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一项关于人工智能辅助DICE算法在低资源环境下管理行为和心理症状的有效性的12周整群随机对照试验:研究方案。

A 12-week cluster randomized controlled trial of the effectiveness of an AI-aided DICE algorithm for BPSD management in low-resource settings: a study protocol.

作者信息

Zheng Yaonan, Zhang Xingyu, Li Wenxiu, Ji Jun, Wang Huali

机构信息

Dementia Care and Research Center, Peking University Institute of Mental Health (Sixth Hospital), Beijing, China.

National Clinical Research Center for Mental Disorders (Peking University), NHC Key Laboratory for Mental Health, Beijing, China.

出版信息

Front Psychiatry. 2025 May 23;16:1548638. doi: 10.3389/fpsyt.2025.1548638. eCollection 2025.

Abstract

BACKGROUND

The "Describe-Investigate-Create-Evaluate" (DICE) approach has been considered a guide for managing behavioral and psychological symptoms of dementia (BPSD). However, limited resources may limit the implementation of the DICE approach. With the development of AI technology, the effectiveness of the AI-aided DICE algorithm for BPSD management has yet to be determined. Therefore, this study aims to examine the effectiveness of the AI-aided DICE algorithm for managing BPSD in low-resource settings.

METHODS

The cluster randomized controlled trial will be conducted in 12 medical facilities where geriatric psychiatrists are not fully installed. One hundred eighty-four persons with mild and moderate BPSD will be enrolled and randomized to the AI-aided DICE group (n=92) and usual care group (n=92). In the AI-aided DICE group, all participants will receive a comprehensive assessment on a digital triage platform to identify individualized needs and target symptoms, be prescribed a personalized management plan based on the AI-aided decision process, be monitor the implementation of the management plan, and receive follow-up assessment to evaluate the effectiveness. The neuropsychiatric inventory questionnaire and caregiver burden inventory will measure primary and secondary outcomes. The study duration for each participant will be 12 weeks.

DISCUSSION

The study will examine the effectiveness of the AI-aided DICE algorithm for managing BPSD in low-resource settings. The findings will support the implementation of an AI-aided algorithm and leverage the practice of quality care for dementia.

摘要

背景

“描述-调查-制定-评估”(DICE)方法被认为是管理痴呆行为和心理症状(BPSD)的指南。然而,资源有限可能会限制DICE方法的实施。随着人工智能技术的发展,人工智能辅助DICE算法用于BPSD管理的有效性尚未确定。因此,本研究旨在检验人工智能辅助DICE算法在资源匮乏环境中管理BPSD的有效性。

方法

将在12个未配备足额老年精神科医生的医疗设施中进行整群随机对照试验。184名轻度和中度BPSD患者将被纳入研究,并随机分为人工智能辅助DICE组(n=92)和常规护理组(n=92)。在人工智能辅助DICE组中,所有参与者将在数字分诊平台上接受全面评估,以确定个体化需求和目标症状,根据人工智能辅助决策过程制定个性化管理计划,监测管理计划的实施情况,并接受随访评估以评估有效性。神经精神科问卷和照料者负担问卷将用于测量主要和次要结局。每位参与者的研究持续时间为12周。

讨论

本研究将检验人工智能辅助DICE算法在资源匮乏环境中管理BPSD的有效性。研究结果将支持人工智能辅助算法的实施,并推动痴呆症优质护理实践。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ab98/12143266/9f973dc67b65/fpsyt-16-1548638-g001.jpg

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