International Journal of Environmental Research and Public Health

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22 pages, 2902 KiB

Open AccessArticle

Assessing Public Willingness to Wear Face Masks during the COVID-19 Pandemic: Fresh Insights from the Theory of Planned Behavior

by Muhammad Irfan, Nadeem Akhtar, Munir Ahmad, Farrukh Shahzad, Rajvikram Madurai Elavarasan, Haitao Wu and Chuxiao Yang

Int. J. Environ. Res. Public Health 2021, 18(9), 4577; https://doi.org/10.3390/ijerph18094577 - 26 Apr 2021

Cited by 82 | Viewed by 10474

Abstract

Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009′s H1N1 swine flu and 2003′s severe acute respiratory syndrome (SARS) outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in [...] Read more.

Face masks are considered an effective intervention in controlling the spread of airborne viruses, as evidenced by the 2009′s H1N1 swine flu and 2003′s severe acute respiratory syndrome (SARS) outbreaks. However, research aiming to examine public willingness to wear (WTW) face masks in Pakistan are scarce. The current research aims to overcome this research void and contributes by expanding the theoretical mechanism of theory of planned behavior (TPB) to include three novel dimensions (risk perceptions of the pandemic, perceived benefits of face masks, and unavailability of face masks) to comprehensively analyze the factors that motivate people to, or inhibit people from, wearing face masks. The study is based on an inclusive questionnaire survey of a sample of 738 respondents in the provincial capitals of Pakistan, namely, Lahore, Peshawar, Karachi, Gilgit, and Quetta. Structural equation modeling (SEM) is used to analyze the proposed hypotheses. The results show that attitude, social norms, risk perceptions of the pandemic, and perceived benefits of face masks are the major influencing factors that positively affect public WTW face masks, whereas the cost of face masks and unavailability of face masks tend to have opposite effects. The results emphasize the need to enhance risk perceptions by publicizing the deadly effects of COVID-19 on the environment and society, ensure the availability of face masks at an affordable price, and make integrated and coherent efforts to highlight the benefits that face masks offer. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 751 KiB

Open AccessArticle

Understanding the Health Behavior Decision-Making Process with Situational Theory of Problem Solving in Online Health Communities: The Effects of Health Beliefs, Message Credibility, and Communication Behaviors on Health Behavioral Intention

by Xiaoting Xu, Honglei Li and Shan Shan

Int. J. Environ. Res. Public Health 2021, 18(9), 4488; https://doi.org/10.3390/ijerph18094488 - 23 Apr 2021

Cited by 18 | Viewed by 5238

Abstract

Online health communities (OHCs) offer users the opportunity to share and seek health information through these platforms, which in turn influence users’ health decisions. Understanding what factors influence people’s health decision-making process is essential for not only the design of the OHC, but [...] Read more.

Online health communities (OHCs) offer users the opportunity to share and seek health information through these platforms, which in turn influence users’ health decisions. Understanding what factors influence people’s health decision-making process is essential for not only the design of the OHC, but also for commercial health business who are promoting their products to patients. Previous studies explored the health decision-making process from many factors, but lacked a comprehensive model with a theoretical model. The aim of this paper is to propose a research model from the situational theory of problem solving in relation to forecasting health behaviors in OHCs. An online questionnaire was developed to collect data from 321 members of online health communities (HPV Tieba and HPV vaccina Tieba) who have not received an HPV vaccination. The partial least squares structural equation modeling (PLS-SEM) method was employed for the data analysis. Findings showed that information selection and acquisition is able to forecast HPV vaccination intentions, perceived seriousness and perceived susceptibility can directly impact HPV vaccination intention and have an indirect impact by information selection and acquisition, and perceived message credibility indirectly affected HPV vaccination intention via information selection. The current paper supports health motivations analysis in OHCs, with potential to assist users’ health-related decision-making. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 998 KiB

Open AccessArticle

Hospital Climate and Peer Report Intention on Adverse Medical Events: Role of Attribution and Rewards

by Xiaoxiang Li, Shuhan Zhang, Rong Chen and Dongxiao Gu

Int. J. Environ. Res. Public Health 2021, 18(5), 2725; https://doi.org/10.3390/ijerph18052725 - 8 Mar 2021

Cited by 1 | Viewed by 2212

Abstract

Adverse medical events (AMEs) often occur in the healthcare workplace, and studies have shown that a positive atmosphere can reduce their incidence by increasing peer report intention. However, few studies have investigated the effect and action mechanism therein. We aimed to extend upon [...] Read more.

