Agrarian distress management among farmers of south Gujarat: Multidimensional assessment, district-level disparities and measurement reliability

Introduction

Agriculture remains a cornerstone of the Indian economy, with nearly 60 per cent of the population depending on it for their livelihood. However it is increasingly exposed to multiple challenges such as climate change, market volatility, resource constraints and declining farm profitability, which threaten livelihood security and sustainability (Raghavendra et al., 2024; Gamit and Vinaya, 2024; Gamit and Vinaya, 2022) [14,10,9] . The inherent vulnerability of Indian agriculture to uncontrollable external forces renders it highly susceptible to production and income uncertainties (Kumar and Karthikeyan, 2017). Agrarian distress has emerged as a critical issue, driven by crop failures, natural calamities, income instability, indebtedness and limited access to institutional support systems (Mishra, 2007; Deshpande and Prabhu, 2005) [12,8] . The growing frequency and intensity of extreme weather events, as highlighted by the Intergovernmental Panel on Climate Change have further intensified risks in agriculture. Along with economic stress, farmers also experience psychological and social pressures, making agrarian distress a multidimensional phenomenon. In this context, agrarian distress management has gained importance as it reflects farmers' ability to cope with and adapt to diverse stressors. The present study conceptualizes ADM as a multidimensional construct encompassing six key dimensions: preventive farm management, time management and organization, health and lifestyle coping, www.extensionjournal.com cognitive and emotional adjustment, social, communal and institutional support and diversion and spiritual coping. These dimensions collectively represent behavioural, psychological, organizational and social strategies adopted by farmers to mitigate distress and sustain their livelihoods. Regionally, Gujarat is increasingly vulnerable to climate variability due to rising temperatures of the Arabian Sea, resulting in erratic rainfall and higher humidity in coastal areas. Environmental degradation, including declining forest cover reported by the Forest Survey of India (Anonymous, 2025b) [6] , has further intensified climatic instability. South Gujarat, in particular, faces multiple agro-ecological challenges such as cyclones, flooding, salinity and soil degradation, which adversely affect agricultural productivity (Patil et al., 2023) [13] . Recurrent extreme events, including excess rainfall, unseasonal rains and Cyclone Biparjoy, have resulted in significant crop losses and economic damage (Anonymous, 2020; 2023a; 2023b) [1,2,3] . Recent prolonged rainfall leading to "leelo dukaal" ("green famine," a condition of crop damage due to excess rainfall) conditions further reflects the persistent nature of agrarian distress in the region (Anonymous, 2024; 2025a) [4,5] . In this context, there is an urgent need to understand how farmers manage agrarian distress at the field level, particularly under recurring climate-induced challenges in South Gujarat. Despite extensive research on agrarian distress in India, the majority of studies have primarily focused on its causes, including climatic variability, economic instability and farmer suicides, with comparatively limited attention to farmers' management strategies at the field level. Existing literature predominantly emphasizes macro-level analyses and policy perspectives, often overlooking micro-level behavioural responses and multidimensional ADM mechanisms adopted by farmers. Although a few studies have addressed psychological stress and adaptation, there remains a lack of comprehensive frameworks integrating farm management, organizational, psychological, social and spiritual dimensions of distress management. In addition, region-specific empirical evidence from South Gujarat is limited, particularly in the context of recurring climateinduced shocks and agro-ecological vulnerabilities. The present study attempts to fill this gap by developing and applying a structured, multidimensional framework to assess agrarian distress management among farmers in South Gujarat. The findings of the study will be useful for policymakers, agricultural extension agencies and development practitioners in designing farmer-centric interventions. The study also holds significance for agricultural extension by providing insights into farmers' ADM behaviour, which can guide the development of targeted advisory and support systems. Further, the use of a standardized and reliable measurement tool enhances the scientific rigor of the study and provides a foundation for future research in ADM. Objectives 1. To quantify the level of agrarian distress management among farmers in South Gujarat 2. To examine dimension-wise patterns and district-level disparities in agrarian distress management among farmers of South Gujarat 3. To assess the reliability of the ADM measurement schedule using Cronbach's Alpha, Hotelling's T² test and Intraclass Correlation Coefficient

