Outcomes and Device Usage for Fully Automated Internet Interventions Designed for a Smartphone or Personal Computer: The MobileQuit Smoking Cessation Randomized Controlled Trial

Effectiveness of immersive technologies in oral health promotion and education: A systematic review

OBJECTIVE

To evaluate the effectiveness of immersive technologies in oral health promotion and education.

METHODS

An extensive literature review was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) method. This study was systematically performed in six electronic databases (PubMed, Google Scholar, Web of Science, Cochrane, Scopus, and EBSCO). The risk of bias was assessed with the Cochrane tools using RoB 2.0 and ROBINS-I.

RESULTS

PICOS criteria were formulated for study inclusion. The bibliographical search identified 10,074 articles, which were filtered subsequently. Finally, the most pertinent nine articles were included and scrutinized for data synthesis and analysis. This includes five randomized controlled trials and four non-randomized controlled trials in different countries that focused on children (33.3%), adolescents (11.1%), and adults (55.6%). The interventions used virtual reality (VR) and augmented reality (AR) to promote knowledge and attitudes towards oral care, improve toothbrushing performance, and smoking cessation, and reduce anxiety levels in oral health education.

CONCLUSION

This systematic review demonstrates that immersive technologies, including VR and AR, significantly enhance oral health knowledge, attitudes, and self-efficacy, leading to improved health outcomes.

CLINICAL SIGNIFICANCE

Immersive technologies such as VR and AR have the potential to provide innovative and effective methods for enhancing oral health promotion and education, while promoting positive health behaviours, which are crucial for improving overall oral health outcomes.

Digital Smoking Cessation With a Comprehensive Guideline-Based App-Results of a Nationwide, Multicentric, Parallel, Randomized Controlled Trial in Germany

BACKGROUND

Smoking tobacco implies significant health hazards. Digital cessation support can get more smokers in contact with guideline-based cessation. The objective was to test the efficacy of a guideline-based smoking cessation app (NichtraucherHelden®). The hypothesis was a significantly higher cessation rate in the intervention group.

METHODS

The study was a nationwide, multicentric, prospective, parallel, randomized controlled trial in Germany from November 2021 to March 2023. Recruitment took place in medical practices and by telephone via study centers. Eligible participants were adult tobacco-dependent smokers according to ICD-10 (F17.2). Randomization (1:1) was operated by a computer-generated stratified 1:1 block procedure. Intervention (IG; n = 336) and control group (CG; n = 325) were briefly advised with regard to stop smoking, IG was additionally treated with the cessation app. The primary endpoint was the self-reported 7-day-point abstinence after 6 months with an intention to treat analysis. Secondary endpoints comprised prolonged abstinence and biochemically verified abstinence. The study was registered at the German Registry of Clinical Trials (DRKS00025933, UTN U1111-1268-2181) and was approved by the competent ethics committees (leading ethic committee Berlin #Eth-52/20).

RESULTS

Three hundred thirty six participants (IG) and 325 (CG) were analyzed. Seven-day point prevalence was significantly higher in the app group (IG) (20% vs. 10%, OR 2.2 (1.4-3.4)). Additionally, the prolonged abstinence and the objective abstinence rates were significantly higher in the app group.

CONCLUSIONS

The NichtraucherHelden app doubles the abstinence rate. Apps can bridge the gap between the small number of therapeutic offers and the need for modern evidence-based cessation support.

IMPLICATIONS

The study is the first to provide evidence for the feasibility and efficacy of guideline-based digital smoking cessation provided by a smartphone app for the German statutory health insurance (SHI) system. Smoking cessation support by smartphone apps could be broadly distributed and thus bring more smokers in contact with guideline-based cessation support than to date and increase the number of successful quitters substantially.

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.

Preliminary Efficacy of a Cognitive Behavioral Therapy-Based Smartphone App for Smoking Cessation in China: Randomized Controlled Pilot Trial

BACKGROUND

The overall prevalence of cigarette smokers in China is very high, and China's total cigarette consumption makes up more than 40% of the world's consumption. In view of the lack of smoking cessation services and social support in China and the effectiveness of mobile phone apps for quitting smoking in other countries, we carried out a smartphone app-based smoking cessation trial in China.

OBJECTIVE

This study aimed to evaluate the efficacy of a cognitive behavioral therapy (CBT)-based smoking cessation smartphone app among smokers seeking treatment in China.

METHODS

We conducted a randomized controlled, web-based pilot clinical trial in China between February 23 and June 27, 2021. Eligible participants were randomly assigned to the smoking cessation app intervention group or the control group in a ratio of 1:1. The intervention group received the CBT smoking cessation intervention using a smartphone app, and the control group received a "thank you" message. The intervention was 4 weeks long, and the patients were followed up for 4 weeks. The primary outcome was self-reported continuous smoking abstinence at week 4 after the quit date. The secondary outcomes included self-reported 7-day point prevalence of smoking abstinence; reduction of the number of cigarettes smoked per day at weeks 1, 2, 3, and 4; and program acceptability.

