Evolution of Online Health-Related Information Seeking in France From 2010 to 2017: Results From Nationally Representative Surveys

Health information-seeking behavior in patients with coronary artery disease: Activating methods

INTRODUCTION

Coronary artery disease (CAD) has a high mortality rate worldwide, and continuous health behavior practice and careful management are required owing to risks such as rapid changes in symptoms and emergency hospitalization. The utilization of health-related information is an important factor for long-term disease management in patients with CAD. For this purpose, an understanding of health information-seeking behavior is needed first.

METHODS

This study analyzed data from the 2021 Korea Medical Panel Survey, and logistic regression analysis was conducted to confirm the factors influencing the health information-seeking behavior of patients with CAD.

RESULTS

The health information-seeking behavior of patients with CAD differed according to demographic characteristics, and differences in preferred information use were confirmed. Finally, it was identified that insufficient levels of health literacy were a major reason for CAD patients not engaging in health information-seeking behaviors (OR, 0.17; 95% CI, 0.09-0.33; p < 0.001).

CONCLUSION

This study suggests that to improve health information-seeking behaviors, the application of education and intervention programs to increase the level of health literacy is necessary.

Evaluating a Public Health Information Service According to Users' Socioeconomic Position and Health Status: Protocol for a Cross-Sectional Study

BACKGROUND

The increasing use of information technology in the field of health is supposed to promote users' empowerment but can also reinforce social inequalities. Some health authorities in various countries have developed mechanisms to offer accurate and relevant information to health care system users, often through health websites. However, the evaluation of these sociotechnical tools is inadequate, particularly with respect to differences and inequalities in use by social groups.

OBJECTIVE

Our study aims to evaluate the access, understanding, appraisal, and use of the French website Santé.fr by users according to their socioeconomic position and perceived health status.

METHODS

This cross-sectional study involves the entire French population to which Santé.fr is offered. Data will be collected through mixed methods, including a web-based questionnaire for quantitative data and interviews and focus groups for qualitative data. Collected data will cover users' access, understanding, appraisal, and use of Santé.fr, as well as sociodemographic and socioeconomic characteristics, health status, and digital health literacy. A validation of the dimensions of access, understanding, appraisal, and use of Santé.fr will be conducted, followed by principal component analysis and ascendant hierarchical classification based on the 2 main components of principal component analysis to characterize homogeneous users' profiles. Regression models will be used to investigate the relationships between each dimension and socioeconomic position and health status variables. NVivo 11 software (Lumivero) will be used to categorize interviewees' comments into preidentified themes or themes emerging from the discourse and compare them with the comments of various types of interviewees to understand the factors influencing people's access, understanding, appraisal, and use of Santé.fr.

RESULTS

Recruitment is scheduled to begin in January 2024 and will conclude when the required number of participants is reached. Data collection is expected to be finalized approximately 7 months after recruitment, with the final data analysis programmed to be completed around December 2024.

CONCLUSIONS

This study would be the first in France and in Europe to evaluate a public health information service, in this case the Santé.fr website (the official website of the French Ministry of Health), according to users' socioeconomic position and health status. The study could discover issues related to inequalities in access to, and the use of, digital technologies for obtaining health information on the internet. Given that access to health information on the internet is crucial for health decision-making and empowerment, inequalities in access may have subsequent consequences on health inequalities among social categories. Therefore, it is important to ensure that all social categories have access to Santé.fr.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/51123.

Understanding Trust Determinants in a Live Chat Service on Familial Cancer: Qualitative Triangulation Study With Focus Groups and Interviews in Germany

BACKGROUND

In dealing with familial cancer risk, seeking web-based health information can be a coping strategy for different stakeholder groups (ie, patients, relatives, and those suspecting an elevated familial cancer risk). In the vast digital landscape marked by a varied quality of web-based information and evolving technologies, trust emerges as a pivotal factor, guiding the process of health information seeking and interacting with digital health services. This trust formation in health information can be conceptualized as context dependent and multidimensional, involving 3 key dimensions: information seeker (trustor), information provider (trustee), and medium or platform (application). Owing to the rapid changes in the digital context, it is critical to understand how seekers form trust in new services, given the interplay among these different dimensions. An example of such a new service is a live chat operated by physicians for the general public with personalized cancer-related information and a focus on familial cancer risk.

