Dataset Information

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

ABSTRACT:

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.

SUBMITTER: Dang Y

PROVIDER: S-EPMC7899802 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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Publications

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

Dang Yuanyuan Y Guo Shanshan S Guo Xitong X Wang Mohan M Xie Kexin K

JMIR mHealth and uHealth 20210208 2

<h4>Background</h4>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.<h4>Objective</h4>Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a rational and linear ...[more]

PMID: 33555266

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Project description:BackgroundHealth care providers are driven by greater participation and systemic cost savings irrespective of benefits to individual patients derived from sharing Personal Health Information (PHI). Protecting PHI is a critical issue in the sharing of health care information systems; yet, there is very little literature examining the topic of sharing PHI electronically. A good overview of the regulatory, privacy, and societal barriers to sharing PHI can be found in the 2009 Health Information Technology for Economic and Clinical Health Act.ObjectiveThis study investigated the factors that influence individuals' intentions to share their PHI electronically with health care providers, creating an understanding of how we can represent a patient's interests more accurately in sharing settings, instead of treating patients like predetermined subjects. Unlike privacy concern and trust, patient activation is a stable trait that is not subject to change in the short term and, thus, is a useful factor in predicting sharing behavior. We apply the extended privacy model in the health information sharing context and adapt this model to include patient activation and issue involvement to predict individuals' intentions.MethodsThis was a survey-based study with 1600+ participants using the Health Information National Trends Survey (HINTS) data to validate a model through various statistical techniques. The research method included an assessment of both the measurement and structural models with post hoc analysis.ResultsWe find that privacy concern has the most influence on individuals' intentions to share. Patient activation, issue involvement, and patient-physician relationship are significant predictors of sharing intention. We contribute to theory by introducing patient activation and issue involvement as proxies for personal interest factors in the health care context.ConclusionsOverall, this study found that although patients are open to sharing their PHI, they still have concerns over the privacy of their PHI during the sharing process. It is paramount to address this factor to increase information flow and identify how patients can assure that their privacy is protected. The outcome of this study is a set of recommendations for motivating the sharing of PHI. The goal of this research is to increase the health profile of the patients by integrating the testing and diagnoses of various doctors across health care providers and, thus, bring patients closer to the physicians.

Project description:BackgroundComplying with individual privacy perceptions is essential when processing personal information for research. Our specific research area is performance development of elite athletes, wherein nutritional aspects are important. Before adopting new automated tools that capture such data, it is crucial to understand and address the privacy concerns of the research subjects that are to be studied. Privacy as contextual integrity emphasizes understanding contextual sensitivity in an information flow. In this study, we explore privacy perceptions in image-based dietary assessments. This research field lacks empirical evidence on what will be considered as privacy violations when exploring trends in long-running studies. Prior studies have only classified images as either private or public depending on their basic content. An assessment and analysis are thus needed to prevent unwanted consequences of privacy breach and other issues perceived as sensitive when designing systems for dietary assessment by using food images.ObjectiveThe aim of this study was to investigate common perceptions of computer systems using food images for dietary assessment. The study delves into perceived risks and data-sharing behaviors.MethodsWe investigated the privacy perceptions of 105 individuals by using a web-based survey. We analyzed these perceptions along with perceived risks in sharing dietary information with third parties.ResultsWe found that understanding the motive behind the use of data increases its chances of sharing with a social group.ConclusionsIn this study, we highlight various privacy concerns that can be addressed during the design phase. A system design that is compliant with general data protection regulations will increase participants' and stakeholders' trust in an image-based dietary assessment system. Innovative solutions are needed to reduce the intrusiveness of a continuous assessment. Individuals show varying behaviors for sharing metadata, as knowing what the data is being used for, increases the chance of it being shared.

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Project description:ObjectiveDigital nudging has been mooted as a tool to alter user privacy behavior. However, empirical studies on digital nudging have yielded divergent results: while some studies found nudging to be highly effective, other studies found no such effects. Furthermore, previous studies employed a wide range of digital nudges, making it difficult to discern the effectiveness of digital nudging. To address these issues, we performed a systematic review of empirical studies on digital nudging and information disclosure as a specific privacy behavior.MethodThe search was conducted in five digital libraries and databases: Scopus, Google Scholar, ACM Digital Library, Web of Science, and Science Direct for peer-reviewed papers published in English after 2006, examining the effects of various nudging strategies on disclosure of personal information online.ResultsThe review unveiled 78 papers that employed four categories of nudge interventions: presentation, information, defaults, and incentives, either individually or in combination. A meta-analysis on a subset of papers with available data (n = 54) revealed a significant small-to-medium sized effect of the nudge interventions on disclosure (Hedges' g = 0.32). There was significant variation in the effectiveness of nudging (I2 = 89%), which was partially accounted for by interventions to increase disclosure being more effective than interventions to reduce disclosure. No evidence was found for differences in the effectiveness of nudging with presentation, information, defaults, and incentives interventions.ConclusionIdentifying ways to nudge users into making more informed and desirable privacy decisions is of significant practical and policy value. There is a growing interest in digital privacy nudges for disclosure of personal information, with most empirical papers focusing on nudging with presentation. Further research is needed to elucidate the relative effectiveness of different intervention strategies and how nudges can confound one another.

Project description:BackgroundPrivacy has always been a concern, especially in the health domain. The proliferation of mobile health (mHealth) apps has led to a large amount of sensitive data being generated. Some authors have performed privacy assessments of mHealth apps. They have evaluated diverse privacy components; however, different authors have used different criteria for their assessments.ObjectiveThis scoping review aims to understand how privacy is assessed for mHealth apps, focusing on the components, scales, criteria, and scoring methods used. A simple taxonomy to categorize the privacy assessments of mHealth apps based on component evaluation is also proposed.MethodsWe followed the methodology defined by Arksey and O'Malley to conduct a scoping review. Included studies were categorized based on the privacy component, which was assessed using the proposed taxonomy.ResultsThe database searches retrieved a total of 710 citations-24 of them met the defined selection criteria, and data were extracted from them. Even though the inclusion criteria considered articles published since 2009, all the studies that were ultimately included were published from 2014 onward. Although 12 papers out of 24 (50%) analyzed only privacy, 8 (33%) analyzed both privacy and security. Moreover, 4 papers (17%) analyzed full apps, with privacy being just part of the assessment. The evaluation criteria used by authors were heterogeneous and were based on their experience, the literature, and/or existing legal frameworks. Regarding the set of items used for the assessments, each article defined a different one. Items included app permissions, analysis of the destination, analysis of the content of communications, study of the privacy policy, use of remote storage, and existence of a password to access the app, among many others. Most of the included studies provided a scoring method that enables the comparison of privacy among apps.ConclusionsThe privacy assessment of mHealth apps is a complex task, as the criteria used by different authors for their evaluations are very heterogeneous. Although some studies about privacy assessment have been conducted, a very large set of items to evaluate privacy has been used up until now. In-app information and privacy policies are primarily utilized by the scientific community to extract privacy information from mHealth apps. The creation of a scale based on more objective criteria is a desirable step forward for privacy assessment in the future.

Dataset Information

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

Background

Objective

Methods

Results

Conclusions

Publications

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

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