Toward an era of impact of digital contingency management in the treatment of substance use disorders.

Digital contingency management entails remote methods to obtain biochemical confirmation of drug status and provide desirable, tangible consequences contingent on abstinence. Advances in digital CM suggest that it may be on the cusp of making a public health impact. Specific advances include technological capabilities and affordability, companies that specialize in digital CM, policies and reimbursement models, and the increasing availability of resources related to CM. Digital CM has expanded from cigarette smoking to alcohol and illicit substance misuse, and to include a diverse range of underserved and high-risk groups (e.g., pregnant and postpartum women, socioeconomically disadvantaged individuals, adolescents, and rural populations). Although the digital divide continues to narrow, culturally responsive methods may increase uptake and engagement with digital CM. The promise of digital CM is widescale access to an evidence-based treatment with low staff burden, no side effects, high fidelity engagement, acceptability, and effectiveness, and greater equity. We may be close to realizing this promise.

Cost evaluation of tobacco control interventions in clinical settings: A systematic review.

Elucidating the cost implications of tobacco control interventions is a prerequisite to their adoption in clinical settings. This review fills a knowledge gap in characterizing the extent to which cost is measured in tobacco control studies. A search of English literature was conducted in the following electronic databases: MEDLINE, EconLit, PsychINFO, and CINAHL using MeSH terms from 2009 to 2018. Studies were reviewed by two independent reviewers and included if they were conducted in U.S. inpatient or outpatient facilities and reported costs associated with a tobacco control intervention. They were categorized according to evaluation type, clinical setting, target population, cost measures, and stakeholder perspective. Bias risk was evaluated for RCTs. Seventeen publications were included, representing counseling interventions (n = 8) and combination (i.e., counseling and pharmacotherapy) interventions (n = 9). Studies were categorized by evaluation type: cost-effectiveness analysis (n = 10), cost utility analysis (n = 3) and cost identification (n = 4). The selected studies targeted the following populations: general adults (n = 6), hospitalized/inpatient (n = 4), military/veterans (n = 4), individuals with low socioeconomic status (n = 4), mental health or medical comorbidities (n = 2), and pregnant women (n = 2). Intervention costs included personnel, medication, education material, technology, and overhead costs. Stakeholder perspectives included: healthcare organization (n = 10), payer (n = 8), patient (n = 2), and societal (n = 1). Few studies have reported the cost of tobacco control interventions in clinical settings. Cost is a critical outcome that should be consistently measured in evaluations of tobacco control interventions to promote their uptake in clinical settings.

Web-Based Contingency Management for Adolescent Tobacco Smokers: A Clinical Trial.

INTRODUCTION: Adolescence is a critical time when the majority of tobacco users initiate smoking. Contingency management for adolescent smoking cessation has shown promise in previous studies, but efficacy following removal of contingencies is not well understood. This study examined a remote form of contingency management among non-treatment-seeking adolescent smokers. METHODS: Participants (N = 127) submitted breath carbon monoxide (CO) three times daily throughout a 42-day program. For this randomized trial, participants in the active condition (n = 63) were reinforced for providing CO measurements on schedule and below a set criterion, whereas those in the control condition (n = 64) were reinforced for providing CO measurements on schedule. Self-reported smoking and urinary cotinine levels were collected at several timepoints. RESULTS: Active condition showed greater within-group reductions in CO levels relative to control condition, but not at 3- or 6-month follow-up. Active condition reported significantly less smoking during treatment compared to control condition, but not at follow-up. There were no significant differences for urinary cotinine. Overall treatment adherence was low, with only 37% and 51% of possible CO samples being submitted among active and control, respectively. Poor treatment adherence may explain the disparity between CO and cotinine results, and poor follow-up treatment efficacy. CONCLUSIONS: This study replicates feasibility of a remote form of contingency management for adolescent smoking. CO results suggest active condition reduced smoking within group, but treatment adherence and posttreatment efficacy was poor. Future research should focus on increasing adherence for this type of program among adolescent smokers. IMPLICATIONS: This study demonstrates feasibility of a remote form of contingency management therapy for smoking cessation among adolescents, while providing posttreatment efficacy data. Within-group efficacy of this form of treatment is suggested, but treatment adherence and follow-up efficacy were poor. This study underscores the need for further development of contingency management therapy for adolescent smoking cessation, which emphasizes better treatment adherence and posttreatment efficacy.

