Evidence map›Paper›PMID 42412511›Full record

ArticleJMIR infodemiology2026

Self-Reported Tianeptine Experiences on Reddit: Natural Language Processing-Assisted Qualitative Study.

Christopher J Counts, Anthony V Spadaro, Sahithi Lakamana, Abeed Sarker, Rachel Wightman, Jennifer Love, Diane Calello, Jeanmarie Perrone

Abstract read
In one paragraph

Article in JMIR infodemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Christopher J CountsDepartment of Emergency Medicine, Rutgers New Jersey Medical School, 140 Bergen St, Newark, NJ, 07103, United States, 1 720-446-8235.ORCID http://orcid.org/0000-0002-6524-4263
Anthony V SpadaroDepartment of Emergency Medicine, Rutgers New Jersey Medical School, 140 Bergen St, Newark, NJ, 07103, United States, 1 720-446-8235.ORCID http://orcid.org/0000-0002-0941-4651
Sahithi LakamanaDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.ORCID http://orcid.org/0000-0003-1304-7484
Abeed SarkerDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, United States.ORCID http://orcid.org/0000-0001-7358-544X
Rachel WightmanDepartment of Emergency Medicine, Brown University Health, Providence, RI, United States.ORCID http://orcid.org/0000-0001-6141-1776
Jennifer LoveDepartment of Emergency Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, United States.ORCID http://orcid.org/0000-0002-5882-4390
Diane CalelloDepartment of Emergency Medicine, Rutgers New Jersey Medical School, 140 Bergen St, Newark, NJ, 07103, United States, 1 720-446-8235.ORCID http://orcid.org/0000-0003-1752-847X
Jeanmarie PerroneDepartment of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID http://orcid.org/0000-0002-3396-6333

Funding

Mining Social Media Big Data for Toxicovigilance: Studying Substance Use via Natural Language Processing and Machine Learning MethodsR01DA057599 · NIDA · EMORY UNIVERSITY · PI Abeed H Sarker · 2022 to 2026
$2.2M
NIDA NIH HHS R01 DA057599
6 · The paper itself

Abstract

Unlabelled: This study, using natural language processing and manual thematic analysis of Reddit posts, revealed a rapid rise in discussions about tianeptine, with posts frequently reporting dependence, withdrawal, and coingestion with other unregulated substances, highlighting tianeptine as an emerging public health concern.

Indexed as

Antidepressive Agents, TricyclicNatural Language ProcessingSocial MediaThiazepinesHumansQualitative ResearchSelf ReportAntidepressive Agents, TricyclicThiazepinestianeptinenatural language processingopioid use disorderRedditsocial mediasurveillancetianeptine

Identifiers

PMID42412511
PMCPMC13340079

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.