Consumer health information needs: A systematic review of measures

Pian, Wenjing; Song, Shijie; Zhang, Yan

doi:10.1016/j.ipm.2019.102077

Cited by 82 publications

(65 citation statements)

References 46 publications

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“…Such knowledge can help them make informed health-related decisions, including healthcare services selection, disease prevention, and health promotion ( Fu, Chen, & Zheng, 2020 ; Nutbeam, 2000 ). Prior research also indicates that users who have high health literacy are more likely to share health information with others (e.g., Crook, Stephens, Pastorek, Mackert, & Donovan, 2016 ; Pian, Song, & Zhang, 2020 ). This is perhaps because those who hold high health literacy can recognize and articulate their health information needs and thus know how to share the health information with others effectively.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In brief, high online information literacy requires that users should possess a high self-efficacy for using digital technologies and essential online information-search skills. Otherwise, even though someone knows how to recognize and articulate their health information needs, he or she might not obtain prompt online healthcare services due to a lack of the ability to access online health information resources ( Pian, Song, & Zhang, 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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Promoting users’ intention to share online health articles on social media: The role of confirmation bias

Zhao

Chen

2020

Information Processing & Management

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Highlights Users with a high level of eHealth literacy are more likely to share positive health articles when they have extreme confirmation bias. Users with a high level of eHealth literacy are more likely to share negative health articles when they have moderate confirmation bias or no confirmation bias. Users with a low level of eHealth literacy are more likely to share health articles regardless of positive or negative content valence when they have moderate positive confirmation bias.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Promoting users’ intention to share online health articles on social media: The role of confirmation bias

Zhao

Chen

2020

Information Processing & Management

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“…Extant studies consensus on the use of informational and emotional dimensions to depict the communication processes between doctors and patients [1,17,38]. Informational-oriented communication, also termed as task-focused communication [38,39], refers to communication on medical information provision and interpretation. To be more specific, the informational communication can be divided into information providing and information interpreting [14,40].…”

Section: A Computer-mediated Communication Perspective On Poor Dprmentioning

confidence: 99%

The Antecedents of Poor Doctor-Patient Relationship in Mobile Consultation: A Perspective from Computer-Mediated Communication

Yan

Tan

Jia

et al. 2020

IJERPH

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This study aims to understand the underlying reasons for poor doctor-patient relationships (DPR). While extant studies on antecedents of poor DPR mainly focus on the offline context and often adopt the patients' perspective, this work focuses on the mobile context and take both doctors' and mobile consultation users' perspectives into consideration. To fulfill this purpose, we first construct a theoretical framework based on the Computer-Mediated Communication (CMC) literature. Then we coded 592 doctor-user communication records to validate and elaborate the proposed theoretical model. This work reveals that characteristics of mobile technologies pose potential challenges on both doctors' and patients' information providing, informative interpreting, and relationship maintaining behaviors, resulting in 10 and 6 types of inappropriate behaviors of doctors and users, respectively, that trigger poor DPR in the mobile context. The findings enrich the research on online DPR and provide insights for improving DPR in the mobile context. Extant research on mobile healthcare service is emerging, but studies that aim at uncovering the underlying reasons for poor DPRs in the mobile context are still lacking. The majority of previous research tends to focus on the positive experience brought about by mobile healthcare services, such as user satisfaction [10] and the adoption or continuous usage of mobile technology [3,11]. However, the experience of dissatisfied participants is largely ignored. The negative experience is also worth noting because understanding the complaints guide practitioners to improve service quality [8]. Although a few studies have paid attention to the dissatisfying experience of mobile healthcare services, they tend to interpret the experience only from the perspective of users [8,12]. While these studies are insightful, a single perspective from users is not adequate, because they missed the perception of doctors which is considered quite different from that of users [13,14].These two literature gaps (namely lacking studies on dissatisfying experience of mobile healthcare services and lacking dual perspectives from both users and doctors) might partly be attributed to the mainstream research method in the healthcare field. Most studies rely on questionnaires and interviews to collect subjective ratings about mobile healthcare services, such as Akter et al. (2013) [15], Deng et al. (2015) [16], and Wu et al. (2018) [17]. The collected responses are usually inaccurate since respondents are rating events that happened at an earlier time. Besides, it is difficult to match responses from doctors and patients via questionnaires.This work aims to uncover the underlying reasons for poor DPR from dual perspectives of both doctors and users in mobile medical consultation service. To achieve our goals, we first reviewed the literature on Computer-Mediated Communication (hereafter, CMC) in search of theoretical accounts for the poor DPR in the mobile context. The CMC literature focuses on the influence of the fe...

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“…And, how does information overload affect information behavior in the COVID-19 context? Further, it has been suggested to conduct context-specific inquiries (such as type of disease, setting, and user groups) to understand health-related information-seeking behavior ( Pian, Song, & Zhang, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

From information seeking to information avoidance: Understanding the health information behavior during a global health crisis

Soroya

Farooq

Mahmood

et al. 2021

Information Processing & Management

363

276

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Highlights The study examines the factors leading to information avoidance during COVID-19 pandemic. Mass Media, Print Media and official websites are used for information seeking during the pandemic. Only Social Media exposure results in information overload and information anxiety. Information overload is strongly associated with information anxiety which gives rise to information avoidance. We extend the applicability of S-O-R model to the information behavior domain, especially during the uncertain times.

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Consumer health information needs: A systematic review of measures

Cited by 82 publications

References 46 publications

Promoting users’ intention to share online health articles on social media: The role of confirmation bias

Promoting users’ intention to share online health articles on social media: The role of confirmation bias

The Antecedents of Poor Doctor-Patient Relationship in Mobile Consultation: A Perspective from Computer-Mediated Communication

From information seeking to information avoidance: Understanding the health information behavior during a global health crisis

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