Telephone Administration of the Automated Self-Administered 24-hour Dietary Assessment in Older Adults: Lessons Learned
Bibliographic record
Abstract
Automated Self-Administered 24-hour Dietary Assessment (ASA24) is an economical method of estimating dietary intake as nutrient analysis is automated, but its use in older adults is limited. The purpose of this work was to guide dietitians and future researchers on how to use the ASA24 with older adults, considering potential barriers encountered and strategies used to support completion based on our experience using this tool in a pilot clinical trial. ASA24 was completed by phone interview with 39 older adults. Challenges included: recalling food intake in detail, recording frequent eating occasions and complicated recipes, and general problems with communication. Strategies to support collection included making morning phone calls and suggesting that seniors write down the food consumed. Phone interviews were acceptable to older adults, but sufficient time was required. Dietitians and future researchers can use these findings to obtain dietary intake data from this hard-to-reach group.
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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 | 0.020 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".