OBJECTIVE

To gain a comprehensive picture of trust formation in a cancer-related live chat service, this study investigates the 3 dimensions of trust-trustor, trustee, and application-and their respective relevant characteristics based on a model of trust in web-based health information. In addition, the study aims to compare these characteristics across the 3 different stakeholder groups, with the goal to enhance the service's trustworthiness for each group.

METHODS

This qualitative study triangulated the different perspectives of medical cancer advisers, advisers from cancer support groups, and members of the public in interviews and focus group discussions to explore the 3 dimensions of trust-trustor, trustee, and application-and their determinants for a new live chat service for familial cancer risk to be implemented at the German Cancer Information Service.

RESULTS

The results indicate that experience with familial cancer risk is the key trustor characteristic to using, and trusting information provided by, the live chat service. The live chat might also be particularly valuable for people from minority groups who have unmet needs from physician-patient interactions. Participants highlighted trustee characteristics such as ability, benevolence, integrity, and humanness (ie, not a chatbot) as pivotal in a trustworthy cancer live chat service. Application-related characteristics, including the reputation of the institution, user-centric design, modern technology, and visual appeal, were also deemed essential. Despite the different backgrounds and sociodemographics of the 3 stakeholder groups, many overlaps were found among the 3 trust dimensions and their respective characteristics.

CONCLUSIONS

Trust in a live chat for cancer information is formed by different dimensions and characteristics of trust. This study underscores the importance of understanding trust formation in digital health services and suggests potential enhancements for effective, trustworthy interactions in live chat services (eg, by providing biographies of the human medical experts to differentiate them from artificial intelligence chatbots).

Explaining Health Misinformation Belief through News, Social, and Alternative Health Media Use: The Moderating Roles of Need for Cognition and Faith in Intuition

Explaining the spread and impact of health misinformation has garnered considerable attention with the uptake of social media and group messaging applications. This study contributes to that line of work by investigating how reliance on multiple digital media may help support or suppress misinformation belief, and how individual differences in misinformation susceptibility condition this process. Alternative health outlets (AH media), advocating home/homeopathic remedies over conventional medicine can be important sources of misinformation, yet are largely ignored previously. In this study, we first test how reliance on different platforms predicts health misinformation belief. Drawing from the elaboration likelihood model, we further investigate how need for cognition (NFC) and faith in intuition (FI) moderate the relationship between news reliance and susceptibility to misinformation. We conducted a survey in Singapore, Turkey, and the U.S (N = 3,664) to measure how these proposed relationships explain misinformed beliefs about vaccines, genetically modified foods and alternative medicine. We found reliance on online legacy news was negatively associated with the likelihood of believing health misinformation, while the reverse was true for social media and AH media. Additionally, those with both greater NFC and FI were more susceptible to health misinformation when they relied on social media and AH media more. In contrast, neither NFC nor FI moderated the relationship between reliance on online legacy news and health misinformation belief. These findings, mostly consistent across countries, also show that extensive reliance on social media and AH media for news mostly overwhelms the individual differences in predicting misinformation belief.

[Artificial intelligence and internal medicine: The example of hydroxychloroquine according to ChatGPT]

Artificial intelligence (AI) using deep learning is revolutionizing several fields, including medicine, with a wide range of applications. Available since the end of 2022, ChatGPT is a conversational AI or "chatbot", using artificial intelligence to dialogue with its users in all fields. Through the example of hydroxychloroquine (HCQ), we discuss its use for patients, clinicians, or researchers, and discuss its performance and limitations, particularly in relation to algorithmic bias. If AI tools using deep learning do not dispense with the expertise and experience of a clinician (at least, for the moment), they have a potential to improve or simplify our daily practice.

