Suppr超能文献

一种促进精神分裂症及相关障碍患者糖尿病自我管理的新型数字干预措施:SMART的开发与可接受性测试

A Novel Digital Intervention to Facilitate Diabetes Self-Management Among People with Schizophrenia and Related Disorders: Development and Acceptability Testing of SMART.

作者信息

Arnautovska Urska, Ritchie Gabrielle, Soole Rebecca, Menon Anish, Korman Nicole, Milton Alyssa, Varnfield Marlien, Kelly Jaimon T, Jansen Pieter M, Baker Andrea, Ireland Derek, Russell Anthony W, Chapman Justin, Mulligan Kathleen, Hirani Shashivadan P, Vitangcol Kathryn Jemimah, McKeon Gemma, Siskind Dan

机构信息

Faculty of Health, Medicine, and Behavioural Sciences, University of Queensland, Brisbane, Queensland, Australia.

Metro South Addiction and Mental Health Services, Queensland Health, Brisbane, Queensland, Australia.

出版信息

Neuropsychiatr Dis Treat. 2025 Jun 26;21:1289-1305. doi: 10.2147/NDT.S513272. eCollection 2025.

Abstract

INTRODUCTION

Compared with the general population, people with schizophrenia and schizophrenia-related disorders (SSD) have a higher prevalence of type 2 diabetes (T2D) and T2D risk factors such as poor diet and sedentary lifestyle. Antipsychotic drugs significantly contribute to this risk through metabolic adverse effects, including weight gain and insulin resistance. Prevention and self-management of T2D is challenging in this population due to inherent motivational and cognitive challenges associated with schizophrenia. The objective of this study was to describe the co-design and test the feasibility, acceptability, and usability of a novel digital health intervention, Schizophrenia and diabetes Mobile-Assisted Remote Trainer (SMART), for prevention and self-management of T2D in people with SSD.

METHODS

SMART was developed through an iterative process including review of relevant literature (eg, disease-specific guidelines), stakeholder involvement, and user testing. A pre-post mixed-methods design was used to assess the acceptability and feasibility of SMART over 4 weeks among five outpatients with schizophrenia/schizoaffective disorder and pre-diabetes/T2D.

RESULTS

The co-design process resulted in a digital intervention, which consisted of personalised, interactive text messages, providing psychoeducation and strengthening motivation for self-care behaviours that promote effective diabetes self-management (ie, nutrition, physical activity, weight management, and stress coping). The pilot study demonstrated good acceptability of SMART (response rates 75-95%). Trends towards improved clinical outcomes were observed in well-being, depression, anxiety, and mental health recovery. Barriers to usability included lack of mobile/internet data, precluding the ability to reply to text messages, and a preference for more hyperlinks and additional interactive features.

CONCLUSION

The comprehensive co-design process resulted in the development of a novel digital intervention for prevention and self-management of T2D tailored to unique needs and preferences of people with SSD. The pilot study findings indicate that SMART is acceptable and potentially usable for this population. Results will inform further adaptation and a future feasibility study to examine preliminary effectiveness of SMART.

摘要

引言

与普通人群相比,精神分裂症及精神分裂症相关障碍(SSD)患者患2型糖尿病(T2D)的几率更高,且存在饮食不良和久坐不动的生活方式等T2D风险因素。抗精神病药物通过体重增加和胰岛素抵抗等代谢副作用显著增加了这一风险。由于精神分裂症存在内在的动机和认知挑战,T2D的预防和自我管理在这一人群中具有挑战性。本研究的目的是描述一种新型数字健康干预措施——精神分裂症与糖尿病移动辅助远程训练器(SMART)的协同设计过程,并测试其在SSD患者中预防和自我管理T2D的可行性、可接受性和可用性。

方法

SMART是通过一个迭代过程开发的,包括对相关文献(如特定疾病指南)的回顾、利益相关者的参与和用户测试。采用前后混合方法设计,在5名患有精神分裂症/分裂情感性障碍和糖尿病前期/T2D的门诊患者中,评估SMART在4周内的可接受性和可行性。

结果

协同设计过程产生了一种数字干预措施,它由个性化的交互式短信组成,提供心理教育并增强促进有效糖尿病自我管理(即营养、体育活动、体重管理和压力应对)的自我护理行为的动机。试点研究表明SMART具有良好的可接受性(回复率75 - 95%)。在幸福感、抑郁、焦虑和心理健康恢复方面观察到临床结果改善的趋势。可用性障碍包括缺乏移动/互联网数据,无法回复短信,以及对更多超链接和额外交互功能的偏好。

结论

全面的协同设计过程产生了一种针对SSD患者独特需求和偏好定制的预防和自我管理T2D的新型数字干预措施。试点研究结果表明SMART对该人群是可接受的且可能可用。研究结果将为进一步调整以及未来检验SMART初步有效性的可行性研究提供参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6e4c/12208133/d0e005a36e70/NDT-21-1289-g0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验