Susceptibility to retroactive interference: The effect of context as a function of age and cognition
Bibliographic record
Abstract
Previous studies have shown that contextual cues improve memory performance and reduce interference in younger adults. However, it is not clear whether middle-aged and older adults can also benefit from contextual cues, or if this ability diminishes with ageing and cognitive decline. In order to test this question, we tested 69 middle-aged adults (aged 30-50 years) and 65 older adults (aged 65-85). Participants completed a retroactive interference paradigm with or without contextual cues. Cognitive functioning of older adults was assessed using the Montreal Cognitive Assessment, which is a sensitive and highly validated tool to detect cognitive decline in older age. The results showed that while middle-aged adults were able to benefit from context to improve recognition and reduce interference, older adults were not able to benefit from it. However, when we compared older adults with lower (<26) and higher (≥26) scores on the Montreal Cognitive Assessment, we found that older adults with high cognitive functioning could benefit from context advantage at retrieval to improve recognition compared to those with lower cognitive functioning. Yet, similar to older adults with lower cognitive functioning, they could not benefit from context advantage at encoding and hence were still susceptible to interference.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".