Evidence map›Paper›PMID 35547191›Full record

ArticleFrontiers in big data2022

Ethical Views on Sharing Digital Data for Public Health Surveillance: Analysis of Survey Data Among Patients.

Renee Garett, Sean D Young

Open access · goldAbstract read
In one paragraph

Article in Frontiers in big data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 11% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
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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

2 authors at 1 institution in 1 country.

Renee GarettElevateU, Irvine, CA, United States.
Sean D YoungDepartment of Emergency Medicine, University of California, Irvine, Irvine, CA, United States.
University of California, Irvine · US

Funding

Adapting the HOPE Online Support Intervention to Increase MAT Uptake Among OUD PatientsR33AT010606 · NCCIH · UNIVERSITY OF CALIFORNIA-IRVINE · PI YOUNG, SEAN · 2020 to 2021
$3.5M
Mining real-time social media big data to monitor HIV: Development and Ethical IssuesR01AI132030 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YOUNG, SEAN · 2017 to 2020
$3.4M
HOPE Social Media Intervention for HIV Testing and Studying Social NetworksR01MH106415 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YOUNG, SEAN · 2015 to 2019
$2.9M
Digital Device ID Targeting for Increasing Medications for Opioid Use Disorder: A Feasibility and Acceptability StudyR34DA054511 · NIDA · UNIVERSITY OF CALIFORNIA-IRVINE · PI YOUNG, SEAN · 2021 to 2023
$707k
NCCIH NIH HHS R33 AT010606NIAID NIH HHS R01 AI132030NIDA NIH HHS R34 DA054511NIMH NIH HHS R01 MH106415
6 · The paper itself

Abstract

Digital data, including social media, wearable device data, electronic health records, and internet search data, are increasingly being integrated into public health research and policy. Because of the current issues around public distrust of science and other ethical issues in public health research, it is essential that researchers conduct ongoing studies assessing people's perceptions around and willingness to share digital data. This study aims to examine participants' social media use and comfort sharing their data with health researchers. One hundred and sixty-one participants with medical conditions were recruited through social media paid advertisements and referral from a website, and invited to complete surveys on social media use and ethical perspectives on data sharing. Eligibility criteria were adults 18 years old or older, living in the US, self-reported having been diagnosed by a physician with a medical condition, belonging to at least one social media platform, using social media at least twice a week, and owning a smartphone. Study participants were mostly female, White, and with a mean age of 36.31 years. More than one third of participants reported being very comfortable sharing electronic health data and social media data for personalized healthcare and to help others. Findings suggest that participants are very uncomfortable sharing their location and text message data with researchers, with primary concerns centered around loss of privacy, disclosing private information, and that friends, family, and others may find out that they shared text messages with researchers. We discuss the implications of this research before and after the COVID-19 pandemic, along with its potential implications for future collection of digital data for public health.

Indexed as

data sharingdigital dataethicsprivacysocial media

Identifiers

PMID35547191
PMCPMC9082996
OpenAlexW4224706193

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.