The literature on risk and protective factors for depression focuses on biological, demographic, social-environmental, and psychological factors. Estimating a network model, this thesis project...Show moreThe literature on risk and protective factors for depression focuses on biological, demographic, social-environmental, and psychological factors. Estimating a network model, this thesis project explores how dynamic psychological risk and protective factors for depression interact and determines which factors are more central to a network of these factors (Research Question 1). It also tests if dynamic risk and protective coping factors relate to current depressive symptoms, as prior studies suggest (Research Question 2). Cross-sectional data from 453 students at a Dutch higher education participating in the WARN-D research project were analyzed. Overall, protective factors clustered together, as risk factors did. The strongest positive associations emerged between Seeking Distraction and Ignoring and between Locus of Control and Optimism. The strongest negative relations merged between Seeking Social Support and Ignoring, Resilience and Intolerance of Uncertainty, and Catastrophizing. Self-efficacy, Resilience, and Self-esteem were the most central features of the network. The results did not support the hypothesis that all the included risk and protective factors are related to current depressive symptoms. Only some were, with the strongest positive associations being between current depressive symptoms and Persistent Thinking and Optimism. Despite the limitations of the present work, these findings highlight the importance of further research on risk and protective factors for depression.Show less
Poor mental health in students is deemed to be the next global crisis due to the increasing number and severity of symptoms. It is even further amplified by the effects of the Coronavirus Disease...Show morePoor mental health in students is deemed to be the next global crisis due to the increasing number and severity of symptoms. It is even further amplified by the effects of the Coronavirus Disease 2019 (COVID-19). Many students are left alone and are not accommodated by their university, creating a vulnerable group to develop mental illnesses. However, joy as an intense and brief positive emotion may serve as a protective factor. Thus, this study aims to increase our understanding of the relationship between student mental health and the daily experience of joy. By utilizing an ecological momentary assessment for 15 days, 63 Dutch and international bachelor students enrolled at Leiden University were queried about their experience of their mental health (depression, anxiety, and stress) and joy. The data was interpreted by applying a network analysis that generates contemporaneous and temporal network models. The results illustrate that daily fluctuation of joy decreases subclinical measures of depression, anxiety, and stress within the same momentary assessment period on a contemporaneous level. On a temporal level, joy predicts future improvement of anhedonia, worrying, and relaxation, whereas worrying about the future predicts reduced joy. In accordance with prior literature, we conclude that joy may protect against future depressive symptoms and prevent the progression of anxiety. Additionally, joy may contribute to a stress-buffering effect. Bearing in mind the study’s limitations, future research should consider defining joy more precisely, capture the broad spectrum of mental health in EMA, and investigate joy's contribution to resilience.Show less
Sedentary behavior as a medical and psychological risk factor has gained attention in the last decade. However, little is yet known about its relevance in the subclinical student population,...Show moreSedentary behavior as a medical and psychological risk factor has gained attention in the last decade. However, little is yet known about its relevance in the subclinical student population, despite student’s elevated risk for the development of psychological disorders. To investigate the mutual interaction of sedentary behavior with state mental health variables, we conducted a 2-part study, consisting of a baseline questionnaire (N=66) and a 2-week ecological momentary assessment (N=63). The ecological momentary assessment took place 4 times per day and consisted of items assessing states of stress, anxiety and depression, as well as time spent engaging in sedentary behavior. A network analysis was then conducted based on the data from the ecological momentary assessment to investigate partial correlations between the assessed variables. A small relation between sedentary behavior and worrying was found, with worrying predicting sedentary behavior at the next time point with a partial correlation of 0.08. This finding is discussed and evaluated based on strenghts and limitations of the study, with a focus on factors that could have limited statistical power. Future research could be advanced by creating validated measures in terms of ecological momentary assessment items as well as a modern sedentary behavior questionnaire.Show less
