in community-recruited daily smokers. If found effective, the proposed intervention will inform the development of adaptive smoking cessation treatment and benefits smokers non-responding to low-intensity mHealth support.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03992742 . Registered on 20 June 2019.

Could COVID expand the future of addiction research? Long-term implications in the pandemic era

BACKGROUND/AIMS

The COVID-19 pandemic has significantly impacted face-to-face research. This has propelled ideas and plans for more remote styles of research and provided new perspectives on conducting research. This paper aimed to identify challenges specific to conducting remote forms of experimental addiction research, although some of these challenges apply to all types of addiction research.

ARGUMENT

The impact of the COVID-19 pandemic has led to important lessons for future addiction research. Although remote research has been conducted for decades, little experimental research has been performed remotely. To do so require a new perspective on what research questions we can ask and could also enable preferential capture of those who may be more reluctant to engage in research based in clinical settings. There may, however, be crucial factors that will compromise this process. We illustrate our argument with three real-world, ongoing case studies centred on gambling behaviour, opioid overdose, and cannabinoid psychopharmacology. We highlight the obstacles to overcome to enable more remote methods of study.

CONCLUSIONS

The future of experimental research and, more generally, addiction research, will be shaped by the pandemic and may result in advantages, such as reaching different populations and conducting addiction research in more naturalistic settings.

Mindfulness-Based Smoking Cessation Delivered Through Telehealth and Text Messaging for Low-Income Smokers: Protocol for a Randomized Controlled Trial

BACKGROUND

Tobacco use is the leading cause of preventable morbidity and mortality. Adults with low income and members of certain racial and ethnic minority groups are less likely to quit, and therefore, they experience profound tobacco-related health disparities. Mindfulness training can increase the rates of smoking cessation and lapse recovery, and telehealth and SMS text messaging have the potential to provide more accessible treatment.

OBJECTIVE

This study aims to test the efficacy of delivering mindfulness-based smoking cessation treatment through text messaging (iQuit Mindfully) and telehealth (group videoconferencing), both as stand-alone interventions and in combination. In addition, it aims to examine the underlying mechanisms of mindfulness treatment.

METHODS

In this 2×2 randomized controlled trial, participants are randomized into 1 of 4 groups based on assignment to iQuit Mindfully text messages (yes or no) and mindfulness videoconference groups (yes or no). The primary outcomes are biochemically verified smoking abstinence at 8, 12, and 24 weeks after the start of treatment. Secondary outcomes include the frequency of home mindfulness practice and self-reported levels of mindfulness, emotions, craving, withdrawal, dependence, self-efficacy, and social support.

RESULTS

Recruitment, treatment, and assessment began in spring and summer 2021, and data collection is expected to continue through spring 2024.

CONCLUSIONS

This project aims to improve smoking cessation outcomes for low-income, racially and ethnically diverse smokers through mindfulness-based telehealth group counseling and text messaging support. We also aim to advance the scientific study of the mechanisms of action of mindfulness treatment, which could inform the development of more efficacious and efficient treatments to reduce tobacco disparities.

TRIAL REGISTRATION

Clinicaltrials.gov NCT04965181; https://clinicaltrials.gov/ct2/show/NCT04965181.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/35688.

Direct Outreach in Bars and Clubs to Enroll Cigarette Smokers in Mobile Cessation Services: Exploratory Study

Background

Cigarette smoking and alcohol use are well known to be concomitant behaviors, but there is a lack of studies related to recruitment of smokers for mobile cessation services at places where alcohol is consumed, such as bars and clubs. Adapting recruitment strategies to expand the reach of cessation programs to where tobacco users are located may help decrease the health-equity gap in tobacco control by improving reach and enrollment of underserved smokers residing in low-income and rural areas who are not reached by traditional cessation services.

Objective

The purpose of this exploratory study was to assess the feasibility of direct outreach in bars, clubs, and restaurants to recruit smokers to Quitxt, our mobile smoking cessation service. Quitxt is delivered through SMS text messaging or Facebook Messenger.

