Feasibility of an Online Grocery Intervention Pilot to Improve Fruit and Vegetable Purchase and Food Security Among Adults With Children Eligible for SNAP
Bibliographic record
Abstract
OBJECTIVE: To determine the feasibility of an online grocery pilot aimed at supporting healthy food purchases for caregivers of individuals with low income. METHODS: A pretest-posttest pilot study was conducted among 59 primary household food shopper caregivers living ≤ 130% of the poverty line. The 8-week randomized pilot had 4 groups: (1) free delivery-only, (2) trust-targeting SMS, (3) matching credit for online healthy purchases, and (4) grocery list recommendations. The groups received the program concomitantly from October to December, 2022. Feasibility was assessed through the setup of an online grocery account and receipt of the intervention materials via text. Acceptability was assessed via postintervention interviews and participants' ratings of the intervention. RESULTS: Feasibility was medium-high: 47% created an online grocery account, 61% watched the program tutorial. Acceptability was high: 90% found the tutorial helpful, all received text messages, 82% deemed them useful. CONCLUSIONS AND IMPLICATIONS: The promising feasibility and acceptability suggest a potential for a fully powered trial behavioral intervention to support online healthy food shopping.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".