Effect of Energy Restriction on Eating Behavior Traits and Psychobehavioral Factors in the Low Satiety Phenotype
Bibliographic record
Abstract
Studies have shown that individuals with low satiety efficiency may be more susceptible to weight gain, but little is known about the effect of weight loss intervention outcomes in these individuals. This study aimed to evaluate the impact of an energy-restricted weight loss intervention on eating behavior traits and psychobehavioral factors in individuals differing in their satiety responsiveness. A pooled cohort of individuals who were overweight or obese (n = 100; aged 39 ± 9 years) participating in a 12- to 15-week weight loss program targeting an energy deficit of 500–700 kcal/day were included in this study. Satiety responsiveness was determined by a median split of the mean satiety quotient based on appetite sensations measured in response to a test meal at baseline (low satiety responsiveness (LSR) vs. high satiety responsiveness (HSR)). Anthropometric variables, eating behavior traits, psychobehavioral factors, and ad libitum energy intake were assessed before and after the intervention. Although similar weight loss was observed between the LSR and HSR groups (−3.5 ± 3.2 vs. −3.8 ± 2.8 kg, p = 0.64) in response to an energy-restricted weight loss intervention, changes in eating behavior traits were different between groups. Individuals with LSR had a higher increase in cognitive restraint (+5.5 ± 4.1 vs. +3.5 ± 3.5, p = 0.02) and some of its subscales and a lower decrease in situational susceptibility to disinhibition (−0.6 ± 1.1 vs. −1.2 ± 1.3, p = 0.02) in response to the intervention compared to the HSR group. In conclusion, energy-restricted weight loss intervention seems to trigger undesirable changes in some eating behavior traits in individuals more vulnerable to overeating, which could increase their susceptibility to weight regain.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".