Terror catastrophizing: association with anxiety, depression, and transgenerational effects
Bibliographic record
Abstract
Background & Objectives: Terror catastrophizing, defined as an ongoing fear of future terrorist attacks, is associated with a higher incidence of anxiety disorders, among other psychological impacts. However, previous studies examining terror catastrophizing’s relationship to other mental health disorders are limited. The current study sought to determine if patients diagnosed with anxiety and depression would experience increased terror catastrophizing. Additionally, this study aimed to investigate whether parental terror catastrophizing increases children’s internalizing symptoms.Design & Methods: Individuals were randomly drawn from the Danish Civil Registration System and invited to complete a series of questionnaires to measure terror catastrophizing tendency, lifetime parental trauma, and children’s internalizing symptoms. In total, n = 4,175 invitees completed the survey of which 933 reported on a child between 6 and 18 years. Responses were analyzed using a generalized linear regression model.Results: Participants diagnosed with anxiety alone or comorbid with depression were more likely to experience symptoms of terror catastrophizing than undiagnosed participants (β = 0.10, p < .001; β = 0.07, p = .012). Furthermore, the parental tendency to catastrophize terror was associated with higher internalizing symptoms in children (β = 0.09, p = .006), even after taking parental diagnoses, as well as lifetime and childhood trauma into account.Conclusion: The results can inform clinical practices to account for a patient’s potential to exhibit increased terror catastrophizing tendencies or be more affected by traumatic events. Additionally, they can offer insights for designing novel preventative interventions for the whole family, due to the relation between parental tendencies for terror catastrophizing and the internalizing symptoms observed in children.
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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) | 0.003 | 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".