Questions about quitting (Q2): design and methods of a Multiphase Optimization Strategy (MOST) randomized screening experiment for an online, motivational smoking cessation intervention

Integration of e-Health Strategies for Post-COVID-19 Pandemic Pediatric Weight Management Programs

Background: The COVID-19 pandemic catalyzed a renewed urgency to address the obesity pandemic and accelerated the use of technology to treat pediatric obesity. Yet, there are significant incongruities between the existing literature on technology for obesity management and the current health care system that may lead to suboptimal outcomes and increased costs. This study reviewed the types of e-health strategies currently in use, highlighted inconsistencies and overlap in terminology, and identified future research directions in e-health for childhood obesity, including gaps in implementation science. Methods: This narrative literature review synthesized seminal articles from the literature, as well as recent articles, using PubMed and Google Scholar that focused on the use of technology in treating pediatric obesity. This inclusive strategy was intended to elucidate the heterogeneity in how different disciplines are using digital health terminology in pediatric obesity research. Results: Both the prevalence of e-health interventions and its associated terminology are increasing in the peer-reviewed literature, especially since the beginning of the COVID-19 pandemic. Yet, their definitions and usage are unstandardized, leading to a lack of cohesion in the research and between disciplines. There is a gap in implementation science outcomes, including reimbursement, that may significantly impact external validity and uptake. Conclusion: A more systematic and precise approach to researching e-health that can assess specific technologies and combinations of technologies, their short-term and long-term effect sizes, and feasibility can produce the necessary data that may lead to reimbursement policies and, ultimately, improved pediatric weight management outcomes.

Investigation of Active Ingredients Within Internet-Delivered Cognitive Behavioral Therapy for Depression: A Randomized Optimization Trial

Importance

There is limited understanding of how complex evidence-based psychological interventions such as cognitive behavioral therapy (CBT) for depression work. Identifying active ingredients may help to make therapy more potent, brief, and scalable.

Objective

To test the individual main effects and interactions of 7 treatment components within internet-delivered CBT for depression to investigate its active ingredients.

Design, Setting, and Participants

This randomized optimization trial using a 32-condition, balanced, fractional factorial optimization experiment (IMPROVE-2) recruited adults with depression (Patient Health Questionnaire-9 [PHQ-9] score ≥10) from internet advertising and the UK National Health Service Improving Access to Psychological Therapies service. Participants were randomized from July 7, 2015, to March 29, 2017, with follow-up for 6 months after treatment until December 29, 2017. Data were analyzed from July 2018 to April 2023.

Interventions

Participants were randomized with equal probability to 7 experimental factors within the internet CBT platform, each reflecting the presence vs absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, and self-compassion training).

Main Outcomes and Measures

The primary outcome was depression symptoms (PHQ-9 score). Secondary outcomes include anxiety symptoms and work, home, and social functioning.

Results

Among 767 participants (mean age [SD] age, 38.5 [11.62] years; range, 18-76 years; 635 women [82.8%]), 506 (66%) completed the 6-month posttreatment follow-up. On average, participants receiving internet-delivered CBT had reduced depression (pre-to-posttreatment difference in PHQ-9 score, -7.79 [90% CI, -8.21 to -7.37]; 6-month follow-up difference in PHQ-9 score, -8.63 [90% CI, -9.04 to -8.22]). A baseline score-adjusted analysis of covariance model using effect-coded intervention variables (-1 or +1) found no main effect on depression symptoms for the presence vs absence of activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, or self-compassion training (posttreatment: largest difference in PHQ-9 score [functional analysis], -0.09 [90% CI, -0.56 to 0.39]; 6-month follow-up: largest difference in PHQ-9 score [relaxation], -0.18 [90% CI, -0.61 to 0.25]). Only absorption training had a significant main effect on depressive symptoms at 6-month follow-up (posttreatment difference in PHQ-9 score, 0.21 [90% CI, -0.27 to 0.68]; 6-month follow-up difference in PHQ-9 score, -0.54, [90% CI, -0.97 to -0.11]).

Conclusions and Relevance

In this randomized optimization trial, all components of internet-delivered CBT except absorption training did not significantly reduce depression symptoms relative to their absence despite an overall average reduction in symptoms. The findings suggest that treatment benefit from internet-delivered CBT probably accrues from spontaneous remission, factors common to all CBT components (eg, structure, making active plans), and nonspecific therapy factors (eg, positive expectancy), with the possible exception of absorption focused on enhancing direct contact with positive reinforcers.

Trial Registration

isrctn.org Identifier: ISRCTN24117387.

Successful Optimization of Tobacco Dependence Treatment in the Emergency Department: A Randomized Controlled Trial Using the Multiphase Optimization Strategy

STUDY OBJECTIVE

Tobacco dependence treatment initiated in the hospital emergency department (ED) is effective. However, trials typically use multicomponent interventions, making it difficult to distinguish specific components that are effective. In addition, interactions between components cannot be assessed. The Multiphase Optimization Strategy allows investigators to identify these effects.

