Item analysis on the quality of life scale for anxiety disorders QLICD-AD(V2.0) based on classical test theory and item response theory.

Background: Anxiety disorders can cause serious physical and psychological damage, so many anxiety scales have been developed internationally to measure anxiety disorders, but due to the cultural differences and cultural dependence of quality of life between Chinese and Western cultures, it is difficult to reflect the main characteristics of Chinese patients. Therefore, we developed a scale suitable for Chinese patients with anxiety disorders: the Anxiety Disorders Scale of the Quality of Life Instruments for Chronic Diseases (QLICD-AD), hoping to achieve satisfactory QOL assessments for anxiety disorders.

Objectives: Items from the Anxiety Disorders Scale of the Quality of Life in Chronic Disease Instrument QLICD-AD system were analyzed using CTT and IRT to lay the groundwork for further refinement of the scale to accurately measure anxiety disorders.

Methods: 120 patients with anxiety disorder were assessed using the QLICD-AD (V2.0). Descriptive statistics, variability method, correlation coefficient method, factor analysis and Cronbach's coefficient of CTT, and graded response model (GRM) of item response theory were used to analyze the items of the scale.

Result: CTT analysis showed that the standard deviation of each item was between 0.928 and 1.466; Pearson correlation coefficients of item-to-domain were generally greater than 0.5 and also greater than that of item-to-other domain; the Cronbach 's of the total scale was 0.931, α of each domain was between 0.706 and 0.865. IRT analysis showed that the discrimination was between 1.14 and 1.44. The difficulty parameter of all items increased with the increase of grade. But some items (GPH6,GPH8,GPS3,GSO2-GSO4,AD2,AD5) difficulty parameters were less than 4 or greater than 4. The average of information amount was between 0.022 and 0.910.

Conclusion: Based on CTT and IRT analysis, most items of the QLICD-AD (V2.0) scale have good performance and good differentiation, but a few items still need further revision. Suggests that the QLICD-AD (V2.0) appears to be a valid measure of anxiety disorders. It may effectively improve the diagnosticity of anxiety disorders, but due to the limitations of the current sample, further validation is needed in a broader population extrapolation trial.