Patterns of Symptom Change in Behaviors and Cognitions During 10‐Session Cognitive Behavioral Therapy (<scp>CBT</scp>‐T) for Non‐Underweight Eating Disorders
Bibliographic record
Abstract
OBJECTIVE: Little is known about the timing of behavioral versus cognitive change in 10-session cognitive-behavioral therapy for non-underweight eating disorders (CBT-T). We aimed to: (a) evaluate the magnitude of behavioral and cognitive symptom reduction across treatment; and (b) investigate the relation between early behavioral change and subsequent cognitive change. We hypothesized: (a) large and significant reductions in behavioral and cognitive symptoms from pre- to mid-treatment and from pre- to post-treatment; and (b) that early behavioral change would predict subsequent cognitive change over the course of treatment. METHOD: Patients (N = 63) were offered CBT-T and completed the Eating Disorder-15 on a weekly basis. We used intent-to-treat analyses. For Aim 1, we conducted a series of fixed-effect multilevel models for each outcome variable, accounting for repeated measures (pre-, mid-, and post-treatment) within individuals. For Aim 2, we conducted a linear regression using early behavioral change as the predictor and subsequent cognitive change as the outcome. RESULTS: We observed large and significant reductions in most behavioral and all cognitive symptoms pre- to mid-treatment and pre- to post-treatment. Early changes in behavioral symptoms did not significantly predict subsequent cognitive changes. DISCUSSION: Behavioral improvements occurred rapidly and were sustained throughout treatment, whereas cognitive changes followed a more gradual trajectory. The absence of a significant predictive relationship between early behavioral change and subsequent cognitive change suggests that these domains may improve independently. Future research should investigate the mechanisms linking behavioral and cognitive changes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".