RESULTS

A total of 973 people were recruited to quit smoking, of whom 262 completed basic information, 56 were excluded, and 206 were randomized and included in the final analysis. There were 189 (91.7%) men and 17 (8.3%) women, with an average age of 34.46 (SD 7.53) years and an average daily smoking rate of 15.93 (SD 7.10) cigarettes/day. We found 30 (29.7%) of the 101 participants in the intervention group and 7 (6.7%) of the 105 participants in the control group reported continuous smoking cessation after the quit date at week 4 (odds ratio 5.92, 95% CI 3.78-9.26; P<.001). The 7-day point prevalence abstinence rate of the intervention group varied from 42.6% (43/101) to 46.5% (47/101) after 1, 2, 3, and 4 weeks, while the control group varied from 18.1% (19/105) to 26.7% (28/105). Compared to the control group, continued smokers consumed 1.5-3.0 fewer cigarettes per day in the intervention group. The overall program got positive user feedback with a high satisfaction rate (66/87, 76%) and an average Mobile Application Rating Scale user version score of 3.46.

CONCLUSIONS

Our pilot study provided preliminary evidence that the CBT-based smoking cessation smartphone app led to improved smoking quit rates versus control in Chinese smokers. The study demonstrated the CBT-based smartphone app may be an effective and feasible digital treatment model to help smokers quit, which may improve smoking cessation service quality and accessibility in China.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04421170; https://clinicaltrials.gov/study/NCT04421170.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2020-041985.

Effects of interventions on smoking cessation: A systematic review and network meta-analysis

A network meta-analysis (NMA) including randomized controlled trials (RCTs) was conducted to evaluate the effects of different interventions on smoking cessation. Studies were collected from online databases including PubMed, EMBASE, Cochrane Library, and Web of Science based on inclusion and exclusion criteria. Eligible studies were further examined in the NMA to compare the effect of 14 interventions on smoking cessation. Thirty-four studies were examined in the NMA, including a total of 14 interventions and 28 733 participants. The results showed that health education (HE; odds ratio ([OR] = 200.29, 95% CI [1.62, 24 794.61])), other interventions (OI; OR = 29.79, 95% CI [1.07, 882.17]) and multimodal interventions (MUIs; OR = 100.16, 95% CI [2.06, 4867.24]) were better than self-help material (SHM). HE (OR = 243.31, 95% CI [1.39, 42531.33]), MUI (OR = 121.67, 95% CI [1.64, 9004.86]) and financial incentive (FI; OR = 14.09, 95% CI [1.21, 164.31]) had positive effects on smoking cessation rate than smoking cessation or quitting APP (QA). Ranking results showed that HE (83.6%) and motivation interviewing (MI; 69.6%) had better short-term effects on smoking cessation. HE and MUI provided more smoking cessation benefits than SHM and QA. FI was more effective at quitting smoking than QA. Also, HE and MI were more likely to be optimal smoking cessation interventions.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION

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

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

BACKGROUND

Cigarette smoking remains the leading cause of preventable illness and death, underscoring ongoing need for evidence-based solutions. Pivot, a US Clinical Practice Guideline-based mobile smoking cessation program, comprises a personal carbon monoxide breath sensor; a smartphone app; in-app, text-based human-provided coaching; nicotine replacement therapy; and a moderated web-based community. Promising Pivot cohort studies have established the foundation for comparative assessment.

OBJECTIVE

This study aimed to compare engagement, retention, attitudes toward quitting smoking, smoking behavior, and participant feedback between Pivot and QuitGuide, a US Clinical Practice Guideline-based smoking cessation smartphone app from the National Cancer Institute.

METHODS

In this remote pilot randomized controlled trial, cigarette smokers in the United States were recruited on the web and randomized to Pivot or QuitGuide. Participants were offered 12 weeks of free nicotine replacement therapy. Data were self-reported via weekly web-based questionnaires for 12 weeks and at 26 weeks. Outcomes included engagement and retention, attitudes toward quitting smoking, smoking behavior, and participant feedback. The primary outcome was self-reported app openings at 12 weeks. Cessation outcomes included self-reported 7- and 30-day point prevalence abstinence (PPA), abstinence from all tobacco products, and continuous abstinence at 12 and 26 weeks. PPA and continuous abstinence were biovalidated via breath carbon monoxide samples.

RESULTS

Participants comprised 188 smokers (94 Pivot and 94 QuitGuide): mean age 46.4 (SD 9.2) years, 104 (55.3%) women, 128 (68.1%) White individuals, and mean cigarettes per day 17.6 (SD 9.0). Engagement via mean "total app openings through 12 weeks" (primary outcome) was Pivot, 157.9 (SD 210.6) versus QuitGuide, 86.5 (SD 66.3; P<.001). Self-reported 7-day PPA at 12 and 26 weeks was Pivot, 35% (33/94) versus QuitGuide, 28% (26/94; intention to treat [ITT]: P=.28) and Pivot, 36% (34/94) versus QuitGuide, 27% (25/94; ITT: P=.12), respectively. Self-reported 30-day PPA at 12 and 26 weeks was Pivot, 29% (27/94) versus QuitGuide, 22% (21/94; ITT: P=.32) and Pivot, 32% (30/94) versus QuitGuide, 22% (21/94; ITT: P=.12), respectively. The biovalidated abstinence rate at 12 weeks was Pivot, 29% (27/94) versus QuitGuide, 13% (12/94; ITT: P=.008). Biovalidated continuous abstinence at 26 weeks was Pivot, 21% (20/94) versus QuitGuide, 10% (9/94; ITT: P=.03). Participant feedback, including ease of setup, impact on smoking, and likelihood of program recommendation were favorable for Pivot.

