Rapid Assessment of Reward‐Related Eating: The RED‐X5
Bibliographic record
Abstract
OBJECTIVE: The prevalence of obesity has created a plethora of questionnaires characterizing psychological aspects of eating behavior, such as reward-related eating (RRE). The Reward-based Eating Drive questionnaires (RED-9, RED-13) broadly and deeply assess the RRE construct. However, large-sample research designs require shorter questionnaires that capture RRE quickly and precisely. This study sought to develop a brief, reliable, and valid version of the RED questionnaire. METHODS: All-subset correlation was used to find a subset that maximally associated with the full RED-13 in two separate samples. Results were validated in a third independent sample. Internal consistency, test-retest reliability, and ability to explain variance in external outcomes were also assessed. RESULTS: A five-item questionnaire (RED-X5) correlated strongly with RED-13 in the independent sample (r = 0.95). RED-X5 demonstrated high internal consistency (omega total ≥ 0.80) and 6-month test-retest reliability (r = 0.72). RED-X5 accurately reproduced known associations between RED-13 and BMI, diabetes status, and craving for sweet and savory foods. As a novel finding, RED questionnaires predicted laboratory intake of chips. CONCLUSIONS: RED-X5 is a short, reliable, and valid measure of the RRE construct and can be readily implemented in large-sample research designs in which questionnaire space is limited.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 teacher head, 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".