Revisiting Effective Communication Between Patients and Physicians: Cross-Sectional Questionnaire Study Comparing Text-Based Electronic Versus Face-to-Face Communication

The Purpose of Internet Use and Face-To-Face Communication With Friends and Acquaintances Among Older Adults: A JAGES Longitudinal Study

Internet use influences social interactions in society. However, there is no consensus on whether and what kind of Internet use increases face-to-face communication (FFC). This study investigated the mode of Internet use that increases FFC among older adults after three years. Participants were 8734 adults aged 65 or older who responded to the Japan Gerontological Evaluation Study (JAGES) surveys in 2016 and 2019. The exposures were the purposes of Internet use in 2016. The outcome was the frequency of FFC with friends or acquaintances in 2019. The confounders included 13 demographic, socioeconomic, and psychological variables. We performed modified Poisson regression analyses and found that Internet use for communication in 2016 increased FFC in 2019, especially for low-frequency FFC in 2016. Internet-based non-FFC may help promote FFC and prevent social isolation among older adults who are less likely to interact with others.

The Association of eHealth Literacy Skills and mHealth Application Use Among US Adults With Obesity: Analysis of Health Information National Trends Survey Data

BACKGROUND

Physical inactivity and a poor diet are modifiable behaviors that contribute to obesity. Obesity is a well-recognized risk factor for chronic diseases, including diabetes. Mobile health (mHealth) apps can play an important adjuvant role in preventing and treating chronic diseases and promoting positive health behavior change among people with obesity, and eHealth literacy skills have the potential to impact mHealth app use.

OBJECTIVE

The purpose of this study was to explore the associations between the 2 dimensions, access and application, of eHealth literacy skills and mHealth app use among US adults (≥18 years of age) with obesity (BMI ≥30 kg/m2).

METHODS

Data were obtained from February to June 2020 using the Health Information National Trends Survey 5. A total of 1079 respondents met the inclusion criteria of adults with obesity and owners of smartphones. Individual associations between mHealth app use and sociodemographic variables were explored using weighted chi-square and 2-tailed t tests. A multivariable weighted logistic regression model was fitted, and adjusted odds ratios (ORs) of using mHealth apps with corresponding 95% CIs were reported across multiple sociodemographic variables. An Ising model-weighted network visualization was produced. A receiver operating characteristic curve was calculated, and the area under the curve was reported with the corresponding Delong 95% CI.

RESULTS

A majority of respondents were female (550/923, 59.6%) or non-Hispanic White (543/923, 58.8%). Individuals in households earning less than US $50,000 comprised 41.4% (382/923) of the sample. All sociodemographic variables were found to be univariately significant at the 5% level, except employment and region. Results from the multivariable weighted logistic regression model showed that the adjusted odds of using an mHealth app are 3.13 (95% CI 1.69-5.80) and 2.99 (95% CI 1.67-5.37) times higher among those with an access eHealth literacy skill of using an electronic device to look for health or medical information for themselves and an application eHealth literacy skill of using electronic communications with a doctor or doctor's office, respectively. Several sociodemographic variables were found to be significant, such as education, where adjusted ORs comparing subgroups to the lowest educational attainment were substantial (ORs ≥7.77). The network visualization demonstrated that all eHealth literacy skills and the mHealth app use variable were positively associated to varying degrees.

CONCLUSIONS

This work provides an initial understanding of mHealth app use and eHealth literacy skills among people with obesity, identifying people with obesity subpopulations who are at risk of a digital health divide. Future studies should identify equitable solutions for people with obesity (as well as other groups) and their use of mHealth apps.

The Effect of Characteristics of Patient Communication on Physician Feedback in Online Health Communities: An Observational Cross-Sectional Study

With the rapid development of e-health and telemedicine, previous studies have explored the relationship between physician-patient communication and patient satisfaction; however, there is a paucity of research on the influence of the characteristics of patient communication on the characteristics of physician feedback. Based on the communication accommodation theory, as well as the computer-mediated communication theory and media richness theory, this study aimed to explore how characteristics of patient communication influence characteristics of physician feedback in online health communities. We employed a crawler software to download the communication data between 1652 physicians and 105,325 patients from the Good Doctor platform, the biggest online health community in China. We built an empirical model using this data and employed a multilevel model to test our hypotheses using Stata and Python software. The results indicate that the amount of patients' rendered information positively influences the physicians' text (α = 0.123, t = 33.147, P < .001) and voice feedback (β = 0.201, t = 40.011, P < .001). Patients' hope for help signals and the provision of their electronic health records weaken the effect of the amount of patients' rendered information on physicians' text feedback (α = -0.040, t = -24.857, P < .001; α = -0.048, t = -15.784, P < .001), whereas, it strengthened the effect of the amount of patients' rendered information on physicians' voice feedback (β = 0.033, t = 14.789, P < .001; β = 0.017, t = 4.208, P < .001). Moreover, the occurrence of high-privacy diseases strengthened the effect of the amount of patients' presented information on physicians' text and voice feedback (α = 0.023, t = 4.870, P < .001; β = 0.028, t = 4.282, P < .001). This research contributes to the development of computer-mediated communication theories and sheds light on service delivery in the online health community.