METHODS

We conducted a full-factorial, 24 or 16-condition optimization trial in a busy hospital ED to examine the performance of 4 tobacco dependence interventions: a brief negotiation interview; 6 weeks of nicotine replacement therapy with the first dose delivered in the ED; active referral to a telephone quitline; and enrollment in SmokefreeTXT, a free short-messaging service program. Study data were analyzed with a novel mixed methods approach to assess clinical efficacy, cost-effectiveness, and qualitative participant feedback. The primary endpoint was tobacco abstinence at 3 months, verified by exhaled carbon monoxide using a Bedfont Micro+ Smokerlyzer.

RESULTS

Between February 2017 and May 2019, we enrolled 1,056 adult smokers visiting the ED. Odd ratios (95% confidence intervals) from the primary analysis of biochemically confirmed abstinence rates at 3 months for each intervention, versus control, were: brief negotiation interview, 1.8 (1.1, 2.8); nicotine replacement therapy, 2.1 (1.3, 3.2); quitline, 1.4 (0.9, 2.2); SmokefreeTXT, 1.1 (0.7, 1.7). There were no statistically significant interactions among components. Economic and qualitative analyses are in progress.

CONCLUSION

The brief negotiation interview and nicotine replacement therapy were efficacious. This study is the first to identify components of ED-initiated tobacco dependence treatment that are individually effective. Future work will address the scalability of the brief negotiation interview and nicotine replacement therapy by offering provider-delivered brief negotiation interviews and nicotine replacement therapy prescriptions.

A Proof-of-Concept Pilot Test of a Behavioral Intervention to Improve Adherence to Dietary Recommendations for Cancer Prevention

OBJECTIVES

Prevention programs that can help adults improve the quality of their diets to reduce cancer risk are needed. This Phase IIa study prospectively tested a mHealth intervention designed to improve adherence to dietary quality guidelines for cancer prevention.

METHODS

All participants (N = 62) received nutrition education and a self-regulation skills curriculum, with a primary target of changing grocery shopping behavior. Using a randomized, factorial design, the study varied whether each of the following 4 components were added to the 20-week intervention: (1) location-triggered app messaging, delivered when individuals arrived at grocery stores, (2) reflections on benefits of change, delivered with extra coaching time and tailored app messages, (3) coach monitoring, in which food purchases were digitally monitored by a coach, and (4) involvement of a household member in the intervention.

RESULTS

Benchmarks were successfully met for recruitment, retention, and treatment acceptability. Across conditions, there were significant reductions in highly processed food intake (P < .001, η2 = .48), red and processed meat intake (P < .001, η2 = .20), and sugar-sweetened beverage intake (P = .008, η2 = .13) from pre-to post-treatment. Analyses examining whether each intervention component influenced change across time found that participants who received coach monitoring increased their intake of fruits, vegetables, and fiber, whereas those with no coach monitoring had less improvement (P = .01, η2 = .14). The improvement in red and processed meat was stronger among participants with household support ON, at a marginally significant level, than those with household support OFF (P = .056, η2 = .07).

CONCLUSION

This study showed feasibility, acceptability, and preliminary signals of efficacy of a remotely delivered intervention to facilitate adherence to dietary guidelines for cancer prevention and that coach monitoring and household support may be especially effective strategies. A fully powered clinical trial is warranted to test an optimized version of the intervention that includes nutrition education, self-regulation skills training, coach monitoring, and household member involvement.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04947150.

One view of the next decade of research on behavioral and biobehavioral approaches to cancer prevention and control: intervention optimization

As a new decade begins, we propose that the time is right to reexamine current methods and procedures and look for opportunities to accelerate progress in cancer prevention and control. In this article we offer our view of the next decade of research on behavioral and biobehavioral interventions for cancer prevention and control. We begin by discussing and questioning several implicit conventions. We then briefly introduce an alternative research framework: the multiphase optimization strategy (MOST). MOST, a principled framework for intervention development, optimization, and evaluation, stresses not only intervention effectiveness, but also intervention affordability, scalability, and efficiency. We review some current limitations of MOST along with future directions for methodological work in this area, and suggest some changes in the scientific environment we believe would permit wider adoption of intervention optimization. We propose that wider adoption of intervention optimization would have a positive impact on development and successful implementation of interventions for cancer prevention and control and on intervention science more broadly, including accumulation of a coherent base of knowledge about what works and what does not; establishment of an empirical basis for adaptation of interventions to different settings with different levels and types of resources; and, in the long run, acceleration of progress from Stage 0 to Stage V in the National Institutes of Health Model of Stages of Intervention Development.

