https://orcid.org/0000-0002-6769-783X
Figures
Abstract
Population ageing within the agricultural workforce renders drought adaptation among older farmers an urgent yet underexamined dimension of climate resilience. This study examines how farmers aged 60–69 in drought-prone communities of Buriram Province, Thailand, perceive and respond to drought risk, drawing on social–psychological theories of behavior and decision-making. Using stratified group discussions with older farmers who have more than a decade of farming experience, the analysis indicates that drought adaptation is shaped by the complex interaction of behavioral beliefs, social norms, perceived self-efficacy, and cost–benefit appraisals. Older farmers’ responses are mediated by peer-influenced cognitive processes, including observation, imitation, comparison, and self-regulation, as well as by community norms that reinforce social pressure to maintain traditional farming identities. At the same time, they also apply their own evaluative frameworks to weigh immediate climate threats against the physical and financial costs of altering long-standing practices. This experience-based appraisal determines whether a self-protective strategy is perceived as feasible or too costly within the constraints of their life stage and available resources. Strengthening peer-based knowledge exchange and community-led extension mechanisms tailored to ageing farmers is therefore recommended to align adaptive interventions with these cognitive and social dynamics.
Citation: Pechdin W, Swangsilp S (2026) Psychosocial adaptation as a coping strategy among older farmers facing drought in Thailand. PLOS Clim 5(5): e0000926. https://doi.org/10.1371/journal.pclm.0000926
Editor: Zerina Lokmic-Tomkins, Monash University Faculty of Medicine Nursing and Health Sciences, AUSTRALIA
Received: February 27, 2026; Accepted: April 24, 2026; Published: May 19, 2026
Copyright: © 2026 Pechdin, Swangsilp. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All data that support the findings of this study are included within the article. The full data for the study is not publicly available due to the stipulations of ethical approval. However, inquiries regarding data access requests can be directed to the corresponding author (sorasich@yahoo.fr) and The Human Research Ethics Committee of Thammasat University (Social Sciences) at irbsctu@gmail.com.
Funding: This work was supported by Thammasat University Research Unit in Social Policy and Sustainable Development (Grant Number: N/A, to WP), and the Foundation of Thai Gerontology Research and Development Institute (TGRI) and the Thai Health Promotion Foundation (Grant Number: 66-00304-03 to WP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
The impact of drought ranks among the major threats to human security and well-being globally [1–4], and is particularly significant in Southeast Asia [5–8], with wide-ranging and severe effects on agriculture [9–11], food security and water resources [8,12], as well as the economy and human well-being [8,10]. These impacts are especially pronounced in contexts where agricultural production systems remain highly dependent on labor intensive practices and climate sensitive livelihoods, with limited integration of technological innovation [13,14]. In such settings, exposure to climate variability directly translates into productivity loss and income instability, as adaptive capacity is constrained by structural reliance on natural conditions rather than buffered by innovation or mechanization [15–17].
In Southeast Asia, Thailand represents a critical case at the intersection of drought vulnerability and demographic change. In 2023, the agricultural sector experienced losses exceeding 13.45 million USD (439.67 million Thai Baht) due to a prolonged dry spell between May and September, affecting more than 24,000 farmers and damaging over 110,000 acres of farmland, as reported by the Ministry of Agriculture and Cooperatives of Thailand [18]. At the same time, the sector is increasingly shaped by population ageing. By 2024, more than 50% of the agricultural labor force, approximately 2.84 million individuals, is aged 60 or older [19]. This rapid transition toward an ageing farmer society introduces a distinct structural vulnerability, where declining physical capacity and limited access to innovation intersect with heightened exposure to climate stress. Due to this, Thai farmers face compounded risks that not only reduce immediate productivity but also constrain their ability to transition toward more resilient, innovation driven systems.
Similar trends are observed across multiple countries. In Japan, the average age of farmers reached 68 years in 2020; in the United Kingdom, it was 60 years as of 2016; and in Canada, projections indicate an average age of 65 years by 2025 [20]. These patterns reflect a global demographic shift with significant implications for agricultural sustainability and resilience. An ageing farming population may face constraints in adopting and sustaining effective adaptation strategies, as responses are often partial, reactive, and insufficient to offset the increasing intensity and frequency of drought [15,17]. Consequently, farmer households remain persistently vulnerable and exposed to recurring shocks, emphasizing the need for more in-depth investigation into adaptation processes among older farmers [17,21–23].
Older farmers often face distinct difficulties in the adaptive process due to physical limitations that reduce their ability to acquire and apply new practices [24,25]. Existing agricultural studies both in large-and-small scale indicate these constraints not only limit their participation in drought adaptation practices, such as sustainable land management, crop diversification, and off-farm income activities [17,22,26,27], but also restrict their access to and effective use of climate information, extension services, and technological innovations. In addition, age-related risk aversion and shorter planning horizons may discourage investment in long-term adaptive measures, further constraining their capacity to respond proactively to climatic stress [22,28]. As a result, adaptation among older farmers is often characterized by incremental and coping-oriented responses rather than transformative changes, which may be insufficient to address the increasing severity and frequency of drought.
