Wesley Xavier - Academia.edu (original) (raw)

Papers by Wesley Xavier

Biological Psychiatry, 2021

The American Journal of Geriatric Psychiatry, 2021

Quality of Life Research, 2020

Purpose The experience sampling method (ESM) is used for intensive longitudinal time-series data ... more Purpose The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data. Methods We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive–compulsive disorder with comorbid depression...

BMC Medicine, 2020

Background The complexity of psychopathology is evident from its multifactorial etiology and dive... more Background The complexity of psychopathology is evident from its multifactorial etiology and diversity of symptom profiles and hampers effective treatment. In psychotherapy, therapists approach this complexity by using case conceptualization. During this process, patients and therapists closely collaborate on a personalized working theory of the patient’s psychopathology. This is a challenging process and shows low reliability between therapists. With the experience sampling method (ESM), time-series data—valuable for case conceptualization—can be systematically gathered in a patient’s normal daily life. These data can be analyzed and visualized in person-specific networks (PSNs). PSNs may support case conceptualization by providing a schematic representation of association patterns between affective, cognitive, behavioral, and context variables. Main text We adopt a clinical perspective in considering how PSNs might be implemented to serve case conceptualization and what their role...

The past decades of research have seen an increase in statistical tools to explore the complex dy... more The past decades of research have seen an increase in statistical tools to explore the complex dynamics of mental health from patient data, yet the application of these tools in clinical practice remains uncommon. This is surprising, given that clinical reasoning, e.g., case conceptualizations, largely coincides with the dynamical system approach. We argue that the gap between statistical tools and clinical practice can partly be explained by the fact that current estimation techniques disregard theoretical and practical considerations relevant to psychotherapy. To address this issue, we propose that case conceptualizations should be formalized. We illustrate this approach by introducing a computational model of functional analysis, a framework commonly used by practitioners to formulate case conceptualizations and patient-tailored treatment targets.We outline the general approach of formalizing idiographic theories with differential equations, drawing on the example of a functional...

Journal of Affective Disorders, 2019

Clinical psychological science : a journal of the Association for Psychological Science, 2018

Recent literature has introduced (a) the network perspective to psychology and (b) collection of ... more Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures. Two networks can be computed: a , in which one investigates if symptoms (or other relevant variables) predict one another over time, and a , in which one investigates if symptoms predict one another in the same window of measurement. The contemporaneous network is a partial correlation network, which is emerging in the analysis of cross-sectional data but is not yet utilized in the analysis of time series data. We explain the importance of partial correlation networks and exemplify the network structures on time series data of a psychiatric patient.

Journal of affective disorders, Jan 28, 2015

Stability of diagnosis was listed as an important predictive validator for maintaining separate d... more Stability of diagnosis was listed as an important predictive validator for maintaining separate diagnostic classifications in DSM-5. The aim of this study is to examine the longitudinal stability of anxiety disorder diagnoses, and the difference in stability between subjects with a chronic versus a non-chronic course. Longitudinal data of 447 subjects with a current pure anxiety disorder diagnosis at baseline from the Netherlands Study of Depression and Anxiety were used. At baseline, 2-, 4-, and 6-year follow-up mental disorders were assessed and numbers (and percentages) of transitions from one anxiety disorder diagnosis to another were determined for each anxiety disorder diagnosis separately and for subjects with a chronic (i.e. one or more anxiety disorder at every follow-up assessment) and a non-chronic course. Transition percentages were high in all anxiety disorder diagnoses, ranging from 21.1% for social anxiety disorder to 46.3% for panic disorder with agoraphobia at six y...

