TELEPHONE-BASED COGNITIVE ASSESSMENTS IN A LARGE, MULTISITE RCT: THE COSMOS-MIND STUDY
Bibliographic record
Abstract
Abstract Identifying safe, affordable, and well-tolerated interventions that prevent or delay cognitive decline in older adults is of critical importance. There is growing evidence from basic science and small randomized trials that cocoa flavanols may provide protection against this decline. Funded by the NIA, COSMOS-Mind is an ancillary study of COSMOS and was designed to add cognitive outcomes to the parent study, a 2x2 factorial randomized controlled trial testing the effects of cocoa flavanols (600 mg/d) and a multivitamin with matching placebo on cardiovascular disease and cancer endpoints. A validated telephone-based protocol conducted at baseline and then annually for three years measures attention, memory, language, executive function, and global cognitive functioning in 2,262 women and men, ages 65 and older without insulin-dependent diabetes. Cases of mild cognitive impairment and Alzheimer’s and related dementias will be centrally adjudicated. For participants who score below a pre-specified threshold on a test of global cognition, a study partner is interviewed to obtain additional information regarding cognitive and functional status. With >5,000 interviews completed, this presentation will describe the cognitive battery, operational procedures used to ensure high data fidelity, and strategies employed that have maintained retention at >90%. Our experiences in COSMOS-Mind can inform the design and implementation of other large, multi-site RCTs and epidemiological studies. Telephone-based assessments of cognitive function are a cost-efficient method for assessing cognitive function.
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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 | 0.043 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".