































   Advancements in Agricultural Development 
  Volume 5, Issue 1, 2024 
  agdevresearch.org 

 

1. D. Barry Croom, Professor, University of Georgia, 2360 Rainwater Road, Tifton, GA 31793, dbcroom@uga.edu,  

 https://orcid.org/0000-0001-7710-5212  
2. Anna M. Scheyett, Professor, University of Georgia, Four Towers Room 143, 405 College Station Road, Athens, GA 30602, 

amscheye@uga.edu,  https://orcid.org/0000-0002-3459-3794  
3. Kaitlin Brianna Yoo, Project Management and Communication Graduate Student Researcher, University of Georgia, 321 

Hoke Smith Annex , 1225 Lumpkin  Street, Athens, GA 30602, Brianna.yoo@uga.edu,   

 https://orcid.org/0009-0001-4705-4837 
5 

 
 

Factors That Contribute to Extraordinary Stress in Farmers 
 

D. B. Croom1, A. M. Scheyett2, K. B. Yoo3 

 
 

Article History 
Received: September 27, 2023 
Accepted: February 16, 2024 
Published: March 18, 2024 
 
 
Keywords 
agricultural communities; stressors; 
Delphi technique; Cumulative Stress 
Model; rural stress; farming-related 
stress 
  

Abstract 
This research aimed to identify the conditions leading to stress in farmers. 
Rural and agricultural communities face heightened stress levels due to 
multiple factors, with cumulative negative consequences, as proposed by 
the Cumulative Stress Model (CSM). This study engaged a panel of 
experts with lived and professional experiences in an intentional and 
iterative Delphi process to identify stressors in agricultural communities. 
Employing the three-round Delphi technique by Turoff and Linstone 
(1975), this study integrated diverse perspectives and expertise while 
minimizing biases arising from group discussions or face-to-face 
interactions. The findings indicate that most stressors, such as farm 
operating costs, commodity prices, weather, labor shortages, 
crop/livestock diseases, economic fluctuations, and work-related 
accidents, were beyond individual control. These stressors can lead to a 
sense of powerlessness, particularly challenging in communities valuing 
independence and self-reliance. Furthermore, farm operating costs, 
commodity prices, weather, labor shortages, and crop/livestock diseases 
ranked among the top stressors. Debts, loans, and work-related accidents 
also contributed to stress. Notably, farm operating costs, commodity 
prices, and weather emerged as the three most highly rated stressors 
across all categories—lack of control, sudden fluctuations, and farming-
related stressors. Addressing these stressors is paramount for monitoring 
and improving the well-being of agricultural communities. 

mailto:dbcroom@uga.edu
https://orcid.org/0000-0001-7710-5212
mailto:amscheye@uga.edu
https://orcid.org/0000-0002-3459-3794
mailto:Brianna.yoo@uga.edu


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Introduction and Problem Statement 
 
Farmers and agricultural workers face disproportionately high rates of mental health 
challenges, including suicide, depression, anxiety, and psychological distress (Cuthbertson et al., 
2021; Pratt, 2022). These challenges stem primarily from uncontrollable factors such as 
weather, input costs, commodity prices, labor shortages, and government policies 
(Cuthbertson, 2021), compounded by the physical hazards inherent in farm work. Agriculture 
ranks as one of the most hazardous professions in the United States, with a constant risk of 
fatal and nonfatal injuries (The National Institute for Occupational Safety and Health (NIOSH)). 
Moreover, the unique aspect of farming is that farm families reside and work within the 
confines of the agricultural operation, increasing the risk of injury to adolescent children when 
farmers are under significant stress (Stoneman & Jinnah, 2015). Adding to this complexity is the 
prevailing mental health stigma within agricultural communities, where values of stoicism, 
individualism, and reluctance to seek help contribute to underreporting stress and emotional 
distress (Cuthbertson et al., 2021). Consequently, individuals and families in these communities 
grapple with multiple stressors in an environment that discourages open discussion and 
support for these issues. 

Statement of the Problem 
Addressing stress-induced illnesses in the agricultural sector necessitates more than 
symptomatic treatment based on a general understanding of the causes of stress. To effectively 
assist Georgia armers in managing stress, preventing suicide, and treating stress-related 
illnesses, healthcare professionals and farmer support organizations must pinpoint the 
underlying sources of stress experienced by these farmers. 

Theoretical and Conceptual Framework 
 
Stress is the physical, emotional, or psychological strain caused by difficult circumstances 
(McEwen & Sapolsky, 2006). Chronic stress can be harmful because the body constantly 
produces higher stress hormones without allowing recovery time (Cohen et al., 2007; McEwen 
& Sapolsky, 2006); exposure to chronic stress is more likely to result in permanent changes in a 
person's emotional, physiological, and behavioral responses (Cohen et al., 2007). Over time, 
chronic stress can cause significant damage to a person's body and psyche. Of particular impact 
is the level of empowerment and social support experienced by persons under stress (Rice, 
2012). The feeling of powerlessness (such as helplessness in the face of adverse weather 
events) and the perceived lack of social support exacerbate stress and its impact (Israel et al., 
1994). 

