Agriculture continues to form the primary employment base for most rural households in India and contributes approximately 18.2% of the country’s GDP at the current prices (PIB, 2023). Despite agriculture’s substantial economic contribution and its documented high return on investment, with every rupee invested in agricultural research generating Rs. 13.84 in returns (Ministry of Finance, Government of India, 2023), the sector remains paradoxically afflicted by widespread distress, particularly among small and marginal farmers. This contradiction underscores a critical disconnect: while agriculture demonstrably contributes to national food security and economic growth, structural vulnerabilities continue to undermine the welfare of those who sustain it, thus becoming prey of phenomena of farmers’ distress. The distress is defined as the challenges faced by the farmers and rural communities in terms of economic, social, and political factors due to low productivity of crops, fluctuations in prices, indebtedness among them, lack of access to credit facilities, etc. (Chaithanya et al., 2024). In Haryana, farmer indebtedness is a significant cause of distress, with small and marginalized farmers facing disproportionate challenges in accessing institutional credit. This forces them to rely on non-institutional sources with high-interest rates, perpetuating a cycle of debt and financial strain (Jakhar et al., 2023). In Uttar Pradesh, the agrarian distress is exacerbated by the high cost of farming inputs, market volatility, and inadequate credit facilities. The state has seen a significant rise in farmer suicides, attributed to indebtedness and financial instability (Lal and Singh, 2024).

The story does not end here at the fact that distress is simply the result of the aforementioned factors, but over the last decades, the neoliberal policies of agriculture, the changes occurring in the climate, and increase in the cost of production due to the rise in factor costs have collectively made the farmers vulnerable to these issues (Deshpande and Arora, 2010). Yet, these issues cannot be viewed in isolation. Over recent decades, the combined influence of neoliberal policy reforms, escalating input and living costs, and accelerating climate change has emerged as a complex web of interrelated systemic pressures. Neoliberal policies, which are basically characterized by market deregulation and reduced state intervention, create conditions where the rising costs of essential services and climate change impacts are experienced as mutually reinforcing systemic pressures (Saad-Filho and Feil, 2024). The adoption of these policies has reduced direct government support for small and marginal farmers, thus exposing them to price volatility and diminishing bargaining power (Sonwale and Kadam, 2022; Mishra A., 2020). Additionally, continuous increases in the cost of seeds, fertilizers, and labor have further eroded farm profitability, intensifying indebtedness and restricting access to credit facilities (Anjum, 2021). At the same time, climate change amplifies these economic challenges and adds to the precariousness of already vulnerable rural households (Deshpande and Arora, 2010; Chaithanya et al., 2024). The Cauvery Delta region in Tamil Nadu has experienced persistent monsoon failures, leading to severe water scarcity and crop failures. This has resulted in a notable increase in farmer suicides (Vignesh and Karthikeyan, 2017; Sabarisakthi, 2019). Consequently, these forces do not act in isolation but reinforce each other, compounding agrarian distress and undermining the long-term sustainability and resilience of rural livelihoods in India (Sonwale and Kadam, 2022; Mishra A., 2020). Policy interventions, viz., minimum support prices, loan waiving policies, etc., have produced limited and short-lived relief (Reddy and Mishra, 2010). According to the studies (Jones et al., 2023; Kroll, 2022), the distress in the farming community further leads to chronic depression, anxiety attacks, and attempt to suicide in many cases. The consequences of this distress are not contained within the individual farmer but spread to families and entire communities (Mishra, 2022). Such widespread suffering impacts rural stability, as farm households struggle to remain productive and can ultimately threaten India’s national food security by reducing the agricultural labor force and hampering crop output. Therefore, resolving farmers’ distress remains pivotal, not only for the welfare of farm households but also for sustaining rural communities and ensuring a reliable food supply at a macro level (Chakrabarti et al., 2018). Addressing this issue requires a holistic and multi-pronged approach which includes improving the credit access, insuring the crop against weather uncertainties, modernizing the agricultural inputs, and strengthening the cooperatives and farmer producers organizations as well (Bhoi and Dadhich, 2019). According to a study done by Kaur et al. (2016), farmers’ distress arises from a series of tangled factors, such as economic, social, environmental, and psychological factors. All the given factors interact with each other so much that it becomes difficult to separate and analyze them independently. Furthermore, the distress varies from one region to another depending upon factors such as the size of landholdings, climatic conditions, cropping patterns, etc. A review done by Kaur et al. (2016) reported that many farmers affected by these problems are not ready to participate in the studies or reveal the extent of distress. Moreover, factors that contribute to the farmer’s distress are not static but dynamic (Mishra, 2023). As for the data available on websites, secondary information is fragmented or outdated, which is not reliable for the studies. Moreover, it extends far beyond an individual or occupational issue—it represents a profound societal challenge with wide-ranging economic, social, and psychological implications. The prolonged suffering of farmers triggers a chain reaction that weakens rural households, fragments community networks, and endangers national food security (Mishra, 2022). Such agrarian distress often manifests in reduced productivity, increased indebtedness, rural migration, and growing social unrest, all of which obstruct inclusive and sustainable development (Reddy and Mishra, 2010; Chaithanya et al., 2024). Recognizing it as a collective societal concern, rather than an isolated agrarian crisis, is indispensable for realizing the Sustainable Development Goals and ensuring equitable and long-term rural wellbeing (Food and Agriculture Organization of the United Nations (FAO), 2018). To address the multi-dimensional nature of farmer distress, sophisticated methodological approaches are required that synthesize diverse expert perspectives and generate evidence-based and consensus-driven solutions. Traditional research methodologies often fail to capture the complexity and interconnectedness of factors contributing to farmer distress. Innovative methodologies such as the Delphi method have shown particular effectiveness in agriculture for synthesizing multi-disciplinary viewpoints and generating actionable recommendations (Sturla et al., 2024; Adams et al., 2022a,b; Larsen K. et al., 2019). Therefore, innovative, integrative approaches are needed to synthesize diverse expert perspectives.

