Evidence map›Paper›PMID 33415185›Full record

ArticleJournal of technology in behavioral science2020

Social Media and Mental Health: Benefits, Risks, and Opportunities for Research and Practice.

John A Naslund, Ameya Bondre, John Torous, Kelly A Aschbrenner

Abstract read
In one paragraph

Article in Journal of technology in behavioral science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 210 papers, 12 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
210citing papers in PubMed, 12 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

210 citing papers in PubMed, 12 syntheses or guidelines pooled it.

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150 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.

John A NaslundDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, MA.
Ameya BondreCareNX Innovations, Mumbai, India.
John TorousDepartment of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA.
Kelly A AschbrennerDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH.

Funding

ESSENCE (Enabling translation of Science to Service to ENhance Depression CarE) Scale-UpU19MH113211 · NIMH · HARVARD MEDICAL SCHOOL · PI PATEL, VIKRAM H · 2017 to 2023
$3.7M
Peer Support and Mobile Technology Targeting Cardiometabolic Risk Reduction in Young Adults with SMIR01MH110965 · NIMH · DARTMOUTH-HITCHCOCK CLINIC · PI ASCHBRENNER, KELLY A · 2016 to 2019
$1.9M
Digital Phenotyping for Computational Models of Relapse Prediction in Early Course PsychosisK23MH116130 · NIMH · BETH ISRAEL DEACONESS MEDICAL CENTER · PI TOROUS, JOHN · 2018 to 2021
$872k
NIMH NIH HHS K23 MH116130NIMH NIH HHS R01 MH110965NIMH NIH HHS U19 MH113211
6 · The paper itself

Abstract

Social media platforms are popular venues for sharing personal experiences, seeking information, and offering peer-to-peer support among individuals living with mental illness. With significant shortfalls in the availability, quality, and reach of evidence-based mental health services across the United States and globally, social media platforms may afford new opportunities to bridge this gap. However, caution is warranted, as numerous studies highlight risks of social media use for mental health. In this commentary, we consider the role of social media as a potentially viable intervention platform for offering support to persons with mental disorders, promoting engagement and retention in care, and enhancing existing mental health services. Specifically, we summarize current research on the use of social media among mental health service users, and early efforts using social media for the delivery of evidence-based programs. We also review the risks, potential harms, and necessary safety precautions with using social media for mental health. To conclude, we explore opportunities using data science and machine learning, for example by leveraging social media for detecting mental disorders and developing predictive models aimed at characterizing the aetiology and progression of mental disorders. These various efforts using social media, as summarized in this commentary, hold promise for improving the lives of individuals living with mental disorders.

Indexed as

digital healthmental healthmHealthpsychiatrysafetysocial media

Identifiers

PMID33415185
PMCPMC7785056

What OpenQuestion holds

Textmetadata
LicenceTDM
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.