Evidence map›Paper›PMID 25131661›Full record

ReviewJournal of medical Internet research2014

Behavior change techniques implemented in electronic lifestyle activity monitors: a systematic content analysis.

Elizabeth J Lyons, Zakkoyya H Lewis, Brian G Mayrsohn, Jennifer L Rowland

Abstract readReview
In one paragraph

Review in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 260 papers, 23 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
260citing papers in PubMed, 23 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

260 citing papers in PubMed, 23 syntheses or guidelines pooled it.

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  3. Effects of physical activity-promoting wearable devices on blood pressure in adults: a systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2025
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  4. Interventions on Barriers to the Participation of Adolescents in Physical Activity: A Systematic Review.International journal of environmental research and public health · 2025
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200 more citing papers are in PubMed but not listed here.

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.

Elizabeth J LyonsThe University of Texas Medical Branch, Institute for Translational Sciences, Galveston, TX, United States. ellyons@utmb.edu.ORCID http://orcid.org/0000-0003-1695-2236

Funding

UTMB OAIC Research Education Component (REC)P30AG024832 · NIA · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI JAMES S. GOODWIN, MD, MELISSA M. MORROW · 2005 to 2026
$26.7M
UTMB Clinical and Translational Science AwardUL1TR000071 · NCATS · UNIVERSITY OF TEXAS MED BR GALVESTON · PI BRASIER, ALLAN R. · 2012 to 2014
$14.4M
UTMB WOMEN'S HEALTH RESEARCH SCHOLARS PROGRAMK12HD052023 · NICHD · UNIVERSITY OF TEXAS MEDICAL BR GALVESTON · PI BERENSON, ABBEY B · 2005 to 2023
$8.1M
Patient Centered Outcomes Research in the ElderlyR24HS022134 · AHRQ · UNIVERSITY OF TEXAS MED BR GALVESTON · PI GOODWIN, MD, JAMES S. · 2013 to 2017
$4.8M
AHRQ HHS R24 HS022134AHRQ HHS R24HS22134NCATS NIH HHS UL1 TR000071NCATS NIH HHS UL1TR000071NIA NIH HHS P30 AG024832NIA NIH HHS P30AG024832NICHD NIH HHS K12 HD052023NICHD NIH HHS K12HD052023
6 · The paper itself

Abstract

backgroundElectronic activity monitors (such as those manufactured by Fitbit, Jawbone, and Nike) improve on standard pedometers by providing automated feedback and interactive behavior change tools via mobile device or personal computer. These monitors are commercially popular and show promise for use in public health interventions. However, little is known about the content of their feedback applications and how individual monitors may differ from one another.

objectiveThe purpose of this study was to describe the behavior change techniques implemented in commercially available electronic activity monitors.

methodsElectronic activity monitors (N=13) were systematically identified and tested by 3 trained coders for at least 1 week each. All monitors measured lifestyle physical activity and provided feedback via an app (computer or mobile). Coding was based on a hierarchical list of 93 behavior change techniques. Further coding of potentially effective techniques and adherence to theory-based recommendations were based on findings from meta-analyses and meta-regressions in the research literature.

resultsAll monitors provided tools for self-monitoring, feedback, and environmental change by definition. The next most prevalent techniques (13 out of 13 monitors) were goal-setting and emphasizing discrepancy between current and goal behavior. Review of behavioral goals, social support, social comparison, prompts/cues, rewards, and a focus on past success were found in more than half of the systems. The monitors included a range of 5-10 of 14 total techniques identified from the research literature as potentially effective. Most of the monitors included goal-setting, self-monitoring, and feedback content that closely matched recommendations from social cognitive theory.

conclusionsElectronic activity monitors contain a wide range of behavior change techniques typically used in clinical behavioral interventions. Thus, the monitors may represent a medium by which these interventions could be translated for widespread use. This technology has broad applications for use in clinical, public health, and rehabilitation settings.

Indexed as

ExerciseHealth BehaviorActigraphyBehavior TherapyHumansLife StyleMonitoring, AmbulatorySocial SupportTelemedicinebehavior change techniqueelectronic activity monitormhealthmobilephysical activity

Identifiers

PMID25131661
PMCPMC4147713

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.