Health beliefs and the valence framework in health information seeking behaviors

Actual usage assessment among cloud storage consumers in the Philippines using a machine learning ensemble approach

Cloud storage has been widely considered among developed and developing countries due to its ability to provide a platform for large data and information storage. Developing countries like the Philippines have started using this storage and have only since considered the free services. With the aim to understand utility for development and continuous patronage, there has been lacking evidence in the intention and actual use of cloud storages. The need for study is evident to promote and develop concrete strategies for cloud storage uptake, even if payment is needed for extra storage. This study analyzed the antecedents of actual use behavior of cloud storage in a developing country like the Philippines using a machine learning ensemble (MLE). With 616 valid responses, a total of 33,264 datasets were processed to analyze the actual use of cloud storage among Filipinos, measured using the integrated extended technology acceptance model and valence framework. With an average accuracy of 93% and 90% for the MLE considered, results have presented consistent output of voluntariness, subjective norm, perceived benefit, perceived usefulness, and perceived ubiquity to be contributing factors affecting actual use behavior. It could be posited that both personal and professional usage of cloud storage has been considered by users. In addition, due to people's readiness to use technology nowadays, the adoption of which is relatively convenient for them. Evident from the findings, further technological infrastructure is needed to be enhanced in the country for a more positive continuous intention. Therefore, the application of the integrated framework may be used and expanded for other technology utilities in different countries. Lastly, practical and managerial insights were built on the results to provide strategies and development needed for marketing, utility, and application.

Public perceptions of air pollution and associated health risks in Nevada, USA: applications for health communication

BACKGROUND

We examine the extent to which acute and chronic health conditions motivate individuals to seek air quality information. We apply the theoretical elements of the Health Belief Model (HBM) to improve risk communication about ambient air pollution. We discuss the practical applications of HBM, in tandem with the principles of health communication, within an environmental health context.

METHODS

We test the predictive power of selected components related to the HBM (perceived susceptibility, perceived severity, and cues to action) for intentions to seek information about ambient air quality. We surveyed 325 individuals throughout Nevada where poor air quality poses a risk for vulnerable populations.

RESULTS

Ordinal logistic regression analyses showed that experiencing mucous membrane symptoms (eye itching, nose irritation, and dry throat/cough), perceived severity to future health threats, and having an at-risk member in the household positively and significantly predicted intentions to seek air quality information. Experiencing neuropsychological symptoms (fatigue, feeling heavy-headed, and nausea/dizziness), and having a cardiovascular or a respiratory condition did not have significant effects on reported intentions.

CONCLUSIONS

We discuss how the results of this study can be integrated into health communication practices to increase public engagement with air quality information as a personal intervention measure.

Factors influencing the continuance intention of the women's health WeChat public account: an integrated model of UTAUT2 and HBM

Background

Women's health WeChat public accounts play a crucial role in enhancing health literacy and fostering the development of healthy behaviors among women by disseminating women's health knowledge. Improving users' continuous usage behavior and retention rates for the women's health WeChat public account is vital for influencing the overall effectiveness of health communication on WeChat.

Objective

This study aimed to construct a comprehensive model, delving into the key factors influencing women's continuance intention of the women's health public accounts from the perspectives of perceived health threats, individual abilities, and technological perceptions. The goal is to provide valuable insights for enhancing user stickiness and the effectiveness of health communication on WeChat public accounts.

Method

An online survey was conducted among women receiving gynecological care at a certain hospital to gage their willingness for sustained use of the women's health WeChat public accounts. Through structural equation modeling, the study investigated the influencing factors on women's sustained intention to use the women's health WeChat public accounts.

Results

The study included a total of 853 adult women. Among them, 241 (28.3%) women had followed women's health official accounts in the past but do not currently follow them, 240 (28.1%) women had followed women's health official accounts in the past and are still following them, and 372 (43.6%) women had never followed women's health official accounts. Currently, 240 women are still browsing women's health public accounts, 52 of whom read women's health public accounts every day, and most of them read women's health public accounts for 10-20 min at a time (100, 11.7%). The results of the structural equation model revealed that performance expectancy, social influence, hedonic motivation, habit, and e-health literacy had significantly positive effects on women's sustained intention to use public accounts (performance expectancy: β = 0.341, p < 0.001; social influence: β = 0.087, p = 0.047; hedonic motivation: β = 0.119, p = 0.048; habit: β = 0.102, p < 0.001; e-health literacy: β = 0.158, p < 0.001). E-health literacy and self-efficacy indirectly influence sustained intention by affecting performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit. The effect sizes of e-health literacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.244 (p < 0.001), 0.316 (p < 0.001), 0.188 (p < 0.001), 0.226(p < 0.001), 0.154 (p < 0.001), and 0.073 (p = 0.046). The effect sizes of self-efficacy on performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit were 0.502 (p < 0.001), 0.559 (p < 0.001), 0.454 (p < 0.001), 0.662 (p < 0.001), 0.707 (p < 0.001), and 0.682 (p < 0.001). Additionally, perceived severity and perceived susceptibility indirectly affected sustained intention by influencing performance expectancy and social influence. The effect sizes of perceived severity on performance expectancy and social influence were 0.223 (p < 0.001) and 0.146 (p < 0.001). The effect size of perceived susceptibility to social influence was 0.069 (p = 0.042).

