Effects of Engaging in Repeated Mental Imagery of Future Positive Events on Behavioural Activation in Individuals with Major Depressive Disorder
Bibliographic record
Abstract
Depression is associated with decreased engagement in behavioural activities. A wide range of activities can be promoted by simulating them via mental imagery. Mental imagery of positive events could thus provide a route to increasing adaptive behaviour in depression. The current study tested whether repeated engagement in positive mental imagery led to increases in behavioural activation in participants with depression, using data from a randomized controlled trial (Blackwell et al. in Clin Psychol Sci 3(1):91–111, 2015. doi: 10.1177/2167702614560746 ). Participants (N = 150) were randomized to a 4-week positive imagery intervention or an active non-imagery control condition, completed via the internet. Behavioural activation was assessed five times up to 6 months follow-up using the Behavioural Activation for Depression Scale (BADS). While BADS scores increased over time in both groups, there was an initial greater increase in the imagery condition. Investigating mental imagery simulation of positive activities as a means to promote behavioural activation in depression could provide a fruitful line of enquiry for future research.
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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 | 0.001 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".