CONCLUSIONS

In this randomized controlled trial comparing the app-based smoking cessation programs Pivot and QuitGuide, Pivot participants had higher engagement and biovalidated cessation rates and more favorable user feedback at 12 and 26 weeks. These findings support Pivot as an effective, durable mobile smoking cessation program.

TRIAL REGISTRATION

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION

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

Digital Help for Substance Users (SU): A Systematic Review

The estimated number of Substance Users (SU) globally has currently reached a very high number and is still increasing. This aspect necessitates appropriate interventions for prevention and specific treatments. The literature shows that digital treatments can be useful in the context of health services and substance abuse. This systematic review focuses mainly on research on the effectiveness of digital treatments for SU. Data sources included studies found on PsycINFO, PubMed, SCOPUS, and WebOfScience (WOS) database searches. The following keywords were used: TITLE (digital OR computer OR software OR tablet OR app OR videogame OR seriousgame OR virtualreality) AND ABSTRACT((mental AND health) AND (addiction OR dependence OR substance OR drug)). We focused on peer-reviewed articles published from 2010 through 2021 using PRISMA guidelines. A total of 18 studies met the inclusion criteria (i.e., type of intervention, efficacy in terms of misuse of substances and scored outcomes from questionnaire or toxicology tests, study methodology). The studies included investigations of specific digital treatments for SU of various kinds of drugs. The interventions were administered using personal computers, smartphones, or, in a few cases, tablets. Most of the interventions focused on the cognitive behavior therapy (CBT) model and/or on the use strategies, tips, or feedback. A minority provided information or training programs. The current review shows that digital treatments and interventions are effective in reducing the frequency of use, augmenting abstinence, or reducing the gravity of dependence for most of the studies at post-treatment. However, due to the heterogeneity of the variables (i.e., substance type, digital tool used, and treatment administered), there was a reduced generalizability of the results. This review highlights the need to continue the research in this field, and above all, to create effective digital protocols.

Effectiveness of an optimized text message and Internet intervention for smoking cessation: A randomized controlled trial

AIMS

To evaluate the effectiveness of a combined internet and text message intervention for smoking cessation compared with an internet intervention alone. The text message intervention was optimized for engagement in an earlier multiphase optimization (MOST) screening phase.

DESIGN

A parallel, two-group, individually randomized clinical trial (RCT) was conducted in a MOST confirming phase. Recruitment spanned December 2018 to March 2019. Follow-up was conducted at 3 and 9 months, beginning March 2019 and ending January 2020.

SETTING

United States: a digital study conducted among new registrants on a free tobacco cessation website.

PARTICIPANTS

Eligible individuals were 618 adult current smokers in the United States, age 18 years or older who signed up for text messages during website registration (67.2% female, 70.4% white).

INTERVENTIONS

The treatment arm (WEB+TXT; n = 311) received access to the website and text messaging. The control arm (WEB; n = 307) received access to the website alone.

MEASUREMENTS

The primary outcome was self-reported 30-day point prevalence abstinence (ppa) at 9 months post-randomization analyzed under intent to treat (ITT), counting non-responders as smoking. Secondary outcomes included 3-month measures of 30-day ppa, intervention engagement and intervention satisfaction.

FINDINGS

Abstinence rates at 9 months were 23.1% among WEB+TXT and 23.2% among WEB (OR = 1.00, 95% CI = 0.69-1.45; P = 0.99). WEB+TXT increased engagement with 5 of 6 interactive features (standardized mean difference (SMD) = 0.26-0.47, all P < 0.001) and repeat website visits (48.7% vs 38.9%, SMD = 0.14, P = 0.02). Satisfaction metrics favored WEB+TXT (satisfied: 96.3% vs 90.5%, SMD = 0.17, P = 0.008; recommend to friend: 95.9% vs 90.1%, SMD = 0.16, P = 0.028).

CONCLUSIONS

A randomized controlled trial found no evidence that a combined internet and text message intervention for smoking cessation compared with an internet intervention alone increased 9-month abstinence rates among adult current smokers in the United States, despite evidence of higher levels of intervention engagement and satisfaction at 3 months.

Efficacy of an acceptance and commitment therapy-based smartphone application for helping rural populations quit smoking: Results from the iCanQuit randomized trial

Limited access to evidence-based smoking cessation interventions among rural populations contributes to high rates of cigarette smoking and poor cessation outcomes. Yet, accessible digital interventions for cessation focusing on rural populations are lacking. In a secondary analysis, we determined the acceptability and efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) relative to a U.S. Clinical Practice Guidelines (USCPG)-based smartphone application (QuitGuide) for smoking cessation among rural participants enrolled in the two-arm randomized iCanQuit trial. Participants were enrolled between May 2017 and September 2018 and randomized to either receive iCanQuit or QuitGuide for 12-months. Rural residence was determined by sub-county level Rural-Urban Commuting Area codes. A total of 550 rural participants were recruited from 43 U.S. states. Self-reported complete-case 30-day point-prevalence abstinence was 15% (33/226) for iCanQuit vs. 9% (22/253) for QuitGuide at 3-months (OR = 1.83; 95% CI: 1.03, 3.25) and 29% (66/231) for iCanQuit vs. 25% (64/288) for QuitGuide at 12-months (OR = 1.19 95% CI: 0.80, 1.79). Retention rate was 89% at 12-months and did not differ by arm. iCanQuit vs. QuitGuide participants were significantly more engaged and satisfied with the iCanQuit application. Increased acceptance of internal cues to smoke mediated the effect of treatment on cessation. Findings suggest that iCanQuit had significantly higher short-term quit rates, descriptively higher long-term quit rates, and operated through its hypothesized mechanisms of action relative to QuitGuide. Future larger studies are needed to further evaluate the efficacy of and methods for disseminating the iCanQuit application for smoking cessation among U.S. rural adults nationwide. Trial registrationClinicalTrials.gov Identifier: NCT02724462.

