CoChat
Sign Up
Cited by 314Mobile Health and mHealth ApplicationsSocial Media in Health EducationHealth, Technology, Consumer Behavior

There’s an App for That: Content Analysis of Paid Health and Fitness Apps

Open access
West, Joshua H, Hall, P. Cougar, Hanson, Carl L, Barnes, Michael D, Giraud-Carrier, Christophe, Barrett, James·2012·Journal of Medical Internet Research
DOI 10.2196/jmir.1977PMC PMC3799565
Open this paper in CoChat — free accountOpen PDF

Abstract

BACKGROUND: The 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. OBJECTIVE: This study provides an overview of the developers' written descriptions of health and fitness apps and appraises each app's potential for influencing behavior change. METHODS: Data 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. RESULTS: Compared 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). CONCLUSIONS: Development 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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2196/jmir.1977

Cites

23 of 23 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Generally, smartphone apps are designed to deliver specific therapeutic activities, such as self-monitoring, facilitating skills acquisition, or to provide information about a particular health condition.

    “Generally, smartphone apps are designed to deliver specific therapeutic activities, such as self-monitoring, facilitating skills acquisition, or to provide information about a particular health condition. 51–53”

    From Effectiveness of mobile technologies delivering Ecological Momentary Interventions for stress and anxiety: A systematic review (2016) · cites this paper as [51]

    The Discussion describes apps that teach skills, track progress, record behavior, and provide health information; the Results also identify apps with disease-specific information. These passages support the examples, but the study concerns paid health and fitness apps, not smartphone apps generally, and does not establish that they are generally designed for therapeutic activities. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • Considerable attention has been paid to whether existing, often commercial, apps provide theory and evidence-based BCTs.

    “To date, considerable attention has been paid to whether existing, often commercial, apps provide theory and evidence-based BCTs [66-71].”

    From Understanding Usage of a Hybrid Website and Smartphone App for Weight Management: A Mixed-Methods Study (2014) · cites this paper as [67]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

1 of the 24 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

  1. [11]Fogg BJ Persuasive Technology: Using Computers to Change What We Think and Do Persuasive Technology: Using Computers to Change What We Think and Do 2002 Waltham, MA Morgan Kaufmann
  2. [26]World Health Organization 2011 2012-02-29 Obesity and overweight http://www.who.int/mediacentre/factsheets/fs311/es/index.html 23586117
  3. [30]Shuler C iLearn: A Content Analysis of the iTunes App Store's Education Section 2009 2012-05-08 New York, NY The Joan Ganz Cooney Center at Sesame Workshop http://blogs.edweek.org/edweek/DigitalEducation/iLearn_final%20formatted.pdf

Cited by

Sorted by citations

Related

Authors
West, J. H., Hall, P. C., Hanson, C. L., Barnes, M. D., Giraud-Carrier, C., & Barrett, J.
Affiliations
Brigham Young University (US)
Corresponding author
West, Joshua H
ORCID
Venue
Journal of Medical Internet Research
Publisher
JMIR Publications Inc.
Published
2012-05-14
Volume
14
Issue
3
Pages
e72
ISSN
1438-8871 (ISSN-L)
DOI
10.2196/jmir.1977
PMC
PMC3799565
OpenAlex
W2004006198
Cited by
314
References
24
Citations by year
2026: 1 · 2025: 5 · 2024: 11 · 2023: 13 · 2022: 15 · 2021: 25 · 2020: 24 · 2019: 27 · 2018: 48 · 2017: 36 · 2016: 36 · 2015: 36 · 2014: 19 · 2013: 17 · 2012: 1
FWCI
41.47
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Journal of Medical Internet Research (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Brigham Young University
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Social Sciences › Health › Social Media in Health Education
  • Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords
health and fitness apps, mobile health, app pricing, behavior change, PRECEDE-PROCEED model, public health promotion, healthy eating, physical activity, substance abuse, mental health, sexual and reproductive health, violence prevention
MeSH terms
Costs and Cost Analysis, Humans, Physical Fitness, Software, Cell Phone

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review