The Cumulative Stress Model (CSM) developed by Israel et al. (1994) is a theoretical framework 
that describes how chronic stressors, such as poverty, discrimination, violence, and social 
disadvantage, can impact individuals such as farmers. The model suggests that exposure to 
multiple stressors can lead to a "stress pile-up" effect, where stressors accumulate and interact 
to create a cascade of negative consequences for farmers. 

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The CSM combines internal and external stress factors into one model. In considering an 
individual's stress experience, CSM combines environmental factors with the internal factors of 
powerlessness, lack of social support, and preexisting physical and mental health conditions. 
Israel et al. (1994) organized these factors into five major elements: (a) the psycho-
environmental conditions that lead to stress; (b) the perception of that stress by the individual 
and community; (c) short-term responses to the stressor; (d)  long-term impacts of the stress 
on health and mental health; and (e) variables that mitigate or alleviate stress include a 
supportive social network, secure socioeconomic status, and capacity for autonomous decision-
making (Israel et al., 1994). In farming, the accumulation of stressors may lead to self-harm and 
suicide (Bjornestad et al., 2021). 

Purpose 

The purpose of this study is threefold: (a) to identify the stressors and psycho-environmental 
conditions leading to stress among farmers in Georgia, and (b) to assess the seriousness of 
these stressors in the lives of farmers. This research serves as the initial step toward developing 
Extension-based interventions aimed at addressing the most detrimental stressors identified, 
enhancing social support, and bolstering community resources to mitigate the adverse effects 
of chronic stress on farmers in Georgia. 

Methods 
 
We used a three-round Delphi technique that Turoff and Linstone (1975) proposed to conduct 
this study. One of the strengths of the Delphi method is that it allows for the integration of 
diverse perspectives and expertise while minimizing the potential biases that can arise from 
group discussions or face-to-face interactions.  

Participants 
The panel of experts consisted of a purposive sample of individuals in the agricultural industry 
in Georgia. We used a purposive sampling technique to select participants with the requisite 
expertise and knowledge to provide informed opinions and recommendations on the topic of 
interest. Purposive sampling further allowed us to recruit a diverse and well-rounded group of 
experts with varying perspectives, backgrounds, and experiences related to the research 
question. Delphi studies often address complex or specialized topics, making it essential to 
involve experts most relevant to the research question.  

Table 1 lists the panelists and their areas of expertise in the industry. To increase accuracy and 
reliability, we chose  23 panelists. Dalkey (2002), as referenced by Warner and Harder (2020), 
established that a panel of more than 13 experts yields a Cronbach's Alpha over .90. Of our 23 
panelists, nine were male, and 14 were female, 21 were White, and two were Black. It should 
be noted that most of our panelists lived in rural counties, as defined by the United States 
Census Bureau (Ratcliffe et al., 2016). 

 

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Table 1 
  
Number of panelists and their leadership position or area of expertise 

Number of Panelists Leadership Position or Area of Expertise 
2 Executive leaders in a commodity association 
4 Rural Extension agents 
2 Agricultural Extension agents 
4 Farmers 
2 Leaders in a non-profit farm organization 
4 Rural stress researchers at a major university 
1 Representative in an agricultural finance agency 
1 Agent in the USDA Farm Service Agency 
1 Mental health care professional 
2 Rural disaster response provider 

23 Total panelists 
 
We sent an initial invitation to participate to 27 prospective panelists in the fall of 2022. From 
this initial list, 23 (85%) agreed to serve as expert panelists. We sent the first round of the 
survey by email in December 2022. The questionnaire asked the panel to respond to a list of 24 
variables based on the literature by rating how much stress each caused for agricultural 
communities. Research studies that drove the questionnaire's development pointed to the 
pressing need to address elevated stress levels in rural communities, particularly in regions such 
as rural Georgia, where residents encounter unique challenges. These challenges encompass 
financial hardships, limited healthcare access, and a scarcity of job opportunities, all 
contributing to increased stress (Beehler et al., 2021; Mohatt et al., 2021). One of the primary 
sources of stress in rural areas of Georgia is the pervasive financial hardship experienced by 
many residents. With poverty rates surpassing national averages, individuals and families 
frequently struggle to make ends meet, leading to difficulties paying bills and food insecurity 
(Osinubi & Escalante, 2013). 

