Managing One’s Symptoms
Bibliographic record
Abstract
BACKGROUND: African Americans endure disproportionately high advanced cancer rates and also are disproportionately represented in the lower socioeconomic strata. These individuals work to manage symptoms in order to function and have a satisfactory quality of life. OBJECTIVE: The purpose of this study was to discover what low-income African American adults with advanced cancer do on a day-to-day basis to relieve and manage symptoms. This study viewed the individuals as experts and asked them not what they are told to do, but rather what they actually do. METHODS: A purposive sample of 27 individuals participated in semistructured interviews conducted by 2 research interviewers. This qualitative descriptive approach used content analysis to develop themes to describe symptom self-management. RESULTS: Participants described 2 approaches: making continual adjustments and finding stability through spirituality. In seeking comfort from the distress of their symptoms, they were constantly altering their activities and fine-tuning strategies. They adjusted medical regimens and changed the speed and selection of daily activities, including comfort measures and diet modifications. In contrast, their spirituality was a consistent presence in their lives that provided balance to their unstable symptom experience. CONCLUSIONS: This study illustrates that people with advanced cancer actively engage in multiple complex self-management strategies in response to symptoms. IMPLICATIONS FOR PRACTICE: As providers assess how individuals manage their symptoms, they must find ways to support those efforts. Providers then will recognize the challenges faced by advanced cancer patients in obtaining the best quality of life while managing multiple symptoms, activities, and family responsibilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".