Conclusion

Users' e-health literacy, self-efficacy, perception of disease threat, and users' technological perceptions of the WeChat public accounts are critical factors influencing women's continuance intention of using the WeChat public accounts. Therefore, for female users, attention should be given to improving user experience and enhancing the professionalism and credibility of health information in public account design and promotion. Simultaneously, efforts should be made to strengthen users' health awareness and cultivate e-health literacy, ultimately promoting sustained attention and usage behavior among women toward health-focused public accounts.

Factors Influencing the Purchase Intention for Online Health Popular Science Information Based on the Health Belief Model

There is a growing demand for health popular science information from the public. Online paid health popular science information provides a new channel for the public to obtain health popular science information and can meet users' demands for high-quality health popular science information. In order to improve the popularity of online paid health popular science information, it is urgent to investigate the factors influencing users' intention to pay for online health popular science information. Paid online health popular science information can provide users with higher-quality health knowledge, while monetary compensation can incentivize publishers to create and promote the sustainability of social media platforms. Therefore, paid online health popular science information is important for readers, creators, and platforms. Therefore, this study investigates the factors influencing users' intentions to purchase online health popular science information based on the health belief model (HBM). Our research data were obtained by a questionnaire and empirically analyzed by SmartPLS structural equation modeling. The results of this study indicate that the greater the perceived susceptibility, severity, and irreplaceability of health problems, the greater the intention of users to purchase health information when they read the summary portion of paid online health popular science information. And the higher the perceived risk and the more unreasonable the price of the online health popular science information, the lower the intention to purchase. Moreover, both the perceived susceptibility and perceived severity significantly attenuated the negative impacts of perceived health popular science information risk and perceived price unreasonableness on users' intentions to purchase online health popular science information. This study not only enriches and extends the application of the health belief model, but also has important positive implications for the development of online paid health popular science information.

A study of cross-border E-commerce research trends: Based on knowledge mapping and literature analysis

As a result of the trend toward economic globalization, the vigorous development of cross-border e-commerce has attracted many scholars to study this field, involving many related fields, such as consumer behavior, advertising, information systems, and supply chain management. Throughout the existing literature, it can be found that most of the research focuses on certain influencing factors of the development of cross-border e-commerce, and there is no systematic and macro- overview of the development trend of research in this field in recent years, nor the integration and analysis of keywords. Given that the research in the field of cross-border e-commerce is fragmented to a large extent, to effectively explore the research trend in this field, we must understand the current situation of cross-border e-commerce. Systematic bibliometric analysis can solve this problem by providing publishing trends and information on various topics. Therefore, based on the scientific database web, this study collected 198 references related to cross-border e-commerce from 2016 to 2021, briefly introduced the current situation and development trend of cross-border e-commerce, visually analyzed and refined the journals, authors, research institutions, countries, publication years, keywords, citations of academic publications in this field, and other key information, and summarized the development trend and path of CEBC in the existing research. It is helpful for researchers to solve the current research gap, understand the future research direction in this field, and help academia establish a strict knowledge system.

COVID-19 information seeking behavior versus value perception among U.S. ethnic/racial minorities: differences and vaccination implications

Purpose

This study explores information behavior and perception and vaccination among America's three largest ethnic minorities, Hispanic, Black/African American and Asian, in COVID-19 context. Information behavior and perception are investigated from cultural and demographic characteristics, while vaccination is explored from COVID-19 related information behavior and utility/value of COVID-19 vaccine information.

Design/methodology/approach

Using Qualtrics survey panel, a national survey of America's Hispanic, Black/African American and Asian population was conducted to better understand the impact of cultural and demographic factors on COVID-19 related information. Data were collected in Fall 2021. Multiple and logistic regression were conducted to analyze data.