Psychosocial processes, encompassing the interaction between cognitive factors such as risk perception and self-efficacy, social influences including norms, networks and support, and institutional dimensions such as trust and access to information, are critical to understanding adaptation to slow onset hazards such as drought [29–32]. As drought gradually normalizes resource scarcity, these processes shape how farmers interpret risks, evaluate available options and ultimately select coping strategies [33,34]. This temporal dynamic can reduce the perceived urgency to act or, conversely, heighten stress under prolonged uncertainty [35,36]. Among older farmers, lived experience may both support adaptation and reinforce established practices [37–39], while perceptions of capability, social expectations, and confidence in institutions shape whether strategies such as crop adjustment, resource reallocation, or livelihood diversification are adopted [40–43]. As a result, adaptation is often incremental and reactive despite sustained exposure.
There is a need for climate policy interventions toward ageing farmers that go beyond technical support, by strengthening confidence [44,45], improving access to tailored information [46,47], and fostering trust-based and community-oriented extension systems [44,46,48] to enable more effective and equitable adaptation. Therefore, this study, using Thailand as a case study, investigates adaptation processes with a particular focus on how psychosocial processes including with cognitive, social and institutional dynamics interact to shape the selection of drought coping strategies. It seeks to advance understanding of how age-related constraints, risk perceptions, institutional trust, access to information and community norms collectively influence adaptation behavior. These insights are essential for informing targeted interventions that align with the learning capacities, lived experiences and socio-cultural contexts of ageing farming populations.
Method
Conceptual framework
In Fig 1, the conceptual framework positions psychosocial processes as the central mechanism linking drought exposure to coping behavior. It integrates three interrelated dimensions. First, the social cognitive dimension is based on the assumption that individuals learn and form responses through observation and experience [49–52], and that their level of self-efficacy shapes how they evaluate their capacity to act and make decisions. Second, builds on the proposition that coping behavior is preceded by intention [53], which is shaped by attitudes toward the behavior, perceived social norms, and perceived behavioral control. Third, the risk appraisal dimension is informed by the view that protective actions are driven by how individuals perceive and interpret risk, including their assessment of drought severity, the reliability of available information, and the perceived effectiveness of potential responses [54,55]. These dimensions interact to structure how older farmers interpret drought conditions and select coping strategies, framing responses as outcomes of interconnected cognitive, social, and perceptual processes rather than isolated reactions.
The figure explains how drought exposure triggers psychosocial processes that shape coping behavior along a continuum from avoidance to adaptive responses. Key mechanisms include risk perception, self-efficacy, social norms, and cognitive processes such as imitation, comparison, and self-regulation, which influence how individuals evaluate and select strategies. These processes are further conditioned by social and contextual factors, ultimately determining the adoption of short term or adaptive coping strategies such as livelihood adjustment and water management.
Study area and participants
The study was conducted in three districts in Buriram Province, as shown in Fig 2. The province ranks among the top province in Northeastern of Thailand and the most severely affected by extreme drought, according to the Drought Risk Index from Geo-Informatics and Space Technology Development Agency of Thailand (GISDA) [18].
Buriram province, located in northeastern Thailand on the Khorat Plateau, experiences a tropical dry season from roughly mid-October to late April, with minimal rainfall and high evaporation that can lead to periodic drought conditions affecting agriculture and water resources. Map constructed using QGIS (2024), Version 3.40. Regional border shape file obtained from Natural Earth 1:50, Cultural Vector (download from: https://www.naturalearthdata.com/downloads/50m-cultural-vectors/). Thailand geographic data (GIS) obtained from Royal Survey Department-Thailand Subnational Administrative Boundaries under license CC-BY-IGO (download from https://data.humdata.org/dataset/cod-ab-tha;).
In 2015, Buriram has suffered notable drought episodes, including a severe dry period a decade ago when farmers sought government support after one of the worst droughts in 50 years damaged large areas of cultivated land and low dam storage levels restricted annual crop cultivation [56].
The study participants were older farmers aged between 60 and 69 years, each with over 10 years of farming experience. The target population for this study consists of farmers aged 60–69 years. This specific cohort was selected because they represent older farmers who still possess the functional capacity for training and knowledge transfer. This is supported by physiological research indicating that the ability to acquire new learning typically begins to decline more significantly from the age of 70 onwards [57,58].
Consequently, a total of 18 participants were recruited and organized into three focus groups, each comprising six individuals from the same district. To enhance the diversity of perspectives and reduce potential bias arising from demographic clustering, each group was purposively balanced by age and gender. Specifically, two participants were selected from each age range (60–63, 64–66, and 67–69 years), and an equal gender distribution was maintained (three males and three females). This stratification strengthens the validity of insights by capturing variation across key demographic dimensions.
Participant selection was conducted through consultations with multiple agricultural officers from the district office to reduce selection biases. This approach helped to counterbalance individual subjectivities and gatekeeping effects, which are common risks in a case study research with purposive and network-based recruitment [59]. Additionally, this approach helped minimize the likelihood of systematically overrepresenting more visible, accessible, or cooperative farmers while excluding marginalized or less-connected individuals. Table 1 presents the inclusion and exclusion criteria adopted from these consultations for participant recruitment.