Craving to Quit: A Randomized Controlled Trial of Smartphone App-Based Mindfulness Training for Smoking Cessation.

INTRODUCTION: Mindfulness training may reduce smoking rates and lessen the association between craving and smoking. This trial tested the efficacy of mindfulness training via smartphone app to reduce smoking. Experience sampling (ES) was used to measure real-time craving, smoking, and mindfulness. METHODS: A researcher-blind, parallel randomized controlled trial compared the efficacy of mobile mindfulness training with experience sampling (MMT-ES; Craving to Quit) versus experience sampling only (ES) to (1) increase 1-week point-prevalence abstinence rates at 6 months, and (2) lessen the association between craving and smoking. A modified intent-to-treat approach was used for treatment starters (MMT-ES n = 143; ES n = 182; 72% female, 81% white, age 41 ± 12 year). RESULTS: No group difference was found in smoking abstinence at 6 months (overall, 11.1%; MMT-ES, 9.8%; ES, 12.1%; χ2(1) = 0.43, p = .51). From baseline to 6 months, both groups showed a reduction in cigarettes per day (p < .0001), craving strength (p < .0001) and frequency (p < .0001), and an increase in mindfulness (p < .05). Using ES data, a craving by group interaction was observed (F(1,3785) = 3.71, p = .05) driven by a stronger positive association between craving and cigarettes per day for ES (t = 4.96, p < .0001) versus MMT-ES (t = 2.03, p = .04). Within MMT-ES, the relationship between craving and cigarettes per day decreased as treatment completion increased (F(1,104) = 4.44, p = .04). CONCLUSIONS: Although mindfulness training via smartphone app did not lead to reduced smoking rates compared with control, our findings provide preliminary evidence that mindfulness training via smartphone app may help lessen the association between craving and smoking, an effect that may be meaningful to support quitting in the longer term. IMPLICATIONS: This is the first reported full-scale randomized controlled trial of any smartphone app for smoking cessation. Findings provide preliminary evidence that smartphone app-based MMT-ES may lessen the association between craving and smoking. TRIAL REGISTRATION: Clinicaltrials.gov NCT02134509.

Leveraging technology to address the problem of cigarette smoking among women of reproductive age.

Women of reproductive age and particularly pregnant women underutilize evidence-based smoking cessation services such as counseling and quit lines. Mobile health (mHealth) may constitute an unexplored and innovative avenue for providing smoking cessation support to a population that is otherwise difficult to reach with evidence-based interventions. Female respondents aged 18-44 years (N = 10,023) were drawn from the first wave of the Population Assessment of Tobacco and Health (PATH) study (2013-2014). We examined prevalence of use of various digital forms of communication (e.g., social media, text messaging, smartphone ownership) among non-pregnant women of reproductive age, pregnant women, and among smokers versus non-smokers within these groups. Multiple logistic regression modeling was conducted to identify correlates of using each digital form adjusting for smoking status, pregnancy, and demographic characteristics. Over two thirds of women overall and within subgroups of non-pregnant and pregnant smokers reported using social media, owning a cell phone, owning a smartphone, downloading apps, and sending/receiving text messages. Current smokers and those with lower educational attainment generally had lower odds of using each digital form relative to non-smokers and those with higher educational attainment, the exception being that smokers had higher odds of using social media relative to non-smokers. The high prevalence of using various digital forms among both non-pregnant smokers of reproductive age and pregnant smokers suggests that leveraging technology to expand access to prevention, education, and treatment resources may reduce smoking-attributable adverse health effects among reproductive-aged women and their offspring.

Evidence-based tobacco treatment utilization among dual users of cigarettes and E-cigarettes.

