Perceptions of Cancer in Parents of Adolescent Daughters in Northwest Cameroon
Bibliographic record
Abstract
Background: Cancer is a rapidly rising cause of morbidity and mortality in sub-Saharan Africa. Cervical cancer, in particular, is still one of the leading causes of mortality for women in this setting. The uptake of healthcare services is in part influenced by patients’ belief systems. We sought to better understand the perception of cancer in the Kom tribe of Northwest Cameroon. Methods: A qualitative research study was completed using a semi-structured interview guide and one-on-one interviews with 45 parents of girls aged 9–14 years. These girls were candidates for free HPV vaccination to prevent cervical cancer. The interviews were recorded, transcribed, and analyzed using ATLAS.ti 9. Results: Thirty-five mothers and ten fathers with a median age of 42 yo were interviewed from Mbingo, Belo, Njinikom, and Fundong. Half of the parents were farmers, with three being herbalists or traditional medicine doctors. Seventy-seven percent had either no or only primary school education. None had had cancer. All knew at least one person with cancer. The most common word for cancer in the Kom language is “ngoissu”. It can refer to a bad infection or cancer. The occurrence of ngoissu is the result of either a curse placed on you, ancestral retribution, or transgressing the ngoulatta (snail shell spoken over and usually placed in a garden). The implications are that treatment of ngoissu must involve the traditional doctor who determines the spiritual issue and prescribes a remedy (like a herb or tea) and/or an incantation. Within the context of cancer, this can lead to a delay in diagnosis until the disease is no longer curable by conventional therapies. Conclusion: Ways to bridge biomedical healthcare services and traditional medicine are needed, especially in tribal contexts where the latter is an integral part of daily life.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".