| Title: |
The ILIA study: protocol for a randomized-controlled multicenter clinical trial on smartphone- and web-based relapse monitoring for patients with schizophrenia or schizoaffective disorder |
| Authors: |
Hiller, Selina; Emde, Laura; Jais, Denise; Sikorová, Soňa Nevická; Bakstein, Eduard; Španiel, Filip; Urbanová, Kateřina; Hahn, Eric; Zierhut, Marco; Fürstenau, Daniel; Bühner, Markus; Junker, Lukas; Maurus, Isabel; Pogarell, Oliver; Falkai, Peter; Strube, Wolfgang; Bauer, Ingrid; Skuban-Eiseler, Tobias; Priller, Josef; Brieger, Peter; Heres, Stephan; Hasan, Alkomiet; Böge, Kerem; Leucht, Stefan |
| Publication Year: |
2026 |
| Collection: |
FU Berlin: Refubium |
| Subject Terms: |
Digital monitoring; App; Shared-decision making; Schizophrenia; Outpatient treatment; Relapse; ddc:150 |
| Description: |
Background Despite the proven efficacy of antipsychotics in relapse prevention in schizophrenia and schizoaffective disorder, every third patient experiences a relapse within less than one year. Relapses can worsen psychosocial and treatment related outcomes and lead to substantial economic costs, primarily due to frequent and prolonged hospitalizations. The aim of this project is to evaluate a smartphone- and web-based digital solution for detecting early warning signs of schizophrenia and schizoaffective disorder to reduce relapses and subsequent hospitalizations. Methods This randomized controlled trial compares the add-on use of a smartphone-based app for monitoring relapse warning signs in patients with schizophrenia and schizoaffective disorders (ICD-10 F20/F25) used within the routine psychiatric outpatient treatment against treatment as usual (TAU) without any further study-related intervention. Patients in the intervention group use the app for one year, fill in the weekly ten-item Early Warning Signs Questionnaire (EWSQ-10P) and obtain in-app feedback. Clinicians can access the symptom trajectory via a browser-accessible dashboard. If a threshold is exceeded in the inbuilt automatic algorithm, an alert is sent to both, the clinician and patient, enabling timely contact and, as part of a shared decision-making process, an optional adjustment of treatment decision. A total of 110 outpatients are recruited across eight study sites. Discussion Continuous monitoring of early warning signs is expected to lead to behavioral changes and to decrease the necessity and duration of psychiatric hospital stays, thereby lowering healthcare costs. Additionally, the intervention could reduce symptom severity, alleviate medication adherence, shared decision-making, patient activation or quality of life. Qualitative data is collected to better understand patient needs and preferences regarding app usage and relapses. Insights gained from this study can be integrated into routine psychiatric care, improving the long-term ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
14 Seiten; application/pdf |
| Language: |
English |
| DOI: |
10.17169/refubium-51426 |
| DOI: |
10.1007/s00406-025-02089-7 |
| Availability: |
https://refubium.fu-berlin.de/handle/fub188/51696; https://doi.org/10.17169/refubium-51426; https://doi.org/10.1007/s00406-025-02089-7 |
| Rights: |
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. ; https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.3551233F |
| Database: |
BASE |