Assessing risk taking and decision making associated with late‐life onset mild psychotics symptoms in cognitively normal older adults
Bibliographic record
Abstract
Abstract Background Late‐life onset psychosis assessed in the Mild Behavioral Impairment framework (MBI‐psychosis) is a risk factor for dementia and known to be associated with impaired reasoning and memory in people without dementia. There is evidence that psychotic symptoms across diagnostic boundaries share some common genetic and neuropsychological correlates. In this study we aimed to determine whether MBI‐psychosis is associated cognitive deficits typically associated with other psychoses. To do this, we examined the relationship between MBI‐psychosis and scores on a specialised decision making and risk‐taking test, the Cambridge Gambling Task (CGT), performance on which is impaired in people with earlier life psychotic syndromes. Method 476 participants were drawn from the online PROTECT registry on the basis of the Mild Behavioural Impairment Checklist (MBI‐C) ratings indicating psychosis and invited to complete the Cambridge Gambling Task. The association between performance on six CGT outcome measures, assessing elements of risk taking and decision making, and MBI‐psychosis was tested using linear regression (controlling for age, sex and education level). Result Overall, there was little evidence of a substantial impact of MBI‐psychosis on CGT scores. Our study was powered to detect medium effect sizes. We found modest evidence of higher risk taking associated with more severe MBI‐psychosis scores (β = ‐0.1, SE = 0.05, p = 0.04) but this did not survive multiple testing correction. Conclusion This is the first time a specialist decision making and risk‐taking test has been conducted in MBI‐psychosis. Although MBI‐psychosis is associated with a range of cognitive impairments in later‐life and dementia risk it appears that any shared neuropsychological basis with other psychoses is limited (though we cannot rule out a small non‐clinically significant effect size). This has possible implications for the diagnostic classification of later‐life onset mild psychotic symptoms.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".