ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2021
ESMvis: a tool for visualizing individual Experience Sampling Method (ESM) data.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Studies of Social Anxiety Using Ambulatory Assessment: Systematic Review.JMIR mental health · 2024Pooled it
- Integrating Data Visualizations Into Digital Mental Health Care for Adults With Anxiety and Depression: Participatory Design and Case Study.Journal of participatory medicine · 2026Article
- Experience sampling methods require more than numbers.Communications psychology · 2026Review
- Assessing psychotherapy patients' social context through personal networks and experience sampling: A mixed methods case series exploring feasibility.Neuroscience applied · 2026Article
- An idiographic network approach to modeling daily loneliness and paranoia in psychosis: implications for personalized interventions.Frontiers in psychiatry · 2026Article
- Visualization of Experience Sampling Method Data in Mental Health: Qualitative Study of the Physicians' Perspective in Germany.Journal of medical Internet research · 2025Article
- Real-time Ecological Assessment of the Context of mental and physical Health (REACH) on Curious.Research square · 2025Article
- Developing a qualitative and quantitative ambulatory assessment-based feedback system within cognitive behavioural interventions for people with persecutory beliefs.Internet interventions · 2025Article
- The Association Between Cognitive Functioning and Depression Severity: A Multiwave Longitudinal Remote Assessment Study.Depression and anxiety · 2025Article
- Assessing and accounting for measurement in intensive longitudinal studies: current practices, considerations, and avenues for improvement.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data.Administration and policy in mental health · 2024Article
- Feedback About a Person's Social Context - Personal Networks and Daily Social Interactions.Administration and policy in mental health · 2024Article
- Planning Individual and Population-Based Interventions in Global Health: Applying the DEA-A Framework to Promote Behavioral, Emotional, and/or Cognitive Change among Stakeholders.International journal of environmental research and public health · 2024Article
- Using the experience sampling method to support clinical practice: An illustration with problematic cannabis use.Psychotherapy research : journal of the Society for Psychotherapy Research · 2024Article
- Feedback based on experience sampling data: Examples of current approaches and considerations for future research.Heliyon · 2023Article
- Common methods of determining meaningful change in clinical practice: implications for precision patient-reported outcomes.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023Article
- Integrating personalized experience sampling in psychotherapy: A case illustration of the Therap-i module.Heliyon · 2023Article
- Examining Stress and Residual Symptoms in Remitted and Partially Remitted Depression Using a Wearable Electrodermal Activity Device: A Pilot Study.IEEE journal of translational engineering in health and medicine · 2023Article
- A Web-Based Application for Personalized Ecological Momentary Assessment in Psychiatric Care: User-Centered Development of the PETRA Application.JMIR mental health · 2022Article
- Using feedback tools to enhance the quality and experience of care.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
purposeThe 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.
methodsWe 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.
resultsWe provided personalized feedback, in which both the overall trajectory and specific time moments were captured in a movie format. Two relapses during the study period could be visually determined, and subsequently confirmed by the therapist. The therapist and patient evaluated ESMvis as an insightful add-on tool to care-as-usual.
conclusionESMvis is a showcase on providing personalized feedback by dynamic visualization of ESM time-series data. Our tool is freely available and adjustable, making it widely applicable. In addition to potential applications in clinical practice, ESMvis can work as an exploratory tool that can lead to new hypotheses and inform more complex statistical techniques.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.