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Effectiveness of Digital Interventions for Low-Income, Food-Insecure Populations: Natural Language Processing Study
1Stan Richards School of Advertising and Public Relations, Moody College of Communication, The University of Texas at Austin, 300 W Dean Keeton DMC 4.314 (A1200), Austin, TX, 78712, United States, 1 512 471 1101.
Background:
The Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) is a federal nutrition assistance program for low-income, food-insecure mothers and young children in the United States. Despite its intended goals, many eligible individuals forgo WIC benefits, in part due to administrative burden-defined as the complex, often frustrating processes encountered when navigating public benefit programs. In response, a range of digital interventions and policy waivers were introduced during the COVID-19 pandemic, but their effectiveness in reducing barriers remains unclear.
Objective:
Drawing from administrative burden theory and human-computer interaction research, this study examined user reviews of WIC smartphone apps (WIC Apps) used by local agencies. Specifically, it investigated (1) how obstacles to WIC access manifested in daily app use, (2) how user experiences shifted after the onset of the COVID-19 pandemic, and (3) how these changes were associated with app ratings.
Methods:
An original dataset of user reviews (Nreview=28,212) was compiled for 26 WIC Apps between 2013 and 2024. Structural topic modeling identified 8 key themes, and sentiment was examined with Robustly Optimized Bidirectional Encoder Representations From Transformers Pretraining Approach. Analyses compared topic prevalence and sentiment distributions before and after COVID-19. Mixed-effects models examined the relationship between topics, sentiment, and app ratings.
Results:
Technical concerns related to account authentication and login, document upload, and app updates were among the most prevalent themes. These issues were typically expressed with negative sentiment and appeared more frequently in pre-COVID-19 reviews than in post-COVID-19 reviews. Although reliability problems (eg, outages and maintenance) persisted, post-COVID-19 reviews increasingly emphasized features that facilitated program tracking, shopping and benefit redemption, and general ease of use, which were generally described with positive sentiment. Mixed-effects analyses indicated that these post-COVID-19 topics were significantly associated with higher app ratings (program tracking: B=0.21, SE=0.06; P=.001; shopping and redemption: B=0.18, SE=0.07; P=.01; and ease of use: B=0.10, SE=0.05; P=.04), whereas pre-COVID-19 concerns were not associated with ratings (Ps>.05). When sentiment was added to the mixed-effect model, it became the dominant factor: negative sentiment was associated with lower ratings (B=-1.71, SE=0.03; P<.001), and positive sentiment was associated with higher ratings (B=1.78, SE=0.03; P<.001). After accounting for sentiment, no individual topic was significantly associated with ratings (Ps>.05), suggesting that sentiment contributed to much of the variance previously linked to topics.
Conclusions:
User-centered digital interventions, such as WIC Apps, have the potential to support WIC access and participation.
