81 Assessment of Functional Capacity Interview (AFCI): A New Informant- Report Measure to Detect Disability Risk in Older Adults
Notice bibliographique
Résumé
Objective: Functional disability is a foreseeable consequence of neurodegenerative diseases affecting cognition, yet there are few validated instruments that assess functional capacity for use in pre-clinical and clinical dementia conditions. To our knowledge, the existing instruments do not comprehensively assess decision-making capacity across the numerous functional domains of daily life. We developed and evaluated the utility of an informant-report measure, the Assessment of Functional Capacity Interview (AFCI), within a sample of cognitively unimpaired and preclinical dementia groups. Participants and Methods: Based on a comprehensive literature review, analysis of existing measures, and clinical experience, we generated >40 items consisting of open-ended questions assessing crucial aspects of daily functioning. These items were presented to 12 experts in the field of geriatrics and neuropsychology, through a graded approach (4 rounds of feedback and alterations), resulting in item modification or rejection, as well as addition of new items. The remaining items were piloted on three informants at the time of outpatient clinical evaluations, leading to further item refinement. The final version of the AFCI evaluated capacity across domains of financial affairs and management, medical affairs and healthcare management, home and personal safety, and social behaviors and community functioning. The AFCI contained 6 items per domain with response items that ranged from 0=no difficulty to 3=severe difficulty (scores ranged from 0 to 72). Results: Participants (N = 58; Agemean = 76; Educationmean = 16) were classified as cognitively unimpaired (CU, n = 17), subjective cognitive decline (SCD, n = 24), or mild cognitive impairment (MCI, n = 17) based on established criteria. All participants had a knowledgeable informant who completed the AFCI. We found statistically significant moderate to large correlations between the AFCI total score and an informant report measure of cognitive functioning (Brief Informant Form of Neurobehavioral Symptomatology total score), rs(42) = .73, p < .001, Test of Practical Judgment-informant total score rs(42) = .87, p < .001, and Montreal Cognitive Assessment total score rs(41) = -.34, p = .027. A Kruskal-Wallis H test revealed significant differences in AFCI total score between the three diagnostic groups, H(2) = 12.30, p = .002. Pairwise post-hoc analysis with Bonferroni correction showed a significant difference between CU and MCI (p = .001). The difference in AFCI total score between SCD and MCI was in the expected direction, but did not achieve statistical significance with correction, (p = .068). As expected, there was no statistically significant difference between CU and SCD (p =.353). Conclusions: In this pilot sample (data collection is ongoing), the AFCI showed promise as a brief, clinically useful functional capacity instrument that is easily administered during a clinical interview or completed by knowledgeable informants. Results can help identify compromised decision-making in at-risk older adults to aid the prevention of common safety issues within this vulnerable population. Ongoing research will extend preliminary investigation of validity and further inform the utility of AFCI in both diagnostic and interventional contexts
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,004 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».