Protocol for a randomised controlled trial of Overcome Death Anxiety: an online cognitive behavioural therapy intervention in a clinical sample
Bibliographic record
Abstract
Abstract Background: Evidence suggests that death anxiety is a transdiagnostic construct underlying numerous anxiety-related conditions. A previous phase I trial of Overcome Death Anxiety (ODA), a novel online stand-alone psychological intervention to reduce death anxiety, demonstrated preliminary evidence of efficacy and acceptability in a clinical population. However, this trial was limited by a small sample size (n=20). Aims: To further evaluate the efficacy of this intervention in reducing death anxiety in a clinical population, compared with a waitlist control. Method: This paper describes the protocol of a phase II randomized controlled, unblinded trial of ODA. A total sample of 256 adults living in Australia, diagnosed with an anxiety-related condition, will be recruited. These participants will be randomised to ODA or a waitlist control. Primary outcomes will be measured as changes in scores on death anxiety questionnaires, reflecting treatment efficacy. The secondary outcomes to be measured are depression, anxiety, stress, suicidality, insomnia, and meaning of life, as well as feedback about treatment program acceptability. This trial will assess the efficacy of ODA for reducing death anxiety in a population diagnosed with various anxiety-related conditions, as well as the overall acceptability and tolerability of the intervention. Conclusions: This study will provide evidence to evaluate the efficacy of ODA in people diagnosed with an anxiety-related condition.
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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 | 0.045 | 0.044 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.106 | 0.019 |
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".