Adverse medical events (AMEs) often occur in the healthcare workplace, and studies have shown that a positive atmosphere can reduce their incidence by increasing peer report intention. However, few studies have investigated the effect and action mechanism therein. We aimed to extend upon these studies by probing into the relationship between hospital climate and peer report intention, along with the mediating effect of attribution tendency and moderating effects of rewards. For this purpose, a cross-sectional survey was administered in a hospital among health professionals. We collected 503 valid questionnaires from health professionals in China and verified the hypothesis after sorting the questionnaires. The results of empirical analysis show that a positive hospital climate significantly induces individual internal attribution tendency, which in turn exerts a positive effect on peer report intention. Contract reward also helps to increase peer report intention, especially for health professionals with an internal attribution tendency. The findings contribute to the literature regarding AME management in hospitals by providing empirical evidence of the necessity for hospital climate and contract reward, and by providing insights to improve their integrated application. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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20 pages, 23152 KiB

Open AccessArticle

Navigational Needs and Preferences of Hospital Patients and Visitors: What Prospects for Smart Technologies?

by Jan Ženka, Jan Macháček, Pavel Michna and Pavel Kořízek

Int. J. Environ. Res. Public Health 2021, 18(3), 974; https://doi.org/10.3390/ijerph18030974 - 22 Jan 2021

Cited by 9 | Viewed by 2939

Abstract

In this paper, we map navigational needs and preferences of patients and visitors to evaluate the appropriateness of a smartphone navigation application in the hospital in contrast to other, more traditional navigational cues. We test the effects of sociodemographic variables (age, gender, education) [...] Read more.

In this paper, we map navigational needs and preferences of patients and visitors to evaluate the appropriateness of a smartphone navigation application in the hospital in contrast to other, more traditional navigational cues. We test the effects of sociodemographic variables (age, gender, education) on wayfinding strategies and preferences of respondents (using chi2 tests). Empirical research is based on the survey among 928 patients/visitors of the Vítkovice Hospital in Ostrava, Czechia. We found a relatively weak association between gender and wayfinding—no major differences between men and women in navigational preferences were found. Age was the most important predictor of wayfinding. Respondents in the over-60-year age group were characteristic of a lower interest in changes of the navigational system and low willingness to use mobile applications for navigation—people between 41 years and 60 years were the biggest supporters of changes. Correspondingly, demand for improvement of navigation (including a mobile application) was positively correlated with educational level. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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19 pages, 2643 KiB

Open AccessArticle

Tracking Knowledge Evolution Based on the Terminology Dynamics in 4P-Medicine

by Aida Khakimova, Xuejie Yang, Oleg Zolotarev, Maria Berberova and Michael Charnine

Int. J. Environ. Res. Public Health 2020, 17(20), 7444; https://doi.org/10.3390/ijerph17207444 - 13 Oct 2020

Cited by 7 | Viewed by 2308

Abstract

The accelerating evolution of scientific terms connected with 4P-medicine terminology and a need to track this process has led to the development of new methods of analysis and visualization of unstructured information. We built a collection of terms especially extracted from the PubMed [...] Read more.

The accelerating evolution of scientific terms connected with 4P-medicine terminology and a need to track this process has led to the development of new methods of analysis and visualization of unstructured information. We built a collection of terms especially extracted from the PubMed database. Statistical analysis showed the temporal dynamics of the formation of derivatives and significant collocations of medical terms. We proposed special linguistic constructs such as megatokens for combining cross-lingual terms into a common semantic field. To build a cyberspace of terms, we used modern visualization technologies. The proposed approaches can help solve the problem of structuring multilingual heterogeneous information. The purpose of the article is to identify trends in the development of terminology in 4P-medicine. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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19 pages, 2740 KiB

Open AccessArticle

Knowledge Graph Analysis of Human Health Research Related to Climate Change

by Yating Zhao, Jingjing Guo, Chao Bao, Changyong Liang and Hemant K Jain

Int. J. Environ. Res. Public Health 2020, 17(20), 7395; https://doi.org/10.3390/ijerph17207395 - 11 Oct 2020

Cited by 10 | Viewed by 3621

Abstract

In order to explore the development status, knowledge base, research hotspots, and future research directions related to the impacts of climate change on human health, a systematic bibliometric analysis of 6719 published articles from 2003 to 2018 in the Web of Science was [...] Read more.

In order to explore the development status, knowledge base, research hotspots, and future research directions related to the impacts of climate change on human health, a systematic bibliometric analysis of 6719 published articles from 2003 to 2018 in the Web of Science was performed. Using data analytics tools such as HistCite and CiteSpace, the time distribution, spatial distribution, citations, and research hotspots were analyzed and visualized. The analysis revealed the development status of the research on the impacts of climate change on human health and analyzed the research hotspots and future development trends in this field, providing important knowledge support for researchers in this field. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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9 pages, 734 KiB

Open AccessArticle

Assessing Productivity Development of Public Hospitals: A Case Study of Shanghai, China

by Juan Du, Shuhong Cui and Hong Gao

Int. J. Environ. Res. Public Health 2020, 17(18), 6763; https://doi.org/10.3390/ijerph17186763 - 16 Sep 2020

Cited by 8 | Viewed by 2320

Abstract

As the main provider of medical services for the general public, the productivity changes of public hospitals directly reflect the development of the healthcare system and the implementation effect of medical reform policies. Using the dataset of 126 public hospitals in China from [...] Read more.

