Anna M Langener
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View article: Comparing Training Window Selection Methods for Prediction in Non-Stationarity Time Series
Comparing Training Window Selection Methods for Prediction in Non-Stationarity Time Series Open
The widespread adoption of smartphones creates the possibility to passively monitor everyday behavior via sensors. Sensor data has been linked to moment-tomoment psychological symptoms and mood of individuals and thus could alleviate the b…
View article: Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data
Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data Open
A common goal of researchers using longitudinal data is to develop models that predict emotions orbehaviours, often using passively collected data from smartphone sensors or wearable devices. Afrequent use case for such models is the devel…
View article: Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data
Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data Open
A common goal of researchers using longitudinal data is to develop models that predict emotions orbehaviours, often using passively collected data from smartphone sensors or wearable devices. Afrequent use case for such models is the devel…
View article: Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data
Just in Time or Just a Guess? Addressing Challenges in Validating Prediction Models Based on Longitudinal Data Open
A common goal of researchers using longitudinal data is to develop models that predict emotions orbehaviours, often using passively collected data from smartphone sensors or wearable devices. Afrequent use case for such models is the devel…
View article: Predicting weekly instability in depressive symptoms among individuals diagnosed with Major Depressive Disorder using deep learning and passively-collected movement data
Predicting weekly instability in depressive symptoms among individuals diagnosed with Major Depressive Disorder using deep learning and passively-collected movement data Open
Major Depressive Disorder (MDD) is a prevalent mental health disorder often identified by persistentlow mood, and a lack of motivation and energy. Persons with MDD often experience largefluctuations in their symptoms over hours and days, w…
View article: Assessing daily life activities with experience sampling methodology (ESM): Scoring predefined categories or qualitative analysis of open-ended responses?
Assessing daily life activities with experience sampling methodology (ESM): Scoring predefined categories or qualitative analysis of open-ended responses? Open
One domain frequently assessed in Experience Sampling Methodology (ESM) studies is that of daily activities. This is often done with predefined (and unvalidated) categorical items, but can also be done using open-ended items. ESM researche…
View article: Bidirectional associations between smartphone usage and momentary well-being in young adults: Tackling methodological challenges by combining experience sampling methods with passive smartphone data.
Bidirectional associations between smartphone usage and momentary well-being in young adults: Tackling methodological challenges by combining experience sampling methods with passive smartphone data. Open
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 e…
View article: Assessing Daily Life Activities with Experience Sampling Methodology (ESM): Scoring Predefined Categories or Qualitative Analysis of Open-Ended Responses?
Assessing Daily Life Activities with Experience Sampling Methodology (ESM): Scoring Predefined Categories or Qualitative Analysis of Open-Ended Responses? Open
One domain frequently assessed in Experience Sampling Methodology (ESM) studies is that of daily activities. This is often done with predefined (and unvalidated) categorical items, but can also be done using open-ended items. ESM researche…
View article: A template and tutorial for preregistering studies using passive smartphone measures
A template and tutorial for preregistering studies using passive smartphone measures Open
View article: A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures
A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures Open
Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of dat…
View article: A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures
A Template and Tutorial for Preregistering Studies Using Passive Smartphone Measures Open
Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual's behavior. These measures involve the near-continuous and unobtrusive collection of dat…
View article: Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks
Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks Open
View article: It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data
It’s All About Timing: Exploring Different Temporal Resolutions for Analyzing Digital-Phenotyping Data Open
The use of smartphones and wearable sensors to passively collect data on behavior has great potential for better understanding psychological well-being and mental disorders with minimal burden. However, there are important methodological c…
View article: Bidirectional Associations Between Smartphone Usage and Momentary Well-Being in Young Adults: Tackling Methodological Challenges by Combining Experience Sampling Methods with Passive Smartphone Data
Bidirectional Associations Between Smartphone Usage and Momentary Well-Being in Young Adults: Tackling Methodological Challenges by Combining Experience Sampling Methods with Passive Smartphone Data Open
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) t…
View article: Feedback About a Person’s Social Context - Personal Networks and Daily Social Interactions
Feedback About a Person’s Social Context - Personal Networks and Daily Social Interactions Open
View article: Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review
Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review Open
Background Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people’s social environment. Many different disciplines have developed tools to measure the social environment, …
View article: Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review (Preprint)
Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review (Preprint) Open
BACKGROUND Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people’s social environment. Many different disciplines have developed tools to measure the social environment,…
View article: A shortened version of Raven’s standard progressive matrices for children and adolescents
A shortened version of Raven’s standard progressive matrices for children and adolescents Open
Numerous developmental studies assess general cognitive ability, not as the primary variable of interest, but rather as a background variable. Raven’s Progressive Matrices is an easy to administer non‐verbal test that is widely used to mea…