Litcius/Paper detail

Effect of electronic reminders on patients’ compliance during clear aligner treatment: an interrupted time series study

Lan Huong Timm, Gasser Farrag, D Wolf, Martin Baxmann, Falk Schwendicke

2022Scientific Reports23 citationsDOIOpen Access PDF

Abstract

Patient compliance is relevant to achieving therapeutic goals during clear aligner therapy (CAT). The aim of this study was to evaluate the efficacy of remote electronic (e-)reminders and e-feedback on compliance during CAT using an interrupted time series (ITS) analysis. We used routinely collected mobile application data from a German healthtech company (PlusDental, Berlin). Our primary outcome was self-reported compliance (aligner wear time min. 22 h on 75% of their aligners were classified as fully compliant, min. 22 h on 50-74.9% of their aligners: fairly compliant; min. 22 h on < 50% of their aligners: poorly compliant). E-reminders and e-feedback were introduced in the 1st quarter of 2020. Compliance was assessed at semi-monthly intervals from June-December 2019 (n = 1899) and June-December 2020 (n = 5486), resulting in a pre- and post-intervention group. ITS and segmented regression modelling were used to estimate the effect on the change in levels and trends of poor compliance. Pre-intervention, poor compliance was at 24.47% (95% CI: 22.59% to 26.46%). After the introduction of e-reminders and e-feedback (i.e., post-intervention), the percentage of poorly compliant patients decreased substantially, levelling off at 9.32% (95% CI: 8.31% to 10.45%). E-reminders and e-feedback were effective for increasing compliance in CAT patients.Clinical Significance: Orthodontists and dentists may consider digital monitoring and e-reminders to improve compliance and increase treatment success.

Topics & Concepts

Interrupted Time Series AnalysisSeries (stratigraphy)Interrupted time seriesComputer scienceCompliance (psychology)MedicinePsychologyStatisticsBiologyPsychiatryMathematicsSocial psychologyPaleontologyPsychological interventionMobile Health and mHealth ApplicationsAutism Spectrum Disorder Research