Non-pharmacological interventions for tobacco cessation: A systematic review of existing practices and their effectiveness

Smoking tobacco is associated with lung cancer and other life-threatening diseases which requires serious action to curb it. Tobacco cessation interventions are available as pharmacological and non-pharmacological methods or a combination of both. The present review examines the effectiveness of the existing non-pharmacological tobacco cessation interventions and synthesizes the result for the future development of drug-free treatment in the community for tobacco cessation. The literature search was conducted in August 2020, using two electronic databases (PubMed and JSTOR), with search terms: ['tobacco cessation' OR 'smoking cessation'] AND ['intervention'] which included studies published during 2010 and 2020 (till 31st July 2020). All studies were limited to English language, human participants and excluded patients with comorbidities. A total of 2,114 publications were retrieved out of which 11 articles were reviewed. On the basis of intervention used in reviewed studies, we categorized them into seven categories: i. incentive-based intervention, ii. exercise based, iii. telephone-based proactive counselling, iv. mobile phone SMS (Short Message Service) based, v. smartphone app (application) based, vi. web-based intervention, vii. self-help material. Incentives were provided in most of the studies to maintain the retention rate and motivate the participants for completing follow-up. Non-pharmacological interventions for tobacco cessation include a combination of various elements. Our findings suggest that behavioural counselling is one of the most important elements of any non-pharmacological intervention. In addition to behaviour counselling, yoga and exercises along with self-help material, video and phone counselling may have higher efficacy. Thus, practicing non-pharmacological interventions may also increase the cessation rate and reduce the tobacco use burden.

Efficacy and Utilization of Smartphone Applications for Smoking Cessation Among American Indians and Alaska Natives: Results From the iCanQuit Trial

INTRODUCTION

There is tremendous need for efficacious and accessible interventions for smoking cessation among American Indians and Alaska Natives. We tested the efficacy of an Acceptance and Commitment Therapy (ACT)-based smartphone application (iCanQuit) versus US Clinical Practice Guidelines-based smartphone application (QuitGuide) for smoking cessation among American Indians and Alaska Natives.

AIMS AND METHODS

We compared cessation, changes in ACT-based processes, engagement and satisfaction between American Indian and Alaska Native iCanQuit (n = 89) and QuitGuide (n = 80) participants enrolled in the iCanQuit trial. The primary outcome was self-reported, complete-case, 30-day point-prevalence abstinence. Follow-up timepoints were 12, 6, and 3 months.

RESULTS

Randomized American Indians and Alaska Natives from 31 US states (70% urban, 30% rural, with 25% of participants residing on tribal land). The outcome data retention rates were 93%, 92%, and 90% at the 12-, 6-, and 3-month follow-ups, respectively, with no differential retention between arms. The 30-day point-prevalence abstinence for iCanQuit versus QuitGuide was 30% versus 18% at 12 months (odds ratio [OR] = 1.96; 95% confidence interval [CI]: 0.90 to 4.26) 25% versus 11% at 6 months (OR = 2.62; 95% CI: 1.06 to 6.45), and 15% versus 6% at 3 months (OR = 2.93; 95% CI: 0.90 to 9.59). Increases in acceptance of internal cues to smoke mediated the effect of treatment on smoking cessation at 12 months. iCanQuit arm participants were also significantly more engaged and satisfied with their assigned application.

CONCLUSIONS

In a nationwide sample with high data retention and participant engagement, this is the first study to show that a digital intervention may be efficacious for helping American Indians and Alaska Natives quit smoking.

IMPLICATIONS

This is the first study to provide evidence of an efficacious, accessible, and engaging treatment for helping American Indians and Alaska Natives quit smoking. Compared to a US Clinical Practice Guidelines-based smartphone application (QuitGuide), an ACT-based smartphone application (iCanQuit) was more efficacious, engaging, and satisfactory among American Indians and Alaska Natives nationwide. Our results will inform the tailoring of the iCanQuit smartphone application for American Indian and Alaska Native tribal communities and organizations with potential for broad dissemination and high impact.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies' abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.

Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement

Background

Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.

Methods

We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user’s rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.

Results

We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07–3.23), moderate response rate (OR = 2.30, 95% CI: 1.36–3.88), high response rate (OR = 2.69, 95% CI: 1.58–4.58). The association between perceived message influence and the outcome showed a similar pattern.

Conclusions

High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.

Trial registration

Registration Identifier: NCT03224520. Registration date: July 21, 2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11803-8.

