Self-engagement on social media as a digital intervention to stress coping

Viral Nagori & Bidit Lal Dey

Journal of Enterprise Information Management2026https://doi.org/10.1108/jeim-09-2025-0911article
AJG 2ABDC A
Weight
0.50

Abstract

Purpose The purpose of the article is to explore how digital intervention through technology is used for stress coping among women entrepreneurs during the crisis period. Design/methodology/approach The study employed an interpretivist approach and conducted in-depth interviews with women entrepreneurs in India. We used an inductive coding technique for qualitative data analysis and framework creation. Findings The article proposes a framework for coping responses based on the Transactional Theory of Stress and Coping. The analysis presents family support, self-care, and the ability to adjust to a new normal as the secondary appraisal and demonstrates how self-engagement on social media can act as a digital intervention to help reduce stress. Research limitations/implications The findings provide a platform for scholars to perform future research to empirically test the proposed framework and can extend further to address the differences between men and women in using social media engagement as a digital intervention for stress coping. Originality/value The research is the first of its kind to explore how women entrepreneurs use social media engagement as a digital intervention to stress coping in difficult times.

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https://doi.org/https://doi.org/10.1108/jeim-09-2025-0911

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@article{viral2026,
  title        = {{Self-engagement on social media as a digital intervention to stress coping}},
  author       = {Viral Nagori & Bidit Lal Dey},
  journal      = {Journal of Enterprise Information Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/jeim-09-2025-0911},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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