Adiposity and Eating Behaviors in Patients Under Second Generation Antipsychotics
Bibliographic record
Abstract
BACKGROUND: Second generation antipsychotics (SGA) induce substantial weight gain but the mechanisms responsible for this phenomenon remain speculative. OBJECTIVE: To explore eating behaviors among SGA-treated patients and compare them with nonschizophrenic healthy sedentary individuals (controls). METHODS AND PROCEDURES: Appetite sensations were recorded before and after a standardized breakfast using visual analog scales. Three hours after breakfast, a buffet-type meal was offered to participants to document spontaneous food intake and food preferences. Satiety quotients (SQs) were calculated to determine the satiation of both meals and the Three-Factor Eating Questionnaire (TFEQ) was used to document eating behaviors. Body composition and abdominal fat distribution were assessed. RESULTS: Compared with controls (n = 20), SGA-treated patients (n = 18) showed greater adiposity indices (P < or = 0.04). Patients' degree of hunger was also higher following the standardized breakfast (P = 0.03). Moreover, patients had significantly higher cognitive dietary restraint, disinhibition, and susceptibility to hunger scores than the reference group (P < or = 0.05). Disinhibition in the reference group was positively associated with hunger triggered by external cues (r = 0.48, P = 0.03) whereas internal cues seem to mainly regulate emotional susceptibility to disinhibition in patients (r = 0.56, P = 0.02). Higher strategic restraint behavior in patients was associated with decreased satiation right after the buffet-type meal (r = -0.56, P = 0.02). DISCUSSION: These exploratory findings suggest that patients under SGA seem to develop disordered eating behaviors in response to altered appetite sensations and increased susceptibility to hunger, a factor which may influence the extent of body weight gain triggered by these drugs.
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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 | 0.001 |
| 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".