Evidence map›Paper›PMID 35265945›Full record

ArticleBiomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference)2022

Comparative Analysis of Patient Distress in Opioid Treatment Programs using Natural Language Processing.

Fatemeh Shah-Mohammadi, Wanting Cui, Keren Bachi, Yasmin Hurd, Joseph Finkelstein

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Fatemeh Shah-MohammadiIcahn School of Medicine at Mount Sinai, New York, NY, U.S.A.
Wanting CuiIcahn School of Medicine at Mount Sinai, New York, NY, U.S.A.
Keren BachiIcahn School of Medicine at Mount Sinai, New York, NY, U.S.A.
Yasmin HurdIcahn School of Medicine at Mount Sinai, New York, NY, U.S.A.
Joseph FinkelsteinIcahn School of Medicine at Mount Sinai, New York, NY, U.S.A.

Funding

Mentalizing deficits in cocaine addiction, associations with immune dysregulation and childhood maltreatmentK23DA045928 · NIDA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BACHI, KEREN · 2018 to 2022
$649k
NIDA NIH HHS K23 DA045928
6 · The paper itself

Abstract

Psychiatric and medical disorders, social and family environment, and legal distress are important determinants of distress that impact the effectiveness of the treatment in opioid treatment program (OTP). This information is not routinely captured in electronic health record, but may be found in clinical notes. This study aims to explore the feasibility and effectiveness of natural language processing (NLP) strategy for identifying legal, social, mental and medical determinates of distress along with emotional pain rooted in family environment from clinical narratives of patients with opioid addiction, and then using this information to find its impact on OTP outcomes. Analysis in this study showed that mental and legal distress significantly impact the result of the treatment in OTP.

Indexed as

Determinants of DistressNatural Language Processing (NLP)Opioid Treatment Program (OTP)

Identifiers

PMID35265945
PMCPMC8903064

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.