Assessing Health and Safety Concerns and Psychological Stressors among Agricultural Workers in the U.S. Midwest

Recruitment of Row Crop Farmers into a Research Study to Assess Farm Hazards

Farmers are at an elevated risk for injuries and are, therefore, highly sought after for research studies. However, their participation in research studies is low. We examine how characteristics of the farmer, farm location, and timing of recruitment contact impact the probability that farmers will engage and participate in a study of injuries and related farm hazards. Study data were obtained from the Farm Safety Study conducted at the University of Iowa between June 2019 and March 2020. We used recruitment data from participants enrolled using Farm Journal magazine subscription lists. Multinomial logistic regression was used for predictive modeling. Predictor variables included the time of day and the farm season in which phone contact for study recruitment was attempted, as well as the rurality of the farm. Two models were created to characterize screening and participation of farmers in the study. Farm season and time of day of the last recruitment call increased the likelihood of farmers being screened for study participation and completing the study. Specifically, contacting farmers during the growing season and during the daytime, regardless of farm rurality, resulted in higher probabilities of participation. Studies of agricultural injury may be more efficiently conducted, with higher participation responses, when circumstances of the recruitment call are considered. This work serves as a starting place for much-needed methodological research to identify factors that increase participation of farmers and farm workers in research studies.

A cross-sectional study of alcohol, opioid use, and anxiety in agriculturally based occupations

PURPOSE

Although there are many studies that have examined substance use and mental health concerns in rural areas, there is a paucity of research related to the prevalence of substance use and mental well-being in agriculturally based occupations. This study aimed to determine the prevalence of alcohol and opioid misuse and anxiety among adults in agriculturally based occupations in the rural Midwest and to determine the risk factors for alcohol misuse.

METHODS

Data were collected via mailed surveys with 1,791 surveys returned. Participants completed the Alcohol Use Disorder Identification Test, the Drug Abuse Screening Test-1, the Generalized Anxiety Disorder Screener, and reported demographic data. Multivariable logistic regression was used to examine factors associated with alcohol misuse.

RESULTS

Younger age, male, not married, agriculturally based workers were significantly associated with alcohol misuse. For opioid use, the highest prevalence rate (10%) was found among direct agricultural workers who were not married and in the age group 19-39. The highest anxiety prevalence rate was found in participants aged 19-39 (15.5%) who also scored in the highest level of alcohol misuse with a prevalence rate of 27.9%.

CONCLUSIONS

Future research is suggested in the areas of gender identity and anxiety in agricultural populations and agriculturally based occupations as protective factors for opioid misuse.

Impact of different financial incentive structures on a web-based health survey: do timing and amount matter?

Aim

Financial incentives improve response to electronic health surveys, yet little is known about how unconditional incentives (guaranteed regardless of survey completion), conditional incentives, and various combinations of incentives influence response rates. We compared electronic health survey completion with two different financial incentive structures.

Methods

We invited women aged 30-64 years enrolled in a U.S. healthcare system and overdue for Pap screening to complete a web-based survey after receiving a mailed human papillomavirus (HPV) self-sampling kit in a pragmatic trial. HPV kit returners (n = 272) and non-returners (n = 1,083) were allocated to one of two different incentive structures: (1) Unconditional: $5 pre-incentive only (n = 653); (2) Combined: $2 pre-incentive plus $10 post-incentive conditional on completion (n = 702). Chi-square tests evaluated whether survey completion differed by incentive structure within kit return groups or was modified by kit return status. For each incentive-by-kit status group, the cost-per-survey response was calculated as: ([number invited*pre-incentive amount] + [number responses*post-incentive amount]) / number responses.

Results

Overall, survey response was higher in kit returners vs. kit non-returners (42.6% vs. 11.0%, P < 0.01), and survey response was higher in the combined (20.1%) vs. unconditional (14.4%) incentive group (P = 0.01). Kit return status did not modify the association between incentive type and survey response (P = 0.52). Among respondents, time to survey completion did not differ by incentive type among either kit returners or non-returners. Among returners, the cost-per-survey response was similar between groups ($13.57 unconditional; $14.15 combined); among non-returners, the cost was greater in the unconditional ($57.78) versus the combined ($25.22) group.

Conclusion

A combined incentive can be cost-effective for increasing survey response in health services research, particularly in hard-to-reach populations.

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

OBJECTIVES

Novel information about the relationships between farmers' job demands, lack of resource, burnout, and ill health is reported based on testing the so-called "health impairment process" of the Job Demands─Resources Model (JD-R) on a representative sample of Finnish dairy farmers. The aim was to find out whether two different job demand factors; workload, societal demands and lack of resource; loneliness, were related to the indicators of ill health via burnout.

METHODS

The data is based on a postal survey of 400 Finnish dairy farms. Altogether 265 questionnaires were received from 188 farms and included in the analysis. The response rate was 47 per cent among sample farms. Structural equation modelling (SEM) was used to analyze the relationships between the variables. Explanatory factor analysis was used to group the job demand and lack of resource variables.

RESULTS

We identified two job demand factors, which we labelled workload and societal demands and one lacking job resource, loneliness. Our theoretical model was supported in that two of the factors, namely workload and loneliness, were related to ill health indirectly via burnout. In addition, workload was directly connected with ill health. Societal job demands were not significantly related to burnout, or to ill health.

CONCLUSION

Our results suggest that farmers could benefit from means to reduce workload, especially the physical load. This topic needs further research as the restructuring process has increased farm enterprise sizes. There is a need to develop tools and projects to alleviate loneliness among farmers. Lack of social support, high workload, ill health, and burnout among farmers may have serious direct and indirect negative consequences for the sustainability of farming.