Furthermore, the participations were entirely voluntary, and written consent was obtained from all individuals prior to the discussions. Details of these participants were indicated in Table 2.
Research instrument and data collection
A focus group discussion was employed as the primary research tool to explore community coping mechanisms and support systems related to drought. The discussion was guided by a semi-structured interview with a set of key questions designed to elicit detailed responses about participants’ experiences and strategies. To ensure the content validity of the questions, the five experts were invited to review and verify the research questions using the Index of Item-Objective Congruence (IOC). Only questions with acceptable IOC scores were retained for use in the focus group. These questions and their expectations included:
- (1) What steps do you take when you experience drought?; to understand the steps they take when experiencing drought
- (2) What factors influence your choice of coping strategies during drought?; to understand the factors that influence their choice of coping strategies
- (3) Which agency has helped you the most in recovering from drought?; to explore the agencies that have been most supportive in facilitating recovery
- (4) What is the process of mitigation you received from relevant agencies during the drought?; to explore the mitigation processes provided by relevant institutions during drought events
Ethical statement
Prior to conducting the research, the study was obtained ethical approval from the Human Research Ethics Committee of Thammasat University Social Sciences (Certificate Number 074/2567). The group discussion was conduct during 10–15 November 2024. Written Consent was obtained before conducting data collection. On the date of discussion, the data collection instrument, including key questions, was administered to each group, with follow up questions tailored to the objectives of each main question. Each group was expected to complete the discussion within one hour. During the conversations, participants shared their experiences of coping with drought through a deductive process, drawing upon their recent past five years of plantation calendars to provide insights into their strategies, responses, and interactions with support agencies in relation to drought management.
To ensure a supportive environment, no video or audio recordings were made; instead, detailed notes were taken. Participants’ identities were excluded from the written report. A neutral stance was maintained, with emphasis on attentive, non-judgmental listening. To further foster a safe and comfortable setting, participants were informed of their right to decline any questions that caused discomfort. The interview reports were reviewed and cross-checked with data from available published reports. The completed reports were returned to the informants for review or re-interviewing (in some cases) to verify their intent, consistency, and adequacy before analysis.
Analytical technique
Following the proposed theoretical framework, we applied Braun and and Clarke [60] thematic analysis approach to examine adaptation process through the behavioral responses of older farmers to drought conditions. Our analysis was further guided by the thematic protocol suggested by Luke, McIlveen [61], ensuring a rigorous and structured qualitative examination. The analysis proceeded through six systematic steps as follows:
- (1) Familiarization with the Data: We initiated the process by immersing ourselves in the collected data.
- (2) Generating Initial Codes: Next, we generated preliminary codes based on data we had. Particular attention was given to expressions related to farmers’ self-perception, socio-cultural beliefs, and decision-making processes. Table 3 below provides a visual summary of the initial codes:
- (3) Searching for Themes: In this phase, we clustered the initial codes into overarching themes that encapsulated behavioral tendencies of older farmers during drought. A conceptual map (Fig 1) was developed to illustrate the formation and relationships among these themes.
In Fig 3, risk perception and information are shaped by self-directed learning, drought literacy, and risk awareness, influences how farmers assess their capacity to act. Socio-cultural beliefs, formed through norms, cultural values, and farm responsibilities, determine which actions are considered acceptable or expected. Together, these two domains guide decision-making, affecting how farmers weigh financial burdens, investment risks, and the effort required for adaptation.
The framework illustrates the interactions among farmers’ drought-related decisions, self-perception, and socio-cultural beliefs.
- (4) Reviewing and Refining Themes: We undertook a rigorous review of each emerging theme to confirm their alignment with the overall data. This stage involved cross-checking coded extracts against full transcripts to ensure internal coherence and thematic relevance.
- (5) Defining and Naming Themes: Each theme was carefully defined to capture the essence of the behavioral patterns observed.
- (6) Writing the Report: Finally, we compiled a comprehensive report articulating the findings.
To strengthen the analysis, we also integrated direct quotations from interviewees to illustrate and support each theme. This approach ensured that our thematic discussion remained closely grounded in first-hand data, thereby enhancing the reliability of the findings in addressing the study’s objectives.
Limitations
This study is based on a small, context specific sample of 18 older farmers drawn exclusively from Buriram, one of the most drought prone areas in Thailand. Although this setting shares an important context for examining coping under conditions of severe and persistent drought, the limited sample size constrains statistical generalizability. In addition, the geographic concentration means that findings may reflect location specific environmental, social, and institutional dynamics that are not representative of other regions. Moreover, the study does not incorporate statistical records or quantitative measures, as it prioritizes in-depth discussion and qualitative interpretation of participants’ experiences. This limits the ability to assess the magnitude or distribution of observed patterns. Finally, the study is designed to examine how older farmers respond to drought through psychosocial and behavioral mechanisms, rather than to compare responses across age groups. Therefore, categories such as “young” or “middle-aged” farmers are not operationalized.
