International Differences in Nursing Research, 2005–2006
Bibliographic record
Abstract
PURPOSE: To compare the characteristics of nursing research being done in different countries, using data from studies published in nonspecialty, English-language nursing journals. DESIGN: Data for this cross-sectional analysis were retrieved from a consecutive sample of 1,072 studies published in eight leading English-language research journals in 2005 and 2006. METHODS: For each study, data were extracted on the characteristics of the study participants and authors, study focus-specialty area, funding, and methodologic attributes. Studies from 15 countries or regional groupings were compared. FINDINGS: International differences in authors, participants, and study characteristics were typically large and statistically significant. Studies that were focused on nurses were especially prevalent in Europe, Australia, and Canada, whereas patient-centered studies were most common in Asian countries and the US. Qualitative studies were predominant in Norway, Sweden, and the UK. Asian nurse researchers, by contrast, undertook mostly quantitative studies, and were especially likely to conduct intervention research. Significant country differences existed in the omission of demographic (age and sex) information about participants, with omissions most prevalent in the UK and Ireland and least prevalent in Asian countries. Research funding was reported for 62% of all studies, ranging from 13% in Turkey to over 75% in Canada and the US. CONCLUSIONS: Although this study had several limitations, especially with regard to potential biases in the sample of studies from non-English-speaking countries, this analysis of over 1,000 nursing studies indicates many important inter-country differences in the focus, methods, and authorship patterns of nursing research published in leading journals. CLINICAL RELEVANCE: Because research "informs" practice, international differences that exist in the focus and methods of nursing research have implications for nursing practice in the respective countries.
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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 | 0.035 | 0.084 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 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".