Dual users of e-cigarettes and cigarettes may represent a unique and receptive population for evidence-based tobacco dependence treatment. We measured the frequency of quit attempts during the past year, and the use of evidence-based tobacco dependence treatments (i.e., behavioral and/or pharmacological treatments), among adult smokers who are current e-cigarette users (dual users) compared with those who do not use e-cigarettes (exclusive smokers). Data were analyzed from the 2015 National Health Interview Survey. Multivariate-adjusted regression models were used to examine the correlates of tobacco treatment use among adult smokers, comparing current e-cigarette users with those who did not use e-cigarettes, stratifying by age group, and adjusting for sociodemographic characteristics. Analyses were based on 5415 adult current cigarette smokers. Compared to exclusive smokers, dual users were more likely to report a quit attempt in the past year among adults <65 years: 18-24 years (odds ratio [OR] = 2.25), 25-44 years (OR = 1.60), and 45-64 years (OR = 1.96). With the exception of adults ≥65 years, dual users reported low rates of using combination (behavioral and pharmacological) treatments that were not statistically different from exclusive smokers: 18-24 years (0.1% vs. 2.1%, respectively), 25-44 years (4.3% vs. 4.7%), and 45-64 years (3.0% vs. 8.3%). Despite higher likelihood for dual users to make a quit attempt, their use of evidence-based tobacco treatment is low, similar to exclusive smokers. Dual users of cigarettes and e-cigarettes represent a prime target for interventions to expand access and utilization of evidence-based tobacco use treatments.

Harnessing Facebook for Smoking Reduction and Cessation Interventions: Facebook User Engagement and Social Support Predict Smoking Reduction.

BACKGROUND: Social media technologies offer a novel opportunity for scalable health interventions that can facilitate user engagement and social support, which in turn may reinforce positive processes for behavior change. OBJECTIVE: By using principles from health communication and social support literature, we implemented a Facebook group-based intervention that targeted smoking reduction and cessation. This study hypothesized that participants' engagement with and perceived social support from our Facebook group intervention would predict smoking reduction. METHODS: We recruited 16 regular smokers who live in the United States and who were motivated in quitting smoking at screening. We promoted message exposure as well as engagement and social support systems throughout the intervention. For message exposure, we posted prevalidated, antismoking messages (such as national antismoking campaigns) on our smoking reduction and cessation Facebook group. For engagement and social support systems, we delivered a high degree of engagement and social support systems during the second and third week of the intervention and a low degree of engagement and social support systems during the first and fourth week. A total of six surveys were conducted via Amazon Mechanical Turk (MTurk) at baseline on a weekly basis and at a 2-week follow-up. RESULTS: Of the total 16 participants, most were female (n=13, 81%), white (n=15, 94%), and between 25 and 50 years of age (mean 34.75, SD 8.15). There was no study attrition throughout the 6-time-point baseline, weekly, and follow-up surveys. We generated Facebook engagement and social support composite scores (mean 19.19, SD 24.35) by combining the number of likes each participant received and the number of comments or wall posts each participant posted on our smoking reduction and cessation Facebook group during the intervention period. The primary outcome was smoking reduction in the past 7 days measured at baseline and at the two-week follow-up. Compared with the baseline, participants reported smoking an average of 60.56 fewer cigarettes per week (SD 38.83) at the follow-up, and 4 participants out of 16 (25%) reported 7-day point prevalence smoking abstinence at the follow-up. Adjusted linear regression models revealed that a one-unit increase in the Facebook engagement and social support composite scores predicted a 0.56-unit decrease in cigarettes smoked per week (standard error =.24, P=.04, 95% CI 0.024-1.09) when baseline readiness to quit, gender, and baseline smoking status were controlled (F4, 11=8.85, P=.002). CONCLUSIONS: This study is the first Facebook group-based intervention that systemically implemented health communication strategies and engagement and social support systems to promote smoking reduction and cessation. Our findings imply that receiving one like or posting on the Facebook-based intervention platform predicted smoking approximately one less cigarette in the past 7 days, and that interventions should facilitate user interactions to foster user engagement and social support.

