THE BEHAVIOURAL FEATURES OF GENERALIZED ANXIETY DISORDER DURING THE PERINATAL PERIOD
Bibliographic record
Abstract
Generalized anxiety disorder (GAD) is a leading mental health condition, associated with significant distress and impairment, especially during pregnancy and the postpartum (perinatal) period. However, GAD is a poorly defined mental health disorder, and research devoted to understanding its clinical features is lacking. While excessive and difficult to control worry is the defining feature of GAD, there is growing interest in understanding the role of behaviour. Extant literature alludes to the diagnostic, clinical, and theoretical importance of behaviours in GAD, however, systematic evaluation of the behavioural features of GAD and their bearing on GAD pathology is lacking, particularly during the perinatal period. This dissertation explores the behaviours that perinatal individuals with GAD engage in, in response to their worries, adapts and validates a self-report measure to assess GAD behaviours during the perinatal period, and evaluates the contribution of specific behaviours to our diagnostic understanding of GAD. This program of research suggests that perinatal individuals with GAD engage in a range of avoidance and safety behaviours to manage their distress. We also provide clinicians and researchers with a measure of GAD behaviours for use during the perinatal period to support continued evaluation of this phenomenon. Finally, our research highlights the importance of checking behaviours in perinatal individuals with GAD, with potential implications for theory and practice.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".