As the main provider of medical services for the general public, the productivity changes of public hospitals directly reflect the development of the healthcare system and the implementation effect of medical reform policies. Using the dataset of 126 public hospitals in China from 2013 to 2018, this paper improves the existing literature in both index selection and model formulation, and examines public hospitals’ total factor productivity (TFP) growth. Empirical results not only demonstrate the trend of productivity development but also point out the directions in how to improve the current running status. Our study demonstrates that there were no obvious productivity fluctuations in public hospitals during the recent observing years, indicating that the performance of China’s public health system was generally acceptable in coping with fast-growing medical demand. However, the effect of public hospital reform has not been remarkably shown; thus, no significant productivity improvement was observed in most hospitals. Tertiary hospitals witnessed a slight declining trend in TFP, while secondary hospitals showed signs of rising TFP. To effectively enhance the overall performance of public hospitals in China, practical suggestions are proposed from the government and hospital levels to further promote the graded medical treatment system. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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23 pages, 1145 KiB

Open AccessArticle

Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective

by Yuanyuan Cao, Junjun Li, Xinghong Qin and Baoliang Hu

Int. J. Environ. Res. Public Health 2020, 17(18), 6658; https://doi.org/10.3390/ijerph17186658 - 12 Sep 2020

Cited by 42 | Viewed by 5863

Abstract

Aging has increased the burden of social medical care. Mobile health (mHealth) services provide an effective way to alleviate this pressure. However, the actual usage of mHealth services for elderly users is still very low. The extant studies mainly focused on elderly users’ [...] Read more.

Aging has increased the burden of social medical care. Mobile health (mHealth) services provide an effective way to alleviate this pressure. However, the actual usage of mHealth services for elderly users is still very low. The extant studies mainly focused on elderly users’ mHealth adoption behavior, but resistance behavior has not been sufficiently explored by previous research. A present study tried to remedy this research gap by examining the effect of overload factors on the mHealth application resistance behavior based on the stimulus-organism-response (SOR) framework. The results indicated that information overload and system feature overload of an mHealth application increased the fatigue and technostress of the elderly user, which further increased their resistance behavior. Meanwhile, we integrated the intergeneration support with the SOR model to identify the buffer factor of the elderly user’s resistance behavior. The results showed that intergenerational support not only directly decrease the elderly user’s mHealth application resistance behavior, but also moderates (weaken) the effects of fatigue and technostress on resistance behavior. The present study also provided several valuable theoretical and practical implications. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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23 pages, 15428 KiB

Open AccessArticle

Spatial and Temporal Impacts of Socioeconomic and Environmental Factors on Healthcare Resources: A County-Level Bayesian Local Spatiotemporal Regression Modeling Study of Hospital Beds in Southwest China

by Chao Song, Yaode Wang, Xiu Yang, Yili Yang, Zhangying Tang, Xiuli Wang and Jay Pan

Int. J. Environ. Res. Public Health 2020, 17(16), 5890; https://doi.org/10.3390/ijerph17165890 - 13 Aug 2020

Cited by 24 | Viewed by 4126

Abstract

Comprehensive investigation on understanding geographical inequalities of healthcare resources and their influencing factors in China remains scarce. This study aimed to explore both spatial and temporal heterogeneous impacts of various socioeconomic and environmental factors on healthcare resource inequalities at a fine-scale administrative county [...] Read more.

Comprehensive investigation on understanding geographical inequalities of healthcare resources and their influencing factors in China remains scarce. This study aimed to explore both spatial and temporal heterogeneous impacts of various socioeconomic and environmental factors on healthcare resource inequalities at a fine-scale administrative county level. We collected data on county-level hospital beds per ten thousand people to represent healthcare resources, as well as data on 32 candidate socioeconomic and environmental covariates in southwest China from 2002 to 2011. We innovatively employed a cutting-edge local spatiotemporal regression, namely, a Bayesian spatiotemporally varying coefficients (STVC) model, to simultaneously detect spatial and temporal autocorrelated nonstationarity in healthcare-covariate relationships via estimating posterior space-coefficients (SC) within each county, as well as time-coefficients (TC) over ten years. Our findings reported that in addition to socioeconomic factors, environmental factors also had significant impacts on healthcare resources inequalities at both global and local space–time scales. Globally, the personal economy was identified as the most significant explanatory factor. However, the temporal impacts of personal economy demonstrated a gradual decline, while the impacts of the regional economy and government investment showed a constant growth from 2002 to 2011. Spatially, geographical clustered regions for both hospital bed distributions and various hospital bed-covariates relationships were detected. Finally, the first spatiotemporal series of complete county-level hospital bed inequality maps in southwest China was produced. This work is expected to provide evidence-based implications for future policy making procedures to improve healthcare equalities from a spatiotemporal perspective. The employed Bayesian STVC model provides frontier insights into investigating spatiotemporal heterogeneous variables relationships embedded in broader areas such as public health, environment, and earth sciences. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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16 pages, 9507 KiB

Open AccessArticle

Addition of an Emotionally Stable Node in the SOSa-SPSa Model for Group Emotional Contagion of Panic in Public Health Emergency: Implications for Epidemic Emergency Responses

by Xiaoyang Ni, Haojie Zhou and Weiming Chen

Int. J. Environ. Res. Public Health 2020, 17(14), 5044; https://doi.org/10.3390/ijerph17145044 - 14 Jul 2020

Cited by 15 | Viewed by 2731

Abstract

Sentiment contagion is similar to an infectious disease that spreads in a crowd. In this study, we explore the law of emotional infection under sudden public events by SIR model. The paper adds an emotionally stable node and establishes a group emotional infection [...] Read more.