Online Health Information Seeking: An Italian Case Study for Analyzing Citizens' Behavior and Perception

This study aims to understand people's behavior when searching for online health information (and COVID-19 information) and their perception of the trustworthiness and credibility of the searched information, the actors, and sources used to obtain it. A questionnaire addressed to people who permanently live in Italy between ages 19 and 60 has been used to collect data. Data extracted from the analysis are reassuring from the point of view of trust and credibility both in the actors and in the sources used to obtain information on health and COVID-19. A correlation between the analyzed individual features, the online health information-seeking behavior, and perception resulted from the analysis. The study also underlined a positive correlation between the perception of the influence of information on the knowledge of health problems and the ability to identify false online health information, and between the experience in detecting false health online information and the ability to detect it. Finally, a positive correlation also resulted between the experience in finding online health information and the experience in finding false COVID-19 information.

Relationships among patient activation, social support and online health information seeking of community-dwelling older adults living with coronary heart disease

AIMS

To explore the relationship between patient activation (subjective initiative of patients to participate in disease management in self-health care), social support, self-efficacy and online health information seeking among older patients with coronary heart disease.

DESIGN

A cross-sectional and survey-based design.

METHODS

A total of 451 older patients with coronary heart disease were recruited from July to November 2021 from four communities in Qingdao, China. We collected data using the Patient Activation Measure, Social Support Rating Scale, Self-Efficacy Scale and Online Health Information Seeking Scale. We performed structural equation modelling to analyse the data.

RESULTS

The final model showed good model fit. Patient activation influenced online health information seeking directly (β  = .39, p  < .05) and indirectly through self-efficacy (β  = .17, p  < .05). Social support influenced online health information seeking directly (β  = .23, p  < .05) and indirectly through self-efficacy (β  = .03, p  < .05). Self-efficacy directly influenced online health information seeking (β  = .26, p  < .05).

CONCLUSIONS

We identified the interrelationships of patient activation, social support and self-efficacy and their influence on the online health information seeking of older patients with coronary heart disease. Our findings provide a theoretical basis for developing and evaluating interventions to enhance online health information seeking for older patients with coronary heart disease.

IMPACT

These findings add a better understanding of the relationship between patient activation, social support, self-efficacy and online health information seeking in older patients with coronary heart disease, and help community health workers to intervene in the early stage of disease diagnosis.

Health Disparities in Online COVID-19 Information Seeking and Protective Behaviors: A Two-Wave Longitudinal Study

The COVID-19 outbreak was declared a pandemic by the World Health Organization and claimed hundreds of thousands of lives in the U.S. However, the adoption of protective behaviors in response to COVID-19 varies among sociodemographic groups. To better understand the disparities in U.S. adults' adoption of protective behaviors in relation to sociodemographic factors, we conducted a two-wave panel survey in the U.S. Although sociodemographic factors were not found to be significant predictors in lagged regression analysis, results from a cross-sectional analysis showed that the White, younger, and higher educated individuals were more likely to take protective behaviors. Furthermore, based on the structural equation modeling, indirect effects were observed. Specifically, online COVID-19 information seeking mediated the effects of age and education on performance of protective behaviors, and subjective norms and online COVID-19 information seeking were found to be significant serial mediators of these relationships. The study not only extends the health disparities and health information seeking literature, but also offers practical insights to health campaigns and interventions promoting protective behaviors during a pandemic and reducing health disparities.

Modeling Access Across the Digital Divide for Intersectional Groups Seeking Web-Based Health Information: National Survey

Background

The digital divide refers to technological disparities based on demographic characteristics (eg, race and ethnicity). Lack of physical access to the internet inhibits online health information seeking (OHIS) and exacerbates health disparities. Research on the digital divide examines where and how people access the internet, whereas research on OHIS investigates how intersectional identities influence OHIS. We combine these perspectives to explicate how unique context–device access pairings operate differently across intersectional identities—particularly racial and ethnic groups—in the domain of OHIS.

Objective

This study aims to examine how different types of internet access relate to OHIS for different racial and ethnic groups. We investigate relationships among predisposing characteristics (ie, age, sex, education, and income), internet access (home computer, public computer, work computer, and mobile), health needs, and OHIS.

Methods

Analysis was conducted using data from the 2019 Health Information National Trends Survey. Our theoretical model of OHIS explicates the roles of internet access and health needs for racial and ethnic minority groups’ OHIS. Participant responses were analyzed using structural equation modeling. Three separate group structural equation modeling models were specified based on Black, Latine, and White self-categorizations.

