ArticleInformatics in medicine unlocked2023
Identifying the predictors of severe psychological distress by auto-machine learning methods.
Article in Informatics in medicine unlocked, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed, 12 citations in OpenAlex.
- Integrating ESG indicators and behavioral factors to estimate the mental health index in Italy.International journal of mental health systems · 2026Article
- Comparison of Feature Selection Methods in Machine Learning Models of Cancer Information Seeking Among United States Adults: Cross-Sectional Study.JMIR medical informatics · 2026Article
- Machine learning in the analysis of mental health at work: a scoping review.Journal of occupational health · 2026Article
- Comparing machine learning and artificial neural network models in psychological research: a ROC-based analysis.Frontiers in psychology · 2026Article
- Assessing psychological resilience and its influencing factors in the MSM population by machine learning.Scientific reports · 2025Article
- Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Measuring Raven's Progressive Matrices Combining Eye-Tracking Technology and Machine Learning (ML) Models.Journal of Intelligence · 2024Article
- Loneliness, online learning and student outcomes in college students living with disabilities: results from the National College Health Assessment Spring 2022.Frontiers in psychology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Social stress in daily life and the COVID-19 pandemic have greatly impacted the mental health of the population. Early detection of a predisposition to severe psychological distress is essential for timely interventions. This paper analyzed 4036 samples participating in the 2019-2020 National Health Information Trends Survey (HINTS) and identified 57 candidate predictors of severe psychological distress based on univariate chi-square and
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.