Emotion regulation in mild cognitive impairment and subjective cognitive decline
Bibliographic record
Abstract
Abstract Background Our previous research in emotional verbal memory in mild cognitive impairment (MCI) and work from others suggest the hypothesis that emotion dysregulation is a signature of Alzheimer’s disease (AD) risk. Whether subjective cognitive decline (SCD), conceptualized as a possible preclinical stage of AD, is associated with emotion dysregulation is unknown. In the current study, we compared responses on the Cognitive Emotion Regulation Questionnaire (CERQ) and behavioural responses on a threat task amongst SCD, MCI, and cognitively unimpaired (CU) older adults. Methods The sample included 146 older adults free of lifetime history of psychiatric illness/neurological conditions: 33 MCI [17F, age 72.3(SD7.6)] defined as subjective memory/other cognitive complaints, impaired neuropsychological (NP) test performance, and functional independence, 71 SCD [49F, age 71.1(SD6.3)] based on subjective memory decline with worry with normal NP performance, and 42 CU [27F, age 70.6(SD6.8)] based on absence of subjective memory decline and normal NP test scores. Participants completed the CERQ which assesses cognitive coping strategies in negative emotional situations. A subset (19 MCI, 43 SCD, 19 CU) completed a computerized task in which they rated a physical feature or threat level of faces with varying degrees of threat. Multivariate ANOVA was used to examine group differences, followed by Sidak‐adjusted post hoc comparisons. Results On the CERQ, groups differed in use of catastrophizing [F(2, 142)=3.51, P=.032], with a trend for use of rumination (P=.07), attributable to greater use of both strategies in MCI compared to CU (P=.04). On the threat task, groups differed in response latencies to judging physical features of threatening faces relative to neutral [F(2, 78)=3.17, P=.048)]. Relative to CU, SCD participants were slower to make physical judgements of threatening faces compared to neutral (P=.026). Conclusions Older adults with SCD do not report greater use of maladaptive emotion regulation strategies compared to CU. However, alterations in behavioural responses to threat versus neutral in SCD may represent deficits in regulating attention towards negative emotional information, similar to mood‐congruent cognitive biases observed in depression. These preliminary data highlight the need to increase our understanding of explicit and implicit emotional processing in older adults at risk for AD.
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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 | 0.003 |
| 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 | 0.000 |
| 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".