Accordingly, the study is best interpreted as an in-depth case study analysis that clarifies psychosocial processes underlying coping behavior, rather than as evidence of population wide patterns. These insights generated offer analytical generalizability by showing how risk perception, self-efficacy, and social norms interact under severe drought conditions, but should be applied to broader contexts with caution. To mitigate these limitations, the study adopted data triangulation, a method that helps reduce bias associated with reliance on a single data source [62]. Therefore, following each interview, responses were systematically reviewed and cross checked against available secondary sources from relevant datasets and reports. This process enhanced the consistency and credibility of the findings. Nonetheless, further research with larger and more diverse samples is required to validate and extend these results.
Key findings
Based on the data collected through focus group discussions with older farmers, we found that their adaptation process for selecting coping strategies during drought was closely linked to cognitive processing, the formation of planned behavior, and the implementation of responsive adaptation. This indicates the process was not random but rather guided by reflective thinking and experience-based planning. Details are illustrated in Fig 4 as follows:
The figure illustrates the progression from cognitive thinking, shaped by risk perception, knowledge, and self-efficacy, to planned behavior, and ultimately to responsive adaptation. It highlights how internal cognitive processes translate into deliberate actions that enable effective responses to drought stress within an ageing agricultural context.
Theme 1: The relationship between cognitive thinking and personal adaptation
In this first theme, the degree of drought adaptation among participants is influenced by cognitive processes, including observation, imitation, comparison, and self-regulation, as illustrated in Fig 5.
The figure illustrates how cognitive processes, including imitation and comparison with their household assets, shape adaptation levels by guiding how individuals interpret and respond to environmental stress. These processes are reinforced by self-regulation, through which individuals monitor, evaluate, and adjust their behavior based on observed outcomes and personal goals. Through observing others, comparing alternatives, and regulating their responses, individuals adopt strategies that lead to varying levels of adaptation.
Beginning with farmers’ awareness and risk perception of drought, the participants demonstrated engagement in cognitive appraisal of both the severity of the situation and the household assets available to cope with it. This process involved not only recognizing external threats but also making internal judgments about their capacity to respond. Their decision-making was shaped by cognitive thinking processes, such as evaluating prior experiences, or estimating utilization of their household assets. This was supported by the expression from the participants:
“When drought hits, I try to manage it the best I can on my own, based on what’s worked before.”
(K5,Group 1)
“Sometimes I think, ‘Well, if others aren’t changing, maybe I don’t need to either.’ “
(K2,Group 1)
“We compare, we observe, and we adjust only if we really have to. At this point, it’s more about getting by than trying something uncertain.”
(K1,Group 1)
Their responses illustrated a form of experience-based decision-making shaped by cognitive thinking processes rather than external direction or experimentation. The respondents found reliance heavily on prior experiences, indicating that past successes inform current drought-management strategies. Their decision-making was further guided by an internal assessment of household assets and capacity, as reflected in the preference to cope independently and avoid uncertain options that may strain limited resources.
In addition, social comparison functioned as a cognitive inquiry, with the respondent observing others’ behaviors to validate their own choices and reduce perceived risk. These observations were filtered through individual cognition and experience, enabling them to interpret what worked and why. Due to the fact that mentally simulating possible outcomes based on imitating their peers, they can reduce uncertainty and increase adaptation to drought that aligned with their capacities and perceived risks.
On the one hand, their self-regulation can be understood as the underlying intention behind their adaptation. On the other hand, when self-regulation is heavily influenced by community perceptions, it significantly shapes their degree of adaptation. For example, when only a few individuals in a community take proactive steps, while the majority perceive drought as an unavoidable and unsolvable condition, a shared sense of resignation is reinforced. This can be witnessed by the following discussion:
“We usually watch what our neighbors do. If someone tries something new and it works, maybe we’ll follow. But most of the time, no one’s doing much differently, so we just stick to what we know. I’ve been farming for over 30 years, I know how the land behaves.”
(K10, Group 2)
As one farmer explained, “We usually watch what our neighbors do... if others aren’t changing, maybe I don’t need to either.” This mutual reinforcement of inaction creates a cycle of low responsiveness, in which limited risk awareness and a diminished sense of community lead to minimal efforts to seek out or implement drought adaptation measures. Especially, at the individual level, the farmer’s reliance on long-term experience (“I’ve been farming for over 30 years, I know how the land behaves”) reflects strong confidence in tacit knowledge accumulated over time.
Additionally, at the collective level, decision-making was strongly shaped by observational learning and social norms. Farmers monitored their neighbors’ actions to assess risk, treating peer behavior as a proxy for the viability of innovation. However, when few individuals experimented, the absence of visible change normalized inaction. This created a mutual reinforcement of conservative behavior, in which waiting for others to move first became a rational yet collectively constraining choice. The consequence was then a form of social inertia, whereby adaptation was delayed not solely due to a lack of awareness, but because individual decisions were embedded within shared expectations and norms.
