Evidence map›Paper›PMID 34673528›Full record

ArticleJournal of medical Internet research2021

Willingness to Share Wearable Device Data for Research Among Mechanical Turk Workers: Web-Based Survey Study.

Casey Overby Taylor, Natalie Flaks-Manov, Shankar Ramesh, Eun Kyoung Choe

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

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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.

Casey Overby TaylorDepartments of Medicine and Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States.ORCID 0000-0001-9302-5968
Natalie Flaks-ManovInstitute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States.ORCID 0000-0002-9163-6295
Shankar RameshCollege of Information Studies, University of Maryland, College Park, MD, United States.ORCID 0000-0003-4869-266X
Eun Kyoung ChoeCollege of Information Studies, University of Maryland, College Park, MD, United States.ORCID 0000-0001-5038-8320

Funding

Clinical Decision Support for Unsolicited Genomic ResultsR35HG010714 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI TAYLOR, CASEY OVERBY · 2020 to 2024
$2.8M
NHGRI NIH HHS R35 HG010714
6 · The paper itself

Abstract

backgroundWearable devices that are used for observational research and clinical trials hold promise for collecting data from study participants in a convenient, scalable way that is more likely to reach a broad and diverse population than traditional research approaches. Amazon Mechanical Turk (MTurk) is a potential resource that researchers can use to recruit individuals into studies that use data from wearable devices.

objectiveThis study aimed to explore the characteristics of wearable device users on MTurk that are associated with a willingness to share wearable device data for research. We also aimed to determine whether compensation was a factor that influenced the willingness to share such data.

methodsThis was a secondary analysis of a cross-sectional survey study of MTurk workers who use wearable devices for health monitoring. A 19-question web-based survey was administered from March 1 to April 5, 2018, to participants aged ≥18 years by using the MTurk platform. In order to identify characteristics that were associated with a willingness to share wearable device data, we performed logistic regression and decision tree analyses.

resultsA total of 935 MTurk workers who use wearable devices completed the survey. The majority of respondents indicated a willingness to share their wearable device data (615/935, 65.8%), and the majority of these respondents were willing to share their data if they received compensation (518/615, 84.2%). The findings from our logistic regression analyses indicated that Indian nationality (odds ratio [OR] 2.74, 95% CI 1.48-4.01, P=.007), higher annual income (OR 2.46, 95% CI 1.26-3.67, P=.02), over 6 months of using a wearable device (OR 1.75, 95% CI 1.21-2.29, P=.006), and the use of heartbeat and pulse tracking monitoring devices (OR 1.60, 95% CI 0.14-2.07, P=.01) are significant parameters that influence the willingness to share data. The only factor associated with a willingness to share data if compensation is provided was Indian nationality (OR 0.47, 95% CI 0.24-0.9, P=.02). The findings from our decision tree analyses indicated that the three leading parameters associated with a willingness to share data were the duration of wearable device use, nationality, and income.

conclusionsMost wearable device users indicated a willingness to share their data for research use (with or without compensation; 615/935, 65.8%). The probability of having a willingness to share these data was higher among individuals who had used a wearable for more than 6 months, were of Indian nationality, or were of American (United States of America) nationality and had an annual income of more than US $20,000. Individuals of Indian nationality who were willing to share their data expected compensation significantly less often than individuals of American nationality (P=.02).

Indexed as

CrowdsourcingWearable Electronic DevicesAdolescentAdultCross-Sectional StudiesHumansInternetSurveys and QuestionnairesUnited Statescrowdsourcingpersonal dataresearch participationwearables

Identifiers

PMID34673528
PMCPMC8569545

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LicenceCC BY
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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.