Dataset Information

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

ABSTRACT:

Background

Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects.

Objective

The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social media features as part of their intervention infrastructure. A taxonomy of social media features is presented to inform the development, description, and evaluation of behavioral interventions.

Methods

Search terms were used in 8 databases to identify DBCIs that incorporated social media features and targeted tobacco smoking, diet and nutrition, physical activities, or alcohol consumption. The screening and review process was performed by 2 independent researchers.

Results

A total of 5264 articles were screened, and 143 articles describing a total of 134 studies were retained for full review. The majority of studies (70%) reported positive outcomes, followed by 28% finding no effects with regard to their respective objectives and hypothesis, and 2% of the studies found that their interventions had negative outcomes. Few studies reported on the association between the inclusion of social media features and intervention effect. A taxonomy of social media features used in behavioral interventions has been presented with 36 social media features organized under 7 high-level categories. The taxonomy has been used to guide the analysis of this review.

Conclusions

Although social media features are commonly included in DBCIs, there is an acute lack of information with respect to their effect on outcomes and a lack of clear guidance to inform the selection process based on the features' suitability for the different behaviors. The proposed taxonomy along with the set of recommendations included in this review will support future research aimed at isolating and reporting the effects of social media features on DBCIs, cross-study comparisons, and evaluations.

SUBMITTER: Elaheebocus SMRA

PROVIDER: S-EPMC5843796 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

Elaheebocus Sheik Mohammad Roushdat Ally SMRA Weal Mark M Morrison Leanne L Yardley Lucy L

Journal of medical Internet research 20180222 2

<h4>Background</h4>Incorporating social media features into digital behavior change interventions (DBCIs) has the potential to contribute positively to their success. However, the lack of clear design principles to describe and guide the use of these features in behavioral interventions limits cross-study comparisons of their uses and effects.<h4>Objective</h4>The aim of this study was to provide a systematic review of DBCIs targeting modifiable behavioral risk factors that have included social ...[more]

PMID: 29472174

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Project description:BACKGROUND:Social media are an increasingly commonly used platform for delivering health promotion interventions. Although recent research has focused on the effectiveness of social media interventions for health promotion, very little is known about the optimal content within such interventions, and the active ingredients to promote health behavior change using social media are not clear. Identifying which behavior change techniques (BCTs) are reported may help to clarify the content of interventions using a generalizable terminology that may facilitate future intervention development. OBJECTIVE:This study aimed to identify which BCTs are reported in social media interventions for promoting health behavior change in adults. METHODS:We included 71 studies conducted with adult participants (aged ?18 years) and for which social media intervention was considered interactive in a Cochrane review of the effectiveness of such interventions. We developed a coding manual informed by the Behavior Change Technique Taxonomy version 1 (BCTTv1) to identify BCTs in the included studies. We identified BCTs in all study arms (including control) and described BCTs in the group and self-directed components of studies. We characterized the dose of delivery for each BCT by low and high intensity. We used descriptive analyses to characterize the reported BCTs. RESULTS:Our data consisted of 71 studies published from 2001 to 2017, mainly conducted in high-income countries (n=65). Most studies (n=31) used tailored, interactive websites to deliver the intervention; Facebook was the most used mainstream platform. In developing our coding manual, we adapted some BCTTv1 instructions to better capture unique nuances of how BCTs were operationalized in social media with respect to likes, retweets, smiles, congratulations, and badges. Social support (unspecified), instruction on how to perform the behavior, and credible source were most frequently identified BCTs in intervention arms of studies and group-delivery settings, whereas instruction on how to perform the behavior was most commonly applied in self-directed components of studies, control arms, and individual participant settings. Instruction on how to perform the behavior was also the most frequently reported BCT in both intervention and control arms simultaneously. Instruction on how to perform the behavior, social support (unspecified), self-monitoring of behavior, information about health consequences, and credible source were identified in the top 5 BCTs delivered with the highest intensity. CONCLUSIONS:This study within a review provides a detailed description of the BCTs and their dose to promote behavior change in web-based, interactive social media interventions. Clarifying active ingredients in social media interventions and the intensity of their delivery may help to develop future interventions that can more clearly build upon the existing evidence.

Project description:BACKGROUND:Health authorities recommend educating diabetic patients and their families and initiating measures aimed at improving self-management, promoting a positive behavior change, and reducing the risk of complications. Social media could provide valid channel to intervene in and deliver diabetes education. However, it is not well known whether the use of these channels in such interventions can help improve the patients' outcomes. OBJECTIVE:The objective of our study was to review and describe the current existing evidence on the use of social media in interventions targeting people affected with diabetes. METHODS:A search was conducted across 4 databases (PubMed, Scopus, EMBASE, and Cochrane Library).The quality of the evidence of the included primary studies was graded according to the Grading of Recommendations Assessment, Development and Evaluation criteria, and the risk of bias of systematic reviews was assessed by drawing on AMSTAR (A MeaSurement Tool to Assess systematic Reviews) guidelines. The outcomes reported by these studies were extracted and analyzed. RESULTS:We included 20 moderate- and high-quality studies in the review: 17 primary studies and 3 systematic reviews. Of the 16 publications evaluating the effect on glycated hemoglobin (HbA1c) of the interventions using social media, 13 reported significant reductions in HbA1c values. The 5 studies that measured satisfaction with the interventions using social media found positive effects. We found mixed evidence regarding the effect of interventions using social media on health-related quality of life (2 publications found positive effects and 3 found no differences) and on diabetes knowledge or empowerment (2 studies reported improvements and 2 reported no significant changes). CONCLUSIONS:There is very little good-quality evidence on the use of social media in interventions aimed at helping people with diabetes. However, the use of these channels is mostly linked to benefits on patients' outcomes. Public health institutions, clinicians, and other stakeholders who aim at improving the knowledge of diabetic patients could consider the use of social media in their interventions.

