Inhibitory Control, Attentional Bias, and Palatable Food Consumption in Adolescents: A Laboratory Feasibility Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Understanding relationships among inhibitory control, attentional bias to food cues, and food consumption in nonclinical adolescent samples can inform preventive efforts for disordered eating and associated health risks. OBJECTIVE: This pilot study conducted preliminary testing of an inhibitory control training intervention on attentional bias toward food cues, hedonic appetite, and food consumption, as well as examined inhibitory control's relationship with hedonic appetite, food consumption, binge eating, and cognitive restraint. METHODS: Participants (N=43; mean age 15.1, SD 1.7 years; 31/43, 72% female) were randomized to a food cue-specific go/no go inhibitory control training intervention or control group, took part in a laboratory "taste test," and completed surveys and a dietary recall. Additional data were collected for subsamples through an eye tracking task (15/43, 35%) and cognitive tasks (19/43, 44%). RESULTS: The go/no go intervention showed preliminary associations with attentional bias toward food cues. There were preliminary associations between inhibitory control and sugar consumption measured via dietary recall, binge eating symptoms, and cognitive restraint, which should be examined in a fully powered study. CONCLUSIONS: The role of inhibitory control should be examined in larger studies to inform strategies for promotion of healthy eating behavior and prevention of disordered eating in adolescents.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".