Methods

We collaborated with an advertising agency to conduct in-person recruitment of young adult smokers aged 18-29 years, focusing on urban and rural Spanish-speaking Latino participants, as well as English-speaking rural White and African American participants. Street team members were recruited and trained in a 4-hour session, including a brief introduction to the public health impacts of cigarette smoking and the aims of the project. The street teams made direct, face-to-face contact with smokers in and near smoking areas at 25 bars, clubs, and other venues frequented by young smokers in urban San Antonio and nearby rural areas.

Results

The 3923 interactions by the street teams produced 335 (8.5%) program enrollments. Most participants were English speakers with a mean age of 29.2 (SD 10.6) years and smoked a mean of 8.5 (SD 6.2) cigarettes per day. Among users who responded to questions on gender and ethnicity, 66% (70/106) were women and 56% (60/107) were Hispanic/Latino. Among users ready to make a quit attempt, 22% (17/77) reported 1 tobacco-free day and 16% (10/62) reported maintaining cessation to achieve 1 week without smoking. The response rate to later follow-up questions was low.

Conclusions

Direct outreach in bars and clubs is a useful method for connecting young adult cigarette smokers with mobile cessation services. However, further research is needed to learn more about how mobile services can influence long-term smoking cessation among those recruited through direct outreach, as well as to test the use of incentives in obtaining more useful response rates.

mHealth Interventions to Reduce Physical Inactivity and Sedentary Behavior in Children and Adolescents: Systematic Review and Meta-analysis of Randomized Controlled Trials

Background

Children and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions.

Objective

This review and meta-analysis investigated the effectiveness of mHealth interventions on IPA and SB, with a special focus on the age and level of individualization.

Methods

PubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library were searched for randomized controlled trials published between January 2000 and March 2021. mHealth interventions for primary prevention in children and adolescents addressing behavior change related to IPA and SB were included. Included studies were compared for content characteristics and methodological quality and summarized narratively. In addition, a meta-analysis with a subsequent exploratory meta-regression examining the moderating effects of age and individualization on overall effectiveness was performed.

Results

On the basis of the inclusion criteria, 1.3% (11/828) of the preliminary identified studies were included in the qualitative synthesis, and 1.2% (10/828) were included in the meta-analysis. Trials included a total of 1515 participants (mean age (11.69, SD 0.788 years; 65% male and 35% female) self-reported (3/11, 27%) or device-measured (8/11, 73%) health data on the duration of SB and IPA for an average of 9.3 (SD 5.6) weeks. Studies with high levels of individualization significantly decreased insufficient PA levels (Cohen d=0.33; 95% CI 0.08-0.58; Z=2.55; P=.01), whereas those with low levels of individualization (Cohen d=−0.06; 95% CI −0.32 to 0.20; Z=0.48; P=.63) or targeting SB (Cohen d=−0.11; 95% CI −0.01 to 0.23; Z=1.73; P=.08) indicated no overall significant effect. The heterogeneity of the studies was moderate to low, and significant subgroup differences were found between trials with high and low levels of individualization (χ21=4.0; P=.04; I2=75.2%). Age as a moderator variable showed a small effect; however, the results were not significant, which might have been because of being underpowered.

Conclusions

Evidence suggests that mHealth interventions for children and adolescents can foster moderate reductions in IPA but not SB. Moreover, individualized mHealth interventions to reduce IPA seem to be more effective for adolescents than for children. Although, to date, only a few mHealth studies have addressed inactive and sedentary young people, and their quality of evidence is moderate, these findings indicate the relevance of individualization on the one hand and the difficulties in reducing SB using mHealth interventions on the other.

Trial Registration

PROSPERO CRD42020209417; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=209417

Practice, barriers, and facilitators of healthcare providers in smoking cessation in Mexico

OBJECTIVE

To assess the clinical practice, barriers, and facilitators in promoting smoking cessation in primary healthcare clinics in Mexico City.

MATERIALS AND METHODS

A mixed method design was used. Surveys (n = 70) and semi-structured interviews (n = 9) were conducted with health personnel involved in smoking cessation clinics.

