ArticleHealthcare (Basel, Switzerland)2022
Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 40 citations in OpenAlex.
- Large Language Models for Mental Health Applications: Systematic Review.JMIR mental health · 2024Pooled it
- Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.International journal of environmental research and public health · 2023Pooled it
- Large Language Models for Mental Health Prediction: Scoping Review of Bias and Clinical Utility Documentation in 2019-2024.JMIR AI · 2026Review
- Effectiveness of Hybrid AI and Human Suicide Detection Within Digital Peer Support.Journal of clinical medicine · 2026Article
- Large Language Models for Cardiovascular Disease, Cancer, and Mental Disorders: A Review of Systematic Reviews.Healthcare (Basel, Switzerland) · 2025Review
- Acute suicidal ideation in context: highlighting sentiment-based markers through the diary entries of a clinically depressed sample.BMC psychiatry · 2025Article
- The Applications of Large Language Models in Mental Health: Scoping Review.Journal of medical Internet research · 2025Article
- Applications of Large Language Models in the Field of Suicide Prevention: Scoping Review.Journal of medical Internet research · 2025Article
- Generative multimodal large language models in mental health care: Applications, opportunities, and challenges.PLOS mental health · 2025Review
- A systematic review on passive sensing for the prediction of suicidal thoughts and behaviors.Npj mental health research · 2024Article
- Comparative analysis of BERT-based and generative large language models for detecting suicidal ideation: a performance evaluation study.Cadernos de saude publica · 2024Article
- A Scoping Review of Digital-Based Intervention for Reducing Risk of Suicide Among Adults.Journal of multidisciplinary healthcare · 2024Article
- Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review.Journal of clinical medicine · 2023Review
- The use of advanced technology and statistical methods to predict and prevent suicide.Nature reviews psychology · 2023Article
- Unsupervised natural language processing in the identification of patients with suspected COVID-19 infection.Cadernos de saude publica · 2023Observational
- Suicide risk detection using artificial intelligence: the promise of creating a benchmark dataset for research on the detection of suicide risk.Frontiers in psychiatry · 2023Article
- A randomized 3-month, parallel-group, controlled trial of CALMA m-health app as an adjunct to therapy to reduce suicidal and non-suicidal self-injurious behaviors in adolescents: study protocol.Frontiers in psychiatry · 2023Article
- A Review of Converging Technologies in eHealth Pertaining to Artificial Intelligence.International journal of environmental research and public health · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
People at risk of suicide tend to be isolated and cannot share their thoughts. For this reason, suicidal ideation monitoring becomes a hard task. Therefore, people at risk of suicide need to be monitored in a manner capable of identifying if and when they have a suicidal ideation, enabling professionals to perform timely interventions. This study aimed to develop the
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.