General Practitioners' Experiences With Potentials and Pitfalls of Video Consultations in Norway During the COVID-19 Lockdown: Qualitative Analysis of Free-Text Survey Answers

BACKGROUND

The use of video consultations (VCs) in Norwegian general practice rapidly increased during the COVID-19 pandemic. During societal lockdowns, VCs were used for nearly all types of clinical problems, as in-person consultations were kept to a minimum.

OBJECTIVE

This study aimed to explore general practitioners' (GPs') experiences of potentials and pitfalls associated with the use of VCs during the first pandemic lockdown.

METHODS

Between April 14 and May 3, 2020, all regular Norwegian GPs (N=4858) were invited to answer a web-based survey, which included open-ended questions about their experiences with the advantages and pitfalls of VCs. A total of 2558 free-text answers were provided by 657 of the 1237 GPs who participated in the survey. The material was subjected to reflexive thematic analysis.

RESULTS

Four main themes were identified. First, VCs are described as being particularly convenient, informative, and effective for consultations with previously known patients. Second, strategically planned VCs may facilitate effective tailoring of clinical trajectories that optimize clinical workflow. VCs allow for an initial overview of the problem (triage), follow-up evaluation after an in-person consultation, provision of advice and information concerning test results and discharge notes, extension of sick leaves, and delivery of other medical certificates. VCs may, in certain situations, enhance the GPs' insight in their patients' relational and socioeconomical resources and vulnerabilities, and even facilitate relationship-building with patients in need of care who might otherwise be reluctant to seek help. Third, VCs are characterized by a demarcated communication style and the "one problem approach," which may entail effectiveness in the short run. However, the web-based communication climate implies degradation of valuable nonverbal signals that are more evidently present in in-person consultations. Finally, overreliance on VCs may, in a longer perspective, undermine the establishment and maintenance of relational trust, with a negative impact on the quality of care and patient safety. Compensatory mechanisms include clarifying with the patient what the next step is, answering any questions and giving further advice on treatment if conditions do not improve or there is a need for follow-up. Participation of family members can also be helpful to improve reciprocal understanding and safety.

CONCLUSIONS

The findings have relevance for future implementation of VCs and deserve further exploration under less stressful circumstances.

Insights Into the Relationships Between Health Communication and Doctor-patient Relationship: A Scientometric Analysis Based on CiteSpace and Validation of Questionnaires

In order to understand the research status of the relationship between health communication and doctor-patient relationship, and to explore a new path of the impact of health communication on doctor-patient relationship, this paper adopted qualitative methods to quantize the literature over the past 10 years in the Web of Science database and carried out Co-Authorship Analysis, Co-Citation Analysis and Co-Occurrence Analysis based on CiteSpace. In addition, according to the results of bibliometric research, self-designed questionnaires were used to verify the result. A convenience sampling survey was conducted through the online "Questionnaire Star" platform (https://www.wjx.cn) on May 8, 2022, and a total of 254 questionnaires were collected. Interviewees were asked to use social software to acquire health knowledge. Participants come from 21 provinces, 4 municipalities, and 4 autonomous regions across the country, which is geographically representative. The results show that uncertainty of social media information and the particularity of the epidemic make the research on health communication and doctor-patient relationship in social media become a new hot spot. Social media health information quality (source credibility and content trust perception), information asymmetry perception, doctor-patient communication, doctor-patient consistency, doctor-patient trust, doctor-patient relationship may be the key variables for constructing theoretical models.

Evaluation of Online Patient Portal vs Text-Based Blood Pressure Monitoring Among Black Patients With Medicaid and Medicare Insurance Who Have Hypertension and Cardiovascular Disease

This pilot randomized clinical trial evaluates the increased uptake and acceptability of a text-based model for home blood pressure monitoring compared with online portal use among Black patients with Medicaid and Medicare insurance who have hypertension and cardiovascular disease.

