Validation of a new assessment tool for qualitative research articles
Bibliographic record
Abstract
AIM: This paper presents the development and validation of a new assessment tool for qualitative research articles, which could assess trustworthiness of qualitative research articles as defined by Guba and at the same time aid clinicians in their assessment. BACKGROUND: There are more than 100 sets of proposals for quality criteria for qualitative research. However, we are not aware of an assessment tool that is validated and applicable, not only for researchers but also for clinicians with different levels of training and experience in reading research articles. METHOD: In three phases from 2007 to 2009 we delevoped and tested such an assessment tool called VAKS, which is the Danish acronym for appraisal of qualitative studies. Phase 1 was to develop the tool based on a literature review and on consultation with qualitative researchers. Phase 2 was an inter-rater reliability test in which 40 health professionals participated. Phase 3 was an inter-rater reliability test among the five authors by means of five qualitative articles. RESULTS: The new assessment tool was based on Guba's four criteria for assessing the trustworthiness of qualitative inquiries. The nurses found the assessment tool simple to use and helpful in assessing the quality of the articles. The inter-rater agreement was acceptable, but disagreement was seen for some items. CONCLUSION: We have developed an assessment tool for appraisal of qualitative research studies. Nurses with a range of formal education and experience in reading research articles are able to appraise, relatively consistently, articles based on different qualitative research designs. We hope that VAKS will be used and further developed.
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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: Evaluation · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | Metaresearch Domain: Evaluation · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.477 | 0.700 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.028 | 0.015 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".