The preparation phase in the multiphase optimization strategy (MOST): a systematic review and introduction of a reporting checklist

Multicomponent behavioral interventions developed using the multiphase optimization strategy (MOST) framework offer important advantages over alternative intervention development models by focusing on outcomes within constraints relevant for effective dissemination. MOST consists of three phases: preparation, optimization, and evaluation. The preparation phase is critical to establishing the foundation for the optimization and evaluation phases; thus, detailed reporting is critical to enhancing rigor and reproducibility. A systematic review of published research using the MOST framework was conducted. A structured framework was used to describe and summarize the use of MOST terminology (i.e., preparation phase and optimization objective) and the presentation of preparation work, the conceptual model, and the optimization. Fifty-eight articles were reviewed and the majority focused on either describing the methodology or presenting results of an optimization trial (n = 38, 66%). Although almost all articles identified intervention components (96%), there was considerable variability in the degree to which authors fully described other elements of MOST. In particular, there was less consistency in use of MOST terminology. Reporting on the MOST preparation phase is varied, and there is a need for increased focus on explicit articulation of key design elements and rationale of the preparation phase. The proposed checklist for reporting MOST studies would significantly advance the use of this emerging methodology and improve implementation and dissemination of MOST. Accurate reporting is essential to reproducibility and rigor of scientific trials as it ensures future research fully understands not only the methodology, but the rationale for intervention and optimization decisions.

How to optimise public health interventions: a scoping review of guidance from optimisation process frameworks

Background

Optimisation processes have the potential to rapidly improve the impact of health interventions. Optimisation can be defined as a deliberate, iterative and data-driven process to improve a health intervention and/or its implementation to meet stakeholder-defined public health impacts within resource constraints. This study aimed to identify frameworks used to optimise the impact of health interventions and/or their implementation, and characterise the key concepts, steps or processes of identified frameworks.

Methods

A scoping review of MEDLINE, CINAL, PsycINFO, and ProQuest Nursing & Allied Health Source databases was undertaken. Two reviewers independently coded the key concepts, steps or processes involved in each frameworks, and identified if it was a framework aimed to optimise interventions or their implementation. Two review authors then identified the common steps across included frameworks.

Results

Twenty optimisation frameworks were identified. Eight frameworks were for optimising interventions, 11 for optimising implementation and one covered both intervention and implementation optimisation. The mean number of steps within the frameworks was six (range 3–9). Almost half (n = 8) could be classified as both linear and cyclic frameworks, indicating that some steps may occur multiple times in a single framework. Two meta-frameworks are proposed, one for intervention optimisation and one for implementation strategy optimisation. Steps for intervention optimisation are: Problem identification; Preparation; Theoretical/Literature base; Pilot/Feasibility testing; Optimisation; Evaluation; and Long-term implementation. Steps for implementation strategy optimisation are: Problem identification; Collaborate; Plan/design; Pilot; Do/change; Study/evaluate/check; Act; Sustain/endure; and Disseminate/extend.

Conclusions

This review provides a useful summary of the common steps followed to optimise a public health intervention or its implementation according to established frameworks. Further opportunities to study and/or validate such frameworks and their impact on improving outcomes exist.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-09950-5.

Using the Multiphase Optimization Strategy (MOST) framework to test intervention delivery strategies: a study protocol

Background

Delivery of behavioral interventions is complex, as the majority of interventions consist of multiple components used either simultaneously, sequentially, or both. The importance of clearly delineating delivery strategies within these complex interventions—and furthermore understanding the impact of each strategy on effectiveness—has recently emerged as an important facet of intervention research. Yet, few methodologies exist to prospectively test the effectiveness of delivery strategies and how they impact implementation. In the current paper, we describe a study protocol for a large randomized controlled trial in which we will use the Multiphase Optimization Strategy (MOST), a novel framework developed to optimize interventions, i.e., to test the effectiveness of intervention delivery strategies using a factorial design. We apply this framework to delivery of Family Navigation (FN), an evidence-based care management strategy designed to reduce disparities and improve access to behavioral health services, and test four components related to its implementation.

Methods/design

The MOST framework contains three distinct phases: Preparation, Optimization, and Evaluation. The Preparation phase for this study occurred previously. The current study consists of the Optimization and Evaluation phases. Children aged 3-to-12 years old who are detected as “at-risk” for behavioral health disorders (n = 304) at a large, urban federally qualified community health center will be referred to a Family Partner—a bicultural, bilingual member of the community with training in behavioral health and systems navigation—who will perform FN. Families will then be randomized to one of 16 possible combinations of FN delivery strategies (2 × 2 × 2× 2 factorial design). The primary outcome measure will be achieving a family-centered goal related to behavioral health services within 90 days of randomization. Implementation data on the fidelity, acceptability, feasibility, and cost of each strategy will also be collected. Results from the primary and secondary outcomes will be reviewed by our team of stakeholders to optimize FN delivery for implementation and dissemination based on effectiveness, efficiency, and cost.

Discussion

In this protocol paper, we describe how the MOST framework can be used to improve intervention delivery. These methods will be useful for future studies testing intervention delivery strategies and their impact on implementation.

Trial registration

ClinicalTrials.gov, NCT03569449. Registered on 26 June 2018.

Tobacco dependence treatment in the emergency department: A randomized trial using the Multiphase Optimization Strategy

BACKGROUND

Tobacco dependence remains the leading preventable cause of death in the developed world. Smokers are disproportionately from lower socioeconomic groups, and may use the hospital emergency department (ED) as an important source of care. A recent clinical trial demonstrated the efficacy of a multicomponent intervention to help smokers quit, but the independent contributions of those components is unknown.

