Preserving Self: Medication‐Taking Practices and Preferences of Older Adults With Multiple Chronic Medical Conditions
Bibliographic record
Abstract
PURPOSE: To examine the experiences of older adults with multiple chronic medical conditions when a new medication was added to their existing multiple medication regimen. DESIGN: A multimethod qualitative design was used. Thirty adults 60 years of age with (a) at least three chronic medical diagnoses, (b) at least five medications at baseline, and (c) a new medication prescription were enrolled in a prospective study of 30 days duration, participating from their homes. METHODS: In-depth hermeneutic interviews (2 per 15 participants) and self-assessment diaries recorded on electronic tablets (daily per 30 participants) were completed. Transcribed interviews and self-recorded survey data were analyzed using hermeneutical analysis and ecological momentary assessment and content analysis, respectively. FINDINGS: Common reasons participants did not take medications as prescribed included tolerability, transportation, access to medications, and forgetting. The overarching pattern, "preserving self," was supported by two patterns that subsumed several themes: (a) engaging the powerful hold of my illness, and (b) engaging providers in visioning health. CONCLUSIONS: A deeper understanding of the impact of receiving a new prescription and of managing medication reveals the challenges patients experience in preserving a sense of self. Healthcare providers of all disciplines should understand the meaning of medication prescribing and medication taking to ameliorate medication-taking difficulties. CLINICAL RELEVANCE: The provider-patient relationship is often cited as an area that needs to be addressed in healthcare practice. Our study emphasized the patients' voices and their profound needs around medication management. The emphasis on preservation of self is an important finding that focalizes the concern.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".