Telephones in public health policy processes in sub-Saharan Africa: a scoping review
Bibliographic record
Abstract
Background The telephone is being put to work in the quest for universal health coverage in sub-Saharan Africa. Multiple mobile health pilot projects are being deployed. The use of mobile technologies including citizens in the formulation, analysis, and revision of public health policies in sub-Saharan Africa is recent. This citizen m-participation could influence the democratic engagement of citizens and leaders in the planning, budgeting, and transparency of local governance processes of health systems. Methods We conducted a scoping review. A total of 995 papers were initially identified, 37 documents were finally included in the final synthesis after a review of the abstract and full text by two researchers. Results Despite multiple challenges, the social, technological, and instrumental feasibility of citizen m-participation in health decision-making processes is real. The documents highlight the contribution of m-Citizen Participation to the ongoing construction of a robust health democracy. However, government commitment and leadership for this innovation remain weak. This slows down the processes of inclusion and empowerment of patients on their health needs. Conclusions Evidence suggests that citizen m-participation is relevant to the inclusion of citizens in health decision-making processes. However, research is limited. We recommend participatory action research mechanisms focused on citizen inclusion in health decision-making processes in sub-Saharan Africa to expand the knowledge base on this innovation.
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 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 | 0.011 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".