Effectiveness of E-SBIRT intervention in community healthcare institution in China: study proposal for a randomised controlled trial

BACKGROUND

Many studies have demonstrated the effectiveness of Screening, Brief Intervention and Referral to Treatment (SBIRT) in addressing substance use problem. However, owing to the shortage of counsellors, it has not been widely used in China. With the development of smart medicine, we developed a web-based electronic SBIRT (E-SBIRT) program and explored the effectiveness of E-SBIRT in reducing substance use in China.

METHODS

A randomised controlled trial will be conducted in primary healthcare institutions. Four primary healthcare institutions will be selected and randomly divided into an intervention group and a control group (each institution will recruit 60 participants, and in total, 240 participants will be recruited). The control group will get a pamphlet of drug abuse prevention, and the intervention group will get the E-SBIRT intervention and the pamphlet. Both groups will receive baseline and follow-up assessment at 1 and 3 months after the intervention. The primary outcome is the change in scores on the Alcohol, Smoking and Substance Use Involvement Screening Test, and the secondary outcomes include changes in motivation, depression, anxiety, positive/negative emotion, self-esteem, addiction knowledge and addiction severity index.

CONCLUSIONS

If the 'E-SBIRT' program is found to be effective, it will be an accessible, affordable and widely implementable intervention to help participants at moderate risk of substance use to reduce their consumption. The potential benefit is to provide early intervention to high-risk patients in time and reduce the harmful consequences to individuals and society.

TRIAL REGISTRATION NUMBER

NCT03452241.

Mobile health in preventive cardiology: current status and future perspective

PURPOSE OF REVIEW

Despite cutting edge acute interventions and growing preventive strategies supported by robust clinical trials, cardiovascular disease (CVD) has stubbornly persisted as a leading cause of death in the United States and globally. The American Heart Association recognizes mobile health technologies (mHealth) as an emerging strategy in the mitigation of CVD risk factors, with significant potential for improving population health. The purpose of this review is to highlight and summarize the latest available literature on mHealth applications and provide perspective on future directions and barriers to implementation.

RECENT FINDINGS

While available randomized controlled trials and systematic reviews tend to support efficacy of mHealth, published literature includes heterogenous approaches to similar problems with inconsistent results. Some of the strongest recent evidence has been focused on the use of wearables in arrhythmia detection. Systematic reviews of mHealth approaches demonstrate benefit when applied to risk factor modification in diabetes, cigarette smoking cessation, and physical activity/weight loss, while also showing promise in multi risk factor modification via cardiac rehabilitation.

SUMMARY

Evidence supports efficacy of mHealth in a variety of applications for CVD prevention and management, but continued work is needed for further validation and scaling. Future directions will focus on platform optimization, data and sensor consolidation, and clinical workflow integration. Barriers include application heterogeneity, lack of reimbursement structures, and inequitable access to technology. Policies to promote access to technology will be critical to evidence-based mHealth technologies reaching diverse populations and advancing health equity.

Application of Automated Text Analysis to Examine Emotions Expressed in Online Support Groups for Quitting Smoking

Online support groups offer social support and an outlet for expressing emotions when dealing with health-related challenges. This study examines whether automated text analysis of emotional expressions using Linguistic Inquiry and Word Count (LIWC) can identify emotions related to abstinence expressed in online support groups for quitting smoking, suggesting promise for offering targeted mood management to members. The emotional expressions in 1 month of posts by members of 36 online support groups were related to abstinence at month end. Using the available LIWC dictionary, posts were scored for overall positive emotions, overall negative emotions, anxiety, anger, sadness, and an upbeat emotional tone. Greater expressions of negative emotions, and specifically anxiety, related to nonabstinence, while a more upbeat emotional tone related to abstinence. The results indicate that automated text analysis can identify emotions expressed in online support groups for quitting smoking and enable targeted delivery of mood management to group members.

mHealth Technology and CVD Risk Reduction

PURPOSE OF REVIEW

To review existing mHealth-based interventions and examine their efficacy in reducing cardiovascular disease (CVD) risk factors.

RECENT FINDINGS

A total of 50 articles are included in this review. The majority of the mHealth interventions targeted a specific CVD risk factor, while 4 addressed 2 or more CVD risk factors. Of the 9 mHealth-supported weight loss intervention trials, 4 resulted in significant weight loss. Four out of 7 RCTs targeting improvement in physical activity reported significant improvement, while 4 of the 8 mHealth-supported smoking cessation intervention trials resulted in smoking abstinence. Of the 10 mHealth-based diabetes intervention trials, 5 reported significant reductions in HbA1c; however, only 3 out of the 9 antihypertension interventions resulted in significant reductions in blood pressure. There is a growing body of literature focused on mHealth interventions that address CVD risk factors. Despite the immense potential of mHealth interventions, evidence of their efficacy in mitigating cardiovascular risk is heterogeneous.

