Loh Pei Yi, Martinengo Laura, Heaukulani Creighton, Tan Xin Yang, Hng Moses, Cheah Yong Yin, Morris Robert J T, Tudor Car Lorainne, Lee Jimmy
Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
Centre for Behavioural and Implementation Sciences Interventions, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
J Med Internet Res. 2024 Dec 23;26:e55924. doi: 10.2196/55924.
Mobile health (mHealth) interventions have gained popularity in augmenting psychiatric care for adults with psychosis. Interest has grown in leveraging mHealth to empower individuals living with severe mental illness and extend continuity of care beyond the hospital to the community. However, reported outcomes have been mixed, likely attributed in part to the intervention and adopted outcomes, which affected between-study comparisons.
This study aimed to critically review outcome measures used to evaluate mHealth interventions for adults with psychosis in relation to the characteristics of mHealth interventions.
A systematic mapping review was conducted. We searched PubMed, CINAHL, Embase, PsycINFO, and Cochrane Libraries from 1973 to the present. Selection criteria included randomized controlled studies of mHealth interventions in adults diagnosed with schizophrenia spectrum disorders. Reviewers worked in pairs to screen and extract data from included studies independently using a standardized form; disagreements were resolved by consensus with an independent reviewer. We report our findings in line with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines.
A total of 1703 citations were screened; 29 publications reporting on 23 studies were included in this review. mHealth interventions for psychosis span a wide range, with psychological therapy being the most-deployed intervention (12/23, 52%), followed by psychoeducation (8/23, 35%) and active self-monitoring (8/23, 35%). Several mHealth interventions for psychosis targeted multiple pillars of biopsychosocial well-being (10/23, 43%); the bulk of interventions (16/23, 70%) incorporated features promoting users' self-management. The majority of mHealth interventions were delivered through applications (14/23, 61%) as the main medium and smartphones (17/23, 74%) as the main channel of delivery. Interventions were primarily administered in the outpatient and community settings (16/23, 70%); many were also blended with in-person sessions (11/23, 48%) or guided remotely (6/23, 26%) by persons, including health care providers or trained peer supporters. The severity of psychosis-related symptoms (21/23, 91%) was the most prevalent outcome, of which positive symptoms (13/23, 57%), mood and anxiety (10/23, 43%), and overall psychopathology severity (9/23, 39%) were most commonly measured. Patient-centric outcomes, including well-being (17/23, 74%)-particularly quality of life (10/23, 43%)-and user experience (15/23, 65%), including feasibility (7/23, 30%), acceptability (7/23, 30%), and engagement (7/23, 26%). Notably, outcome choices remained diverse despite stratification by type of mHealth intervention.
mHealth interventions for psychosis encompass a wide range of modalities and use outcome measures that probe various social and behavioral determinants of health. These should be considered complex interventions, and a holistic evaluation approach combining clinical and patient-centric outcomes is recommended.
移动健康（mHealth）干预措施在增强对成年精神病患者的精神科护理方面越来越受欢迎。利用移动健康来增强严重精神疾病患者的能力并将护理的连续性从医院扩展到社区的兴趣日益浓厚。然而，报告的结果参差不齐，这可能部分归因于干预措施和采用的结果，这影响了研究间的比较。
本研究旨在严格审查用于评估针对成年精神病患者的移动健康干预措施的结果指标，并结合移动健康干预措施的特点进行分析。
进行了一项系统映射综述。我们检索了1973年至今的PubMed、CINAHL、Embase、PsycINFO和Cochrane图书馆。选择标准包括针对被诊断患有精神分裂症谱系障碍的成年人的移动健康干预措施的随机对照研究。评审人员成对工作，使用标准化表格独立筛选和提取纳入研究的数据；分歧通过与独立评审人员达成共识来解决。我们按照PRISMA-ScR（系统评价和Meta分析扩展的范围综述的首选报告项目）指南报告我们的研究结果。
共筛选了1703条引文；本综述纳入了29篇报告23项研究的出版物。针对精神病的移动健康干预措施范围广泛，心理治疗是应用最广泛的干预措施（12/23，52%），其次是心理教育（8/23，35%）和主动自我监测（8/23，35%）。一些针对精神病的移动健康干预措施针对生物心理社会福祉的多个方面（10/23，43%）；大部分干预措施（16/23，70%）包含促进用户自我管理的功能。大多数移动健康干预措施通过应用程序（14/23，61%）作为主要媒介和智能手机（17/23，74%）作为主要传递渠道来实施。干预措施主要在门诊和社区环境中进行（16/23，70%）；许多干预措施还与面对面会议相结合（11/23，48%）或由包括医疗保健提供者或经过培训的同伴支持者在内的人员进行远程指导（6/23，26%）。与精神病相关症状的严重程度（21/23，91%）是最普遍的结果，其中阳性症状（13/23，57%）、情绪和焦虑（10/23，43%）以及整体精神病理学严重程度（9/23，39%）是最常测量的。以患者为中心的结果，包括幸福感（17/23，74%）——特别是生活质量（10/23，43%）——以及用户体验（15/23，65%），包括可行性（7/23，30%）、可接受性（7/23，30%）和参与度（7/23，26%）。值得注意的是，尽管按移动健康干预措施的类型进行了分层，但结果选择仍然多种多样。
针对精神病的移动健康干预措施涵盖了广泛的模式，并使用了探究健康的各种社会和行为决定因素的结果指标。这些应被视为复杂的干预措施，建议采用结合临床和以患者为中心的结果的整体评估方法。