A randomized controlled trial of smartphone-based mindfulness training for smoking cessation: a study protocol.

BACKGROUND: Tobacco use is responsible for the death of about 1 in 10 individuals worldwide. Mindfulness training has shown preliminary efficacy as a behavioral treatment for smoking cessation. Recent advances in mobile health suggest advantages to smartphone-based smoking cessation treatment including smartphone-based mindfulness training. This study evaluates the efficacy of a smartphone app-based mindfulness training program for improving smoking cessation rates at 6-months follow-up. METHODS/DESIGN: A two-group parallel-randomized clinical trial with allocation concealment will be conducted. Group assignment will be concealed from study researchers through to follow-up. The study will be conducted by smartphone and online. Daily smokers who are interested in quitting smoking and own a smartphone (n = 140) will be recruited through study advertisements posted online. After completion of a baseline survey, participants will be allocated randomly to the control or intervention group. Participants in both groups will receive a 22-day smartphone-based treatment program for smoking. Participants in the intervention group will receive mobile mindfulness training plus experience sampling. Participants in the control group will receive experience sampling-only. The primary outcome measure will be one-week point prevalence abstinence from smoking (at 6-months follow-up) assessed using carbon monoxide breath monitoring, which will be validated through smartphone-based video chat. DISCUSSION: This is the first intervention study to evaluate smartphone-based delivery of mindfulness training for smoking cessation. Such an intervention may provide treatment in-hand, in real-world contexts, to help individuals quit smoking. TRIAL REGISTRATION: Clinicaltrials.gov NCT02134509 . Registered 7 May 2014.

Physical activity behavior, barriers to activity, and opinions about a smartphone-based physical activity intervention among rural residents.

BACKGROUND: Rural Americans engage in less physical activity (PA) and experience higher rates of consequent health problems (i.e., obesity, cardiovascular disease) than urban Americans. Although geographic barriers have historically made this population hard to reach, rural individuals are increasingly gaining access to smartphones. Thus, the purpose of this study was to evaluate PA behavior and barriers to PA among rural residents and to gauge their receptiveness to a smartphone-based PA intervention that is currently in the development stage. MATERIALS AND METHODS: Rural Floridian adults (n=113), 18 years of age and older, completed surveys to assess PA behavior, PA barriers, and opinions about an intervention to increase PA. Specifically, they were asked to imagine a program that would require them to do PA with their mobile phones and whether they viewed intended aspects of the program as helpful. The present work is therefore formative research that sought to determine the feasibility and acceptability of a smartphone-based intervention among rural residents. RESULTS of the survey will inform the development of a tailored, smartphone-based PA intervention. RESULTS: The 37.2% of participants with low PA levels (<600 metabolic equivalent [MET]-min per week) were more likely to report personal and environmental barriers to PA than the 47.8% of participants with moderate PA levels (≥600 MET-min per week). More barriers were reported among participants who self-reported as white and among participants of older age, lower education level, and lower socioeconomic status. Additionally, 75.9% of participants reported features of the intervention as at least somewhat helpful. CONCLUSIONS: The growing ubiquity of smartphones among rural residents, combined with participants' positive response to the program description, supports the acceptability of a smartphone-based PA intervention for rural communities. Given the participants' receptiveness, future research should evaluate the efficacy of smartphone-delivered health behavior interventions among this population.

A New Frontier: Integrating Behavioral and Digital Technology to Promote Health Behavior.

Modifiable behavioral risk factors such as cigarette smoking, physical inactivity, and obesity contribute to over 40 % of premature deaths in the USA. Advances in digital and information technology are creating unprecedented opportunities for behavior analysts to assess and modify these risk factors. Technological advances include mobile devices, wearable sensors, biomarker detectors, and real-time access to therapeutic support via information technology. Integrating these advances with behavioral technology in the form of conceptually systematic principles and procedures could usher in a new generation of effective and scalable behavioral interventions targeting health behavior. In this selective review of the literature, we discuss how technological tools can assess and modify a range of antecedents and consequences of healthy and unhealthy behavior. We also describe practical, methodological, and conceptual advantages for behavior analysts that stem from the use of technology to assess and treat health behavior.

