Clinical Assessment of Judgment in Adults and the Elderly: Development and Validation of the Three Domains of Judgment Test—Clinical Version (3DJT-CV)
Bibliographic record
Abstract
(1) Background: This article discusses the first two phases of development and validation of the Three Domains of Judgment Test (3DJT). This computer-based tool, co-constructed with users and capable of being administered remotely, aims to assess the three main domains of judgment (practical, moral, and social) and learn from the psychometric weaknesses of tests currently used in clinical practice. (2) Method: First, we presented the 3DJT to experts in cognition, who evaluated the tool as a whole as well as the content validity, relevance, and acceptability of 72 scenarios. Second, an improved version was administered to 70 subjects without cognitive impairment to select scenarios with the best psychometric properties in order to build a future clinically short version of the test. (3) Results: Fifty-six scenarios were retained following expert evaluation. Results support the idea that the improved version has good internal consistency, and the concurrent validity primer shows that 3DJT is a good measure of judgment. Furthermore, the improved version was found to have a significant number of scenarios with good psychometric properties to prepare a clinical version of the test. (4) Conclusion: The 3DJT is an interesting alternative tool for assessing judgment. However, more studies are needed for its implementation in a clinical context.
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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 | 0.056 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads 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".