eHealth - In or out of our daily lives? Measuring the (non-)use of eHealth in summative evaluations

vorm of op enige wijze, zonder voorafgaande schriftelijke toestemming van de auteur. General aim and thesis outlineIn this thesis, use will be broadly defined as every use of the eHealth service among the target population.I focus my research to address the question: why are eHealth services (not) being used by the target population in quantitative and qualitative analyses?The potential of eHealth is not fully employed yet and I wanted to investigate why.The aim of this thesis is to increase our understanding about the (non-)use of eHealth services among the target population in a real-world setting.Lessons learned from this thesis will Abstract Objective: The goal of this study is to identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults.Participants: The study population consisted of older adults, aging 55 years or older living in the Netherlands.Methods: We conducted an observational cohort study.Participants completed a pretest questionnaire and got access to an eHealth intervention, called Stranded, for four weeks.With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affect drop-out.Results: Ninety older adults started using Stranded.45.6% of these participants continued their use for four weeks.32.2% dropped out in the first week (N=29) and 22.2% dropped out in the second or third week of this study (N=13 in week 2, N= 7 in week 3).The final multivariate Cox-regression model which predicts drop-out, consisted of the following variables: perceived computer skills (HR=0.69,BI=0.49-0.99,P=.04) and level of external regulation (HR=1.19,BI=1.03-1.37,P=.02).Conclusions: Predicting the chance of dropping out of an eHealth intervention is possible by using their level of self-perceived computer skills and their level of external regulation (externally controlled rewards or punishments direct behaviour).Anticipating to these factors can improve eHealth adoption.