Introduction: University students are at particular risk for developing mental health problems due to life changes and age of onset. One variable that often influences mental health is fatigue....Show moreIntroduction: University students are at particular risk for developing mental health problems due to life changes and age of onset. One variable that often influences mental health is fatigue. Prior research has found a strong association between fatigue and psychiatric disorders. The study investigated if the level of fatigue influences depression, anxiety, and stress or vice versa. Method: For 15 days and 4 times a day, students were asked questions on their smartphones regarding symptoms of depression, stress, anxiety, and fatigue. With this data, network models estimated the relationship between those variables. Results: Sample descriptives, mental health descriptives, time series data, and network models were made. The network models show that the strongest relationships between variables are between stress and anxiety and between depression items. The temporal network shows a bidirectional link between fatigue and having a bad outlook on the future. Discussion: In spite of its limitations, conclusions about the link between fatigue and outlook on the future can be drawn.Show less
In light of the growing mental health crisis in university students and increased social media usage in this population, we conducted the present study to investigate a potential relationship....Show moreIn light of the growing mental health crisis in university students and increased social media usage in this population, we conducted the present study to investigate a potential relationship. Previous research reports conflicting results about the psychological consequences of social media use. Findings differ depending on the user’s engagement with social networking sites. Active social media use, commenting, and messaging, versus passive use, lurking, and browsing, may benefit mental health. The present study used Ecological Momentary Assessment to collect data at different time points during the day. The sample consisted of Leiden University students (N=63) who were recruited online. Participants reported about their social media use and filled out the DASS-21 before answering four questionnaires per day for fifteen days through a smartphone application. Throughout the length of the study, participants were asked two DASS-21 items for depressive, anxiety, and stress symptoms each and how much time they spend with active SNS activities in the last three hours. Analysis and visualization were provided via a contemporaneous and a temporal model, showing partial correlations and predictions. Depressive and anxiety symptoms did not relate to active social media use on the contemporaneous level. However, one stress symptom, feeling irritable, related to using social media in an active way. No relations between depressive and stress symptoms and active social media use were found on the temporal level. One anxiety symptom, worrying, predicted using social media actively and vice versa. The current findings are discussed in terms of possible explanations and implications for future research.Show less
Coronavirus disease 2019 has negatively affected the general population, and especially university undergraduates. Attending to and being aware of the present moment in an open, accepting and...Show moreCoronavirus disease 2019 has negatively affected the general population, and especially university undergraduates. Attending to and being aware of the present moment in an open, accepting and compassionate manner (i.e. mindfulness) has been shown to decrease depression, anxiety, and stress symptoms, and increase positive affect. In our present study, we used network analysis to examine the associations between anxiety, depression, stress, mindfulness and joy. An observational research design was used with a convenience sample of 66 undergraduate students aged 18 to 34 years who completed an ecological momentary assessment (EMA) on their phones. They were asked eight questionsーtwo psychological constructs and six subclinical psychopathology symptomsーfour times a day for two weeks. Network analysis resulted in temporal and contemporaneous network models, indicating that mindfulness at time t does not significantly predict any variable at later time t+1 on the temporal level. At the contemporaneous level, mindfulness is associated with depression, anxiety, stress, and joy. Given the limitations of the present study and the hypothesis generating nature of network analysis, we conclude that the significant partial correlations between mindfulness, psychological well-being and joy in the contemporaneous network may indicate potential causal relations worth following up on in future research.Show less
In light of the novel coronavirus that emerged in December 2019, changes in our daily lives are inevitable and students’ mental health is at risk. During the third lockdown of the COVID-19 pandemic...Show moreIn light of the novel coronavirus that emerged in December 2019, changes in our daily lives are inevitable and students’ mental health is at risk. During the third lockdown of the COVID-19 pandemic in the Netherlands, we used Ecological Momentary Assessment (EMA) while following 63 bachelor students attending Leiden University, sending them mini-surveys, 4 times a day for a period of 15 days. These surveys included two questions per each subscale of the DASS-21 variables (depression, stress, and anxiety) and one question concerning physical activity (PA). Through the use of network models (contemporaneous and temporal), we analyzed the given partial correlations and interpreted them accordingly. Before the EMA study, participants (N = 66) completed a baseline assessment. In this study, we investigate the influence PA and mental health have on each other, as previous research states that PA has a positive influence on mental health, and that the state of one’s mental health influences how physically active someone is. Our sample of students spent about an hour a day, 2-3 times a week being physically active. Findings based on the EMA data, show a relation between the engagement in physical activities (PAs) for the recommended amount of time, and a drop in depressive and anxiety-like symptoms. This goes together with an increase in one’s mood (affect) and low feelings of arousal. According to previous research, being physically active establishes resilience within an individual, which can act as a buffer against stressful situations. These findings are discussed using possible explanations.Show less
