Evidence map›Paper›PMID 27042689›Full record

ArticleCurrent opinion in psychology2016

Social Media, Big Data, and Mental Health: Current Advances and Ethical Implications.

Mike Conway, Daniel O'Connor

Abstract read
In one paragraph

Article in Current opinion in psychology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed, 3 pooled it
25.6field-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

76 citing papers in PubMed, 3 syntheses or guidelines pooled it, 247 citations in OpenAlex.

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16 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

2 authors at 2 institutions in 2 countries.

Mike ConwayDepartment of Biomedical Informatics, University of Utah, 421 Wakara Way, Salt Lake City, Utah, United States.
Daniel O'ConnorWellcome Trust, Gibbs Building, 215 Euston Road, London NW1 2BE, United Kingdom.
University of Utah · USWellcome Trust · GB

Funding

Utilizing social media as a resource for mental health surveillanceR00LM011393 · NLM · UNIVERSITY OF UTAH · PI CONWAY, MICHAEL AMBROSE · 2014 to 2016
$667k
Utilizing social media as a resource for mental health surveillanceK99LM011393 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CONWAY, MICHAEL AMBROSE · 2013 to 2013
$83k
NLM NIH HHS K99 LM011393NLM NIH HHS R00 LM011393Wellcome Trust
6 · The paper itself

Abstract

Mental health (including substance abuse) is the fifth greatest contributor to the global burden of disease, with an economic cost estimated to be US $2.5 trillion in 2010, and expected to double by 2030. Developing information systems to support and strengthen population-level mental health monitoring forms a core part of the World Health Organization's Comprehensive Action Plan 2013-2020. In this paper, we review recent work that utilizes social media "big data" in conjunction with associated technologies like natural language processing and machine learning to address pressing problems in population-level mental health surveillance and research, focusing both on technological advances and core ethical challenges.

Identifiers

PMID27042689
PMCPMC4815031
OpenAlexW2250240141

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.