Sentiment contagion is similar to an infectious disease that spreads in a crowd. In this study, we explore the law of emotional infection under sudden public events by SIR model. The paper adds an emotionally stable node and establishes a group emotional infection model of U-SOSPa-SPSOa model. Simulation results show that our model is reasonable and can better explain the entire contagion process by considering four groups (unsusceptible-susceptible-optimistic-pessimistic) of people. Our theoretical results show: When the pessimists were below the critical value of 0.34, the number of negative emotional groups first increased and then decreased. As the proportion increases, the emotional peak of pessimists increases. The cure probability θ_o has the least influence on the P(t), and at the same time, under the action of θ_p, the P(t) reaches the stable state first. The increase of the risk coefficient can promote the pessimist infection. When the degree of risk is low, the rate of emotional infection is increased. When the degree of risk is high, the rate of infection is slowed. Therefore, system customizers and related managers can improve the efficiency of stable groups, adjust the proportion of initial negative emotions, control the infection of the spontaneous infection process, and directly deal with negative emotions. They can carry out treatment and other means to stabilize group emotions and maintain social stability. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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10 pages, 1039 KiB

Open AccessArticle

Hospitalized Patients Accessing Information on Prescribed Medications from the Bedside Terminal: A Cross-Sectional Study

by Jungwon Cho, Seungyeon Kim, Sangyoon Shin, Hyejin Yoo, Gi Hyue Park, Eunha Jeon, Eunsook Lee, Ho-Young Lee and Euni Lee

Int. J. Environ. Res. Public Health 2020, 17(13), 4850; https://doi.org/10.3390/ijerph17134850 - 6 Jul 2020

Cited by 3 | Viewed by 3051

Abstract

Studies have documented the impact of various types of health care information technology (HIT) on patient outcomes. However, literature on the HIT products is largely for outpatients and little is known about those for hospitalized patients. In 2014, a Korean hospital developed an [...] Read more.

Studies have documented the impact of various types of health care information technology (HIT) on patient outcomes. However, literature on the HIT products is largely for outpatients and little is known about those for hospitalized patients. In 2014, a Korean hospital developed an inpatient portal known as the Smart Bedside Station (SBS). A retrospective cross-sectional study was conducted to evaluate the associated factors for accessing the medication view menu (Today’s Medication) on the SBS using data from October 2018 through September 2019. A root cause analysis with expert review was conducted to identify additional barriers for accessing the medication view menu. Approximately 92.58% of the study population accessed the SBS at least once during their hospital stay. However, 99.20% of accessed patients used the SBS for entertainment purposes (e.g., television) and 40.16% viewed the medication information. Younger age, higher education, and certain jobs were significant associated factors for accessing the medication information. In conclusion, this study revealed strong associations between accessing the medication view menu on the SBS and a number of associated factors. Based on the results, further research is warranted to suggest new items to access the medication view menu by hospitalized patients. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 1020 KiB

Open AccessArticle

Factors Influencing College Students’ Mental Health Promotion: The Mediating Effect of Online Mental Health Information Seeking

by Wenen Chen, Qian Zheng, Changyong Liang, Yuguang Xie and Dongxiao Gu

Int. J. Environ. Res. Public Health 2020, 17(13), 4783; https://doi.org/10.3390/ijerph17134783 - 3 Jul 2020

Cited by 19 | Viewed by 11485

Abstract

For college students, mental health is an important factor in ensuring their ability to study and have a normal life. This research focuses on factors affecting the mental health of college students in the information network society. We constructed a theoretical model that [...] Read more.

For college students, mental health is an important factor in ensuring their ability to study and have a normal life. This research focuses on factors affecting the mental health of college students in the information network society. We constructed a theoretical model that influences their online mental health information seeking behavior from internal and external perspectives, and by extension, affects their mental health. Through the data obtained by field research and questionnaire survey on the online mental health information seeking behavior of some college students in Internet health information platforms, a structural equation model is used to test the hypotheses. Results show that the quality of external Internet platforms and the quality of internal electronic health literacy have a significantly positive impact on the online health information searching behavior of college students; electronic health literacy and online mental health information seeking behavior have significantly direct positive effects on college students’ mental health. Further, online health information searching behavior has a significant mediating effect between Internet platform quality, electronic health literacy, and college students’ mental health. The research conclusions have theoretical value and practical significance to study the factors influencing college students’ mental health in the context of information network society. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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20 pages, 741 KiB

Open AccessArticle

Examining User’s Initial Trust Building in Mobile Online Health Community Adopting

by Yuanyuan Cao, Jiantong Zhang, Liang Ma, Xinghong Qin and Junjun Li

Int. J. Environ. Res. Public Health 2020, 17(11), 3945; https://doi.org/10.3390/ijerph17113945 - 2 Jun 2020

Cited by 25 | Viewed by 4279

Abstract

Due to the high perceived risk, it is critical to foster users’ initial trust in the promotion of mobile online health community (MOHC) adoption. The present study focused on the role of two different trust elements and examined the initial trust building process [...] Read more.