Findings

Results show that cultural factors (i.e. cultural identity, social identity, social capital and religiousness) exert significant impact on information value and seeking across all three minority groups, while some demographic factors, Republicanism and age, also significantly predict COVID-19 related information seeking and value for Black/African Americans and Hispanics, but less for Asian Americans. Lastly, information value was found to significantly predict vaccine status, willingness and eagerness, the three facets of vaccination as conceptualized in this study, for top three racial/ethic minorities.

Originality/value

The finding of this study reveal that there are variations in terms of the level and type of attachment to one's culture/social group in COVID-19 informational context. Between the three groups, granular differences were observed regarding the relationship between cultural factors and perceived COVID-19 information value. While cultural identity is most associated with African Americans, social capital is most evident for the Asian Americans, but social identity was the strongest predictor among Hispanics. Thus, this study offers important strategic insights into a unique population sample to better understand the impact of COVID-19 related information perception and vaccination implication.

Understanding the impact process of vaccine adoption for COVID-19

Vaccination for the novel coronavirus disease 2019 (COVID-19) provides an effective approach for the general improvement of social safety and individual health. To date, few studies have analyzed the adoption of COVID-19 vaccines from an entire impact process perspective. Using the health belief model (HBM) and the valence theory, this research evaluates the impact process of vaccine adoption for COVID-19. The respondents in this study were individuals who have been vaccinated in China. The effective sample included 595 individuals. Four valuable and novel findings are identified through this research. First, neither perceived susceptibility nor perceived severity has a statistically significant impact on the benefits from vaccination, threats from vaccination and self-efficacy. Second, benefits from vaccination produce a significant positive effect on self-efficacy and vaccine adoption. Third, threats from vaccination produce a significant negative effect on self-efficacy and vaccine adoption. Fourth, both self-efficacy and cues to adoption produce a significantly positive impact on vaccine adoption. Our theoretical model, which is the main contribution of this research, indicates that individual vaccine adoption is simply a process that leads from behavioral cognition to behavioral intention, rather than from psychological perception to behavioral cognition and then from behavioral cognition to behavioral intention.

Online Health Information Seeking Among Patients With Chronic Conditions: Integrating the Health Belief Model and Social Support Theory

BACKGROUND

Chronic diseases are the leading causes of death and disability. With the growing patient population and climbing health care expenditures, researchers and policy makers are seeking new approaches to improve the accessibility of health information on chronic diseases while lowering costs. Online health information sources can play a substantial role in effective patient education and health communication. However, some contradictory evidence suggests that patients with chronic conditions may not necessarily seek online health information.

OBJECTIVE

This study aims to integrate 2 theories (ie, the health belief model and social support theory) and a critical health literacy perspective to understand online health information seeking (OHIS) among patients with chronic conditions.

METHODS

We used the survey method to collect data from online chronic disease communities and groups on social media platforms. Eligible participants were consumers with at least 1 chronic condition and those who have experience with OHIS. A total of 390 valid questionnaires were collected. The partial least squares approach to structural equation modeling was employed to analyze the data.

RESULTS

The results suggested that perceived risk (t=3.989, P<.001) and perceived benefits (t=3.632, P<.001) significantly affected patients' OHIS. Perceived susceptibility (t=7.743, P<.001) and perceived severity (t=8.852, P<.001) were found to influence the perceived risk of chronic diseases significantly. Informational support (t=5.761, P<.001) and emotional support (t=5.748, P<.001) also impacted the perceived benefits of online sources for patients. In addition, moderation analysis showed that critical health literacy significantly moderated the link between perceived risk and OHIS (t=3.097, P=.002) but not the relationship between perceived benefits and OHIS (t=0.288, P=.774).

CONCLUSIONS

This study shows that the health belief model, when combined with social support theory, can predict patients' OHIS. The perceived susceptibility and severity can effectively explain perceived risk, further predicting patients' OHIS. Informational support and emotional support can contribute to perceived benefits, thereby positively affecting patients' OHIS. This study also demonstrated the important negative moderating effects of critical health literacy on the association between perceived risk and OHIS.

