Scoping review of single‐item global rating scales utilized in epilepsy research: Patterns of use, challenges, and recommendations
Bibliographic record
Abstract
SIGRs (single-item global ratings) are gaining popularity among clinicians and health researchers as efficient tools to assess patient-reported outcomes. There has been no systematic assessment of domains explored, methodological aspects, and validation efforts of SIGRs in epilepsy. We aimed to critically appraise and provide recommendations on the use and reporting of SIGRs in epilepsy research. We performed a systematic scoping review using the Joanna Briggs Institute's recommendations. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) method was used to search five electronic databases (MEDLINE, Embase, PsycINFO, CINAHL, and Cochrane Register of Controlled Trials) from 1980 to present day. We included English-language studies utilizing SIGRs that assessed health aspects (concept) in people with epilepsy of all ages (participants), in all settings (context), containing ≥30 patients, and using SIGRs with continuous or categorical responses in any study design. Abstract and full-text review was conducted independently by two reviewers; disagreements were resolved through consensus. Standardized data abstraction was used. Of 16 417 citations, we included 289 studies, involving 114 584 patients who underwent 747 unique measurements using SIGRs. Use increased over time; 30% were published in the last 4 years, and 51% used 1 SIGR (range 1-23 SIGRs). Commonly assessed domains were overall health (24.2%) and seizure-related aspects (23.5%), whereas 37% measured perceived change. Most studies used SIGRs descriptively (80.1%). Numerous SIGR formats were used (most commonly Likert-like, 73.3%). Ad hoc SIGRs without validation occurred frequently (45.6%). Stem questions were absent in 9.5% of measures, and only 6.5% reported SIGR measurement properties. SIGRs are widely used and increasingly prevalent in epilepsy research to assess diverse domains across various formats. However, many SIGRs suffer from poor reporting and methodological limitations. We provide a comprehensive catalog of SIGRs and offer recommendations to improve their use in research and clinical practice.
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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 | 0.191 | 0.488 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.040 | 0.037 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".