Evaluating the research capacity and culture amongst staff at a tertiary level teaching hospital in Rwanda
Bibliographic record
Abstract
BACKGROUND: Building research capacity can strengthen health systems through evidence-based interventions. However, evaluating the current research capacity and increasing it is a layered process that needs to consider different institutional structures, as well as internal factors. This study collects baseline data on the research capacity and culture at King Faisal Hospital Rwanda (KFH), a tertiary-level teaching hospital in Rwanda. It also proposes ways to further strengthen it and recommends ways for other institutions in Rwanda to strengthen research capacity. METHODS: The Research Capacity and Culture Tool was distributed to full-time clinical and non-clinical KFH staff in September 2021. Participants were required to hold a position that minimally requires an Advanced Diploma. The quantitative survey data were analyzed in SPSS Version 27 and analyzed via descriptive statistics across all domains, including the individual, organizational, and team levels. FINDINGS: 152 participants completed the questionnaire. On a 5-point Likert scale, the highest ranked skills were designing questionnaires (3.34) and using digital referencing systems (3.29), while the lowest ranked skills were securing research funding (2.40) and writing for publication in peer-reviewed journals (2.46). Perceptions about the organizational level's research system were overall stronger than those at the team level, with the weakest team-level system being having regular research forums and bulletins (2.14) and having digital tools for conducting research (2.14). Motivators to conducting research included skills development (87%) and career advancement (74%), while barriers included a lack of time (64%) and access to funding (56%). DISCUSSION: To strengthen the research capacity and culture at KFH, focus should be on allocating tools, resources, and training opportunities to staff. Research should be integrated into staff job descriptions, with a time audit conducted to ensure they have adequate time for these activities. Finally, decentralizing research and ensuring team-level ownership will help with staff buy in.
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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 | 0.023 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".