Alternative School Breakfast Service Models and Associations with Breakfast Participation, Diet Quality, Body Mass Index, Attendance, Behavior, and Academic Performance: A Systematic Review
Bibliographic record
Abstract
The United States (US) School Breakfast Program provides Breakfast After The Bell (BATB) to alleviate hunger, provide nutrition, and ensure students have a healthy start to the day. This study aims to review the evidence regarding the impact of BATB on students' diet and academic outcomes, including participation, diet quality and consumption, body mass index (BMI) and weight status, attendance, classroom behavior, and academic performance. The articles were extracted from three electronic databases and published since the start of the literature through December 2022. Studies were peer-reviewed; quantitative research articles or government reports; and conducted in public or private elementary, middle, and high schools. Quality was assessed using the Newcastle-Ottawa Scale. Thirty-seven studies were included in this review. This review found BATB increased school breakfast participation, improved diet quality, and improved classroom behavior particularly among students from racial and ethnic minority backgrounds and students eligible for free or reduced-price meals. The impact of BATB on BMI and weight status, academic achievement and attendance was mixed. This review is particularly timely given free school meals and updated school nutrition standards are being prioritized over the next decade in the US. Thus, it is important to evaluate the nutritional and educational outcomes of BATB. (PROSPERO registration: CRD42021289719).
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 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".