Patients’ Willingness to Share Information in Online Patient Communities: Questionnaire Study

Zhu, Panpan; Shen, Jiang; Xu, Man

doi:10.2196/16546

Cited by 17 publications

(22 citation statements)

References 47 publications

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“…Although the P value is at the .1 level, the negative effect of information support on the privacy concerns is a valuable finding that supports the hypotheses [79]. However, we find that emotional support has no direct moderation effect on either privacy concerns or health information disclosure intention.…”

Section: Resultssupporting

confidence: 66%

“…Furthermore, informational support will have a negative moderation effect on the relationship between privacy concerns and health information disclosure (beta path coefficient –0.105, P =.092). Although the P value is at the .1 level, the negative effect of information support on the privacy concerns is a valuable finding that supports the hypotheses [ 79 ]. However, we find that emotional support has no direct moderation effect on either privacy concerns or health information disclosure intention.…”

Section: Resultsmentioning

confidence: 56%

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Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support

Dang¹,

Guo²,

Guo³

et al. 2021

JMIR Mhealth Uhealth

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Background Mobile health (mHealth) provides a new opportunity for disease prediction and patient health self-management. However, privacy problems in mHealth have drawn significant attention to patients’ online health information disclosure and to the possibility that privacy concerns may hinder mHealth development. Objective Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a rational and linear decision-making process. However, cognitive behavior processes are complex and mutual. In an attempt to gain a fuller understanding of information disclosure behavior, we further optimize a PCT-based information disclosure model by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proven to be a distinct and significant disclosure benefit of mHealth, was chosen as the representative benefit of information disclosure. Methods We examine a structural equation model that incorporates privacy concerns, health information disclosure intention in mHealth, and social support from mHealth, all at the individual level. Results A validated questionnaire was completed by 253 randomly selected participants. The result indicated that perceived health information sensitivity positively enhances patients’ privacy concern (beta path coefficient 0.505, P<.001), and higher privacy concern levels will decrease their health information disclosure intention (beta path coefficient –0.338, P<.001). Various individual characteristics influence perceived health information sensitivity in different ways. One dimension of social support, informational support, negatively moderates the effect of the relationship between perceived health information sensitivity and privacy concerns (beta path coefficient –0.171, P=.092) and the effect of the relationship between privacy concerns and health information disclosure intention (beta path coefficient –0.105, P=.092). However, another dimension, emotional support, has no direct moderation effect on the relationship between privacy concerns and health information disclosure intention. Conclusions The results indicate that social support can be regarded as a disutility reducer. That is, on the one hand, it reduces patients’ privacy concerns; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderation effect of social support is partially supported. Informational support, one dimension of social support, is significant (beta path coefficient –0.171, P=.092), while the other dimension, emotional support, is not significant (beta path coefficient –0.137, P=.146), in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.

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Section: Resultssupporting

confidence: 66%

Section: Resultsmentioning

confidence: 56%

Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support

Dang¹,

Guo²,

Guo³

et al. 2021

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…14 Despite the potential benefits of sharing self-generated health and lifestyle data with others, a number of barriers have been identified that prevent the acceptance of these data-sharing practices. For instance, as electronic health data become increasingly integrated into healthcare systems, there is an increased potential for privacy breaches and misrepresentation, negatively influencing end-user trust 20 In this research we will discuss concerns surrounding concepts of Trust, Identity, Privacy and Security (TIPS) adopted from research into privacy and security perspectives. 21 TIPS concerns play an important role in facilitating sharing of health data via technology applications.…”

Section: Introductionmentioning

confidence: 99%

Collecting and sharing self-generated health and lifestyle data: Understanding barriers for people living with long-term health conditions – a survey study

et al. 2022

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Background The growing popularity of collecting self-generated health and lifestyle data presents a valuable opportunity to develop our understanding of long-term health conditions and improve care. Barriers remain to the effective sharing of health and lifestyle data by those living with long-term health conditions which include beliefs around concepts of Trust, Identity, Privacy and Security, experiences of stigma, perceptions of risk and information sensitivity. Method We surveyed 250 UK adults who reported living with a range of long-term health conditions. We recorded data to assess self-reported behaviours, experiences, attitudes and motivations relevant to sharing self-generated health and lifestyle data. We also asked participants about their beliefs about Trust, Identity, Privacy and Security, stigma, and perceptions of risk and information sensitivity regarding their health and lifestyle data. Results Three-quarters of our sample reported recording information about their health and lifestyle on a daily basis. However, two-thirds reported never or rarely sharing this information with others. Trust, Identity, Privacy and Security concerns were considered to be ‘very important’ by those with long-term health conditions when deciding whether or not to share self-generated health and lifestyle data with others, with security concerns considered most important. Of those living with a long-term health condition, 58% reported experiencing stigma associated with their condition. The greatest perceived risk from sharing with others was the potential for future harm to their social relationships. Conclusions Our findings suggest that, in order for health professionals and researchers to benefit from the increased prevalence of self-generated health and lifestyle data, more can be done to address security concerns and to understand perceived risks associated with data sharing. Digital platforms aimed at facilitating the sharing of self-generated health and lifestyle data may look to highlight security features, enable users to control the sharing of certain information types, and emphasise the practical benefits to users of sharing health and lifestyle data with others.

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“…Health information sharing is one of the most important aspects in the research area of information sharing. Zhu et al [ 9 ] established an influencing factor model of patients’ willingness to share health information. The model includes variables of privacy concerns, online information support, information sensitivity, and disease severity.…”

Section: Introductionmentioning

confidence: 99%

Users’ Willingness to Share Health Information in a Social Question-and-Answer Community: Cross-sectional Survey in China

Li¹,

Lin²,

Tang³

et al. 2021

JMIR Med Inform

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Background Social question-and-answer communities play an increasingly important role in the dissemination of health information. It is important to identify influencing factors of user willingness to share health information to improve public health literacy. Objective This study explored influencing factors of social question-and-answer community users who share health information to provide reference for the construction of a high-quality health information sharing community. Methods A cross-sectional study was conducted through snowball sampling of 185 participants who are Zhihu users in China. A structural equation analysis was used to verify the interaction and influence of the strength between variables in the model. Hierarchical regression was also used to test the mediating effect in the model. Results Altruism (β=.264, P<.001), intrinsic reward (β=.260, P=.03), self-efficacy (β=.468, P<.001), and community influence (β=.277, P=.003) had a positive effect on users’ willingness to share health information (WSHI). By contrast, extrinsic reward (β=−0.351, P<.001) had a negative effect. Self-efficacy also had a mediating effect (β=.147, 29.15%, 0.147/0.505) between community influence and WSHI. Conclusions The findings suggest that users’ WSHI is influenced by many factors including altruism, self-efficacy, community influence, and intrinsic reward. Improving the social atmosphere of the platform is an effective method of encouraging users to share health information.

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Patients’ Willingness to Share Information in Online Patient Communities: Questionnaire Study

Cited by 17 publications

References 47 publications

Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support

Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support

Collecting and sharing self-generated health and lifestyle data: Understanding barriers for people living with long-term health conditions – a survey study

Users’ Willingness to Share Health Information in a Social Question-and-Answer Community: Cross-sectional Survey in China

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