The Automated Self‐Administered 24‐Hour (ASA24) is Now Mobile and Can Collect Both 24‐Hour Recalls and Food Records
Bibliographic record
Abstract
ASA24 is a fully automated, web‐based, self‐administered 24‐hour dietary recall that provides a complete system for probing, coding, and calculating nutrient and food group intakes. The system is based on the U.S. Department of Agriculture's interviewer‐administered Automated Multiple‐Pass Method, the recall method used in the National Health and Nutrition Examination Survey (NHANES). It has been available to extramural investigators, clinicians, and educators at no cost since 2009. From 2009 until October 2015, more than 1,800 studies registered to use ASA24 and more than 204,000 recalls were completed. Modified versions are available for use with children and Canadian participants, and an Australian version is under development. All U.S. versions can be completed in English or Spanish, and the Canadian version will soon be available in French. By early 2016, the National Cancer Institute (NCI) and Westat will release a new mobile version of ASA24 that will be accessible using smart phones and tablets in addition to laptops and desktops. With this new version, researchers will be able to collect food records as well as 24‐hour recalls. The user interface has been modernized to reflect current best practices for web‐users, and includes new features for searching and filtering to find foods consumed, identifying favorites, and obtaining context‐specific help. Supplements are now reported using a more intuitive approach similar to the way in which foods and beverages are reported. The following databases have been updated: the list of foods and beverages provided to respondents, based on NHANES 2011–12; nutrients in foods/beverages, based on the Food and Nutrient Database for Dietary Studies 2011–12; food groups, based on the Food Patterns Equivalents Database 2011–12; the list of supplements and nutrient database associated with supplements, based on the NHANES Dietary Supplement Database 2011–12. The updated version will allow for expanded usage of ASA24, enabling the collection of high‐quality dietary intake data in a range of settings and study types. The NCI and other Institutes and Centers at the National Institutes of Health are committed to providing a low‐cost means for investigators to obtain high‐quality 24‐hour dietary recalls, and now, food records, in surveillance, epidemiologic, intervention, and clinical research. Support or Funding Information National Cancer Institute
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.021 |
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".