Communities and service providers address access to perinatal care in postconflict Northern Uganda: socialising evidence for participatory action
Bibliographic record
Abstract
OBJECTIVES: Describe participatory codesign of interventions to improve access to perinatal care services in Northern Uganda. STUDY DESIGN: Mixed-methods participatory research to codesign increased access to perinatal care. Fuzzy cognitive mapping, focus groups and a household survey identified and documented the extent of obstructions to access. Deliberative dialogue focused stakeholder discussions of this evidence to address the obstacles to access. Most significant change stories explored the participant experience of this process. SETTING: Three parishes in Nwoya district in the Gulu region, Northern Uganda. PARTICIPANTS: Purposively sampled groups of women, men, female youth, male youth, community health workers, traditional midwives and service providers. Each of seven stakeholder categories included 5-8 participants in each of three parishes. RESULTS: Stakeholders identified several obstructions to accessing perinatal care: lack of savings in preparation for childbirth in facility costs, lack of male support and poor service provider attitudes. They suggested joining saving groups, practising saving money and income generation to address the short-term financial shortfall.They recommended increasing spousal awareness of perinatal care and they proposed improving service provider attitudes. Participants described their own improved care-seeking behaviour and patient-provider relationships as short-term gains of the codesign. CONCLUSION: Participatory service improvement is feasible and acceptable in postconflict settings like Northern Uganda. Engaging communities in identifying perinatal service delivery issues and reflecting on local evidence about these issues generate workable community-led solutions and increases trust between community members and service providers.
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 | 0.068 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.019 |
| Research integrity | 0.004 | 0.003 |
| 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".