Methodology

The present investigation was conducted in the South Gujarat region of Gujarat under the jurisdiction of Navsari Agricultural University. An ex-post facto research design was adopted, as the variables under study had already occurred and were beyond the control of the researcher. The study covered seven districts, namely Bharuch, Surat, Narmada, Tapi, Navsari, Valsad and The Dangs. A multistage random sampling technique was employed. In the first stage, two talukas from each district were selected randomly, followed by the selection of two villages from each taluka in the second stage through simple random sampling. In the final stage, ten farmers from each village were selected through simple random sampling, resulting in a total sample size of 280 respondents. Primary data were collected through personal interviews using a wellstructured and pre-tested interview schedule designed to measure ADM across multiple dimensions. Secondary data were obtained from annual reports, research publications, bulletins, books and official records. Data collection was carried out during November 2025 to January 2026 through farm and household visits. The collected data were coded, tabulated and analysed using MS Excel, R software (version 4.6.0) and Python (version 3.14). ADM was assessed dimension-wise by computing scores for each dimension. Descriptive statistical tools such as mean, frequency, percentage and standard deviation were used for analysis. A radar mapping technique was employed to visually represent the comparative performance of different dimensions. The reliability of the structured schedule was assessed using Cronbach's Alpha, while content validity was ensured through expert consultation and pilot testing prior to the main survey. The ADM index was computed using minmax normalization, and the scores were standardized on a 0-100 scale using the following formula:

The minimum and maximum possible scores were derived based on the number of respondents, number of items and the 5-point continuum scale. Dimension-wise analysis was carried out by aggregating the scores of respective items and expressing them as percentage indices. Equal weightage was assigned to all dimensions to maintain comparability. The dimensions were ranked in descending order, where higher index values indicated stronger coping capacity. Similarly, the district-wise ADM index was computed by aggregating the total scores of respondents across all dimensions within each district and expressing them as percentage values. Districts were ranked accordingly based on the obtained index values. Further, Hotelling's T² test was employed to determine whether significant differences existed among the mean scores of items, thereby assessing their discriminating ability. The Intraclass Correlation Coefficient (ICC) was computed to evaluate the consistency and reliability of measurements across items, providing estimates for both single and average measures, using a two-way mixed effects model based on absolute agreement for average measures, following the guidelines of Koo and Mae. www.extensionjournal.com The analysis reveals that a considerable proportion of farmers fell under moderate to high ADM (73.22%), indicating that a majority of respondents were able to adopt various coping and adaptive strategies to manage agrarian distress. This pattern may be attributed to accumulated farming experience, informal support networks and exposure to extension services, which collectively enhance farmers' coping capacity. However, the presence of farmers in lower categories indicates structural and resource constraints, suggesting the need for targeted institutional interventions and capacity building programmes. These findings are in line with the studies of Tandekar (2014) [15] , Kerketta (2022) [11] and Belokar (2022) [7] , who reported that farmers predominantly fell under moderate ADM categories due to partial access to institutional and social support systems. In the Diversion and Spiritual Coping dimension Tapi district obtained the highest index value reflecting greater engagement in relaxation and spiritual practices as coping mechanisms while Narmada district recorded the lowest value. Overall, the results indicate that although most districts demonstrated moderate to high levels of ADM noticeable disparities exist particularly in interior and resource constrained districts highlighting the need for targeted extension support institutional strengthening and psychological resilience programmes to ensure balanced ADM across districts. The results of Hotelling's T² test indicated a statistically significant difference among the mean scores of the items (T² = 378.545; F = 8.384; p < 0.01). This finding suggests that the items do not have equal mean values and vary significantly in their responses and confirming the heterogeneity and discriminating ability of the scale items. Such significant differences in item means confirm that each item captures a distinct aspect of ADM, thereby demonstrating adequate discriminating ability. It may be noted that redundancy of items is assessed through interitem correlations and not through mean differences; Hotelling's T² thus confirms discriminating power rather than uniqueness of content. The Intraclass Correlation Coefficient (ICC) analysis revealed a low reliability for single measures (ICC = 0.185), indicating limited consistency when individual items are considered independently. However, the average measures ICC (0.901) was found to be very high, with a narrow confidence interval (0.884-0.917), demonstrating excellent reliability of the composite scale. The statistically significant F-value (p < 0.01) further confirms the consistency of the measurements. These results indicate that although individual items may show variability, the aggregated scale provides a highly stable and reliable measure of ADM. Overall, the findings indicate that farmers in South Gujarat exhibit moderate to high levels of ADM, primarily driven by managerial efficiency and personal ADM strategies. The reliability analysis further confirms that the ADM scale is a robust and consistent instrument for assessing ADM behaviour. However, the observed inter-district disparities and relatively lower performance in certain dimensions highlight the need for targeted interventions, strengthened extension support and improved institutional mechanisms to enhance farmers' resilience against agrarian distress.

Reliability of the Adm Measurement Schedule

Acknowledgement

AcknowledgementWe would like to express our sincere gratitude to all the members of the research advisory committee and Department of Agricultural Extension and Communication, Navsari Agricultural University, Navsari for their invaluable contributions to this manuscript in shaping the content & improving the quality of our work. We would also thankful to the Scheme of Developing High Quality Research (SHODH) Gujarat, for their financial support and also thankful for the farmers of respective selected villages and local administration.

References

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