Results

Overall, predisposing characteristics (ie, age, sex, education, and income) were associated with internet access, health needs, and OHIS; internet access was associated with OHIS; and health needs were associated with OHIS. Home computer and mobile access were most consistently associated with OHIS. Several notable linkages between predisposing characteristics and internet access differed for Black and Latine individuals. Older racial and ethnic minorities tended to access the internet on home and public computers less frequently; home computer access was a stronger predictor of OHIS for White individuals, and mobile access was a stronger predictor of OHIS for non-White individuals.

Conclusions

Our findings necessitate a deeper unpacking of how physical internet access, the foundational and multifaceted level of the digital divide, affects specific racial and ethnic groups and their OHIS. We not only find support for prior work on the digital divide but also surface new insights, including distinct impacts of context–device access pairings for OHIS and several relationships that differ between racial and ethnic groups. As such, we propose interventions with an intersectional approach to access to ameliorate the impact of the digital divide.

The Use of Big Data via 5G to Alleviate Symptoms of Acute Stress Disorder Caused by Quarantine Measures

This article investigates the role of Big Data in situations of psychological stress such as during the recent pandemic caused by the COVID-19 health crisis. Quarantine measures, which are necessary to mitigate pandemic risk, are causing severe stress symptoms to the human body including mental health. We highlight the most common impact factors and the uncertainty connected with COVID-19, quarantine measures, and the role of Big Data, namely, how Big Data can help alleviate or mitigate these effects by comparing the status quo of current technology capabilities with the potential effects of an increase of digitalization on mental health. We find that, while Big Data helps in the pre-assessment of potentially endangered persons, it also proves to be an efficient tool in alleviating the negative psychological effects of quarantine. We find evidence of the positive effects of Big Data on human health conditions by assessing the effect of internet use on mental health in 173 countries. We found positive effects in 110 countries with 90 significant results. However, increased use of digital media and exclusive exposure to digital connectivity causes negative long-term effects such as a decline in social empathy, which creates a form of psychological isolation, causing symptoms of acute stress disorder.

An examination of the quality of late-life depression websites on the Internet (Preprint)

Background

The internet can increase the accessibility of mental health information and improve the mental health literacy of older adults. The quality of mental health information on the internet can be inaccurate or biased, leading to misinformation.

Objective

This study aims to evaluate the quality, usability, and readability of websites providing information concerning depression in later life.

Methods

Websites were identified through a Google search and evaluated by assessing quality (DISCERN), usability (Patient Education Materials Assessment Tool), and readability (Simple Measure of Gobbledygook).

Results

The overall quality of late-life depression websites (N=19) was adequate, and the usability and readability were poor. No significant relationship was found between the quality and readability of the websites.

Conclusions

The websites can be improved by enhancing information quality, usability, and readability related to late-life depression. The use of high-quality websites may improve mental health literacy and shared treatment decision-making for older adults.

Analyzing Psychotherapy on Twitter: An 11-Year Analysis of Tweets From Major U.S. Media Outlets

BACKGROUND

The Internet has become the main source of information on health issues, and information now determines the therapeutic preferences of patients. For this reason, it is relevant to analyze online information discussing psychotherapy.

OBJECTIVE

To investigate tweets posted by 25 major US media outlets between 2009 and 2019 concerning psychotherapy.

METHODS

We investigated tweets posted by 25 major US media outlets about psychotherapy between January 2009 and December 2019 as well as the likes generated. In addition, we measured the sentiment analysis of these tweets.

RESULTS

Most of the tweets analyzed focused on Mindfulness (5,498), while a low number were related to Psychoanalysis (376) and even less to Cognitive-Behavioral Therapy (61). Surprisingly, Computer-supported therapy, Psychodynamic therapy, Systemic therapy, Acceptance and commitment therapy, and Dialectical behavior therapy did not generate any tweet. In terms of content, efficacy was the main focus of the posted tweets, receiving Cognitive-Behavioral Therapy and Mindfulness a positive appraisal.

CONCLUSIONS

US media outlets focused their interest on Mindfulness which may have contributed to the growing popularity in the past years of this therapeutic modality.