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
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
Background. Student populations show higher prevalence rates of procrastination and symptoms of stress, anxiety and depression compared to the general population. Previous research found evidence...Show moreBackground. Student populations show higher prevalence rates of procrastination and symptoms of stress, anxiety and depression compared to the general population. Previous research found evidence for an association between mental health and procrastination. The current study investigated the association of procrastination with mental health problems using the network perspective and dealt with the question whether procrastination is a state or a trait. Methods. We used Ecological Momentary Assessment (EMA) to collect data from 79 undergraduate students from Dutch universities. Our participants answered questions concerning procrastination and symptoms of stress, anxiety and depression four times a day over a time course of two weeks. We estimated contemporaneous and temporal networks to gain insight in the dynamic connections between these constructs. Moreover, we assessed procrastination with a questionnaire before and after two weeks and compared both assessments in order to investigate if procrastination categorizes as a state or a trait. Results. We found significant contemporaneous associations of procrastination with symptoms of anxiety and depression and a temporal association between procrastination and anxiety. Pre- and posttest on procrastination did not differ significantly. Conclusions. Symptoms of anxiety and depression co-occur at the same point in time and procrastination is a predictor for anxiety symptoms. The pre- and posttest results indicated no change of procrastination over time. However, the dynamic network analysis indicated fluctuations of procrastination over time and situation. We concluded that procrastination exists at trait and state level. It is important to mention that data collection took place during the Covid-19 outbreak.Show less
Previous research has investigated the association between hunger and mental health. Although constructs such as stress, anxiety and depression have been indeed found to be related to appetite,...Show morePrevious research has investigated the association between hunger and mental health. Although constructs such as stress, anxiety and depression have been indeed found to be related to appetite, results are often contradictory and point to different causal directions. The present study investigates such associations in a student population of 84 individuals, by means of an Ecological Momentary Assessment (EMA) method. Participants’ perceived levels of stress, anxiety, depression and hunger were recorded four times per day, during a two-weeks period. In addition, before accessing the study, students had to fill in a baseline assessment, which allowed for a further investigation of the relationship between trait and state hunger. A network approach was utilized for the first statistical analysis, allowing for the depiction of contemporaneous, temporal and between-subjects network, whilst a linear regression analysis was used to compare hunger data at baseline and during EMA. Results failed to replicate previous findings concerning appetite and mental health, as for all networks, hunger was not associated with any other variable of interest. However, we were able to identify a linear relationship between trait and state hunger, with the former being a significant positive predictor of the latter.Show less
Background: Research indicates that probiotics, specific strains of beneficial bacteria, are beneficial against anxiety and depression. There are indications that a potential mechanism behind this...Show moreBackground: Research indicates that probiotics, specific strains of beneficial bacteria, are beneficial against anxiety and depression. There are indications that a potential mechanism behind this might be that probiotics alter interoception and the way we respond to our body needs, which is reflected in interoception. Both critically influence anxiety and depression. Objective: The present study aimed to test whether administering probiotics over a period of four weeks increases the degree of interoception and adaptive responding to body needs in healthy individuals. Also, anxiety and depression were measured. Confirming an increase in the degree of interoception and adaptive responding would show that probiotics trigger a mechanism that reduces anxiety and depression. Design: The study was set up as a randomized, tripleblinded, placebo-controlled within/between subject (placebo versus probiotics), pre- and postintervention assessment design. 89 healthy participants without diagnosed mood or anxiety disorders, aged 18-35 years, received multispecies (diverse strains) probiotics or placebo supplementation over four weeks. In the pre- and post-intervention, degree of interoceptive awareness, adaptive responses, depression, and anxiety. Results: There were no significant changes on any measure, but one unexpected decrease in adaptive responding for the probiotics group. Conclusion: It cannot be concluded that probiotics increase the degree of interoceptive awareness and adaptive responding. Moreover, the results suggest that anxiety and depression are not influenced by probiotics in a healthy sample. However, insights from other research suggests that the effect might be stronger in a depressed and anxious sample. Further research is needed to see whether probiotics might affect interoception and adaptive responding differently in depressed and anxious individuals.Show less
According to the WHO, depression is one of the major causes of disability worldwide. However, the understanding of the disorder remains incomplete. Recently, antibiotic use has been associated with...Show moreAccording to the WHO, depression is one of the major causes of disability worldwide. However, the understanding of the disorder remains incomplete. Recently, antibiotic use has been associated with the onset of mood disorders. It is assumed that microbiota-gut-brain interactions are partly managed by the immune system. Accordingly, this study aimed to clarify the correlations between antibiotic-induced microbial dysbiosis, cognitive reactivity to sad mood (CRSM), and concentration of the antibody secretory immunoglobulin A (sIgA). Participants, which finished an antibiotic treatment within the past three months (n = 47), were compared to control participants (n = 60). Participants’ CRSM was measured using the Leiden Index of Depression Sensitivity (LEIDS-R). Antibody levels of salivary sIgA were investigated by obtaining saliva samples from the participants. Results indicated that antibiotic use was not associated with remarkable differences in sIgA concentration or depression sensitivity, i.e. CRSM. However, based on exploratory observations the preliminary idea of antibiotic use resulting in sex-specific responses was developed and is proposed valuable to be investigated in future research. Moreover, it was examined if antibiotic use can be considered a moderator in the relation between sIgA concentration and CRSM. Antibiotic use did not display a moderating role and CRSM was not predicted by sIgA concentration. The findings within this study were limited by a reduced dataset of sIgA concentrations. Ultimately, in contrast to the hypothesized outcome antibiotic-induced microbial dysbiosis was not associated with a decreased sIgA concentration or increased depression sensitivity of healthy individuals within this study. To clarify the correlation between the microbiota-immune-brain axis, antibiotic use, and mental health future research is needed.Show less
