Improving Adherence to Smoking Cessation Treatment: Intervention Effects in a Web-Based Randomized Trial

Gender Differences in the Interrelations Among Social Support, Stressful Life Events, and Smoking Cessation in People With Severe Mental Illnesses

BACKGROUND

Social support and stressful life events (SLEs) have been found to be influential factors for smoking cessation in the general population, but little is known about these factors among smokers with severe mental illnesses (SMIs) and whether their associations with smoking cessation differ by gender.

AIMS

To examine the association between social support and smoking cessation as mediated by SLEs in people with SMI and to examine whether the interrelations among social support, SLEs, and smoking cessation differ by gender.

METHODS

A population sample of 4,610 American lifetime adult smokers with schizophrenia, bipolar disorder, or major depressive disorder were identified in a limited public use data set of the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions. Four mediation and moderated mediation models were used to examine gender differences in the interrelations among social support (total and three subscales of the Interpersonal Support Evaluation List-12), SLEs (summative score of positive responses to 16 types experienced in past year and related to health, job, death, or legal situations), and smoking status in prior year.

RESULTS

Total, appraisal, and tangible support among females exerted indirect effects on smoking cessation via decreasing SLE scores. Among males, only belonging support exerted an indirect effect on smoking cessation via an increased SLE score.

CONCLUSIONS

Findings suggest that interventions focusing on improving social support should be a priority for those working with smokers with SMI.

Evaluating the Efficacy of a Social Media-Based Intervention (Warna-Warni Waktu) to Improve Body Image Among Young Indonesian Women: Parallel Randomized Controlled Trial (Preprint)

BACKGROUND

Body dissatisfaction is a global issue, particularly among adolescent girls and young women. Effective body image interventions exist but face barriers to scaling up, particularly in lower- and middle-income countries, such as Indonesia, where a need exists.

OBJECTIVE

We aimed to evaluate the acceptability and efficacy of Warna-Warni Waktu, a social media-based, fictional 6-episode video series with self-guided web-based activities for improving body image among young Indonesian adolescent girls and young women. We hypothesized that Warna-Warni Waktu would increase trait body satisfaction and mood and decrease internalization of appearance ideals and skin shade dissatisfaction relative to the waitlist control condition. We also anticipated improvements in state body satisfaction and mood immediately following each video.

METHODS

We conducted a web-based, 2-arm randomized controlled trial among 2000 adolescent girls and young women, aged 15 to 19 years, recruited via telephone by an Indonesian research agency. Block randomization (1:1 allocation) was performed. Participants and researchers were not concealed from the randomized arm. Participants completed self-report assessments of trait body satisfaction (primary outcome) and the internalization of appearance ideals, mood, and skin shade dissatisfaction at baseline (before randomization), time 2 (1 day after the intervention [T2]), and time 3 (1 month after the intervention [T3]). Participants also completed state body satisfaction and mood measures immediately before and after each video. Data were evaluated using linear mixed models with an intent-to-treat analysis. Intervention adherence was tracked. Acceptability data were collected.

RESULTS

There were 1847 participants. Relative to the control condition (n=923), the intervention group (n=924) showed reduced internalization of appearance ideals at T2 (F_1,1758=40.56, P<.001, partial η²=0.022) and T3 (F_1,1782=54.03, P<.001, partial η²=0.03) and reduced skin shade dissatisfaction at T2 (F_1,1744=8.05, P=.005, partial η²=0.005). Trait body satisfaction improvements occurred in the intervention group at T3 (F_{1, 1781}=9.02, P=.005, partial η²=0.005), which was completely mediated by the internalization change scores between baseline and T2 (indirect effect: β=.03, 95% CI 0.017-0.041; direct effect: β=.03, P=.13), consistent with the Tripartite Influence Model of body dissatisfaction. Trait mood showed no significant effects. Dependent sample t tests (2-tailed) found each video improved state body satisfaction and mood. Cumulative analyses found significant and progressive improvements in pre- and poststate body satisfaction and mood. Intervention adherence was good; participants watched an average of 5.2 (SD 1.66) videos. Acceptability scores were high for understandability, enjoyment, age appropriateness, usefulness, and likelihood to recommend.

CONCLUSIONS

Warna-Warni Waktu is an effective eHealth intervention to reduce body dissatisfaction among Indonesian adolescent girls and young women. Although the effects were small, Warna-Warni Waktu is a scalable, cost-effective alternative to more intense interventions. Initially, dissemination through paid social media advertising will reach thousands of young Indonesian women.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05383807, https://clinicaltrials.gov/ct2/show/NCT05383807 ; ISRCTN Registry ISRCTN35483207, https://www.isrctn.com/ISRCTN35483207.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/33596.

Smoking cessation medicines and e-cigarettes: a systematic review, network meta-analysis and cost-effectiveness analysis

BACKGROUND

Cigarette smoking is one of the leading causes of early death. Varenicline [Champix (UK), Pfizer Europe MA EEIG, Brussels, Belgium; or Chantix (USA), Pfizer Inc., Mission, KS, USA], bupropion (Zyban; GlaxoSmithKline, Brentford, UK) and nicotine replacement therapy are licensed aids for quitting smoking in the UK. Although not licensed, e-cigarettes may also be used in English smoking cessation services. Concerns have been raised about the safety of these medicines and e-cigarettes.

OBJECTIVES

To determine the clinical effectiveness, safety and cost-effectiveness of smoking cessation medicines and e-cigarettes.

DESIGN

Systematic reviews, network meta-analyses and cost-effectiveness analysis informed by the network meta-analysis results.

SETTING

Primary care practices, hospitals, clinics, universities, workplaces, nursing or residential homes.