Enhancing suicide prevention outreach via mobile-enabled website design

Online outreach campaigns are a potential public health method for reaching service members at risk for suicide. The Real Warriors Campaign website underwent a full redesign in 2019 to enhance its ability to provide crisis resources and increase engagement by adopting a mobile-first strategy and implementing a responsive framework, meaning the site renders properly on all devices, including desktop, tablets, and mobile. Usability testing with end-user service members led to several innovations on the website, including a one-click banner that directly linked users on their mobile phones to crisis resources, the redesign of menus and content to better display on mobile devices, and promoting use of website resources through gateway topics. Comparing the 6 months before and after the mobile redesign showed significant increases in new mobile users, pages viewed on mobile devices, and new users coming to the site through social media. There was also a significant increase in specific help-seeking actions by users, including use of referral links and live chat, as well as 200 individuals accessing crisis phone lines through new one-click dialing banners. Suicide prevention campaigns should continue to optimize their online presence to reach groups at risk. This study of the website redesign from the Real Warriors Campaign illustrates several best practices in digital outreach as applied to suicide prevention, including leveraging usability testing, synching outreach material with social media, and ensuring mobile compatibility.

Durability of Abstinence After Completing a Comprehensive Digital Smoking Cessation Program Incorporating a Mobile App, Breath Sensor, and Coaching: Cohort Study

BACKGROUND

Despite decreasing prevalence over the last several decades, cigarette smoking remains the leading cause of preventable death and disease, underscoring the need for innovative, effective solutions. Pivot is a novel, inclusive smoking cessation program designed for smokers along the entire spectrum of readiness to quit. Pivot leverages proven methods and technological advancements, including a personal portable breath carbon monoxide sensor, smartphone app, and in-app text-based coaching. We previously reported outcomes from the end of active Pivot program participation in 319 adult smokers. Herein, we report longer-term follow up in this cohort.

OBJECTIVE

The aim of this study was to assess and report participant outcomes 3 months after completion of Pivot, including smoking behavior, quit rates, continuous abstinence rates and durability, and predictors of abstinence.

METHODS

This prospective remote cohort study included US-based cigarette smokers aged 18 to 65 years who smoked ≥5 cigarettes per day (CPD). Three months after completion of active participation in Pivot, final follow-up data were collected via an online questionnaire. Outcomes included smoking behavior (CPD and quit attempts), self-reported quit rates (7- and 30-day point prevalence abstinence [PPA]), and continuous abstinence rates (proportion who achieved uninterrupted abstinence) and duration. Exploratory regression analyses were performed to identify baseline characteristics associated with achievement of 7-day PPA, 30-day PPA, and continuous abstinence.

RESULTS

A total of 319 participants completed onboarding (intention-to-treat [ITT]); 288/319 participants (90.3%) completed follow up (completers) at a mean of 7.2 (SD 1.2) months after onboarding. At final follow up, CPD were reduced by 52.6% (SE 2.1; P<.001) among all 319 participants, and most completers (152/288, 52.8%) reduced their CPD by at least 50%. Overall, most completers (232/288, 80.6%) made at least one quit attempt. Quit rates increased after the end of Pivot; using ITT analyses, 35.4% (113/319) achieved 7-day PPA and 31.3% (100/319) achieved 30-day PPA at final follow up compared with 32.0% (102/319) and 27.6% (88/319), respectively, at the end of the Pivot program. Continuous abstinence was achieved in about a quarter of those who onboarded (76/319, 23.8%) and in most who reported 30-day PPA at the end of Pivot (76/88, 86.4%), with a mean abstinence duration of 5.8 (SD 0.6) months. In exploratory regression analyses, lower baseline CPD, more positive baseline attitudes reflecting higher self-efficacy (higher confidence to quit and lower perceived difficulty of quitting), and higher education were associated with achieving abstinence.

CONCLUSIONS

This study provides the first longer-term outcomes of the Pivot smoking cessation program. At final follow up, quit rates increased and continuous abstinence was favorable; the majority who achieved abstinence at the end of Pivot sustained abstinence throughout follow up. Decreases in CPD persisted and most participants made a quit attempt. Overall, final follow-up outcomes were stable or improved when compared to previous outcomes from the end of the program. These findings validate earlier results, and suggest that Pivot is an effective and durable solution for smoking cessation.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03295643; https://clinicaltrials.gov/ct2/show/NCT03295643.

Randomized controlled study using text messages to help connect new medicaid beneficiaries to primary care

Accessing primary care is often difficult for newly insured Medicaid beneficiaries. Tailored text messages may help patients navigate the health system and initiate care with a primary care physician. We conducted a randomized controlled trial of tailored text messages with newly enrolled Medicaid managed care beneficiaries. Text messages included education about the importance of primary care, reminders to obtain an appointment, and resources to help schedule an appointment. Within 120 days of enrollment, we examined completion of at least one primary care visit and use of the emergency department. Within 1 year of enrollment, we examined diagnosis of a chronic disease, receipt of preventive care, and use of the emergency department. 8432 beneficiaries (4201 texting group; 4231 control group) were randomized; mean age was 37 years and 24% were White. In the texting group, 31% engaged with text messages. In the texting vs control group after 120 days, there were no differences in having one or more primary care visits (44.9% vs. 45.2%; difference, −0.27%; p = 0.802) or emergency department use (16.2% vs. 16.0%; difference, 0.23%; p = 0.771). After 1 year, there were no differences in diagnosis of a chronic disease (29.0% vs. 27.8%; difference, 1.2%; p = 0.213) or appropriate preventive care (for example, diabetes screening: 14.1% vs. 13.4%; difference, 0.69%; p = 0.357), but emergency department use (32.7% vs. 30.2%; difference, 2.5%; p = 0.014) was greater in the texting group. Tailored text messages were ineffective in helping new Medicaid beneficiaries visit primary care within 120 days.

