A Systematic Review of the Psychometric Properties of the Geriatric Anxiety Inventory
Bibliographic record
Abstract
The Geriatric Anxiety Inventory (GAI) and its short form (GAI-SF) are self-reported scales used internationally to assess anxiety symptoms in older adults. In this study, we conducted the first critical comprehensive review of these scales' psychometric properties. We rated the quality of 31 relevant studies with the COSMIN checklist. Both the GAI and GAI-SF showed adequate internal consistency and test-retest reliability. Convergent validity indices were highest with generalized anxiety measures; lowest with instruments relating to somatic symptoms. We detected substantial overlap with depression measures. While there was no consensus on the GAI's factorial structure, we found the short version to be unidimensional. Although we found good sensitivity and specificity for detecting anxiety, cut-off scores varied. The GAI and GAI-SF are relevant instruments showing satisfactory psychometric properties; to broaden their use, however, some psychometric properties warrant closer examination. This review calls attention to weaknesses in the methodological quality of the studies.
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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 | 0.012 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".