Elevated social anxiety symptoms across childhood and adolescence predict adult mental disorders and cannabis use
Bibliographic record
Abstract
AIM: We assessed the heterogeneous development of self-reported social anxiety symptoms across childhood and adolescence (ages 10 to 18; N = 701) and examined whether these groups predicted clinically derived diagnoses of social anxiety disorder (SAD), generalized anxiety disorder (GAD), depressive episodes, panic disorder (PD), agoraphobia, obsessive compulsive disorder (OCD), and substance use in adulthood (ages 19 to 22). RESULTS: Three distinct social anxiety symptom trajectories were found: a high increasing group (15.5%), a moderate group (37.3%), and a low group (47.2%). The high increasing and moderate trajectory groups were differentiated from the low trajectory group on the adult mental disorders examined: SAD (high OR = 15.74; moderate OR = 11.72), GAD (high OR = 13.08; moderate OR = 8.98), depressive episode (high OR = 19.75), PD (high OR = 8.43; moderate OR = 5.90), agoraphobia (high OR = 16.39; moderate OR = 9.68), and OCD (high OR = 3.49; moderate OR = 2.98). The high and moderate groups were not differentiated on SAD, GAD, PD, or OCD but were differentiated on depressive episodes (OR = 3.24). Relative to the low and moderate trajectory groups, the high increasing social anxiety symptoms trajectory group also predicted cannabis use, but not alcohol use in adulthood. Gender, ethnicity, household income, and parental education were accounted for when predicting adult outcomes. CONCLUSION: These results highlight the importance of early treatment of symptoms of childhood social anxiety in the prevention of mental health problems in adulthood.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".