A mobile-phone-based breath carbon monoxide meter to detect cigarette smoking.

INTRODUCTION: Mobile phones hold considerable promise for delivering evidence-based smoking cessation interventions that require frequent and objective assessment of smoking status via breath carbon monoxide (Breath CO) measurement. However, there are currently no commercially available mobile-phone-based Breath CO meters. We developed a mobile-phone-based Breath CO meter prototype that attaches to and communicates with a smartphone through an audio port. We then evaluated the reliability and the validity of Breath CO measures collected with the mobile meter prototype and assessed the usability and acceptability of the meter. METHODS: Participants included 20 regular smokers (≥10 cigarettes/day), 20 light smokers (<10 cigarettes/day), and 20 nonsmokers. Expired air samples were collected 4 times from each participant: twice with the mobile meter and twice with a commercially available Breath CO meter. RESULTS: Measures calculated by the mobile meter correlated strongly with measures calculated by the commercial meter (r = .96, p < .001). Additionally, the mobile meter accurately distinguished between smokers and nonsmokers. The area under the receiver-operating characteristic curve for the mobile meter was 94.7%, and the meter had a combined sensitivity and specificity of 1.86 at an abstinence threshold of ≤6 ppm. Responses on an acceptability survey indicated that smokers liked the meter and would be interested in using it during a quit attempt. CONCLUSIONS: The results of our study suggest that a mobile-phone-based Breath CO meter is a reliable, valid, and acceptable device for distinguishing between smokers and nonsmokers.

Single-case experimental designs to evaluate novel technology-based health interventions.

Technology-based interventions to promote health are expanding rapidly. Assessing the preliminary efficacy of these interventions can be achieved by employing single-case experiments (sometimes referred to as n-of-1 studies). Although single-case experiments are often misunderstood, they offer excellent solutions to address the challenges associated with testing new technology-based interventions. This paper provides an introduction to single-case techniques and highlights advances in developing and evaluating single-case experiments, which help ensure that treatment outcomes are reliable, replicable, and generalizable. These advances include quality control standards, heuristics to guide visual analysis of time-series data, effect size calculations, and statistical analyses. They also include experimental designs to isolate the active elements in a treatment package and to assess the mechanisms of behavior change. The paper concludes with a discussion of issues related to the generality of findings derived from single-case research and how generality can be established through replication and through analysis of behavioral mechanisms.

Reducing problematic social media use via a package intervention.

Problematic social media use can be characterized as that which interferes with relationships, work, school, or sleep. Currently, there are no empirically supported treatments for reducing problematic social media use. We tested a package intervention to reduce the daily duration of social media use measured by a smartphone application with nine undergraduate students who scored as "addicted" to social media via a version of the Internet Addiction Test. The package intervention included contingency management, automated notifications of application use, and the selection of alternative activities. The package intervention was effective at reducing the daily duration of social media use to goal levels, or below, for all participants. Eight out of nine participants showed a decrease in their Internet Addiction Test scores from pre- to postintervention, and overall, participants did not show an increase in the time spent engaged in their selected alternative activities. These findings demonstrate that social media use is amenable to behavioral treatment.

An evaluation of methods for studying the effects of conditioned reinforcement on human choice.

