scholarly journals Correction: Non-Hispanic White Mothers’ Willingness to Share Personal Health Data With Researchers: Survey Results From an Opt-in Panel

10.2196/24183 ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. e24183
Author(s):  
Adam Bouras ◽  
Eduardo J Simoes ◽  
Suzanne Boren ◽  
Lanis Hicks ◽  
Iris Zachary ◽  
...  
Keyword(s):  
Health Data ◽  
Personal Health ◽  
White Mothers ◽  
Survey Results ◽  
Hispanic White

scholarly journals Non-Hispanic White Mothers’ Willingness to Share Personal Health Data With Researchers: Survey Results From an Opt-in Panel

10.2196/14062 ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. e14062
Author(s):  
Adam Bouras ◽  
Eduardo J Simoes ◽  
Suzanne Boren ◽  
Lanis Hicks ◽  
Iris Zachary ◽  
...  
Keyword(s):  
Health Information ◽  
Medical Record ◽  
Health Data ◽  
Personal Health ◽  
Patient Portal ◽  
Patient Portals ◽  
Web Based ◽  
Privacy Concerns ◽  
White Mothers ◽  
Hispanic White

Background Advances in information communication technology provide researchers with the opportunity to access and collect continuous and granular data from enrolled participants. However, recruiting study participants who are willing to disclose their health data has been challenging for researchers. These challenges can be related to socioeconomic status, the source of data, and privacy concerns about sharing health information, which affect data-sharing behaviors. Objective This study aimed to assess healthy non-Hispanic white mothers’ attitudes in five areas: motivation to share data, concern with data use, desire to keep health information anonymous, use of patient portal and willingness to share anonymous data with researchers. Methods This cross-sectional study was conducted on 622 healthy non-Hispanic white mothers raising healthy children. From a Web-based survey with 51 questions, we selected 15 questions for further analysis. These questions focused on attitudes and beliefs toward data sharing, internet use, interest in future research, and sociodemographic and health questions about mothers and their children. Data analysis was performed using multivariate logistic regressions to investigate the factors that influence mothers’ willingness to share their personal health data, their utilization of a patient portal, and their interests in keeping their health information anonymous. Results The results of the study showed that the majority of mothers surveyed wanted to keep their data anonymous (440/622, 70.7%) and use patient portals (394/622, 63.3%) and were willing to share their data from Web-based surveys (509/622, 81.8%) and from mobile phones (423/622, 68.0%). However, 36.0% (224/622) and 40.5% (252/622) of mothers were less willing to share their medical record data and their locations with researchers, respectively. We found that the utilization of patient portals, their attitude toward keeping data anonymous, and their willingness to share different data sources were dependent on the mothers’ health care provider status, their motivation, and their privacy concerns. Mothers’ concerns about the misuse of personal health information had a negative impact on their willingness to share sensitive data (ie, electronic medical record: adjusted odds ratio [aOR] 0.43, 95% CI 0.25-0.73; GPS: aOR 0.4, 95% CI 0.27-0.60). In contrast, mothers’ motivation to share their data had a positive impact on disclosing their data via Web-based surveys (aOR 5.94, 95% CI 3.15-11.2), apps and devices designed for health (aOR 5.3, 95% CI 2.32-12.1), and a patient portal (aOR 4.3, 95% CI 2.06-8.99). Conclusions The findings of this study suggest that mothers’ privacy concerns affect their decisions to share sensitive data. However, mothers’ access to the internet and the utilization of patient portals did not have a significant effect on their willingness to disclose their medical record data. Finally, researchers can use our findings to better address their study subjects concerns and gain their subjects trust to disclose data.

scholarly journals Correction: Non-Hispanic White Mothers’ Willingness to Share Personal Health Data With Researchers: Survey Results From an Opt-in Panel (Preprint)

2020 ◽  
Author(s):  
Adam Bouras ◽  
Eduardo J Simoes ◽  
Suzanne Boren ◽  
Lanis Hicks ◽  
Iris Zachary ◽  
...  
Keyword(s):  
Health Information ◽  
Medical Record ◽  
Health Data ◽  
Personal Health ◽  
Patient Portal ◽  
Patient Portals ◽  
Web Based ◽  
Privacy Concerns ◽  
White Mothers ◽  
Hispanic White