Research master thesis | Psychology (research) (MSc)
open access
Evidence-based mental health programs have long conceptualized mental disorders as interactions between thoughts, feelings, behaviours and external factors. Idiographic network models are a...Show moreEvidence-based mental health programs have long conceptualized mental disorders as interactions between thoughts, feelings, behaviours and external factors. Idiographic network models are a relatively novel way of estimating such intra-individual psychological processes. These methods are not without limitations, and concerns have been raised about the stability and accuracy of estimated networks. The extend to which idiographic networks are stable, or vary over time, is unknown. We explored temporal network stability from three angles, exploring variation within people, across different stability metrics, and across people. We reanalysed daily symptom records of people with personality disorders. We fit graphical Vector Autoregressive models separately for the first and second 50 days of consecutive measurements. Contemporaneous but not temporal idiographic networks appeared to be relatively stable within people. The assessment of stability varied considerably across metrics applied. There was large variation in network stability of contemporaneous structures across people, which could not be explained by subject-specific variables. We illustrate the temporal changes in contemporaneous network structures of two participants with high and low network stability and discuss the most pressing questions to be considered by future research.Show less
Research master thesis | Psychology (research) (MSc)
open access
Eating disorders (EDs) are characterized by extreme symptom heterogeneity within diagnostic categories, which complicates treatment and inherently causes high relapse rates. The ability to predict...Show moreEating disorders (EDs) are characterized by extreme symptom heterogeneity within diagnostic categories, which complicates treatment and inherently causes high relapse rates. The ability to predict ED course in individuals would support clinicians in identifying early warning signals of relapse and to intervene accordingly. Traditional approaches have considered EDs as the shared origin of all symptoms which are reflective of a disorder, hindering prediction as it does not allow to unravel mechanisms of symptom progression. Network analysis provides new insights on EDs as it allows to model symptoms as networks of mutually causal relationships. However, most network analysis studies are limited as they only allow for conclusions on group-level at one single time point. By using time series data and intraindividual networks we can incorporate both individual and temporal information yielding insight in within-person variations over time. In this proof-of-concept study, we predicted ED severity using time series and intra-individual network features derived from ecological momentary assessment data in a transdiagnostic ED sample (n = 63). We explored whether time series and network features added to model performance on top of demographic and clinical features using machine learning and what features were most predictive of ED severity. Our findings show no convincing evidence that time series and network features improve predictive accuracy. Nonetheless, some time series and network features were identified as important, highlighting their potential clinical value. We consider our proposed combination of intra-individual networks and machine learning as a starting point towards personalized prediction of psychological outcomes.Show less
Background: Humans do not only act to benefit themselves but also others, i.e. they engage in prosocial behavior. This is especially true for people high in empathy. A prerequisite for prosocial...Show moreBackground: Humans do not only act to benefit themselves but also others, i.e. they engage in prosocial behavior. This is especially true for people high in empathy. A prerequisite for prosocial behavior is that people learn how to obtain benefits for others (prosocial reinforcement learning). Studies indicate enhancing effects of oxytocin on prosocial behavior; however, little is known about the relationship between oxytocin, learning to benefit others, and empathy. This study investigated the effects of oxytocin on prosocial reinforcement learning and whether these effects differ based on empathic abilities. Method: A double-blind placebo-controlled cross-sectional study was conducted. Healthy male participants (N=28) were administered 24 international units of intranasal oxytocin or a placebo and performed a prosocial learning task in which they could earn a monetary reward for oneself, another person, or no one. Empathy was measured with the online simulation subscale (Reniers et al., 2011). Results: Results revealed no significant difference in prosocial learning when participants received oxytocin or placebo. Further, the effects of oxytocin did not significantly differ when empathy was taken into account. Conclusions: Findings suggest that oxytocin does not facilitate prosocial learning. Further, empathy did not have an influence on the effects of oxytocin on prosocial learning. Although the findings did not provide supportive evidence for the Social Salience Hypothesis (ShamayTsoory & Abu-Akel, 2016), the current study revealed new insights on potential effects of oxytocin on reinforcement learning in a prosocial context considering empathy.Show less
