Using a Neural Network Analysis to Assess Stressors in the Farming Community

Abstract

In the 1980s and 1990s, with decreasing numbers of full-time farmers and adverse economic conditions, chronic stress was common in farmers, and remains so today. A neural network was implemented to conduct an in-depth analysis of stress risk factors. Two Colorado farm samples (1992–1997) were combined (n = 1501) and divided into training and test samples. The outcome, stress, was measured using seven stress-related items from the Center for Epidemiologic Studies-Depression Scale. The initial model contained 32 predictors. Mean squared error and model fit parameters were used to identify the best fitting model in the training data. Upon testing for reproducibility, the test data mirrored the training data results with 20 predictors. The results highlight the importance of health, debt, and pesticide-related illness in increasing the risk of stress. Farmers whose primary occupation was farming had lower stress levels than those who worked off the farm. Neural networks reflect how the brain processes signals from its environment and algorithms allow the neurons “to learn”. This approach handled correlated data and gave greater insight into stress than previous approaches. It revealed how important providing health care access and reducing farm injuries are to reducing farm stress.

Well-being at work and Finnish dairy farmers─from job demands and loneliness towards burnout

“…The prevalence of chronic diseases appears to be more common among farm entrepreneurs than among the working population in Finland ( Perkiö-Mäkelä et al, 2016 ). Similarly, Beseler and Stallones (2020) found that health, the economic situation, and disease related to pesticides were key elements increasing stress among Colorado farmers. In Finland, a nationally representative population sample (n = 5,834) measured the work ability index among salaried workers, entrepreneurs with and without personnel, and farmers: the score for farmers was lower (37.9) than for the other groups and the whole sample on average (40.0) ( Saarni et al, 2008 ).…”

Injury, Musculoskeletal Symptoms, and Stress as a Function of Aging in Agricultural Operators in the Central United States

“…In our surveillance data, 49.8% of principal operators worked 75% or more on the farm/ranch but in second and third operators combined only 16% worked more than 75% on the farm/ranch. Younger farmers are more likely to work off the farm (USDA, 2017), although the added time pressure might be expected to increase the risk of injury by increasing stress (Beseler & Stallones, 2020). Older farmers may have greater assistance from family members as they transition to retirement.…”