利用干预绘图为中风幸存者和雇主开发数字化、自我指导的重返工作工具包。

IF 7.7
PLOS digital health Pub Date : 2025-08-06 eCollection Date: 2025-08-01 DOI:10.1371/journal.pdig.0000971
Kristelle Craven, Jain Holmes, Jade Kettlewell, Kathryn Radford
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引用次数: 0

摘要

在高收入国家的工作年龄成年人中,中风发病率正在上升。雇主往往缺乏支持中风后重返工作岗位的知识和技能。在英国,近40%的中风幸存者停止工作。职业康复很难获得,自我指导的资源往往缺乏支持实际应用的工具。这项研究为中风幸存者和雇主开发了一个自我指导的重返工作工具包。遵循六步干预映射方法中的步骤1-4。干预目标、内容和设计是通过与雇主(n = 12)的三次在线研讨会和与咨询小组(n = 20)的会议来了解的,咨询小组包括中风慈善机构和工会代表、中风幸存者、医疗保健专业人员以及人力资源和职业康复专家。基于理论的预测试(基于任务的可用性审查,咨询小组讨论)由咨询小组成员的原型审查形成,包括雇主(n = 4),中风幸存者(n = 7)和医疗保健专业人员(n = 4)。框架分析用于构建与可接受性、易用性/易学性、可访问性、包容性、感知有用性以及技术或环境问题相关的反馈。没有分析个人资料。该工具包旨在增强中风幸存者和雇主的权能,使他们能够规划和管理中风后可持续的重返工作岗位。它以两个Xerte电子学习包的形式存在,具有屏幕阅读器兼容性和键盘导航等辅助功能。该工具包为a)中风幸存者和b)雇主提供理论和循证内容,并包括可下载的PDF工具。以中风幸存者为中心的内容提供了识别和向雇主披露支持需求的指导。以雇主为中心的内容指导雇主增加和保持对中风幸存者工作能力的了解,并实施和监测量身定制的合理调整。预测试表明,该工具包是全面的,授权的,并促进开放的沟通,提供关键信息和实用工具。提出了一些小的改进和技术改进。该工具包解决了联合王国在重返工作指导方面的差距。需要在实际环境中进行细化、测试和评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Development of a digital, self-guided return-to-work toolkit for stroke survivors and employers using intervention mapping.

Stroke incidence is rising among working-age adults in high-income countries. Employers often lack knowledge and skills to support return-to-work post-stroke. In the United Kingdom, nearly 40% of stroke survivors stop working. Vocational rehabilitation is rarely accessible, and self-guided resources often lack tools to support practical application. This study developed a self-guided return-to-work toolkit for stroke survivors and employers. Steps 1-4 of the six-step Intervention Mapping approach were followed. Intervention goal, content, and design were informed by three online workshops with employers (n = 12) and meetings with an advisory group (n = 20), including stroke charity and trade union representatives, stroke survivors, healthcare professionals, and experts in human resources and vocational rehabilitation. Theory-based pretesting (task-based usability review, advisory group discussions) was shaped by prototype review with advisory group members, including employers (n = 4), stroke survivors (n = 7), and healthcare professionals (n = 4). Framework analysis was used to structure feedback related to acceptability, ease of use/learnability, accessibility, inclusivity, perceived usefulness, and technical or environmental issues. No personal data were analysed. The toolkit aims to empower stroke survivors and employers to plan and manage a sustainable return-to-work post-stroke. It exists as two Xerte eLearning packages, with accessibility features such as screen reader compatibility and keyboard navigation. The toolkit contains theory- and evidence-based content for a) stroke survivors and b) employers, and includes downloadable PDF tools. Stroke survivor-focused content provides guidance on identifying and disclosing support needs to employers. Employer-focused content guides employers in increasing and maintaining understanding of stroke survivors' work abilities, and implementing and monitoring tailored reasonable adjustments. Pretesting indicated the toolkit is comprehensive, empowering, and fosters open communication, offering key information and practical tools. Minor refinements and technical improvements were suggested. This toolkit addresses a gap in return-to-work guidance in the United Kingdom. Refinement, testing, and evaluation in real-world settings are needed.

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