PARTICIPANTS

Smokers aged ≥ 18 years of all ethnicities using UK-licensed smoking cessation therapies and/or e-cigarettes.

INTERVENTIONS

Varenicline, bupropion and nicotine replacement therapy as monotherapies and in combination treatments at standard, low or high dose, combination nicotine replacement therapy and e-cigarette monotherapies.

MAIN OUTCOME MEASURES

Effectiveness - continuous or sustained abstinence. Safety - serious adverse events, major adverse cardiovascular events and major adverse neuropsychiatric events.

DATA SOURCES

Ten databases, reference lists of relevant research articles and previous reviews. Searches were performed from inception until 16 March 2017 and updated on 19 February 2019.

REVIEW METHODS

Three reviewers screened the search results. Data were extracted and risk of bias was assessed by one reviewer and checked by the other reviewers. Network meta-analyses were conducted for effectiveness and safety outcomes. Cost-effectiveness was evaluated using an amended version of the Benefits of Smoking Cessation on Outcomes model.

RESULTS

Most monotherapies and combination treatments were more effective than placebo at achieving sustained abstinence. Varenicline standard plus nicotine replacement therapy standard (odds ratio 5.75, 95% credible interval 2.27 to 14.90) was ranked first for sustained abstinence, followed by e-cigarette low (odds ratio 3.22, 95% credible interval 0.97 to 12.60), although these estimates have high uncertainty. We found effect modification for counselling and dependence, with a higher proportion of smokers who received counselling achieving sustained abstinence than those who did not receive counselling, and higher odds of sustained abstinence among participants with higher average dependence scores. We found that bupropion standard increased odds of serious adverse events compared with placebo (odds ratio 1.27, 95% credible interval 1.04 to 1.58). There were no differences between interventions in terms of major adverse cardiovascular events. There was evidence of increased odds of major adverse neuropsychiatric events for smokers randomised to varenicline standard compared with those randomised to bupropion standard (odds ratio 1.43, 95% credible interval 1.02 to 2.09). There was a high level of uncertainty about the most cost-effective intervention, although all were cost-effective compared with nicotine replacement therapy low at the £20,000 per quality-adjusted life-year threshold. E-cigarette low appeared to be most cost-effective in the base case, followed by varenicline standard plus nicotine replacement therapy standard. When the impact of major adverse neuropsychiatric events was excluded, varenicline standard plus nicotine replacement therapy standard was most cost-effective, followed by varenicline low plus nicotine replacement therapy standard. When limited to licensed interventions in the UK, nicotine replacement therapy standard was most cost-effective, followed by varenicline standard.

LIMITATIONS

Comparisons between active interventions were informed almost exclusively by indirect evidence. Findings were imprecise because of the small numbers of adverse events identified.

CONCLUSIONS

Combined therapies of medicines are among the most clinically effective, safe and cost-effective treatment options for smokers. Although the combined therapy of nicotine replacement therapy and varenicline at standard doses was the most effective treatment, this is currently unlicensed for use in the UK.

FUTURE WORK

Researchers should examine the use of these treatments alongside counselling and continue investigating the long-term effectiveness and safety of e-cigarettes for smoking cessation compared with active interventions such as nicotine replacement therapy.

STUDY REGISTRATION

This study is registered as PROSPERO CRD42016041302.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 59. See the NIHR Journals Library website for further project information.

Internet-based intervention compared to brief intervention for smoking cessation in Brazil: a pilot study (Preprint)

Background

Smoking is still the leading cause of preventable death. Governments and health care providers should make available more accessible resources to help tobacco users stop.

Objective

This study describes a pilot longitudinal study that evaluated the efficacy of an internet-based intervention compared to the brief intervention for smoking cessation among Brazilians.

Methods

Eligible participants were recruited and randomly allocated to one of the two interventions. Measures were drawn by comparing cessation rates, motivation scores, and sought treatment between groups, assessed 1 and 3 months after the intervention. Inferential analysis was performed to compare the participants’ characteristics, and the intention to treat was calculated.

Results

A total of 49 smokers were enrolled in this study (n=25, 51% in the brief intervention group; n=24, 49% in the internet-based intervention group). Mean age was 44.5 (SD 13.3) years; most were male (n=29, 59.2%), had elementary school (n=22, 44.9%), smoked 14.5 cigarettes per day on average (SD 8.6), and had a mean score of 4.65 for nicotine dependence and 5.7 for motivation to quit. Moreover, 35 (71%) participants answered follow-up 1, and 19 (39%) answered follow-up 2. The results showed similar rates of cessation and reduction for both intervention groups.

Conclusions

The internet-based intervention was slightly more effective for smoking cessation, while the brief intervention was more effective in reducing the number of cigarettes smoked per day. This difference was small and had no statistical significance even after adjusting for intention-to-treat analysis. These results should be interpreted with caution, especially due to the small sample size.

Effectiveness of a voluntary casino self-exclusion online self-management program

Despite evidence for effectiveness, only a small proportion of individuals with gambling disorder ever access treatment and support resources for their problem. Voluntary self-exclusion (VSE) programs are an ideal circumstance to engage individuals who are reluctant or have not yet sought formal treatment, given that individuals are already electing to prevent themselves from gambling through self-exclusion. The present study was a randomized controlled trial of a novel, online VSE self-management intervention. Individuals who chose to self-exclude at gambling venues (N = 201) were randomly assigned to participate in an online self-management program combined with VSE or to an in-person self-awareness educational workshop combined with VSE comparison group. Following a baseline assessment, participants were followed up at three, six, and twelve months via telephone interviews. Measured outcomes were gambling frequency and expenditure, problem gambling scores, problem drinking scores, type of goal set for gambling behaviour, quality of life, and treatment-seeking. The 12-month follow-up rate was 71% (n = 143). Participants in both VSE groups gambled less, spent less money gambling, and reported decreased need for formal treatment. However, there were no significant group differences on any of the primary or secondary outcomes. Only 30-35% of the participants completed their assigned workshop, depending on the group. Results from the online program satisfaction survey revealed that participants generally liked the program and rated the quality of the content highly, but thought there could be improvement regarding interactivity, variety, stimulation and greater clarity around registration steps and program objectives. The online VSE program is an effective alternative to the face-to-face VSE program. Although the outcomes between the two programs were not significantly different, the online program is easier to administer, able to reach more individuals since it only requires access to a computer and is based on motivational evidence-based principles of psychotherapy for gambling disorder.