The association between frequency of e-cigarette use and long-term smoking cessation outcomes among treatment-seeking smokers receiving a behavioral intervention

INTRODUCTION

A growing body of literature suggests daily, but not non-daily, e-cigarette use is associated with greater odds of quitting combustible cigarettes in the general adult population. However, it is unknown if these findings generalize to treatment-seeking smokers who are receiving a behavioral intervention. Our primary aim was to examine whether frequency of e-cigarette use was associated with subsequent cessation among treatment-seeking smokers who are receiving a behavioral smoking cessation intervention.

METHODS

Participants (N = 2637) enrolled in a RCT of web-based smoking treatments reported their use of e-cigarettes at baseline, 3-, and 6-months. Three groups were created based on e-cigarette use: (1) non-users, (2) intermittent users, and (3) daily users. The primary outcome was complete-case, self-reported 30-day point prevalence abstinence at 12 months.

RESULTS

Compared to non-users, daily e-cigarette users were significantly less likely to be abstinent (21.39 % vs. 29.68 %; p = .006). Quit rates for intermittent users (24.56 %) were not significantly different from non-users (p = .092). Nicotine dependence moderated the results such that among smokers with low nicotine dependence, those who used e-cigarettes (intermittently or daily) were less likely to quit than non-users; these differences were not significant among those with high nicotine dependence. Post hoc analyses indicated that initiating daily e-cigarette use after baseline, but not daily e-cigarette use at baseline, was associated with lower odds of cessation.

CONCLUSIONS

Daily e-cig use may be associated with lower odds of quitting smoking among treatment-seeking smokers, particularly among those with lower nicotine dependence and who initiate daily use after beginning an intervention.

Effectiveness of mobile applications to quit smoking: Systematic review and meta-analysis

INTRODUCTION

Tobacco is the leading cause of preventable mortality. The use of mobile phones has grown exponentially, becoming a powerful tool to be used in health care.

METHODS

In order to assess the effectiveness of mobile phones to quit smoking, we have carried out a systematic review and meta-analysis of randomized clinical trials evaluating interventions based on mobile applications for smartphones, that were not a smaller version of the same application, against other types of therapy. To address this, a bibliographic search was carried out in MEDLINE, EMBASE and COCHRANE LIBRARY. To obtain the combined effect, the relative risk and the 95% confidence interval were used. A heterogeneity and sensitivity analysis were also conducted.

RESULTS

A total of nine studies were identified, but five were excluded. Qualitative review was performed with four selected studies, but quantitative analysis was carried out for only three, given the impossibility of calculating the RR in one of the studies. After combining the results, an RR of 0.901 (95% CI: 0.57-1.423) was calculated comparing the effectiveness of mobile applications versus others type of interventions. This measure was robust, as shown by the sensitivity analysis.

CONCLUSIONS

According to the results, it cannot be concluded that apps are effective for quitting tobacco. There are very few clinical trials published evaluating the effectiveness of mobile applications compared to other alternatives. Several clinical trials are still in progress, therefore their results have not been included in the present meta-analysis.

The Put It Out Project (POP) Facebook Intervention for Young Sexual and Gender Minority Smokers: Outcomes of a Pilot, Randomized, Controlled Trial

INTRODUCTION

This trial investigated whether a Facebook smoking cessation intervention culturally tailored to young sexual and gender minority (SGM) smokers (versus non-tailored) would increase smoking abstinence.

METHODS

Participants were 165 SGM young adult US smokers (age 18-25) recruited from Facebook in April 2018 and randomized to an SGM-tailored (POP; N = 84) or non-tailored (TSP-SGM; N = 81) intervention. Interventions delivered weekly live counseling sessions and 90 daily Facebook posts to participants in Facebook groups. Primary analyses compared POP and TSP-SGM on biochemically verified smoking abstinence (yes/no; primary outcome), self-reported 7-day point prevalence abstinence (yes/no), reduction in cigarettes per week by 50+% from baseline (yes/no), making a quit attempt during treatment (yes/no), and stage of change (precontemplation/contemplation vs. preparation/action). Supplemental analyses compared POP to two historical control groups.

RESULTS

POP participants were more likely than TSP-SGM participants to report smoking abstinence at 3 (23.8% vs. 12.3%; OR = 2.50; p = .03) and 6 months (34.5% vs. 12.3%; OR = 4.06; p < .001) and reduction in smoking at 3 months (52.4% vs. 39.5%; OR = 2.11; p = .03). Biochemically verified smoking abstinence did not significantly differ between POP and TSP-SGM at 3 (OR = 2.00; p = .33) or 6 months (OR = 3.12; p = .08), potentially due to challenges with remote biochemical verification. In supplemental analyses, POP participants were more likely to report abstinence at 3 (OR = 6.82, p = .01) and 6 (OR = 2.75, p = .03) months and reduced smoking at 3 months (OR = 2.72, p = .01) than participants who received a referral to Smokefree.gov.

CONCLUSIONS

This pilot study provides preliminary support for the effectiveness of a Facebook smoking cessation intervention tailored to SGM young adults.

IMPLICATIONS

SGM individuals have disproportionately high smoking prevalence. It is unclear whether smoking cessation interventions culturally tailored to the SGM community are more effective than non-tailored interventions. This pilot trial found preliminary evidence that an SGM-tailored Facebook smoking cessation intervention increased reported abstinence from smoking, compared to a non-tailored intervention.

