Updating the positivity bias in older adults: how do subjective memory complaints influence emotional distraction in a working memory task?
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Subjective memory complaints (SMCs), commonly reported by older adults, refer to self-perceived difficulties with memory. While the link between SMCs and objective cognitive decline remains unclear, SMCs may reflect subtle cognitive changes, particularly in working memory, which is known to be influenced by emotional context. Older adults typically display a positivity bias, which is a tendency to focus more on and better remember positive over negative information. However, the positivity bias has yet to be explored in individuals with SMCs. This study aims to address this gap by examining how emotional distractors affect working memory performance in older adults with varying levels of SMCs. METHOD: Forty-seven older adults (ages 55-79) were categorized into low and high SMCs groups based on self-reported memory complaints. Participants completed an emotional n-back task with three levels of cognitive load (0-back, 1-back, 2-back) and emotional distractors (positive, negative, neutral). Task performance was measured using accuracy, response bias, and reaction times. Mixed-design ANOVAs were conducted, with cognitive load, emotional condition, and complaint group as factors. RESULTS: Results revealed significant main effects of cognitive load on performance, with performance declining as task demands increased. A three-way interaction between cognitive load, emotional condition, and complaint group showed that participants with high SMCs were more distracted by positive stimuli under high cognitive load, leading to decreased accuracy. In contrast, participants with low SMCs showed reduced accuracy with positive distractors under low cognitive load. CONCLUSIONS: These findings suggest that emotional distractors, particularly positive ones, affect working memory performance differently in older adults depending on their level of SMCs. Future research should aim to uncover the mechanisms underlying theses effects.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it