International Journal of Geriatric Psychiatry, 2015

Biological Psychiatry, 2021

The American Journal of Geriatric Psychiatry, 2021

Quality of Life Research, 2020

Purpose The experience sampling method (ESM) is used for intensive longitudinal time-series data ... more Purpose The experience sampling method (ESM) is used for intensive longitudinal time-series data collection during normal daily life. ESM data give information on momentary affect, activities and (social) context of, for example, patients suffering from mental disorders, and allows for person-specific feedback reports. However, current personalized feedback reports only display a selection of measured variables, and typically involve only summary statistics, thus not reflecting the dynamic fluctuations in affect and its influencing factors. To address this shortcoming, we developed a tool for dynamically visualizing ESM data. Methods We introduce a new framework, ESMvis, for giving descriptive feedback, focusing on direct visualization of the dynamic nature of raw data. In this ESM feedback approach, raw ESM data are visualized using R software. We applied ESMvis to data collected for over 52 weeks on a patient diagnosed with an obsessive–compulsive disorder with comorbid depression...

BMC Medicine, 2020

Background The complexity of psychopathology is evident from its multifactorial etiology and dive... more Background The complexity of psychopathology is evident from its multifactorial etiology and diversity of symptom profiles and hampers effective treatment. In psychotherapy, therapists approach this complexity by using case conceptualization. During this process, patients and therapists closely collaborate on a personalized working theory of the patient’s psychopathology. This is a challenging process and shows low reliability between therapists. With the experience sampling method (ESM), time-series data—valuable for case conceptualization—can be systematically gathered in a patient’s normal daily life. These data can be analyzed and visualized in person-specific networks (PSNs). PSNs may support case conceptualization by providing a schematic representation of association patterns between affective, cognitive, behavioral, and context variables. Main text We adopt a clinical perspective in considering how PSNs might be implemented to serve case conceptualization and what their role...

The past decades of research have seen an increase in statistical tools to explore the complex dy... more The past decades of research have seen an increase in statistical tools to explore the complex dynamics of mental health from patient data, yet the application of these tools in clinical practice remains uncommon. This is surprising, given that clinical reasoning, e.g., case conceptualizations, largely coincides with the dynamical system approach. We argue that the gap between statistical tools and clinical practice can partly be explained by the fact that current estimation techniques disregard theoretical and practical considerations relevant to psychotherapy. To address this issue, we propose that case conceptualizations should be formalized. We illustrate this approach by introducing a computational model of functional analysis, a framework commonly used by practitioners to formulate case conceptualizations and patient-tailored treatment targets.We outline the general approach of formalizing idiographic theories with differential equations, drawing on the example of a functional...

Journal of Affective Disorders, 2019

Clinical psychological science : a journal of the Association for Psychological Science, 2018

Recent literature has introduced (a) the network perspective to psychology and (b) collection of ... more Recent literature has introduced (a) the network perspective to psychology and (b) collection of time series data to capture symptom fluctuations and other time varying factors in daily life. Combining these trends allows for the estimation of intraindividual network structures. We argue that these networks can be directly applied in clinical research and practice as hypothesis generating structures. Two networks can be computed: a , in which one investigates if symptoms (or other relevant variables) predict one another over time, and a , in which one investigates if symptoms predict one another in the same window of measurement. The contemporaneous network is a partial correlation network, which is emerging in the analysis of cross-sectional data but is not yet utilized in the analysis of time series data. We explain the importance of partial correlation networks and exemplify the network structures on time series data of a psychiatric patient.

Journal of affective disorders, Jan 28, 2015

Stability of diagnosis was listed as an important predictive validator for maintaining separate d... more Stability of diagnosis was listed as an important predictive validator for maintaining separate diagnostic classifications in DSM-5. The aim of this study is to examine the longitudinal stability of anxiety disorder diagnoses, and the difference in stability between subjects with a chronic versus a non-chronic course. Longitudinal data of 447 subjects with a current pure anxiety disorder diagnosis at baseline from the Netherlands Study of Depression and Anxiety were used. At baseline, 2-, 4-, and 6-year follow-up mental disorders were assessed and numbers (and percentages) of transitions from one anxiety disorder diagnosis to another were determined for each anxiety disorder diagnosis separately and for subjects with a chronic (i.e. one or more anxiety disorder at every follow-up assessment) and a non-chronic course. Transition percentages were high in all anxiety disorder diagnoses, ranging from 21.1% for social anxiety disorder to 46.3% for panic disorder with agoraphobia at six y...

International Journal of Geriatric Psychiatry, 2015