Mixed Methods Studies Using Secondary Analysis in Nursing and Midwifery: A Methodological Review
Bibliographic record
Abstract
AIM: To identify mixed methods studies in nursing and midwifery using secondary analysis and to examine their methodological characteristics. DESIGN: Methodological review. METHODS: A systematic search was conducted to identify empirical mixed methods studies in nursing and midwifery that used secondary analysis. A data extraction sheet was developed based on previous methodological reviews of secondary analysis and mixed methods. DATA SOURCES: SCOPUS, Web of Science and CINAHL were searched from inception to March 10, 2023. Supplementary searches were conducted in two methodological journals and six nursing journals. RESULTS: A total of 26 mixed methods studies published between 2000 and 2022 were included in the review. Of these, only 13 studies explicitly mentioned the type of mixed methods design used. Twenty studies showed evidence of integration of the quantitative and qualitative components. Most of these studies integrated the components at the interpretation stage, whereas fewer integrated the components during data collection. None of the studies mentioned the rationale for using secondary analysis in the context of a mixed methods study. CONCLUSION: The included studies demonstrated fairly good reporting of mixed methods features, although they generally lacked a rationale for the use of secondary data. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: Adequate reporting of mixed methods studies using secondary analysis is essential in order to allow readers to assess whether secondary analysis was appropriately incorporated into a mixed methods study and whether the potential of secondary analysis was fully exploited. IMPACT: This review provides a set of recommendations to transparently report information regarding the research process and results obtained in mixed methods studies using secondary analysis. REPORTING METHOD: Items relevant to methodological reviews included in the PRISMA Extension for Scoping Reviews (PRISMA-ScR) were considered for reporting the review.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
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 | 0.242 | 0.401 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.016 |
| Bibliometrics | 0.040 | 0.029 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.006 | 0.009 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".