UNSTRUCTURED Advances in information communication technology provide researchers with the opportunity to access and collect continuous and granular data from enrolled participants. However, recruiting study participants who are willing to disclose their health data has been challenging for researchers. These challenges can be related to socioeconomic status, the source of data, and privacy concerns about sharing health information, which affect data-sharing behaviors. This study aimed to assess healthy non-Hispanic white mothers’ attitudes in five areas: motivation to share data, concern with data use, desire to keep health information anonymous, use of patient portal and willingness to share anonymous data with researchers. This cross-sectional study was conducted on 622 healthy non-Hispanic white mothers raising healthy children. From a Web-based survey with 51 questions, we selected 15 questions for further analysis. These questions focused on attitudes and beliefs toward data sharing, internet use, interest in future research, and sociodemographic and health questions about mothers and their children. Data analysis was performed using multivariate logistic regressions to investigate the factors that influence mothers’ willingness to share their personal health data, their utilization of a patient portal, and their interests in keeping their health information anonymous. The results of the study showed that the majority of mothers surveyed wanted to keep their data anonymous (440/622, 70.7%) and use patient portals (394/622, 63.3%) and were willing to share their data from Web-based surveys (509/622, 81.8%) and from mobile phones (423/622, 68.0%). However, 36.0% (224/622) and 40.5% (252/622) of mothers were less willing to share their medical record data and their locations with researchers, respectively. We found that the utilization of patient portals, their attitude toward keeping data anonymous, and their willingness to share different data sources were dependent on the mothers’ health care provider status, their motivation, and their privacy concerns. Mothers’ concerns about the misuse of personal health information had a negative impact on their willingness to share sensitive data (ie, electronic medical record: adjusted odds ratio [aOR] 0.43, 95% CI 0.25-0.73; GPS: aOR 0.4, 95% CI 0.27-0.60). In contrast, mothers’ motivation to share their data had a positive impact on disclosing their data via Web-based surveys (aOR 5.94, 95% CI 3.15-11.2), apps and devices designed for health (aOR 5.3, 95% CI 2.32-12.1), and a patient portal (aOR 4.3, 95% CI 2.06-8.99). The findings of this study suggest that mothers’ privacy concerns affect their decisions to share sensitive data. However, mothers’ access to the internet and the utilization of patient portals did not have a significant effect on their willingness to disclose their medical record data. Finally, researchers can use our findings to better address their study subjects concerns and gain their subjects trust to disclose data.

scholarly journals Non-Hispanic White Mothers’ Willingness to Share Personal Health Data With Researchers: Survey Results From an Opt-in Panel (Preprint)

2019 ◽  
Author(s):  
Adam Bouras ◽  
Eduardo Simoes ◽  
Suzanne Boren ◽  
Lanis Hicks ◽  
Iris Zachary ◽  
...  
Keyword(s):  
Health Information ◽  
Medical Record ◽  
Health Data ◽  
Personal Health ◽  
Patient Portal ◽  
Patient Portals ◽  
Web Based ◽  
Privacy Concerns ◽  
White Mothers ◽  
Hispanic White

BACKGROUND Advances in information communication technology provide researchers with the opportunity to access and collect continuous and granular data from enrolled participants. However, recruiting study participants who are willing to disclose their health data has been challenging for researchers. These challenges can be related to socioeconomic status, the source of data, and privacy concerns about sharing health information, which affect data-sharing behaviors. OBJECTIVE This study aimed to assess healthy non-Hispanic white mothers’ attitudes in five areas: motivation to share data, concern with data use, desire to keep health information anonymous, use of patient portal and willingness to share anonymous data with researchers. METHODS This cross-sectional study was conducted on 622 healthy non-Hispanic white mothers raising healthy children. From a Web-based survey with 51 questions, we selected 15 questions for further analysis. These questions focused on attitudes and beliefs toward data sharing, internet use, interest in future research, and sociodemographic and health questions about mothers and their children. Data analysis was performed using multivariate logistic regressions to investigate the factors that influence mothers’ willingness to share their personal health data, their utilization of a patient portal, and their interests in keeping their health information anonymous. RESULTS The results of the study showed that the majority of mothers surveyed wanted to keep their data anonymous (440/622, 70.7%) and use patient portals (394/622, 63.3%) and were willing to share their data from Web-based surveys (509/622, 81.8%) and from mobile phones (423/622, 68.0%). However, 36.0% (224/622) and 40.5% (252/622) of mothers were less willing to share their medical record data and their locations with researchers, respectively. We found that the utilization of patient portals, their attitude toward keeping data anonymous, and their willingness to share different data sources were dependent on the mothers’ health care provider status, their motivation, and their privacy concerns. Mothers’ concerns about the misuse of personal health information had a negative impact on their willingness to share sensitive data (ie, electronic medical record: adjusted odds ratio [aOR] 0.43, 95% CI 0.25-0.73; GPS: aOR 0.4, 95% CI 0.27-0.60). In contrast, mothers’ motivation to share their data had a positive impact on disclosing their data via Web-based surveys (aOR 5.94, 95% CI 3.15-11.2), apps and devices designed for health (aOR 5.3, 95% CI 2.32-12.1), and a patient portal (aOR 4.3, 95% CI 2.06-8.99). CONCLUSIONS The findings of this study suggest that mothers’ privacy concerns affect their decisions to share sensitive data. However, mothers’ access to the internet and the utilization of patient portals did not have a significant effect on their willingness to disclose their medical record data. Finally, researchers can use our findings to better address their study subjects concerns and gain their subjects trust to disclose data.

