Is Geriatric Depression Scale-15 a suitable instrument for measuring depression in Brazil? Results of a Rasch analysis
Bibliographic record
Abstract
Depressive symptoms are the most prevalent mental health condition in older adults. Since it cannot be measured directly, the use of instruments is mandatory. The 15-item Geriatric Depression Scale (GDS) is one of the most widely used scales to measure depression in the elderly. It is recognized that the cultural context is a major determinant of the instrument's psychometric performance. Up to the present, this scale has mainly been investigated through classical psychometric approaches. The present study aims to explore whether the 15-item GDS is a suitable instrument in a Brazilian sample. In addition, it explores the potential improvement in the psychometric performance by item refinement. Four hundred twenty-four elderly adults selected through convenience sampling completed the 15-item GDS. Data were analyzed by the Rasch Measurement Model. The Rasch analysis is a powerful modern approach to explore psychometric performance of instruments in health sciences. It examines both the scale and the individual item performance in depth. The 15-item GDS proved not to be suitable in a Brazilian sample. Item misfit and differential item functioning were responsible for considerable misperformance. Scale reduction led to a 10-item structure. This refined format presented adequate psychometric performance and no differential item functioning. The present study offers an alternative and more adequate version of the GDS to be applied in Brazilian subjects. It is also in line with the need for shorter, valid scales in clinical settings. Further investigations are needed to develop a set of cultural-invariant items, which could then be applied in transcultural investigations free of bias.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".