Obviously, this dynamic produces a self-perpetuating cycle of low responsiveness. Limited experimentation reduces opportunities for social learning, which in turn weakens risk perception and diminishes motivation to actively seek adaptation measures. The reference to “getting by” rather than planning ahead suggests a coping-oriented mindset focused on immediate survival rather than long-term resilience.
Overall, the group discussion revealed a coping-oriented mindset focused on short-term survival rather than proactive adaptation. Uncertainty, resource constraints, and potential losses discourage experimentation, leading to incremental adjustments only when conditions become unavoidable. This pattern suggests that adaptation decisions are not solely technical but are deeply embedded in cognitive processes, social learning dynamics, and perceptions of risk and resilience within the community.
Theme 2: Planned behavioral and selection of coping strategies
Behavioral and intention nexus plays a critical and deeply rooted role in processing older farmers’ responses to drought. As illustrated in Fig 6, participants’ decisions were not made in isolation but are strongly guided by ingrained community values and collective expectations. These values, coupled with behavioral beliefs and normative beliefs, heavily influence how they perceive and respond to selection of coping strategies.
The figure illustrates how behavioral and normative beliefs shape the selection of coping strategies. Decisions among older farmers are influenced not only by individual evaluations but also by perceived social expectations, including normative reference and motivative conformity within the community. The inclusion of solidarity further underlines the role of collective orientation in reinforcing and guiding the adoption of adaptive strategies.
In terms of behavioral belief, their decisions are directly influenced by expected outcomes of coping strategies, framed as cost-benefit comparisons. More often, they selected the strategies through a lens of cost-benefit immediacy rather than long-term gains. When the perceived costs, for example, in terms of physical effort, financial burden, or cognitive load, were high, they were more likely to adopt low-effort, risk-averse strategies, such as traditional practices.
“At our age, adopting new innovations is not easy. Trying a new coping method requires money, time, and labor, with no guarantee that it will succeed. If it fails, I lose not only the investment but also an entire farming season that cannot be recovered.
(K7, Group 2)
The practices I already use may not bring high returns, but I am familiar with their limits and risks.”
(K11, Group 2)
This expression demonstrated the older farmers’ reluctance to adopt drought-coping innovations reflects constrained intentions shaped by attitudes, perceived control, and social norms. Their attitudes are predominantly risk-averse, as the high costs and uncertain outcomes of new practices outweigh potential benefits, particularly given the irreversibility of losing a farming season. Perceived behavioral control is low due to age-related limitations and financial constraints, reducing confidence in successful implementation. As a result, these factors weaken their adoption intentions and sustain conservative coping strategies.
Another influential factor is a normative belief, which establishes agricultural norms in their societies. The participants said they often emulated reference groups (e.g., successful peers or community leaders). When these figures adopted certain actions, others followed with a hope of achieving similar success. This collective orientation is shaped not only by personal benefit but by a commitment to a strong sense of solidarity, as expressed by one of the participants:
“When a successful farmer adopted something new, e.g., like a water-sharing system or a different planting method, many of us followed their lead because we trust their experience.”
(K3, Group 1)
“Sometime, I felt uncertain on my own, but when the community moved together, I join in. This was not just for personal gain, but to stay connected and show that I belong.”
(K15, Group 3)
In addition, this statement reflects motivational conformity grounded in a strong sense of solidarity. Although the individual initially experiences uncertainty, collective action reduces perceived risk and provides social reassurance. Participation is driven primarily by the desire to maintain social ties, avoid isolation, and affirm group membership. Acting alongside others signals loyalty and mutual commitment, thereby reinforcing social cohesion within the community. On the one hand, conformity functions as a relational strategy. On the other hand, the fear of social exclusion or being seen as non-cooperative can be a powerful deterrent to deviant behavior even when such deviation may offer personal advantages.
Theme 3: Threat-protective behavior in adaptation strategy selection
Another essential adaptation pattern shown by these participants is the pattern of self-protection, which reflects both instinctive self-interest and complex cognitive responses to climatic stress. When confronted with drought, these participants tended to respond in two distinct ways as illustrated in Fig 7.
This figure illustrates how the degree of perceived threats and the cost of strategy selection shape individuals’ cognitive evaluation through threat comparison, which in turn informs self-protective responses. This process highlights that adaptation decisions are developed from the complex interaction between perceived risk severity and the perceived feasibility or cost of available strategies.
The first was a defence threat response, where they actively engage in safeguarding their crop yields, seeking to enhance their agricultural skills, and implementing measures to improve their resilience. This approach reflects proactive adaptation and a desire to maintain control over their livelihoods. Conversely, the second was an avoidance response, characterized by a more passive stance such as accepting drought as a certain part of farming, rejecting available mitigation measures, or placing hope in improved outcomes in future planting cycles, as expressed by the participants:
“Most of us have been farming the same way for decades. When the drought comes, we just wait it out; what else can we do? Everyone around here does the same.”
(K6, Group 1)
“We’ve seen dry seasons before, and we’ve always gotten through them somehow.”