A Digital Smoking Cessation Program for Heavy Drinkers: Pilot Randomized Controlled Trial

Background

Heavy drinking (HD) is far more common among smokers compared with nonsmokers and interferes with successful smoking cessation. Alcohol-focused smoking cessation interventions delivered by counselors have shown promise, but digital versions of these interventions—which could have far greater population reach—have not yet been tested.

Objective

This pilot randomized controlled trial aimed to examine the feasibility, acceptability, and effect sizes of an automated digital smoking cessation program that specifically addresses HD using an interactive web-based intervention with an optional text messaging component.

Methods

Participants (83/119, 69.7% female; 98/119, 82.4% white; mean age 38.0 years) were daily smokers recruited on the web from a free automated digital smoking cessation program (BecomeAnEX.org, EX) who met the criteria for HD: women drinking 8+ drinks/week or 4+ drinks on any day and men drinking 15+ drinks/week or 5+ drinks on any day. Participants were randomized to receive EX with standard content (EX-S) or an EX with additional content specific to HD (EX-HD). Outcomes were assessed by web-based surveys at 1 and 6 months.

Results

Participants reported high satisfaction with the website and the optional text messaging component. Total engagement with both EX-S and EX-HD was modest, with participants visiting the website a median of 2 times, and 52.9% of the participants enrolled to receive text messages. Participants in both the conditions showed substantial, significant reductions in drinking across 6 months of follow-up, with no condition effects observed. Although smoking outcomes tended to favor EX-HD, the condition effects were small and nonsignificant. A significantly smaller proportion of participants in EX-HD reported having a lapse back to smoking when drinking alcohol (7/58, 16%) compared with those in EX-S (18/61, 41%; χ²₁=6.2; P=.01).

Conclusions

This is the first trial to examine a digital smoking cessation program tailored to HD smokers. The results provide some initial evidence that delivering such a program is feasible and may reduce the risk of alcohol-involved smoking lapses. However, increasing engagement in this and other web-based interventions is a crucial challenge to address in future work.

Trial Registration

ClinicalTrials.gov NCT03068611; https://clinicaltrials.gov/ct2/show/NCT03068611

Evaluation of nicotine patch adherence measurement using self-report and saliva cotinine among abstainers in a smoking cessation trial

BACKGROUND

Adherence to nicotine patches relates to cessation. This is the first study to examine the validity of self-reported nicotine patch adherence relative to saliva cotinine.

METHODS

We used data from 198 clinical trial participants who received 11 weeks of nicotine patches, self-reported patch use, had saliva cotinine 1-week after the start of treatment assessed, and were not smoking when saliva was collected (CO < 6). Self-reported patch adherence was defined as: 3-day (before saliva collection), 7-day (before saliva collection), 3-week use (7 days before, and 14 days after, saliva collection), and 11-week use (7 days before, and 10 weeks after, saliva collection). Analyses, including receiver operating characteristic curves, considered differences in nicotine metabolism. Sensitivity, specificity and positive (PPV) and negative predictive value (NPV) assessed optimal cotinine cut-point for adherence.

RESULTS

Self-reported 7-day (r = 0.13) and 3-week (r = 0.13) patch use marginally correlated with week 1 cotinine (p's = 0.08) but not 3-day or 11-week. Significant area under the curve (AUC) values of 0.67 (95 %CI: 0.55-0.79) and 0.72 (95 %CI: 0.57-0.88) were found using 7-day self-report for the overall sample and for slow metabolizers (p's<0.01), but not for normal metabolizers. Optimal 1-week cotinine cut-points using 7-day self-report were 170 ng/mL (overall) and 184 ng/mL (slow), with sensitivity = 0.56-0.62, specificity = 0.69-0.78, PPV = 0.96-0.97, and NPV = 0.13-0.14.

CONCLUSIONS

Among CO-confirmed abstainers, self-reported patch use and saliva cotinine assessed 1-week into treatment, were modestly correlated and optimal cotinine cut-point differed by rate of nicotine metabolism. Seven-day patch use may be a more valid self-report measure of patch adherence based on cotinine than 3-day, 3-week, or 11-week. Rate of nicotine metabolism may affect this relationship.

Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment

BACKGROUND

Smoking remains a leading cause of preventable death and illness. Internet interventions for smoking cessation have the potential to significantly impact public health, given their broad reach and proven effectiveness. Given the dose-response association between engagement and behavior change, identifying strategies to promote engagement is a priority across digital health interventions. Text messaging is a proven smoking cessation treatment modality and a powerful strategy to increase intervention engagement in other areas of health, but it has not been tested as an engagement strategy for a digital cessation intervention.

OBJECTIVE

This study examined the impact of 4 experimental text message design factors on adult smokers' engagement with an internet smoking cessation program.

METHODS

We conducted a 2×2×2×2 full factorial screening experiment wherein 864 participants were randomized to 1 of 16 experimental conditions after registering with a free internet smoking cessation program and enrolling in its automated text message program. Experimental factors were personalization (on/off), integration between the web and text message platforms (on/off), dynamic tailoring of intervention content based on user engagement (on/off), and message intensity (tapered vs abrupt drop-off). Primary outcomes were 3-month measures of engagement (ie, page views, time on site, and return visits to the website) as well as use of 6 interactive features of the internet program. All metrics were automatically tracked; there were no missing data.