METHODS

This is a full-factorial (16-arm) randomized trial in a busy hospital ED of 4 tobacco dependence interventions: brief motivational interviewing, nicotine replacement therapy, referral to a telephone quitline, and a texting program. The trial utilizes the Multiphase Optimization Strategy (MOST) and a novel mixed methods analytic design to assess clinical efficacy, cost effectiveness, and qualitative participant feedback. The primary endpoint is tobacco abstinence at 3months, verified by participants' exhaled carbon monoxide.

RESULTS

Study enrollment began in February 2017. As of April 2017, 52 of 1056 planned participants (4.9%) were enrolled. Telephone-based semi-structured participant interviews and in-person biochemical verification of smoking abstinence are completed at the 3-month follow-up. Efficacy and cost effectiveness analyses will be conducted after follow-up is completed.

DISCUSSION

The goal of this study is to identify a clinically efficacious, cost-effective intervention package for the initial treatment of tobacco dependence in ED patients. The efficacy of this combination can then be tested in a subsequent confirmatory trial. Our approach incorporates qualitative feedback from study participants in evaluating which intervention components will be tested in the future trial.

TRIAL REGISTRATION

Trial (NCT02896400) registered in ClinicalTrials.gov on September 6, 2016.

A Multimedia Support Skills Intervention for Female Partners of Male Smokeless Tobacco Users: Use and Perceived Acceptability

Background

UCare is a new multimedia (website+booklet) intervention for women who want their male partner to quit their use of smokeless tobacco. The intervention is based on research showing that perceived partner responsiveness to social support is highest when the supporter conveys respect, understanding, and caring in their actions. The website included both didactic and interactive features, with optional video components, and special activities to help women develop empathy for nicotine addiction. The booklet reinforced the website content, encouraged women to use the website, and served both as a physical reminder of the intervention and a convenient way to share the information with her partner.

Objective

The objective of this study was to describe the utilization and acceptability of a multimedia intervention among women seeking to support their partner in quitting smokeless tobacco. Lessons learned with respect to design considerations for online interventions are also summarized.

Methods

We present the evaluation of the intervention components' use and usefulness in a randomized trial.

Results

In the randomized clinical trial, more than 250,000 visits were made to the website in a 2-year period, with the vast majority from mobile devices. Of the 552 women randomized to receive the intervention, 96.9% (535/552) visited the website at least once, and 30.8% (170/552) completed the core website component, "The Basics." About half of the women (287/552) used the interactive "Take Notes" feature, and 37% (204/552) used the checklists. Few women used the post-Basics features. At 6 weeks, 40.7% (116/285) reported reading the printed and mailed booklet. Website and booklet use were uncorrelated. User ratings for the website and booklet were positive overall.

Conclusions

Intervention website designers should consider that many users will access the program only once or twice, and many will not complete it. It is also important to distinguish between core and supplemental features and to consider whether the primary purpose is training or support. Furthermore, printed materials still have value.

Trial Registration

ClinicalTrials.gov NCT01885221; https://clinicaltrials.gov/ct2/show/NCT01885221 (Archived by WebCite at http://www.webcitation.org/6zdIgGGtx).

Internet-based interventions for smoking cessation

BACKGROUND

Tobacco use is estimated to kill 7 million people a year. Nicotine is highly addictive, but surveys indicate that almost 70% of US and UK smokers would like to stop smoking. Although many smokers attempt to give up on their own, advice from a health professional increases the chances of quitting. As of 2016 there were 3.5 billion Internet users worldwide, making the Internet a potential platform to help people quit smoking.

OBJECTIVES

To determine the effectiveness of Internet-based interventions for smoking cessation, whether intervention effectiveness is altered by tailoring or interactive features, and if there is a difference in effectiveness between adolescents, young adults, and adults.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group Specialised Register, which included searches of MEDLINE, Embase and PsycINFO (through OVID). There were no restrictions placed on language, publication status or publication date. The most recent search was conducted in August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs). Participants were people who smoked, with no exclusions based on age, gender, ethnicity, language or health status. Any type of Internet intervention was eligible. The comparison condition could be a no-intervention control, a different Internet intervention, or a non-Internet intervention. To be included, studies must have measured smoking cessation at four weeks or longer.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed and extracted data. We extracted and, where appropriate, pooled smoking cessation outcomes of six-month follow-up or more, reporting short-term outcomes narratively where longer-term outcomes were not available. We reported study effects as a risk ratio (RR) with a 95% confidence interval (CI).We grouped studies according to whether they (1) compared an Internet intervention with a non-active control arm (e.g. printed self-help guides), (2) compared an Internet intervention with an active control arm (e.g. face-to-face counselling), (3) evaluated the addition of behavioural support to an Internet programme, or (4) compared one Internet intervention with another. Where appropriate we grouped studies by age.

