Gee Brendan Loo, Han Jin, Benassi Helen, Batterham Philip J
Centre for Mental Health Research, Australian National University, Acton, Australia.
Australasian Institute of Digital Health, Level 1, 85 Buckhurst Street, South Melbourne, Australia.
Digit Health. 2020 Nov 3;6:2055207620963958. doi: 10.1177/2055207620963958. eCollection 2020 Jan-Dec.
Ecological Momentary Assessments (EMA) offer an approach to understand the daily risk factors of suicide and self-harm of individuals through the use of self-monitoring techniques using mobile technologies.
This systematic review aimed to examine the results of studies on suicidality risk factors and self-harm that used Ecological Momentary Assessments.
Pubmed and PsycINFO databases were searched up to April 2020. Bibliographies of eligible studies were hand-searched, and 744 abstracts were screened and double-coded for inclusion.
The 49 studies using EMA included in the review found associations between daily affect, rumination and interpersonal interactions and daily non-suicidal self-injury (NSSI). Studies also found associations between daily negative affect and positive affect, social support, sleep, and emotions and a person's history of suicide and self-harm. Associations between daily suicide thoughts and self-harm, and psychopathology factors measured at baseline were also observed.
Research using EMA has the potential to offer clinicians the ability to understand the daily predictors, or risk factors, of suicide and self-harm. However, there are no clear reporting standards for EMA studies on risk factors for suicide. Further research should utilise longitudinal study designs, harmonise datasets and use machine learning techniques to identify patterns of proximal risk factors for suicide behaviours.
生态瞬时评估(EMA)提供了一种通过使用移动技术的自我监测技术来了解个体自杀和自我伤害的日常风险因素的方法。
本系统评价旨在研究使用生态瞬时评估的自杀风险因素和自我伤害的研究结果。
检索截至2020年4月的Pubmed和PsycINFO数据库。对符合条件的研究的参考文献进行手工检索,并对744篇摘要进行筛选和双重编码以纳入研究。
纳入该评价的49项使用EMA的研究发现,日常情绪、沉思和人际互动与日常非自杀性自我伤害(NSSI)之间存在关联。研究还发现日常消极情绪与积极情绪、社会支持、睡眠以及情绪与一个人的自杀和自我伤害史之间存在关联。还观察到日常自杀念头与自我伤害之间以及基线时测量的精神病理学因素之间的关联。
使用EMA的研究有可能使临床医生能够了解自杀和自我伤害的日常预测因素或风险因素。然而,关于自杀风险因素的EMA研究尚无明确的报告标准。进一步的研究应采用纵向研究设计,统一数据集,并使用机器学习技术来识别自杀行为的近端风险因素模式。