Investigating the longevity of real-world memory following a smartphone intervention in older adults: A multi-year follow-up study
Bibliographic record
Abstract
Our ability to re-experience the events from our personal past tends to decline with age, which can have profound effects on well-being. HippoCamera is a smartphone-based application developed to mitigate age-related decline by guiding users to record and review cues for real-world events using established mnemonic strategies, with previous work demonstrating improved episodic recollection and enhanced hippocampal activity following use. Here, we followed-up with older adult participants who had used HippoCamera several years prior to investigate whether any benefits persisted following use. Using a mixed-methods approach, we found stronger subjective re-experiencing of events that were recorded with HippoCamera compared to those that were not. Further, participants reported extended benefits to their overall sense of meaning and well-being. These results provide preliminary evidence characterizing the long-lasting effects of a smartphone-based tool that improves memory for everyday events in aging.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".