MAIN RESULTS

We identified 67 RCTs, including data from over 110,000 participants. We pooled data from 35,969 participants.There were only four RCTs conducted in adolescence or young adults that were eligible for meta-analysis.Results for trials in adults: Eight trials compared a tailored and interactive Internet intervention to a non-active control. Pooled results demonstrated an effect in favour of the intervention (RR 1.15, 95% CI 1.01 to 1.30, n = 6786). However, statistical heterogeneity was high (I² = 58%) and was unexplained, and the overall quality of evidence was low according to GRADE. Five trials compared an Internet intervention to an active control. The pooled effect estimate favoured the control group, but crossed the null (RR 0.92, 95% CI 0.78 to 1.09, n = 3806, I² = 0%); GRADE quality rating was moderate. Five studies evaluated an Internet programme plus behavioural support compared to a non-active control (n = 2334). Pooled, these studies indicated a positive effect of the intervention (RR 1.69, 95% CI 1.30 to 2.18). Although statistical heterogeneity was substantial (I² = 60%) and was unexplained, the GRADE rating was moderate. Four studies evaluated the Internet plus behavioural support compared to active control. None of the studies detected a difference between trial arms (RR 1.00, 95% CI 0.84 to 1.18, n = 2769, I² = 0%); GRADE rating was moderate. Seven studies compared an interactive or tailored Internet intervention, or both, to an Internet intervention that was not tailored/interactive. Pooled results favoured the interactive or tailored programme, but the estimate crossed the null (RR 1.10, 95% CI 0.99 to 1.22, n = 14,623, I² = 0%); GRADE rating was moderate. Three studies compared tailored with non-tailored Internet-based messages, compared to non-tailored messages. The tailored messages produced higher cessation rates compared to control, but the estimate was not precise (RR 1.17, 95% CI 0.97 to 1.41, n = 4040), and there was evidence of unexplained substantial statistical heterogeneity (I² = 57%); GRADE rating was low.Results should be interpreted with caution as we judged some of the included studies to be at high risk of bias.

AUTHORS' CONCLUSIONS

The evidence from trials in adults suggests that interactive and tailored Internet-based interventions with or without additional behavioural support are moderately more effective than non-active controls at six months or longer, but there was no evidence that these interventions were better than other active smoking treatments. However some of the studies were at high risk of bias, and there was evidence of substantial statistical heterogeneity. Treatment effectiveness in younger people is unknown.

An Overview of Research and Evaluation Designs for Dissemination and Implementation

The wide variety of dissemination and implementation designs now being used to evaluate and improve health systems and outcomes warrants review of the scope, features, and limitations of these designs. This article is one product of a design workgroup that was formed in 2013 by the National Institutes of Health to address dissemination and implementation research, and whose members represented diverse methodologic backgrounds, content focus areas, and health sectors. These experts integrated their collective knowledge on dissemination and implementation designs with searches of published evaluations strategies. This article emphasizes randomized and nonrandomized designs for the traditional translational research continuum or pipeline, which builds on existing efficacy and effectiveness trials to examine how one or more evidence-based clinical/prevention interventions are adopted, scaled up, and sustained in community or service delivery systems. We also mention other designs, including hybrid designs that combine effectiveness and implementation research, quality improvement designs for local knowledge, and designs that use simulation modeling.

Implementing multifactorial psychotherapy research in online virtual environments (IMPROVE-2): study protocol for a phase III trial of the MOST randomized component selection method for internet cognitive-behavioural therapy for depression

BACKGROUND

Depression is a global health challenge. Although there are effective psychological and pharmaceutical interventions, our best treatments achieve remission rates less than 1/3 and limited sustained recovery. Underpinning this efficacy gap is limited understanding of how complex psychological interventions for depression work. Recent reviews have argued that the active ingredients of therapy need to be identified so that therapy can be made briefer, more potent, and to improve scalability. This in turn requires the use of rigorous study designs that test the presence or absence of individual therapeutic elements, rather than standard comparative randomised controlled trials. One such approach is the Multiphase Optimization Strategy, which uses efficient experimentation such as factorial designs to identify active factors in complex interventions. This approach has been successfully applied to behavioural health but not yet to mental health interventions.

METHODS/DESIGN

A Phase III randomised, single-blind balanced fractional factorial trial, based in England and conducted on the internet, randomized at the level of the patient, will investigate the active ingredients of internet cognitive-behavioural therapy (CBT) for depression. Adults with depression (operationalized as PHQ-9 score ≥ 10), recruited directly from the internet and from an UK National Health Service Improving Access to Psychological Therapies service, will be randomized across seven experimental factors, each reflecting the presence versus absence of specific treatment components (activity scheduling, functional analysis, thought challenging, relaxation, concreteness training, absorption, self-compassion training) using a 32-condition balanced fractional factorial design (2_IV^7-2). The primary outcome is symptoms of depression (PHQ-9) at 12 weeks. Secondary outcomes include symptoms of anxiety and process measures related to hypothesized mechanisms.

