The Apathy Evaluation Scale (AES-C): Psychometric Properties and Invariance of Italian Version in Mild Cognitive Impairment and Alzheimer's Disease.
Giovanna FurneriSilvia PlataniaAlessandra PriviteraFederica MartelliRossana SmeriglioGrazia RazzaTiziana MaciSabrina CastellanoFilippo DragoMario SantagatiPasquale CaponnettoFilippo CaraciSanto di NuovoPublished in: International journal of environmental research and public health (2021)
Apathy is a neuropsychiatric symptom observed in different neurological and psychiatric disorders. Although apathy is considered a symptom, it has been recently reconsidered as a syndrome characterised by three dimensions: cognitive symptoms, affective symptoms and behavioural symptoms. Recent studies have shown that apathy can be considered as a prodromal symptom of Alzheimer's disease (AD), but also an indicator of the transition from mild cognitive impairment to AD. According to this scenario, an early detection of apathy in subjects with Mild Cognitive Impairment (MCI) and Mild AD can be a valid psychometric strategy to improve an early diagnosis and promote a prompt intervention. The Apathy Evaluation Scale is a validated tool composed of 18 items that assess and quantify emotional, behavioural and cognitive aspects of apathy. The aim of this study is to assess the specific reliability and validity of the Italian version of the Apathy Evaluation Scale-Clinician Version (AES-C) to detect apathy both in amnestic MCI and mild AD patients. In the present paper, we therefore examined the psychometric properties and the invariance of the Italian Version of the AES-C conducted on a sample composed of an experimental group of amnestic MCI and AD patients (N = 107) and a control group (N = 107) constituted by Age- and Sex-matched healthy controls. Results confirm the goodness of the scale. Confirmatory factory analysis confirmed that the AES-C Italian Version presents the same stability of one second-order factor and three first-order factors identified in the original version, and all items are predicted by a single general factor. Moreover, the scale was found to be invariant across both populations. Moreover, reliability and discriminant analysis showed good values. We found in the experimental group a negative correlation between the AES-C and Frontal Assessment Battery (FAB) (rs = -0.21, p < 0.001) and Mini Mental State Examination (MMSE) (rs = -0.04, p < 0.001), while a positive correlation was found between the AES-C and Hamilton psychiatric Rating scale for Depression (HAM-D) scores (rs = 0.58, p < 0.001) Overall, our data demonstrated the validity of the Italian version of the AES-C for the assessment of apathy both in MCI and in AD patients.
Keyphrases
- mild cognitive impairment
- psychometric properties
- cognitive decline
- end stage renal disease
- chronic kidney disease
- newly diagnosed
- peritoneal dialysis
- ejection fraction
- mental health
- randomized controlled trial
- prognostic factors
- brain injury
- patient reported outcomes
- physical activity
- machine learning
- deep learning
- big data
- artificial intelligence
- data analysis
- patient reported
- genetic diversity
- electronic health record
- case report
- cerebral ischemia