The Influence of Message Framing on Elderly Tourists' Purchase Intentions of Health Services: A Case Study of Guangxi Bama

Traveling has become an increasingly important lifestyle for the elderly to realize active aging. The elderly are more inclined to pay attention to wellbeing-related products whilst on vacations, representing a market opportunity for providers of tourism health services. This study conducted an experiment to explore how message framing affects intentions to purchase health services in elderly tourists over the age of 59 years. A total of 216 elderly tourists from Bama, a famous wellness tourism destination in China, were recruited as participants for a single-factor (message framing: positive versus negative) experiment. Our results indicate the following: (1) message framing has a significant impact on elderly tourists' intentions to purchase health services. Compared with messages that are negatively framed, positive messages are more persuasive. (2) Perceived benefits mediate the above relationship. (3) Perceived susceptibility moderates the impact of message framing around perceived benefits, as well as the indirect effect of perceived benefits on purchase intention. Theoretically, this paper clarifies the mechanism and conditions of message framing in relation to its effects on consumer intentions, enriching knowledge about the intersection between tourism and health consumption. This paper also provides guidance for providers of health tourism who are seeking to capture the market of elderly tourists.

Effects of personalization and source expertise on users' health beliefs and usage intention toward health chatbots: Evidence from an online experiment

Objective

Based on the heuristic–systematic model (HSM) and health belief model (HBM), this study aims to investigate how personalization and source expertise in responses from a health chatbot influence users’ health belief-related factors (i.e. perceived benefits, self-efficacy and privacy concerns) as well as usage intention.

Methods

A 2 (personalization vs. non-personalization) × 2 (source expertise vs. non-source expertise) online between-subject experiment was designed. Participants were recruited in China between April and May 2021. Data from 260 valid observations were used for the data analysis.

Results

Source expertise moderated the effects of personalization on health belief factors. Perceived benefits and self-efficacy mediated the relationship between personalization and usage intention when the source expertise cue was presented. However, the privacy concerns were not influenced by personalization and source expertise and did not significantly affect usage intention toward the health chatbot.

Discussion

This study verified that in the health chatbot context, source expertise as a heuristic cue may be a necessary condition for effects of the systematic cue (i.e. personalization), which supports the HSM's arguments. By introducing the HBM in the chatbot experiment, this study is expected to provide new insights into the acceptance of healthcare AI consulting services.

Health information seeking and sharing behavior of young adults on social media in Pakistan

Social media such as Facebook, YouTube, WhatsApp, and Twitter have radically enhanced the public access to health information. Still, studies have unexplored the factors that contribute toward such behaviors especially in developing countries. Therefore, this study identifies the factors that contribute to the likelihood of young adults’ health information seeking and sharing on social media. Specifically, drawing upon health belief model (HBM), the study attempts to understand how health belief and e-Health literacy affects health information seeking and sharing on social media. The study collected data from 413 young adults through Google Forms on a random basis. The results generated applying structural equation modeling confirmed that HBM related factors such as perceived susceptibility, perceived severity and perceived benefits positively while perceived barriers negatively influence young adults’ health information seeking and sharing intentions on social media. Furthermore, e-Health literacy was positively associated with health information seeking and sharing intentions on social media. This study is amongst a first few studies in the context of developing world to investigate the young adults’ intentions of seeking and sharing health information on social media based on HBM.

A multi-method analytical approach to predicting young adults' intention to invest in mHealth during the COVID-19 pandemic

Mobile-based health (mHealth) systems are proving to be a popular alternative to the traditional visits to healthcare providers. They can also be useful and effective in fighting the spread of infectious diseases, such as the COVID-19 pandemic. Even though young adults are the most prevalent mHealth user group, the relevant literature has overlooked their intention to invest in and use mHealth services. This study aims to investigate the predictors that influence young adults' intention to invest in mHealth (IINmH), particularly during the COVID-19 crisis, by designing a research methodology that incorporates both the health belief model (HBM) and the expectation-confirmation model (ECM). As an expansion of the integrated HBM-ECM model, this study proposes two additional predictors: mobile Internet speed and mobile Internet cost. A multi-method analytical approach, including partial least squares structural equation modelling (PLS-SEM), fuzzy-set qualitative comparative analysis (fsQCA), and machine learning (ML), was utilised together with a sample dataset of 558 respondents. The dataset-about young adults in Bangladesh with an experience of using mHealth-was obtained through a structured questionnaire to examine the complex causal relationships of the integrated model. The findings from PLS-SEM indicate that value-for-money, mobile Internet cost, health motivation, and confirmation of services all have a substantial impact on young adults' IINmH during the COVID-19 pandemic. At the same time, the fsQCA results indicate that a combination of predictors, instead of any individual predictor, had a significant impact on predicting IINmH. Among ML methods, the XGBoost classifier outperformed other classifiers in predicting the IINmH, which was then used to perform sensitivity analysis to determine the relevance of features. We expect this multi-method analytical approach to make a significant contribution to the mHealth domain as well as the broad information systems literature.