According to Frewer et al. (2011), the Delphi technique is appropriate where the problem is ill-structured, and the data available are scattered or scarce. Although the traditional Delphi methods have been widely accepted as an effective tool and have been used in a wide range of applications, problems of ambiguity and uncertainty in experts’ opinions still remain. The measurement of human judgement is considered to be an emotional, complex, perceptual, subjective, and personal phenomenon, involving many domains of an individual’s life experience. In general, classic rating scales (e.g., 5- or 7-point Likert scales) inherently consider crisp numbers to measure human thinking. The Fuzzy Delphi Method (FDM) was developed to overcome this problem through the combination of fuzzy theory and the classical methodology.

The Fuzzy Delphi Method (FDM) is a variation of the traditional Delphi method that incorporates fuzzy logic to handle uncertainties and ambiguities in expert judgment (Hierro et al., 2021). Kaufmann and Gupta (1988) presented the application of the Fuzzy Delphi technique for forecasting.

According to Mohd Jamil et al. (2014) and Mohd Ridhuan and Nurulrabihah (2020), Fuzzy Delphi consists of the following steps:

It involves using a Fuzzy Scale, which is a 5-point scale derived from the Likert Scale, to measure the level of agreement among experts. This scale allows for a more nuanced analysis of expert opinions compared to a traditional Likert Scale. The Fuzzy Scale assigns fuzzy values to each Likert scale value, ranging from 0 to 1, to quantify the degree of agreement or disagreement. Table 3 represents the Likert scale, linguistic variable, and triangular fuzzy number.

