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Given the popularity of online health communities (OHCs) and medical question-and-answer (Q&A) services, it is increasingly important to understand what constitutes useful answers and user-adopted standards in healthcare domain. However, few studies provide insights into how health information characteristics, provider characteristics and recipient characteristics jointly influence user information adoption decisions. To fill this research gap, this study examines the combined effects of physicians' certainty tone as information characteristics, seniority as provider characteristics and disease severity as recipient characteristics on patients' health information adoption.

Drawing on dual-process theory and information adoption model, an extended information adoption model is established in this study to examine the effect of attitude certainty on patients' health information adoption, and the moderating effects of online seniority and offline seniority, as well as patient motivation level—disease severity. Utilizing logit regression models, the authors empirically tested the hypotheses based on 4,224 Q&A records from a popular Chinese OHC.

The results show that (1) attitude certainty has a significant positive impact on patients' health information adoption, (2) the relationship between attitude certainty and information adoption is negatively moderated by physicians' online seniority, but is positively moderated by offline seniority; (3) there is a negative three-way interaction effect of attitude certainty, online seniority and disease severity on patients' health information adoption.

This study extends the information adoption model to examine the two-way interaction between argument quality and source reliability, as well as the three-way interaction with user motivation level, especially for health information adoption in the healthcare field. These findings also provide direct practical applications for knowledge contributors and OHCs.

The higher-level aim of this study is to investigate the impact of health information needs satisfaction on the fear of COVID-19 for the general population. The investigation is theoretically grounded on Wilsons’ model of information seeking in the context of inquesting the reasons for seeking health information as well as the information sources the general population deploy during the COVID-19 pandemic.

This cross-sectional survey examines the correlations between health information seeking behavior and the COVID-19 generated fear in the general population through the application of a specially designed structured questionnaire which was distributed online. The questionnaire comprised four main distinct research dimensions (i.e. information needs, information sources, obstacles when seeking information and COVID-19 generated fear) that present significant validity levels.

Individuals were motivated to seek COVID-related health information to cope with the pandemic generated uncertainty. Information needs satisfaction as well as digital health literacy levels is associated with the COVID-19 generated fear in the general population. Finally, a conceptual framework based on Wilsons’ macro-model for information seeking behavior was developed to illustrate information needs satisfaction during the pandemic period. These results indicate the need for incentives to enhance health information needs satisfaction appropriately.

The COVID-19 generated fear in the general population is studied through the information seeking behavior lenses. A well-studied theoretical model for information seeking behavior is adopted for health-related information seeking during pandemic. Finally, digital health information literacy levels are also associated with the fear of COVID-19 reported in the authors’ survey.

The goal of this study is to test the real-world use of an emotion recognition system.

The researchers chose an existing algorithm that displayed high accuracy and speed. Four emotions: happy, sadness, anger and surprise, are used from six of the universal emotions, associated by their own mood markers. The mood-matrix interface is then coded as a web application. Four guidance counselors and 10 students participated in the testing of the mood-matrix. Guidance counselors answered the technology acceptance model (TAM) to assess its usefulness, and the students answered the general comfort questionnaire (GCQ) to assess their comfort levels.

Results from TAM found that the mood-matrix has significant use for the guidance counselors and the GCQ finds that the students were comfortable during testing.

No study yet has tested an emotion recognition system applied to counseling or any mental health or psychological transactions.

Online health question-and-answer (Q&A) forums have developed a new business model whereby listeners (peer patients) can pay to read health information derived from consultations between askers (focal patients) and answerers (physicians). However, research exploring the mechanism behind peer patients' purchase decisions and the specific nature of the information driving these decisions has remained limited. This study aims to develop a theoretical model for understanding how peer patients make such decisions based on limited information, i.e. the first question displayed in each focal patient-physician interaction record, considering argument quality (interrogative form and information details) and source credibility (patient experience of focal patients), including the contingent role of urgency.

