Evidence map›Paper›PMID 28293619›Full record

ArticlemHealth2017

The fitness of apps: a theory-based examination of mobile fitness app usage over 5 months.

Lynn Katherine Herrmann, Jinsook Kim

Abstract read
In one paragraph

Article in mHealth, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. A Sensor-Controlled Digital Game for Heart Failure Self-Care Based on Behavioral Change Frameworks.SeGAH ... IEEE ... International Conference on Serious Games and Applications for Health : book of proceedings. IEEE International Conference on Serious Games and Applications for Health · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Acceptance of Technologies for Aging in Place: A Conceptual Model.Journal of medical Internet research · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. The evidence gap.Nature biotechnology · 2018
    Article
  20. Article
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

2 authors.

Lynn Katherine HerrmannSchool of Health Studies, Northern Illinois University, DeKalb, IL, USA.
Jinsook KimSchool of Health Studies, Northern Illinois University, DeKalb, IL, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are thousands of fitness-related smartphone applications ("apps") available for free and purchase, but there is uncertainty if these apps help individuals achieve and maintain personal fitness. Technology usage attrition is also a concern among research studies on health technologies.

methodsUsage of three fitness apps was examined over 5 months to assess adherence and effectiveness. Initially, 64 participants downloaded three free apps available on Android and iOS and 47 remained in the study until posttest. With a one group pre-posttest design and checkpoints at months 1, 3, and 5, exercise and exercise with fitness apps were examined in the framework of the Theory of Planned Behavior (TPB) using a validated survey. Apps were selected based on their function from the Functional Triad. Perceived fitness was also measured.

resultsForty-seven participants completed both pre and posttests. Individual item scores indicated no significant change pre to posttest except for decreases observed in usefulness of using apps for exercise (attitude) (-0.78, P<0.01), peer influence on exercise (subjective norm) (-0.51, P<0.05), peer influence on exercise with apps (subjective norm) (-1.02, P<0.01), perceived difficulties in exercising with apps (perceived behavioral control) (-1.29, P<0.001), and the expected frequency of exercise with apps over the next 2 weeks (behavioral intention) (P<0.0001 in a sign test). Subscale total scores indicated significant decreases in subjective norm regarding exercise (-0.72, P<0.05), subjective norm regarding exercise with apps (-1.72, P<0.01), and perceived behavioral control over exercising with apps (-2.56, P<0.01) between pre and posttest. When comparing app users (n=32) to non-users (n=15), there was only a significant difference in subscale total scores at posttest for attitude toward exercising using apps, which was significantly more favorable among users than non-users (32.3

conclusionsApp usage and effectiveness appears to have a connection to usefulness (attitude) and to perceived difficulties of exercising using apps (perceived behavioral control). Exercise and exercise using apps are not influenced by peer influence (subjective norm). Intention to exercise using these particular apps decreased (behavioral intention). Those who utilized the apps were more likely to have a positive attitude about the apps. Usefulness and perceived difficulties in particular should be considered with future app development. App usefulness and ease of use may be facilitated by using health behavior theories to guide development.

Indexed as

behaviormobile appsPhysical fitnesstechnologytheory

Identifiers

PMID28293619
PMCPMC5344171

What OpenQuestion holds

Textmetadata
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.