RESULTS

Main effects were detected for integration and dynamic tailoring. Integration significantly increased interactive feature use by participants, whereas dynamic tailoring increased the number of features used and page views. No main effects were found for message intensity or personalization alone, although several synergistic interactions with other experimental features were observed. Synergistic effects, when all experimental factors were active, resulted in the highest rates of interactive feature use and the greatest proportion of participants at high levels of engagement. Measured in terms of standardized mean differences (SMDs), effects on interactive feature use were highest for Build Support System (SMD 0.56; 95% CI 0.27 to 0.81), Choose Quit Smoking Aid (SMD 0.38; 95% CI 0.10 to 0.66), and Track Smoking Triggers (SMD 0.33; 95% CI 0.05 to 0.61). Among the engagement metrics, the largest effects were on overall feature utilization (SMD 0.33; 95% CI 0.06 to 0.59) and time on site (SMD 0.29; 95% CI 0.01 to 0.57). As no SMD >0.30 was observed for main effects on any outcome, results suggest that for some outcomes, the combined intervention was stronger than individual factors alone.

CONCLUSIONS

This factorial experiment demonstrates the effectiveness of text messaging as a strategy to increase engagement with an internet smoking cessation intervention, resulting in greater overall intervention dose and greater exposure to the core components of tobacco dependence treatment that can promote abstinence.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02585206; https://clinicaltrials.gov/ct2/show/NCT02585206.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1136/bmjopen-2015-010687.

Predictors of adherence to nicotine replacement therapy: Machine learning evidence that perceived need predicts medication use

BACKGROUND

Nonadherence to smoking cessation medication is a frequent problem. Identifying pre-quit predictors of nonadherence may help explain nonadherence and suggest tailored interventions to address it.

AIMS

Identify and characterize subgroups of smokers based on adherence to nicotine replacement therapy (NRT).

METHOD

Secondary classification tree analyses of data from a 2-arm randomized controlled trial of Recommended Usual Care (R-UC, n = 315) versus Abstinence-Optimized Treatment (A-OT, n = 308) were conducted. R-UC comprised 8 weeks of nicotine patch plus brief counseling whereas A-OT comprised 3 weeks of pre-quit mini-lozenges, 26 weeks of nicotine patch plus mini-lozenges, 11 counseling contacts, and 7-11 automated reminders to use medication. Analyses identified subgroups of smokers highly adherent to nicotine patch use in both treatment conditions, and identified subgroups of A-OT participants highly adherent to mini-lozenges.

RESULTS

Varied facets of nicotine dependence predicted adherence across treatment conditions 4 weeks post-quit and between 4- and 16-weeks post-quit in A-OT, with greater baseline dependence and greater smoking trigger exposure and reactivity predicting greater medication use. Greater quitting motivation and confidence, and believing that stop smoking medication was safe and easy to use were associated with greater adherence.

CONCLUSION

Adherence was especially high in those who were more dependent and more exposed to smoking triggers. Quitting motivation and confidence predicted greater adherence, while negative beliefs about medication safety and acceptability predicted worse adherence. Results suggest that adherent use of medication may reflect a rational appraisal of the likelihood that one will need medication and will benefit from it.

Improving Adherence to Smoking Cessation Treatment: Smoking Outcomes in a Web-based Randomized Trial

Background

Partial adherence in Internet smoking cessation interventions presents treatment and evaluation challenges. Increasing adherence may improve outcomes.

Purpose

To present smoking outcomes from an Internet randomized trial of two strategies to encourage adherence to tobacco dependence treatment components: (i) a social network (SN) strategy to integrate smokers into an online community and (ii) free nicotine replacement therapy (NRT). In addition to intent-to-treat analyses, we used novel statistical methods to distinguish the impact of treatment assignment from treatment utilization.

Methods

A total of 5,290 current smokers on a cessation website (WEB) were randomized to WEB, WEB + SN, WEB + NRT, or WEB + SN + NRT. The main outcome was 30-day point prevalence abstinence at 3 and 9 months post-randomization. Adherence measures included self-reported medication use (meds), and website metrics of skills training (sk) and community use (comm). Inverse Probability of Retention Weighting and Inverse Probability of Treatment Weighting jointly addressed dropout and treatment selection. Propensity weights were used to calculate Average Treatment effects on the Treated.

Results

Treatment assignment analyses showed no effects on abstinence for either adherence strategy. Abstinence rates were 25.7%-32.2% among participants that used all three treatment components (sk+comm +meds).Treatment utilization analyses revealed that among such participants, sk+comm+meds yielded large percentage point increases in 3-month abstinence rates over sk alone across arms: WEB = 20.6 (95% CI = 10.8, 30.4), WEB + SN = 19.2 (95% CI = 11.1, 27.3), WEB + NRT = 13.1 (95% CI = 4.1, 22.0), and WEB + SN + NRT = 20.0 (95% CI = 12.2, 27.7).

Conclusions

Novel propensity weighting approaches can serve as a model for establishing efficacy of Internet interventions and yield important insights about mechanisms.

Clinical Trials.gov

NCT01544153.

Evaluating a Video-Based, Personalized Webpage in Genitourinary Oncology Clinical Trials: A Phase 2 Randomized Trial

Background

The pace of drug discovery and approvals has led to expanding treatments for cancer patients. Although extensive research exists regarding barriers to enrollment in oncology clinical trials, there are limited studies evaluating processes to optimize patient education, oral anticancer therapy administration, and adherence for patients enrolled in clinical trials. In this study, we assess the feasibility of a video-based, personalized webpage for patients enrolled in genitourinary oncology clinical trials involving 1 or more oral anticancer therapy.

