Evidence map›Paper›PMID 29141607›Full record

ArticleBMC public health2017

Users' experiences of wearable activity trackers: a cross-sectional study.

Carol Maher, Jillian Ryan, Christina Ambrosi, Sarah Edney

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 4 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

75 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Inequalities in Exclusively Mobile Interventions Targeting Weight-Related Behaviors: Systematic Review of Observational Studies.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026
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  6. Smart wearable devices as a psychological intervention for healthy lifestyle and quality of life: a randomized controlled trial.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021
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15 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.

Carol MaherAlliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences & Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia. carol.maher@unisa.edu.au.
Jillian RyanAlliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences & Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
Christina AmbrosiAlliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences & Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia.
Sarah EdneyAlliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences & Sansom Institute for Health Research, University of South Australia, GPO Box 2471, Adelaide, South Australia, 5001, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWearable activity trackers offer considerable promise for helping users to adopt healthier lifestyles. This study aimed to explore users' experience of activity trackers, including usage patterns, sharing of data to social media, perceived behaviour change (physical activity, diet and sleep), and technical issues/barriers to use.

methodsA cross-sectional online survey was developed and administered to Australian adults who were current or former activity tracker users. Results were analysed descriptively, with differences between current and former users and wearable brands explored using independent samples t-tests, Mann-Whitney, and chi square tests.

resultsParticipants included 200 current and 37 former activity tracker users (total N = 237) with a mean age of 33.1 years (SD 12.4, range 18-74 years). Fitbit (67.5%) and Garmin devices (16.5%) were most commonly reported. Participants typically used their trackers for sustained periods (5-7 months) and most intended to continue usage. Participants reported they had improved their physical activity (51-81%) more commonly than they had their diet (14-40%) or sleep (11-24%), and slightly more participants reported to value the real time feedback (89%) compared to the long-term monitoring (78%). Most users (70%) reported they had experienced functionality issues with their devices, most commonly related to battery life and technical difficulties.

conclusionsResults suggest users find activity trackers appealing and useful tools for increasing perceived physical activity levels over a sustained period.

Indexed as

Health BehaviorAdolescentAdultAgedAustraliaCross-Sectional StudiesDietExerciseFemaleFitness TrackersHumansMaleMiddle AgedSleepSocial MediaSurveys and QuestionnairesFitnessHealth behaviourMeasurementMotion sensorsPedometryPhysical activity assessment

Identifiers

PMID29141607
PMCPMC5688726

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.