Psychobiological effects observed in obese men experiencing body weight loss plateau
Bibliographic record
Abstract
Our objective was to investigate the psychobiological impact associated with resistance to further weight loss in obese men. Anthropometric and body composition measurements, resting metabolic rate (RMR) measurement, appetite sensation markers, and three questionnaires [Short Form-36 Health Survey (SF-36), Three-Factor Eating Questionnaire (TFEQ), and Beck Depression Inventory (BDI)] were assessed at baseline and after 1 month of body weight loss plateau induced by a supervised diet and exercise clinical intervention in 11 obese men. The weight loss plateau corresponded to 11.2% of initial body weight (93.9% from fat stores). However, this amount of weight loss induced a significant decrease in RMR (P <.05) and a significant increase in hunger (P <.05) and desire to eat (P <.05). Using the SF-36 Health Survey, physical and mental health were shown to be unchanged at plateau as compared to baseline. The TFEQ showed that cognitive dietary restraint increased (P <.001) compared to baseline. Finally, depression risk as measured by the BDI significantly increased at plateau (P <.01) compared to baseline. Weight loss until resistance to further weight loss may be detrimental for some psychobiological variables including depression, which emphasizes the relevance of caution and reasonable objectives when prescribing a weight reduction program for obese individuals.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".