Identifying what matters to adults with mobility limitations regarding their experiences with medications: A concept mapping study
Bibliographic record
Abstract
BACKGROUND: Despite the high prevalence of medication use among persons with mobility limitations, there are currently no patient-reported measures that have been co-developed to assess the experiences of medications in everyday life. Therefore, the objective of this study was to develop potential items for a patient-reported experience measure related to medication use for adults with mobility limitations. METHODS: We conducted a concept mapping study with people with mobility limitations. Participants were required to: be 18 years of age or older, live in Canada, live in the community, speak, and read English or French, have a mobility limitation, and take at least one medication recommended by a prescriber in the preceding three months. Participants generated statements in response to the focal prompt: what matters to you about medications in your everyday life? Participants then sorted piles of statements based on their conceptual similarity, rated each statement on two dimensions (importance and realistic), and created visual maps of the data. RESULTS: A total of 45 individuals participated in at least one step of the concept mapping. Participants generated 694 statements which were synthesized into 80 unique statements. The final map contained ten clusters: (1) medication-related financial considerations and support; (2) pharmacy-related services and supports; (3) access to medications and medication-related supports; (4) acceptance and stigma around medication use; (5) ability and ease of taking medications; (6) shared decision-making and access to medication-related research and information; (7) medication effectiveness, side effects and risks; (8) knowledge, self-awareness and empowerment; (9) accessibility of healthcare providers; and (10) communication and relationships with healthcare providers. CONCLUSIONS: In this participatory-based research, we have identified key items and domains related to medication-related experiences. Understanding what matters to patients will support quality improvement of healthcare delivery and outcomes for adults with mobility limitations who take medications.
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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 | 0.012 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".