Rasch Model of the COVID-19 Symptom Checklist - Towards a Higher Quality of Self-Reported Measurement

Abstract Background: Inaccurate measurement of self-reported instruments including questionnaires and symptom checklists jeopardizes the comparability of the results. We therefore used advanced psychometric modelling to determine if the fundamental principles of measurement of an online self-reported COVID-19 symptom checklist were met or whether adaptations were necessary to increase measurement precision.Methods: Fit to the Rasch model was examined in a sample of 1638 Austrian citizens who completed an online COVID-19 symptom checklist on up to 20 days during a period of restrictive country-wide COVID-19 measures.Results: The longitudinal application of the self-reported COVID-19 symptom checklist increased the fit to the Rasch model. The items ‘fatigue’, ‘headache’ and ‘sneezing’ had the highest likelihood to be affirmed. The item ‘cough’ showed a significant misfit to the fundamental measurement model and an additional dependency to ’dry cough/no sputum production’. Several personal factors, such as gender, age group, educational status, COVID-19 test status, comorbidities, immunosuppressive medication, pregnancy and pollen allergy led to systematic differences in the patterns of how symptoms were affirmed. Adjustments ranged from ±0.25 to ±0.01 on the metric scales (0 to 10) to which the raw scores were transformed.Conclusion: Except for some basic adaptations, the present analysis supports the combination of items. More accurate item wordings co-created with lay persons and adjustments for personal factors would increase measurement precision of the self-reported COVID-19 symptom checklist.