TRIAL REGISTRATION

NCT03259360.

Mobile phone text messaging and app-based interventions for smoking cessation

BACKGROUND

Mobile phone-based smoking cessation support (mCessation) offers the opportunity to provide behavioural support to those who cannot or do not want face-to-face support. In addition, mCessation can be automated and therefore provided affordably even in resource-poor settings. This is an update of a Cochrane Review first published in 2006, and previously updated in 2009 and 2012.

OBJECTIVES

To determine whether mobile phone-based smoking cessation interventions increase smoking cessation rates in people who smoke.

SEARCH METHODS

For this update, we searched the Cochrane Tobacco Addiction Group's Specialised Register, along with clinicaltrials.gov and the ICTRP. The date of the most recent searches was 29 October 2018.

SELECTION CRITERIA

Participants were smokers of any age. Eligible interventions were those testing any type of predominantly mobile phone-based programme (such as text messages (or smartphone app) for smoking cessation. We included randomised controlled trials with smoking cessation outcomes reported at at least six-month follow-up.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures described in the Cochrane Handbook for Systematic Reviews of Interventions. We performed both study eligibility checks and data extraction in duplicate. We performed meta-analyses of the most stringent measures of abstinence at six months' follow-up or longer, using a Mantel-Haenszel random-effects method, pooling studies with similar interventions and similar comparators to calculate risk ratios (RR) and their corresponding 95% confidence intervals (CI). We conducted analyses including all randomised (with dropouts counted as still smoking) and complete cases only.

MAIN RESULTS

This review includes 26 studies (33,849 participants). Overall, we judged 13 studies to be at low risk of bias, three at high risk, and the remainder at unclear risk. Settings and recruitment procedures varied across studies, but most studies were conducted in high-income countries. There was moderate-certainty evidence, limited by inconsistency, that automated text messaging interventions were more effective than minimal smoking cessation support (RR 1.54, 95% CI 1.19 to 2.00; I² = 71%; 13 studies, 14,133 participants). There was also moderate-certainty evidence, limited by imprecision, that text messaging added to other smoking cessation interventions was more effective than the other smoking cessation interventions alone (RR 1.59, 95% CI 1.09 to 2.33; I² = 0%, 4 studies, 997 participants). Two studies comparing text messaging with other smoking cessation interventions, and three studies comparing high- and low-intensity messaging, did not show significant differences between groups (RR 0.92 95% CI 0.61 to 1.40; I² = 27%; 2 studies, 2238 participants; and RR 1.00, 95% CI 0.95 to 1.06; I² = 0%, 3 studies, 12,985 participants, respectively) but confidence intervals were wide in the former comparison. Five studies compared a smoking cessation smartphone app with lower-intensity smoking cessation support (either a lower-intensity app or non-app minimal support). We pooled the evidence and deemed it to be of very low certainty due to inconsistency and serious imprecision. It provided no evidence that smartphone apps improved the likelihood of smoking cessation (RR 1.00, 95% CI 0.66 to 1.52; I² = 59%; 5 studies, 3079 participants). Other smartphone apps tested differed from the apps included in the analysis, as two used contingency management and one combined text messaging with an app, and so we did not pool them. Using complete case data as opposed to using data from all participants randomised did not substantially alter the findings.

AUTHORS' CONCLUSIONS

There is moderate-certainty evidence that automated text message-based smoking cessation interventions result in greater quit rates than minimal smoking cessation support. There is moderate-certainty evidence of the benefit of text messaging interventions in addition to other smoking cessation support in comparison with that smoking cessation support alone. The evidence comparing smartphone apps with less intensive support was of very low certainty, and more randomised controlled trials are needed to test these interventions.

Public health digitalization in Europe

BACKGROUND

As digitalization is progressively permeating all aspects of society, how can be it fruitfully employed to sustain the public health goals of quality, accessibility, efficiency and equity in health care and prevention? In this paper, we reflect on the potential of applying digital tools to public health and discuss some key challenges.

METHODS

We first define 'digitalization' in its broader sense, as well as applied to public health. We then build a conceptual framework where key public health domains are associated to available digital technologies in a matrix that help to identify digital features that bolster public health action. We also provide illustrative data and evidence on the application of digital solutions on selected public health areas. In the second part, we identify the strategic pillars for a successful European strategy for public health digitalization and we outline how the approach being pursued by the European Public Health Association (EUPHA) applies to digital health.

RESULTS

From a public health perspective, digitalization is being touted as providing several potential benefits and advantages, including support for the transition from cure to prevention, helping to put people and patients at the center of care delivery, supporting patient empowerment and making healthcare system more efficient, safer and cheaper. These benefits are enabled through the following features of digital technologies: (i) Personalization and precision; (ii) Automation; (iii) Prediction; (iv) Data analytics and (v) Interaction.

CONCLUSION

A successful European strategy for public health digitalization should integrate the following pillars: political commitment, normative frameworks, technical infrastructure, targeted economic investments, education, research, monitoring and evaluation. EUPHA acknowledges digitalization is an asset for public health and is working both to promote the culture of "public health digitalization", as well as to enable its planning, implementation and evaluation at the research, practice and policy level.