Epilepsy Care in Zambia: A Study of Traditional Healers
Bibliographic record
Abstract
PURPOSE: Most people with epilepsy (PWE) reside in developing countries with limited access to medical care. In sub-Saharan Africa (SSA), traditional healers (THs) play a prominent role in caring for PWE, yet little is known about epilepsy care by THs. We conducted a multimethod, qualitative study to better understand the epilepsy care delivered by THs in Zambia. METHODS: We conducted focus-group discussions with THs, in-depth semistructured interviews with a well-recognized TH at his place of work, and multiple informal interviews with healthcare providers in rural Zambia. RESULTS: THs recognize the same symptoms that a neurologist elicits to characterize seizure onset (e.g., olfactory hallucinations, jacksonian march, automatisms). Although THs acknowledge a familial propensity for some seizures and endorse causes of symptomatic epilepsy, they believe witchcraft plays a central, provocative role in most seizures. Treatment is initiated after the first seizure and usually incorporates certain plant and animal products. Patients who do not experience further seizures are considered cured. Those who do not respond to therapy may be referred to other healers. Signs of concomitant systemic illness are the most common reason for referral to a hospital. As a consequence of this work, our local Epilepsy Care Team has developed a more collaborative relationship with THs in the region. CONCLUSIONS: THs obtain detailed event histories, are treatment focused, and may refer patients who have refractory seizures to therapy to other healers. Under some circumstances, they recognize a role for modern health care and refer patients to the hospital. Given their predominance as care providers for PWE, further understanding of their approach to care is important. Collaborative relationships between physicians and THs are needed if we hope to bridge the treatment gap in SSA.
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) | 0.001 | 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".