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. 2021 Apr 20;8(4):e25097. doi: 10.2196/25097

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©Indra Prakash Jha, Raghav Awasthi, Ajit Kumar, Vibhor Kumar, Tavpritesh Sethi. Originally published in JMIR Mental Health (https://mental.jmir.org), 20.04.2021.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included.

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(a) Outline of the analytical pipeline. (b) Item reliability analysis of mental health indicators revealed a high degree of internal consistency (Cronbach alpha value >.70) for most of the psychological variables, thus indicating suitability for the modeling exercise. ML: machine learning.