<p>Spaced Retrieval and Episodic Memory Training in Alzheimer’s Disease</p>
Bibliographic record
Abstract
INTRODUCTION: This study replicated and extended the findings from the author's previous pilot study to further explore how a spaced retrieval (SR) memory training program might be effectively applied to help persons with Alzheimer's disease (AD) improve both short- and long-term recall of recent episodic events. METHODS: A quasi-experimental within-subject group study was conducted with 15 participants with a diagnosis of AD. RESULTS: Compared to a control condition, all participants were able to spontaneously recall significantly more specific details about trained events, and their recall was significantly enhanced when they were provided with cues. Although the findings indicated that people with AD were able to encode information during training, recall gains diminished by the end of the maintenance period. DISCUSSION: This study provides evidence that individuals with mild to moderate AD can learn and recall new episodic information through SR training. These findings support the use of SR as an intervention tool to help individuals maintain their functioning in episodic recent memory. However, more research into maintaining the long-term recall of recent episodic events is warranted.
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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 | 0.001 |
| 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 | 0.000 |
| 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".