Should doctors use or avoid medical terms? The influence of medical terms on service quality of E-health

With epidemics and pandemics like COVID-19, many offline healthcare services have been suspended and shifted to online, where patients and doctors typically communicate by typing texts. The limited communication poses a threat to the service quality of E-health, and also raises higher demand on the language skills of doctors, in which medical terms are a common concern. Traditional studies of offline healthcare mostly hold a negative attitude towards the use of medical terms by doctors. However, should we still advise doctors to avoid using medical terms in E-health? To answer this question, this paper conducts a study combining technical and empirical analyses based on real data. In this paper, a novel unsupervised text-mining method is proposed to automatically identify medical terms with crowd wisdom from large-scale doctor-patient communication texts. Then, a TREC-type experiment is carried out to validate the proposed method in terms of Precision, Recall, and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_1$$\end{document}F1-measure, demonstrating that it can identify accurate and comprehensive medical terms. Based on the identified medical terms, an empirical analysis is conducted to verify the influence of medical terms used by doctors on the service quality of E-health. The analysis results show that for patients with low health literacy, the use of medical terms by doctors would decrease their service quality. However, for patients with high health literacy, the use of medical terms by doctors can significantly increase their service quality, revealing that doctors could improve their service quality in E-health by adjusting their medical term usage according to the health literacy of patients.

Machine Learning Techniques for Personalised Medicine Approaches in Immune-Mediated Chronic Inflammatory Diseases: Applications and Challenges

In the past decade, the emergence of machine learning (ML) applications has led to significant advances towards implementation of personalised medicine approaches for improved health care, due to the exceptional performance of ML models when utilising complex big data. The immune-mediated chronic inflammatory diseases are a group of complex disorders associated with dysregulated immune responses resulting in inflammation affecting various organs and systems. The heterogeneous nature of these diseases poses great challenges for tailored disease management and addressing unmet patient needs. Applying novel ML techniques to the clinical study of chronic inflammatory diseases shows promising results and great potential for precision medicine applications in clinical research and practice. In this review, we highlight the clinical applications of various ML techniques for prediction, diagnosis and prognosis of autoimmune rheumatic diseases, inflammatory bowel disease, autoimmune chronic kidney disease, and multiple sclerosis, as well as ML applications for patient stratification and treatment selection. We highlight the use of ML in drug development, including target identification, validation and drug repurposing, as well as challenges related to data interpretation and validation, and ethical concerns related to the use of artificial intelligence in clinical research.

Are Diverse Media Better than a Single Medium? The Relationship between Mixed Media and Perceived Effect from the Perspective of Online Psychological Counseling

The progress of new media has promoted the development of online health consultations. Previous research has investigated the impact of media richness on user satisfaction; however, little attention has been given to the mixed effects of the nesting of multiple media. The purpose of this study is to analyze the impact and differences of the use of single or mixed media on users' perceived effect from the perspectives of social support and satisfaction by mining user reviews on online health platforms. The data were collected from a professional online psychological counseling platform. We collected data on 48,807 reviews from 11,694 users. Text annotation and sentiment analysis were then used to extract variable eigenvalues from the reviews. One-way analysis of variance (ANOVA) and hierarchical regression analysis were used for statistical analysis. The results show that mixed media with different richness has a significant impact on the users' perceived effects. Among them, compared to "text + audio," using "text + audio + video/face to face" can significantly improve the users' perceived social support and satisfaction. However, compared to single medium, mixed media with higher richness may not necessarily achieve a better effect. We found that the inclusion of "video/face to face" mixed media significantly reduced the users' perceived social support and satisfaction compared to text or audio use alone. These research results complement the blank media richness theory in the field of online health care and provide guidance for improving the personalized customization of online psychological counseling platforms.

Analysis of topics and characteristics of user reviews on different online psychological counseling methods

BACKGROUND

Psychological support is available more widely supported by emerging technologies as an addition to face-to-face consultations, more and more people are accessing psychological support using online resources.

OBJECTIVE

This research provides insights into the perception of the key factors that affect the effectiveness of different online psychological counseling methods through the user reviews of four online psychological counseling modes and the tendency to choose the different counseling methods for users with different psychological problems.

METHODS

Using topic modeling analysis, Gooseeker content analysis, and the TextMind Chinese psychological analysis system, we analyzed 163,377 online reviews from 2,375 psychological consultants extracted from a leading online psychological consultation platform in China.

