Group interviews in primary care research: advancing the state of the art or ritualized research?
Bibliographic record
Abstract
BACKGROUND: Focus groups have become an important data gathering technique in primary care research. OBJECTIVES: This study provides an integrated review of recent articles that used focus groups as a data collection method to gather information from family physicians. METHODS: Medline was searched for articles that used focus groups with family physicians in a North American setting during the 1990s. Articles that met this criteria were critically evaluated to determine who participated, the number of groups conducted, setting, length, inclusion and exclusion criteria, sampling technique and whether the groups were used as part of a larger study. RESULTS: The twenty articles discussed herein revealed tremendous variation in how focus group research is conducted and reported. CONCLUSIONS: Focus group research is a popular form of qualitative research in primary care research. Journals reporting qualitative research should require that certain basic information be present, thereby advancing the state of the art and permitting readers to better evaluate these articles.
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 | 0.263 | 0.231 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.012 | 0.020 |
| Science and technology studies | 0.006 | 0.039 |
| Scholarly communication | 0.020 | 0.036 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.010 | 0.006 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".