Evidence map›Paper›PMID 22584372›Full record

ArticleJournal of medical Internet research2012

There's an app for that: content analysis of paid health and fitness apps.

Joshua H West, P Cougar Hall, Carl L Hanson, Michael D Barnes, Christophe Giraud-Carrier, James Barrett

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical Internet research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 113 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 6 pooled it
44.2field-weighted citation impact, top 1% of its field
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

113 citing papers in PubMed, 6 syntheses or guidelines pooled it, 337 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Trial
  8. Crush: A Randomized Trial to Evaluate the Impact of a Mobile Health App on Adolescent Sexual Health.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2023
    Trial
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Article
  14. Review
  15. Article
  16. Article
  17. Technology-Supported Behavior Change-Applying Design Thinking to mHealth Application Development.European journal of investigation in health, psychology and education · 2024
    Article
  18. Article
  19. Article
  20. Article

53 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

6 authors at 1 institution in 1 country.

Joshua H WestComputational Health Science Research Group, Department of Health Science, Brigham Young University, Provo, UT 84602, USA. josh.west@byu.edu
P Cougar Hall
Carl L Hanson
Michael D Barnes
Christophe Giraud-Carrier
James Barrett
Brigham Young University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe introduction of Apple's iPhone provided a platform for developers to design third-party apps, which greatly expanded the functionality and utility of mobile devices for public health.

objectiveThis study provides an overview of the developers' written descriptions of health and fitness apps and appraises each app's potential for influencing behavior change.

methodsData for this study came from a content analysis of health and fitness app descriptions available on iTunes during February 2011. The Health Education Curriculum Analysis Tool (HECAT) and the Precede-Proceed Model (PPM) were used as frameworks to guide the coding of 3336 paid apps.

resultsCompared to apps with a cost less than US $0.99, apps exceeding US $0.99 were more likely to be scored as intending to promote health or prevent disease (92.55%, 1925/3336 vs 83.59%, 1411/3336; P<.001), to be credible or trustworthy (91.11%, 1895/3336 vs 86.14%, 1454/3349; P<.001), and more likely to be used personally or recommended to a health care client (72.93%, 1517/2644 vs 66.77%, 1127/2644; P<.001). Apps related to healthy eating, physical activity, and personal health and wellness were more common than apps for substance abuse, mental and emotional health, violence prevention and safety, and sexual and reproductive health. Reinforcing apps were less common than predisposing and enabling apps. Only 1.86% (62/3336) of apps included all 3 factors (ie, predisposing, enabling, and reinforcing).

conclusionsDevelopment efforts could target public health behaviors for which few apps currently exist. Furthermore, practitioners should be cautious when promoting the use of apps as it appears most provide health-related information (predisposing) or make attempts at enabling behavior, with almost none including all theoretical factors recommended for behavior change.

Indexed as

Cell PhoneCosts and Cost AnalysisPhysical FitnessSoftwareHumans

Identifiers

PMID22584372
PMCPMC3799565
OpenAlexW2004006198

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.