RESULTS

Quantitative data revealed that physicians were more likely than nurses to 1) ask patients if they smoke (57.9% vs 34.5%, p = .057), 2) ask patients if they are interested in quitting smoking (65.7% vs 26.9%, p = .003), 3) provide advice to quit smoking (54.3% vs 29.2%, p = .056), and 4) assess whether pharmacotherapy is needed (21.9% vs 10%, p = .285). Qualitative data showed that nurses were more likely than physicians to report lack of resources to refer patients to smoking cessation services, lack of pharmacotherapy availability, and lack of provider training in smoking cessation. Reported barriers include lack of motivation among patients, lack of time for assessment, long appointment wait times, and lack of training. Reported facilitators include existence of smoking cessation programmes and pharmacotherapy at no cost to the patient, and having a multidisciplinary team.

CONCLUSIONS

Due to numerous barriers, smoking cessation interventions are partially implemented in primary care clinics in Mexico City. A restructuring of services is necessary, and nurses should be given a more prominent role.

Gamification for Machine Learning in Surgical Patient Engagement

Patients and their surgeons face a complex and evolving set of choices in the process of shared decision making. The plan of care must be tailored to individual patient risk factors and values, though objective estimates of risk can be elusive, and these risk factors are often modifiable and can alter the plan of care. Machine learning can perform real-time predictions of outcomes, though these technologies are limited by usability and interpretability. Gamification, or the use of game elements in non-game contexts, may be able to incorporate machine learning technology to help patients optimize their pre-operative risks, reduce in-hospital complications, and hasten recovery. This article proposes a theoretical mobile application to help guide decision making and provide evidence-based, tangible goals for patients and surgeons with the goal of achieving the best possible operative outcome that aligns with patient values.

Digital health RCT interventions for cardiovascular disease risk reduction: a systematic review and meta-analysis

Heart disease is a leading cause of UK mortality. Evidence suggests digital health interventions (DHIs), such as smartphone applications, may reduce cardiovascular risk, but no recent reviews are available. This review examined the effect of DHIs on cardiovascular disease (CVD) risk scores in patients with increased CVD risk, compared to usual care alone. PubMed, Cochrane Database, Medline, and Google Scholar were searched for eligible trials published after 01/01/2010, involving populations with at least one CVD risk factor. Primary outcome was change in CVD risk score (e.g. QRISK3) between baseline and follow-up. Meta-analysis was undertaken using Revman5/STATA using random-effects modelling. Cochrane RoB-2 tool determined risk-of-bias. 6 randomised controlled trials from 36 retrieved articles (16.7%) met inclusion criteria, involving 1,157 patients treated with DHIs alongside usual care, and 1,127 patients offered usual care only (control group). Meta-analysis using random-effects model in STATA showed an inconclusive effect for DHIs as effective compared to usual care (Mean Difference, MD -0.76, 95% CI -1.72, 0.20), with moderate certainty (GRADEpro). Sensitivity analysis by DHI modality suggested automated email messaging was the most effective DHI (MD -1.09, 95% Cl -2.15, -0.03), with moderate certainty (GRADEpro). However, substantial study heterogeneity was noted in main and sensitivity analyses (I2 = 66% and 64% respectively). Quality assessment identified risk-of-bias concerns, particularly for outcome measurement. Findings suggest specific DHIs such as automated email messaging may improve CVD risk outcomes, but were inconclusive for DHIs overall. Further research into specific DHI modalities is required, with longer follow-up.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12553-022-00651-0.

MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions

Advances in digital technologies have created unprecedented opportunities to deliver effective and scalable behavior change interventions. Many digital interventions include multiple components, namely several aspects of the intervention that can be differentiated for systematic investigation. Various types of experimental approaches have been developed in recent years to enable researchers to obtain the empirical evidence necessary for the development of effective multiple-component interventions. These include factorial designs, Sequential Multiple Assignment Randomized Trials (SMARTs), and Micro-Randomized Trials (MRTs). An important challenge facing researchers concerns selecting the right type of design to match their scientific questions. Here, we propose MCMTC – a pragmatic framework that can be used to guide investigators interested in developing digital interventions in deciding which experimental approach to select. This framework includes five questions that investigators are encouraged to answer in the process of selecting the most suitable design: (1) Multiple-component intervention: Is the goal to develop an intervention that includes multiple components; (2) Component selection: Are there open scientific questions about the selection of specific components for inclusion in the intervention; (3) More than a single component: Are there open scientific questions about the inclusion of more than a single component in the intervention; (4) Timing: Are there open scientific questions about the timing of component delivery, that is when to deliver specific components; and (5) Change: Are the components in question designed to address conditions that change relatively slowly (e.g., over months or weeks) or rapidly (e.g., every day, hours, minutes). Throughout we use examples of tobacco cessation digital interventions to illustrate the process of selecting a design by answering these questions. For simplicity we focus exclusively on four experimental approaches—standard two- or multi-arm randomized trials, classic factorial designs, SMARTs, and MRTs—acknowledging that the array of possible experimental approaches for developing digital interventions is not limited to these designs.

