Publication Name	World Journal of Psychiatry
Manuscript ID	123346
DOI	10.5498/wjp.123346
Country	South Africa

Category	Psychology, Clinical
Manuscript Type	Observational Study
Article Title	Artificial intelligence based prediction of psychological distress among ride-hailing drivers in a low resource setting
Manuscript Source	Invited Manuscript
All Author List	Mkpoikanke S Otu and Maximus M Sefotho
Funding Agency and Grant Number
Corresponding Author	Mkpoikanke S Otu, Senior Postdoctoral Fellow, Department of Educational Psychology, University of Johannesburg, Corner Kingsway and University Road, Auckland Park, Johannesburg 2092, Gauteng, South Africa. mkpoikankeotu@gmail.com
Key Words	Psychological distress; Ride-hailing drivers; Artificial intelligence; Machine learning; Gig economy; Occupational stress; Low-resource settings
Core Tip	This study explores the use of artificial intelligence and machine learning to predict psychological distress among ride-hailing drivers in a low-resource setting, addressing a critical gap in occupational mental health research within the gig economy. By identifying psychosocial and work-related risk factors, the study offers an innovative, scalable approach for early mental health screening and intervention among vulnerable informal workers. Findings contribute to digital psychiatry, global mental health, and the development of context-sensitive preventive strategies in underserved populations.
Citation	Otu MS, Sefotho MM. Artificial intelligence based prediction of psychological distress among ride-hailing drivers in a low resource setting. World J Psychiatry 2026; In press DOI: https://doi.org/10.5498/wjp.123346
PDF	123346-in-press.pdf

Received	2026-05-25 08:54
Peer-Review Started	2026-05-25 08:54
First Decision by Editorial Office Director
Return for Revision	2026-07-21 02:28
Revised	2026-08-14 21:35
Publication Fee Transferred
Second Decision by Editor	2026-11-05 03:30
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director	2026-11-05 05:37
Articles in Press	2026-11-05 05:37
Edit the Manuscript by Language Editor
Typeset the Manuscript

ISSN	2220-3206 (online)
Open Access	This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
Copyright	©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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