DISCUSSION

Better understanding of the active ingredients of efficacious therapies, such as CBT, is necessary in order to improve and further disseminate these interventions. This study is the first application of a component selection experiment to psychological interventions in depression and will enable us to determine the main effect of each treatment component and its relative efficacy, and cast light on underlying mechanisms, so that we can systematically enhance internet CBT.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN24117387 . Registered 26 August 2014.

Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol

INTRODUCTION

Millions of smokers use the Internet for smoking cessation assistance each year; however, most smokers engage minimally with even the best designed websites. The ubiquity of mobile devices and their effectiveness in promoting adherence in other areas of health behaviour change make them a promising tool to address adherence in Internet smoking cessation interventions. Text messaging is used by most adults, and messages can proactively encourage use of a web-based intervention. Text messaging can also be integrated with an Internet intervention to facilitate the use of core Internet intervention components.

METHODS AND ANALYSIS

We identified four aspects of a text message intervention that may enhance its effectiveness in promoting adherence to a web-based smoking cessation programme: personalisation, integration, dynamic tailoring and message intensity. Phase I will use a two-level full factorial design to test the impact of these four experimental features on adherence to a web-based intervention. The primary outcome is a composite metric of adherence that incorporates general utilisation metrics (eg, logins, page views) and specific feature utilisation shown to predict abstinence. Participants will be N=860 adult smokers who register on an established Internet cessation programme and enrol in its text message programme. Phase II will be a two-arm randomised trial to compare the efficacy of the web-based cessation programme alone and in conjunction with the optimised text messaging intervention on 30-day point prevalence abstinence at 9 months. Phase II participants will be N=600 adult smokers who register to use an established Internet cessation programme and enrol in text messaging. Secondary analyses will explore whether adherence mediates the effect of treatment condition on outcome.

ETHICS AND DISSEMINATION

This protocol was approved by Chesapeake IRB. We will disseminate study results through peer-reviewed manuscripts and conference presentations related to the methods and design, outcomes and exploratory analyses.

TRIAL REGISTRATION NUMBER

NCT02585206.

Acceptance and Commitment Therapy and nicotine patch for smokers with bipolar disorder: preliminary evaluation of in-person and telephone-delivered treatment

OBJECTIVES

People with bipolar disorder are two to three times more likely to smoke and 50% less likely to quit than the general population. New treatments are needed to improve smoking cessation outcomes in this group. The study aim was to develop and pilot test a novel cessation intervention for smokers with bipolar disorder using Acceptance and Commitment Therapy (ACT) combined with nicotine patches.

METHODS

The ten-session ACT intervention was initially evaluated as in-person, individual counseling (n = 10), then as telephone-delivered counseling (n = 6). Participants were adult smokers with no more than mild current symptoms of bipolar disorder.

RESULTS

For the in-person protocol, end-of-treatment outcomes were: 80% retention, 40% of participants with carbon monoxide (CO)-verified seven-day point prevalence abstinence (PPA), 90% satisfied with treatment, 8.3 of ten sessions attended, and 54% increase in acceptance of cravings to smoke (i.e., ACT's theory-based change process) from baseline. The seven-day PPA at one-month follow-up was 30%. For the telephone protocol, end-of-treatment outcomes were: 67% retention, 33% reporting seven-day PPA, 100% satisfied with treatment, 6.7 of ten treatment calls completed, and 55% increase in acceptance from baseline. At one-month follow-up, seven-day PPA was 17%. The proportion of treatment completers who used at least 80% of the nicotine patches was 62.5% for the in-person protocol and 0% for the telephone protocol.

CONCLUSIONS

Both in-person and telephone-delivered ACT were feasible. Despite low adherence to nicotine patches, the intervention showed preliminary evidence of facilitating quitting and impacting ACT's change mechanism. A randomized, controlled trial of this targeted ACT intervention is now needed.

Impact of a brief telephone referral on quitline use, quit attempts and abstinence

Quitline use can prompt quit attempts and promote abstinence among smokers, but rates of use are low and outcomes of brief quitline referrals unclear. In this study, a brief intervention was delivered to smokers who expressed motivation to quit in the next 30 days (N = 221) to encourage use of their state quitline. Correlates of quitline use were examined, and quitline callers versus non-callers were compared on the following outcomes at 2-month follow-up: cessation medication use, quit attempts and abstinence. Of the 221 smokers given a quitline referral, 34% called the quitline. Baseline motivation alone distinguished quitline callers from non-callers. Quitline use was positively associated with use of cessation medication, an association that remained robust even after adjusting for baseline motivation to quit. A trend was observed in which callers were marginally more likely than non-callers to report both a 24-h quit attempt and 7-day point prevalence abstinence. Relative to non-callers, callers also endorsed greater confidence to quit and increased self-efficacy to resist smoking temptations at follow-up. This study demonstrates a minimal intervention can promote acceptance of quitlines and favorable cessation outcomes among smokers motivated to quit.

