Evidence map›Paper›PMID 31984346›Full record

ArticleJAMIA open2019

Beyond novelty effect: a mixed-methods exploration into the motivation for long-term activity tracker use.

Grace Shin, Yuanyuan Feng, Mohammad Hossein Jarrahi, Nicci Gafinowitz

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

Article in JAMIA open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
18.4field-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

56 citing papers in PubMed, 3 syntheses or guidelines pooled it, 143 citations in OpenAlex.

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  12. Self-efficacy and Physical Activity in Overweight and Obese Adults Participating in a Worksite Weight Loss Intervention: Multistate Modeling of Wearable Device Data.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
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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

4 authors at 2 institutions in 1 country.

Grace ShinSchool of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Yuanyuan FengInstitute for Software Research School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
Mohammad Hossein JarrahiSchool of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Nicci GafinowitzSchool of Information and Library Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
University of North Carolina at Chapel Hill · USCarnegie Mellon University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesActivity trackers hold the promise to support people in managing their health through quantified measurements about their daily physical activities. Monitoring personal health with quantified activity tracker-generated data provides patients with an opportunity to self-manage their health. Many have been conducted within short-time frames; makes it difficult to discover the impact of the activity tracker's novelty effect or the reasons for the device's long-term use. This study explores the impact of novelty effect on activity tracker adoption and the motivation for sustained use beyond the novelty period. MATERIALS AND

methodsThis study uses a mixed-methods approach that combines both quantitative activity tracker log analysis and qualitative one-on-one interviews to develop a deeper behavioral understanding of 23 Fitbit device users who used their trackers for at least 2 months (range of use = 69-1073 days).

resultsLog data from users' Fitbit devices revealed 2 stages: the novelty period and the long-term use period. The novelty period for Fitbit users in this study was approximately 3 months, during which they might have discontinued using their devices. DISCUSSION: The qualitative interview data identified various factors that users to continuously use the Fitbit devices in different stages. The discussion of these results provides design implications to guide future development of activity tracking technology.

conclusionThis study reveals important dynamics emerging over long-term activity tracker use, contributes new knowledge to consumer health informatics and human-computer interaction, and offers design implications to guide future development of similar health-monitoring technologies that better account for long-term use in support of patient care and health self-management.

Indexed as

activity trackerconsumer health informaticsmotivationpatient generated health data

Identifiers

PMID31984346
PMCPMC6952057
OpenAlexW2903195636

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.