(K8, Group 2)
“Changing how we farm feels risky at our age, and to be honest, I don’t see others making changes either. So, we just carry on, hoping the rain will return next year. It’s not that we don’t care; it’s just hard to believe anything we do will really make a difference.”
(K13, Group 3)
All these expressions illustrate a dominant avoidance-based threat response rather than a proactive defence response. Across all groups, drought is framed as a familiar and inevitable condition of farming, leading those farmers to rely on endurance, experience, and hope rather than active adaptation. Statements such as “we just wait it out” and “we’ve always gotten through them somehow” reflect a normalization of risk, where past survival substitutes for deliberate mitigation. This acceptance reduces the perceived urgency to seek new skills or implement resilience-enhancing measures.
Moreover, reluctance to change farming practices, generally among older farmers, was reinforced by uncertainty, perceived inefficacy, and social conformity. In Group 3, the absence of observable change among peers further reinforced inaction, while hope for future rainfall replaced intentional control. Although these farmers expressed concern (“it’s not that we don’t care”), their responses indicated a passive coping strategy characterized by waiting, hoping, and maintaining established routines. In contrast, elements of a defence threat response such as actively safeguarding yields, improving skills, or adopting adaptive measures were notably absent. Rather than seeking to enhance resilience, farmers relinquished agency by viewing drought as beyond their influence. This pattern underscores how avoidance responses, shaped by experience, age, and collective norms, can delay adaptation even in the face of recurrent environmental threats.
Threat comparisons are of view as a critical role in shaping level of their self-protective responses. As discussed, they emphasized the tangible and intangible costs such as labor demands, time investment, and effort required for participation, against the perceived benefits, including direct compensation, access to resources, or skill development offered through government programs. Their evaluations were not made lightly; they were grounded in a pragmatic understanding of personal capacity and past outcomes. As a result, if the perceived benefits do not clearly outweigh the costs, they were more likely to opt for low-effort or familiar coping methods.
Corresponding themes and summary
In Table 4, all participant codes (K1–K18) represent key arguments derived from individual narratives, with each case contributing evidence aligned with the thematic domains of risk perception and information, norms and intentions, and the decision-making process.
The arguments indicate that drought coping among older farmers is shaped by an interaction of experiential knowledge, social context, and iterative decision-making. At Theme 1, risk perception is not formed solely through formal information but emerges from accumulated experience, peer exchange, and close observation of environmental change (e.g., K3, K4, K5, K6). This blended knowledge base enables farmers to interpret drought as a gradual and manageable risk rather than a singular shock.
At Theme 2, norms and intentions are socially embedded. Community expectations, shared practices, and observational learning create a normative environment that both encourages and legitimizes adaptive behavior (e.g., K2, K7, K9, K15). Intentions to adopt drought-resilient strategies are therefore not purely individual choices but are reinforced through collective orientation and a sense of solidarity.
At Theme 3, the decision-making process is adaptive and incremental. Farmers rarely rely on fixed plans; instead, they continuously adjust planting, water management, and input use in response to evolving conditions (e.g., K1, K10, K16). Consequently, Decisions are guided by practical experience, perceived effectiveness of past actions, and the need to balance risk across the farming cycle.
In summary, the discussion concludes that drought adaptation among older farmers is not driven by single influences but by the complex interaction of knowledge, social influence, and flexible decision-making. Processes such as knowledge exchange, the development of community-based norms that guide adaptation, and the evaluation of risks in relation to farmers’ context-specific, experience-based capacities play critical roles in shaping their coping strategies.
Discussion
Three adaptation patterns of older farmers coping with drought
First, self-recognition plays a crucial role in the adaptability of ageing farmers, whose long-standing reliance on traditional agricultural practices often leads to the belief that their methods are best suited to local conditions. However, this mindset may hinder awareness of shifting environmental challenges and reduce openness to innovation. Adaptation among older farmers typically occurs through observation, imitation, comparison, and self-regulation which are core elements of social cognition framework, which posits that older farmers form knowledge and behaviors based on social interactions and environmental cues [49–51]. For example, in Ghana, the decisions of experienced farmers strongly influence community norms, leading to widespread reinforcement of traditional practices despite climate variability [63]. In Vietnam’s Mekong Delta, transformative social learning has been recognized as essential for climate adaptation, though it must be supported by resources such as training and financial aid to be effective [64].
Second, social-cultural beliefs are an influential factor in shaping older farmers’ behavior and decisions when selecting drought coping strategies. As suggested by the Theory of Planned Behavior (TPB) [65], behavior is influenced by intention. In this study, behavioral beliefs are shaped by expectations of the outcomes of participating in programs, particularly in terms of cost-effectiveness. When benefits appear favorable, adoption among older farmers become more likely. For example, a study in Bangladesh’s lower Teesta basin found that older farmers were willing to adopt irrigation adaptations when perceived as cost-effective [66]. Regarding a normative belief, the study’s findings show that the participated older farmers tend to look to their immediate social circle-such as successful older farmers, community leaders, and local institutions-for cues on acceptable and effective responses to drought. This follows the concept of normative values among agricultural community, when the prevailing norm within the reference groups favor traditional practices and resists change, individual farmers are motivated to conform in order to maintain social cohesion, avoid conflict, and uphold their identity within the community [67–69].
