数字健康干预文化适应的当前实践和专家观点:定性研究。

IF 6.2 2区 医学 Q1 HEALTH CARE SCIENCES & SERVICES
Vasileios Nittas, Sarah J Chavez, Paola Daniore
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引用次数: 0

摘要

背景:有些人比其他人更不可能从数字卫生干预措施(DHIs)中受益。文化和其他因素共同造成了这些差异。不考虑人群文化规范或关注点的DHIs可能效果较差。创造具有文化敏感性的DHIs的一种方法是通过文化适应。然而,目前几乎没有关于何时以及如何调整DHIs的循证指导。目的:我们旨在收集专家的经验,以了解(1)当前的实践,(2)挑战,以及(3)围绕文化适应DHIs的建议。方法:我们在2023年5月至8月期间通过Zoom (Zoom Video Communications, Inc .)与之前从事过DHIs文化适应的学术专家进行了半结构化访谈(n=15)。专家是通过出版物和滚雪球抽样确定的。我们使用了主题分析方法,从初步演绎密码本开始,然后进行三阶段分析。所有转录本用MAXQDA (VERBI Software GmbH)软件编码。审查代码,并将类似或相关代码分类为更广泛的主题,将一个或多个代码合并为单个主题。结果:我们的分析产生了30个准则,这些准则分为(1)定义文化,(2)证明适应的合理性,(3)选择适应要素,(4)实施适应,(5)理解挑战,(6)建议。根据他们的经验,专家们建议:(1)适应团队是多专业的,具有数字能力,并具有文化敏感性;(2) DHI用户和(3)所有其他相关利益相关者持续参与;(4)适应包括评价和知识交流。他们进一步强调,与文化相适应的发展目标必须是可理解的、相关的、吸引人的、易于遵守的,确保卫生技术和内容反映目标人群的生活经历、社会人口特征和数字素养。当被问及文化DHI适应的哪些因素时,最常见的回答是语言、生活经验和技术。回应揭示了与dhi相关的五个常见挑战,包括(1)技术,(2)不确定性,(3)用户参与,(4)沟通,以及(5)评估和可持续性。结论:DHIs的文化适应被描述为一个迭代的、通常是非结构化的、资源密集的过程,需要仔细的论证和对文化和具体文化群体的深刻理解。我们的访谈证实了技术特定框架的缺失,以指导DHIs的文化适应。根据我们的发现,这样一个框架应该指导选择文化的正确定义和评估适应需要的标准。它还应该提供工具来推动利益相关者的参与,优先考虑适应因素,并解决共同的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Current Practice and Expert Perspectives on Cultural Adaptations of Digital Health Interventions: Qualitative Study.

Background: Some people are less likely to benefit from digital health interventions (DHIs) than others. Culture, along with other factors, contributes to these differences. DHIs that do not address a population's cultural norms or concerns are likely to be less effective. One way to create culturally sensitive DHIs is through cultural adaptations. Yet, there is currently little evidence-based guidance on when and how to adapt DHIs.

Objective: We aimed to capture the experiences of experts to understand the (1) current practices, (2) challenges, and (3) recommendations around culturally adapting DHIs.

Methods: We conducted semistructured interviews (n=15) via Zoom (Zoom Video Communications, Inc) between May and August 2023, with academic experts who have previously undertaken cultural adaptations of DHIs. Experts were identified through publications and snowball sampling. We used a thematic analytical approach, beginning with a preliminary deductive codebook and then following a three-stage analysis. All transcripts were coded with the MAXQDA (VERBI Software GmbH) software. Codes were reviewed, and similar or related codes were categorized into broader themes, consolidating one or multiple codes into a single topic.

Results: Our analysis produced 30 codes, which were categorized into (1) defining culture, (2) justifying the adaptation, (3) choosing the adaptation elements, (4) implementing the adaptation, (5) understanding the challenges, and (6) recommendations. Based on their experiences, experts recommended that (1) the adaptation team is multiprofessional, digitally competent, and culturally sensitive; (2) DHI users and (3) all other relevant stakeholders are continuously involved; and (4) the adaptations incorporate evaluations and knowledge exchange. They further emphasized that culturally adapted DHIs must be understandable, relatable, appealing, and easy to adhere to, ensuring that health technology and content reflect the target population's lived experiences, sociodemographic characteristics, and digital literacy. When asked which elements of cultural DHI adaptations, the most common responses were language, lived experience, and technology. Responses revealed five common DHI-relevant challenges, including (1) technology, (2) uncertainty, (3) user involvement, (4) communication, and (5) evaluation and sustainability.

Conclusions: The cultural adaptation of DHIs was described as an iterative, often unstructured, and resource-intensive process that requires careful justification and a solid understanding of the culture and the specific cultural group for which it is implemented. Our interviews confirmed the absence of technology-specific frameworks to guide the cultural adaptations of DHIs. Based on our findings, such a framework should guide the choice of the correct definition of culture and the criteria for assessing the need to adapt. It should also offer tools to drive stakeholder engagement, prioritize adaptation elements, and address common challenges.

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来源期刊
JMIR mHealth and uHealth
JMIR mHealth and uHealth Medicine-Health Informatics
CiteScore
12.60
自引率
4.00%
发文量
159
审稿时长
10 weeks
期刊介绍: JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636. The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics. JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.
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