文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support.

作者信息

Hatch Ainslie, Hoffman Julia E, Ross Ruth, Docherty John P

机构信息

Otsuka America Pharmaceutical, Inc, Princeton, NJ, United States.

Behavior Dx, San Jose, CA, United States.

出版信息

JMIR Ment Health. 2018 Jun 12;5(2):e46. doi: 10.2196/mental.9777.


DOI:10.2196/mental.9777
PMID:29895514
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6019847/
Abstract

BACKGROUND: Digital technology is increasingly being used to enhance health care in various areas of medicine. In the area of serious mental illness, it is important to understand the special characteristics of target users that may influence motivation and competence to use digital health tools, as well as the resources and training necessary for these patients to facilitate the use of this technology. OBJECTIVE: The aim of this study was to conduct a quantitative expert consensus survey to identify key characteristics of target users (patients and health care professionals), barriers and facilitators for appropriate use, and resources needed to optimize the use of digital health tools in patients with serious mental illness. METHODS: A panel of 40 experts in digital behavioral health who met the participation criteria completed a 19-question survey, rating predefined responses on a 9-point Likert scale. Consensus was determined using a chi-square test of score distributions across three ranges (1-3, 4-6, 7-9). Categorical ratings of first, second, or third line were designated based on the lowest category into which the CI of the mean ratings fell, with a boundary >6.5 for first line. Here, we report experts' responses to nine questions (265 options) that focused on (1) user characteristics that would promote or hinder the use of digital health tools, (2) potential benefits or motivators and barriers or unintended consequences of digital health tool use, and (3) support and training for patients and health care professionals. RESULTS: Among patient characteristics most likely to promote use of digital health tools, experts endorsed interest in using state-of-the-art technology, availability of necessary resources, good occupational functioning, and perception of the tool as beneficial. Certain disease-associated signs and symptoms (eg, more severe symptoms, substance abuse problems, and a chaotic living situation) were considered likely to make it difficult for patients to use digital health tools. Enthusiasm among health care professionals for digital health tools and availability of staff and equipment to support their use were identified as variables to enable health care professionals to successfully incorporate digital health tools into their practices. The experts identified a number of potential benefits of and barriers to use of digital health tools by patients and health care professionals. Experts agreed that both health care professionals and patients would need to be trained in the use of these new technologies. CONCLUSIONS: These results provide guidance to the mental health field on how to optimize the development and deployment of digital health tools for patients with serious mental illness.

摘要

相似文献

[1]
Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support.

JMIR Ment Health. 2018-6-12

[2]
The expert consensus guideline series. Optimizing pharmacologic treatment of psychotic disorders. Introduction: methods, commentary, and summary.

J Clin Psychiatry. 2003

[3]
Promoting and supporting self-management for adults living in the community with physical chronic illness: A systematic review of the effectiveness and meaningfulness of the patient-practitioner encounter.

JBI Libr Syst Rev. 2009

[4]
Right care, first time: a highly personalised and measurement-based care model to manage youth mental health.

Med J Aust. 2019-11

[5]
Expert Consensus Survey on Medication Adherence in Psychiatric Patients and Use of a Digital Medicine System.

J Clin Psychiatry. 2017-7

[6]
Listening to Communities: Mixed-Method Study of the Engagement of Disadvantaged Mothers and Pregnant Women With Digital Health Technologies.

J Med Internet Res. 2017-7-5

[7]
Understanding Technology Preferences and Requirements for Health Information Technologies Designed to Improve and Maintain the Mental Health and Well-Being of Older Adults: Participatory Design Study.

JMIR Aging. 2021-1-6

[8]
The expert consensus guideline series: adherence problems in patients with serious and persistent mental illness.

J Clin Psychiatry. 2009

[9]
The Expert Consensus Guideline Series. Treatment of behavioral emergencies.

Postgrad Med. 2001-5

[10]
Using antipsychotic agents in older patients.

J Clin Psychiatry. 2004

引用本文的文献

[1]
Digital Assessment of Wellbeing in New Parents (DAWN-P): protocol of a randomised feasibility trial comparing digital screening for maternal postnatal depression with usual care screening.

Pilot Feasibility Stud. 2025-4-12

[2]
Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis.

JMIR Ment Health. 2025-1-20

[3]
Machine learning models for temporally precise lapse prediction in alcohol use disorder.

J Psychopathol Clin Sci. 2024-10

[4]
Application of an Adapted Health Action Process Approach Model to Predict Engagement With a Digital Mental Health Website: Cross-Sectional Study.

JMIR Hum Factors. 2024-8-7

[5]
Assessing the Influence of Patient Empowerment Gained Through Mental Health Apps on Patient Trust in the Health Care Provider and Patient Compliance With the Recommended Treatment: Cross-sectional Study.

J Med Internet Res. 2024-2-12

[6]
Facilitators of and Barriers to Integrating Digital Mental Health Into County Mental Health Services: Qualitative Interview Analyses.

JMIR Form Res. 2023-5-16

[7]
Digital Technology in Psychiatry: Survey Study of Clinicians.

JMIR Form Res. 2022-11-10

[8]
Learnings from user feedback of a novel digital mental health assessment.

Front Psychiatry. 2022-10-20

[9]
An examination of neurocognition and theory of mind as predictors of engagement with a tailored digital therapeutic in persons with serious mental illness.

Schizophr Res Cogn. 2022-1-17

[10]
Prescriber Attitudes, Experiences, and Proclivities Toward Digital Medicine and How They Influence Adoption of Digital Medicine Platforms.

Neuropsychiatr Dis Treat. 2021-12-16

本文引用的文献

[1]
Characterizing Smartphone Engagement for Schizophrenia: Results of a Naturalist Mobile Health Study.

Clin Schizophr Relat Psychoses. 2017-8-4

[2]
Accelerating Digital Mental Health Research From Early Design and Creation to Successful Implementation and Sustainment.

J Med Internet Res. 2017-5-10

[3]
Issues for eHealth in Psychiatry: Results of an Expert Survey.

J Med Internet Res. 2017-2-28

[4]
Efficacy of Self-guided Internet-Based Cognitive Behavioral Therapy in the Treatment of Depressive Symptoms: A Meta-analysis of Individual Participant Data.

JAMA Psychiatry. 2017-4-1

[5]
What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions.

PLoS One. 2017-2-2

[6]
Effectiveness and cost-effectiveness of a guided Internet- and mobile-based intervention for the indicated prevention of major depression in patients with chronic back pain-study protocol of the PROD-BP multicenter pragmatic RCT.

BMC Psychiatry. 2017-1-21

[7]
Do We Still Have a Digital Divide in Mental Health? A Five-Year Survey Follow-up.

J Med Internet Res. 2016-11-22

[8]
Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions.

Am J Prev Med. 2016-11

[9]
Adoption of e-health technology by physicians: a scoping review.

J Multidiscip Healthc. 2016-8-1

[10]
mHealth for Schizophrenia: Patient Engagement With a Mobile Phone Intervention Following Hospital Discharge.

JMIR Ment Health. 2016-7-27

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

推荐工具

医学文档翻译智能文献检索