Characteristics of joint displays illustrating data integration in mixed‐methods nursing studies
Bibliographic record
Abstract
AIMS: To identify the characteristics of joint displays illustrating the data integration in mixed-methods nursing studies and to make recommendations for effective use of joint displays for the integration of qualitative and quantitative data in mixed-methods studies. DESIGN: Discussion Paper. DATA SOURCES: We have completed this paper as a part of a mixed-methods prevalence review of 190 studies published in nursing journals. We searched 10 nursing journals and three databases from January 2014-April 2018, additional journal search was performed from May-September 2018. We reviewed 17 studies that used joint displays as the method of data integration. Using a joint display typology, checklists, summary tables, and personal experiences of using joint displays, we evaluated the quality of displays. IMPLICATIONS FOR NURSING: Nurse researchers should use advanced data integration approaches to increase the rigour of the mixed-methods studies. Joint displays can enable nurse researchers to efficiently integrate and synthesize the qualitative and quantitative data in mixed-methods studies. However, nurse researchers should clearly label the type and title of the display, include both qualitative and quantitative data and interpretations, and highlight the mixed-methods interpretations as confirmed, divergent, or expanded in the displays. CONCLUSION: Joint displays are adopted for data integration in nursing mixed-methods studies. Improvements are required concerning data presentation in the displays. Researchers should provide clear titles and supporting data and inferences and identify the meta-inferences by assessing the fit between quantitative and qualitative data. IMPACT: Despite the importance of integration in mixed methods, reviews indicated a consistent lack of integration in nursing research. Joint displays are structured frameworks used for the integration and synthesis of the qualitative and quantitative data at the analysis and interpretation levels. The discussed typology and characteristics of displays can enable nurse researchers to enhance the quality and presentation of integrated results in mixed-methods studies.
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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 | 0.213 | 0.547 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.019 | 0.023 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".