Nigerian Health Care Providers and Diabetes Self-Management Support: Their Perspectives and Practices
Bibliographic record
Abstract
Nigeria struggles to reframe its traditional acute-care disease approach to health care to accommodate rising needs for chronic disease care. This interpretive descriptive study explored Nigerian healthcare providers' (HCPs) perspectives, experiences, and practices related to self-management support (SMS). Observational and experiential data were gathered from 19 HCPs at two urban hospitals in Southeastern Nigeria (seven physicians, four nurses, five dietitians/nutritionists, and three health educators). There were four themes: (a) compliance-oriented medical model, (b) SMS as advice, informal counseling, and education, (c) navigating the sociocultural terrain, and (d) workarounds. Nigerian HCPs perspectives and SMS practices were characterized by attempts to foster compliance with healthcare instructions within a traditional biomedical model. Participants enhanced patient support using specific strategies to bypass structural system obstacles. These findings demonstrate the need to reevaluate the current understanding of SMS in Nigeria and its practice.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".