Development and validation of a patient-report measure of fatigue associated with depression.

INTRODUCTION Among researchers and clinicians who treat depression, there is growing interest in treatment of specific residual symptoms such as fatigue. However, there is no available measure that provides a detailed assessment of fatigue associated with depression. Thus, the purpose of the current study was to develop and validate a patient-reported outcome measure designed to assess depression-related fatigue and its impact. METHODS The Fatigue Associated with Depression Questionnaire (FAsD) was developed based on literature review, clinician interviews, and focus groups and cognitive debriefing interviews with patients. Then, a draft questionnaire was administered to a sample of patients with depression. Statistical analysis first focused on item reduction and subscale identification, followed by psychometric evaluation of the FAsD. RESULTS The per protocol sample (n = 317) was primarily female (68.1%), with a mean age of 47.0 years. Based on item performance and exploratory factor analysis, three items were dropped from the draft FAsD, yielding a final 13-item questionnaire with two subscales (experience and impact). The FAsD demonstrated good internal consistency reliability (Cronbach's alphas ≥ 0.88) and test-retest reliability (intraclass correlation coefficients ≥ 0.78). The FAsD demonstrated construct validity through strong correlations with measures assessing fatigue/energy and symptoms of depression. The FAsD also discriminated among groups of participants differentiated by clinician ratings of global severity of depression (CGI-S). LIMITATIONS Limitations include heterogeneity of current treatments received by the sample, as well as lack of knowledge regarding the extent to which FAsD scores were influenced by patients' treatments rather than the depression itself. CONCLUSIONS In this initial psychometric evaluation, the FAsD demonstrated good reliability, validity, and factor structure. This questionnaire may be a useful tool for evaluating treatment interventions that focus specifically on fatigue associated with depression.