Evidence map›Paper›PMID 32217499›Full record

ArticleJournal of medical Internet research2020

Social Comparison Features in Physical Activity Promotion Apps: Scoping Meta-Review.

Danielle Arigo, Megan M Brown, Kristen Pasko, Jerry Suls

Abstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Danielle ArigoDepartment of Psychology, Rowan University, Glassboro, NJ, United States.ORCID 0000-0002-7807-5913
Megan M BrownDepartment of Psychology, Rowan University, Glassboro, NJ, United States.ORCID 0000-0001-6451-106X
Kristen PaskoDepartment of Psychology, Rowan University, Glassboro, NJ, United States.ORCID 0000-0002-9467-3059
Jerry SulsCenter for Personalized Health, Feinstein Institute for Medical Research, New York, NY, United States.ORCID 0000-0002-8436-7488

Funding

Identifying and Targeting Unique Physical Activity Determinants for Midlife WomenK23HL136657 · NHLBI · UNIVERSITY OF SCRANTON · PI ARIGO, DANIELLE · 2018 to 2022
$762k
NHLBI NIH HHS K23 HL136657
6 · The paper itself

Abstract

backgroundSmartphone apps promoting physical activity (PA) are abundant, but few produce substantial and sustained behavior change. Although many PA apps purport to induce users to compare themselves with others (by invoking social comparison processes), improvements in PA and other health behaviors are inconsistent. Existing literature suggests that social comparison may motivate PA for some people under some circumstances. However, 2 aspects of work that apply social comparison theory to PA apps remain unclear: (1) how comparison processes have been operationalized or harnessed in existing PA apps and (2) whether incorporating sources of variability in response to comparison have been used to tailor comparison features of apps, which could improve their effectiveness for promoting PA.

objectiveThe aim of this meta-review was to summarize existing systematic, quantitative, and narrative reviews of behavior change techniques in PA apps, with an emphasis on social comparison features, to examine how social comparison is operationalized and implemented.

methodsWe searched PubMed, Web of Science, and PsycINFO for reviews of PA smartphone apps. Of the 3743 initial articles returned, 26 reviews met the inclusion criteria. Two independent raters extracted the data from these reviews, including the definition of social comparison used to categorize app features, the percentage of apps categorized as inducing comparison, specific features intended to induce comparison, and any mention of tailoring comparison features. For reference, these data were also extracted for related processes (such as behavioral modeling, norm referencing, and social networking).

resultsOf the included review articles, 31% (8/26) categorized app features as prompting social comparison. The majority of these employed Abraham and Michie's earliest definition of comparison, which differs from versions in later iterations of the same taxonomy. Very few reviews specified what dimension users were expected to compare (eg, steps, physical fitness) or which features of the apps were used to induce comparison (eg, leaderboards, message boards). No review referenced tailoring of comparison features. In contrast, 54% (14/26) reviews categorized features for prompting behavioral modeling and 31% (8/26) referenced tailoring app features for users' personal goals or preferences.

conclusionsThe heterogeneity across reviews of PA apps and the absence of relevant information (eg, about dimensions or features relevant for comparison) create confusion about how to best harness social comparison to increase PA and its effectiveness in future research. No evidence was found that important findings from the broader social comparison literature (eg, that people have differing preferences for and responses to social comparison information) have been incorporated in the design of existing PA apps. Greater integration of the mobile health (mHealth) and social comparison literatures may improve the effectiveness of PA apps, thereby increasing the public health impact of these mHealth tools. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-https://osf.io/nh4td/.

Indexed as

ExerciseHealth BehaviorHumansMobile ApplicationsReview Literature as Topicbehavior change techniquemHealthphysical activitysmartphone appsocial comparison

Identifiers

PMID32217499
PMCPMC7148546

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.