The model was tested by text mining 1,960 consultation records from a popular Chinese online health Q&A forum on the Yilu App. These records involved interactions between focal patients and physicians and were purchased by 447,718 peer patients seeking health-related information until this research.

Patient experience embedded in focal patients' questions plays a significant role in inducing peer patients to purchase previous consultation records featuring exchanges between focal patients and physicians; in particular, increasingly detailed information is associated with a reduced probability of making a purchase. When focal patients demonstrate a high level of urgency, the effect of information details is weakened, while the interrogative form is strengthened.

The originality of this study lies in its exploration of the monetization mechanism forming the trilateral relationship between askers (focal patients), answerers (physicians) and listeners (peer patients) in the business model “paying to view others' answers” in the online health Q&A forum and the moderating role of urgency in explaining the mechanism of how first questions influence peer patients' purchasing behavior.

This paper proposes a Web-based patient portal based on the electronic medical record. Such a portal can allow patients to manage their own health care, reduce health-care visits and significantly improve the quality of their health care.

A patient portal prototype and an accompanying online survey were distributed to assess the adoption readiness among a group of people in the United Arab Emirates (UAE).

The results from 470 survey participants demonstrated an enhanced awareness of this technology, and support the study hypotheses indicating that both intrinsic and extrinsic factors are important when considering the implementation of a patient portal in the UAE.

This study adds value to the few research studies undertaken in the Middle East discussing online health information technology and its adoption and usage among the population at large. The extended technology acceptance model, which contains two additional constructs, had not been previously validated in terms of a patient portal in the UAE, according to the author’s knowledge, adding more value. The UAE’s health-care system must use the benefits from the available IT infrastructure to provide a user-friendly online portal to encourage patients to manage their health care and health information.

The scope of this study is to explore and summarize the pool of dimensions, models and measurement techniques of service quality used in healthcare services and to propose a comprehensive conceptual model for practitioners and researchers.

This research employs a comprehensive review of available literature by using multiple keywords on different electronic repositories using the recommendations of the PRISMA approach for the selection of articles. A critical analysis of available studies helped in compiling a list of core service quality dimensions in healthcare services.

This paper presents a comprehensive account of different dimensions and their measurement items used by various researchers to assess service quality in healthcare systems. Most of the researchers have used SERVQUAL model either in its original or modified form while the others have proposed and used totally different dimensions to assess the service quality in healthcare. Many dimensions are just an existing dimension of SERVQUAL that has undergone a name change while others are completely new. The dimensions used by many researchers have items drawn from more than one dimension of SERVQUAL model. The availability of so many dimensions and models adds to the confusion that researchers and practicing managers experience when determining the appropriate model to be used in their work. To mitigate this confusion, there is a need to develop a comprehensive model; the current work is an attempt to meet this need. Through our analysis, we identify four major service quality dimensions: clinical quality, infrastructural quality, relationship and managerial quality and propose a model named CIRMQUAL.

After exploring all available models in the domain of healthcare, this research presents the best possible areas to enhance the quality of healthcare services. It also enhances the research insights for academicians and working professionals by developing and proposing a comprehensive model for measuring healthcare service quality. The proposed model covers almost all of the service quality dimensions used by other researchers and will make the choice of dimensions/model easy for the future researchers/practitioners interested in measuring and improving the quality of services offered by their healthcare units. Such a comprehensive model has not been developed by any researcher thus far.

The advent of online live streaming platforms (OLSPs) and online health communities (OHCs) has expedited the integration of traditional medical services with Internet new media technology. Since the practice of physicians conducting live streaming is a relatively new phenomenon, the potential cross-platform effects of such physicians’ live streaming have not received adequate attention.

This study collected data from 616 physicians specializing in cardiology, obstetrics and gynecology and neurology between April and November 2022 on Live.Baidu.com and WeDoctor.com. It constructed a panel data set comprising a total of 4,928 observations over an 8-month period and validated the model using empirical analysis with the fixed-effects method.