Additionally, limited access to healthcare and mental health services compounds the problem, 
as medically underserved rural areas lack sufficient healthcare providers and facilities, leaving 
physical and mental health issues untreated (Kutek et al., 2011; Osgood & Pink, 2022; Scheyett 
et al., 2023). Furthermore, the dearth of job opportunities in rural Georgia, stemming from the 
decline of traditional industries, contributes to feelings of hopelessness and high stress levels 
(Erwin, 2017; Myers, 2019). Finally, stressors of direct relevance to agriculture, such as weather, 
input costs, commodity prices, and labor availability, were considered, given the importance of 
agriculture to the economy of rural communities in Georgia (Smith & Maples, 2023). 

We also encouraged panelists to add variables to this list based on their experiences. We placed 
the items in a Likert-type instrument with responses ranging from 1(no stress) to 4 (severe 
stress). We utilized a four-point scale because it may be easier for respondents to navigate. 
With fewer response options, the respondents are forced, in a sense, to make a decisive choice. 

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Twenty-three (100%) panel members from round one replied to the first round of the survey in 
mid-December 2022. Following guidelines described by Warner and Harder (2020), we 
established a priori that consensus on items in the first round was achieved when 67% of 
panelists indicated that the item was a moderate or severe stressor. In round two, sent to 
panelists on January 10, 2023, we provided panelists with a list of the factors that had attained 
67% or more consensus and asked them if they agreed that these factors were 
moderate/severe stressors (1 = strongly disagree, 4 = strongly agree) and a priori agreed that 
those where 67% or more of panels agreed these were moderate/severe stressors would be 
retained, and sent on to round three. In round three, sent to panelists on January 30, 2023, we 
asked panelists how important it was to retain each factor as a significant stressor in 
agricultural communities (1=not at all important, 4=very important); we also established a 
priori the consensus cutoff at 67%.  

Limitations 
The Delphi method relies on subjective expert opinions, so findings may not be universally 
applicable. In addition, our participants were predominantly White and female, so responses 
may not fully represent the community. Despite these limitations, the study provides valuable 
insights and a basis for further research and targeted interventions, with the need to interpret 
results in light of these constraints and address them in future studies. 

Findings  
 
Fourteen of the original 24 factors were rated as moderate/severe stressors for agricultural 
communities by 67% or more of the panelists in the first round of responses. In round two, six 
factors were retained at the 67% consensus level, and the remaining eight factors that attained 
67% consensus were used in round three. Seven of these eight factors attained 67% consensus 
or higher.  

Results of the three rounds of the Delphi process, including the average score for each factor 
and the number and percentage of panelists who selected each variable at either of the two 
highest Likert points (3 or 4), are shown in Table 2. 

 

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Table 2 

Delphi process stress factor results 
Stress Factors Round 1 (n=23) Round 2 (n=21) Round 3 (n=23) Final  

Decision  M # 3 or 4 % 3  or 4 M # 3 or 4 % 3  or 4 M # 3 or 4 % 3 or 4 
Weather 3.26 22 96% 3.55 19 90% Retained from round 2 Retain 
Commodity prices 3.52 23 100% 3.65 20 95% Retained from round 2 Retain 
Farm operating costs 3.52 20 87% 3.85 20 95% Retained from round 2 Retain 
Crop/livestock disease 3.00 16 70% 3.15 17 81% Retained from round 2 Retain 
Farm-related pests 3.00 13 57%     Discard 
Lack of available labor 3.35 20 87% 3.50 20 95% Retained from round 2 Retain 
Poor health 2.87 14 61%     Discard 
Lack of access to healthcare 2.90 17 74% 2.95 15 71% 3.17 18 78% Retain 
Lack of health insurance 2.96 16 70% 3.00 16 76% 3.13 19 83% Retain 
High rates of COVID-19 2.13 8 35%       Discard 
Alcohol misuse 2.70 11 48%       Discard 
Opioid and other drug misuse 2.96 15 67% 3.00 16 76% 3.09 16 70% Retain 
Work-related accidents 2.87 16 70% 2.85 16 76% 3.09 17 74% Retain 
A high proportion of older adults in the 

community 
2.48 12 52% 

      
Discard 

Sudden changes to the local economy (e.g., 
a large employer shuts down) 

3.09 17 74% 3.01 16 76% 3.13 18 78% Retain 

Divorce 2.30 10 43%       Discard 
Debts and loans 3.35 19 83% 3.55 19 90% Retained from round 2 Retain 
Poverty 3.00 18 78% 2.85 14 67% 2.96 18 78% Retain 
High housing costs 3.09 16 70% 3.10 15 71% 2.82 13 57% Discard 
Low high school graduation rates 2.35 11 48%       Discard 
Poor quality housing 2.78 14 61%       Discard 
High unemployment 2.78 15 67% 2.75 13 62% 2.87 16 70% Retain 
High number of single-parent households 2.65 13 57%       Discard 
Lack of transportation 2.78 14 61%       Discard 

Note. The column labeled "# 3 or 4" refers to the number of participants who chose agreed (3) or strongly agreed (4) on the instrument. 

