An appraisal of the psychometric properties of the Clinician version of the Apathy Evaluation Scale (AES-C).
This article examines the psychometric properties of the clinician version of the Apathy Evaluation Scale (AES-C) to determine its ability to characterize, quantify and differentiate apathy. Critical appraisals of the item-reduction processes, effectiveness of the administration, coding and scoring procedures, and the reliability and validity of the scale were carried out. For training, administration and rating of the AES-C, clearer guidelines, including a more standardized list of verbal and non-verbal apathetic cues, are needed. There is evidence of high internal consistency for the scale across studies. In addition, the original study reported good test-retest and inter-rater reliability coefficients. However, there is a lack of replication on these more stable and informative measures of reliability and as such they warrant further investigation. The research evidence confirms that the AES-C shows good discriminant, convergent and criterion validity. However, evidence of its predictive validity is limited. As this aspect of validity refers to the scale's ability to predict future outcomes, which is important for treatment and rehabilitation planning, further assessment of the predictive validity of the AES-C is needed. In conclusion, the AES-C is a reliable and valid measure for the characterization and quantification of apathy.
Clarke
Diana E
DE
Toronto Rehabilitation Institute and Department of Psychiatry, Baycrest Centre for Geriatric Care, Canada. dclarke@jhsph.edu
Van Reekum
Robert
R
Patel
Jigisha
J
Simard
Martine
M
Gomez
Everlyne
E
Streiner
David L
DL
D000342:Affective Symptoms / Q000175:diagnosis / Q000523:psychology*; D000368:Aged; D006801:Humans; D001523:Mental Disorders / Q000175:diagnosis* / Q000523:psychology; D008875:Middle Aged; D009042:Motivation; D009633:Nonverbal Communication; D015588:Observer Variation; D010552:Personality Assessment / Q000706:statistics & numerical data*; D011594:Psychometrics / Q000706:statistics & numerical data; D015203:Reproducibility of Results