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融合主动和被动数字技术方法以改善早期精神病症状监测。

Blending active and passive digital technology methods to improve symptom monitoring in early psychosis.

机构信息

Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

South London & Maudsley NHS Foundation Trust, Maudsley Hospital, London, UK.

出版信息

Early Interv Psychiatry. 2019 Oct;13(5):1271-1275. doi: 10.1111/eip.12796. Epub 2019 Feb 28.

DOI:10.1111/eip.12796
PMID:30821079
Abstract

AIMS

Psychotic symptoms fluctuate over time and effective and regular monitoring may contribute to relapse prevention and improve long-term outcomes. In this proof-of-concept study we test the feasibility, acceptability and potential usefulness of a novel digital method assessing the association between physiological signals and psychotic symptom distress.

METHODS

Fifteen participants with first episode psychosis were asked to use a self-assessment mobile phone application for psychotic symptom monitoring for 10 days while using a wrist worn device continuously recording heart rate variability (HRV) and electrodermal activity (EDA). We compared physiological activity when participants reported experiencing distressing and non-distressing psychotic symptoms.

RESULTS

Participants completed on average 76% of the mobile phone symptom assessments. When reporting distressing hallucinations and delusions participants had significantly higher EDA levels and non-significant lower HRV values compared to when these symptoms were non-distressing.

CONCLUSIONS

This study provides further evidence linking psychotic symptom's distress, as experienced in everyday life, and autonomic deregulation. This proof-of-concept study may lead to further longer-term efforts to identify relapse biosignatures using automated methods based on passive monitoring. This method may allow for earlier interventions, contribute to improve relapse prevention and reduce symptoms interfering with recovery.

摘要

目的

精神症状随时间波动,有效的定期监测可能有助于预防复发并改善长期预后。在这项概念验证研究中,我们测试了一种评估生理信号与精神症状困扰之间关联的新型数字方法的可行性、可接受性和潜在有用性。

方法

15 名首发精神病患者被要求在 10 天内使用自我评估手机应用程序进行精神病症状监测,同时连续佩戴腕部设备记录心率变异性 (HRV) 和皮肤电活动 (EDA)。我们比较了参与者报告出现痛苦和非痛苦精神症状时的生理活动。

结果

参与者平均完成了手机症状评估的 76%。当报告痛苦的幻觉和妄想时,与这些症状不痛苦时相比,参与者的 EDA 水平显著升高,HRV 值显著降低。

结论

这项研究进一步证明了日常生活中经历的精神症状困扰与自主神经失调有关。这项概念验证研究可能会进一步努力,使用基于被动监测的自动化方法来识别复发的生物标志物。这种方法可能允许更早的干预,有助于预防复发,并减少症状对康复的干扰。

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