When can research from one setting be useful in another? Understanding perceptions of the applicability and transferability of research
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Determining whether research findings from one setting are relevant to another is complex and poorly understood. This study aimed to explore the factors affecting whether research from other settings was perceived to be of potential use to those working in or researching maternal health in Ghana. Semi-structured interviews were conducted with 69 purposively sampled government decision-makers, researchers and other stakeholders working in maternal health in Ghana in 2008-09. The most influential factors affecting perceptions of applicability/transferability were the study's congruence with interviewees' previous experiences and beliefs. Interventions' adaptability was also considered crucial (and more important than remaining faithful to the original intervention). However, it was frequently considered a distinct stage in the research use process rather than a consideration of applicability/transferability. More attention was paid to the implementability of the intervention in the new setting, than to whether it would be as effective there. Interpretations of intervention descriptions and evaluation findings varied between interviewees, even when the same information was presented. This study is one of the first to explore perceptions of applicability/transferability of public health research among researchers and potential research users in a low-income setting. The findings suggest that existing frameworks of applicability/transferability do not reflect the factors considered to be most important in Ghana.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.030 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it