A scoping review of clinical communication in cancer care in Africa
Bibliographic record
Abstract
BACKGROUND: Cancer care involves disclosing difficult information, making treatment decisions, and advance care planning. Communication practices and preferences are strongly influenced by sociocultural context. This scoping review aims to identify, map, and appraise the available evidence on clinical communication in cancer care in Africa and recommend priorities for future work. METHODS: A search strategy was developed to identify studies conducted in Africa with a primary focus on patient-clinician communication in cancer care and performed in PubMed, Embase, Web of Science, CINAHL, African Index Medicus, and PsycINFO. Two reviewers independently screened titles and abstracts, full texts, and cited references. Study characteristics were analyzed using descriptive statistics and content analysis. Critical appraisal was performed using the Mixed Methods Appraisal Tool. RESULTS: Our search yielded 58 articles from 19 countries. Study designs were quantitative survey (53%), qualitative (38%), non-randomized experimental (5%), and mixed methods (3%), with no randomized trials. Populations included patients with cancer (n = 25), doctors (n = 24), nurses (n = 16), family/caregivers (n = 16), and/or others. Seven studies (12%) focused on pediatrics. Most studies (60%) focused on clinicians' disclosure of information, often framed as "breaking bad news" or "truth-telling." The remainder focused on information preferences (14%), advance care planning (10%), illness understanding (5%), shared decision making (5%), and communication training (3%). Critical appraisal demonstrated higher quality among qualitative than quantitative studies. CONCLUSIONS: Future work should explore underexamined research areas such as patient-centered communication, translate observational findings into intervention development and testing, implement communication skills training, and evaluate outcomes related to communication in cancer care in Africa.
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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 | 0.022 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.032 | 0.033 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".