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The study examines the amplifying role of users in the e-healthcare sector and holistically show its current state and potential. The paper aims at contributing to the scientific literature with a comprehensive review of the current state of the art on the application of user innovation (UI) in the e-healthcare sector, as a solid step for discussing the potential, trends, managerial gaps and future research avenues in this field. Despite the crucial importance of the topic and increasing attention toward it in the last few years, there is a lack of comprehensive scrutiny on different angles of involving users in health technology innovations so far.

This study combines two methods of bibliometric analysis and extensive content analysis of 169 journal articles on Scopus and Web of Science to unfold five research questions regarding the mechanisms of involving users, innovations characteristics and the role of users throughout the innovation process.

A clear result of the applied methodology is the profiling of users involved in e-health innovations in seven categories. The results of this study shed light on the current practice of not involving users in all the stages of the innovation process of m-health, telemedicine, self-managing technologies, which is contrary to the best practices of the UI application.

Collection of relevant studies due to lack of comprehensibility of the keywords.

The offered propositions can act as a roadmap to potential research opportunities as well as to organize such innovations from a managerial perspective in particular healthcare organization managers and the middle managers operating at R&D sectors and policymakers.

This study is the first of its kind that digs out the application of UI strategies such as user-centered design in the context of e-healthcare and provides a bibliometric and extensive content analysis of the studies conducted in this theme over the years.

Innovation in a decentralized blockchain infrastructure can be used by medicine as a prerequisite for the exchange of patient data. Developments in the medical device industry that support the technology of the internet of things and wireless sensor networks also facilitate the examination of patient medical records that no longer require visits to the practice of doctors or hospitals which in some cases takes in a considerable time. Not to mention the consideration of traffic congestion and busy routine in the work. Patients can check their healthcare concerns using only sensors such as e-Health Sensor Shield Platform which then sends recording results through the transmission line to the data lakes. However, this patient’s medical record data is very confidential and may only be accessed by certain parties only. This required the design of the concept of security in the transmission of data so that the data does not leak to parties who are not eligible. This paper attempts to provide an overview of the concept of using encryption with an asymmetric key for securing data from sensors to data lakes before forwarding to a decentralized, interconnected blockchain infrastructure.

The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.

This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.

Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.

To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.

The pandemic has reinforced the need for revamping the healthcare service delivery systems around the world to meet the increased challenges of modern-day illnesses. The use of medical cyber–physical system (MCPS) in the healthcare is one of the means of transforming the landscape of the traditional healthcare service delivery system. The purpose of this study is to critically examine the impact of MCPS on the quality of healthcare service delivery.

This paper uses an evidence-based approach, the authors have conducted a systematic literature review to study the impact of MCPS on healthcare service delivery. Fifty-four articles were thematically examined to study the impact of MCPS on eight characteristics of the healthcare service delivery proposed by the world health organisation.

The study proposes support that MCPS will positively impact (1) comprehensiveness, (2) accessibility, (3) coverage, (4) continuity, (5) quality, (6) person-centredness, (7) coordination, (8) accountability and (9) efficiency dimension of the healthcare service delivery. The study further draws nine propositions to support the impact of MCPS on the healthcare service delivery.

This study can be used by stakeholders as a guide point while using MCPS in healthcare service delivery systems. Besides, healthcare managers can use this study to understand the performance of their healthcare system. This study can further be used for designing effective strategies for deploying MCPS to be effective and efficient in each of the dimensions of healthcare service delivery.

The previous studies have focussed on technology aspects of MCPS and none of them critically analysed the impact on healthcare service delivery. This is the first literature review carried out to understand the impact of MCPS on the nine dimensions of healthcare service delivery proposed by WHO. This study provides improved thematic awareness of the resulting body of knowledge, allowing the field of MCPS and healthcare service delivery to progress in a more informed and multidisciplinary manner.

This research is motivated by the increasing need for international interactions during the gradual recovery of the tourism industry. By recognizing the paucity of research on cultural closeness and accommodation categories, this research aims to illuminate the influencing mechanisms of psychological closeness and travelers’ willingness to book an accommodation-sharing property while booking an accommodation.

The authors employ a mixed-methods approach, including an experiment and semistructured interviews.

