Evidence map›Paper›PMID 30578201›Full record

ArticleJournal of medical Internet research2018

Using a Mobile Social Networking App to Promote Physical Activity: A Qualitative Study of Users' Perspectives.

Huong Ly Tong, Enrico Coiera, Liliana Laranjo

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 pooled it
14.1field-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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 72 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Using photovoice to explore young women's experiences of behaviour change techniques in physical activity mobile apps.The international journal of behavioral nutrition and physical activity · 2023
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  5. Mobile apps for cancer patient education: a technology foresight analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026
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  14. What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022
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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

3 authors at 1 institution in 1 country.

Huong Ly TongCentre for Health Informatics, Australian Institute of Health Innovation, Sydney, Australia.ORCID 0000-0002-8462-0105
Enrico CoieraCentre for Health Informatics, Australian Institute of Health Innovation, Sydney, Australia.ORCID 0000-0002-6444-6584
Liliana LaranjoCentre for Health Informatics, Australian Institute of Health Innovation, Sydney, Australia.ORCID 0000-0003-1020-3402
Australian Institute of Health and Welfare · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite many health benefits of physical activity, nearly a third of the world's adult population is insufficiently active. Technological interventions, such as mobile apps, wearable trackers, and Web-based social networks, offer great promise in promoting physical activity, but little is known about users' acceptability and long-term engagement with these interventions.

objectiveThe aim of this study was to understand users' perspectives regarding a mobile social networking intervention to promote physical activity.

methodsParticipants, mostly university students and staff, were recruited using purposive sampling techniques. Participants were enrolled in a 6-month feasibility study where they were provided with a wearable physical activity tracker (Fitbit Flex 2) and a wireless scale (Fitbit Aria) integrated with a social networking mobile app (named "fit.healthy.me"). We conducted semistructured, in-depth qualitative interviews and focus groups pre- and postintervention, which were recorded and transcribed verbatim. The data were analyzed in Nvivo 11 using thematic analysis techniques.

resultsIn this study, 55 participants were enrolled; 51% (28/55) were females, and the mean age was 23.6 (SD 4.6) years. The following 3 types of factors emerged from the data as influencing engagement with the intervention and physical activity: individual (self-monitoring of behavior, goal setting, and feedback on behavior), social (social comparison, similarity and familiarity between users, and participation from other users in the network), and technological. In addition, automation and personalization were observed as enhancing the delivery of both individual and social aspects. Technological limitations were mentioned as potential barriers to long-term usage.

conclusionsSelf-regulatory techniques and social factors are important to consider when designing a physical activity intervention, but a one-size-fits-all approach is unlikely to satisfy different users' preferences. Future research should adopt innovative research designs to test interventions that can adapt and respond to users' needs and preferences throughout time.

Indexed as

Social NetworkingAdultExerciseFemaleFitness TrackersHumansMaleMobile ApplicationsQualitative ResearchYoung Adultexercisefitness trackersmobile appsmobile phonesocial networking

Identifiers

PMID30578201
PMCPMC6320410
OpenAlexW2905879257

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.