Study on the feasibility of data sharing and collecting consumer wearable and mobile survey data to assess physical and mental health status : data quality and study challenges using an opt-in panel

2020 ◽  
Author(s):  
◽  
Adam Bouras
Keyword(s):  
Data Quality ◽  
Wearable Devices ◽  
Health Data ◽  
Wearable Device ◽  
Physical And Mental Health ◽  
White Mothers ◽  
Status Data ◽  
The Impact ◽  
Mobile Survey ◽  
Hispanic White

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] The use of opt-in panel for health research and smartphones are still in their infancy, and the impact of how opt-in panel members share their health data for a different purpose for research is not yet well explored more specifically data from consumer wearable devices. Thus, we implemented the eCaregiving study, a two-phase feasibility study, to assesses opt-in panel members' behavior to share their health data with researchers and establish a linkage between consumer wearable devices data and self-reported outcome. The first phase was about assessing opt-in panel members to share their patient health data and their interest to participate in sharing their wearable devices' data using a survey questionnaire -- the panel is composed of healthy non-Hispanic white mothers. The second phase of eCaregiving was to recruit those who expressed interest in sharing their wearable device data and participate in the self-reported outcome mobile survey questionnaire. We grouped our participants into those who use Fitbit and those who do not use any wearable devices, and the later was given a Fitbit Charger HR as an incentive for their participation. Although we targeted fifty participants from each group, we were able to recruit only five participants from those who use Fitbit, and we achieved our target for those who never used any wearable device. The feasibility study showed that the interest to participate in the study did not translate into actual participation. Although we gave incentives to these participants, we found a discrepancy in the actual participation, and this discrepancy warranted further studies to determine the exact reasons for non-participation. Throughout this study, our participants received minimal guidance and training on how to use wearables devices or how to synchronize their device with the mobile application -- e4 research app. We found that mobile survey has better participation, attrition, and completion rate and completion time than the traditional surveys. We also investigated the data quality from the consumer wearable device, and we found that number of days captured of step count is significant. We also found that the number of sleep hours captured is low, but they are better than another controlled study where the participants have trained to use these consumer wearable devices. All in all, our study can be used as a guideline for future studies on mhealth and wearable devices to develop efficient protocols to maximize data quality from wearable devices and mobile surveys. The study provides a systematic approach to recruit and link subjective and objective data for more actionable insight. Besides, we reported the impact of incentives on the participation rate and the attrition rate in mobile surveys. Overall, mobile surveys and wearable devices can complement each other and enhance our understanding of the overall daily activity of our participants. The remaining of this thesis is structured as follows; the first chapter introduces the first paper entitled non-Hispanic white mothers' willingness to share personal health data with researchers: survey results from an opt-in panel. The final chapter introduces the second paper entitled study on the feasibility of collecting consumer wearable and mobile survey data to assess physical and mental health status -- data quality and study chall

(Preprint)

2018 ◽  
Author(s):  
Ram Dixit ◽  
Sahiti Myneni
Keyword(s):  
Cancer Survivors ◽  
Mental Models ◽  
Health Systems ◽  
Information Needs ◽  
Health Data ◽  
Information Architecture ◽  
Personal Health ◽  
User Centered Design ◽  
Card Sort ◽  
Connected Health