A triangular fuzzy number (TFN) is a fuzzy number, which is displayed with three real numbers [F = (l, m, u)]. The upper bound denoted by u is the maximum value of the fuzzy number F. The lower bound denoted by l is the minimum value of fuzzy number F; m is the most probable value of a fuzzy number (Figure 2). The membership function μ(x) of a triangular fuzzy number defines the degree of membership of any value x within the fuzzy set, ranging from 0 to 1, with 1 indicating complete membership and 0 indicating no membership. It is represented as follows:

Figure 3 represents values in a Triangular Fuzzy Number, denoted as 𝑀 = (𝑚₁, 𝑚₂, 𝑚₃), where 𝑚₁, 𝑚₂, and 𝑚₃ represent the lower, modal (most likely), and upper bounds of the fuzzy set, respectively. The horizontal axis corresponds to the universe of discourse, while the vertical axis (𝜇_𝑢) indicates the membership degree ranging from 0 to 1. The membership function increases linearly from 0 at 𝑚₁ to 1 at 𝑚₂, and then decreases linearly back to 0 at 𝑚₃. 𝑀ⁱ(𝑦) and 𝑀^𝑟(𝑦) denote the left and right membership functions of the TFN, respectively, which define the degree of belonging of a value 𝑦 within the fuzzy set. The membership function is represented as follows:

This section summarizes the findings of the Fuzzy Delphi Method (FDM) analysis for the strategies of farmer distress based on expert consensus. For each strategy, the table displays the triangular fuzzy numbers (A), threshold values (C), expert agreement percentages (D), fuzzy scores (E), and ranks (F). A total of 61 strategies were identified using the Delphi method. After conducting fuzzy Delphi, out of 61 total strategies evaluated, 47 strategies (77.0%) achieved expert consensus and were accepted based on dual criteria: threshold value (d ≤ 0.2) and expert agreement percentage (≥75%) (see Figure 5).

A comprehensive assessment of expert feedback was conducted to refine financial strategies relevant to the domain. By applying the Fuzzy Delphi Method, 14 potential strategies were evaluated based on four criteria. Supplementary Table S1 presents the fuzzy Delphi analysis of all the strategies that were asked from the expert with respect to the financial domain. There were a total of 14 strategies finalized, out of which four got rejected. The fifth strategy, named “Promote cooperative marketing initiatives and linkage to cooperative societies’, was highest among consensus based on ease of application. The same strategies were evaluated based on cost-effectiveness, the third strategy, named “low-cost subsidized life insurance to farmers,” was highest in terms of expert agreement, while “Promote cooperative marketing initiatives and linkage to cooperative societies” strategy was ranked highest in terms of both ease of application and cost-effectiveness. The strategies “Provision of credit guarantee schemes with better availability of credit” and “Low-cost subsidized life insurance to farmers” were ranked as top most strategies in terms of relevance and alignment to national policies/programs/SDG goals.

Supplementary Table S2 shows the selected and rejected strategies of the marketing domain. The strategies “Organizing regular buyer seller meet by KVK and line department in the particular locality” and “Strengthening market intelligence to enable farmers and to make informed decisions about what to grow, when to sell, and where to sell” were ranked as top strategies to combat farmer distress according to ease of application and alignment to national policies/programs/SDG goals, respectively. The strategy “Better price realization to farmers by directly connecting them to consumers through an electronic platform” achieved the highest overall ranking for both cost-effectiveness and relevancy, highlighting the importance of digital platforms. The single rejected strategy involved government market regulation and monopoly prevention, which failed to achieve consensus across all criteria (25–30% agreement) due to concerns about implementation feasibility and effectiveness at the societal level.

There were a total of nine strategies for the psychological domain. The strategy “Provision of community centers for group discussion, farmers meeting and to attend Agri-related rituals” was ranked top according to ease of application and relevancy, and it also ranked second in terms of cost-effectiveness, whereas the strategy “Organize workshops and campaigns to educate farmers about mental health” was second in terms of relevancy and alignment to programs and policies. It shows the need of community-driven mental health approaches and points out the importance of collective learning. The strategy “Conduct awareness campaigns to reduce stigma around mental health issues” was rejected across all sub-categories, which suggests that intense and mobilizing community-based engagement may not be impactful. The findings further indicate that active involvement may be more effective than merely providing awareness through campaigns.

