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ILIA研究:一项针对精神分裂症或精神分裂情感性障碍患者基于智能手机和网络的复发监测的随机对照多中心临床试验方案。

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.

作者信息

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

机构信息

Technical University of Munich, TUM School of Medicine and Health, Department of Psychiatry and Psychotherapy, TUM University Hospital, Munich, Germany.

Department of Psychiatry and Neuroscience, Charité - Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany.

出版信息

Eur Arch Psychiatry Clin Neurosci. 2025 Aug 19. doi: 10.1007/s00406-025-02089-7.

Abstract

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 treatment of patients with schizophrenia or schizoaffective disorder.

TRIAL REGISTRATION

German Clinical Trials Register (ID: DRKS00034991; registration date: 30.08.2024).

摘要

背景

尽管抗精神病药物在预防精神分裂症和分裂情感性障碍复发方面已被证明有效,但每三名患者中仍有一名在不到一年的时间内复发。复发会使心理社会和治疗相关结果恶化,并导致巨大的经济成本,主要是由于频繁和长期住院。本项目的目的是评估一种基于智能手机和网络的数字解决方案,用于检测精神分裂症和分裂情感性障碍的早期预警信号,以减少复发和随后的住院治疗。

方法

本随机对照试验比较了在常规精神科门诊治疗中,将一款基于智能手机的应用程序附加用于监测精神分裂症和分裂情感性障碍(ICD-10 F20/F25)患者的复发预警信号,与常规治疗(TAU)且无任何进一步研究相关干预措施的效果。干预组患者使用该应用程序一年,填写每周十项的早期预警信号问卷(EWSQ-10P)并获得应用程序内反馈。临床医生可通过浏览器访问的仪表板查看症状轨迹。如果内置自动算法超过阈值,会向临床医生和患者发送警报,以便及时联系,并作为共同决策过程的一部分,对治疗决策进行可选调整。在八个研究地点共招募了110名门诊患者。

讨论

持续监测早期预警信号有望导致行为改变,并减少精神科住院的必要性和时长,从而降低医疗成本。此外,该干预措施可降低症状严重程度、改善药物依从性、促进共同决策、提高患者积极性或改善生活质量。收集定性数据以更好地了解患者对应用程序使用和复发的需求及偏好。从本研究中获得的见解可整合到常规精神科护理中,改善精神分裂症或分裂情感性障碍患者的长期治疗。

试验注册

德国临床试验注册中心(编号:DRKS00034991;注册日期:2024年8月30日)。

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