What attributes of digital devices are important to clinicians in rehabilitation? A cross-cultural best-worst scaling study

IF 3.7 2区 医学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Louise Michelle Nettleton Pearce , Martin Howell , Tiê Parma Yamato , Jéssica Maria Ribeiro Bacha , José Eduardo Pompeu , Kirsten Howard , Catherine Sherrington , Leanne Hassett
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引用次数: 0

Abstract

Background

Digital interventions are becoming increasingly popular in rehabilitation. Understanding of device features which impact clinician adoption and satisfaction is limited. Research in the field should be conducted across diverse settings to ensure digital interventions do not exacerbate healthcare inequities.

Objective

This study aimed to understand rehabilitation clinicians’ preferences regarding device attributes and included a cross-cultural comparison.

Materials and Methods

Choice experiment methodology (best-worst scaling) was used to survey rehabilitation clinicians across Australia and Brazil. Participants completed 10 best-worst questions, choosing the most and least important device attributes from subsets of 31 attributes in a partially balanced block design. Results were analysed using multinomial models by country and latent class. Attribute preference scores (PS) were scaled to 0–100 (least to most important).

Results

A total of 122 clinicians from Brazil and 104 clinicians from Australia completed the survey. Most respondents were physiotherapists (83%) working with neurological populations (51%) in the private/self-employed sector (51%) who had experience using rehabilitation devices (87%). Despite preference heterogeneity across country and work sector (public/not-for-profit versus private/self-employed/other), clinicians consistently prioritised patient outcomes (PS 100.0, 95%CI: 86.2–100.0), patient engagement (PS 93.9, 95%CI: 80.6–94.2), usability (PS 81.3, 95%CI: 68.8–82.5), research evidence (PS 80.4, 95%CI: 68.1–81.7) and risk (PS 75.7, 95%CI: 63.8–77.3). In Australia, clinicians favoured device attributes which facilitate increased therapy dosage (PS 79.2, 95%CI: 62.6–81.1) and encourage patient independent practice (PS 66.8, 95%CI: 52.0–69.2). In Brazil, clinicians preferred attributes enabling device use for providing clinical data (PS 67.6, 95%CI: 51.8–70.9) and conducting clinical assessments (PS 65.6, 95%CI: 50.2–68.8).

Conclusion

Clinicians prioritise patients’ needs and practical application over technical aspects of digital rehabilitation devices. Contextual factors shape clinician preferences rather than individual clinician characteristics. Future device design and research should consider preferences and influences, involving diverse stakeholders to account for context-driven variations across cultures and healthcare settings.

数字设备的哪些特性对康复临床医生很重要?跨文化最佳-最差比例研究
数字干预在康复领域越来越受欢迎。人们对影响临床医生采用率和满意度的设备功能了解有限。该领域的研究应在不同的环境中进行,以确保数字化干预不会加剧医疗保健的不平等。本研究旨在了解康复临床医生对设备属性的偏好,并进行跨文化比较。研究采用选择实验方法(最佳-最差比例)对澳大利亚和巴西的康复临床医生进行了调查。参与者完成了 10 个 "最佳-最差 "问题,并在部分平衡块设计中从 31 个属性子集中选择了最重要和最不重要的设备属性。结果采用多项式模型按国家和潜在类别进行分析。属性偏好分数 (PS) 为 0-100(从最不重要到最重要)。共有 122 名巴西临床医生和 104 名澳大利亚临床医生完成了调查。大多数受访者是物理治疗师(83%),他们在私人/自营部门(51%)从事神经系统人群的工作,拥有使用康复设备的经验(87%)。尽管不同国家和不同工作部门(公共/非营利与私营/自营/其他)的偏好存在差异,但临床医生始终优先考虑(PS 100.0,95%CI:86.2-100.0)(PS 93.9,95%CI:80.6-94.2)(PS 81.3,95%CI:68.8-82.5)、(PS 80.4,95%CI:68.1-81.7)和(PS 75.7,95%CI:63.8-77.3)在澳大利亚,临床医生更青睐有利于增加(PS 79.2,95%CI:62.6-81.1)和鼓励患者(PS 66.8,95%CI:52.0-69.2)的设备属性。在巴西,临床医生更倾向于使用设备提供(PS 67.6,95%CI:51.8-70.9)和进行(PS 65.6,95%CI:50.2-68.8)。临床医生优先考虑的是患者的需求和实际应用,而不是数字康复设备的技术方面。影响临床医生偏好的是环境因素,而非临床医生的个人特征。未来的设备设计和研究应考虑偏好和影响因素,让不同的利益相关者参与其中,以考虑不同文化和医疗环境下的环境驱动差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Medical Informatics
International Journal of Medical Informatics 医学-计算机:信息系统
CiteScore
8.90
自引率
4.10%
发文量
217
审稿时长
42 days
期刊介绍: International Journal of Medical Informatics provides an international medium for dissemination of original results and interpretative reviews concerning the field of medical informatics. The Journal emphasizes the evaluation of systems in healthcare settings. The scope of journal covers: Information systems, including national or international registration systems, hospital information systems, departmental and/or physician''s office systems, document handling systems, electronic medical record systems, standardization, systems integration etc.; Computer-aided medical decision support systems using heuristic, algorithmic and/or statistical methods as exemplified in decision theory, protocol development, artificial intelligence, etc. Educational computer based programs pertaining to medical informatics or medicine in general; Organizational, economic, social, clinical impact, ethical and cost-benefit aspects of IT applications in health care.
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