Motivations Toward Using Digital Health and Exploring the Possibility of Using Digital Health for Mental Health in Bangladesh University Students: Cross-sectional Questionnaire Study

Background

Digital health is efficacious for the management and prevention of mental health (MH) problems. It is particularly helpful for the young adult population, who appreciate the autonomy digital health provides, and in low-income countries, where the prevalence of MH problems is high but the supply of professionals trained in MH is low.

Objective

The objectives of this study are 2-fold: to determine whether university students in Bangladesh find using digital health for MH promotion acceptable and to examine motivational factors for using digital health for MH.

Methods

This study used a cross-sectional survey to examine the likelihood that university students in Bangladesh (n=311) would use different forms of digital health platforms for MH promotion and assessed drivers of intention to use and actual use of digital health generally and digital health for MH through the lens of the Technology Acceptance Model. The results provided evidence that the university student population in Bangladesh is likely to use digital health to promote their MH.

Results

Social influence (adjusted odds ratio [aOR] 1.68, 95% CI 1.40-2.01; P<.001), ease of use (aOR 1.85, 95% CI 1.35-2.53; P<.001), and perceived usefulness (aOR 4.12, 95% CI 1.79-9.51; P=.001) of digital health were found to be significant drivers of the intention to use general digital health, and having an intention to use digital health (aOR 2.10, 95% CI 1.17-3.78; P=.01) had the greatest influence on actual use of digital health. Social influence (aOR 1.71, 95% CI 1.43-2.04; P<.001), perceived usefulness (aOR 8.92, 95% CI 4.18-19.04; P<.001), and use of general digital health (aOR 2.16, 95% CI 1.18-3.97; P=.01) were associated with higher intention to use digital health for MH. The use of general digital health (aOR 4.19, 95% CI 2.37-7.41; P<.001) was associated with the actual use of digital health for MH, as were greater non–stigma-related barriers to using traditional clinical MH services (aOR 2.05, 95% CI 1.10-3.80; P=.02).

Conclusions

Overall, we see that the use of digital health for MH is acceptable in this population and can be helpful for students who perceive barriers to receiving traditional care. We also gain insight into how to promote the intention to use digital health, which in turn promotes the actual use of digital health.

Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials

Mobile phone-based interventions have been proposed as a means for reducing the burden of disease associated with mental illness. While numerous randomized controlled trials and meta-analyses have investigated this possibility, evidence remains unclear. We conducted a systematic meta-review of meta-analyses examining mobile phone-based interventions tested in randomized controlled trials. We synthesized results from 14 meta-analyses representing 145 randomized controlled trials and 47,940 participants. We identified 34 effect sizes representing unique pairings of participants, intervention, comparisons, and outcome (PICO) and graded the strength of the evidence as using umbrella review methodology. We failed to find convincing evidence of efficacy (i.e., n > 1000, p < 10^-6, I ² < 50%, absence of publication bias); publication bias was rarely assessed for the representative effect sizes. Eight effect sizes provided highly suggestive evidence (i.e., n > 1000, p < 10^-6), including smartphone interventions outperforming inactive controls on measures of psychological symptoms and quality of life (ds = 0.32 to 0.47) and text message-based interventions outperforming non-specific controls and active controls for smoking cessation (ds = 0.31 and 0.19, respectively). The magnitude of effects and strength of evidence tended to diminish as comparison conditions became more rigorous (i.e., inactive to active, non-specific to specific). Four effect sizes provided suggestive evidence, 14 effect sizes provided weak evidence, and eight effect sizes were non-significant. Despite substantial heterogeneity, no moderators were identified. Adverse effects were not reported. Taken together, results support the potential of mobile phone-based interventions and highlight key directions to guide providers, policy makers, clinical trialists, and meta-analysts working in this area.