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder marked by inattention, hyperactivity, or impulsive behavior. This disorder affects areas such as academic...Show moreAttention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder marked by inattention, hyperactivity, or impulsive behavior. This disorder affects areas such as academic functioning, social interactions, and general mental wellbeing. The current study aimed to investigate how these domains are connected in adolescents with ADHD as compared to their peers without the disorder. To examine this, we employed the network approach which allows to model the statistical relations of multiple variables as a network, where separate associations between variables can be observed. The current study used data from sweep 6 of the Millennium Cohort Study, a longitudinal study from the UK following a cohort of children throughout their lives. The final sample consisted of two groups (healthy and ADHD) with 185 14-year-old participants in each group. Networks of the following variables were estimated: hyperactivity, conduct problems, emotional symptoms, peer problems, prosocial behavior, mood and feelings, academic self-concept, school motivation, and truancy. Completed analyses showed that the ADHD network had higher global strength, i.e., the number of connections in the network. This demonstrates the potential stronger associations between variables relating to school, peers, and mental wellbeing in children with ADHD and indicates possible different mechanisms of the disorder. We also found conduct problems to be the most central variable in both networks, suggesting it may be a factor with complex and meaningful relationships to other variables of interest. Overall, the current study encourages future research to investigate ADHD in academic contexts more closely and focus on mental health-related factors.Show less
Research master thesis | Psychology (research) (MSc)
open access
Death by suicide a global health problem, often preceded with the experience of suicidal ideation. Both depression and anxiety increase the risk of experiencing suicidal ideation. However, the...Show moreDeath by suicide a global health problem, often preceded with the experience of suicidal ideation. Both depression and anxiety increase the risk of experiencing suicidal ideation. However, the specific relations between symptoms of depression and anxiety on the one hand, and suicidal ideation on the other, remain unexplored. Therefore, we investigated these relations both at the cross-sectional (N = 2981) and the temporal level (N = 2596), with a follow-up time of 2 years. We included data from the NESDA study and controlled for the covariates age and gender. To do so, we used unregularized network models, each consisting of 21 nodes. In each network, 10 nodes represented depression items, 10 nodes represented anxiety items, and one node represented suicidal ideation. Results showed that the relation between suicidal ideation and depression was stronger than the relation between suicidal ideation and anxiety. This held true at the cross-sectional and temporal level. Overall, depression and anxiety symptoms at baseline explained about 15% of suicidal ideation at the cross-sectional level, and up to 13% at the temporal level. However, these percentages are not directly comparable, because only for the temporal analyses did we control for previous suicidal ideation. Results should be replicated and further investigated in order to be able to draw firm conclusions.Show less
The growth and development of psychology and mental healthcare is accompanied by a rapid increase in the number of assessment instruments that are utilizer. The downside of presented variety and...Show moreThe growth and development of psychology and mental healthcare is accompanied by a rapid increase in the number of assessment instruments that are utilizer. The downside of presented variety and availability is an abundance, which hinders interpretation of test results, comparison of outcomes, and communication among colleagues and with patients about their test results. This may lead to diminished patient involvement and treatment progress. A common metric is lacking, linking test scores to a common metric, such as the T-score metric based on the Item Response Theory (IRT), may provide a solution to the Babel tower dilemma. The current study investigates the feasibility of an approach to develop a common metric and applies this to three anxiety-related questionnaires: Agoraphobic Cognitions Questionnaire (ACQ), Bodily Sensations Questionnaire (BSQ), and Mobility Inventory (MI) based on the data collected from 210 patients and 430 normal participants. IRT was applied to attain T-scores, form non-linear transformation formulas to estimate T-scores based on raw test scores and theory-based T-scores. The distributions and correspondence of the two Tscores were inspected. The theory-based T-scores and T-scores based on transformation formulas correspond sufficiently for ACQ and BSQ, but for the MI the proposed approach failed to produce useable T-scores. The reasons, pros and cons of IRT are discussed, as well as practical applications, focusing the attention on Routine Outcome Monitoring (ROM). The use of a common metric will allow ease comparison of scores from various instruments and aids communication, while characteristics of IRT allow the use of variable questionnaires and adaptive tailored testing assisting the utilization of ROM in treatment.Show less