Due to the high perceived risk, it is critical to foster users’ initial trust in the promotion of mobile online health community (MOHC) adoption. The present study focused on the role of two different trust elements and examined the initial trust building process based on elaboration likelihood model and trust transfer theory. The results indicated that initial trust in MOHC context was composed of two interrelated components: health service provider (doctor) and underlying technology (MOHC platform). Especially, the initial trust in MOHC platform exerted greater effects on adopting intention. Both performance-based cue (doctors’ information quality and interaction quality) and transfer-based cue (trust in the offline doctors’ health service) positively shaped the initial trust in doctor. Meanwhile, only the performance-based cue (MOHC platform’s information quality and service quality) has significant positive association with initial trust in MOHC platform. However, interpersonal recommend is insignificantly related to the initial trust in doctor. Trust in the mobile internet service is insignificantly related to the initial trust in MOHC platform. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 699 KiB

Open AccessArticle

“Smart Process” of Medical Innovation: The Synergism Based on Network and Physical Space

by Ailian Zhang and Mengmeng Pan

Int. J. Environ. Res. Public Health 2020, 17(11), 3798; https://doi.org/10.3390/ijerph17113798 - 27 May 2020

Cited by 3 | Viewed by 2619

Abstract

Medical innovation has a profound impact on public health, and it is always of social concern to encourage innovation and enhance the value in health care delivery. Based on a sample of China’s listed firms in the medical industry from 2007 to 2018, [...] Read more.

Medical innovation has a profound impact on public health, and it is always of social concern to encourage innovation and enhance the value in health care delivery. Based on a sample of China’s listed firms in the medical industry from 2007 to 2018, this paper highlights the independent and mixed roles of informatization and high-speed rail in public medical innovation. The results show that informatization at network space and high-speed rail at physical space effectively promote the innovation of medical enterprises. In addition, “online” information technology and “offline” high-speed rail technology have a synergistic effect on medical innovation, especially in areas with a low level of innovation. The conclusion supports the positive significance of technology in the application of public health and proposes that the construction of smart society is very important to public health. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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18 pages, 1791 KiB

Open AccessArticle

The Voice of Drug Consumers: Online Textual Review Analysis Using Structural Topic Model

by Lifeng He, Dongmei Han, Xiaohang Zhou and Zheng Qu

Int. J. Environ. Res. Public Health 2020, 17(10), 3648; https://doi.org/10.3390/ijerph17103648 - 22 May 2020

Cited by 24 | Viewed by 4919

Abstract

Many web-based pharmaceutical e-commerce platforms allow consumers to post open-ended textual reviews based on their purchase experiences. Understanding the true voice of consumers by analyzing such a large amount of user-generated content is of great significance to pharmaceutical manufacturers and e-commerce websites. The [...] Read more.

Many web-based pharmaceutical e-commerce platforms allow consumers to post open-ended textual reviews based on their purchase experiences. Understanding the true voice of consumers by analyzing such a large amount of user-generated content is of great significance to pharmaceutical manufacturers and e-commerce websites. The aim of this paper is to automatically extract hidden topics from web-based drug reviews using the structural topic model (STM) to examine consumers’ concerns when they buy drugs online. The STM is a probabilistic extension of Latent Dirichlet Allocation (LDA), which allows the consolidation of document-level covariates. This innovation allows us to capture consumer dissatisfaction along with their dynamics over time. We extract 12 topics, and five of them are negative topics representing consumer dissatisfaction, whose appearances in the negative reviews are substantially higher than those in the positive reviews. We also come to the conclusion that the prevalence of these five negative topics has not decreased over time. Furthermore, our results reveal that the prevalence of price-related topics has decreased significantly in positive reviews, which indicates that low-price strategies are becoming less attractive to customers. To the best of our knowledge, our work is the first study using STM to analyze the unstructured textual data of drug reviews, which enhances the understanding of the aspects of drug consumer concerns and contributes to the research of pharmaceutical e-commerce literature. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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16 pages, 4219 KiB

Open AccessArticle

Coordination of a Dual-Channel Pharmaceutical Supply Chain Based on the Susceptible-Infected-Susceptible Epidemic Model

by Yanhong Hou, Fan Wang, Zhitong Chen and Victor Shi

Int. J. Environ. Res. Public Health 2020, 17(9), 3292; https://doi.org/10.3390/ijerph17093292 - 8 May 2020

Cited by 6 | Viewed by 2936

Abstract

With the continuous development of Internet, online pharmaceutical channels in many countries have seen rapid expansion. As a result, pharmaceutical supply chain participants can adopt dual channels, namely, both online channels and offline channels. As online channels compete with traditional offline channels, it [...] Read more.

