Alleviating distressing intrusive memories in depression: A comparison between computerised cognitive bias modification and cognitive behavioural education
Bibliographic record
Abstract
Negative appraisals maintain intrusive memories and intrusion-distress in depression, but treatment is underdeveloped. This study compared the efficacy of computerised bias modification positive appraisal training (CBM) versus a therapist-delivered cognitive behavioural therapy session (CB-Education) that both aimed to target and alter negative appraisals of a negative intrusive autobiographical memory. Dysphoric participants (Mean BDI-II = 27.85; N = 60) completed baseline ratings of a negative intrusive memory, negative appraisals and the Impact of Event Scale, and were randomly allocated either one session of CBM, CB-Education, or a no intervention monitoring control condition (Control). Mood and intrusion symptoms were assessed at one week follow-up. For all groups, there were significant reductions over one week in mood (depression and anxiety), memory intrusiveness and negative appraisals. Groups differed in terms of intrusion-related distress, with the CB-Education group showing greatest reduction, followed by the CBM group. The study provides evidence for the link between maladaptive appraisals of intrusive memories and distress in depressed mood. Further, both a single session of CB-Education and (to a lesser degree) CBM are useful in reducing intrusion-related distress. This study may have been underpowered to detect differences and replication is needed with larger samples.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".