We find evidence of cross-platform influence in online healthcare. Physicians’ live streaming behavior (whether live or not and the heat of their streams) on OLSPs positively impacts both their consultation and reputation on OHCs. Additionally, physicians’ ability positively moderates the relationships between live streaming heat and their performance (in terms of consultation volume and reputation) on OHCs. However, ability does not moderate the relationship between physicians’ live streaming status (live or not) and their performance (in terms of consultation and reputation) on OHCs. Furthermore, the attractive appearance of the physicians also significantly moderates the impact in a positive way.

This is one of the pioneering studies on physicians’ live streaming. The study offers vital guidance for physicians and patients utilizing dual platforms and holds significant reference value for platform operators (such as OLSPs and OHCs) aiming to optimize platform operations and for the government in policy formulation and industry regulation.

This qualitative study aimed to explore the barriers and facilitators faced by workers during the COVID-19 pandemic restrictions in Ecuador. It focused on three work modalities: on-site, telework and mixed or hybrid. It also inquired into practical implications for management based on the workers’ experiences.

Between October and December 2021, 41 semistructured interviews were conducted to delve into the experiences of Ecuadorian workers. Thematic content analysis was employed for data charting and analysis.

Barriers and facilitators varied according to each working modality, although some were shared, contingent upon the specific contextual factors and job characteristics. The findings suggest that organizations should consider implementing flexible working hours and modalities, provide safe workspaces, ensure appropriate technology and connectivity, support employees and maintain their health and well-being.

This research explores the experiences of teleworkers, on-site workers and hybrid workers during the COVID-19 pandemic in an under-researched labor market within a developing country. The study provides valuable insights that highlight the potential for management development initiatives specifically tailored to hybrid work environments.

The purpose of this research paper is to explore the determinants of patients' service choices between telephone consultation and text consultation in online health communities (OHCs).

This study utilized an empirical model based on the elaboration likelihood model and examined the effect of information, regarding service quality (the central route) and service price (the peripheral route), using online health consultation data from one of the largest OHCs in China.

The logistic regression results indicated that both physician- and patient-generated information can influence the patients' service choices; service price signals will lead patients to cheaper options. However, individual motivations, disease risk and consulting experience change a patients' information processing regarding central and peripheral cues.

Previous researchers have investigated the mechanism of patient behavior in OHCs; however, the researchers have not focused on the patients' choices regarding the multiple health services provided in OHCs. The findings of this study have theoretical and practical implications for future researchers, OHC designers and physicians.

Today, e-government (electronic government) applications have extended to the frontiers of health-care delivery. E-Nabız contains personal health records of health services received, whether public or private. The use of the application by patients and physicians has provided efficiency and cost advantages. The success of e-Nabız depends on the level of technology acceptance of health-care service providers and recipients. While there is a large research literature on the technology acceptance of service recipients in health-care services, there is a limited number of studies on physicians providing services. This study aims to determine the level of influence of trust and privacy variables in addition to performance expectancy, effort expectancy, social influence and facilitating factors in the unified theory of acceptance and use of technology (UTAUT) model on the intention and behavior of using e-Nabız application.

The population of the study consisted of general practitioners and specialist physicians actively working in any health facility in Turkey. Data were collected cross-sectionally from 236 physicians on a voluntary basis through a questionnaire. The response rate of data collection was calculated as 47.20%. Data were collected cross-sectionally from 236 physicians through a questionnaire. Descriptive statistics, correlation analysis and structural equation modeling were used to analyze the data.

The study found that performance expectancy, effort expectancy, trust and perceived privacy had a significant effect on physicians’ behavioral intentions to adopt the e-Nabız system. In addition, facilitating conditions and behavioral intention were determinants of usage behavior (p < 0.05). However, no significant relationship was found between social influence and behavioral intention (p > 0.05).

This study confirms that the UTAUT model provides an appropriate framework for predicting factors influencing physicians’ behaviors and intention to use e-Nabız. In addition, the empirical findings show that trust and perceived privacy, which are additionally considered in the model, are also influential.