With the continuous development of Internet, online pharmaceutical channels in many countries have seen rapid expansion. As a result, pharmaceutical supply chain participants can adopt dual channels, namely, both online channels and offline channels. As online channels compete with traditional offline channels, it is of great relevance to study the potential conflicts and coordination between them, which is the focus of this paper. Specifically, this article develops a susceptible-infected-susceptible epidemic model of the dual channels for a pharmaceutical supply chain. Our main findings are that in a competitive situation, there is a positive stable equilibrium. Furthermore, increasing the rate of influence of offline transmission, online transmission, and cross transmission will improve sales. Moreover, improving the transmission influence rate will turn more potential customers into purchasers, increase channel sales, and achieve dual channel coordination. We then conduct numerical analysis to illustrate and complement the findings from the model. Finally, we provide managerial insights for implementing successful dual-channel pharmaceutical supply chains. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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19 pages, 7655 KiB

Open AccessArticle

A New Design Scheme for Intelligent Upper Limb Rehabilitation Training Robot

by Yating Zhao, Changyong Liang, Zuozuo Gu, Yunjun Zheng and Qilin Wu

Int. J. Environ. Res. Public Health 2020, 17(8), 2948; https://doi.org/10.3390/ijerph17082948 - 24 Apr 2020

Cited by 33 | Viewed by 5760

Abstract

In view of the urgent need for intelligent rehabilitation equipment for some disabled people, an intelligent, upper limb rehabilitation training robot is designed by applying the theories of artificial intelligence, information, control, human-machine engineering, and more. A new robot structure is proposed that [...] Read more.

In view of the urgent need for intelligent rehabilitation equipment for some disabled people, an intelligent, upper limb rehabilitation training robot is designed by applying the theories of artificial intelligence, information, control, human-machine engineering, and more. A new robot structure is proposed that combines the use of a flexible rope with an exoskeleton. By introducing environmentally intelligent ergonomics, combined with virtual reality, multi-channel information fusion interaction technology and big-data analysis, a collaborative, efficient, and intelligent remote rehabilitation system based on a human’s natural response and other related big-data information is constructed. For the multi-degree of the freedom robot system, optimal adaptive robust control design is introduced based on Udwdia-Kalaba theory and fuzzy set theory. The new equipment will help doctors and medical institutions to optimize both rehabilitation programs and their management, so that patients are more comfortable, safer, and more active in their rehabilitation training in order to obtain better rehabilitation results. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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28 pages, 3480 KiB

Open AccessArticle

Uncertain Multiplicative Language Decision Method Based on Group Compromise Framework for Evaluation of Mobile Medical APPs in China

by Junchang Li, Jiantong Zhang and Ye Ding

Int. J. Environ. Res. Public Health 2020, 17(8), 2858; https://doi.org/10.3390/ijerph17082858 - 21 Apr 2020

Cited by 11 | Viewed by 2488

Abstract

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel [...] Read more.

The mobile medical application (M-medical APP) can optimize medical service process and reduce health management costs for users, which has become an important complementary form of traditional medical services. To assist users including patients choose the ideal M-medical APP, we proposed a novel multiple attribute group decision making algorithm based on group compromise framework, which need not determine the weight of decision-maker. The algorithm utilized an uncertain multiplicative linguistic variable to measure the individual original preference to express the real evaluation information as much as possible. The attribute weight was calculated by maximizing the differences among alternatives. It determined the individual alternatives ranking according to the net flow of each alternative. By solved the 0–1 optimal model with the objective of minimizing the differences between individual ranking, the ultimate group compromise ranking was obtained. Then we took 10 well-known M-medical APPs in Chinese as an example, we summarized service categories provided for users and constructed the assessment system consisting of 8 indexes considering the service quality users are concerned with. Finally, the effectiveness and superiority of the proposed method and the consistency of ranking results were verified, through comparing the group ranking results of 3 similar algorithms. The experiments show that group compromise ranking is sensitive to attribute weight. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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16 pages, 2145 KiB

Open AccessArticle

Improving the Named Entity Recognition of Chinese Electronic Medical Records by Combining Domain Dictionary and Rules

by Xianglong Chen, Chunping Ouyang, Yongbin Liu and Yi Bu

Int. J. Environ. Res. Public Health 2020, 17(8), 2687; https://doi.org/10.3390/ijerph17082687 - 14 Apr 2020

Cited by 22 | Viewed by 3925

Abstract

Electronic medical records are an integral part of medical texts. Entity recognition of electronic medical records has triggered many studies that propose many entity extraction methods. In this paper, an entity extraction model is proposed to extract entities from Chinese Electronic Medical Records [...] Read more.