Internet interventions for mental health and addictions: current findings and future directions

Over the last several years, there has been a substantial increase in the number of publications reporting on Internet interventions for mental health and addictions. This paper provides a summary of the recent research on Internet interventions for the most common mental health and addictions concerns-depression, anxiety, alcohol and smoking. There is considerable evidence for the effectiveness of Internet-based interventions targeting depression, anxiety disorders, alcohol use and smoking. Small to moderate effect sizes have been reported for interventions targeting depression, anxiety and alcohol use, and smoking interventions have shown large effects. The addition of human support to depression and anxiety interventions has generally resulted in larger treatments effects, but this trend has not been observed in trials of interventions targeting alcohol use. There is some evidence that online interventions can be as effective as face-to-face therapies, at least for anxiety disorders. Despite a proliferation of research activity in this area, gaps in knowledge remain. Future research should focus on the development and evaluation of interventions for different platforms (e.g. smartphone applications), examining the long-term impacts of these interventions, determining active intervention components and identifying methods for enhancing tailoring and engagement. Careful consideration should be given to the ongoing technical and clinical expertise required to ensure that Internet interventions are delivered safely and professionally in a rapidly changing technology environment.

Factorial experiments: efficient tools for evaluation of intervention components

BACKGROUND

An understanding of the individual and combined effects of a set of intervention components is important for moving the science of preventive medicine interventions forward. This understanding can often be achieved in an efficient and economical way via a factorial experiment, in which two or more independent variables are manipulated. The factorial experiment is a complement to the RCT; the two designs address different research questions.

PURPOSE

To offer an introduction to factorial experiments aimed at investigators trained primarily in the RCT.

METHODS

The factorial experiment is compared and contrasted with other experimental designs used commonly in intervention science to highlight where each is most efficient and appropriate.

RESULTS

Several points are made: factorial experiments make very efficient use of experimental subjects when the data are properly analyzed; a factorial experiment can have excellent statistical power even if it has relatively few subjects per experimental condition; and when conducting research to select components for inclusion in a multicomponent intervention, interactions should be studied rather than avoided.

CONCLUSIONS

Investigators in preventive medicine and related areas should begin considering factorial experiments alongside other approaches. Experimental designs should be chosen from a resource management perspective, which states that the best experimental design is the one that provides the greatest scientific benefit without exceeding available resources.

Moving beyond the treatment package approach to developing behavioral interventions: addressing questions that arose during an application of the Multiphase Optimization Strategy (MOST)

Given current pressures to increase the public health contributions of behavioral interventions, intervention scientists may wish to consider moving beyond the classical treatment package approach that focuses primarily on achieving statistical significance. They may wish also to focus on goals directly related to optimizing public health impact. The Multiphase Optimization Strategy (MOST) is an innovative methodological framework that draws on engineering principles to achieve more potent behavioral interventions. MOST is increasingly being adopted by intervention scientists seeking a systematic framework to engineer an optimized intervention. As with any innovation, there are challenges that arise with early adoption. This article describes the solutions to several critical questions that we addressed during the first-ever iterative application of MOST. Specifically, we describe how we have applied MOST to optimize an online program (myPlaybook) for the prevention of substance use among college student-athletes. Our application of MOST can serve as a blueprint for other intervention scientists who wish to design optimized behavioral interventions. We believe using MOST is feasible and has the potential to dramatically improve program effectiveness thereby advancing the public health impact of behavioral interventions.

Exploring the "active ingredients" of an online smoking intervention: a randomized factorial trial

INTRODUCTION

Research needs to systematically identify which components increase online intervention effectiveness (i.e., active ingredients). This study explores the effects of 4 potentially important design features in an Internet-based, population-level smoking intervention.

METHODS

Smokers (n = 1,865) were recruited from a large health care organization, regardless of readiness to quit. Using a full factorial design, participants were randomized to 1 of the 2 levels of each experimental factor (message tone [prescriptive vs. motivational], navigation autonomy [dictated vs. not], e-mail reminders [yes vs. no], and receipt of personally tailored testimonials [yes vs. no]) and provided access to the online intervention. Primary outcomes were self-reported 7-day point-prevalent smoking abstinence and confirmed utilization of adjunct treatment (pharmacotherapy or phone counseling) available through the health plan at 1 year. Outcomes were also assessed at 2 and 6 months and were examined among all enrolled participants (intent-to-treat [ITT]) and all who viewed the intervention (modified ITT).

RESULTS

At 1 year, 13.7% were abstinent and 26.0% utilized adjunct treatment. None of the contrasting factor levels differentially influenced abstinence or treatment utilization at 12 months. In the modified ITT sample, smokers receiving testimonials were less likely to use adjunct treatment at 6 months (odds ratio = 0.54, 95% confidence interval = 0.30-0.98, p = .04).

CONCLUSIONS

None of the design features enhanced treatment outcome. The negative effect observed for testimonials is provocative, but it should be viewed with caution. This study offers a model for future research testing the "active ingredients" of online interventions.

