OBJECTIVES: Loneliness is a significant public health concern with negative effects on physical and mental well-being. The De Jong Gierveld Loneliness Scale (DJGLS) is a widely used instrument for measuring loneliness, ranging from 0-11. However, to our best knowledge, there is no method to quantify loneliness over time to be integrated in benefit-harm and cost-effectiveness analysis. This study, framed within the EU Horizon 2020 project RECETAS, introduces a novel approach to quantify longitudinal data on loneliness by converting DJGLS scores into loneliness-free days (LFD).

METHODS: We followed the approach of estimating depression-free days by transforming results of the Patient Health questionnaire. DJGLS values of 0-2 indicate “not lonely”, 3-8 “moderate loneliness”, and 9-11 “strong loneliness”. Cut-offs are based on “self-assessed levels of loneliness”. As loneliness scores are usually assessed at several time points instead of every day, weighting loneliness by the time period between assessment points was undertaken to calculate LFD.

RESULTS: The DJGLS state “not lonely” was assigned a utility of 1 (representing a day free of loneliness), whereas the state “strongly lonely” was assigned a utility of 0 (indicating a lonely day). Intermediate DJGLS states representing the scores 3-8 (“moderately lonely”) were assigned utilities between 0 and 1 by linear interpolation. Multiplying the mean loneliness utility value between two time points with the corresponding days and summing up these estimations for each interval, results in total LFDs over the full assessment period.

CONCLUSIONS: The conversion of DJGLS scores into score-based states and corresponding loneliness utility values between 0 and 1 and, by considering time, transforming into LFD offers a practical approach to quantifying loneliness experiences over time. LFDs could be considered as a patient-relevant outcome indicator providing valuable insight into the experience of persons with loneliness. Reporting outcomes in loneliness research are important and could be used as denominator in cost-effectiveness analyses.