The role of Self-Help Groups in strengthening resilience amidst the COVID-19 pandemic: Insights from India

Abstract Self-Help Groups (SHGs), the credit based voluntary groups in India are widely known for their potential to alleviate poverty and empower women. This research article explores a lesser-known theme. It tries to analyze the possibility of utilizing the current SHG model of the Indian Government to build and strengthen resilience of the SHG members in case of an external shock like financial stress, food insecurity, dispute in home for joining SHG, and difficulty to repay loan amidst lockdown due to the COVID-19 pandemic. This article also focuses on their coping mechanisms and attitude towards these crises. By utilizing primary data collected from 320 SHG members in one of the aspirational districts in West Bengal, India, the present paper tries to fulfill its objective. It provides a comprehensive understanding of the problems faced by the SHG members by combining both quantitative and qualitative techniques. The findings reveal that from organizing vocational trainings to relaxing loan repayment, SHGs and its women members overcame various adversities with tenacity, especially during the COVID-19 pandemic. Based on the study findings, it is reasonable to conclude that the current SHG model in India presents a promising avenue for enhancing the resilience of its members in the face of external shocks.

Authors

Institutions

Publication Details

Journal
Discover Global Society
Published
2024-09-06
DOI
https://doi.org/10.1007/s44282-024-00057-5
Citations
4
Primary Topic
COVID-19 and Mental Health
Type
article
Field-Weighted Citation Impact
2.56
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The role of Self-Help Groups in strengthening resilience amidst the COVID-19 pandemic: Insights from India

Debashree Sinha, Aparajita Chattopadhyay
4 citations
Discover Global Society
COVID-19 and Mental Health
2.56
article

The role of Self-Help Groups in strengthening resilience amidst the COVID-19 pandemic: Insights from India

Debashree Sinha, Aparajita Chattopadhyay
article en
4 citations

Abstract

Abstract Self-Help Groups (SHGs), the credit based voluntary groups in India are widely known for their potential to alleviate poverty and empower women. This research article explores a lesser-known theme. It tries to analyze the possibility of utilizing the current SHG model of the Indian Government to build and strengthen resilience of the SHG members in case of an external shock like financial stress, food insecurity, dispute in home for joining SHG, and difficulty to repay loan amidst lockdown due to the COVID-19 pandemic. This article also focuses on their coping mechanisms and attitude towards these crises. By utilizing primary data collected from 320 SHG members in one of the aspirational districts in West Bengal, India, the present paper tries to fulfill its objective. It provides a comprehensive understanding of the problems faced by the SHG members by combining both quantitative and qualitative techniques. The findings reveal that from organizing vocational trainings to relaxing loan repayment, SHGs and its women members overcame various adversities with tenacity, especially during the COVID-19 pandemic. Based on the study findings, it is reasonable to conclude that the current SHG model in India presents a promising avenue for enhancing the resilience of its members in the face of external shocks.

Discover Global SocietyVol. 2(1)
International Institute for Population Sciences (IN)
Openalex Percentile: Top 11%
COVID-19 and Mental Health
2.56
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.