Supplementary Table S4 represents all the accepted and rejected strategies of the legal domain. It shows that 10 strategies were accepted and two strategies were rejected. The strategy “Providing farmers with access to legal aid clinics or counselling services where they can receive guidance on their rights, entitlements, and legal options” was ranked first in terms of ease of application and cost-effectiveness, whereas it was ranked as the second preferred strategy in terms of alignment to national policies/programs/SDG. The strategy named “Simplify and streamline legal procedures related to land ownership, tenancy rights, and access to government support schemes” was preferred best in terms of relevancy. The strategy “Strengthening land tenure security through legal reforms and ensuring that farmers have clear title deeds or lease agreements” was rejected due to low feasibility and weak consensus. It may indicate that experts are focusing on localized and accessible solutions rather than broader structural reforms.

Supplementary Table S5 represents all the accepted and rejected strategies for the production domain. There were a total of 12 strategies, out of which two strategies were rejected. The strategy named “Cover production risk by providing PMFBY and support schemes like RYTHU BANDHU (Andhra Pradesh) Yojana, KALIA Yojana (Orissa) etc.” was ranked first in terms of cost-effectiveness and relevancy and the strategy was ranked as fourth in terms of alignment to national policies/programs/SDG. The strategy “Soil testing & distribution of soil health cards on a regular basis” was ranked first in terms of alignment to national policies/programs/SDG. The strategies named “Encourage collaboration between farmers, local institutions, NGOs, and government agencies to address common challenges and promote inclusive development” and “Facilitation of information from the nearest KVK or SAU about production technologies, innovative technologies or any other initiative with respect to production domain” were rejected. It may be rejected due to perceived implementation challenges.

Farmers’ distress is an ever-present phenomenon, especially among farmers of developing and underdeveloped countries, given the nature of agriculture, which cannot be equated with any fully commercial operations. The scarcity of resources, given the huge number of people dependent on agriculture in India, and the transformative pressure on farmers from both the family and market sides start and sustain the phenomenon of farmers’ distress, which often remains undetected. Thus, instead of becoming reactive to certain farmer distress incidents, which often manifest themselves in the form of self-harm, the policymaker should become proactive to implement strategies to nip it in the bud. The efforts to alleviate distress must therefore emphasize adaptability, inclusiveness, and ongoing stakeholder consultation. This study, through a fuzzy Delphi framework, brings together expert consensus to illuminate pathways that are both evidence-based and contextually grounded. Across the five domains, the financial emerged as the most consistently accepted domain, indicating that financial vulnerability is perceived as the most immediate and critical driver of farmer distress. The validation of 47 actionable strategies across five domains underscores the necessity of integrated policy frameworks rather than fragmented interventions. The findings reveal that sustainable solutions must move beyond temporary relief measures to embrace long-term resilience—through cooperative marketing, inclusive financial protection, strengthened legal support, and community-based mental health systems. The key findings of this study indicate that farmer distress is driven not by a single factor but by the cumulative interaction of market failures, financial vulnerability, legal uncertainty, institutional gaps, and inadequate mental health support. The fuzzy Delphi analysis revealed strong expert consensus on strategies that prioritize collective action, institutional convergence, and preventive support mechanisms, while standalone awareness-based or short-term relief measures showed limited effectiveness. The recommendations proposed in this study directly emerge from these validated findings and are intended to guide policymakers toward integrated, participatory, and long-term interventions that address both the causes and consequences of farmer distress. The present study presents a policy checklist and dynamic roadmap for strengthening resilience and wellbeing in rural India. Ultimately, this research advocates for a paradigm shift: from viewing farmer distress as an episodic crisis to addressing it as a structural and societal phenomenon demanding collective action. Embedding these expert-driven strategies within national policy can foster a more equitable, resilient, and sustainable agricultural system—where sustainability is measured by both the productivity and wellbeing of farmers.