Quantified Self and Comprehensive Geriatric Assessment: Older Adults Are Able to Evaluate Their Own Health and Functional Status
Bibliographic record
Abstract
BACKGROUND: There is an increased interest of individuals in quantifying their own health and functional status. The aim of this study was to examine the concordance of answers to a self-administered questionnaire exploring health and functional status with information collected during a full clinical examination performed by a physician among cognitively healthy adults (CHI) and older patients with mild cognitive impairment (MCI) or mild-to-moderate Alzheimer disease (AD). METHODS: Based on cross-sectional design, a total of 60 older adults (20 CHI, 20 patients with MCI, and 20 patients with mild-to-moderate AD) were recruited in the memory clinic of Angers, France. All participants completed a self-administered questionnaire in paper format composed of 33 items exploring age, gender, nutrition, place of living, social resources, drugs daily taken, memory complaint, mood and general feeling, fatigue, activities of daily living, physical activity and history of falls. Participants then underwent a full clinical examination by a physician exploring the same domains. RESULTS: High concordance between the self-administered questionnaire and physician's clinical examination was showed. The few divergences were related to cognitive status, answers of AD and MCI patients to the self-administered questionnaire being less reliable than those of CHI. CONCLUSION: Older adults are able to evaluate their own health and functional status, regardless of their cognitive status. This result needs to be confirmed and opens new perspectives for the quantified self-trend and could be helpful in daily clinical practice of primary care.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".