Lastly, self-protective behavior in older farmers during drought reflects a spectrum of cognitive and emotional coping strategies, ranging from proactive adaptation to passive avoidance. On one end, farmers adopt problem-focused coping by engaging in direct actions, such as protecting crops, enhancing agricultural skills, or implementing resilience-building practices to maintain control over their livelihoods. These behaviors align with the concept of self-efficacy, where confidence in one’s abilities motivates adaptive actions [54,55], and are often reinforced by deep-rooted farming experience and identity [70]. Especially, emotion-focused coping among older farmers during drought is often influenced by factors such as cognitive fatigue, low perceived efficacy, and social conformity. These elements can lead to the downplaying of climate risks and resistance to change, despite increased vulnerability. Such avoidance behaviors could be further influenced by psychological factors such as fatalism, cognitive dissonance, and learned helplessness that make them inactive even when confronted with significant threats. These findings align with existing studies; for instance, in rural Australia, older farmers have been found to exhibit self-reliance, which serve as barriers to seeking help and adopting adaptive strategies [71]. This impassive attitude is linked to maintaining social image and traditional roles, often resulting in avoidance behaviors rather than proactive adaptation.
Adaptive governance is essential for strengthening drought adaptability
To better align with the study objective of informing policy, this study posits that developing adaptive governance holds significant potential. This approach emphasizes the importance of collaboration, knowledge co-production, and institutional responsiveness to local contexts [72]. At its core, adaptive governance integrates decentralized decision making, stakeholder participation, and knowledge co-production to ensure that responses remain context specific and responsive. It relies on iterative learning processes, where experiences and outcomes inform future actions, thereby improving effectiveness over time. In the context of drought, adaptive governance facilitates systems to move beyond rigid, top down control toward dynamic and inclusive management, aligning institutional responses with human behavior, social norms, and environmental variability to enhance long term resilience and adaptability [73].
Because adaptation decisions emerge from the interaction between internal cognitive processes and socio-cultural conditions, agricultural governance must move beyond static [74,75], top–down interventions and instead operate as flexible [76], learning-oriented frameworks that respond to these dynamics [77]. Within this paradigm, adaptive governance strengthens cognitive capacities by embedding continuous learning and systemic feedback into policy design [78]. Enabling conditions (e.g., participatory extension systems, peer-to-peer knowledge exchange, and locally grounded drought literacy) function to reinforce feedback loops and build adaptive capacity in complex and uncertain environments. In this context, meta-governance arrangements that create space for collaborative experimentation and learning are critical, as they institutionalize feedback processes [78]. Collectively, these mechanisms enhance farmers’ self-perception, risk awareness, and self-efficacy, enabling older farmers to reassess their adaptive capacity under evolving climate conditions.
Adaptive governance addresses socio-cultural constraints by aligning interventions with existing norms, values, and community structures. Through the co-production of knowledge and inclusive decision-making, it reduces the likelihood that adaptation strategies are perceived as externally imposed or socially disruptive. This is particularly important for older farmers, who often rely on traditional practices and exhibit greater risk aversion, limiting the uptake of innovations perceived as disruptive or top–down [22,79]. Empirical evidence from East Africa, South Asia, and Ethiopia indicates that older or older-headed households are more likely to adopt low-risk coping strategies (e.g., reducing consumption or drawing on savings) rather than implementing new agricultural practices [22,80]. In contrast, when adaptation builds on local knowledge, leverages social networks, and promotes group-based learning through farmer associations and social capital, uptake is higher and more consistent with farmers’ identities and community ties [81,82].
Adaptive governance that integrates human and cultural dimensions has been increasingly shown to be effective in drought management, globally. For example, Adaptive governance mechanisms that institutionalize policy through problem centered and learning oriented approaches, such as providing experiential learning opportunities, can help older farmers overcome skepticism and cognitive fatigue by linking new strategies to familiar contexts and increasing problem learnings, thereby strengthening both self-efficacy and perceived drought relevance [83]. Engaging relevant stakeholders such as community leaders, who possess strong social influence and knowledge of local customs; agricultural extension officers, who are formally trained in agronomy and skilled in knowledge transfer; local cooperatives, experienced in collective resource management and market access; and farmer associations, which facilitate peer-to-peer learning and advocacy, can strengthen adaptive governance strategies by reducing social resistance to change. Our findings, consistent with previous studies. This suggestion is consistent with previous studies [84] show that social norms and peer modeling play a significant role in shaping farmers’ risk perceptions and adaptation decisions.