Project description:BACKGROUND:Blended behavior change interventions combine therapeutic guidance with online care. This new way of delivering health care is supposed to stimulate patients with chronic somatic disorders in taking an active role in their disease management. However, knowledge about the effectiveness of blended behavior change interventions and how they should be composed is scattered. OBJECTIVE:This comprehensive systematic review aimed to provide an overview of characteristics and effectiveness of blended behavior change interventions for patients with chronic somatic disorders. METHODS:We searched for randomized controlled trials published from 2000 to April 2017 in PubMed, Embase, CINAHL, and Cochrane Central Register of Controlled Trials. Risk of bias was assessed using the Cochrane Collaboration tool. Study characteristics, intervention characteristics, and outcome data were extracted. Studies were sorted based on their comparison group. A best-evidence synthesis was conducted to summarize the effectiveness. RESULTS:A total of 25 out of the 29 included studies were of high quality. Most studies (n=21; 72%) compared a blended intervention with no intervention. The majority of interventions focused on changing pain behavior (n=17; 59%), and the other interventions focused on lifestyle change (n=12; 41%). In addition, 26 studies (90%) focused on one type of behavior, whereas 3 studies (10%) focused on multiple behaviors. A total of 23 studies (79%) mentioned a theory as basis for the intervention. The therapeutic guidance in most studies (n=18; 62%) was non face-to-face by using email, phone, or videoconferencing, and in the other studies (partly), it was face-to-face (n=11; 38%). In 26 studies (90%), the online care was provided via a website, and in 3 studies (10%) via an app. In 22 studies (76%), the therapeutic guidance and online care were integrated instead of two separate aspects. A total of 26 outcome measures were included in the evidence synthesis comparing blended interventions with no intervention: for the coping strategy catastrophizing, we found strong evidence for a significant effect. In addition, 1 outcome measure was included in the evidence synthesis comparing blended interventions with face-to-face interventions, but no evidence for a significant effect was found. A total of 6 outcome measures were included in the evidence synthesis comparing blended interventions with online interventions, but no evidence for a significant effect was found. CONCLUSIONS:Blended behavior change interventions for patients with chronic somatic disorders show variety in the type of therapeutic guidance, the type of online care, and how these two delivery modes are integrated. The evidence of the effectiveness of blended interventions is inconsistent and nonsignificant for most outcome measures. Future research should focus on which type of blended intervention works for whom.

Project description:BackgroundThe prevalence of chronic health conditions in childhood is increasing, and behavioral interventions can support the management of these conditions. Compared with face-to-face treatment, the use of digital interventions may be more cost-effective, appealing, and accessible, but there has been inadequate attention to their use with younger populations (children aged 5-12 years).ObjectiveThis systematic review aims to (1) identify effective digital interventions, (2) report the characteristics of promising interventions, and (3) describe the user's experience of the digital intervention.MethodsA total of 4 databases were searched (Excerpta Medica Database [EMBASE], PsycINFO, Medical Literature Analysis and Retrieval System Online [MEDLINE], and the Cochrane Library) between January 2014 and January 2019. The inclusion criteria for studies were as follows: (1) children aged between 5 and 12 years, (2) interventions for behavior change, (3) randomized controlled trials, (4) digital interventions, and (5) chronic health conditions. Two researchers independently double reviewed papers to assess eligibility, extract data, and assess quality.ResultsSearches run in the databases identified 2643 papers. We identified 17 eligible interventions. The most promising interventions (having a beneficial effect and low risk of bias) were 3 targeting overweight or obesity, using exergaming or social media, and 2 for anxiety, using web-based cognitive behavioral therapy (CBT). Characteristics of promising interventions included gaming features, therapist support, and parental involvement. Most were purely behavioral interventions (rather than CBT or third wave), typically using the behavior change techniques (BCTs) feedback and monitoring, shaping knowledge, repetition and substitution, and reward. Three papers included qualitative data on the user's experience. We developed the following themes: parental involvement, connection with a health professional is important for engagement, technological affordances and barriers, and child-centered design.ConclusionsOf the 17 eligible interventions, digital interventions for anxiety and overweight or obesity had the greatest promise. Using qualitative methods during digital intervention development and evaluation may lead to more meaningful, usable, feasible, and engaging interventions, especially for this underresearched younger population. The following characteristics could be considered when developing digital interventions for younger children: involvement of parents, gaming features, additional therapist support, behavioral (rather than cognitive) approaches, and particular BCTs (feedback and monitoring, shaping knowledge, repetition and substitution, and reward). This review suggests a model for improving the conceptualization and reporting of behavioral interventions involving children and parents.

Dataset Information

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

Background

Objective

Methods

Results

Conclusions

Publications

Peer-Based Social Media Features in Behavior Change Interventions: Systematic Review.

Similar Datasets

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