Empirically derived subtypes of lifetime anxiety disorders: Developmental and clinical correlates in U.S. Adolescents.
Bibliographic record
Abstract
OBJECTIVE: The current study examined the sex- and age-specific structure and comorbidity of lifetime anxiety disorders among U.S. adolescents. METHOD: The sample consisted of 2,539 adolescents (1,505 females and 1,034 males) from the National Comorbidity Survey-Adolescent Supplement who met criteria for Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev. [DSM-IV-TR]) lifetime anxiety disorders (American Psychiatric Association, 2000). Adolescents ranged in age from 13 to 18 years (M = 15.2 years, SE = 0.08 years) and were 39% non-White. Multiple-group latent class analysis was conducted by adolescent sex and age to identify subgroups of adolescents with similar anxiety disorder profiles. Developmental and clinical correlates of empirically derived classes were also examined to assess the nomological validity of identified subgroups. RESULTS: A 7-class solution provided the best fit to the data, with classes defined primarily by one rather than multiple anxiety disorders. Results also indicated that classes displayed similar diagnostic profiles across age, but varied by sex. Classes characterized by multiple anxiety disorders were consistently associated with a greater degree of persistence, clinical severity, impairment, and comorbidity with other DSM-IV-TR psychiatric disorders. CONCLUSIONS: The presentation of lifetime anxiety disorders among adolescents and the observation of unique correlates of specific classes provide initial evidence for the utility of individual DSM-IV-TR anxiety disorder categories. Although findings of the present study should be considered preliminary, results emphasize the potential value of early intervention and gender-specific conceptualization and treatment of anxiety disorders.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".