Evidence map›Paper›PMID 29599105›Full record

ArticleJMIR mHealth and uHealth2018

Participants' Perceptions on the Use of Wearable Devices to Reduce Sitting Time: Qualitative Analysis.

Michelle Takemoto, Brittany Lewars, Samantha Hurst, Katie Crist, Camille Nebeker, Hala Madanat, Jeanne Nichols, Dori E Rosenberg, Jacqueline Kerr

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 16 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
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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

9 authors at 3 institutions in 1 country.

Michelle TakemotoDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0002-6061-3226
Brittany LewarsDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0003-2804-725X
Samantha HurstDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0001-9843-2845
Katie CristDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0002-7549-8523
Camille NebekerDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0001-6819-1796
Hala MadanatGraduate School of Public Health, San Diego State University, San Diego, CA, United States.ORCID http://orcid.org/0000-0002-2547-2202
Jeanne NicholsDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0003-4612-1302
Dori E RosenbergKaiser Permanente Washington Health Research Institute, Seattle, WA, United States.ORCID http://orcid.org/0000-0003-1017-8833
Jacqueline KerrDepartment of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States.ORCID http://orcid.org/0000-0003-2341-8138
University of California San Diego · USKaiser Permanente Washington Health Research Institute · USSan Diego State University · US

Funding

Investigating Sedentary Time In Aging: New Directions Using Technology (iSTAND)K23HL119352 · NHLBI · KAISER FOUNDATION HEALTH PLAN OF WASHINGTON · PI ROSENBERG, DORI E · 2014 to 2017
$564k
NHLBI NIH HHS K23 HL119352
6 · The paper itself

Abstract

backgroundRecent epidemiological evidence indicates that, on average, people are sedentary for approximately 7.7 hours per day. There are deleterious effects of prolonged sedentary behavior that are separate from participation in physical activity and include increased risk of weight gain, cancer, metabolic syndrome, diabetes, and heart disease. Previous trials have used wearable devices to increase physical activity in studies; however, additional research is needed to fully understand how this technology can be used to reduce sitting time.

objectiveThe purpose of this study was to explore the potential of wearable devices as an intervention tool in a larger sedentary behavior study through a general inductive and deductive analysis of focus group discussions.

methodsWe conducted four focus groups with 15 participants to discuss 7 different wearable devices with sedentary behavior capabilities. Participants recruited for the focus groups had previously participated in a pilot intervention targeting sedentary behavior over a 3-week period and were knowledgeable about the challenges of reducing sitting time. During the focus groups, participants commented on the wearability, functionality, and feedback mechanism of each device and then identified their two favorite and two least favorite devices. Finally, participants designed and described their ideal or dream wearable device. Two researchers, who have expertise analyzing qualitative data, coded and analyzed the data from the focus groups. A thematic analysis approach using Dedoose software (SocioCultural Research Consultants, LLC version 7.5.9) guided the organization of themes that reflected participants' perspectives.

resultsAnalysis resulted in 14 codes that we grouped into themes. Three themes emerged from our data: (1) features of the device, (2) data the device collected, and (3) how data are displayed.

conclusionsCurrent wearable devices for increasing physical activity are insufficient to intervene on sitting time. This was especially evident when participants voted, as several participants reported using a "process of elimination" as opposed to choosing favorites because none of the devices were ideal for reducing sitting time. To overcome the limitations in current devices, future wearable devices designed to reduce sitting time should include the following features: waterproof, long battery life, accuracy in measuring sitting time, real time feedback on progress toward sitting reduction goals, and flexible options for prompts to take breaks from sitting.

Indexed as

focus groupsqualitative researchtechnologywearable devices

Identifiers

PMID29599105
PMCPMC5897621
OpenAlexW2794715525

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.