Evidence map›Paper›PMID 33375934›Full record

ArticleBMC bioinformatics2020

Analysis of associations between emotions and activities of drug users and their addiction recovery tendencies from social media posts using structural equation modeling.

Deeptanshu Jha, Rahul Singh

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

9 citing papers in PubMed, 25 citations in OpenAlex.

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  8. Investigating Substance Use via Reddit: Systematic Scoping Review.Journal of medical Internet research · 2023
    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

2 authors at 1 institution in 1 country.

Deeptanshu JhaDepartment of Computer Science, San Francisco State University, 1600 Holloway Ave., San Francisco, CA, 94132, USA.
Rahul SinghDepartment of Computer Science, San Francisco State University, 1600 Holloway Ave., San Francisco, CA, 94132, USA. rahul@sfsu.edu.ORCID http://orcid.org/0000-0003-3900-4298
San Francisco State University · US

Funding

HEART & SOUL: Enabling full representation in biomedical Big Data scienceR25MD011714 · NIMHD · SAN FRANCISCO STATE UNIVERSITY · PI AKOM, ANTWI AARON · 2017 to 2019
$950k
Directorate for Computer and Information Science and Engineering IIS-1817239Foundation for the National Institutes of Health 1R25MD011714NIMHD NIH HHS R25 MD011714
6 · The paper itself

Abstract

backgroundAddiction to drugs and alcohol constitutes one of the significant factors underlying the decline in life expectancy in the US. Several context-specific reasons influence drug use and recovery. In particular emotional distress, physical pain, relationships, and self-development efforts are known to be some of the factors associated with addiction recovery. Unfortunately, many of these factors are not directly observable and quantifying, and assessing their impact can be difficult. Based on social media posts of users engaged in substance use and recovery on the forum Reddit, we employed two psycholinguistic tools, Linguistic Inquiry and Word Count and Empath and activities of substance users on various Reddit sub-forums to analyze behavior underlining addiction recovery and relapse. We then employed a statistical analysis technique called structural equation modeling to assess the effects of these latent factors on recovery and relapse.

resultsWe found that both emotional distress and physical pain significantly influence addiction recovery behavior. Self-development activities and social relationships of the substance users were also found to enable recovery. Furthermore, within the context of self-development activities, those that were related to influencing the mental and physical well-being of substance users were found to be positively associated with addiction recovery. We also determined that lack of social activities and physical exercise can enable a relapse. Moreover, geography, especially life in rural areas, appears to have a greater correlation with addiction relapse.

conclusionsThe paper describes how observable variables can be extracted from social media and then be used to model important latent constructs that impact addiction recovery and relapse. We also report factors that impact self-induced addiction recovery and relapse. To the best of our knowledge, this paper represents the first use of structural equation modeling of social media data with the goal of analyzing factors influencing addiction recovery.

Indexed as

EmotionsSocial MediaHumansLatent Class AnalysisRecurrenceResearch DesignSubstance-Related DisordersAddiction recoveryOnline communitiesOpioid epidemicPersonalized interventionsRedditSocial mediaStructural equation modelingSubstance misuse disorderText mining

Identifiers

PMID33375934
PMCPMC7772931
OpenAlexW3116180094

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.