Reliability and construct validity of the Automated Neuropsychological Assessment Metrics (ANAM) mood scale

Abstract

The reliability and construct validity of the Automated Neuropsychological Assessment Metrics (ANAM) mood scale (AMS) were examined using concurrent, well-validated measures of mood and confirmatory factor analysis (CFA) with a sample of 210 volunteer college students. The AMS was given in computerized format with multiple adjectives using a visual analog Likert scale yielding seven dimensions of mood including vigor, restlessness, depression, anger, fatigue, anxiety, and happiness. All seven mood dimensions of the AMS demonstrated excellent test–retest reliability and internal consistency. Also, the AMS anxiety dimension correlated strongly with the Spielberger's State Anxiety Inventory (r=0.67) and the AMS depression dimension correlated strongly with the Beck Depression Inventory-II (r=0.71). CFA revealed that the AMS 7-factor mood model fit the data well and significantly better than an alternative, theoretically plausible model. When concurrent measures of mood were incorporated in the CFA model, the AMS demonstrated both convergent and discriminant validity. The AMS 7-factor model explained 55.12% of the total variance in the items. It was concluded that the AMS provides a brief yet reasonably complete and valid assessment of mood.