Eating disorder recovery is associated with absence of major depressive disorder and substance use disorders at 22-year longitudinal follow-up
Bibliographic record
Abstract
BACKGROUND: Psychiatric comorbidity is common in eating disorders (EDs) and associated with poor outcomes, including increased risk for relapse and premature death. Yet little is known about comorbidity following ED recovery. METHODS: We examined two common comorbidities, major depressive disorder (MDD) and substance use disorder (SUD), in adult women with intake diagnoses of anorexia nervosa and bulimia nervosa who participated in a 22-year longitudinal study. One hundred and seventy-six of 228 surviving participants (77.2%) were interviewed 22 years after study entry using the Eating Disorders Longitudinal Interval Follow-up Evaluation to assess ED recovery status. Sixty-four percent (n = 113) were recovered from their ED. The Structured Clinical Interview for DSM-IV was used to assess MDD and SUD at 22 years. RESULTS: At 22-year follow-up, 28% (n = 49) met criteria for MDD, and 6% (n = 11) met criteria for SUD. Those who recovered from their ED were 2.17 times more likely not to have MDD at 22-year follow-up (95% CI [1.10, 4.26], p = .023) and 5.33 times more likely not to have a SUD at 22-year follow-up than those who had not recovered from their ED (95% CI [1.36, 20.90], p = .008). CONCLUSION: Compared to those who had not fully recovered from their ED, those who had recovered were twice as likely not to be diagnosed with MDD in the past year and five times as likely not to be diagnosed with SUDs in the past year. These findings provide evidence that long-term recovery from EDs is associated with recovery from or absence of these common major comorbidities. Because comorbidity in EDs can predict poor outcomes, including greater risk for relapse and premature death, our findings of reduced risk for psychiatric comorbidity following recovery at long-term follow-up is cause for optimism.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".