Objective

The primary objective of this trial was to assess the differences in the number of patient-initiated violations in the intervention arm compared with a control arm over 4 treatment cycles. Secondary objectives included patient satisfaction, frequently asked questions by patients on the intervention arm, patient-initiated calls to study team members, and patient-reported stress levels.

Methods

Eligible patients enrolling on a therapeutic clinical trial for a genitourinary malignancy were randomized 2:1 to the intervention arm or control arm. Patients randomized to the intervention arm received access to a video-based, personalized webpage, which included videos of patients’ own clinic encounters with their providers, instructional videos on medication administration and side effects, and electronic versions of educational documents.

Results

A total of 99 patients were enrolled (89 were evaluable; 66 completed 4 cycles). In total, 71% (40/56) of patients in the intervention arm had 1 or more patient-initiated violation compared with 70% (23/33) in the control arm. There was no difference in the total number of violations across 4 cycles between the 2 arms (estimate=−0.0939, 95% CI−0.6295 to 0.4418, P value=.73). Median baseline satisfaction scores for the intervention and control arms were 72 and 73, respectively, indicating high levels of patient satisfaction in both arms. Median baseline patient-reported stress levels were 10 and 13 for the intervention and control arms, respectively, indicating low stress levels in both arms at baseline.

Conclusions

This study is among the first to evaluate a video-based, personalized webpage that provides patients with educational videos and video recordings of clinical trial appointments. Despite not meeting the primary endpoint of reduced patient-initiated violations, this study demonstrates the feasibility of a video-based, personalized webpage in clinical trials. Future research assessing this tool might be better suited for realms outside of clinical trials and might consider the use of an endpoint that assesses patient-reported outcomes directly. A major limitation of this study was the lack of prior data for estimating the null hypothesis in this population.

Predicting Outcomes from Engagement With Specific Components of an Internet-Based Physical Activity Intervention With Financial Incentives: Process Analysis of a Cluster Randomized Controlled Trial

Background

Investigating participant engagement and nonusage attrition can help identify the likely active ingredients of electronic health interventions. Research on engagement can identify which intervention components predict health outcomes. Research on nonusage attrition is important to make recommendations for retaining participants in future studies.

Objective

This study aimed to investigate engagement and nonusage attrition in the Physical Activity Loyalty (PAL) scheme, a 6-month complex physical activity intervention in workplaces in Northern Ireland. The intervention included financial incentives with reward redemption and self-regulation techniques. Specific objectives were (1) to determine whether engagement in specific intervention components predicted physical activity at 6 months, (2) to determine whether engagement in specific intervention components predicted targeted mediators at 6 months, and (3) to investigate predictors of nonusage attrition for participants recording daily activity via the PAL scheme physical activity monitoring system and logging onto the website.

Methods

Physical activity was assessed at baseline and 6 months using pedometers (Yamax Digiwalker CW-701, Japan). Markers of engagement and website use, monitoring system use, and reward redemption were collected throughout the scheme. Random-effects generalized least-squares regressions determined whether engagement with specific intervention components predicted 6-month physical activity and mediators. Cox proportional hazards regressions were used to investigate predictors of nonusage attrition (days until first 2-week lapse).

Results

A multivariable generalized least-squares regression model (n=230) showed that the frequency of hits on the website’s monitoring and feedback component (regression coefficient [b]=50.2; SE=24.5; P=.04) and the percentage of earned points redeemed for financial incentives (b=9.1; SE=3.3; P=.005) were positively related to 6-month pedometer steps per day. The frequency of hits on the discussion forum (b=−69.3; SE=26.6; P=.009) was negatively related to 6-month pedometer steps per day. Reward redemption was not related to levels of more internal forms of motivation. Multivariable Cox proportional hazards regression models identified several baseline predictors associated with nonusage attrition. These included identified regulation (hazard ratio [HR] 0.88, 95% CI 0.81-0.97), recovery self-efficacy (HR 0.88, 95% CI 0.80-0.98), and perceived workplace environment safety (HR 1.07, 95% CI 1.02-1.11) for using the physical activity monitoring system. The EuroQoL health index (HR 0.33, 95% CI 0.12-0.91), financial motivation (HR 0.93, 95% CI 0.87-0.99), and perceived availability of physical activity opportunities in the workplace environment (HR 0.96, 95% CI 0.93-0.99) were associated with website nonusage attrition.

Conclusions

Our results provide evidence opposing one of the main hypotheses of self-determination theory by showing that financial rewards are not necessarily associated with decreases in more internal forms of motivation when offered as part of a complex multicomponent intervention. Identifying baseline predictors of nonusage attrition can help researchers to develop strategies to ensure maximum intervention adherence.

Trial Registration

ISRCTN Registry ISRCTN17975376; http://www.isrctn.com/ISRCTN17975376 (Archived by WebCite at http://www.webcitation.org/76VGZsZug)

Interrelations between participant and intervention characteristics, process variables and outcomes in online interventions: A protocol for overarching analyses within and across seven clinical trials in ICare

BACKGROUND

It is well known that web-based interventions can be effective treatments for various conditions. Less is known about predictors, moderators, and mediators of outcome and especially interrelations between participant and interventions characteristics, process variables and outcomes in online interventions. Clinical trials often lack statistical power to detect variables that affect intervention effects and their interrelations. Within ICare, we can investigate the interrelation of potential predictor and process variables in a large sample.

