Understanding the collaborative experience between researchers and health care practitioners:Implications for gerontological nursing practice
Bibliographic record
Abstract
The health care field is a new arena for collaborative research carried out by practitioner-researcher teams. Although the current literature discusses factors supportive of such teams, most evidence is anecdotal or descriptive of pilot projects. In this article, the authors use survey and interview data to document health care practitioners' views on collaborative research with an experienced researcher/ mentor. Topics covered include a description of the research project and process, positive and negative aspects of doing research, expectations, recommendations to colleagues starting research, and desirable characteristics in practitioners and researchers on collaborative research teams. Of all attributes mentioned, personal traits and skills were among the most frequently mentioned for both practitioners and researchers, followed by research knowledge and attitudes for practitioners, and teaching skills for researchers. The article also addresses factors important to the success of collaborative research: how to develop a project, characteristics of collaborative team members, team functioning, and institutional support.
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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 | 0.105 | 0.157 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.026 | 0.039 |
| Scholarly communication | 0.031 | 0.042 |
| Open science | 0.005 | 0.026 |
| Research integrity | 0.012 | 0.009 |
| 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; 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".