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Silent struggles: a machine learning approach for predicting suicidal ideation based on crisis symptoms and childhood trauma in Saudi adolescents

Published Online: 2025-12-10

Authors

Keshky, Mogeda El Sayed El https://orcid.org/0000-0003-0456-9889
Hamididin, Radeah Mohammed https://orcid.org/0000-0002-2160-2823
Funding

Funding for this research was provided by:

The National Centre for Social Research (NCSS) in Saudi Arabia (ن ع – 46 - 1)
License Information

Text and Data Mining valid from 2025-12-10

Version of Record valid from 2026-01-14
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Article History

Received: 20 August 2025

Accepted: 4 December 2025

First Online: 10 December 2025

Declarations

:

: This study received ethical approval from the Ethics Committee of the Faculty of Arts and Humanities, King Abdulaziz University, Jeddah, Saudi Arabia. All participants were informed about the aim of the study and their right to withdraw from the study at any time, and informed consent was obtained from all participants. For participants under the age of 16, informed consent was additionally obtained from their parents or legal guardians. All procedures followed were carried out in accordance with the Helsinki Declaration of 1975, as revised in 2000.

: Not applicable.

: The authors declare no competing interests.

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