The caring experiences of family caregivers for patients with advanced cancer in Uganda: A qualitative study
Bibliographic record
Abstract
BACKGROUND: Cancer morbidity and mortality is rising in sub-Saharan Africa. Given this rise, family caregivers play an integral role in provision of quality cancer care services. This study explored the family caregivers (FCGs)/relatives' experiences of caring for patients with advanced cancer (stage 3 or stage 4) in Uganda. METHODS: This was a descriptive qualitative study exploring the lived experiences of FCGs of patients with advanced cancer attending care at the Uganda cancer institute. We purposively recruited twelve FCGs and conducted face-to-face in-depth interviews using an interviewer-guided semi-structured questionnaire. Data were analyzed by thematic analysis. RESULTS: The age range of participants was 19 to 49 years. Most participants were children of the patients (n = 7), had attained tertiary education (n = 7), and had taken care of their loved ones for at least one year (n = 10). Six themes emerged from data analysis; (i) caring roles, (ii) caring burdens, (iii) role conflict, (iv) health system tensions, (v) support and motivation, (vi) caring benefits, lessons and recommendations. CONCLUSION: Study findings highlight the fundamental role of FCGs in the care of their loved ones, and illuminate the neglected physical, psychological and social challenges of family caregivers amidst health system tensions and conflicting roles. The needs of family caregivers should be embedded within cancer care, prevention and control programs particularly in low resource settings.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".