COVID-19 complications and entrepreneurial intention among the entrepreneurs of Pakistan: evidence from the second wave of the pandemic

Purpose

At present, nearly the whole globe is facing a severe threat of COVID-19. This study aims to examine the COVID-19 complications and entrepreneurial intention among the entrepreneurs of Pakistan.

Design/methodology/approach

The study used a deductive approach. An online survey is conducted to collect cross-sectional data from entrepreneurs of Pakistan. Convenience sampling is applied to target the respondents. In total, 278 usable answers proceed for final analysis. The structural equation model (SEM) is used to infer the results.

Findings

The findings of the study highlight a significant negative effect of fear of COVID-19 (FO19), perceived susceptibility (PSU) and perceived severity (PSE) on entrepreneurial intention (EI) among the entrepreneurs.

Practical implications

The study would provide the guidelines for policymakers and planners to combat the barriers of fear, PSU and PSE during a pandemic. The findings of the second wave of COVID-19 may provide a warning to the government to take preventive measures to face the severe effect of the pandemic. Finally, the outcomes of the study may enrich the depth of COVID-19 literature globally.

Originality/value

This study is the first study highlighting factors such as fear, PSU and PSE toward EI in COVID-19 second wave.

Introducing an Integrated Model of Adults' Wearable Activity Tracker Use and Obesity Information-Seeking Behaviors From a National Quota Sample Survey

BACKGROUND

Research from multiple perspectives to investigate adults' use of wearable activity-tracking devices is limited. We offer a multiperspective model and provide empirical evidence of what leads to frequent usage of wearable health technologies from a large, nationally representative survey sample.

OBJECTIVE

This study aims to explore factors affecting the use of wearable activity-tracking devices among health consumers from the perspectives of individual health beliefs (perceived severity, perceived susceptibility, perceived benefits, and self-efficacy) and information-seeking behaviors.

METHODS

Our Integrated Model of Wearable Activity Tracker (IMWAT) use and proposed hypotheses were validated and tested with data collected from a telephone survey with a national quota sample. The data were analyzed using a variety of statistical techniques, including structural equation analysis.

RESULTS

The sample comprised 2006 participants. Our results showed that the perceived benefits of physical activity, perceived susceptibility, and self-efficacy toward obesity were significant predictors of information-seeking behaviors, which, in turn, mediated their effects on the use of wearable activity trackers. Perceptions of obesity severity directly promoted wearable device usage.

CONCLUSIONS

This study provided a new and powerful theoretical model that combined the health beliefs and information-seeking behaviors behind the use of wearable activity trackers in the adult population. The findings provide meaningful implications for developers and designers of wearable health technology products and will assist health informatics practitioners and obesity prevention communicators.

A model of digital health communication media use during the Covid-19 pandemic

Purpose

This research aims to develop and test a model of digital health communication media (DHCM) use for healthy food information – DHCM usage – during the Covid-19 pandemic. More specifically, this research investigated the simultaneous effects of perceived threat of Covid-19, e-health literacy, attitude toward DHCM usage, knowledge toward DHCM usage, facilitating conditions and information quality on the DHCM usage.

Design/methodology/approach

The empirical data were collected through a survey. The respondents of the survey are 192 DHCM users who lived in Tangerang Regency. Structural equation modelling (SEM) analysis was performed.

Findings

The DHCM usage during the Covid-19 pandemic is significantly affected by the attitude towards the DHCM usage and the facilitating conditions. However, the DHCM usage during the Covid-19 pandemic is not significantly affected by the perceived threat of Covid-19, e-health literacy, information quality and knowledge of the DHCM usage.

Research limitations/implications

This research was conducted only in Tangerang Regency and employed a purposive sampling technique. Future research should be conducted in other contexts to examine the stability of the research findings.

Practical implications

In order to improve DHCM usage for healthy food information, it is important for building a positive attitude towards DHCM usage and ensuring the availability of the facilitating conditions.

Originality/value

This paper is the first that develops and tests a model of DHCM usage for healthy food information during the Covid-19 pandemic.

Can we trust AI? An empirical investigation of trust requirements and guide to successful AI adoption

Purpose

Artificial intelligence (AI) fosters economic growth and opens up new directions for innovation. However, the diffusion of AI proceeds very slowly and falls behind, especially in comparison to other technologies. An important path leading to better adoption rates identified is trust-building. Particular requirements for trust and their relevance for AI adoption are currently insufficiently addressed.

