Pain in Homebound Older Adults with Heart Failure after Hospital Discharge
Bibliographic record
Abstract
Pain is not uncommon in older adult patients with heart failure (HF) and has been identified as a risk factor for rehospitalization of homebound patients with HF. Little is known about the pain experiences and management of older adults with HF after hospital discharge. We sought to describe pain and other symptoms among homebound older adults with HF using a qualitative and descriptive approach. We conducted semistructured interviews to obtain qualitative data and used the Brief Pain Instrument-Short Form and the Edmonton Symptom Assessment Scale to obtain descriptive data on symptom burden. We interviewed 18 participants within 10 days after hospital discharge. Participants' mean age was 75.8 ± 9.0 years; 78% were White. The mean pain score at its worst was 5.2 ± 3.1, and for pain interfering with sleep was 4.3 ± 3.41. Most participants managed pain with medications. Using thematic analysis of qualitative data, we identified three distinct categories: (1) the diversity of patients' pain experiences, (2) the diversity of pain management routines, and (3) patients' experiences with healthcare providers' pain assessment and management practices. Our findings show that homebound older adults with HF experience various pain symptoms and receive inconsistent education about how to manage pain from healthcare providers. This study supports the need for better pain assessment and education about the appropriate use of pain medications and nonpharmacologic approaches to pain control for homebound older adults with HF.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".