Dataset Information

Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression.

ABSTRACT:

Background

Digital behavior change interventions (DBCIs) appear to reduce alcohol consumption, but greater understanding is needed of their mechanisms of action.

Purpose

To describe the behavior change techniques (BCTs) used in DBCIs and examine whether individual BCTs, the inclusion of more BCTs or more Control Theory congruent BCTs is associated with increased effectiveness.

Methods

Forty-one randomized control trials were extracted from a Cochrane review of alcohol reduction DBCIs and coded for up to 93 BCTs using an established and reliable method. Random effects unadjusted and adjusted meta-regression models were performed to assess associations between BCTs and intervention effectiveness.

Results

Interventions used a mean of 9.1 BCTs (range 1-22), 23 different BCTs were used in four or more trials. Trials that used "Behavior substitution" (-95.112 grams per week [gpw], 95% CI: -162.90, -27.34), "Problem solving" (-45.92 gpw, 95% CI: -90.97, -0.87) and "Credible source" (-32.09 gpw, 95% CI: -60.64, -3.55) were significantly associated with greater alcohol reduction than trials without these BCTs. The "Behavior substitution" result should be treated as preliminary because it was reported in only four trials, three of which were conducted by the same research group. "Feedback" was used in 98% of trials (n = 41); other Control Theory congruent BCTs were used less frequently: for example, "Goal setting" 43% (n = 18) and "Self-monitoring" 29%, (n = 12).

Conclusions

"Behavior substitution," "Problem solving," and "Credible source" were associated with greater alcohol reduction. Many BCTs were used infrequently in DBCIs, including BCTs with evidence of effectiveness in other domains, such as "Self-monitoring" and "Goal setting."

SUBMITTER: Garnett CV

PROVIDER: S-EPMC6361280 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Publications

Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression.

Garnett Claire V CV Crane David D Brown Jamie J Kaner Eileen F S EFS Beyer Fiona R FR Muirhead Colin R CR Hickman Matthew M Beard Emma E Redmore James J de Vocht Frank F Michie Susan S

Annals of behavioral medicine : a publication of the Society of Behavioral Medicine 20180501 6

<h4>Background</h4>Digital behavior change interventions (DBCIs) appear to reduce alcohol consumption, but greater understanding is needed of their mechanisms of action.<h4>Purpose</h4>To describe the behavior change techniques (BCTs) used in DBCIs and examine whether individual BCTs, the inclusion of more BCTs or more Control Theory congruent BCTs is associated with increased effectiveness.<h4>Methods</h4>Forty-one randomized control trials were extracted from a Cochrane review of alcohol reduc ...[more]

PMID: 29788261

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Project description:BackgroundWeb-based interventions are thought to overcome barriers to treatment, such as accessibility and geographical location, which can undermine the effectiveness of traditional face-to-face interventions. Owing to these features, researchers are increasingly testing the efficacy of web-based interventions as ways to reduce alcohol misuse, binge eating, and gambling. However, many web-based interventions have poorly defined mechanisms of action; therefore, it is often uncertain how they propose to bring about behavior change.ObjectiveThis systematic review aims to identify effective behavior change techniques (BCTs) present in web-based interventions aimed at reducing alcohol consumption, binge eating, or gambling.MethodsThis systematic review covered research conducted in the last 20 years. Inclusion criteria for interventions were web-based administration; targeting alcohol use, binge eating, and/or gambling; and reporting on baseline and postintervention measures of behavior. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines were followed. We coded intervention effectiveness, study quality, and BCTs present in the interventions.ResultsFollowing removal of 4152 ineligible articles, 45 were included in the review: 32 (71%) targeted alcohol misuse, 6 (13%) targeted binge eating, and 7 (16%) targeted gambling. In total, 5 frequency counts were performed to identify the most commonly used BCTs: all studies, effective interventions, high-quality studies at 2 thresholds, and both high quality and effective studies. The results obtained from this were integrated to identify 7 BCTs. These 7 BCTs were problem solving, feedback on behavior, self-monitoring of behavior, self-monitoring of outcomes, instruction on how to perform a behavior, information about social and health consequences, and social comparison. A total of 4 BCTs were found in all frequency counts: feedback on behavior, self-monitoring of behavior, instruction on how to perform a behavior, and social comparison. Self-monitoring of outcomes of behavior was found in 3 of the 5 frequency counts, problem solving was found in 2 frequency counts, and information about social and health consequences was found in 1 frequency count.ConclusionsThis systematic review identified 7 of the most frequently used BCTs used in web-based interventions focused on alcohol misuse, binge eating, and gambling. These results can inform the development of evidence-based eHealth interventions that have the potential to lead to effective, positive behavior changes in all 3 areas.

