Self-Reference Effect and Self-Reference Recollection Effect for Trait Adjectives in Amnestic Mild Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVES: The self-reference effect (SRE), enhanced memory for self-related information, has been studied in healthy young and older adults but has had little investigation in people with age-related memory disorders, such as amnestic mild cognitive impairment (aMCI). Self-referential encoding may help to improve episodic memory in aMCI. Additionally, self-referential processing has been shown to benefit recollection, the vivid re-experiencing of past events, a phenomenon that has been termed the self-reference recollection effect (SRRE; Conway & Dewhurst, 1995). Furthermore, it remains unclear whether the valence of stimuli influences the appearance of the SRE and SRRE. METHODS: The current study investigated the SRE and SRRE for trait adjective words in 20 individuals with aMCI and 30 healthy older adult controls. Ninety trait adjective words were allocated to self-reference, semantic, or structural encoding conditions; memory was later tested using a recognition test. RESULTS: While healthy older adults showed a SRE, individuals with aMCI did not benefit from self-referential encoding over and above that of semantic encoding (an effect of "deep encoding"). A similar pattern was apparent for the SRRE; healthy controls showed enhanced recollection for words encoded in the self-reference condition, while the aMCI group did not show specific benefit to recollection for self-referenced over semantically encoded items. No effects of valence were found. CONCLUSIONS: These results indicate that while memory for trait adjective words can be improved in aMCI with deep encoding strategies (whether self-reference or semantic), self-referencing does not provide an additional benefit. (JINS, 2018, 24, 821-832).
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 | 0.000 | 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".