METHOD

The ICare consortium postulated a model of interrelations between participant and intervention characteristics, process variables and outcomes in online interventions. We will assess general and disorder-specific interrelations between characteristics of the intervention, characteristics of the participants, adherence, working alliance, early response, and intervention outcomes in a sample of over 7500 participants from seven clinical trials evaluating 15 online interventions addressing a range of mental health conditions and disorders, using an individual participant data meta-analyses approach.

DISCUSSION/CONCLUSION

Existing research tends to support the efficacy of online mental health interventions, but the knowledge base regarding factors that affect intervention effects needs to be expanded. The overarching analyses using data from the ICare intervention trials will add considerably to the evidence.

Technological Interventions for Medication Adherence in Adult Mental Health and Substance Use Disorders: A Systematic Review

BACKGROUND

Medication adherence is critical to the effectiveness of psychopharmacologic therapy. Psychiatric disorders present special adherence considerations, notably an altered capacity for decision making and the increased street value of controlled substances. A wide range of interventions designed to improve adherence in mental health and substance use disorders have been studied; recently, many have incorporated information technology (eg, mobile phone apps, electronic pill dispensers, and telehealth). Many intervention components have been studied across different disorders. Furthermore, many interventions incorporate multiple components, making it difficult to evaluate the effect of individual components in isolation.

OBJECTIVE

The aim of this study was to conduct a systematic scoping review to develop a literature-driven, transdiagnostic taxonomic framework of technology-based medication adherence intervention and measurement components used in mental health and substance use disorders.

METHODS

This review was conducted based on a published protocol (PROSPERO: CRD42018067902) in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses systematic review guidelines. We searched 7 electronic databases: MEDLINE, EMBASE, PsycINFO, the Cochrane Central Register of Controlled Trials, Web of Science, Engineering Village, and ClinicalTrials.gov from January 2000 to September 2018. Overall, 2 reviewers independently conducted title and abstract screens, full-text screens, and data extraction. We included all studies that evaluate populations or individuals with a mental health or substance use disorder and contain at least 1 technology-delivered component (eg, website, mobile phone app, biosensor, or algorithm) designed to improve medication adherence or the measurement thereof. Given the wide variety of studied interventions, populations, and outcomes, we did not conduct a risk of bias assessment or quantitative meta-analysis. We developed a taxonomic framework for intervention classification and applied it to multicomponent interventions across mental health disorders.

RESULTS

The initial search identified 21,749 results; after screening, 127 included studies remained (Cohen kappa: 0.8, 95% CI 0.72-0.87). Major intervention component categories include reminders, support messages, social support engagement, care team contact capabilities, data feedback, psychoeducation, adherence-based psychotherapy, remote care delivery, secure medication storage, and contingency management. Adherence measurement components include self-reports, remote direct visualization, fully automated computer vision algorithms, biosensors, smart pill bottles, ingestible sensors, pill counts, and utilization measures. Intervention modalities include short messaging service, mobile phone apps, websites, and interactive voice response. We provide graphical representations of intervention component categories and an element-wise breakdown of multicomponent interventions.

CONCLUSIONS

Many technology-based medication adherence and monitoring interventions have been studied across psychiatric disease contexts. Interventions that are useful in one psychiatric disorder may be useful in other disorders, and further research is necessary to elucidate the specific effects of individual intervention components. Our framework is directly developed from the substance use disorder and mental health treatment literature and allows for transdiagnostic comparisons and an organized conceptual mapping of interventions.

Inferring Smoking Status from User Generated Content in an Online Cessation Community

Introduction

User generated content (UGC) is a valuable but underutilized source of information about individuals who participate in online cessation interventions. This study represents a first effort to passively detect smoking status among members of an online cessation program using UGC.

Methods

Secondary data analysis was performed on data from 826 participants in a web-based smoking cessation randomized trial that included an online community. Domain experts from the online community reviewed each post and comment written by participants and attempted to infer the author's smoking status at the time it was written. Inferences from UGC were validated by comparison with self-reported 30-day point prevalence abstinence (PPA). Following validation, the impact of this method was evaluated across all individuals and time points in the study period.

Results

Of the 826 participants in the analytic sample, 719 had written at least one post from which content inference was possible. Among participants for whom unambiguous smoking status was inferred during the 30 days preceding their 3-month follow-up survey, concordance with self-report was almost perfect (kappa = 0.94). Posts indicating abstinence tended to be written shortly after enrollment (median = 14 days).

Conclusions

Passive inference of smoking status from UGC in online cessation communities is possible and highly reliable for smokers who actively produce content. These results lay the groundwork for further development of observational research tools and intervention innovations.

Implications

A proof-of-concept methodology for inferring smoking status from user generated content in online cessation communities is presented and validated. Content inference of smoking status makes a key cessation variable available for use in observational designs. This method provides a powerful tool for researchers interested in online cessation interventions and establishes a foundation for larger scale application via machine learning.

Exposure to positive peer sentiment about nicotine replacement therapy in an online smoking cessation community is associated with NRT use

BACKGROUND

Little is known about the influence of online peer interactions on health behavior change. This study examined the relationship between exposure to peer sentiment about nicotine replacement therapy (NRT) in an online social network for smoking cessation and NRT use.

METHODS

Participants were 3297 current smokers who enrolled in an Internet smoking cessation program, participated in a randomized trial, and completed a 3-month follow-up. Half received free NRT as part of the trial. Automated text classification identified 27,038 posts about NRT that one or more participants were exposed to in the social network. Sentiment towards NRT was rated on Amazon Mechanical Turk. Participants' exposure to peer sentiment about NRT was determined by analysis of clickstream data. Modified Poisson regression examined self-reported use of NRT at 3-months as a function of exposure to NRT sentiment, controlling for study arm and post exposure.

