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The COVID-19 pandemic has boosted information and communication technologies (ICT) and digital technologies integration in everyday practices. Digital technology-based telemedicine (or telehealth) is one of the main areas that have grown significantly since the start of the pandemic (1–3). Nonetheless, it has widened the digital divide for multiple groups, such as those from remote locations, vulnerable socio-economic background, people with severe physical or mental disabilities, as well as regions with poor access to internet technologies (4, 5). In particular, the elderly groups (or older adults) are affected the most, where we see growing challenges in long-term care facilities (LTCFs) (6), elderly care centers, and private households. Despite the growing attention on the development of ICT infrastructure, availability of ICT devices, and technology interest (7), there are still barriers to the effective use of telemedicine, particularly for vulnerable groups.
In response to the arguments by Shen et al. (3), digital technology-based telemedicine is incorporated in different ways to optimize clinical workflow. The four suggested modes are considered as (1) “many to one” mode, (2) “one to many” mode, (3) “consultation” mode, and (4) “practical operation” mode. In all cases, effectiveness and higher efficiency in data sharing and exchange are evident, but we argue against the point that such platforms are all-inclusive. Hence, this commentary highlights the neglected digital divide in healthcare systems through telemedicine and telehealth platforms, growing much faster than before.
According to Van Dijk and Hacker (8), there are four types of digital divide barriers, including mental (e.g., interests, attractiveness), material (e.g., possession of hardware), skill (e.g., user-friendliness, education, and social support), and usage (e.g., usage opportunities) (9). While we appreciate telemedicine or telehealth as an excellent platform for data exchange and reducing direct interactions between healthcare services/providers/workers and patients, we note that it also creates barriers to multiple groups. Telehealth creates barriers to those with no or little access to digital devices, whether this is related to economic issues, socio-economic issues, or acceptance and use factors. It also becomes a significant burden to those with language barriers, learning difficulties, and digital illiteracy. In particular, such a barrier affects the elderly or older adults as they may be reluctant to use digital/online platforms for healthcare services. They remain a vulnerable group amid the COVID-19 era, who may become more disconnected from their healthcare services. Apart from mental and material digital barriers, skill barriers could be beyond the fundamental skills and more related to the user-friendliness of telehealth platforms. There is often a lack of social support for those in need, leading to further disconnections between the vulnerable groups and the online healthcare services. Such barriers could particularly affect two modes of “many to one mode” and “consultation mode,” where one-to-one online interactions are deemed essential. Lastly, barriers to usage opportunities could be augmented easily due to lack of utilization (including use and utility of the internet), availability, accessibility, and support. Thus, telehealth is not necessarily an all-inclusive digital platform.
Despite the benefits of “telemedicine in the context of a huge health crisis” (3), the digital divide barriers caused by telemedicine cannot and must not be neglected. Its effectiveness is mainly related to “data exchange” and “data sharing,” which is indeed efficient and impactful amid the COVID-19 pandemic. However, many people are still reluctant to use telemedicine platforms due to at least six key factors, including lack of trust in such digital platforms, lack of accessibility, digital illiteracy, user-unfriendly platforms, lack of support, and inequalities related to gender, age, social groups, etc. Bakhtiar et al. (10) argue that if we do not concern about the risks of elevating disparities and providing less and poor-quality services to those most underserved patients, “internet access and device ownership could become social determinants of health.” There is an urgent need to foster and support equitable access to telemedicine. It is appreciated that Shen et al. (3) did not refer to telemedicine platforms as all-inclusive platforms. Still, we argue that telemedicine services are not yet equal to traditional care systems. There are still significant barriers, including but not limited to the digital divide barriers, which need to be addressed. Other barriers include a lack of standardized telemedicine pathways and poor digital literacy (11). Hence, we urge ongoing and future research to not neglect the presence and growing impacts of digital divide barriers in online or internet services. We have to appreciate the fact that certain groups have tangible barriers, and they should be addressed more promptly to optimize current (and future) telemedicine platforms and online healthcare services.
More specifically, the mental digital divide barrier (DDB) is the most intangible barrier, relying on people's willingness and intention to use telemedicine. Regarding the Unified Theory of Acceptance in Technology (UTAT), it is suggested that the most significant influential factors of an individual's intention to use telemedicine are performance expectations, effort expectations, and facilitating conditions (12). Facilitating conditions reflect the material DDB, while performance expectancy mainly depends on doctors' opinions, and the effort expectancy is closely linked to computer anxiety (12, 13). This implies that improving people's awareness and fostering behaviors change through political incentives and propaganda activities to boost individuals' perceptions and intentions to use telemedicine might be a possible solution to intangible mental DDBs.
