Testing an integrated model of population mental health: an incidence and inception cohort study

测试人口心理健康的综合模型：发病率和起始队列研究

• 批准号: 506236606
• 负责人: Professor Dr. Ulrich Reininghaus
• 金额: --
• 依托单位: Abteilung Public Mental Health
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/506236606?language=en
• 关键词: Testing; integrated; model; population; mental

Monitoring of population mental health is now considered to play a vital role in health, risk factor and demographic surveillance systems across the globe. Adopting a public mental health perspective on monitoring and surveillance requires us to consider the entire spectrum of mental-ill health, which broadly ranges from severe mental disorders via at-risk populations to positive mental health and well-being. This population mental health approach has become the mainstay of public mental health provision in many European countries, but there has been a dearth of research on this issue in Germany in the past 20 years, and fundamental conceptual and methodological issues remain to be addressed in relation to this approach at both the national and international level. The research aims to establish and delineate the basic epidemiology of population mental health by testing key aspects (i.e., treated incidence, clinical stage transitions, transdiagnostic dimensions, digital momentary phenotypes, population mean) of an integrated transdiagnostic model encompassing the entire continuum of mental ill-health. To achieve this, we will establish a highly innovative, two-arm population-based incidence and inception cohort study, in two tightly defined catchment areas (Mannheim, Rhine-Neckar-Region) in Germany using cutting-edge statistical approaches and digital technology. In the incidence arm, incident cases will be identified using rigorous case ascertainment procedures (including a leakage study) from around 853,816 persons at risk in the two catchment areas over a two-year case ascertainment period, which will provide an equivalent of 1,707,632 person-years at risk. In the inception cohort-arm, we will recruit, at baseline (t0), a population-based, epidemiologically characterized cohort of individuals, who meet criteria for a clinical high-risk state for severe mental disorder (CHARMS, stage 1b) or non-specific psychological distress (stage 1a), as well as individuals, who do not meet these criteria (stage 0), by selecting a stratified random sample from the same catchment areas as incident cases. This cohort will be recruited over a period of 18 months and followed every 6 months, with a minimum follow-up time of 12 months for all participants, corresponding to a total duration for recruitment and assessment of 2.5 years. This will ensure that all participants will be followed at 6 months (t1) and 12 months (t2), whilst allowing us to collect data, where possible, at 18 months (t3) and 24 months (t4), thereby making optimal use of time to event (survival) data. This two-arm design will allow us to calibrate the entire mental ill-health continuum, examine fundamental conceptual and methodological issues, establish nationwide feasibility of design and methods for more comprehensive monitoring of population mental health, and, thereby, provide the basis for assessing the impact of novel public mental health services at the population level.

目前，对人口心理健康的监测被认为在地球仪的健康、风险因素和人口监测系统中发挥着至关重要的作用。从公共心理健康的角度来看待监测和监督，要求我们考虑整个精神疾病的健康范围，从严重的精神障碍到高危人群，再到积极的心理健康和幸福。这种人口心理健康方法已成为许多欧洲国家提供公共心理健康服务的支柱，但在过去20年里，德国对这一问题的研究一直很缺乏，在国家和国际层面上，这种方法的基本概念和方法问题仍有待解决。该研究旨在通过测试关键方面（即，治疗的发病率，临床阶段转换，transdiagnosis尺寸，数字瞬间表型，人口平均值）的综合transdiagnosis模型，涵盖整个连续的精神疾病健康。为了实现这一目标，我们将在德国的两个严格定义的集水区（曼海姆，莱茵-内卡地区）使用尖端的统计方法和数字技术建立一项高度创新的、基于两组人群的发病率和初始队列研究。在发病率组中，将使用严格的病例确定程序（包括泄漏研究）在两年的病例确定期内从两个集水区约853，816名风险人群中确定事件病例，这将提供相当于1，707，632人-年的风险。在初始队列研究中，我们将在基线（t0）招募一组符合严重精神障碍临床高危状态标准的人群，具有流行病学特征（CHARMS，阶段1b）或非特异性心理困扰（第1a阶段），以及不符合这些标准的个人（第0阶段），方法是从与事件病例相同的服务区选择分层随机样本。该队列将在18个月内招募，每6个月随访一次，所有受试者的最短随访时间为12个月，相当于招募和评估的总持续时间为2.5年。这将确保在6个月（t1）和12个月（t2）时对所有受试者进行随访，同时允许我们在可能的情况下收集18个月（t3）和24个月（t4）时的数据，从而最佳利用事件发生时间（生存期）数据。这种双臂设计将使我们能够校准整个精神疾病健康连续体，研究基本的概念和方法问题，建立全国范围内的可行性设计和方法，更全面地监测人口心理健康，从而为评估新的公共精神卫生服务在人口层面的影响提供基础。