Conceptualisation of African primal health care within mental health care
Bibliographic record
Abstract
BACKGROUND: It is believed by western education systems that the first contact should be with the nurse in primary health care. However, it is not the case. Therefore, the researcher attempts to correct this misconception by conceptualising the correct beginning of health seeking behaviour in an indigenous African community, namely African Primal Health Care (APHC). 'Primal' was coined during a colloquium by Dr Mbulawa and Seboka team members; however no formal conceptualisation took place, only operational definition. Due to the study scope, conceptualisation is narrowed to mental health, but this concept is applicable in the broader health context. The research purpose was to contribute to the body of indigenous knowledge systems to advocate towards co-existence of primal health care and mental health care. AIM: Formulate APHC within a mental health care context. OBJECTIVES: To explore philosophical grounding of APHC and describe epistemology of APHC. To analyse and crystallise the exploration to establish understanding within mental health and conceptualise APHC within mental health care to enhance co-existence. METHODOLOGY: Narrative synthesis, concept analysis (qualitative design). Lekgotla was used as a method of data collection and data were analysed using Leedy and Ormrod's five steps of data analysis. RESULTS: APHC is a health care system that existed in Africa prior to the introduction of the western health care system. It is based on the African belief system and practices. The practices come from the community, for the community and are authenticated by the community. APHC uses a holistic approach and the family and community are involved in the healing process.
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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 | 0.013 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.053 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| 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".