Evidence map›Paper›PMID 39506139›Full record

ReviewNpj mental health research2024

Automatically extracting social determinants of health for suicide: a narrative literature review.

Annika M Schoene, Suzanne Garverich, Iman Ibrahim, Sia Shah, Benjamin Irving, Clifford C Dacso

Abstract readReview
In one paragraph

Review in Npj mental health research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Life events extraction from healthcare notes for veteran acute suicide risk prediction.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
  2. Article
  3. Comparing LLM and Fine-Tuned Model Performance on NVDRS Circumstance Extraction with Varying Prompt Complexity.Proceedings. IEEE International Conference on Healthcare Informatics · 2026
    Article
  4. 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

6 authors.

Annika M SchoeneNortheastern University, Institute for Experiential AI, Boston, USA. a.schoene@northeastern.edu.
Suzanne GarverichNortheastern University, Institute for Health Equity and Social Justice Research, Boston, USA.
Iman IbrahimNortheastern University, Institute for Health Equity and Social Justice Research, Boston, USA.
Sia ShahNortheastern University, Institute for Health Equity and Social Justice Research, Boston, USA.
Benjamin IrvingNortheastern University, Institute for Experiential AI, Boston, USA.
Clifford C DacsoMedicine Baylor College of Medicine, Houston, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Suicide is a complex phenomenon that is often not preceded by a diagnosed mental health condition, therefore making it difficult to study and mitigate. Artificial Intelligence has increasingly been used to better understand Social Determinants of Health factors that influence suicide outcomes. In this review we find that many studies use limited SDoH information and minority groups are often underrepresented, thereby omitting important factors that could influence risk of suicide.

Identifiers

PMID39506139
PMCPMC11541747

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.