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Peer-based social media features in behavior change interventions: Systematic review

Peer-based social media features in behavior change interventions: Systematic review
Peer-based social media features in behavior change interventions: Systematic review
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.
systematic review, social media, behavior control, health behavior, behavioral medicine, eHealth
1438-8871
Elaheebocus, Sheik Mohammad Roushdat Ally
ae59cca2-1b28-4865-9684-3415e71282b7
Weal, Mark
e8fd30a6-c060-41c5-b388-ca52c81032a4
Morrison, Leanne
920a4eda-0f9d-4bd9-842d-6873b1afafef
Yardley, Lucy
64be42c4-511d-484d-abaa-f8813452a22e
Elaheebocus, Sheik Mohammad Roushdat Ally
ae59cca2-1b28-4865-9684-3415e71282b7
Weal, Mark
e8fd30a6-c060-41c5-b388-ca52c81032a4
Morrison, Leanne
920a4eda-0f9d-4bd9-842d-6873b1afafef
Yardley, Lucy
64be42c4-511d-484d-abaa-f8813452a22e

Elaheebocus, Sheik Mohammad Roushdat Ally, Weal, Mark, Morrison, Leanne and Yardley, Lucy (2018) Peer-based social media features in behavior change interventions: Systematic review. Journal of Medical Internet Research, 20 (2). (doi:10.2196/jmir.8342).

Record type: Article

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.

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Accepted/In Press date: 19 November 2017
e-pub ahead of print date: 22 February 2018
Keywords: systematic review, social media, behavior control, health behavior, behavioral medicine, eHealth

Identifiers

Local EPrints ID: 418531
URI: https://eprints.soton.ac.uk/id/eprint/418531
ISSN: 1438-8871
PURE UUID: a3309e70-df59-423c-8fb4-cbf670e467b9
ORCID for Mark Weal: ORCID iD orcid.org/0000-0001-6251-8786
ORCID for Leanne Morrison: ORCID iD orcid.org/0000-0002-9961-551X

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Date deposited: 09 Mar 2018 17:31
Last modified: 06 Jun 2018 13:08

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Contributors

Author: Sheik Mohammad Roushdat Ally Elaheebocus
Author: Mark Weal ORCID iD
Author: Leanne Morrison ORCID iD
Author: Lucy Yardley

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