Qualitative analysis of hotspots and intrusive memories after viewing an aversive film highlights their sensory and spatial features
Bibliographic record
Abstract
Intrusive memories of trauma are recurrent distressing sensory-perceptual impressions of the traumatic event that enter consciousness spontaneously and unwanted. They often contain the worst moment/s ('hotspots') of the trauma memory and have primarily been studied in clinical populations after real trauma. Intrusive memories can also be studied using analogue trauma as an 'experimental psychology model'. Little is known about the features of analogue trauma hotspots. Here we report an ancillary analysis of data from a randomized controlled trial. Seventy non-clinical participants viewed a trauma film containing COVID-19 related footage. Features of hotspots/intrusive memories of the film were explored using linguistic analysis and qualitative content coding. Participants reported on average five hotspots (M = 9.5 words/hotspot). Akin to hotspots soon after real trauma, analogue hotspots/intrusions primarily contained words related to space. Most contained sensory features, yet few cognitions and emotions. Results indicate that features of analogue trauma hotspots mirror those of hotspots soon after real trauma, speaking to the clinical validity of this 'experimental psychology model'.ClinicalTrials.gov ID: NCT04608097, registered on 29/10/2020.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".