Project description:BackgroundInterventions delivered by smartphone apps have the potential to help drinkers reduce their consumption of alcohol. To optimize engagement and reduce the high rates of attrition associated with the use of digital interventions, it is necessary to ensure that an app's design and functionality is appropriate for its intended purposes and target population.AimsTo understand the usability of an app to help people reduce their alcohol consumption.MethodThe app, Drink Less, contains a core module focusing on goal setting, supplemented by five additional modules: self-monitoring and feedback, identity change, cognitive bias re-training, action planning, and social comparison. Two studies were conducted, a "think aloud" study performed with people using the app for the first time and a semistructured interview study performed after users had had access to the app for at least 2 weeks. A thematic analysis of the "think aloud" and interview transcripts was conducted by one coder and verified by a second.ResultsTwenty-four participants, half of whom were women and half from disadvantaged groups, took part in the two studies. Three main themes identified in the data were "Feeling lost and unsure of what to do next," "Make the app easy to use," and "Make the app beneficial and rewarding to use." These themes reflected participants' need for (i) guidance, particularly when first using the app or when entering data; (ii) the data entry process to be simple and the navigation intuitive; (iii) neither the amount of text nor range of options to be overwhelming; (iv) the app to reward them for effort and progress; and (v) it to be clear how the app could help alcohol reduction goals be reached.ConclusionFirst-time and experienced users want an alcohol reduction app to be easy, rewarding, and beneficial to use. An easy-to-use app would reduce user burden, offer ongoing help, and be esthetically pleasing. A rewarding and beneficial app would provide positive reinforcement, give feedback about progress, and demonstrate credibility. Users need help when first using the app, and they need a compelling reason to continue using it.

Project description:Behavior change interventions typically contain multiple potentially active components: behavior change techniques (BCTs). Identifying which specific BCTs or BCT combinations have the potential to be effective for a given behavior in a given context presents a major challenge. The aim of this study was to review the methods that have been used to identify effective BCTs for given behaviors in given contexts and evaluate their strengths and limitations. A scoping review was conducted of studies that had sought to identify effective BCTs. Articles referring to "behavio(u)r change technique(s)" in the abstract/text were located, and ones that involved identification of effective BCTs were selected. The methods reported were coded. The methods were analyzed in general terms using "PASS" criteria: Practicability (facility to apply the method appropriately), Applicability (facility to generalize from findings to contexts and populations of interest), Sensitivity (facility to identify effective BCTs), and Specificity (facility to rule out ineffective BCTs). A sample of 10% of the studies reviewed was then evaluated using these criteria to assess how far the strengths and limitations identified in principle were borne out in practice. One hundred and thirty-five studies were identified. The methods used in those studies were experimental manipulation of BCTs, observational studies comparing outcomes in the presence or absence of BCTs, meta-analyses of BCT comparisons, meta-regressions evaluating effect sizes with and without specific BCTs, reviews of BCTs found in effective interventions, and meta-classification and regression trees. The limitations of each method meant that only weak conclusions could be drawn regarding the effectiveness of specific BCTs or BCT combinations. Methods for identifying effective BCTs linked to target behavior and context all have important inherent limitations. A strategy needs to be developed that can systematically combine the strengths of the different methods and that can link these constructs in an ontology of behavior change interventions.

Dataset Information

Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression.

Background

Purpose

Methods

Results

Conclusions

Publications

Behavior Change Techniques Used in Digital Behavior Change Interventions to Reduce Excessive Alcohol Consumption: A Meta-regression.

Similar Datasets

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