Evidence map›Paper›PMID 42378779›Full record

ArticleDrug and alcohol dependence2026

Monitoring novel psychoactive substance trends on social media: Analysis of discussions and dashboard implementation.

Sahithi Lakamana, Sudeshna Das, Anthony Spadaro, Rachel Wightman, Jeanmarie Perrone, Abeed Sarker

Abstract read
In one paragraph

Article in Drug and alcohol dependence, 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

6 authors.

Sahithi LakamanaDepartment of Biomedical Informatics, School of Medicine, Emory University, USA.
Sudeshna DasDepartment of Biomedical Informatics, School of Medicine, Emory University, USA.
Anthony SpadaroDepartment of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, USA.
Rachel WightmanDepartment of Medicine, The Warren Alpert Medical School, Brown University, USA.
Jeanmarie PerroneDepartment of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, USA.
Abeed SarkerDepartment of Biomedical Informatics, School of Medicine, Emory University, USA. Electronic address: abeed@dbmi.emory.edu.

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

introductionNovel psychoactive substances (NPSs), due to rapid emergence and evolving use patterns, pose a significant public health surveillance challenge. Traditional surveillance lags street-level reality, necessitating the exploration of novel strategies and data sources like Reddit for continuous NPS trend monitoring and presenting a public dashboard.

methodsWe mined data from 60,601 subreddits between January 2015 and June 2025 for seven NPSs (kratom, xylazine, medetomidine, nitazenes, tianeptine, bromazolam, and 2C-B) using keyword-variants. We performed Mann-Kendall trend tests to assess temporal patterns, computed correlations to compare post volumes with National Forensic Laboratory Information System (NFLIS) drug report counts (2015-2024), conducted cross-correlation analyses at ±2-year lags to identify lead-lag relationships, and created a public dashboard for data visualization.

resultsThe dataset comprised 328,223 posts from 139,901 accounts. We observed moderate to strong correlations between Reddit volumes and three out of five NPSs with NFLIS reports: bromazolam (ρ = 0.81, p < 0.001), tianeptine (ρ = 0.48, p = 0.04), xylazine (ρ = 0.60, p < 0.001). Cross-correlation analyses indicated Reddit discussions preceded NFLIS reports for medetomidine (ρ = 0.93, lag = -2 years), bromazolam (ρ = 0.86, lag = -1year), tianeptine (ρ = 0.81, lag = -2years), and xylazine (ρ = 0.62, lag = -2years), suggesting Reddit discussions as a potential leading indicator. Co-mention of other substances with NPSs often matched known trends from retrospective data.

conclusionReddit-based surveillance provides timely and complementary signals to traditional forensic systems for NPS monitoring. Interactive visualizations and downloadable aggregated statistics are available via our dashboard.

Indexed as

Illicit DrugsPsychotropic DrugsSocial MediaSubstance-Related DisordersDashboard SystemsHumansIllicit DrugsPsychotropic DrugsNovel psychoactive substancesPublic healthSocial mediaSubstance useVisualization

Identifiers

PMID42378779
PMCPMC13333105

What OpenQuestion holds

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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.