Research master thesis | Psychology (research) (MSc)
open access
Ecological momentary assessment (EMA) is a data collection method in which participants’ current behaviors and experiences are sampled repeatedly in their natural environment. EMA has advantages...Show moreEcological momentary assessment (EMA) is a data collection method in which participants’ current behaviors and experiences are sampled repeatedly in their natural environment. EMA has advantages over retrospective research methods, in that it reduces retrospective bias, increases ecological validity, and offers the possibility to observe dynamical changes of variables. However, EMA protocols are burdensome for participants and may interfere with their daily activities. This can lead to non-compliance over the course of a study. Missing data can subsequently decrease statistical power, and even induce bias. This paper explored whether missing data can be predicted by various variables related to students’ primary motivation to participate, mental health, stress levels, and demographics. We analyzed data of the first cohort (N = 418) of the ongoing WARN- D project on student mental health. Participants completed a comprehensive baseline survey and took part in an 85-day long EMA study. We predicted overall rates of non- compliance by participant characteristics at baseline (Analysis 1) and weekly rates of non- compliance by time-varying factors during the EMA stage (Analysis 2). Analysis 1 showed that overall non-compliance can be predicted by baseline measures such as age, depression, substance use, and primary motivation to participate. Analysis 2 showed that weekly assessed time-varying measures like time into study, enjoyment of the study, weekly stress, anxiety, and depression may predict weekly rates of non-compliance. Participant’s sex and smartphone operating system were not related to overall non-compliance. Summarizing, non-compliance rates of participants can be predicted by participant characteristics at baseline as well as by time-varying predictors. Our findings may inform future research on potential mechanisms behind noncompliance in EMA designs that should be considered to maximize participation rates while avoiding biased conclusions.Show less
With the United Kingdom leaving the European Union, the United Kingdom no longer has the same drug approval process as the European Union. This study therefore compares the approval processes of...Show moreWith the United Kingdom leaving the European Union, the United Kingdom no longer has the same drug approval process as the European Union. This study therefore compares the approval processes of the United Kingdom and the Netherlands by examining which country was quicker to approve the COVID-19 vaccines. Three possible explanations will be used to examine which aspect of the procedure could explain any differences. The explanations are about coordination, multi-level governance and the rigor of the approval process. The analysis shows that the United Kingdom was quicker to approve the first two COVID-19 vaccines and the Netherlands was quicker to approve the other two COVID-19 vaccines. Thus, no country can be classified as quicker. Of the possible explanations, only the coordination explanation possibly played a role in the speed of the approval process.Show less
Although ecological momentary assessment (EMA) is increasingly used in clinical and research settings due to its high ecological validity, low compliance rates still hinder its full fruition....Show moreAlthough ecological momentary assessment (EMA) is increasingly used in clinical and research settings due to its high ecological validity, low compliance rates still hinder its full fruition. Inconsistency in which predictors interfere with EMA compliance persists. As students frequently suffer from mental health problems, we as a Bachelor project group conducted an EMA study measuring mental health and related behaviors in 84 Bachelor students of Dutch universities via a smartphone application. The study consisted of a baseline assessment, a two-week-long EMA with four measurements per day, and a post-assessment. My goal was to explore whether mental health and self-efficacy predict EMA compliance and whether self-efficacy mediates the relationship between mental health and compliance? I computed a multiple linear regression model and mediation analysis with bootstrapping using the program “PROCESS” (Hayes, 2009) on IBM SPSS Statistics, version 24. The dependent variable was compliance, derived from the percentage completed EMA surveys, and the independent variables were mental health and self-efficacy at baseline, where the latter ran as the mediator between mental health and compliance. I added age and gender as covariates. Results depicted a mean EMA compliance rate of 83.9% with minimal time variations. No predictor was significantly related to EMA compliance (R 2 = 0%). The mediation analysis showed non-significant direct and indirect paths with compliance. This demonstrates that students generally complied well with the EMA and did not systematically miss EMA reports based on their mental health and self-efficacy, which is promising for future EMA use.Show less
