Using a supportive care framework to understand and improve palliative care among cancer patients in Africa
Bibliographic record
Abstract
OBJECTIVE: Cancer incidence and mortality are increasing in Africa, which is leading to greater demands for palliative care. There has been little progress in terms of research, pain management, and policies related to palliative care. Palliative care in Africa is scarce and scattered, with most African nations lacking the basic services. To address these needs, a guiding framework that identifies care needs and directs palliative care services could be utilized. Therefore, using the supportive care framework developed by Fitch (Fitch, 2009), we here review the literature on palliative care for patients diagnosed with cancer in Africa and make recommendations for improvement. METHOD: The PubMed, Scopus, CINAHL, Web of Science, Embase, PsycINFO, Social Sciences Citation Index, and Medline databases were searched. Some 25 English articles on research from African countries published between 2004 and 2014 were selected and reviewed. The reviewed literature was analyzed and presented using the domains of the supportive care framework. RESULTS: Palliative care patients with cancer in Africa, their families, and caregivers experience increasing psychological, physical, social, spiritual, emotional, informational, and practical needs. Care needs are often inadequately addressed because of a lack of awareness as well as deficient and scattered palliative care services and resources. In addition, there is sparse research, education, and policies that address the dire situation in palliative care. SIGNIFICANCE OF RESULTS: Our review findings add to the existing body of knowledge demonstrating that palliative care patients with cancer in Africa experience disturbing care needs in all domains of the supportive care framework. To better assess and address these needs, holistic palliative care that is multidomain and multi-professional could be utilized. This approach needs to be individualized and to offer better access to services and information. In addition, research, education, and policies around palliative care for cancer patients in Africa could be more comprehensive if they were based on the domains of the supportive care framework.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".