Evidence map›Paper›PMID 40256165›Full record

ArticleFrontiers in psychiatry2025

A predictive model of non-suicidal self-injury - a study based on the construction and validation of a nomogram.

YuJie Liu, TaiMin Wu, Shu Yan, Yang Zhou, Lianzhong Liu

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. 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

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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.

YuJie LiuSchool of Medicine, Jianghan University, Wuhan, Hubei, China.
TaiMin WuOffice of Psychosocial Services, Wuhan Mental Health Center, Wuhan, Hubei, China.
Shu YanOffice of Psychosocial Services, Wuhan Mental Health Center, Wuhan, Hubei, China.
Yang ZhouOffice of Psychosocial Services, Wuhan Mental Health Center, Wuhan, Hubei, China.
Lianzhong LiuDepartment of Psychiatry, Wudong Hospital, Wuhan, Hubei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The issue of psychological maladjustment, particularly Non-Suicidal Self-Injury (NSSI), is prevalent among vocational high school students. Therefore, timely identification of high-risk individuals is important in providing further intervention. Methods: A survey was conducted among 2081 students from a vocational high school in Wuhan, China. The students were divided into two groups: those who had engaged in Non-Suicidal Self-Injury (NSSI) within the past two weeks and those who had not. Lasso regression and logistic regression were employed to identify significant risk factors associated with NSSI. Subsequently, a nomogram was developed to enhance the accuracy and efficiency of identifying individuals at high risk for NSSI. The performance of the model was assessed through various validation methods including Area Under the Curve (AUC), calibration curves, and Decision Curve Analysis (DCA). Results: The significant predictors of NSSI encompassed gender, problem behavior, depressive mood, and borderline personality tendencies. Based on these predictors, a nomogram was constructed. The model's accuracy was validated using AUC, calibration curves, and DCA, showing high accuracy. Conclusion: A nomogram prediction tool for NSSI among vocational high school students was constructed, providing an accurate and quick method for predicting adolescent NSSI behavior.

Indexed as

bioinformaticsclinical applicationsdata analysismachine learningneural networks

Identifiers

PMID40256165
PMCPMC12006177

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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.