Rosen Marlene, Betz Linda T, Montag Christian, Kannen Christopher, Kambeitz Joseph
Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany.
Institute of Psychology and Education, Ulm University, Ulm, Germany.
JMIR Res Protoc. 2022 Aug 1;11(8):e35206. doi: 10.2196/35206.
Prevention in psychiatry provides a promising way to address the burden of mental illness. However, established approaches focus on specific diagnoses and do not address the heterogeneity and manifold potential outcomes of help-seeking populations that present at early recognition services. Conceptualizing the psychopathology manifested in help-seeking populations from a network perspective of interacting symptoms allows transdiagnostic investigations beyond binary disease categories. Furthermore, modern technologies such as smartphones facilitate the application of the Experience Sampling Method (ESM).
This study is a combination of ESM with network analyses to provide valid insights beyond the established assessment instruments in a help-seeking population.
We will examine 75 individuals (aged 18-40 years) of the help-seeking population of the Cologne early recognition center. For a maximally naturalistic sample, only minimal exclusion criteria will be applied. We will collect data for 14 days using a mobile app to assess 10 transdiagnostic symptoms (ie, depressive, anxious, and psychotic symptoms) as well as distress level 5 times a day. With these data, we will generate average group-level symptom networks and personalized symptom networks using a 2-step multilevel vector autoregressive model. Additionally, we will explore associations between symptom networks and sociodemographic, risk, and resilience factors, as well as psychosocial functioning.
The protocol was designed in February 2020 and approved by the Ethics Committee of the University Hospital Cologne in October 2020. The protocol was reviewed and funded by the Köln Fortune program in September 2020. Data collection began in November 2020 and was completed in November 2021. Of the 258 participants who were screened, 93 (36%) fulfilled the inclusion criteria and were willing to participate in the study. Of these 93 participants, 86 (92%) completed the study. The first results are expected to be published in 2022.
This study will provide insights about the feasibility and utility of the ESM in a help-seeking population of an early recognition center. Providing the first explorative phenotyping of transdiagnostic psychopathology in this population, our study will contribute to the innovation of early recognition in psychiatry. The results will help pave the way for prevention and targeted early intervention in a broader patient group, and thus, enable greater intended effects in alleviating the burden of psychiatric disorders.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/35206.
精神病学中的预防为应对精神疾病负担提供了一条有前景的途径。然而，既定方法侧重于特定诊断，并未解决早期识别服务中求助人群的异质性和多种潜在结果。从相互作用症状的网络角度对求助人群中表现出的精神病理学进行概念化，有助于进行超越二元疾病类别的跨诊断研究。此外，智能手机等现代技术促进了经验取样法（ESM）的应用。
本研究将ESM与网络分析相结合，以在求助人群中提供超越既定评估工具的有效见解。
我们将对科隆早期识别中心求助人群中的75名个体（年龄在18至40岁之间）进行研究。为了获得最大限度的自然主义样本，仅应用极少的排除标准。我们将使用移动应用程序收集14天的数据，每天5次评估10种跨诊断症状（即抑郁、焦虑和精神病性症状）以及痛苦程度。利用这些数据，我们将使用两步多级向量自回归模型生成平均组水平症状网络和个性化症状网络。此外，我们将探索症状网络与社会人口统计学、风险和复原力因素以及心理社会功能之间的关联。
该方案于2020年2月设计，并于2020年10月获得科隆大学医院伦理委员会批准。该方案于2020年9月由科隆财富计划进行审查和资助。数据收集于2020年11月开始，并于2021年11月完成。在接受筛查的258名参与者中，93名（36%）符合纳入标准并愿意参与研究。在这93名参与者中，86名（92%）完成了研究。首批结果预计于2022年发表。
本研究将提供关于ESM在早期识别中心求助人群中的可行性和效用的见解。我们的研究提供了该人群中跨诊断精神病理学的首次探索性表型分析，将有助于精神病学早期识别的创新。研究结果将有助于为更广泛患者群体的预防和有针对性的早期干预铺平道路，从而在减轻精神疾病负担方面产生更大的预期效果。
国际注册报告识别码（IRRID）：DERR1-10.2196/35206。