Design/methodology/approach

To close this gap, the authors follow a qualitative approach, drawing on the extended valence framework by assessing semi-structured interviews with experts from various companies.

Findings

The authors contribute to research by finding several subcategories for the three main trust dimensions ability, integrity and benevolence, thereby revealing fundamental differences for building trust in AI compared to more traditional technologies. In particular, the authors find access to knowledge, transparency, explainability, certification, as well as self-imposed standards and guidelines to be important factors that increase overall trust in AI.

Originality/value

The results show how the valence framework needs to be elaborated to become applicable to the AI context and provide further structural orientation to better understand AI adoption intentions. This may help decision-makers to identify further requirements or strategies to increase overall trust in their AI products, creating competitive and operational advantage.

Factors Affecting Public Adoption of COVID-19 Prevention and Treatment Information During an Infodemic: Cross-sectional Survey Study

BACKGROUND

With the spread of COVID-19, an infodemic is also emerging. In public health emergencies, the use of information to enable disease prevention and treatment is incredibly important. Although both the information adoption model (IAM) and health belief model (HBM) have their own merits, they only focus on information or public influence factors, respectively, to explain the public's intention to adopt online prevention and treatment information.

OBJECTIVE

The aim of this study was to fill this gap by using a combination of the IAM and the HBM as the framework for exploring the influencing factors and paths in public health events that affect the public's adoption of online health information and health behaviors, focusing on both objective and subjective factors.

METHODS

We carried out an online survey to collect responses from participants in China (N=501). Structural equation modeling was used to evaluate items, and confirmatory factor analysis was used to calculate construct reliability and validity. The goodness of fit of the model and mediation effects were analyzed.

RESULTS

The overall fitness indices for the model developed in this study indicated an acceptable fit. Adoption intention was predicted by information characteristics (β=.266, P<.001) and perceived usefulness (β=.565, P<.001), which jointly explained nearly 67% of the adoption intention variance. Information characteristics (β=.244, P<.001), perceived drawbacks (β=-.097, P=.002), perceived benefits (β=.512, P<.001), and self-efficacy (β=.141, P<.001) jointly determined perceived usefulness and explained about 81% of the variance of perceived usefulness. However, social influence did not have a statistically significant impact on perceived usefulness, and self-efficacy did not significantly influence adoption intention directly.

CONCLUSIONS

By integrating IAM and HBM, this study provided the insight and understanding that perceived usefulness and adoption intention of online health information could be influenced by information characteristics, people's perceptions of information drawbacks and benefits, and self-efficacy. Moreover, people also exhibited proactive behavior rather than reactive behavior to adopt information. Thus, we should consider these factors when helping the informed public obtain useful information via two approaches: one is to improve the quality of government-based and other official information, and the other is to improve the public's capacity to obtain information, in order to promote truth and fight rumors. This will, in turn, contribute to saving lives as the pandemic continues to unfold and run its course.

Re-Examining the Impact of Multidimensional Trust on Patients' Online Medical Consultation Service Continuance Decision

Recent years have witnessed the rapid growth of an emerging digital healthcare service - online medical consultation (OMC). Despite its popularity, many OMC platforms have encountered issues in initial adoption and continuance use among patients. We posit that many of the hesitation and resistance may arise from a lack of trust toward OMC, which is a complex phenomenon that involves both interpersonal and technological-oriented considerations. This study seeks to clarify the conceptualization of online trust in the context of OMC. It compares two plausible explanations (i.e., trust as a direct cause vs. trust as a moderator) regarding how interpersonal and technological trust contributes to the service continuance decision in OMC. By contextualizing the valence framework, we identify the critical factors in making the risk-benefit assessment of patients' OMC decision. We conduct an online survey of 365 experienced OMC users and analyze our structural model using a partial least square approach. Our results show that the multidimensional conceptualization approach, which incorporates both interpersonal and technological aspects of trust, is superior to the unitary approach. Besides, our findings suggest that the role trust plays in determining service continuance decisions in OMC is more of a direct cause than a qualifier that buffers the impacts of risk-benefit evaluation. We believe the findings can help both researchers and practitioners recognize the multidimensional perspective of trust and better understand the role trust plays in OMC and other online healthcare delivery problems.

How technology impacts communication between cancer patients and their health care providers: A systematic literature review

OBJECTIVE

To ensure the well-being of their patients, health care providers (HCPs) are putting more effort into the quality of the communication they provide in oncology clinics. With the emergence of Health Information Technology (HIT), the dynamics between doctors and patients in oncology settings have changed. The purpose of this literature review is to explore and demonstrate how various health information technologies impact doctor-patient communication in oncology settings.

