Using machine learning methods to predict non-suicidal self-injury and suicidal behavior in the general adolescent population: a cross-sectional study

Using machine learning methods to predict non-suicidal self-injury and suicidal behavior in the general adolescent population: a cross-sectional study - Explore the relationship and impact factors of non-suicidal self-injury and suicidal behavior among teenagers in general

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2400082948

Enrollment

Unknown

Registered

2024-04-11

Start date

2024-04-11

Completion date

Unknown

Last updated

2024-04-15

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Non-suicidal self-injury

Interventions

General adolescent group:No

Eligibility

Sex/Gender

All

Age

11 Years to 18 Years

Inclusion criteria

Inclusion criteria: (1) The age was 12-18 years old and gender was not limited; (2) Patients and their legal guardians agreed to participate in this study and signed an informed consent form.

Exclusion criteria

Exclusion criteria: (1) Those who were unable to understand the content of the questionnaire and could not complete the questionnaire assessment; (2) Excluding patients with clinically diagnosed mental illness; (3) Excluding those with serious physical diseases, such as serious respiratory, cardiovascular, endocrine and hematologic diseases.

Design outcomes

Primary

Measure	Time frame
Adolescent Non-suicidal Self-injury Assessment Questionnaire;suicide attempt;suicide ideation;	—

Secondary

Measure	Time frame
center for epidemiological survey,depressionscale,CES-D;Study Stress Questionnaire for Middle School Students;	—

Countries

China

Contacts

Public ContactXu Chen

Shandong Mental Health Center

ch99jn@163.com+86 187 0531 7127

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026