Why Do Consumers Review Doctors Online? Topic Modeling Analysis of Positive and Negative Reviews on an Online Health Community in China

Consumers often learn from others through a social learning process (e.g. electronic word of mouth) before making decisions. From the e-business perspective, online reviews have changed how people select products and services, and no doubt it is the same in the e-health sector. In this study, we examine online reviews of patients and health consumers for their doctors in an online health consultation platform in China. We combine machine learning and qualitative techniques to derive the themes of online reviews and the factors leading to positive and negative reviews. Our analysis demonstrates that service levels of hospitals, doctors’ communication skills and their professional skills influence the sentiment of reviews. Our findings offer important insights into theories and practice for studying online reviews in the healthcare context

ONLINE HEALTH INFORMATION SEEKING BEHAVIOUR: UNDERSTANDING DIFFERENT SEARCH APPROACHES

People intuitively use search engines to look for health information. However, people take an exploratory search approach to find the information in some scenarios, and current search engines do not support these cases well. This exploratory information seeking behaviour is rarely investigated by researchers in the context of online consumer health information. We report on a qualitative study to conceptualise the health information seeking behaviour of lay-people. This paper describes the result of this study, and makes a contribution towards a conceptual understanding of search approaches by people seeking health information, search strategies used by health information seekers, and design implications for providing a better exploratory health search experience

INNOVATION IN DESIGNING HEALTH INFORMATION WEBSITES: RESULTS FROM A QUANTITATIVE STUDY

A wealth of health information exists on the Internet, but successfully finding that information is not easy. One of the issues causing this is the lack of tools for exploring information and assisting in navigation within health websites. As a result, relevant information cannot be easily discovered. We hope to rectify this issue from the design perspective. Based on previous work, we have created a prototype website called Better Health Explorer to better support such information seeking behaviours. This paper reports on a quantitative study evaluating this prototype. The results demonstrate several improvements in health information seeking supported by the tool. Furthermore, we have identified three general design characteristics that should to be considered when designing consumer health websites. These findings have design implications for health information seeking applications, as well as identifying directions for further research

IvyGPT: InteractiVe Chinese pathwaY language model in medical domain

General large language models (LLMs) such as ChatGPT have shown remarkable success. However, such LLMs have not been widely adopted for medical purposes, due to poor accuracy and inability to provide medical advice. We propose IvyGPT, an LLM based on LLaMA that is trained and fine-tuned with high-quality medical question-answer (QA) instances and Reinforcement Learning from Human Feedback (RLHF). After supervised fine-tuning, IvyGPT has good multi-turn conversation capabilities, but it cannot perform like a doctor in other aspects, such as comprehensive diagnosis. Through RLHF, IvyGPT can output richer diagnosis and treatment answers that are closer to human. In the training, we used QLoRA to train 33 billion parameters on a small number of NVIDIA A100 (80GB) GPUs. Experimental results show that IvyGPT has outperformed other medical GPT models.Comment: 5 pages, 3 figure

The impacts of tobacco control legislation on public view of e-cigarette usage in Macao—The co-word analysis of Macao daily

IntroductionMacao has been certified as a “Healthy City” by the World Health Organization, and has been adhering to the principle of combining prevention with proper medical care to build its medical system. As tobacco epidemic is a risk factor leading to a series of non-communicable diseases, the Macao SAR Government has continuously improved tobacco control measures.MethodsThe data for this study were derived from a news report on “e-cigarettes” published in Macao Daily. Co-word analysis and thematic analysis were conducted to analyze the development of tobacco control legislation against e-cigarettes. Co-word analysis examined the association and frequency of keywords, while thematic analysis identified prevalent themes within the data.ResultsThe study identified three stages of legislation against e-cigarettes: the pre-implementation stage, the early implementation stage, and the epidemic period. Each stage exhibited distinct characteristics and attention toward specific groups, particularly “teenagers” and “students,” increased significantly. Thematic analysis further highlighted the potential issues of drug use and smuggling associated with e-cigarettes.DiscussionThe findings suggest that the Macao SAR Government should prioritize the development of healthy behaviors among adolescents in the context of e-cigarette control. Additionally, considering regional cooperation to promote the “Healthy Bay Area” could be beneficial. Social media platforms and effective data management should be utilized as tools in these efforts

Intention of Use of the Patient-centric Research Engagement Portal (PREP)

Patients are keen to participate in health research in this era of participatory health, but they cannot easily obtain information about research; meanwhile, researchers are facing challenges when recruiting participants for their research because their messages cannot reach patients efficiently. To mitigate both issues, we explore the use of a patient-centric research engagement portal (PREP), which is a unified system to disseminate information about research studies and to collect registrations for the participation of research projects. In this paper, we particularly investigate the intention of use of PREPs by conducting focus groups and semi-structured interviews. As a part of our analysis, we propose a model to describe the patientrelated and the owner-related factors that affect the intention of use. Finally, we conclude with several design implications for information systems to recruit and engage with research participants

Changes in Doctor–Patient Relationships in China during COVID-19: A Text Mining Analysis

Doctor–patient relationships (DPRs) in China have been straining. With the emergence of the COVID-19 pandemic, the relationships and interactions between patients and doctors are changing. This study investigated how patients’ attitudes toward physicians changed during the pandemic and what factors were associated with these changes, leading to insights for improving management in the healthcare sector. This paper collected 58,600 comments regarding Chinese doctors from three regions from the online health platform Good Doctors Online (haodf.com, accessed on 13 October 2022). These comments were analyzed using text mining techniques, such as sentiment and word frequency analyses. The results showed improvements in DPRs after the pandemic, and the degree of improvement was related to the extent to which a location was affected. The findings also suggest that administrative services in the healthcare sector need further improvement. Based on these results, we summarize relevant recommendations at the end of this paper

ONLINE HEALTH INFORMATION SEEKING BEHAVIOUR: UNDERSTANDING DIFFERENT SEARCH APPROACHES

Abstract People intuitively use search engines to look for health information. However, people take an exploratory search approach to find the information in some scenarios, and current search engines do not support these cases well. This exploratory information seeking behaviour is rarely investigated by researchers in the context of online consumer health information. We report on a qualitative study to conceptualise the health information seeking behaviour of lay-people. This paper describes the result of this study, and makes a contribution towards a conceptual understanding of search approaches by people seeking health information, search strategies used by health information seekers, and design implications for providing a better exploratory health search experience