Utility of Qualitative Research Findings in Evidence‐Based Public Health Practice
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
Epidemiological data, derived from quantitative studies, provide important information about the causes, prevalence, risk correlates, treatment and prevention of diseases, and health issues at a population level. However, public health issues are complex in nature and quantitative research findings are insufficient to support practitioners and administrators in making evidence-informed decisions. Upshur's Synthetic Model of Evidence (2001) situates qualitative research findings as a credible source of evidence for public health practice. This article answers the following questions: (1) where does qualitative research fit within the paradigm of evidence-based practice and (2) how can qualitative research be used by public health professionals? Strategies for using qualitative research findings instrumentally, conceptually, and symbolically are identified by applying Estabrooks' (1999) conceptual structure of research utilization. Different research utilization strategies are illustrated through the use of research examples from the field of work on intimate partner violence against women. Recommendations for qualitative researchers disseminating findings and for public health practitioners/policy makers considering the use of qualitative findings as evidence to inform decisions are provided.
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 | 0.283 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.006 | 0.013 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.007 |
| 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