Experiences from other countries support our view. For instance, in India, the National Initiative on Climate Resilient Agriculture (NICRA) integrated both hard and soft infrastructure approaches by combining drought-tolerant technologies with village-level capacity-building. As reported by CRIDA [85], local climate risk management committees were formed to encourage inclusive decision-making and strengthen trust between farmers and institutions. This approach led to greater participation among older, particularly when local champions (respected peers or leaders) were actively engaged in knowledge dissemination and adaptation planning. Similarly, in Vietnam, the Climate-Smart Agriculture Program also provides a supportive example. Its interventions reflected the same dynamics illustrated in our framework: farmers’ self-perception which was driven by drought literacy, risk awareness, and self-directed learning, which was strengthened through targeted training, while socio-cultural beliefs were engaged through community norms, peer influence, and collective farm duties. By addressing these cognitive and cultural dimensions alongside practical concerns such as financial burdens, required efforts, and investment risks, the program improved farmers’ decision-making processes and increased adoption of adaptive practices. These approaches helped reduce skepticism and resistance among older farmers by integrating traditional practices with innovative, climate-resilient techniques, thereby enabling experiential learning and collective problem-solving [86].
Such examples demonstrate that transformative policy frameworks, when grounded in social realities and inclusive processes, can effectively mobilize behavioral change and adaptive action even among groups that are typically resistant due to age, past experience, or strong self-reliance.
A model for strengthening drought resilience in ageing agricultural ecosystems
In Fig 8, based on the aforementioned discussion, the study illustrates model for developing drought resiliency to older farmers. pathway through which adaptive governance shapes drought adaptability by linking institutional processes with individual level behavioral responses. At the upstream level, adaptive governance, characterized by policy flexibility and decentralization, operates through participatory and community-based processes that engage local actors, including community leaders, farmer organizations, and academic or civil society institutions. These interactions facilitate knowledge co production and experiential learning, allowing stakeholders to engage in practical activities and generate context specific insights. Such processes are further supported by key intervening conditions, including the quality and relevance of information, as well as institutional trust and legitimacy, which together determine how effectively governance mechanisms are translated into practice.
Adaptive governance operates through participatory and learning based processes, mediated by information quality and institutional trust, to activate psychosocial factors including risk perception, self-efficacy, and social norms. Shaped by age related characteristics, these processes influence coping and adaptation strategies, contributing to resilience and reduced vulnerability, with feedback loops informing continuous policy refinement.
At the individual level, adaptive governance must ensure that stakeholder engagement in practical activities activates key psychosocial processes among older farmers, particularly by strengthening risk perception, self-efficacy, and community-based social reference. Older farmers typically access information through fewer channels and peer networks [87], contributing to higher perceived constraints and lower levels of adaptation. Evidence indicates that farmer-to-farmer communication and village-level interactions play a more decisive role in shaping drought risk appraisal than formal government messaging. In this context, engagement through local networks, extension services, and communication platforms influences how farmers perceive risk, assess their capacity to act, and interpret prevailing social norms. Well-designed, locally grounded engagement can therefore activate critical psychosocial drivers of adaptation, although older farmers often require targeted support to overcome persistent information and capacity gaps.
Furthermore, the stakeholder engagement must ensure that information is trusted, context-specific, and embedded within supportive institutional arrangements. Hands-on, socially embedded activities, which are rooted in experiential and place-based knowledge, are more likely to motivate behavioral change. Farmers tend to value local knowledge for its practical relevance, underscoring the need to integrate it with formal scientific expertise. Trust is also more readily placed in peer networks than in distant authorities; accordingly, communication strategies are most effective when they feature credible farmer role models and narrative forms aligned with local style.
More importantly, this model emphasizes a feedback loop in which local experiences and outcomes are fed back into knowledge co-production (via research input) and policy processes (via livelihood outcome). This enables iterative learning and continuous refinement of governance strategies. This dynamic interaction highlights that drought adaptability is not solely a function of environmental exposure or resource availability, but emerges from the alignment between institutional flexibility, social learning, and human cognition.
Conclusion
This study stresses the importance of integrating adaptation process to develop a more comprehensive policy development and adaptive governance to enhance drought resilience among older farmers. The findings reveal that while older farmers possess extensive experience, their coping responses are shaped by emotion-focused strategies, social conformity, and perceptions of self-efficacy, which links beliefs and perceived control to behavioral intentions, and psychological frameworks on coping, including cognitive appraisal and learned helplessness.
A robust policy recommendation for addressing drought resilience should integrate the principles of adaptive governance within the broader socio-ecological system as discussed in previous section. Policymakers should focus on decentralizing decision-making processes and empowering local institutions to facilitate more responsive, context-specific drought management. This involves creating inclusive platforms where farmers, local officials, researchers, and civil society actors can collaborate to identify risks and design appropriate responses. In socio-ecological terms, this means recognizing and leveraging the interconnectedness of human behavior, institutional dynamics, and ecological processes.
Lastly, the study is limited by its focus on a single drought-prone region, which may not fully represent diverse agro-ecological or socio-cultural contexts across the country. The reliance on qualitative data from small focus group discussions, although rich in context, may also limit generalizability. Furthermore, generational dynamics and the willingness of both younger and older farmers to collaborate were not empirically tested in this phase. Future research should consider these limitations as a basis for developing more comprehensive research proposals. In addition, statistical analysis of drought impacts or coping strategy adoption rates among older farmers may be also considered.
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