BACKGROUND Connected Health technologies are a promising solution for chronic disease management. However, the scope of connected health systems makes it difficult to employ user-centered design in their development, and poorly designed systems can compound the challenges of information management in chronic care. The Digilego Framework addresses this problem with informatics methods that complement quantitative and qualitative methods in system design, development, and architecture. OBJECTIVE To determine the accuracy and validity of the Digilego information architecture of personal health data in meeting cancer survivors’ information needs. METHODS We conducted a card sort study with 9 cancer survivors (patients and caregivers) to analyze correspondence between the Digilego information architecture and cancer survivors’ mental models. We also analyzed participants’ card sort groups qualitatively to understand their conceptual relations. RESULTS We observed significant correlation between the Digilego information architecture and cancer survivors’ mental models of personal health data. Heuristic analysis of groups also indicated informative discordances and the need for patient-centric categories relating health tracking and social support in the information architecture. CONCLUSIONS Our pilot study shows that the Digilego Framework can capture cancer survivors’ information needs accurately; we also recognize the need for larger studies to conclusively validate Digilego information architectures. More broadly, our results highlight the importance of complementing traditional user-centered design methods and innovative informatics methods to create patient-centered connected health systems.

scholarly journals The funhouse mirror: the I in personalised healthcare

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Mira W. Vegter ◽  
Hub A. E. Zwart ◽  
Alain J. van Gool
Keyword(s):  
Precision Medicine ◽  
Personal Data ◽  
Health Data ◽  
Personal Health ◽  
Lifestyle Interventions ◽  
Phenotypic Data ◽  
Individual Health ◽  
Data Source ◽  
Tracking Devices ◽  
Personalised Healthcare

AbstractPrecision Medicine is driven by the idea that the rapidly increasing range of relatively cheap and efficient self-tracking devices make it feasible to collect multiple kinds of phenotypic data. Advocates of N = 1 research emphasize the countless opportunities personal data provide for optimizing individual health. At the same time, using biomarker data for lifestyle interventions has shown to entail complex challenges. In this paper, we argue that researchers in the field of precision medicine need to address the performative dimension of collecting data. We propose the fun-house mirror as a metaphor for the use of personal health data; each health data source yields a particular type of image that can be regarded as a ‘data mirror’ that is by definition specific and skewed. This requires competence on the part of individuals to adequately interpret the images thus provided.

scholarly journals Public Interest, Health Research and Data Protection Law: Establishing a Legitimate Trade-Off between Individual Control and Research Access to Health Data

Laws ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 6 ◽  
Author(s):  
Mark J. Taylor ◽  
Tess Whitton
Keyword(s):  
Public Interest ◽  
Data Protection ◽  
Health Research ◽  
Health Data ◽  
Personal Health ◽  
Positive Contribution ◽  
Data Governance ◽  
The Public ◽  
Individual Control ◽  
Data Protection Law

The United Kingdom’s Data Protection Act 2018 introduces a new public interest test applicable to the research processing of personal health data. The need for interpretation and application of this new safeguard creates a further opportunity to craft a health data governance landscape deserving of public trust and confidence. At the minimum, to constitute a positive contribution, the new test must be capable of distinguishing between instances of health research that are in the public interest, from those that are not, in a meaningful, predictable and reproducible manner. In this article, we derive from the literature on theories of public interest a concept of public interest capable of supporting such a test. Its application can defend the position under data protection law that allows a legal route through to processing personal health data for research purposes that does not require individual consent. However, its adoption would also entail that the public interest test in the 2018 Act could only be met if all practicable steps are taken to maximise preservation of individual control over the use of personal health data for research purposes. This would require that consent is sought where practicable and objection respected in almost all circumstances. Importantly, we suggest that an advantage of relying upon this concept of the public interest, to ground the test introduced by the 2018 Act, is that it may work to promote the social legitimacy of data protection legislation and the research processing that it authorises without individual consent (and occasionally in the face of explicit objection).

scholarly journals Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research: Bibliometric Analysis (Preprint)

2021 ◽  
Author(s):  
Jianxia Gong ◽  
Vikrant Sihag ◽  
Qingxia Kong ◽  
Lindu Zhao
Keyword(s):  
Health Care ◽  
Human Factors ◽  
Computer Science ◽  
Bibliometric Analysis ◽  
Focal Point ◽  
Empirical Studies ◽  
Health Data ◽  
Personal Health ◽  
Knowledge Evolution ◽  
Research Hotspots

BACKGROUND The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots. OBJECTIVE The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis. METHODS We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence. RESULTS The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention. CONCLUSIONS Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including “allocative value,” “technology value,” and “personalized value.”

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