Assessing What Matters Most in Older Adults With Multicomplexity
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Abilities and activities that are often simultaneously valued may not be simultaneously achievable for older adults with multicomplexity. Because of this, the Geriatrics 5Ms framework prioritizes care on "what matters most." This study aimed to evaluate and refine the What Matters Most-Structured Tool (WMM-ST). RESEARCH DESIGN AND METHODS: About 105 older adults with an average of 4 chronic conditions completed the WMM-ST along with open-ended questions from the Serious Illness Conversation Guide. Participants also provided demographic and social information, completed cognitive screening with the Telephone-Montreal Cognitive Assessment-Short and frailty screening with the Frail scale. Quantitative and qualitative analyses aimed to (a) describe values; (b) evaluate the association of patient characteristics with values; and (c) assess validity via the tool's acceptability, educational bias, and content accuracy. RESULTS: Older adults varied in what matters most. Ratings demonstrated modest associations with social support, religiosity, cognition, and frailty, but not with age or education. The WMM-ST was rated as understandable (86%) and applicable to their current situation (61%) independent of education. Qualitative analyses supported the content validity of WMM-ST, while revealing additional content. DISCUSSION AND IMPLICATIONS: It is possible to assess what matters most to older adults with multicomplexity using a structured tool. Such tools may be useful in making an abstract process clearer but require further validation in diverse samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".