Evidence map›Paper›PMID 40671703›Full record

ArticleChina CDC weekly2025

Establishment and Validation of a Risk Prediction Model for Non-Suicidal Self-Injury Among Adolescents Based on Machine Learning Methods - Jiangsu Province, China, 2023.

Xin Wang, Yan Wang, Jiawen Tang, Yang Wang, Ran Zhang, Xiyan Zhang, Wenyi Yang, Wei Du, Fei Wang, Jie Yang

Abstract read
In one paragraph

Article in China CDC weekly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Xin WangDepartment of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China.
Yan WangDepartment of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China.
Jiawen TangSchool of Public Health, Nanjing Medical University, Nanjing City, Jiangsu Province, China.
Yang WangEarly Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing City, Jiangsu Province, China.
Ran ZhangEarly Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing City, Jiangsu Province, China.
Xiyan ZhangDepartment of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China.
Wenyi YangDepartment of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China.
Wei DuSchool of Public Health, Southeast University, Nanjing City, Jiangsu Province, China.
Fei WangEarly Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing City, Jiangsu Province, China.
Jie YangDepartment of Child and Adolescent Health Promotion, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Non-suicidal self-injury (NSSI) has become increasingly common among adolescents, posing a significant public health concern that impacts both physical and mental well-being. What is added by this report?: A total of 12.72% of adolescents aged 10-18 had engaged in NSSI in Jiangsu Province, China. A well-calibrated risk prediction model [AUC=0.800, 95% confidence interval ( What are the implications for public health practice?: This study underscores the importance of personalized prevention strategies for NSSI and highlights the necessity of implementing comprehensive behavioral interventions, such as providing mental health support, enhancing sleep quality, and cultivating supportive family environments.

Indexed as

AdolescentsMachine LearningNon-suicidal self-injury

Identifiers

PMID40671703
PMCPMC12259475

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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.