Evaluating individual change with the Quality of Life in Neurological Disorders (Neuro-QoL) Short Forms - Kozlowski, Allan J. (Arch Phys Med Rehabil, 2015)
OBJECTIVE: To provide a clinically useful means of interpreting change for individual patients on the Neurological Quality of Life (Neuro-QoL) adult short forms (SFs) by applying a Classical Test Theory concept for interpreting individual change. DESIGN: Secondary analysis of existing data. SETTING: Community. PARTICIPANTS: Persons with neurological conditions including stroke, epilepsy, amyotrophic lateral sclerosis, multiple sclerosis, and Parkinson’s disease residing in community settings. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Neuro-QOL SFs for Applied Cognition-General Concerns, Applied Cognition-Executive Function, Applied Cognition-Combined, Ability to Participate in Social Roles and Activities, Satisfaction with Social Roles and Activities, Positive Affect and Well-Being, Depression, Stigma, Upper Extremity Function (Fine Motor, Activities of Daily Living), Lower Extremity Function (Mobility), Anxiety, Sleep Disturbance, Fatigue, and Emotional and Behavioral Dyscontrol. METHODS: We estimated conditional minimal detectable change (cMDC) indices from the pooled standard errors (SEs) adjusted for a 95% confidence interval (CI) using the average of the SEs for any given pair of scores multiplied by the z-score, or [(SE(Score1) +SE(Score2))/2 · 1.96]. RESULTS: The cMDC indices are generally smallest in the mid-range of all scales, ranging from 3.6 to 11.2 T-score points, and higher on the outer quartiles ranging from 3.7 to 21.6 T-score points. The lowest mid-range cMDCs were for Satisfaction with Social Roles and Activities (3.6–4.7 T-score points) and the largest was for Sleep Disturbance (9.4–11.2 T-score points). CONCLUSIONS: Change indices can help clinicians and investigators identify differences for individual patients or subjects that are large enough to motivate treatment change. cMDCs can reduce misclassification of magnitudes of change that are near the margins of error across the range of the Neuro-QoL SFs.