Generalized Anxiety Disorder: Does the Emotion Dysregulation Model Predict Symptoms Above the Metacognitive Model?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Individuals with generalized anxiety disorder (GAD) experience excessive anxiety and uncontrollable worry lasting at least six months, with their worry not limited to a single type or context. The Metacognitive Model (MCM) is a well-established framework of GAD, emphasizing negative beliefs about worry (NB). Recently, the Emotion Dysregulation Model (EDM) of GAD was proposed, focusing on issues with understanding, expressing, and managing emotions. However, there is a lack of research examining the utility of the EDM by comparing it to more established models, such as the MCM. This study extends the current literature by examining whether the EDM helps explain GAD symptoms when compared to the MCM. Self-report measures of worry, GAD symptoms, the EDM, and the MCM were administered to a non-clinical university sample (N = 400). The following was hypothesized: GAD symptoms and worry would positively correlate with emotion dysregulation; GAD symptoms and worry would positively correlate with NB; and emotion dysregulation would predict GAD symptoms independently of NB. Bivariate correlations were conducted to determine whether measures of the MCM and EDM correlated with GAD and worry. Regression analyses tested which measures uniquely predicted GAD and worry. Findings demonstrated that NB and various components of the EDM correlate with GAD and worry. Regression analyses found that when controlling for NB, emotional expressivity (EE) and fear of emotions predicted GAD, while EE and difficulty regulating emotions predicted worry. Findings have implications for GAD treatment, encouraging an approach including emotion psychoeducation and development of effective emotional regulation strategies. Discipline: Psychology (Honours) Faculty Mentor: Dr. Alexander Penney
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it