Identifying the components of clinical vignettes describing Alzheimer’s disease or other dementias: a scoping review
Bibliographic record
Abstract
BACKGROUND: Clinical vignettes are often used to elicit information about health conditions in research studies. This review summarizes the components of clinical vignettes describing Alzheimer's disease (AD) or other dementias. The purpose is to provide recommendations for the development of standardized vignettes that may be used in future studies. METHODS: MEDLINE, EMBASE, PsycINFO, ASSIA, CINAHL were searched from their inception to June 2014. Primary English-language studies employing vignettes to describe AD or similar disorders (including other dementias and Parkinson's disease) were included in the review. Included studies had to describe the content of the vignettes in the published manuscripts. The characteristics of the included studies and the vignettes were extracted in tabular form and summarized qualitatively. RESULTS: Forty-two studies were included in the review. Twenty-four of the studies contained at least one AD vignette, 11 had vignettes focusing on non-AD dementias, and seven contained vignettes describing conditions other than dementia. In total, 58 vignettes were obtained from the 42 included studies. CONCLUSIONS: Key aspects to consider when constructing vignettes for AD or other dementias include writing the vignettes from a third-person perspective and presenting hypothetical patients as being at least 65 years of age. Researchers should develop standardized vignettes for use across studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".