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The final list of factors selected by the panel as the most significant stressors in agricultural 
communities is summarized in Table 3. 

Table 3 
The final list of stressors, average final score, and round in which selected 

Stressor f 
Round 

Selected 
Farm operating costs 20 2 
Commodity prices 20 2 
Lack of available labor 20 2 
Weather 19 2 
Debts and loans 19 2 
Lack of health insurance 19 3 
Lack of access to healthcare 18 3 
Sudden changes to local economy (e.g., a large employer shuts down) 18 3 
Poverty 18 3 
Crop/livestock disease 17 2 
Work-related accidents 17 3 
Opioid and other drug misuse 16 3 
High unemployment 16 3 

 
Conclusions, Discussion, and Recommendations 

 
First, it is essential to note that over half of the stressors involve factors over which an 
individual would have little or no control—the costs associated with operating a farm, 
commodity prices, weather, lack of labor, crop/livestock disease, sudden changes to the local 
economy, and work-related accidents. Given that the impacts of stress are made worse by an 
accompanying sense of powerlessness and lack of self-efficacy (Braveman et al., 2018; Scheyett 
et al., 2019), it is essential to recognize the particular toxicity of stressors over which an 
individual can have little impact. This may be difficult for farmers individuals in agricultural 
communities, where values such as independence, autonomy, and "pull yourself up by your 
bootstraps" are held dear (Scheyett et al., 2019). 

All but one (labor) of these lack-of-control stressors identified by the panel were also factors 
where sudden fluctuations or changes in situation are possible—sudden changes in farm costs, 
commodity prices fluctuations, weather events such as hail storms or tornadoes, the sudden 
appearance of diseases such as corn rust or avian influenza in crops or animals, sudden changes 
in local economies, and work-related accidents.  

Five factors directly related to farming were rated in the top half of the stressors list —farm 
operating costs, commodity prices, weather, lack of available labor, and crop/livestock disease. 
One could arguably add debts and loans to this list since farmers may carry debt from year to 
year and work-related accidents, given the high rates of accidents associated with farming. 

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Looking at the list generated by the panel, it is striking that three stressors -- farm operating 
costs, commodity prices, and weather -- were most highly rated across all three categories. As 
Waldman et al. (2021) and Yazd et al. (2019) suggest, when the negative attributes of these 
three factors are present, such as high farm operating costs, low commodity prices, and severe 
weather, the stress levels of farmers may reach levels where self-harm and suicide are the only 
solutions that farmers perceive will alleviate the stress. Our findings suggest that attending to 
these three stressors, in particular, will be important in monitoring the well-being of farmers in 
Georgia. 

The agricultural industry in Georgia plays a significant role in the health and welfare of the 
citizens in this state (National Agricultural Statistics Service, 2019), and farming is a mainstay in 
the industry's role. This study reveals critical stressors for Georgia farmers that suggest the 
need for continual monitoring, perhaps by, but not limited to, state agencies and public health 
organizations. While we relied on studies conducted in other states to guide the development 
of this study, we hesitate to suggest that these previous studies have answered the question of 
what causes stress among farmers. As Conn (2023) notes, the characteristics and demographics 
of American farming communities are highly varied. For example, Jones and Field (2002) found 
no evidence of farmer suicide or self-harm in selected farming communities in Pennsylvania. 
Nevertheless, Bjornestad et al. (2021) found several factors that may contribute to farmer 
suicide and self-harm in midwestern states. The diverse geographic, economic, social, and 
demographic characteristics of American farmers call for further research to continually identify 
and rank the most significant stressors farmers face in their respective locations. Extension 
programs are tailor-made for local farmers' needs, so we recommend that Extension implement 
systematic mechanisms to identify high-risk stress factors experienced by farmers. Researchers 
at the University of Georgia are working to develop a model system designed to predict where 
stressful conditions are likely to appear within a specific geographic region by combining 
economic, agronomic, climate, social, health, and emergency services databases and analyzing 
the data. Once the model predicts the presence of stress in a local area, the Extension Disaster 
Education Network can be deployed to assist with mitigation and recovery efforts (Extension 
Disaster Education Network, 2019). Extension can also foster collaboration between local 
Extension services and community stakeholders, including counseling centers, churches, and 
public health programs, to develop and implement supportive programs and interventions. 
These collaborative efforts can offer essential mental health services, financial support, and 
social resources to help farmers cope with their unique challenges. Implementing these 
recommendations can enhance farmers' quality of life and mental health. 

Acknowledgements 
 
D.B. Croom and A.M. Scheyett conducted the formal analysis, investigation, and writing-original 
draft; K.B. Yoo conducted portions of the literature review, and assisted with the formal 
analysis, writing, review, and editing. 

 

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