Digital Health

Background As artificial intelligence (AI) continues to permeate various sectors including healthcare, understanding its impact on nursing students’ attitudes and intentions to use is crucial. To examine the association of AI ethical awareness, attitudes, anxiety, and intention-to-use AI technology among Jordanian nursing students. Method A descriptive, cross-sectional design was used. The study was conducted in three private universities in Jordan, utilizing a convenience sampling technique; data were collected from a sample of 140 nursing students between January and March 2024. Results Results showed moderate levels of AI ethical awareness, attitudes toward AI technology, anxiety to use AI, and intention-to-use AI technology among Jordanian nursing students. There are no significant differences found in the levels of AI ethical awareness, attitudes toward AI technology, anxiety to use AI, and intention-to-use AI based on gender and study year ( p &lt; 0.01). Intention-to-use AI had a significant positive relationship with AI ethical awareness ( r = 0.521, p &lt; 0.001), students’ attitudes toward AI (0.558, p &lt; 0.001), and anxiety to use AI ( r = 0.407, p &lt; 0.001). Conclusion The need to keep pace with technological developments is urgent and crucial, especially in nursing educational institutions. The findings shed important light on the levels of behavioral intention toward AI, as well as on variables such as ethical awareness, attitudes, and anxiety about AI, and the effect of demographics on participants’ attitudes, anxiety, and intentions to use AI technology.

Moh''d Khair Migdadi

Islam Ali Oweidat

Mohammad R. Alosta

Khalid Al-Mugheed

Amany Anwar Saeed Alabdullah

Sally Mohammed Farghaly Abdelaliem

The association of artificial intelligence ethical awareness, attitudes, anxiety, and intention-to-use artificial intelligence technology among nursing students

护理学生人工智能伦理意识、态度、焦虑与使用意向的关联研究

Background Preparing for aging with personalized technology is crucial due to the growing elderly population. Artificial Intelligence (AI), notably AI chatbots in healthcare, has transformed technology by simulating human-like conversations. Research on middle-aged adults’ acceptance of AI chatbots is limited. Assessing middle-aged individuals’ intentions to use AI is vital for enhancing AI competency among the elderly and guiding future interventions. Objective This study aims to explore the acceptance of middle-aged individuals toward AI chatbots and influencing factors and verify the usability of Technology Acceptance Model 2 (TAM2) in the use of AI technology in middle-aged people, also to inspire the design of future intelligent systems and online interventions for improving the health and well-being of the aging population. Methods A cross-sectional design and snowball sampling method were utilized to conduct an online questionnaire survey among middle-aged adults. The questionnaire was compiled based on TAM2 and was created using the online survey platform. SPSS 26.0 software was used for statistical analysis. Results A total of 259 valid questionnaires were included in the final data analysis. The study reported the Cronbach's α of 0.94 for the questionnaire. We found that perceived ease of use, subjective norm, and user image significantly influence users’ intention to use AI chatbots. Notably, perceived usefulness emerged as a complete mediator in the relationship between subjective norm and intention to use, highlighting its central role in shaping user perceptions. The study also revealed a moderate acceptance level among middle-aged adults, emphasizing the need for targeted interventions. Conclusions This study emphasized the importance of customizing AI technology to improve its adoption among middle-aged adults, providing valuable guidance for developers and policymakers. The findings indicated the need for effective aging preparation that includes technological competency, suggesting that future planning should encompass comprehensive preparations for aging to enhance AI competency among the middle-aged population.

Aoqi Wang

You Zhou

Haoming Ma

Xingyi Tang

Sijia Li

Runyuan Pei

Meihua Piao

Preparing for aging: Understanding middle-aged user acceptance of AI chatbots through the technology acceptance model

为老龄化做准备：基于技术接受模型理解中年用户对AI聊天机器人的接受度

Currently, there is an increased interest in providing mental health care through digital devices and services, and the demand for these services is growing.

Elizaveta Fomicheva

Jasmin Jyrgalbek

Oxana Mikhaylova

What explains trust in online mental health therapy provision platforms? An online descriptive survey

在线心理健康治疗提供平台信任度的解释因素是什么？一项在线描述性调查

In 2018, the UK National Institute for Health and Care Excellence (NICE), in partnership with Public Health England, NHS England, NHS Improvement and others, developed an evidence standards framework (ESF) for digital health and care technologies (DHTs). The ESF was designed to provide a standardised approach to guide developers and commissioners on the levels of evidence needed for the clinical and economic evaluation of DHTs by health and care systems.The framework was developed using an agile and iterative methodology that included a literature review of existing initiatives and comparison of these against the requirements set by NHS England; iterative consultation with stakeholders through an expert working group and workshops; and questionnaire-based stakeholder input on a publicly available draft document.The evidence standards framework has been well-received and to date the ESF has been viewed online over 55,000 times and downloaded over 19,000 times.In April 2021 we published an update to the ESF. Here, we summarise the process through which the ESF was developed, reflect on its global impact to date, and describe NICE's ongoing work to maintain and improve the framework in the context for a fast moving, innovative field.

