Learning sung lyrics aids retention in normal ageing and Alzheimer's disease
Bibliographic record
Abstract
Previous studies have suggested that presenting to-be-memorised lyrics in a singing mode, instead of a speaking mode, may facilitate learning and retention in normal adults. In this study, seven healthy older adults and eight participants with mild Alzheimer's disease (AD) learned and memorised lyrics that were either sung or spoken. We measured the percentage of words recalled from these lyrics immediately and after 10 minutes. Moreover, in AD participants, we tested the effect of successive learning episodes for one spoken and one sung excerpt, as well as long-term retention after a four week delay. Sung conditions did not influence lyrics recall in immediate recall but increased delayed recall for both groups. In AD, learning slopes for sung and spoken lyrics did not show a significant difference across successive learning episodes. However, sung lyrics showed a slight advantage over spoken ones after a four week delay. These results suggest that singing may increase the load of initial learning but improve long-term retention of newly acquired verbal information. We further propose some recommendations on how to maximise these effects and make them relevant for therapeutic applications.
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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 | 0.000 |
| 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".