DEVELOPMENT AND VALIDATION OF THE NOVEL MEDICATION TAKING INSTRUMENT - FOUR FACETS OF ADHERENCE (MTI-4)
Bibliographic record
Abstract
Abstract Medication adherence is critical for disease management among aging African-Americans who are at greatest risk for poor adherence and affliction with chronic diseases. However, medication adherence is a complex behavior with distinct facets (frequency, pattern of adherence, barriers, and beliefs related to adherence), which current instruments cannot comprehensively measure in this underrepresented population. The Medication Taking Instrument – Four Facets of Adherence is an instrument developed to measure all facets of adherence among diverse, community-dwelling aging adults using the innovative application of the “Nursing Rights” of medication administration. Items were developed following a scoping review of the literature. Validation was obtained from medical professionals in Canada and the United States who prescribe medications to diverse patient populations. 12 of 13 medical professionals responded to the survey request (67% Nurse Practitioners, 33% Physicians) and rated each item (0=Low Agreement to 5=High Agreement) for clarity and validity of each item representing the specific facet. Most instrument items obtained high agreement (response rating > 3) for both validity and clarity from 83% or more of respondents. Experts’ feedback augmented items for two facets (barriers and beliefs), improved clarity, minimized jargon, and supported instrument use in the clinical setting. The resulting instrument will comprehensively characterize medication adherence, direct more targeted research aims, and guide interventions to augment adherence among aging African Americans. Ongoing data collection in the Detroit Aging Brain Study will provide additional tests of factor structure, internal scale reliability, and convergent validity using other indicators of medication history and symptom control.
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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 | 0.030 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".