JOURNAL ARTICLE

Trade-Offs Faced by 2-and 4-Year College Students Experiencing Food Insecurity: An Analysis of Qualitative Data.

  • Published In: American Journal of Health Promotion, 2023, v. 37, n. 8. P. 1133 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: McGuire, Cydney M.; Stebleton, Michael J.; Lenk, Kathleen M.; Lust, Katherine; Porta, Carolyn M.; Laska, Melissa N. 3 of 3

Abstract

This article examines the trade-offs—defined as compromises students make to prioritize one need over another—experienced by food insecure (FI) college students at both 2- and 4-year institutions in Minnesota, and how these trade-offs affect their health, well-being, and academic success. Through eight semi-structured focus groups with 53 students screening positive for FI, five key themes emerged: sacrificing food quality and quantity, missing out on social relationships, sacrificing academic studies, choosing between basic needs (e.g., housing, personal care), and maintaining physical and mental well-being. The study highlights the multifaceted and stressful nature of these trade-offs, emphasizing the challenges faced by financially independent students living off-campus. Findings suggest that understanding these trade-offs can inform college staff and policymakers in prioritizing interventions to improve student health and academic outcomes, including expanding access to food assistance programs and mental health services.

Additional Information

  • Source:American Journal of Health Promotion. 2023/11, Vol. 37, Issue 8, p1133
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0890-1171
  • DOI:10.1177/08901171231184074
  • Accession Number:173490888
  • Copyright Statement:Copyright of American Journal of Health Promotion is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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