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首页> 外文期刊>JMIR Research Protocols >Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support
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Early Signs Monitoring to Prevent Relapse in Psychosis and Promote Well-Being, Engagement, and Recovery: Protocol for a Feasibility Cluster Randomized Controlled Trial Harnessing Mobile Phone Technology Blended With Peer Support

机译：早期签署监测，以防止精神病复发，促进福祉，参与和恢复：可行性集群的协议随机控制试验利用与同行支持混合的手机技术混合

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Background Relapse in schizophrenia is a major cause of distress and disability and is predicted by changes in symptoms such as anxiety, depression, and suspiciousness (early warning signs [EWSs]). These can be used as the basis for timely interventions to prevent relapse. However, there is considerable uncertainty regarding the implementation of EWS interventions. Objective This study was designed to establish the feasibility of conducting a definitive cluster randomized controlled trial comparing Early signs Monitoring to Prevent relapse in psychosis and prOmote Well-being, Engagement, and Recovery (EMPOWER) against treatment as usual (TAU). Our primary outcomes are establishing parameters of feasibility, acceptability, usability, safety, and outcome signals of a digital health intervention as an adjunct to usual care that is deliverable in the UK National Health Service and Australian community mental health service (CMHS) settings. We will assess the feasibility of candidate primary outcomes, candidate secondary outcomes, and candidate mechanisms for a definitive trial. Methods We will randomize CMHSs to EMPOWER or TAU. We aim to recruit up to 120 service user participants from 8 CMHSs and follow them for 12 months. Eligible service users will (1) be aged 16 years and above, (2) be in contact with local CMHSs, (3) have either been admitted to a psychiatric inpatient service or received crisis intervention at least once in the previous 2 years for a relapse, and (4) have an International Classification of Diseases-10 diagnosis of a schizophrenia-related disorder. Service users will also be invited to nominate a carer to participate. We will identify the feasibility of the main trial in terms of recruitment and retention to the study and the acceptability, usability, safety, and outcome signals of the EMPOWER intervention. EMPOWER is a mobile phone app that enables the monitoring of well-being and possible EWSs of relapse on a daily basis. An algorithm calculates changes in well-being based on participants’ own baseline to enable tailoring of well-being messaging and clinical triage of possible EWSs. Use of the app is blended with ongoing peer support. Results Recruitment to the trial began September 2018, and follow-up of participants was completed in July 2019. Data collection is continuing. The database was locked in July 2019, followed by analysis and disclosing of group allocation. Conclusions The knowledge gained from the study will inform the design of a definitive trial including finalizing the delivery of our digital health intervention, sample size estimation, methods to ensure successful identification, consent, randomization, and follow-up of participants, and the primary and secondary outcomes. The trial will also inform the final health economic model to be applied in the main trial.
机译：精神分裂症中的背景复发是痛苦和残疾的主要原因，并受到焦虑，抑郁和可疑的症状的变化预测（预警迹象[EWSS]）。这些可以用作及时干预以防止复发的基础。但是，关于EWS干预的实施存在相当大的不确定性。目的本研究旨在确定进行最终集群随机对照试验的可行性，比较早期迹象监测，以防止在精神病中复发，并促进常见的福祉，参与和恢复（Empower），以防止常见的治疗（TAU）。我们的主要结果是建立数字健康干预的可行性，可接受性，可用性，安全性和结果信号的参数，作为常规护理的辅助服务，可在英国国家卫生服务和澳大利亚社区心理健康服务（CMHS）环境中提供。我们将评估候选人初级成果，候选二次成果和候选机制的可行性。方法我们将随机化CMHSS授权或TAU。我们的目标是招募高达8名CMHS的服务用户参与者，并按照12个月追随它们。符合条件的服务用户将（1）为16岁及以上，（2）与本地CMHSS接触，（3）已被录取为精神病住院服务或至少在过去的2年中至少接受一次危机干预一次复发，（4）具有国际疾病-10诊断的国际分类，对精神分裂症有关的疾病。还将邀请服务用户提名参与者参加。我们将在招聘和保留方面确定主要审判的可行性以及授权干预的可接受性，可用性，安全性和结果信号。 Empower是一款手机应用程序，可以每天监控福祉和可能的复发EWS。一种算法根据参与者自己的基线计算变化，以便衡量可能的EWS的幸福消息和临床分类。使用应用程序的使用与正在进行的对等支持。结果征聘审判开始于2018年9月，并在2019年7月完成了参与者的后续行动。数据收集正在继续。数据库于2019年7月被锁定，其次是分析和披露组分配。结论该研究中获得的知识将为设计提供明确的试验，包括最终确定提供我们的数字健康干预，样本规范，方法，以确保参与者的成功识别，同意，随机化和后续行动以及主要和主要和二次结果。该审判还将通知最终的健康经济模式在主要审判中适用。

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