Shahan et al. (2006) found that the relative rate of pigeons' pecking on two observing responses (i.e., responses that only produced an S+ or stimulus correlated with primary reinforcement) was well described by the relative rate of S+ delivery. Researchers have not evaluated the effects of S+ delivery rate in a concurrent observing response procedure with human subjects, so the necessary procedural modifications for studying the effects of conditioned reinforcement on human choice remain unclear. The purpose of the current study was to conduct an additive component analysis of modifications to the procedures of Shahan et al. (2006). We evaluated the additive effects of introducing response cost, a changeover response, and ordinal discriminative stimuli on correspondence with the results of Shahan et al. and the quality of fits of the generalized matching equation. When our procedures were most similar to those of Shahan et al., we observed low rates of observing and indifference between the two observing responses. For the group of subjects with whom all three additive components were included, we obtained the highest level of sensitivity to relative rate of S+ delivery, but the slope and R2 of our fits of the generalized matching equation were still much lower than those obtained by Shahan et al. Potential reasons for these discrepancies, methods of resolving them, and implications for future research are discussed.

Effects of economic context and reward amount on delay and probability discounting.

Steep delay and shallow probability discounting are associated with myriad problem behaviors; thus, it is important to understand factors that influence the degree of discounting. The present study evaluated the effects of economic context and reward amount on delay and probability discounting. Two hundred thirteen undergraduate psychology students completed four delay- or probability-discounting tasks. Participants were exposed to hypothetical narratives involving four bank amounts ($750, $12,000, $125,000, and $2,000,000). The delayed/probabilistic amount was $3,000 for the two smaller bank amounts and $500,000 for the two larger bank amounts. The discounting tasks included five delays to, or probabilities of, receipt of the larger amount. The area under the empirical discounting function was calculated for each participant. Participants discounted delayed and uncertain outcomes more when the bank amount was smaller than the outcome (i.e., the economic context was low). Participants discounted the delayed larger amounts less than delayed smaller amounts, even when the relative economic context was the same. In contrast, probability discounting did not differ across magnitudes, which suggests that economic context may attenuate the magnitude effect in probability discounting. The results further highlight the importance of considering the economic context in delay and probability discounting.

Comparative effectiveness of mobile health smoking cessation approaches among underserved patients in primary care: Study protocol for the PROMOTE-UP trial.

INTRODUCTION: Tobacco smoking is the leading cause of preventable disease, disability, and premature death in the United States. Recent advances have led to two efficacious mobile health (mHealth) treatments for smoking cessation: iCanQuit, an Acceptance and Commitment Therapy-based behavioral treatment promoting cessation through accepting triggers and committing to values; and Motiv8, a contingency management intervention promoting smoking cessation with financial incentives via biochemically verified abstinence. This study will evaluate the comparative effectiveness of the Florida Quitline, iCanQuit alone, and iCanQuit+Motiv8 in a pragmatic trial among patients who smoke in underserved primary care settings. METHODS: The study will be an individually-randomized controlled trial with three arms (Florida Quitline, iCanQuit alone, iCanQuit+Motiv8 combined) conducted in multiple primary care practices affiliated with the OneFlorida+ Clinical Research Consortium. Adult patients who smoke will be randomized to one of the 3 study arms (n = 444/arm), stratified by healthcare setting (academic vs. community). The primary outcome will be 7-day point prevalence smoking abstinence at 6 months post-randomization. Secondary outcomes will be 12-month smoking abstinence, patient satisfaction with the interventions, and changes in patient quality of life and self-efficacy. The study will also assess how and for whom the interventions help sub-group patients in achieving smoking abstinence by measuring theory-derived factors that mediate smoking outcome-specific baseline moderators. CONCLUSIONS: Results from this study will provide evidence for the comparative effectiveness of mHealth smoking cessation interventions in healthcare settings. Use of mHealth interventions can make smoking cessation resources more equitably accessible and have far-reaching impact on community and population health. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05415761, Registered 13 June 2022.

Monetary-based consequences for drug abstinence: methods of implementation and some considerations about the allocation of finances in substance abusers.

