Personality Traits and Existential Concerns as Predictors of the Functions of Reminiscence in Older Adults
Bibliographic record
Abstract
This study examines to what extent personality and existential constructs predict the frequency of reminiscence, in general, and its various functions, in particular. Eighty-nine older adults completed the NEO-Five Factor Inventory, the Life Attitude Profile--Revised, and the Reminiscence Functions Scale. Neuroticism predicted total reminiscence frequency, as well as reminiscence for self-understanding and ruminating about a negative past. Extraversion predicted total reminiscence frequency, as well as reminiscence for generating stimulation, conversation, and maintaining memories of departed loved ones. Openness to experience predicted total reminiscence frequency and reminiscence for addressing life meaning and death. Existential concerns, and in particular low desire to seek new challenges, added significant additional predictive power for total reminiscence frequency and for such uses as generating stimulation, preparing for death, and ruminating about the past. The discussion draws the implications of the finding that the combination of personality traits and existential concerns predicted the overall reminiscence frequency together with the intrapersonal functions of reminiscence.
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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 | 0.007 |
| 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) | 0.001 | 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".