Norms and associated factors of the STAI-Y State anxiety inventory in older adults: results from the PAQUID study
Bibliographic record
Abstract
BACKGROUND: The latest version of the State-Trait Anxiety Inventory (STAI-Y) is commonly used in older adults, even though this anxiety scale was developed in and for young adults. Norms and associated factors of the STAI-Y are lacking for older adults in the general population. The objectives of the present study were to produce norms on the STAI-Y State scale for older adults using a large sample of older adults selected from a general population and to examine the sociodemographic and health-related factors associated with the STAI-Y State score. METHODS: 993 community-dwelling individuals aged 66 years and over from the PAQUID study were evaluated at home by a psychologist for the following variables: age, education, marital status, proximity of relatives, self-assessment of income sufficiency, occupation during active life, depressive symptomatology, objective and subjective health, objective and subjective cognitive functioning, adverse life events, activities of daily living, drug use, and cigarette consumption. RESULTS: Norms were stratified for age, sex, and education and were produced separately for older adults with and without depressive symptomatology. Multivariate analyses revealed that younger age (66-79 years), female sex, lower education, perception of income insufficiency, depressive symptomatology, poor subjective health, subjective cognitive complaints, psychotropic drugs use, and recent adverse life events were independently associated with higher STAI-Y State score. CONCLUSIONS: This study provides norms for the STAI-Y State anxiety inventory in a general population of older adults and indicates the specific factors linked with state anxiety. Such factors should be taken into account by clinicians in order to better understand state anxiety in older adults.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".