Electronic medical records are an integral part of medical texts. Entity recognition of electronic medical records has triggered many studies that propose many entity extraction methods. In this paper, an entity extraction model is proposed to extract entities from Chinese Electronic Medical Records (CEMR). In the input layer of the model, we use word embedding and dictionary features embedding as input vectors, where word embedding consists of a character representation and a word representation. Then, the input vectors are fed to the bidirectional long short-term memory to capture contextual features. Finally, a conditional random field is employed to capture dependencies between neighboring tags. We performed experiments on body classification task, and the F1 values reached 90.65%. We also performed experiments on anatomic region recognition task, and the F1 values reached 93.89%. On both tasks, our model had higher performance than state-of-the-art models, such as Bi-LSTM-CRF, Bi-LSTM-Attention, and Vote. Through experiments, our model has a good effect when dealing with small frequency entities and unknown entities; with a small training dataset, our method showed 2–4% improvement on F1 value compared to the basic Bi-LSTM-CRF models. Additionally, on anatomic region recognition task, besides using our proposed entity extraction model, 12 rules we designed and domain dictionary were adopted. Then, in this task, the weighted F1 value of the three specific entities extraction reached 84.36%. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 2929 KiB

Open AccessArticle

Study on Differences between Patients with Physiological and Psychological Diseases in Online Health Communities: Topic Analysis and Sentiment Analysis

by Jingfang Liu, Jun Kong and Xin Zhang

Int. J. Environ. Res. Public Health 2020, 17(5), 1508; https://doi.org/10.3390/ijerph17051508 - 26 Feb 2020

Cited by 14 | Viewed by 4073

Abstract

The development of online social platforms has promoted the improvement of online health communities (OHCs). However, OHCs often ignore differences in user discussions caused by the characteristics of diseases. The purpose of this research was to study differences in the topics and emotions [...] Read more.

The development of online social platforms has promoted the improvement of online health communities (OHCs). However, OHCs often ignore differences in user discussions caused by the characteristics of diseases. The purpose of this research was to study differences in the topics and emotions of patients with physiological and psychological diseases by mining the text that they posted in OHCs as well as to discuss how to satisfy these differences. The data came from Baidu Post Bar, the world’s biggest Chinese forum. We collected 50,230 posts from heart disease, hypertension, depression and obsessive-compulsive bars. Then, we used topic modeling and sentiment analysis techniques on these posts. The results indicate that there are significant differences in the preferences of discussion and emotion between patients with physiological and psychological diseases. First, people with physiological diseases are more likely to discuss treatment of their illness, while people with psychological diseases are more likely to discuss feelings and living conditions. Second, psychological disease patients’ posts included more extreme and negative emotions than those of physiological disease patients. These results are helpful for society to provide accurate medical assistance based on disease type to different patients, perfecting the national medical service system. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 344 KiB

Open AccessArticle

Technical Blossom in Medical Care: The Influence of Big Data Platform on Medical Innovation

by Bai Liu, Shuyan Guo and Bin Ding

Int. J. Environ. Res. Public Health 2020, 17(2), 516; https://doi.org/10.3390/ijerph17020516 - 14 Jan 2020

Cited by 7 | Viewed by 3198

Abstract

Medical innovation has consistently been an essential subject and a source of support for public health research. Furthermore, improving the level of medical research and development is of great concern in this field. This paper highlights the role of big data in public [...] Read more.

Medical innovation has consistently been an essential subject and a source of support for public health research. Furthermore, improving the level of medical research and development is of great concern in this field. This paper highlights the role of big data in public medical innovation. Based on a sample of China’s listed firms in the medical industry from 2013 to 2018, this paper explores the exogenous shock effect of China’s big data medical policy. Results show that the construction of the medical big data platform effectively promotes innovation investment and the innovation patent of medical firms. In addition, the heterogeneity of this promoting effect is reflected in firm size through the overcoming of different innovation bottlenecks. The research conclusions support the positive significance of the macro-led implementation of the medical big data platform, and suggest that the positive economic externalities generated by this policy are critical to public health. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

22 pages, 823 KiB

Open AccessArticle

Perceived Community Support, Users’ Interactions, and Value Co-Creation in Online Health Community: The Moderating Effect of Social Exclusion

by Wenlong Liu, Xiucheng Fan, Rongrong Ji and Yi Jiang

Int. J. Environ. Res. Public Health 2020, 17(1), 204; https://doi.org/10.3390/ijerph17010204 - 27 Dec 2019

Cited by 39 | Viewed by 5866

Abstract

Online health communities (OHCs) face the same problem as other social media platforms in terms of decreasing activity and user attrition. Drawing upon organizational support theory, this study explores how perceived community support affects user interactions and value co-creation which in turn influence [...] Read more.

