Psychometric Evaluation and Workflow Integration Study of a Tablet-Based Tool to Detect Mild Cognitive Impairment in Older Adults: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: With the rapid aging of the global population, experts anticipate a surge in the prevalence of mild cognitive impairment (MCI) and dementia worldwide. It is argued that developing more sensitive, easy to administer, and valid MCI screening tools for use in primary care settings may initiate timely clinical and personal care planning and treatment, enabling early access to programs and services. Including functional competence measures in screening tests makes them more ecologically valid and may help to identify cognitive deficits at an earlier stage. OBJECTIVE: We aim to conduct a preliminary evaluative study comparing the sensitivity, specificity, and reliability of the BrainFx Screen (referred to as SCREEN hereafter), a novel digital tool designed to assess functional competence and detect early signs of cognitive impairment, with the Quick Mild Cognitive Impairment, a validated and highly sensitive tool that detects MCI in the older adult population. We will also investigate the perceived usefulness and integration of the SCREEN into primary care practice to identify demonstrable impacts on clinical workflow and health care providers' (HCP) perceptions of its success as a screening tool. Patients' perceptions of completing the SCREEN and its impact on their quality of life will also be explored. METHODS: This study has a concurrent, mixed methods, prospective, and quasi-experimental design. Participants will be recruited from 5 primary care family health teams (FHTs; defined by multidisciplinary practice and capitated funding) across southwestern Ontario, Canada. Participants will include HCPs, patients, care partners, and FHT administrative executives. Patients 55 years and older with no history of diagnoses for MCI, dementia, or Alzheimer disease rostered in one of the FHTs participating in the study will be eligible to participate. Their care partners will help triangulate the qualitative data collected from patients. Participating FHTs will identify an occupational therapist from their site to participate in the study; this HCP will both administer the research protocol and participate in semistructured in-depth interviews and questionnaires. Principal component analysis will be conducted on the SCREEN data to understand the test components better. Tests comparing sensitivity, specificity, and test-retest reliability will assess the validity of SCREEN as a screening tool for MCI. RESULTS: This paper describes the study protocol and its activities to date. Data collection was halted early because of COVID-19 restrictions on research activity, and data analysis is currently in progress. CONCLUSIONS: At the end of the project, we anticipate having an initial comparative evaluation of the SCREEN as a tool for early detection of MCI in primary care older adult patient populations. Resource constraints on this research study limit our ability to conduct a randomized controlled trial; however, the results will assist developers of the SCREEN in determining whether rigorous controlled testing is warranted. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25520.
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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 | 0.052 | 0.040 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".