A DIGITAL APPLICATION FOR ASSESSMENT OF NEUROCOGNITIVE DISABILITIES
Notice bibliographique
Résumé
Background: Neuropsychological assessment is designed to identify neurocognitive impairment and has traditionally relied on pen-and-paper tests. The behavior collected from these tests is usually expressed as a total summary score or a score that reflects a restricted number of features that assess errors. There is now interest in coupling traditional paper and pencil tests with digital assessment technology. In this context traditional metrics such as summary scores are still available. However, using digital technology, a host of time-based parameters can now be obtained. These time-based parameters include the total time to complete the task or total time to completion, as well the time necessary to generate all responses within a task or test trial. In addition to a wealth of highly nuance data, audio and video files of patients' behavior can be created. This permits subsequent, downstream data mining to uncover and discover new features and variables of interest. Digital assessment platforms are reliable and inexpensive and can be deployed in virtually any clinical situation such as a comprehensive, outpatient dementia evaluation where detailed assessment is conducted, as well as in a primary medical care setting to screen for neurocognitive difficulty associated with chronic or acute medical illness. Cardiovascular risks such as hypertension, elevated cholesterol, and diabetes are common if not endemic. In addition to increasing the risk for heart attack and stroke, it is now commonly understood that cardiovascular risks also convey risk for dementia such as Alzheimer's disease. Indeed, most insidious onset dementia illness presents with some degree of vascular alteration in the brain. Moreover, chronic cardiovascular is now well known to associate with a variety of neuropsychological disabilities such as executive control. Objectives: The current research presents data on the Philadelphia Pointing Span Test (PPST), a digital test designed to measure executive abilities. The current research tested two predictions. The first prediction is that indices from the PPST measuring auditory span and mental manipulation will be related to other indices that assess executive abilities, providing some evidence for criterion validity of the PPST as an executive measure. The second prediction is to assess the degree digitally administered and scored PPST indices are related to cardiovascular risks. Methods: Fifty-one patients from an outpatient ambulatory medical practice were recruited. All participants were assessed with the PPST and the Montreal Cognitive Assessment (MoCA). Statistical analyses of MoCA test performance resulted in neuropsychological indices measuring executive, language, and memory abilities. The PPST was implemented onto an iPad application capable of tracking accuracy and latency between responses. PPST outcome variables of interest included ANY ORDER and SERIAL Order recall, measures of executive abilities related to auditory span and mental manipulation, respectively; and the latency to generate all responses. Results: Consistent with our first prediction, PPST SERIAL ORDER recall was correlated to the MoCA executive index where reduced MoCA executive performance was seen along with reduced PPST SERIAL ORDER recall. Consistent with our second prediction slower or longer latencies from selected PPST tests items were associated with greater cardiovascular risk. Conclusions: The PPST, a digitally administered and scored test, appears to provide an efficient assessment of executive abilities. The relationship between PPST performance and cardiovascular risk suggests that the PPST may be means to screen for neuropsychological difficulty as related to medical illness in a primary care setting.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».