A5026082079- Mental Health Research Topics
- Digital Mental Health Interventions
- Behavioral Health and Interventions
- Health, Environment, Cognitive Aging
- Functional Brain Connectivity Studies
- Psychological and Temporal Perspectives Research
- Flow Experience in Various Fields
- Impact of Technology on Adolescents
- Cognitive Abilities and Testing
- Education, Achievement, and Giftedness
- Cognitive and developmental aspects of mathematical skills
- Machine Learning in Healthcare
- Schizophrenia research and treatment
University of Groningen
2021-2025
Interuniversity Center for Social Science Theory and Methodology
2022-2024
The use of smartphones and wearable sensors to passively collect data on behavior has great potential for better understanding psychological well-being mental disorders with minimal burden. However, there are important methodological challenges that may hinder the widespread adoption these passive measures. A crucial one is issue timescale: chosen temporal resolution summarizing analyzing affect how results interpreted. Despite its importance, choice rarely justified. In this study, we aim...
Abstract Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context predict well-being, including mood. Different tools used measure various aspects of the context. Digital phenotyping is a commonly technology assess person's behavior objectively. The experience sampling method (ESM) can subjective perception specific interactions. Lastly, egocentric networks often relationship characteristics. These different...
Social interactions are important for well-being, and therefore, researchers increasingly attempting to capture people's social environment. Many different disciplines have developed tools measure the environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology study dynamics within a person In addition, passive sensing behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks...
Given the pervasive role of smartphones in modern life, research into their impact on well-being has flourished. This study addresses existing methodological shortcomings using smartphone log data and experience sampling methods (ESM) to explore bidirectional within-person relationship between usage momentary variables (i.e., affect valence, loneliness, positive affect, negative affect). We further examine different categories usage, namely, communication, social media, other apps. analyze...
Major Depressive Disorder (MDD) is a prevalent mental health disorder often identified by persistentlow mood, and lack of motivation energy. Persons with MDD experience largefluctuations in their symptoms over hours days, which can offer valuable clinical insights,highlighting potential targets for treatment intervention strategies. However, there remains gapin our understanding how feasible it to accurately predict fluctuations depressive symptoms. Inthis preregistered study, we aim explore...
A common goal of researchers using longitudinal data is to develop models that predict emotions orbehaviours, often passively collected from smartphone sensors or wearable devices. Afrequent use case for such the development just-in-time adaptive interventions (JITAIs).However, real-world effectiveness depends on rigorous evaluation. Previous research highlightschallenges in selecting appropriate evaluation methods. To address these, we review key pitfalls inpredictive modelling and provide...
Abstract The social context of a person, meaning their relationships and daily interactions, is an important factor for understanding mental health. However, personalised feedback approaches to psychotherapy do not consider this sufficiently yet. Therefore, we developed interactive prototype focusing specifically on person’s as captured with personal networks (PSN) interactions experience sampling methodology (ESM). We describe the development well two evaluation studies: Semi-structured...
Numerous developmental studies assess general cognitive ability, not as the primary variable of interest, but rather a background variable. Raven’s Progressive Matrices is an easy to administer non‐verbal test that widely used measure ability. However, relatively long administration time (up 45 min) still drawback for it often leaves little interest. Therefore, we machine learning approach – regularized regression in combination with cross‐validation develop short 15‐item version. We did so...
Passive smartphone measures hold significant potential and are increasingly employed in psychological biomedical research to capture an individual's behavior. These involve the near-continuous unobtrusive collection of data from smartphones without requiring active input participants. For example, GPS sensors used determine (social) context a person, accelerometers measure movement. However, utilizing passive presents methodological challenges during analysis. Researchers must make multiple...
One domain frequently assessed in Experience Sampling Methodology (ESM) studies is that of daily activities. This often done with predefined (and unvalidated) categorical items, but can also be using open-ended items. ESM researchers, however, lack tools and guidance analyzing the obtained data. In first part this paper, we use data from a 28-day study which students reported their activities both categorically open-endedly to compare these two assessment approaches. We additionally present...
Abstract Passive smartphone measures hold significant potential and are increasingly employed in psychological biomedical research to capture an individual's behavior. These involve the near-continuous unobtrusive collection of data from smartphones without requiring active input participants. For example, GPS sensors used determine (social) context a person, accelerometers measure movement. However, utilizing passive presents methodological challenges during analysis. Researchers must make...
Passive smartphone measures hold significant potential and are increasingly employed in psychological biomedical research to capture an individual's behavior. These involve the near-continuous unobtrusive collection of data from smartphones without requiring active input participants. For example, GPS sensors used determine (social) context a person, accelerometers measure movement. However, utilizing passive presents methodological challenges during analysis. Researchers must make multiple...
Given the pervasive role of smartphones in modern life, research into their impact on well-being has flourished. This study addresses existing methodological shortcomings by using smartphone-log data and Experience Sampling Methods (ESM) to explore bidirectional within-person relationship between smartphone usage momentary variables (i.e., affect valence, loneliness, positive affect, negative affect). We further examine different categories usage, namely communication, social media, other...
<sec> <title>BACKGROUND</title> Social interactions are important for well-being, and therefore, researchers increasingly attempting to capture people’s social environment. Many different disciplines have developed tools measure the environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology study dynamics within a person In addition, passive sensing behavior via sensors from smartphones or other wearable devices. Furthermore,...