Using multiple imputations to accommodate time-outs in online interventions

BACKGROUND

Accurately estimating the period of time that individuals are exposed to online intervention content is important for understanding program engagement. This can be calculated from time-stamped data reflecting navigation to and from individual webpages. Prolonged periods of inactivity are commonly handled with a time-out feature and assigned a prespecified exposure duration. Unfortunately, this practice can lead to biased results describing program exposure.

OBJECTIVE

The aim of the study was to describe how multiple imputations can be used to better account for the time spent viewing webpages that result in a prolonged period of inactivity or a time-out.

METHODS

To illustrate this method, we present data on time-outs collected from the Q(2) randomized smoking cessation trial. For this analysis, we evaluate the effects on intervention exposure of receiving content written in a prescriptive versus motivational tone. Using multiple imputations, we created five complete datasets in which the time spent viewing webpages that resulted in a time-out were replaced with values estimated with imputation models. We calculated standard errors using Rubin's formulas to account for the variability due to the imputations. We also illustrate how current methods of accounting for time-outs (excluding timed-out page views or assigning an arbitrary viewing time) can influence conclusions about participant engagement.

RESULTS

A total of 63.00% (1175/1865) of participants accessed the online intervention in the Q(2) trial. Of the 6592 unique page views, 683 (10.36%, 683/6592) resulted in a time-out. The median time spent viewing webpages that did not result in a time-out was 1.07 minutes. Assuming participants did not spend any time viewing a webpage that resulted in a time-out, no difference between the two message tones was observed (ratio of mean time online: 0.87, 95% CI 0.75-1.02). Assigning 30 minutes of viewing time to all page views that resulted in a time-out concludes that participants who received content in a motivational tone spent less time viewing content (ratio of mean time online: 0.86, 95% CI 0.77-0.98) than those participants who received content in a prescriptive tone. Using multiple imputations to account for time-outs concludes that there is no difference in participant engagement between the two message tones (ratio of mean time online: 0.87; 95% CI 0.75-1.01).

CONCLUSIONS

The analytic technique chosen can significantly affect conclusions about online intervention engagement. We propose a standardized methodology in which time spent viewing webpages that result in a time-out is treated as missing information and corrected with multiple imputations.

TRIAL REGISTRATION

Clinicaltrials.gov NCT00992264; http://clinicaltrials.gov/ct2/show/NCT00992264 (Archived by WebCite at http://www.webcitation.org/6Kw5m8EkP).

The effect of program design on engagement with an internet-based smoking intervention: randomized factorial trial

BACKGROUND

Participant engagement influences treatment effectiveness, but it is unknown which intervention design features increase treatment engagement for online smoking cessation programs.

OBJECTIVE

We explored the effects of 4 design features (ie, factors) on early engagement with an Internet-based, motivational smoking cessation program.

METHODS

Smokers (N=1865) were recruited from a large health care organization to participate in an online intervention study, regardless of their interest in quitting smoking. The program was intended to answer smokers' questions about quitting in an effort to motivate and support cessation. Consistent with the screening phase in the multiphase optimization strategy (MOST), we used a 2-level, full-factorial design. Each person was randomized to 1 of 2 levels of each factor, including message tone (prescriptive vs motivational), navigation autonomy (dictated vs not), proactive email reminders (yes vs no), and inclusion of personally tailored testimonials (yes vs no). The effects of each factor level on program engagement during the first 2 months of enrollment were compared, including number of visits to the website resulting in intervention content views (as opposed to supplemental content views), number of intervention content areas viewed, number of intervention content pages viewed, and duration of time spent viewing this content, as applicable to each factor.

RESULTS

Adjusting for baseline readiness to quit, persons who received content written in a prescriptive tone made the same number of visits to the website as persons receiving content in a motivational tone, but viewed 1.17 times as many content areas (95% CI 1.08-1.28; P<.001) and 1.15 times as many pages (95% CI 1.04-1.28; P=.009). Time spent viewing materials did not differ among groups (P=.06). Persons required to view content in a dictated order based on their initial readiness to quit made the same number of visits as people able to freely navigate the site, but viewed fewer content areas (ratio of means 0.80, 95% CI 0.74-0.87; P<.001), 1.17 times as many pages (95% CI 1.06-1.31; P=.003), and spent 1.37 times more minutes online (95% CI 1.17-1.59; P<.001). Persons receiving proactive email reminders made 1.20 times as many visits (95% CI 1.09-1.33; P<.001), viewed a similar number of content areas as persons receiving no reminders, viewed 1.58 times as many pages (95% CI 1.48-1.68; P<.001), and spent 1.51 times as many minutes online (95% CI 1.29-1.77; P<.001) as those who did not receive proactive emails. Tailored testimonials did not significantly affect engagement.

CONCLUSIONS

Using a prescriptive message tone, dictating content viewing order, and sending reminder emails each resulted in greater program engagement relative to the contrasting level of each experimental factor. The results require replication, but suggest that a more directive interaction style may be preferable for online cessation programs.

TRIAL REGISTRATION

clinicaltrials.gov NCT00992264; http://clinicaltrials.gov/ct2/show/NCT00992264 (Archived by WebCite at http://www.webcitation.org/6F7H7lr3P).