Online health communities (OHCs) face the same problem as other social media platforms in terms of decreasing activity and user attrition. Drawing upon organizational support theory, this study explores how perceived community support affects user interactions and value co-creation which in turn influence their continuous participation. OHCs act as both health knowledge-sharing platforms and important social media for patients, and thus, interpersonal interactions in OHCs are categorized into health-related and general topic interactions. Considering the identity of patients, this study also examines the moderating effect of user-perceived social exclusion on the relationship between community support and user interaction. A total of 292 valid samples from a diabetic patient community in China were used to examine the proposed hypotheses through structural equation modeling. The results show that: (1) Community support has a positive effect on health topic and general topic interactions; (2) both types of interactions have significant positive effects on users’ perceived functional and social values, while general topic interaction is also related positively to users’ perceived affective value; (3) perceived functional value can result directly in continuous participation, while perceived social value contributes indirectly to continuous participation intention through perceived affective value; and (4) users perceived higher social exclusion are more influenced by community support to participate in health topic interactions than those who perceived lower social exclusion, while no significant difference in general topic interactions between two groups. The results of this study can provide implications for both researchers and practitioners. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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17 pages, 1428 KiB

Open AccessArticle

How to Manage Diversity and Enhance Team Performance: Evidence from Online Doctor Teams in China

by Xuan Liu, Meimei Chen, Jia Li and Ling Ma

Int. J. Environ. Res. Public Health 2020, 17(1), 48; https://doi.org/10.3390/ijerph17010048 - 19 Dec 2019

Cited by 19 | Viewed by 4816

Abstract

(1) Background: Traditional one-to-one online consultations with doctors often fail to provide timely and accurate treatment plans; consequently, creating cross-hospital and cross-regional teams has become a new pattern for doctors aiming to offer Internet medical services. Because the online doctor team is a [...] Read more.

(1) Background: Traditional one-to-one online consultations with doctors often fail to provide timely and accurate treatment plans; consequently, creating cross-hospital and cross-regional teams has become a new pattern for doctors aiming to offer Internet medical services. Because the online doctor team is a new virtual organizational model, it remains to be explained and investigated. (2) Methods: Combining the information processing view and the social categorization view, this study takes the perspective of team diversity and empirically investigates the effect of team diversity on team performance. We consider four kinds of team diversity, including status capital diversity, decision capital diversity, online reputation diversity, and professional knowledge diversity, and we investigate how team composition from the diversity perspective affects online doctor team performance and how leader reputation moderates the effect of team diversity on team performance. We use secondary data from a leading online medical consultation platform in China (Good Doctor), and our research data include 1568 teams with a total of 5481 doctors. (3) Results: The results show that status capital diversity and decision capital diversity negatively affect team performance; diversity in terms of online reputation and professional knowledge positively affect team performance; and leader reputation moderates the impact of status capital diversity and online reputation on team performance. (4) Conclusions: Our study offers management suggestions on how to form a high-performance doctor team and provides advice for the future development of online doctor teams. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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Review

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19 pages, 3231 KiB

Open AccessReview

The Prediction of Infectious Diseases: A Bibliometric Analysis

by Wenting Yang, Jiantong Zhang and Ruolin Ma

Int. J. Environ. Res. Public Health 2020, 17(17), 6218; https://doi.org/10.3390/ijerph17176218 - 27 Aug 2020

Cited by 48 | Viewed by 6016

Abstract

Objective: The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars [...] Read more.

Objective: The outbreak of infectious diseases has a negative influence on public health and the economy. The prediction of infectious diseases can effectively control large-scale outbreaks and reduce transmission of epidemics in rapid response to serious public health events. Therefore, experts and scholars are increasingly concerned with the prediction of infectious diseases. However, a knowledge mapping analysis of literature regarding the prediction of infectious diseases using rigorous bibliometric tools, which are supposed to offer further knowledge structure and distribution, has been conducted infrequently. Therefore, we implement a bibliometric analysis about the prediction of infectious diseases to objectively analyze the current status and research hotspots, in order to provide a reference for related researchers. Methods: We viewed “infectious disease*” and “prediction” or “forecasting” as search theme in the core collection of Web of Science from inception to 1 May 2020. We used two effective bibliometric tools, i.e., CiteSpace (Drexel University, Philadelphia, PA, USA) and VOSviewer (Leiden University, Leiden, The Netherlands) to objectively analyze the data of the prediction of infectious disease domain based on related publications, which can be downloaded from the core collection of Web of Science. Then, the leading publications of the prediction of infectious diseases were identified to detect the historical progress based on collaboration analysis, co-citation analysis, and co-occurrence analysis. Results: 1880 documents that met the inclusion criteria were extracted from Web of Science in this study. The number of documents exhibited a growing trend, which can be expressed an increasing number of experts and scholars paying attention to the field year by year. These publications were published in 427 different journals with 11 different document types, and the most frequently studied types were articles 1618 (83%). In addition, as the most productive country, the United States has provided a lot of scientific research achievements in the field of infectious diseases. Conclusion: Our study provides a systematic and objective view of the field, which can be useful for readers to evaluate the characteristics of publications involving the prediction of infectious diseases and for policymakers to take timely scientific responses. Full article

(This article belongs to the Special Issue Innovating Public Health in Smart Society: Technical, Behavioral and Management Perspectives)

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