Effort expenditure for rewards task modified for food: A novel behavioral measure of willingness to work for food
Bibliographic record
Abstract
OBJECTIVE: Binge eating and associated eating disorders are characterized by abnormalities in reward processing. One component of reward is willingness to expend effort to obtain a reinforcer. The Effort Expenditure for Rewards Task (EEfRT) is a widely used behavioral measure of willingness to work for money. We sought to modify the EEfRT to examine willingness to work for food reward and to preliminarily examine the association between binge eating and effort expenditure for food. METHOD: Participants were 63 females recruited to span the spectrum of binge-eating severity. The modified EEfRT required participants to make a series of choices between an easier, low-reward option (one portion of food) and a harder, high-reward option (between two to five portions of food). Each trial also varied on probability of winning. RESULTS: Participants self-reported engagement in the task, working hard at easy and hard tasks, and making choices based on reward probability and magnitude. As with the original EEfRT, probability, reward magnitude, and their interaction predicted the likelihood of choosing the hard task. Across two different measures, binge-eating symptoms interacted with reward magnitude, such that those with high binge eating used reward magnitude more to make trial choices than those with low binge eating. DISCUSSION: These data provide initial support for the validity of the EEfRT modified for food as a behavioral measure of willingness to work for food reward. The impact of binge eating on effort expenditure must be replicated in samples of patients with eating disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".