Panic attacks as a risk for later psychopathology: results from a nationally representative survey
Bibliographic record
Abstract
BACKGROUND: There is a growing body of literature suggesting that panic attacks without panic disorder are associated with increases in a wide range of psychopathology and impairment. However, the majority of the literature to date has been cross-sectional. Some longitudinal research supports the view that panic attacks are a nonspecific risk factor for future psychopathology. Using a large nationally representative longitudinal survey of adults, we sought to determine whether panic attacks predict new onset Axis I disorders. METHODS: The Alcohol Use Disorder and Associated Disabilities Interview Schedule-DSM-IV Version was used to make diagnoses of psychiatric disorders in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2 (n = 34,653, aged 18 and older, response rate = 70.2%). Incident psychiatric disorders at Wave 2 were compared between people with and without panic attacks at Wave 1. RESULTS: Panic attacks at Wave 1 were significantly associated with increased incidents of generalized anxiety disorder, panic disorder, social phobia, major depression, dysthymia, mania and hypomania, any anxiety disorder, and any mood disorder even after adjusting for sociodemographic variables, Wave 1 Axis I disorders, and Axis II disorders (OR's ranging from 1.62 to 2.77). CONCLUSIONS: The presence of panic attacks may be an important indicator of overall psychological distress and the risk of more severe psychopathology in the future.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".