Secondly, for material DDB of telemedicine, most telemedicine platforms require smartphone use. However, some people cannot even afford or get access, like the poor, the elders, and children. This situation might be mitigated or partially solved by sharing economy like providing public laptops, desktops, and smart devices in public places (e.g., streets, community activity centers, pharmacies, etc.). After overcoming the second DDB of material accessibility, education level, digital literacy, and learning abilities form the third DDB: skill DDB. Since digital advances and technologies develop rapidly, people with limited and/or less ability to adapt to rapid digital innovations and upgrades will all suffer from skill DDB. Not only are patients from the socially marginalized and/or disadvantaged groups impacted by skill DDB the most, but doctors and/or medical practitioners need to learn and adapt to the use of telemedicine systems to provide more accurate and effective diagnoses since they will be using them the most. On the other hand, usage of DDB is highly connected to mental and accessibility DDBs, behavioral intentions, related popularization & promotion of telemedicine platforms, and the fifth DDB: utility DDB.
Beyond mental, material, skill, and usage DDBs, we argue that there is another type of DDB interconnecting with all the four DDBs, utility DDB. The underlying factors of utility DDB can be divided into users' and providers' factors while they are closely intertwined with each other DDBs. For instance, some hospitals don't provide enough financial and technological support to build their telemedicine systems, making it very hard to use or useless to some extent. Consequently, this will deepen mental issues concerning the usage of DDBs while making digital literacy less relevant while such technologies may not be readily used by consumers due to cost and utility barriers. To resolve this, it is suggested that collaborations between academics and practitioners are required to develop the feasibility and utility of telemedicine in resource-limited settings. At the same time, emerging technologies like Artificial Intelligence and wearable devices are expected to mitigate DDBs of telemedicine and resolve their limitations (14).
Generally, those neglected barriers can be mitigated through an integrated approach from macro, meso, and micro levels. At macro level, strategies include implementing national elder-orientated standards and regulations for telemedicine systems/platforms (e.g., elder's mode, simple mode, in-app training sessions, AI, and other supportive features). They promote a systematic transformation of medicine systems to minimize health system–created barriers [e.g., provide incentives for hospitals to build better telemedicine systems through top-down approaches, advocate for policies, and infrastructure that facilitate equitable telemedicine access (15). They also integrate scopes and functions of social welfare institutions for more inclusive service objects (i.e., not only the disabled groups but also other vulnerable population groups); and smart and dynamic management protocols with a particular classification of people with special needs. At meso levels, local government and communities can play very significant roles in mitigating the DDB of telemedicine. Not all the DDBs can be resolved completely, particularly for skill and utility DDBs, but these strategies can be applied. First, by setting special channels at the hospital to enhance inclusivity; and target developing digital vulnerable people-friendly cities/communities, e.g., age-friendly communities (16, 17). Second, by setting public desktops booth on the streets/parks or combining public libraries with Internet cafes]. This approach can create new jobs for assisting and supporting those digital vulnerable people to get the most benefits of telemedicine (e.g., home telemedicine consultants, social workers, or volunteers). Thirdly, an individual's skill and mental DDBs can be dealt with more effectively and precisely at micro-levels. Such mitigation strategies may involve awareness enhancement/training programs, and more user-friendly interfaces. Some examples include in-app training modes, AI assistant robots (18), chatbots (19), etc. (20). Lastly, we could set up programs and courses to train medical practitioners to use telemedicine by offering related courses at universities for seniors.
