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Record W3116797537 · doi:10.2196/21602

Grocery Delivery of Healthy Foods to Pregnant Young Women With Low Incomes: Feasibility and Acceptability Mixed Methods Study

2020· article· en· W3116797537 on OpenAlexvenueno aff
Ione Locher, Marika Waselewski, Kendrin R. Sonneville, Ken Resnicow, Tammy Chang

Bibliographic record

VenueJMIR Formative Research · 2020
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicineReceiptEnvironmental healthPregnancyGrocery storeAdvertising

Abstract

fetched live from OpenAlex

BACKGROUND: Poor maternal diets increase the risk of excess gestational weight gain which can contribute to serious intergenerational morbidity for both the mother and infant. Pregnant young women with low incomes have disproportionately high rates of inadequate fruit and vegetable consumption as well as excess weight gains during pregnancy. OBJECTIVE: Our aim was to describe the feasibility and acceptability of Special Delivery, a longitudinal nutrition intervention that delivers healthy foods to pregnant youth (aged 14-24 years) with low incomes. METHODS: The Special Delivery pilot study, conducted in Michigan, enrolled pregnant young women with low incomes. Study participants were sent twice-monthly grocery deliveries consisting of US $35 worth of healthy foods, primarily fruits and vegetables. Between grocery deliveries, participants received daily SMS text message prompts to confirm receipt of delivery and document diet and weight. Program feasibility was assessed by the number of grocery orders placed, delivered, and confirmed by participants. Qualitative interviews and SMS text message data were used to determine acceptability by assessing participants' perspectives on grocery delivery, participants' perspectives on dietary impact of the program, and foods consumed by participants. RESULTS: A total of 27 participants were enrolled in the pilot study. The mean age was 20.3 years (SD 2.0), and 59.3% (16/27) were African American or Black. During the pilot, 263 deliveries were sent with 98.5% (259/263) successful deliveries and 89.4% (235/263) deliveries confirmed by participants. Participants reported that grocery delivery was convenient; that delivered foods were high quality; and that the program improved their diet, increased access to healthy foods, and promoted healthy habits during pregnancy. CONCLUSIONS: A grocery delivery-based weight gain and nutrition intervention is both feasible and acceptable among low-income pregnant youth. Grocery deliveries were successfully completed and participants were willing and able to receive grocery deliveries, eat the healthy foods that were delivered, and communicate via SMS text message with study coordinators. The Special Delivery program warrants further evaluation for efficacy in promoting healthy weight gain for low-income youth during pregnancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.024
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.089
GPT teacher head0.469
Teacher spread0.380 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations11
Published2020
Admission routes1
Has abstractyes

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