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Prediction of suicidal behavior among substance abusers using artificial neural network

Prediction of suicidal behavior among substance abusers using artificial neural network: A case study of Princess Mother National Institute on Drug Abuse Treatment.

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
TCTR
Registry ID
TCTR20200423004
Enrollment
Unknown
Registered
2020-04-23
Start date
2020-04-25
Completion date
Unknown
Last updated
2026-08-03

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

Conditions

substance abusers Suicidal behavior SUICIDAL BEHAVIOR SUBSTANCE ABUSE ARTIFICIAL NEURAL NETWORK

Interventions

substance abusers with suicidal ideation (frequent thoughts of ending one&#39
s life) or suicide attempts (the actual event of trying to kill one&#39
s self),substance abusers without suicidal ideation (frequent thoughts of ending one&#39
s life) and suicide attempts (the actual event of trying to kill one&#39
s self)
Screening,Screening
substance abusers with Suicidal behavior,substance abusers Non suicidal behavior

Sponsors

Faculty of Pharmacy, Silpakorn University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 65 Years

Inclusion criteria

Inclusion criteria: patients were diagnosed with ICD-10 code F10 to F19 in Princess Mother National Institute on Drug Abuse Treatment

Exclusion criteria

Exclusion criteria: 1. head trauma with residual effects 2. severe cognitive impairment 3. intellectual disabilities 4. palliative care

Design outcomes

Primary

MeasureTime frame
suicidal behavior The 2 weeks before enrolled PHQ-9 score—

Secondary

MeasureTime frame
clinical variables and demographic variables 12 months before enrolled Medical Record—

Countries

Thailand

Contacts

Public ContactSutthipun suriya

College of Pharmacy Rangsit university

pharm_J@hotmail.com0909328189

Outcome results

None listed

Source: TCTR (via WHO ICTRP) · Data processed: Aug 9, 2026