RESULTS

One in five participants (19.3%, n = 639) were exposed to any NRT-related posts (mean exposure = 6.5 ± 14.7, mean sentiment = 5.4 ± 0.8). The association between sentiment exposure and NRT use varied by receipt of free NRT. Greater exposure to positive NRT sentiment was associated with an increased likelihood of NRT use among participants who did not receive free NRT (adjusted rate ratio 1.22, 95% CI 1.01, 1.47; p = .043), whereas no such relationship was observed among participants who did receive free NRT (p = .48).

CONCLUSIONS

Exposure to positive sentiment about NRT was associated with increased NRT use when smokers obtained it on their own. Highlighting user-generated content containing positive NRT sentiment may increase NRT use among treatment-seeking smokers.

How Online Communities of People With Long-Term Conditions Function and Evolve: Network Analysis of the Structure and Dynamics of the Asthma UK and British Lung Foundation Online Communities

Background

Self-management support can improve health and reduce health care utilization by people with long-term conditions. Online communities for people with long-term conditions have the potential to influence health, usage of health care resources, and facilitate illness self-management. Only recently, however, has evidence been reported on how such communities function and evolve, and how they support self-management of long-term conditions in practice.

Objective

The aim of this study is to gain a better understanding of the mechanisms underlying online self-management support systems by analyzing the structure and dynamics of the networks connecting users who write posts over time.

Methods

We conducted a longitudinal network analysis of anonymized data from 2 patients’ online communities from the United Kingdom: the Asthma UK and the British Lung Foundation (BLF) communities in 2006-2016 and 2012-2016, respectively.

Results

The number of users and activity grew steadily over time, reaching 3345 users and 32,780 posts in the Asthma UK community, and 19,837 users and 875,151 posts in the BLF community. People who wrote posts in the Asthma UK forum tended to write at an interval of 1-20 days and six months, while those in the BLF community wrote at an interval of two days. In both communities, most pairs of users could reach one another either directly or indirectly through other users. Those who wrote a disproportionally large number of posts (the superusers) represented 1% of the overall population of both Asthma UK and BLF communities and accounted for 32% and 49% of the posts, respectively. Sensitivity analysis showed that the removal of superusers would cause the communities to collapse. Thus, interactions were held together by very few superusers, who posted frequently and regularly, 65% of them at least every 1.7 days in the BLF community and 70% every 3.1 days in the Asthma UK community. Their posting activity indirectly facilitated tie formation between other users. Superusers were a constantly available resource, with a mean of 80 and 20 superusers active at any one time in the BLF and Asthma UK communities, respectively. Over time, the more active users became, the more likely they were to reply to other users’ posts rather than to write new ones, shifting from a help-seeking to a help-giving role. This might suggest that superusers were more likely to provide than to seek advice.

Conclusions

In this study, we uncover key structural properties related to the way users interact and sustain online health communities. Superusers’ engagement plays a fundamental sustaining role and deserves research attention. Further studies are needed to explore network determinants of the effectiveness of online engagement concerning health-related outcomes. In resource-constrained health care systems, scaling up online communities may offer a potentially accessible, wide-reaching and cost-effective intervention facilitating greater levels of self-management.

Nicotine replacement therapy versus control for smoking cessation

BACKGROUND

Nicotine replacement therapy (NRT) aims to temporarily replace much of the nicotine from cigarettes to reduce motivation to smoke and nicotine withdrawal symptoms, thus easing the transition from cigarette smoking to complete abstinence.

OBJECTIVES

To determine the effectiveness and safety of nicotine replacement therapy (NRT), including gum, transdermal patch, intranasal spray and inhaled and oral preparations, for achieving long-term smoking cessation, compared to placebo or 'no NRT' interventions.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group trials register for papers mentioning 'NRT' or any type of nicotine replacement therapy in the title, abstract or keywords. Date of most recent search is July 2017.

SELECTION CRITERIA

Randomized trials in people motivated to quit which compared NRT to placebo or to no treatment. We excluded trials that did not report cessation rates, and those with follow-up of less than six months, except for those in pregnancy (where less than six months, these were excluded from the main analysis). We recorded adverse events from included and excluded studies that compared NRT with placebo. Studies comparing different types, durations, and doses of NRT, and studies comparing NRT to other pharmacotherapies, are covered in separate reviews.

DATA COLLECTION AND ANALYSIS

Screening, data extraction and 'Risk of bias' assessment followed standard Cochrane methods. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically validated rates if available. We calculated the risk ratio (RR) for each study. Where appropriate, we performed meta-analysis using a Mantel-Haenszel fixed-effect model.

MAIN RESULTS

We identified 136 studies; 133 with 64,640 participants contributed to the primary comparison between any type of NRT and a placebo or non-NRT control group. The majority of studies were conducted in adults and had similar numbers of men and women. People enrolled in the studies typically smoked at least 15 cigarettes a day at the start of the studies. We judged the evidence to be of high quality; we judged most studies to be at high or unclear risk of bias but restricting the analysis to only those studies at low risk of bias did not significantly alter the result. The RR of abstinence for any form of NRT relative to control was 1.55 (95% confidence interval (CI) 1.49 to 1.61). The pooled RRs for each type were 1.49 (95% CI 1.40 to 1.60, 56 trials, 22,581 participants) for nicotine gum; 1.64 (95% CI 1.53 to 1.75, 51 trials, 25,754 participants) for nicotine patch; 1.52 (95% CI 1.32 to 1.74, 8 trials, 4439 participants) for oral tablets/lozenges; 1.90 (95% CI 1.36 to 2.67, 4 trials, 976 participants) for nicotine inhalator; and 2.02 (95% CI 1.49 to 2.73, 4 trials, 887 participants) for nicotine nasal spray. The effects were largely independent of the definition of abstinence, the intensity of additional support provided or the setting in which the NRT was offered. A subset of six trials conducted in pregnant women found a statistically significant benefit of NRT on abstinence close to the time of delivery (RR 1.32, 95% CI 1.04 to 1.69; 2129 participants); in the four trials that followed up participants post-partum the result was no longer statistically significant (RR 1.29, 95% CI 0.90 to 1.86; 1675 participants). Adverse events from using NRT were related to the type of product, and include skin irritation from patches and irritation to the inside of the mouth from gum and tablets. Attempts to quantitatively synthesize the incidence of various adverse effects were hindered by extensive variation in reporting the nature, timing and duration of symptoms. The odds ratio (OR) of chest pains or palpitations for any form of NRT relative to control was 1.88 (95% CI 1.37 to 2.57, 15 included and excluded trials, 11,074 participants). However, chest pains and palpitations were rare in both groups and serious adverse events were extremely rare.

