The independent contribution of executive functions to health related quality of life in older women
Bibliographic record
Abstract
BACKGROUND: Cognition is a multidimensional construct and to our knowledge, no previous studies have examined the independent contribution of specific domains of cognition to health related quality of life. To determine whether executive functions are independently associated with health related quality of life assessed using Quality Adjusted Life Years (QALYs) calculated from the EuroQol EQ-5D (EQ-5D) in older women after adjusting for known covariates, including global cognition. Therefore, we conducted a secondary analysis of community-dwelling older women aged 65-75 years who participated in a 12-month randomized controlled trial of resistance training. We assessed global cognition using the Mini-Mental State Examination (MMSE) and executive functions using the: 1) Stroop Test; 2) Trail Making Test (Part B) and 3) Digits Verbal Span Backwards Test. We calculated QALYs from the EQ-5D administered at baseline, 6 months and 12 months. RESULTS: Our multivariate linear regression model demonstrated the specific executive processes of set shifting and working memory, as measured by Trail Making Test (Part B) and Digits Verbal Span Backward Test (p < 0.01) respectively, were independently associated with QALYs after accounting for age, comorbidities, general mobility, and global cognition. The final model explained 50% of the variation in QALYs. CONCLUSIONS: Our study highlights the specific executive processes of set shifting and working memory were independently associated with QALYs -- a measure of health related quality of life. Given that executive functions explain variability in QALYs, clinicians may need to consider assessing executive functions when measuring health related quality of life. Further, the EQ-5D may be used to track changes in health status over time and serve as a screening tool for clinicians.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".