Psychometric Properties of the QoL-ME: A Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems

Abstract

Background: Quality of Life (QoL) assessment in people with severe mental health problems may benefit from improved personalization and accessibility. Therefore, an innovative, digital, visual, and personalized QoL assessment app for people with severe mental health problems was recently developed: the QoL-ME. The aim of this study was to evaluate the psychometric quality of the QoL-ME by assessing its reliability, validity, and responsiveness. Methods: To examine the reliability of the QoL-ME, the internal consistency of its subscales was assessed using Cronbach's Alpha. Correlations between the QoL-ME and the MANSA were computed to appraise the construct validity of the QoL-ME. Internal responsiveness was evaluated using the standardized response mean and external responsiveness was investigated using hierarchical regression. Results: Cronbach's Alpha's of the subscales of the QoL-ME ranged between 0.5 and 0.84. In accordance with expectations, the language-based core version of the QoL-ME correlated strongly (r = between 0.55 and 0.76) with the MANSA, whilst the picture-based additional modules of the QoL-ME correlated moderately (r = 0.3) with the MANSA. The standardized response mean was 0.23 and the regression model revealed a coefficient β of −0.01. Conclusions: The QoL-ME has adequate psychometric properties. In comparison with similar pictorial instruments, both the QoL-ME's reliability and validity can be considered as sufficient. The results indicate that the responsiveness of the QoL-ME is insufficient. Additional research is needed to evaluate and potentially modify the instrument to improve its responsiveness.