AUTHORS' CONCLUSIONS

There is high-quality evidence that all of the licensed forms of NRT (gum, transdermal patch, nasal spray, inhalator and sublingual tablets/lozenges) can help people who make a quit attempt to increase their chances of successfully stopping smoking. NRTs increase the rate of quitting by 50% to 60%, regardless of setting, and further research is very unlikely to change our confidence in the estimate of the effect. The relative effectiveness of NRT appears to be largely independent of the intensity of additional support provided to the individual. Provision of more intense levels of support, although beneficial in facilitating the likelihood of quitting, is not essential to the success of NRT. NRT often causes minor irritation of the site through which it is administered, and in rare cases can cause non-ischaemic chest pain and palpitations.

Clarifying the Concept of Adherence to eHealth Technology: Systematic Review on When Usage Becomes Adherence

BACKGROUND

In electronic health (eHealth) evaluations, there is increasing attention for studying the actual usage of a technology in relation to the outcomes found, often by studying the adherence to the technology. On the basis of the definition of adherence, we suggest that the following three elements are necessary to determine adherence to eHealth technology: (1) the ability to measure the usage behavior of individuals; (2) an operationalization of intended use; and (3) an empirical, theoretical, or rational justification of the intended use. However, to date, little is known on how to operationalize the intended usage of and the adherence to different types of eHealth technology.

OBJECTIVE

The study aimed to improve eHealth evaluations by gaining insight into when, how, and by whom the concept of adherence has been used in previous eHealth evaluations and finding a concise way to operationalize adherence to and intended use of different eHealth technologies.

METHODS

A systematic review of eHealth evaluations was conducted to gain insight into how the use of the technology was measured, how adherence to different types of technologies was operationalized, and if and how the intended use of the technology was justified. Differences in variables between the use of the technology and the operationalization of adherence were calculated using a chi-square test of independence.

RESULTS

In total, 62 studies were included in this review. In 34 studies, adherence was operationalized as "the more use, the better," whereas 28 studies described a threshold for intended use of the technology as well. Out of these 28, only 6 reported a justification for the intended use. The proportion of evaluations of mental health technologies reporting a justified operationalization of intended use is lagging behind compared with evaluations of lifestyle and chronic care technologies. The results indicated that a justification of intended use does not require extra measurements to determine adherence to the technology.

CONCLUSIONS

The results of this review showed that to date, justifications for intended use are often missing in evaluations of adherence. Evidently, it is not always possible to estimate the intended use of a technology. However, such measures do not meet the definition of adherence and should therefore be referred to as the actual usage of the technology. Therefore, it can be concluded that adherence to eHealth technology is an underdeveloped and often improperly used concept in the existing body of literature. When defining the intended use of a technology and selecting valid measures for adherence, the goal or the assumed working mechanisms should be leading. Adherence can then be standardized, which will improve the comparison of adherence rates to different technologies with the same goal and will provide insight into how adherence to different elements contributed to the outcomes.

A prospective examination of online social network dynamics and smoking cessation

Introduction

Use of online social networks for smoking cessation has been associated with abstinence. Little is known about the mechanisms through which the formation of social ties in an online network may influence smoking behavior. Using dynamic social network analysis, we investigated how temporal changes of an individual’s number of social network ties are prospectively related to abstinence in an online social network for cessation. In a network where quitting is normative and is the focus of communications among members, we predicted that an increasing number of ties would be positively associated with abstinence.

Method

Participants were N = 2,657 adult smokers recruited to a randomized cessation treatment trial following enrollment on BecomeAnEX.org, a longstanding Internet cessation program with a large and mature online social network. At 3-months post-randomization, 30-day point prevalence abstinence was assessed and website engagement metrics were extracted. The social network was constructed with clickstream data to capture the flow of information among members. Two network centrality metrics were calculated at weekly intervals over 3 months: 1) in-degree, defined as the number of members whose posts a participant read; and 2) out-degree-aware, defined as the number of members who read a participant’s post and commented, which was subsequently viewed by the participant. Three groups of users were identified based on social network engagement patterns: non-users (N = 1,362), passive users (N = 812), and active users (N = 483). Logistic regression modeled 3-month abstinence by group as a function of baseline variables, website utilization, and network centrality metrics.

Results

Abstinence rates varied by group (non-users = 7.7%, passive users = 10.7%, active users = 20.7%). Significant baseline predictors of abstinence were age, nicotine dependence, confidence to quit, and smoking temptations in social situations among passive users (ps < .05); age and confidence to quit among active users. Among centrality metrics, positive associations with abstinence were observed for in-degree increases from Week 2 to Week 12 among passive and active users, and for out-degree-aware increases from Week 2 to Week 12 among active users (ps < .05).

Conclusions

This study is the first to demonstrate that increased tie formation among members of an online social network for smoking cessation is prospectively associated with abstinence. It also highlights the value of using individuals’ activities in online social networks to predict their offline health behaviors.