METHOD

A systematic literature review was conducted in 4 databases (PubMed, Cochrane, Web of Science, IEEE Xplore) to select publications that are in English, published between January 2009 and September 2020. This review reports outcomes related to the impacts of using health information technologies on doctor-patient communication according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Reviews and Meta-Analysis guidelines (PRISMA).

RESULTS

We identified 31 studies which satisfied the selection and eligibility criteria. The review revealed a diverse range of HIT used to support communication between cancer patients and their HCPs in oncology settings. Outcomes related to communication were examined to demonstrate how technology can improve access to care in clinical settings and online. When technology is used effectively to support patient knowledge and shared understanding, this increases the patient's satisfaction and ability to manage emotions, make decisions, and progress in their treatment, in addition to increasing social support and building a stronger therapeutic alliance based on shared knowledge and transparency between clinicians and patients.

CONCLUSION

Technology-based solutions can help strengthen the relationship and communication between patients and their doctors. They can empower the patient's well-being, help doctors make better decisions and enhance the therapeutic alliance between them. Thus, using technology to enhance communication in healthcare settings remains beneficial if its use is structured and target oriented. Future studies should focus on comparing in-depth the difference between outpatient and inpatient settings in terms of the efforts required and the extent of the impacts from both clinicians' and cancer patients' perspectives.

Health Information behaviour during COVID-19 outbreak among Egyptian library and information science undergraduate students

Health information shared on the Internet has the potential to improve people’s quality of life. However, the level of health information literacy and informational skills determines the individuals’ ability to obtain credible health information useful for them. This study investigates the Egyptian LIS undergraduates’ health information behaviour during the COVID-19 pandemic. The study has adopted a quantitative approach using a questionnaire to explore library and information science undergraduates’ health information behaviour. A sample of 161 students answered a questionnaire. The data were analysed using SPSS software. The study results show that official health websites, social media, and family and friends are the primary sources for health information for the participants. The findings also revealed that the sample has adequate health information skills, though many of the participants still need to raise their information literacy skills. Information credibility and personal beliefs were found to affect the participants’ decision to share health information on the Internet. One of the limitations of the study is that the sample selected in this study was LIS students who are trained to find reliable information as part of their education. Findings may be different for the “average” student. Furthermore, the questionnaire was distributed in one university, which means that the results cannot be generalised in other LIS departments using different courses. Therefore, more studies need to be conducted in other LIS departments with different course plans as they may produce different results. This study explores the health information behaviour of LIS undergraduates during the COVID-19 pandemic. The current study results may help develop the course plan in many LIS departments in Egypt and the Middle East, which would help improve the students’ health information literacy.

Internet users beware, you follow online health rumors (more than counter-rumors) irrespective of risk propensity and prior endorsement

Purpose

The Internet is a breeding ground for rumors. A way to tackle the problem involves the use of counter-rumor messages that refute rumors. This paper analyzes users' intention to follow rumors and counter-rumors as a function of two factors: individuals' risk propensity and messages' prior endorsement.

Design/methodology/approach

The paper conducted an online experiment. Complete responses from 134 participants were analyzed statistically.

Findings

Risk-seeking users were keener to follow counter-rumors compared with risk-averse ones. No difference was detected in terms of their intention to follow rumors. Users' intention to follow rumors always exceeded their intention to follow counter-rumors regardless of whether prior endorsement was low or high.

Research limitations/implications

This paper contributes to the scholarly understanding of people's behavioral responses when, unknowingly, exposed to rumors and counter-rumors on the Internet. Moreover, it dovetails the literature by examining how risk-averse and risk-seeking individuals differ in terms of intention to follow rumors and counter-rumors. It also shows how prior endorsement of such messages drives their likelihood to be followed.

Originality/value

The paper explores the hitherto elusive question: When users are unknowingly exposed to both a rumor and its counter-rumor, which entry is likely to be followed more than the other? It also takes into consideration the roles played by individuals' risk propensity and messages' prior endorsement.

Factors influencing intention to follow the “stay at home” policy during the COVID-19 pandemic

Purpose

This research seeks to simultaneously test the effect of attitude towards the behavior of following the “Stay at Home” policy, subjective norm, perceived behavioral control, perceived susceptibility and perceived severity on people's intention to follow the “Stay at Home” policy during COVID-19 pandemic.

