P1‐138: Alzheimer's disease and the ability to speak of self‐as‐agent in future contexts: description and analysis
Bibliographic record
Abstract
Alzheimer's disease (AD) can impair agency, reflected in, for instance, reduced ability to plan and carry out (instrumental) activities of daily living. Several related neural systems may contribute to impaired agency in AD: episodic memory impairments may affect recall of plans; degradation of semantic systems may alter representations of component activities for carrying out plans; executive function deficits may compromise forming or carrying out plans. Relatedly, people with AD seldom speak of themselves as agents in future contexts (e.g. “Tomorrow I'm going to visit my daughter”). To aid understanding everyday behavioural correlates of neural dysfunction in AD, we investigated whether treatment response correlates with ability to respond to simple questions about plans for the future. This is a retrospective analysis of videos recorded in a placebo-controlled, double-blind trial of galantamine [CMAJ 2006; 174(8): 1099-105]. Participants had mild/moderate AD. A novel “evaluation of memory and temporality” (EMT) test was recorded for a subset (74 at baseline, 63 with follow-up). To investigate participants’ ability to speak of themselves as agents in the future, we coded whether responses to eight simple, future-directed questions were unequivocally informative, negative or confabulated. We correlated EMT responses with the trial's outcome measures, ADAS-cog 11, CIBIC-plus, and GAS, and also with sub-components of these measures to investigate the contributions of episodic and semantic memory and executive function to response patterns. In the 35 participants examined to date, all responded positively to at least one question in one interview. Although there does not appear to be an absolute inability to conceptualize oneself as a future agent, the time frames may affect responses: at baseline, 32 participants answered “what are you going to do in the next few minutes ?” positively. By contrast, 21 responded positively to “What are you going to do the day after tomorrow?”. Half of positive responses were equivocal. At eight months, there were 15% fewer positive responses. Simple questions about future activities may be sensitive to change in AD and might help measure treatment response.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.019 | 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".