UNLABELLED: Conceptualizing drug abuse within the framework of behavioral theories of choice highlights the relevance of environmental variables in shifting behavior away from drug-related purchases. Choosing to use drugs results in immediate and certain consequences (e.g., drug high and relief from withdrawal), whereas choosing abstinence typically results in delayed, and often uncertain, consequences (e.g., improved health, interpersonal relationships, money). METHODS: This is a selective review of the literature on Contingency management (CM). RESULTS: We highlight a variety of methods to deliver CM in practical, effective, and sustainable ways. We consider a number of parameters that are critical to the success of monetary-based CM, and the role of the context in influencing CM's effects. To illustrate the broad range of applications of CM, we also review different methods for arranging contingencies to promote abstinence and other relevant behavior. Finally, we discuss some considerations about how drug-dependent individuals allocate their finances in the context of CM interventions. CONCLUSIONS: Contingency management (CM) increases choice for drug abstinence via the availability of immediate, financial-based gains, contingent on objective evidence of abstinence.

The Family of Single-Case Experimental Designs.

Single-case experimental designs (SCEDs) represent a family of research designs that use experimental methods to study the effects of treatments on outcomes. The fundamental unit of analysis is the single case-which can be an individual, clinic, or community-ideally with replications of effects within and/or between cases. These designs are flexible and cost-effective and can be used for treatment development, translational research, personalized interventions, and the study of rare diseases and disorders. This article provides a broad overview of the family of single-case experimental designs with corresponding examples, including reversal designs, multiple baseline designs, combined multiple baseline/reversal designs, and integration of single-case designs to identify optimal treatments for individuals into larger randomized controlled trials (RCTs). Personalized N-of-1 trials can be considered a subcategory of SCEDs that overlaps with reversal designs. Relevant issues for each type of design-including comparisons of treatments, design issues such as randomization and blinding, standards for designs, and statistical approaches to complement visual inspection of single-case experimental designs-are also discussed.

Ecological Momentary Assessment: A Systematic Review of Validity Research.

Ecological momentary assessment (EMA) is a self-report method that involves intensive longitudinal assessment of behavior and environmental conditions during everyday activities. EMA has been used extensively in health and clinical psychology to investigate a variety of health behaviors, including substance use, eating, medication adherence, sleep, and physical activity. However, it has not been widely implemented in behavior analytic research. This is likely an example of the empirically based skepticism with which behavioral scientists view self-report measures. We reviewed studies comparing electronic, mobile EMA (mEMA) to more objective measures of health behavior to explore the validity of mEMA as a measurement tool, and to identify procedures and factors that may promote the accuracy of mEMA. We identified 32 studies that compared mEMA to more objective measures of health behavior or environmental events (e.g., biochemical measures or automated devices such as accelerometers). Results showed that the correspondence rates varied considerably across individuals, behavior, and studies (agreement rates ranged from 1.8%-100%), and no unifying variables could be identified across the studies that found high correspondence. The findings suggest that mEMA can be an accurate measurement tool, but further research should be conducted to identify procedures and variables that promote accurate responding.

Patients' beliefs towards contingency management: Target behaviours, incentives and the remote application of these interventions.

INTRODUCTION: Contingency management interventions are among the most efficacious psychosocial interventions in promoting abstinence from smoking, alcohol and substance use. The aim of this study was to assess the beliefs and objections towards contingency management among patients in UK-based drug and alcohol services to help understand barriers to uptake and support the development and implementation of these interventions. METHODS: The Service User Survey of Incentives was developed and implemented among patients (N = 181) at three UK-based drug and alcohol treatment services. Descriptive analyses were conducted to ascertain positive and negative beliefs about contingency management, acceptability of different target behaviours, incentives and delivery mechanisms including delivering incentives remotely using technology devices such as mobile telephones. RESULTS: Overall, 81% of participants were in favour of incentive programs, with more than 70% of respondents agreeing with the majority of positive belief statements. With the exception of two survey items, less than a third of participants agreed with negative belief statements. The proportion of participants indicating a neutral response was higher for negative statements (27%) indicating greater levels of ambiguity towards objections and concerns regarding contingency management. DISCUSSION AND CONCLUSIONS: Positive beliefs towards contingency management interventions were found, including high levels of acceptability towards a range of target behaviours, incentives and the use of technology devices to remotely monitor behaviour and deliver incentives. These findings have implications for the development and implementation of remote contingency management interventions within the UK drug treatment services.