Year: 2024
Type: editorial
Abstract: field of digital healthcare, more research resources have been invested in this area (Palanica et al., 2020).The combination of artificial intelligence and DTx can further enhance the effectiveness and efficiency of DTx. Multiple studies have shown that by utilizing artificial intelligence algorithms to analyze and mine extensive patient data, more personalized treatment plans can be formulated, leading to improved treatment outcomes (Lin et al., 2020) (Wang et al., 2020). However, the application of artificial intelligence in DTx also faces several challenges. Firstly, the accuracy and reliability of artificial intelligence algorithms need further validation and confirmation. Secondly, the application of artificial intelligence requires substantial data support, and acquiring and processing this data pose significant challenges. The development of DTx not only relies on technological support but also necessitates close integration with clinical research (Patel and Butte, 2020). While past digital healthcare primarily focused on health management, the future is centered on therapeutic functionalities. This requires conducting comprehensive clinical research for each new DTx product to validate its safety and efficacy. In clinical research, relevant norms and standards must be established to ensure the reliability and reproducibility of studies. Clinical experience also needs to be better summarized and used as a reference to help healthcare providers and patients understand and apply DTx effectively. Additionally, the application of artificial intelligence must consider privacy protection and ethical issues (Refolo et al., 2022). Therefore, in the future development of DTx, there is a need to further strengthen technological research and policy development to standardize the research and application of DTx. Simultaneously, there is a need to enhance societal awareness and increase public trust and acceptance of DTx. We believe that DTx integrated with artificial intelligence and computing technology will become the industry standard of the future. DTx will transition from the era of DTx to the era of intelligent DTx (iDTx), and the future will witness extensive research on the intersection of digital therapy and intelligent technology. With breakthroughs in hardware technology, iDTx will benefit patients even more.The time that digital therapeutics have truly entered human life is only a few short years. As a new phenomenon, policy makers, policy implementers, physicians, patients, and communities are all learning to accept it. Participants, starting from their respective roles, are actively exploring how to use digital therapeutics correctly. Lutz et al., 2022 delved into the intricacies surrounding the implementation of appropriate controls for digital therapeutics (DTx) within the context of clinical trials. The discourse primarily centered on critical factors pertaining to the design and regulatory facets of digital therapeutics, underscoring the imperative for meticulous evidence substantiation through rigorous clinical trials.Additionally, the paper brought into focus the inherent potential of real-world data aggregation as a pivotal means to evaluate the efficacy and user engagement of DTx. The study accentuated the paramount significance of randomized controlled trials (RCTs) in furnishing the requisite evidentiary foundation for DTx, particularly those poised for regulatory endorsement. It was posited that the rigidity of digital control conditions could be contingent upon variables such as the risk profile and innovative nature of the intervention. Furthermore, the article posited that, given the generally subdued risk profile associated with DTx, there exists a conceivable propensity towards the adoption of less stringent controls, or even the incorporation of waitlist controls, as a strategic measure to enhance accessibility to personalized care.Noteworthy attention was also directed towards the potential hazards entailed in DTx, encompassing technical exigencies and the conceivable inadequacy in treatment selection. Consequently, the authors advocated for a thoroughgoing integration of these considerations in forthcoming DTx trials. Moreover, the paper judiciously acknowledged the prevailing US-centric orientation of the majority of the trials scrutinized, thereby, conscientiously apprising that the regulatory deliberations proffered may not comprehensively encompass potential divergences in regulatory protocols beyond the purview of the United States. The authors astutely underscored the unique capacity of DTx to directly amass real-world data through their software applications, thereby, lending substantial support to the burgeoning traction of real-world and pragmatic study methodologies in the realm of evidence generation. Additionally, the study underscores the pivotal contribution of healthcare workers in driving innovation, emphasizing the need for their active involvement in the development of digital health solutions.Markatou et al. discussed various aspects related to social determinants of health. It covered a range of topics, including the impact of drug addiction stigma on methadone maintenance therapy, reforming physician payments for enhanced equity and value in healthcare, and strategies for screening social determinants of health in populations with complex needs. It highlighted the challenges associated with collecting, integrating, and effectively using clinical data for this purpose. The authors proposed a collaborative approach, bringing together expertise from medical, statistical, and computer and data science domains. They emphasized the importance of using provenance-aware, self-documenting workflow tools to facilitate data integration and create reproducible workflows. By addressing the unique data needs of underserved populations, this approach aimed to improve well-being and drive policy improvements for individuals with OUD. The paper concludes by advocating for policy frameworks to address disparities and discrimination in healthcare. Overall, it offers a comprehensive overview of factors influencing health outcomes, from social determinants to policy considerations. Understanding the adoption of computing and AI technologies among DTx users will also be critical to guide product developers and policy makers.Upon comprehensive examination of prevailing advanced models, it is evident that machine learning technology has attained a heightened level of refinement, thereby accruing significant technical acumen within the medical domain. Nevertheless, digital healthcare constitutes a complex and multidisciplinary domain necessitating profound scrutiny when implementing models, with the overarching objective of attaining optimal alignment with the patient's therapeutic journey. This affords robust tools for physician The study involved participants completing thought records using a conversational agent, and the results indicated that this approach was viable, with all participants successfully completing the task. The research also examined the impact of feedback richness on motivation and engagement. The findings showed that feedback richness did not significantly influence motivation, but participants who reported a greater need for self-reflection reported higher engagement in the task. Additionally, the study provided insights into the content and frequency of the thought records, highlighting that participants often focused on interpersonal and social situations. The document concluded by suggesting potential avenues for future research, including combining content-based feedback with motivational interviewing strategies. Overall, the study suggested that using a conversational agent for thought recording could be a valuable tool in cognitive therapy, especially for individuals with subclinical depression symptoms.The pivotal advancement from digital health to DTx hinges on the comprehensive validation of digital therapeutic modalities, thereby heightening our expectations of digital health to a level equivalent to By synthesizing a diverse range of studies, it explored the effectiveness of various digital tools, including mobile applications and online self-help programs, in assisting individuals dealing with persistent pain conditions. The review encompassed a wide spectrum of pain disorders, such as chronic headaches, fibromyalgia, and arthritis. The collective findings suggested that digital health technologies held significant promise in alleviating chronic pain, ultimately leading to an enhanced quality of life and empowering patients in self-managing their condition. However, the study highlighted the importance of personalized treatment approaches and the necessity for robust assessments of their effectiveness. In essence, this review underscored the potential of digital health technologies in chronic pain management, while emphasizing the ongoing need for research and refinement in this field. applications. These advances point towards a future where DTx is poised to play an increasingly pivotal role in healthcare, benefiting a diverse array of patient groups and paving the way for an era of intelligent, personalized medical solutions.
Source: Frontiers in Medicine
Authors: Pengwei Hu, Lun Hu, Fei Wang, Jing Mei
Language: English
Subfield: Applied Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $3,295
OpenAlex ID: W4390610873