Harriet Unsworth

Bernice Dillon

Lucie Collinson

Helen Powell

Mark Salmon

Tosin Oladapo

Lynda Ayiku

Gary Shield

Joanne Holden

Neelam Patel

Mark Campbell

Felix Greaves

Indra Joshi

John Powell

Alexia Tonnel

DIGITAL HEALTH

The NICE Evidence Standards Framework for digital health and care technologies – Developing and maintaining an innovative evidence framework with global impact

《NICE数字健康与护理技术证据标准框架——开发和维护具有全球影响力的创新证据框架》

Objective Chronic disease is the leading cause of morbidity and mortality on a global scale. Recent use of intelligent home environments for remote health monitoring has allowed patients to feel safe at home. By encouraging patient engagement and, if necessary, care delivery, smart home environments may be a useful method for managing chronic diseases at home. The purpose of this study is to synthesize the evidence on the usage of smart healthcare in the home for chronic illness management. Methods We conducted a scoping review using the Joanna Briggs Methodology and searched three databases from 2017 to 2022 for original research papers on smart healthcare, smart home technology, home-based technology, home monitoring, and physiological monitoring for chronic illness management. We did a descriptive study on the pertinent data we collected, as well as an analysis of whether the devices met its objectives. Results The final analysis included nine papers, the majority of which were randomized controlled trials. All of the studies were carried out in developed countries. The gadgets or smart healthcare in these studies are categorized based on the technology used and the outcomes measured. Respiratory, weight, and ballistocardiograph measurements, as well as changes in questionnaire ratings, hospitalization, activity monitoring, device acceptability, medication adherence, exercise capacity, and body function, were all measured. Conclusion Smart healthcare applications boost health by monitoring health and wellness, recording physical activity and rehabilitation, and improving overall quality of life. Not all smart home applications, however, served their intended purpose. As a result, more research into the efficacy of smart healthcare is needed to improve its application for chronic illness treatment.

Inge Dhamanti

Ika M. Nia

Krishnaraj Nagappan

Balaji P. Srikaanth

Smart home healthcare for chronic disease management: A scoping review

智能家居医疗在慢性病管理中的应用：范围综述

The COVID-19 pandemic necessitated a major expansion in telemedicine use. The continued use of telemedicine post-pandemic has the potential to enhance healthcare use for people at risk for sub-optimal healthcare access and utilization, such as patients with previous preventable hospitalization. This study analyzed the association between pre-pandemic preventable hospitalizations (PPHs) and telemedicine use during the pandemic.

Chinedum O Ojinnaka

Sandra Yuh

Lora Nordstrom

Omolola E Adepoju

Marisa Domino

Pre-pandemic preventable hospitalization is associated with increased telemedicine use in safety-net settings.

疫情前可预防的住院与安全网环境中增加的远程医疗使用相关。

Objectives To evaluate the effectiveness of shared decision-making informed dietary intervention based on digital health technology, for older adults with type 2 diabetes mellitus and determine its impact on patients’ glycemic control (hemoglobin A1c (HbA1c) and fasting plasma glucose), physical indicators (blood pressure and body mass index), self-management behavior, and self-efficacy. Design A double-arm-randomized controlled trial using a parallel group design was conducted. Participants 124 older adults with type 2 diabetes mellitus recruited from the endocrinology department or diabetes clinics were randomly assigned to the intervention ( n = 64) or control group ( n = 60). Interventions Patients in the intervention group received shared decision-making informed dietary intervention through the digital health system and those in the controlled group received routine dietary management. Primary and secondary outcome measures The primary outcome was HbA1c, and the secondary outcomes were fasting plasma glucose, blood pressure, body mass index, self-management ability, and self-efficacy. Results After 3 months of intervention, compared to the control group, the intervention group showed a statistically significant decrease in HbA1c, diastolic blood pressure, and fasting plasma glucose ( P &lt; 0.05). After the intervention, there were time, group main effects, and interaction effects on diabetes self-management ability and diabetes self-efficacy scores of older adults with type 2 diabetes mellitus ( P &lt; 0.05). Conclusions The intervention program based on a digital health system significantly improved glycemic control and enhanced self-care ability in older adults with type 2 diabetes mellitus. Practice implications Clinicians can integrate digital health technology in behavior change intervention, especially in older adults with chronic disease. Trial registration It was registered and approved by the China Clinical Trials Center (ChiCTR2300071455).

Wei Zhang

Xiaoling Zhu

Xianfeng Que

Xiaoyi Zhang

The effects of shared decision-making informed dietary intervention based on digital health technology in older adults with type 2 diabetes mellitus: A randomized controlled trial

基于数字健康技术的共享决策知情饮食干预对老年2型糖尿病患者的影响：一项随机对照试验

Abbreviation	Digit. Health
Journal Impact	3.00
Quartiles(Global)	PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH(Q2)

ISSN	2055-2076
h-index	30

Publication Information	Publisher: SAGE Publications Inc.，Publishing cycle: ，Journal Type: journal，Open Access Journals: Yes
Basic data	Year of publication: 2018，Proportion of original research papers: 87.05%，Self Citation Rate:10.30%， Gold OA Rate: 93.81%
Journal Fees	$2000Details
Average review cycle	网友分享经验：15 Weeks

Digital Health

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The association of artificial intelligence ethical awareness, attitudes, anxiety, and intention-to-use artificial intelligence technology among nursing students

Preparing for aging: Understanding middle-aged user acceptance of AI chatbots through the technology acceptance model

What explains trust in online mental health therapy provision platforms? An online descriptive survey

The NICE Evidence Standards Framework for digital health and care technologies – Developing and maintaining an innovative evidence framework with global impact

Smart home healthcare for chronic disease management: A scoping review

Pre-pandemic preventable hospitalization is associated with increased telemedicine use in safety-net settings.

The association of artificial intelligence ethical awareness, attitudes, anxiety, and intention-to-use artificial intelligence technology among nursing students

Preparing for aging: Understanding middle-aged user acceptance of AI chatbots through the technology acceptance model

The effects of shared decision-making informed dietary intervention based on digital health technology in older adults with type 2 diabetes mellitus: A randomized controlled trial

What explains trust in online mental health therapy provision platforms? An online descriptive survey