Are the Items of the Starkstein Apathy Scale Fit for the Purpose of Measuring Apathy Post-Stroke?
Bibliographic record
Abstract
Abstract Given the importance of apathy for stroke, we felt it was time to scrutinize the commonly used Starkstein Apathy Scale (SAS) for psychometric evidence that it is fit for this purpose. The objectives were to: (i) estimate the extent to which the SAS items fit a hierarchical continuum of the Rasch Model; and (ii) estimate the strength of the relationships between the Rasch analysed SAS and converging constructs related to stroke outcomes. Methods Data on 238 people with stroke (mean age=63.1 years (SD=12.1) women=37.4%) from a clinical trial of a community-based intervention targeting participation were available at 5 time points yielding 856 SAS questionnaires. SAS has 14 items, rated on a 4-point scale with higher values indicating more apathy. Psychometric properties were tested using Rasch partial-credit model, correlation, and regression. The construct was modeled as motivation with items rescored as high is better. Results Rasch analysis indicated that the response options were disordered for 8/14 items, pointing to unreliability in the interpretation of the response options; they were consequently reduced from 4 to 3. Only 9/14 items fit the Rasch model and therefore suitable for creating a total score. The new rSAS was deemed unidimensional (residual correlations: < 0.3), reasonably reliable (person separation index: 0.74), with item-locations uniform across time, age, sex, and education. However, 30% of scores were >2 SD above the standardized mean but only 2/9 items covered this range (construct mistargeting). Apathy (rSAS/SAS) was correlated weakly with anxiety/depression and uncorrelated with physical capacity. Regression showed that the effect of apathy on participation and health perception was similar for rSAS/SAS versions: R 2 participation measures ranged from 0.11 to 0.29; R 2 for health perception was ∼0.25. When placed on the same scale (0-42), rSAS value was 6.5 units lower than SAS value with minimal floor/ceiling effects. Estimated change over time was identical (0.12 units/month) which was not substantial (1.44 units/year) but greater than expected assuming no change (t: 3.6 and 2.4). Conclusion The retained items of the rSAS targeted behaviours more than beliefs and results support the rSAS as a robust measure of apathy in people with chronic stroke.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; a candidate call from one source (direct Gemma or distilled Codex), 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".