Bipolar disorder (BP) is a common psychiatric disorder characterized by extreme fluctuations in mood. Recent studies have indicated the involvement of cerebellum in the pathogenesis of BP. However, no study has focused on the precise role of cerebellum exclusively in patients with bipolar I disorder (BP-I). Forty-five patients with BP-I and 40 healthy controls were recruited. All subjects underwent clinical evaluation and Magnetic Resonance diffusion Tension Imaging scans. For structural images, we used a spatially unbiased infratentorial template toolbox to isolate the cerebellum and then preformed voxel-based morphometry (VBM) analyses to assess the difference in cerebellar gray matter volume (GMV) between the two groups. For the functional images, we chose the clusters that survived from VBM analysis as seeds and performed functional connectivity (FC) analysis. Between-group differences were assessed using the independent Students t test or the nonparametric Mann-Whitney U Test. For multiple comparisons, the results were further corrected with Gaussian random field (GRF) approach (voxel-level P < 0.001, cluster-level P < 0.05). Compared with healthy controls, BP-I patients showed significantly decreased GMV in left lobule V and left lobule VI (P < 0.05, GRF corrected). The FC of cerebellum with bilateral superior temporal gyrus, bilateral insula, bilateral rolandic operculum, right putamen, and left precentral gyrus was disrupted in BP-I patients (P < 0.05, GRF corrected). BP-I patients showed decreased cerebellar GMV and disrupted cerebellar-cortex resting-state FC. This suggests that cerebellar abnormalities may play an important role in the pathogenesis of BP-I.

Background: The swift shift toward internet hospitals has relied on the willingness of medical practitioners to embrace new systems and workflows. Low engagement or acceptance by medical practitioners leads to difficulties in patient access. However, few investigations have focused on barriers and facilitators of adoption of internet hospitals from the perspective of medical practitioners. Objective: This study aims to identify both enabling and inhibiting predictors associated with resistance and behavioral intentions of medical practitioners to use internet hospitals by combining the conservation of resources theory with the Unified Theory of Acceptance and Use of Technology and technostress framework. Methods: A mixed methods research design was conducted to qualitatively identify the factors that enable and inhibit resistance and behavioral intention to use internet hospitals, followed by a quantitative survey-based study that empirically tested the effects of the identified factors. The qualitative phase involved conducting in-depth interviews with 16 experts in China from June to August 2022. Thematic analysis was performed using the qualitative data analysis software NVivo version 10 (QSR International). On the basis of the findings and conceptual framework gained from the qualitative interviews, a cross-sectional, anonymous, web-based survey of 593 medical practitioners in 28 provincial administrative regions of China was conducted. The data collected were analyzed using the partial least squares method, with the assistance of SPSS 27.0 (IBM Corp) and Mplus 7.0 (Muthen and Muthen), to measure and validate the proposed model. Results: On the basis of qualitative results, this study identified 4 facilitators and inhibitors, namely performance expectancy, social influence, work overload, and role ambiguity. Of the 593 medical practitioners surveyed in the quantitative research, most were female (n=364, 61.4%), had a middle title (n=211, 35.6%) or primary title (n=212, 35.8%), and had an average use experience of 6 months every year. By conducting structural equation modeling, we found that performance expectancy (β=−.55; P<.001) and work overload (β=.16; P=.005) had the most significant impact on resistance to change. Resistance to change fully mediated the influence of performance expectancy and partially mediated the influences of social influence (variance accounted for [VAF]=43.3%; P=.002), work overload (VAF=37.2%; P=.03), and role ambiguity (VAF=12.2%; P<.001) on behavioral intentions to use internet hospitals. In addition, this study found that the sex, age, professional title, and use experience of medical practitioners significantly moderated the aforementioned influencing mechanisms. Conclusions: This study investigated the factors that facilitate or hinder medical practitioners’ resistance to change and their behavioral intentions to use internet hospitals. The findings suggest that policy makers avoid the resistance and further promote the adoption of internet hospitals by ensuring performance expectancy and social influence and eliminating work overload and role ambiguity.

Smart health is considered to be a new phase in the application of information and communication technologies (ICT) in healthcare that can improve its efficiency and sustainability. However, based on our literature review on the concept of smart health, there is a lack of a comprehensive perspective on the concept of smart health and a framework for how to link the drivers and outcomes of smart health. This paper aims to interweave the drivers and outcomes in a multi-dimensional framework under the input–process–output (IPO) logic of the “system view” so as to promote a deeper understanding of the model of smart health. In addition to the collection of studies, we used the modified Delphi method (MDM) to invite 10 experts from different fields, and the views of the panelists were analyzed and integrated through a three-round iterative process to reach a consensus on the elements included in the conceptual framework. The study revealed that smart health contains five drivers (community, technology, policy, service, and management) and eight outcomes (efficient, smart, sustainable, planned, trustworthy, safe, equitable, health-beneficial, and economic). They all represent a unique aspect of smart health. This paper expands the research horizon of smart health, shifting from a single technology to multiple perspectives, such as community and management, to guide the development of policies and plans in order to promote smart health.

Objectives: To solve the labour shortage, we clarify the definition and dimensions of sustainable employability, and make it possible to develop sustainable employability scales in the future and lay the foundation for subsequent quantitative research. Finally, people’s sustainable employability can be improved. Highly sustainable employability employees can continue to work in the labour market and their working lives can be prolonged. Labour market supply will increase and labour shortage will be partly solved. Methods: We discuss the concept of sustainable employability based on some previous studies. Our conclusion is that the existing definitions and measurement dimensions are problematic. The swAge-model, a tool that helps us understand how to make working life more sustainable and healthier for all ages, can be the basis of sustainable employability. Results: We develop a discussion paper concerning the definition and measurement dimensions of sustainable employability using the swAge-model with an added factor of intrinsic work value and the dynamic chain. Conclusions: Our definition of sustainable employability takes environmental factors into consideration and makes it clear that it is not a solely personal characteristic, but the result of an interaction between individuals and the environment, thus distinguishing employability from work ability. We use the swAge-model as a basis to make the composition of our definition more logical and informed. Our measurement dimensions are clearly described to facilitate the future development of a scale, and our concept may ultimately help to extend the working lives of older and retired workers and thus solve the future labour shortage problem.

Medical institutions face a variety of challenges as they seek to enhance their reputation and increase the influence of their social media accounts. Becoming a social media influencer in the health field in today’s complex online environment requires integrated social and technical systems. However, rather than holistically investigating the mechanism of account influence, studies have focused on a narrow subset of social and technical conditions that drive online influence. We attribute this to the mismatch between complex causality problems and traditional symmetric regression methods. In this study, we adopted an asymmetric configurational perspective that allowed us to test a causally complex model of the conditions that create strong and not-strong account influence. We used fuzzy-set qualitative comparative analysis (fsQCA) to detect the effects of varying configurations of three social system characteristics (i.e., an oncology-related attribute, a public attribute, and comment interaction) and two technical system characteristics (i.e., telepresence and video collection) on the TikTok accounts of 63 elderly Chinese doctors (60 to 92 years old). Our results revealed two pathways associated with distinct sociotechnical configurations to strong account influence and three pathways associated with distinct sociotechnical configurations to not-strong account influence. Furthermore, the results confirmed that a single antecedent condition cannot, on its own, produce an outcome, i.e., account influence. Multiple inter-related conditions are required to produce an influential account. These results offer a more holistic picture of how health science communication accounts operate and reconcile the scattered results in the literature. We also demonstrate how configurational theory and methods can be used to analyze the complexities of social media platforms.