ArticleHeliyon2023
Integrating personalized experience sampling in psychotherapy: A case illustration of the Therap-i module.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Mechanistic Non-Response After Psychotherapy for Anxiety Disorders: A Maintenance-Mechanism-Based Clinical Taxonomy.Journal of clinical medicine · 2026Review
- Experience sampling methods require more than numbers.Communications psychology · 2026Review
- Integrating Digital Health Data into Clinical Practice: Perspectives and Practical Recommendations.Practice innovations (Washington, D.C.) · 2026Article
- Assessing psychotherapy patients' social context through personal networks and experience sampling: A mixed methods case series exploring feasibility.Neuroscience applied · 2026Article
- Developing a qualitative and quantitative ambulatory assessment-based feedback system within cognitive behavioural interventions for people with persecutory beliefs.Internet interventions · 2025Article
- The Effect of the Virtual Reality-Based Biofeedback Intervention DEEP on Stress, Emotional Tension, and Anger in Forensic Psychiatric Inpatients: Mixed Methods Single-Case Experimental Design.JMIR formative research · 2025Article
- To Use or Not to Use: Exploring Therapists' Experiences with Pre-Treatment EMA-Based Personalized Feedback in the TheraNet Project.Administration and policy in mental health · 2025Article
- 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
- Congruency of multimodal data-driven personalization with shared decision-making for StayFine: individualized app-based relapse prevention for anxiety and depression in young people.Frontiers in psychiatry · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The experience sampling methodology (ESM) is increasingly being suggested as a clinical tool in mental health care, as it offers ecologically valid, microlevel information on psychopathological processes. Patients and clinicians have recommended that applications of ESM should be personalized and integrated into the existing clinical process, but there is still much uncertainty about how implementation may look like. Objective: To provide an example of personalized ESM assessment and feedback being integrated into psychotherapy for depression, specifically looking at the collaborative use of ESM in case conceptualization. Methods: George, a 27-year-old man diagnosed with depression, and his therapist participated in the Therap-i randomized controlled trial, which investigates the efficacy of a personalized ESM module added to psychotherapy. Together, they created a personalized ESM questionnaire, aiming to capture their hypotheses and questions regarding George's case conceptualization. George then filled out his ESM questionnaire five times per day, for 8 weeks. During this period, ESM data were discussed and interpreted by George, his therapist, and a researcher, in three feedback sessions. In these sessions, data were visualized in a flexible feedback interface that allowed for collaborative exploration of George's data. Both patient and therapist evaluated the module through questionnaires and George also participated in a semi-structured evaluation interview. Results: George's ESM questionnaire included personalized items on the topics of self-esteem and open versus withdrawn behavior. He completed 241 (89.3%) assessments. Discussions during the feedback sessions focused on two core themes: First, George's low energy level, which was further explored with regard to his sleep, medication, and activity patterns. Second, his low sense of self-esteem, which led to an in-depth exploration of his thinking patterns and social interactions. The ESM module was seen as useful and insightful by both George and therapist. Conclusions: This case shows how ESM and ESM-based feedback can stimulate the collaborative exploration of the patient's complaints, and how it can provide useful insights for treatment. We discuss how our personalized ESM module relates to current clinical principles and practices, and make suggestions for further implementation.
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