全文翻译（仅供参考）
COVID-19 大流行促进了信息和通信技术 (ICT) 和数字技术在日常实践中的整合。基于数字技术的（或远程医疗）是自大流行开始以来显着增长的主要领域之一 ( 1-3 )。尽管如此，它还是扩大了多个群体的数字鸿沟，例如来自偏远地区、脆弱的社会经济背景、有严重身体或精神残疾的人，以及互联网技术普及率低的地区 ( 4 , 5 )。特别是老年人群体（或老年人）受到的影响最大，我们看到长期护理机构（LTCF）面临越来越大的挑战（6)、老年护理中心和私人家庭。尽管人们越来越关注 ICT 基础设施的发展、ICT 设备的可用性和技术兴趣 ( 7 )，但远程医疗的有效使用仍然存在障碍，特别是对于弱势群体而言。
回应沉等人的论点。( 3 )、基于数字技术的远程医疗以不同方式融入临床工作流程。四个建议的模式被认为是（1）“多对一”模式，（2）“一对多”模式，（3）“咨询”模式，以及（4）“实际操作”模式。在所有情况下，数据共享和交换的有效性和更高效率都是显而易见的，但我们反对这样的平台是包罗万象的。因此，这篇评论通过远程医疗和远程医疗平台强调了医疗保健系统中被忽视的数字鸿沟，其增长速度比以前快得多。
根据 Van Dijk 和 Hacker ( 8 )，数字鸿沟障碍有四种类型，包括心理（如兴趣、吸引力）、物质（如拥有硬件）、技能（如用户友好、教育和社交支持）和使用（例如，使用机会）（9）。虽然我们赞赏远程医疗或远程医疗作为数据交换和减少医疗服务/提供者/工人和患者之间直接互动的绝佳平台，但我们注意到它也为多个群体制造了障碍。远程医疗给那些无法或很少使用数字设备的人制造了障碍，无论这与经济问题、社会经济问题还是接受和使用因素有关。对于那些有语言障碍、学习困难和数字文盲的人来说，这也成为一个沉重的负担。特别是，这种障碍会影响老年人或老年人，因为他们可能不愿意使用数字/在线平台进行医疗保健服务。在 COVID-19 时代，他们仍然是一个弱势群体，他们可能会与医疗保健服务更加脱节。除了精神和物质上的数字障碍，技能障碍可能超出了基本技能，更多地与远程医疗平台的用户友好性有关。对有需要的人往往缺乏社会支持，导致弱势群体与在线医疗服务之间进一步脱节。这些障碍可能特别影响“多对一模式”和“咨询模式”两种模式，其中一对一的在线互动被认为是必不可少的。最后，由于缺乏利用（包括互联网的使用和效用）、可用性、可访问性和支持，使用机会的障碍很容易增加。因此，远程医疗不一定是一个包罗万象的数字平台。对有需要的人往往缺乏社会支持，导致弱势群体与在线医疗服务之间进一步脱节。这些障碍可能特别影响“多对一模式”和“咨询模式”两种模式，其中一对一的在线互动被认为是必不可少的。最后，由于缺乏利用（包括互联网的使用和效用）、可用性、可访问性和支持，使用机会的障碍很容易增加。因此，远程医疗不一定是一个包罗万象的数字平台。对有需要的人往往缺乏社会支持，导致弱势群体与在线医疗服务之间进一步脱节。这些障碍可能特别影响“多对一模式”和“咨询模式”两种模式，其中一对一的在线互动被认为是必不可少的。最后，由于缺乏利用（包括互联网的使用和效用）、可用性、可访问性和支持，使用机会的障碍很容易增加。因此，远程医疗不一定是一个包罗万象的数字平台。由于缺乏利用（包括互联网的使用和效用）、可用性、可访问性和支持，使用机会的障碍很容易增加。因此，远程医疗不一定是一个包罗万象的数字平台。由于缺乏利用（包括互联网的使用和效用）、可用性、可访问性和支持，使用机会的障碍很容易增加。因此，远程医疗不一定是一个包罗万象的数字平台。
尽管“巨大健康危机背景下的远程医疗”（3）带来了诸多好处，但远程医疗造成的数字鸿沟障碍不能也不能被忽视。它的有效性主要与“数据交换”和“数据共享”有关，这在 COVID-19 大流行中确实是有效和有影响的。然而，由于至少六个关键因素，许多人仍然不愿意使用远程医疗平台，包括对此类数字平台缺乏信任、缺乏可访问性、数字文盲、用户不友好的平台、缺乏支持以及与性别相关的不平等，年龄、社会群体等。Bakhtiar 等人。( 10) 认为，如果我们不担心扩大差距和向那些服务最欠缺的患者提供更少和质量差的服务的风险，“互联网接入和设备所有权可能成为健康的社会决定因素。” 迫切需要促进和支持公平获得远程医疗。值得赞赏的是沉等人。( 3 )没有将远程医疗平台称为全包平台。尽管如此，我们认为远程医疗服务还不等同于传统的护理系统。仍然存在重大障碍，包括但不限于数字鸿沟障碍，需要加以解决。其他障碍包括缺乏标准化的远程医疗路径和较差的数字素养（11）。因此，我们敦促正在进行和未来的研究不要忽视在线或互联网服务中数字鸿沟障碍的存在和日益增长的影响。我们必须认识到，某些群体存在切实的障碍，应该更迅速地解决这些障碍，以优化当前（和未来）的远程医疗平台和在线医疗服务。