Design/methodology/approach

The data were collected through an online survey with 148 respondents in the Greater Area of Jakarta, Indonesia. The data were then analyzed using multiple regressions.

Findings

The findings show that attitude towards the behavior, subjective norm and perceived behavioral control positively and significantly affect intention to follow “Stay at Home” during the COVID-19 pandemic. However, perceived susceptibility and perceived severity of COVID-19 do not significantly influence the intention to follow “Stay at Home” during the COVID-19 pandemic.

Research limitations/implications

This research was limited to the Greater Area of Jakarta, Indonesia. Furthermore, sampling was done through convenience sampling. Therefore, future research should be conducted in a different context to test the generalization of this research's findings.

Practical implications

To encourage citizens' adherence to the stay-at-home policy during the COVID-19 pandemic, they must be directed to have positive attitudes toward the policy. Financial and non-financial supports are critical to ensure citizens' ability to sufficiently observe the policy sufficiently. Another important aspect is the influence of leaders and public figures to consistently call for obedience consistently.

Originality/value

This is the first research that studies citizens' behavior related to the “Stay at Home” policy requisitioned by the government to hinder the spread of COVID-19.

An empirical investigation of the utilitarian, social benefits in LBS information disclosure-The moderating effect of the gender based social role theory

•

Locatability, personalization and social benefit affect information disclosure intention.

•

Locatability shows the greatest impact on information disclosure intention in LBS.

•

Locatability and personalization are more important for female users in predicting information disclosure intention.

•

Social benefit has a more salient effect on information disclosure intention for male users than female users.

The prior studies on information disclosure in location-based services (LBS) suggested that the perceived benefits of information disclosure in LBS were manifested by three benefits, namely, locatability, personalization, and social benefits. The three benefits might affect information disclosure intention differently. As an extension, individual factors, such as gender, may affect the relationship. However, according to literature, little research has investigated on the combined influence of the three benefits on the information disclosure intention in LBS with the gender as a moderator. Based upon the self-determination and social role theories, this study intends to bridge the gap empirically. The hypotheses are largely supported by 215 respondents. Unexpectedly, the research findings show that for females, locatability and personalization are more important in predicting their information disclosure intention, whereas for males, the social benefit has more of an impact on information disclosure intention, which is opposite to the hypotheses and convention. Furthermore, the research findings indicate that the behaviors of males and females may conform to the roles distributed within a society of this information age rather than to the personalities of the individuals. Finally, the implications are presented.

Factors Influencing the Adoption of Online Health Consultation Services: The Role of Subjective Norm, Trust, Perceived Benefit, and Offline Habit

The cyberspace plays an important role in improving the quality, equity, and efficiency of health services. Studying people's adoption of online health services, such as online health consultation services (OHCS) can benefit both industry and policy in the health service sector. This paper investigates influencing factors and paths of people's intention of adopting OHCS by employing the extended valence framework, with our new contribution of integrating subjective norm and offline habit into the model. Five hundred forty-three university students participated in the survey. Structural equation models and Sobel-Goodman tests were applied to test the models. The results show that subjective norm (β = 0.077, p = 0.041), trust in providers (β = 0.194, p = 0.002) and perceived benefit (β = 0.463, p < 0.001) positively affect the intention to adopt OHCS, while offline habit (β = -0.111, p = 0.026) has a negative effect. However, the association of perceived risk (β = -0.062, p = 0.315) and adoption is not supported. Moreover, trust in providers plays a mediating role between subjective norm and the intention of adopting, while perceived benefit mediates the relationship between trust in providers and the intention of adopting. This study highlights the importance of trust, subjective norm, perceived benefit, and persisting habits in promoting the adoption of OHCS.

Exploring the Determinants of Online Health Information-Seeking Behavior Using a Meta-Analytic Approach

Although key factors of online health information-seeking behavior (OHISB), such as self-efficacy, Internet experience, and perceived ease of use, are analyzed in many studies, the research results are controversial. The purpose of this meta-analysis, based on 27 related empirical studies, is to explore the determinants of OHISB. The determinants of OHISB are classified into four categories: demographic characteristic factors, cognitive factors, internal factors, and external factors. According to the results of the analysis using Stata13.0, our study found a weak effect of perceived cost and health anxiety on the OHISB, while subjective norm, perceived usefulness, and attitude have a strong positive effect on the OHISB. Understanding the determinants of OHISB is beneficial in order to know why users utilize online health applications. The findings of the study can contribute to developing and extending the existing theoretical concepts.