Web-Based Tool Designed to Encourage Supplemental Nutrition Assistance Program Use in Urban College Students: Usability Testing Study
Bibliographic record
Abstract
BACKGROUND: Food insecurity continues to be a risk for college students in the United States. It is associated with numerous problems, such as chronic health conditions, increased stress and anxiety, and a lower grade point average. After COVID-19, the Supplemental Nutrition Assistance Program (SNAP) benefits were extended to college-aged students; however, there were some barriers to participation, which persisted such as lack of perceived food insecurity risk, lack of knowledge regarding the SNAP application process, the complexity of determining eligibility, and stigma associated with needing social assistance. A technology-enhanced tool was developed to address these barriers to SNAP enrollment and encourage at-risk college students to apply for SNAP. OBJECTIVE: The purpose of this study was to test the usability and acceptability of a web-based SNAP screening tool designed for college-aged students. METHODS: College students aged 18-25 years were recruited to participate in 2 rounds of usability testing during fall 2022. Participants tested the prototype of a web-based SNAP screener tool using a standardized think-aloud method. The usability and acceptability of the tool were assessed using a semistructured interview and a 10-item validated System Usability Scale questionnaire. Audio recordings and field notes were systematically reviewed by extracting and sorting feedback as positive or negative comments. System Usability Scale questionnaire data were analyzed using the Wilcoxon signed rank test and sign test. RESULTS: A total of 12 students (mean age 21.8, SD 2.8 years; n=6, 50% undergraduate; n=11, 92% female; n=7, 58% Hispanic or Black or African American; n=9, 78% low or very low food security) participated in both rounds of user testing. Round 1 testing highlighted overall positive experiences with the tool, with most participants (10/12) stating that the website fulfills its primary objective as a support tool to encourage college students to apply for SNAP. However, issues related to user interface design, navigation, and wording of some questions in the screening tool were noted. Key changes after round 1 reflected these concerns, including improved design of response buttons and tool logo and improved clarity of screening questions. The overall system usability showed slight, but not statistically significant, improvement between round 1 and round 2 (91.25 vs 92.50; P=.10, respectively). CONCLUSIONS: Overall usability findings suggest that this web-based tool was highly usable and acceptable to urban college students and could be an effective and appealing approach as a support tool to introduce college students to the SNAP application process. The findings from this study will inform further development of the tool, which could eventually be disseminated publicly among various college campuses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".