46 Comparison of Anxiety Measures in a Memory Clinic Sample
Notice bibliographique
Résumé
Objective: As the presentation of anxiety may differ between younger and older adults, it is important to select measures that accurately capture anxiety symptoms for the intended population. The 21-item Beck Anxiety Inventory (BAI) is widely used; however, its high reliance on somatic symptoms may result in artificial inflation of anxiety ratings among older adults, particularly those with medical conditions. The 30-item Geriatric Anxiety Scale (GAS) was specifically developed for older adults and has shown strong psychometric properties in community-dwelling and long-term care samples. The reliability and validity of the GAS in a memory clinic setting is unknown. The present study aimed to compare the psychometric properties of the GAS and the BAI in a memory disorder clinic sample. Participants and Methods: Participants included 35 older adults (age=73.3±5.0 years; edu=15.3±2.8 years; 42% female; 89% non-Hispanic white) referred for a neuropsychological evaluation in a memory disorders clinic. In addition to the GAS and BAI, the Geriatric Depression Scale (GDS) and Montreal Cognitive Assessment (MoCA) were included. Cutoffs for clinically significant anxiety were based on published data for each measure. A dichotomous anxiety rating (yes/no) was created to examine inter-measure agreement; minimal anxiety was classified as “no” and mild, moderate and severe anxiety were classified as “yes.” Internal scale reliability was examined using Cronbach’s alpha. Convergent and discriminant validity were examined using Spearman rank correlation coefficients. Frequency distributions determined the proportion of yes/no anxiety ratings, and a McNemar test compared the proportion of anxiety classifications between the two measures. Results: Both measures had excellent internal consistency (BAI: a=.88; GAS: a=.94). The BAI and GAS were highly correlated with each other (r=.79, p<.001) and positively correlated with a depression measure (BAI-GDS: r=.51, p=.002; GAS-GDS: r=.53, p=.001). Discriminant validity was supported by lower correlations between the anxiety measures and cognition (BAI-MoCA: r=.38, p=.061; GAS-MoCA: r=.34, p=.098). The BAI classified 14 participants as having anxiety (40%) and 21 participants as not having anxiety (60%), whereas the GAS classified 21 participants as having anxiety (60%) and 14 participants as not having anxiety (40%). The proportion of anxiety classifications were significantly different between the two measures (p =.016). For 28 participants (80%), there was agreement between the anxiety ratings. Seven participants (20%) were classified as having anxiety by the GAS, but not by the BAI; GAS items related to worry about being judged or embarrassed may contribute to discrepancies, as they were frequently endorsed by these participants and are unique to the GAS. Conclusions: Results support that both anxiety measures have adequate psychometric properties in a clinical sample of older adult patients with memory concerns. It was expected that the BAI would result in higher classification of anxiety due to reliance on somatic symptoms; however, the GAS rated more participants as having anxiety. The GAS may be more sensitive to detecting anxiety in our sample, but formal anxiety diagnoses were not available in the current dataset. Future research should examine the diagnostic accuracy of the GAS in this population. Overall, preliminary results support consideration of the GAS in memory disorder evaluations.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».