General and Eating Disorder Psychopathology in Relation to Short- and Long-Term Weight Change in Treatment-Seeking Children: A Latent Profile Analysis
Bibliographic record
Abstract
BACKGROUND: Concurrent general psychopathology (GP) and eating disorder psychopathology (EDP) are commonly reported among youth with overweight/obesity and may impact weight change. PURPOSE: We identified patterns of GP and EDP in children with overweight/obesity and examined the impact on weight change following family-based behavioral obesity treatment (FBT) and maintenance interventions. METHODS: Children (N = 172) participated in 4 month FBT and subsequent 8 month weight maintenance interventions. GP and EDP were assessed prior to FBT (baseline). Child percentage overweight was assessed at baseline, post-FBT (4 months), and post-maintenance (12 months). Latent profile analysis identified patterns of baseline GP and EDP. Linear mixed-effects models examined if profiles predicted 4- and 12-month change in percentage overweight and if there were two-way and three-way interactions among these variables, adjusting for relevant covariates. RESULTS: Results indicated a three-profile structure: lower GP and EDP (LOWER); subclinically elevated GP and EDP without loss of control (LOC; HIGHER); and subclinically elevated GP and EDP with LOC (HIGHER + LOC). Across profiles, children on average achieved clinically meaningful weight loss (i.e., ≥9 unit change in percentage overweight) from baseline to 4 month FBT and sustained these improvements at 12 month maintenance. There was no evidence that latent profiles were related to percentage overweight change from baseline to FBT (p > .05) or baseline to maintenance (p > .05). There was no evidence for two-way or three-way interactions (p > .05). CONCLUSION: Concurrent GP and EDP do not portend differential short- or long-term weight change following FBT and maintenance. Future research is warranted on the durability of weight change among youth with GP and EDP. TRIAL REGISTRATION: NCT00759746.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".