A brief treatment for fear of heights
Bibliographic record
Abstract
Objective To assess the effectiveness of a novel imaginal intervention for people with acrophobia. Methods The design was a randomized controlled trial with concealed randomization and blinded to other participants' intervention. The intervention was a single novel imaginal intervention session or a 15-min meditation. The setting was in Auckland, New Zealand. The participants were a convenience sample of the public with a score >29 on the Heights Interpretation Questionnaire (HIQ), a questionnaire validated against actual height exposure. The primary outcomes were the proportion of participants with a score <26 on the HIQ at eight weeks and difference between the HIQ scores between the two arms of the study. Results Ninety-eight participants (92%) returned their questionnaire and were included in the intention to treat analysis. The HIQ score <26 was 34.6% (18/52) in the intervention group and 15.2% (7/46) in the control group RR = 2.26, 95% CI (1.05, 4.95) and p = 0.028. The numbers needed to treat is six 95% CI (3 to 36). Participants with scores <26 report their fear of heights is very much improved. There was a 4.5-point difference in the HIQ score at eight weeks (p = 0.055) on the multiple regression analysis. Conclusions This is the first randomized trial of this novel imaginal intervention which is probably effective, brief, easily learnt, and safe. It may be worth considering doing this prior to some of the longer or more expensive exposure therapies. This study will be of interest to family doctors, psychiatrists, and psychologists.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".