Results show that hosts’ higher cultural identity congruence leads to travelers’ higher willingness to book an accommodation-sharing property. Psychological closeness mediates the positive effect of cultural identity congruence on travelers’ willingness to book. The authors further explore the moderating role of room types (entire room vs. private room) and find that the mediation effect is stronger for booking an entire room.

The current research underlines the importance of cultural identity congruence and accommodation type on travelers’ willingness to book an accommodation-sharing property and psychological closeness.

AAL (Ambient Assisted Living) is lacking a RM (Reference Model) to serve as an abstraction of the domain. Therefore, to help implement new architectures established on the prior experiences of the designer’s expertise and former competences, in this paper, we propose a novel approach of an AAL RM. Our objective is to handle the resolution of conflicts that appear between the developers, and give an overview of the basis for implementing concrete software architectures for different families of AAL applications. Our proposed RM is a standardized clarification for developers to apply in the process of the design and implementation. We illuminate the AAL domain fundamental dimensions and we established a formal RM with an infrastructure that could survive the domain’s progression. To achieve integrated system-of-systems composed of systems, subsystems and components, our RM describes a standard and regulated structure to be established. High-level elements, essential properties and characteristics that must appear in the application’s design are described and illustrated in this work.

This paper aims to design a vision-based non-contact real-time accurate heart rate (HR) measurement framework for home nursing assistant.

The study applied Second-Order Blind Signal Identification (SOBI) algorithm to extract remote HR signal and analyzed it with Fast Fourier Transform (FFT). Multiple regions of interest are chosen and analyzed to obtain a more accurate result.

An accurate non-contact hear rate (HR) measurement framework is proposed and proved to be efficient.

The contributions of this HR measurement framework are as follows: accurate measurement of HR, real-time performance, robust under various scenes such as conversation, lightweight computation which is suitable and necessary for home nursing assistance. This framework is designed to be flexibly used in various real-life scenes such as domestic health assistance and affectively intelligent agents and is proved to be robust under such scenes.

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

There has been a move towards the implementation of digital/e-health interventions for some time. Digital/e-health interventions have demonstrable efficacy in increasing individual empowerment, providing timely access to psychological interventions for those experiencing mental ill-health and improving outcomes for those using them. This study aims to determine the efficacy of digital/e-health interventions for individuals detained in prison who experience mental ill-health.

A systematic search of five academic databases – CINAHL, ASSIA, PsycINFO, Embase and Medline – was completed in December 2020 and updated in February 2022. The review was guided by the Whittemore and Knafl (2005) framework for integrative reviews. A total of 6,255 studies were returned and screened by title and abstract. A full-text screening of nine (n = 9) studies was conducted.

No study met the inclusion criteria for the clinical efficacy of digital/e-health interventions in a prison setting. Subsequently, a review of the literature that made it to the full-text review stage was conducted, and gaps in the literature were identified to inform policy, practice and future research.

To the best of the authors’ knowledge, this is the first integrative review conducted on the efficacy of digital/e-health interventions for mental ill-health in prison settings.

This paper aims to examine the relationship between surface acting (SA), deep acting (DA) and organizational commitment (OC).

Guided by affective events theory, the study adapted emotional labour scale and three components model to profile 373 teachers from 30 schools around Peninsular Malaysia. A list-based simple random sampling technique was used to select respondents. Structural equation modeling (SEM) was used to test hypotheses, and the proposed model was assessed through renowned fit indices.

OC was hypothesized as a second-order construct. SEM result indicates that both SA and DA have significant negative relationship with OC. Fit indices of the hypothesized model showed χ²/df ratio (560.069/265) = 2.113, RMSEA (0.055), and CFI (0.936). This result provides empirical support for the data collected.

The study provides new insight on the ongoing debate about SA and DA. Therefore, it advances body of research in this regard. The implication for HR managers is that strategic polices can be institutionalized to buffer the consequences of SA and DA. This is due to the fact that SA and DA may not be abolished for service employees like teachers. The practical implication for teachers is the understanding that emotional regulation process is inevitable because teaching is profoundly an emotional activity job. Besides being a cross-sectional study, the sampled population may have limited the study’s outcomes.

Given existing inconsistent results on the consequences of SA and DA, this study shows that not only SA can lead to negative after-effects, DA can also cause the same. Future study can explore spiritual intelligence to examine how best SA and DA can be performed at reduced consequences on OC.