RESULTS

(1) Telephone counseling gains the most preferences among users. Text counseling has strong privacy protection. Video and face-to-face consultations are more authentic and comprehensive. (2) Parent-child education consultation users are more likely to choose face-to-face consultation, patients with common mental illnesses are more inclined to choose online counseling methods than offline consultation, career planning consultation clients prefer video consultation, and text counseling is more consistent with the periodical characteristics of relationship counseling.

CONCLUSION

The research examined user reviews and used content analysis to understand patients' views on the effectiveness of online counseling methods, which supplement the current research gap through innovation in research methods.

Investigating the Acceptance of Video Consultation by Patients in Rural Primary Care: Empirical Comparison of Preusers and Actual Users

BACKGROUND

The ongoing digitalization in health care is enabling patients to receive treatment via telemedical technologies, such as video consultation (VC), which are increasingly being used by general practitioners. Rural areas in particular exhibit a rapidly aging population, with an increase in associated health issues, whereas the level of attraction for working in those regions is decreasing for young physicians. Integrating telemedical approaches in treating patients can help lessen the professional workload and counteract the trend toward the spatial undersupply in many countries. As a result, an increasing number of patients are being confronted with digital treatment and new forms of care delivery. These novel ways of care engender interactions with patients and their private lives in unprecedented ways, calling for studies that incorporate patient needs, expectations, and behavior into the design and application of telemedical technology within the field of primary care.

OBJECTIVE

This study aims to unveil and compare the acceptance-promoting factors of patients without (preusers) and with experiences (actual users) in using VC in a primary care setting and to provide implications for the design, theory, and use of VC.

METHODS

In total, 20 semistructured interviews were conducted with patients in 2 rural primary care practices to identify and analyze patient needs, perceptions, and experiences that facilitate the acceptance of VC technology and adoption behavior. Both preusers and actual users of VC were engaged, allowing for an empirical comparison. For data analysis, a procedure was followed based on open, axial, and selective coding.

RESULTS

The study delivers factors and respective subdimensions that foster the perceptions of patients toward VC in rural primary care. Factors cover attitudes and expectations toward the use of VC, the patient-physician relationship and its impact on technology assessment and use, patients' rights and obligations that emerge with the introduction of VC in primary care, and the influence of social norms on the use of VC and vice versa. With regard to these factors, the results indicate differences between preusers and actual users of VC, which imply ways of designing and implementing VC concerning the respective user group. Actual users attach higher importance to the perceived benefits of VC and their responsibility to use it appropriately, which might be rooted in the technological intervention they experienced. On the contrary, preusers valued the opinions and expectations of their peers.

CONCLUSIONS

The way the limitations and potential of VC are perceived varies across patients. When practicing VC in primary care, different aspects should be considered when dealing with preusers, such as maintaining a physical interaction with the physician or incorporating social cues. Once the digital intervention takes place, patients tend to value benefits such as flexibility and effectiveness over potential concerns.

Factors affecting cancer patients' electronic communication with providers: Implications for COVID-19 induced transitions to telehealth

OBJECTIVE

Because of the pandemic, electronic communication between patients and clinicians has taken on increasing significance in the delivery of cancer care. The study explored personal, clinical, and technology factors predicting cancer survivors' electronic communication with clinicians.

METHODS

Data for this investigation came from the Health Information National Trends Survey (HINTS5, Cycle 2) that included 593 respondents who previously or currently had cancer. Multivariate regression analyses were used to predict electronic communication with clinicians. Predictors included demographic variables and health status, technology use (online health information-seeking behavior, tracking of health-related data such as using a Fitbit), and quality of past communication experiences with clinicians.

RESULTS

In this pre COVID-19 sample, 42 % respondents (N = 252) did not engage in any type of electronic communication (e.g., emailing, texting, data sharing) with providers. In multivariate analyses, predictors of more electronic communication with clinicians included frequency of seeking health-related information online (ß = .267, p < .001) and better communication experiences with clinicians (ß = .028, p = .034), while no demographic variable showed significance. The technology use variables (online health information seeking, health tracking) were significantly higher predictors of electronic communication with clinicians (ΔR2 = .142, p < .001) than was past experiences with clinicians (ΔR2 = .029, p = .016).

CONCLUSIONS

Access and past experience with interactive media technologies are strong predictors of cancer patients' electronic communication than with clinicians. Adoption of telehealth technology likely depends as much on patients' relationships with technology as it does their relationships with clinicians.

PRACTICE IMPLICATIONS

Since Covid-19, cancer care providers have turned to telehealth provide patients with needed cancer care services. Enhancing patients' digital competence and experience with electronic communication will help them more easily navigate telehealth care. Providers can leverage their relationship with patients to facilitate more effective use of telehealth services.