更具体地说，心理数字鸿沟障碍（DDB）是最无形的障碍，取决于人们使用远程医疗的意愿和意图。关于技术接受的统一理论 (UTAT)，建议个人使用远程医疗的意图的最重要影响因素是绩效期望、努力期望和便利条件 ( 12 )。促进条件反映物质DDB，而绩效期望主要取决于医生的意见，而努力期望与计算机焦虑密切相关（12、13））。这意味着通过政治激励和宣传活动来提高人们的意识和促进行为改变，以提高个人使用远程医疗的看法和意图，可能是解决无形心理 DDB 的一个可能解决方案。
其次，对于远程医疗的物质DDB，大部分远程医疗平台都需要使用智能手机。然而，有些人甚至买不起或无法使用，如穷人、老人和儿童。这种情况可能会通过共享经济得到缓解或部分解决，例如在公共场所（例如街道、社区活动中心、药店等）提供公共笔记本电脑、台式机和智能设备。在克服了物质可及性、教育水平、数字素养和学习能力的第二个 DDB 之后，形成了第三个 DDB：技能 DDB。由于数字化进步和技术发展迅速，适应快速数字化创新和升级的能力有限和/或能力较弱的人都将受到技能 DDB 的影响。不仅来自社会边缘化和/或弱势群体的患者受技能 DDB 影响最大，但是医生和/或医疗从业人员需要学习和适应远程医疗系统的使用，以提供更准确和有效的诊断，因为他们将最常使用远程医疗系统。另一方面，DDB 的使用与心理和可及性 DDB、行为意图、远程医疗平台的相关普及和推广以及第五个 DDB：效用 DDB 高度相关。
除了精神、物质、技能和使用 DDB，我们认为还有另一种类型的 DDB 与所有四个 DDB 互连，即效用 DDB。效用 DDB 的底层因素可以分为用户因素和提供者因素，它们与其他 DDB 密切相关。例如，一些医院没有提供足够的资金和技术支持来建立他们的远程医疗系统，使其在某种程度上很难使用或无用。因此，这将加深有关使用 DDB 的心理问题，同时降低数字素养的相关性，而由于成本和实用性障碍，消费者可能不会轻易使用此类技术。为了解决这个问题，建议需要学术界和从业人员之间的合作，以发展远程医疗在资源有限的环境中的可行性和实用性。与此同时，人工智能和可穿戴设备等新兴技术有望缓解远程医疗的 DDB 并解决其局限性。14 )。
一般来说，这些被忽视的障碍可以通过宏观、中观和微观层面的综合方法来缓解。在宏观层面，策略包括针对远程医疗系统/平台（例如，老年人模式、简单模式、应用内培训课程、人工智能和其他支持功能）实施面向老年人的国家标准和法规。它们促进医疗系统的系统转型，以尽量减少卫生系统造成的障碍[例如，通过自上而下的方法鼓励医院建立更好的远程医疗系统，倡导促进公平远程医疗的政策和基础设施（15）。它们还整合了社会福利机构的范围和功能，以提供更具包容性的服务对象（即不仅包括残疾人群体，还包括其他弱势群体）；智能和动态管理协议，对有特殊需要的人进行特定分类。在中观层面，地方政府和社区可以在缓解远程医疗的 DDB 方面发挥非常重要的作用。并非所有的 DDB 都可以完全解决，特别是对于技能和实用 DDB，但可以应用这些策略。一是在医院设置特殊渠道，增强包容性；并以发展数字弱势人群友好型城市/社区为目标，例如老年友好型社区 ( 16 , 17）。二是在街道/公园设置公共桌面展台或将公共图书馆与网吧结合]。这种方法可以创造新的就业机会，帮助和支持那些数字弱势群体从远程医疗中获得最大收益（例如，家庭远程医疗顾问、社会工作者或志愿者）。第三，可以在微观层面更有效、更精确地处理个人的技能和心理 DDB。这种缓解策略可能涉及意识增强/培训计划，以及更加用户友好的界面。一些示例包括应用内培训模式、AI 助手机器人 ( 18 )、聊天机器人 ( 19 ) 等 ( 20）。最后，我们可以通过在大学为老年人提供相关课程来建立计划和课程，以培训医生使用远程医疗。
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