scholarly journals Motives of contributing personal data for health research: (Non-)participation in a Dutch biobank

2020 ◽  
Author(s):  
Reinder Broekstra ◽  
Els Maeckelberghe ◽  
Judith Aris-Meijer ◽  
Ronald Stolk ◽  
Sabine Otten
Keyword(s):  
Health Research ◽  
Large Scale ◽  
Behavioural Change ◽  
Personal Data ◽  
Population Based ◽  
Research Data ◽  
Current Data ◽  
Data Repositories ◽  
Regulatory Frameworks ◽  
Public Data

Abstract Background: Large-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal. Methods: We conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data. Results: The decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non­-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society and public goods, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants.Conclusions: Our findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures.

scholarly journals Motives of contributing personal data for health research:(Non-)participation in a Dutch biobank

2019 ◽  
Author(s):  
Reinder Broekstra ◽  
Els Maeckelberghe ◽  
Judith Aris-Meijer ◽  
Ronald Stolk ◽  
Sabine Otten
Keyword(s):  
Health Research ◽  
Large Scale ◽  
Behavioural Change ◽  
Personal Data ◽  
Population Based ◽  
Research Data ◽  
Current Data ◽  
Data Repositories ◽  
Regulatory Frameworks ◽  
Public Data

Abstract Background: Large-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal. Methods: We conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data. Results: The decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non­-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society and public goods, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants. Conclusions: Our findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures.

scholarly journals Motives of contributing personal data for health research: (Non-)participation in a Dutch biobank

2020 ◽  
Author(s):  
Reinder Broekstra ◽  
Els Maeckelberghe ◽  
Judith Aris-Meijer ◽  
Ronald Stolk ◽  
Sabine Otten
Keyword(s):  
Health Research ◽  
Large Scale ◽  
Behavioural Change ◽  
Personal Data ◽  
Population Based ◽  
Research Data ◽  
Current Data ◽  
Data Repositories ◽  
Regulatory Frameworks ◽  
Public Data

Abstract Background: Large-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal. Methods: We conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data. Results: The decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non­-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society and public goods, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants.Conclusions: Our findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures.

scholarly journals Motives of contributing personal data for health research: (Non-)participation in a Dutch biobank

2020 ◽  
Author(s):  
Reinder Broekstra ◽  
Els Maeckelberghe ◽  
Judith Aris-Meijer ◽  
Ronald Stolk ◽  
Sabine Otten
Keyword(s):  
Health Research ◽  
Large Scale ◽  
Behavioural Change ◽  
Personal Data ◽  
Population Based ◽  
Research Data ◽  
Current Data ◽  
Data Repositories ◽  
Regulatory Frameworks ◽  
Public Data

Abstract Background: Large-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal. Methods: We conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data. Results: The decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non­-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society and public goods, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants. Conclusions: Our findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures.

scholarly journals Motives of contributing personal data for health research: (Non-)participation in a Dutch biobank

2020 ◽  
Author(s):  
Reinder Broekstra ◽  
Els Maeckelberghe ◽  
Judith Aris-Meijer ◽  
Ronald Stolk ◽  
Sabine Otten
Keyword(s):  
Health Research ◽  
Large Scale ◽  
Behavioural Change ◽  
Personal Data ◽  
Population Based ◽  
Research Data ◽  
Current Data ◽  
Data Repositories ◽  
Regulatory Frameworks ◽  
Public Data

Abstract Background: Large-scale, centralized data repositories are playing a critical and unprecedented role in fostering innovative health research, leading to new opportunities as well as dilemmas for the medical sciences. Uncovering the reasons as to why citizens do or do not contribute to such repositories, for example, to population-based biobanks, is therefore crucial. We investigated and compared the views of existing participants and non-participants on contributing to large-scale, centralized health research data repositories with those of ex-participants regarding the decision to end their participation. This comparison could yield new insights into motives of participation and non-participation, in particular the behavioural change of withdrawal. Methods: We conducted 36 in-depth interviews with ex-participants, participants, and non-participants of a three-generation, population-based biobank in the Netherlands. The interviews focused on the respondents’ decision-making processes relating to their participation in a large-scale, centralized repository for health research data. Results: The decision of participants and non-participants to contribute to the biobank was motivated by a desire to help others. Whereas participants perceived only benefits relating to their participation and were unconcerned about potential risks, non­-participants and ex-participants raised concerns about the threat of large-scale, centralized public data repositories and public institutes, such as social exclusion or commercialization. Our analysis of ex-participants’ perceptions suggests that intrapersonal characteristics, such as levels of trust in society and public goods, participation conceived as a social norm, and basic societal values account for differences between participants and non-participants.Conclusions: Our findings indicate the fluidity of motives centring on helping others in decisions to participate in large-scale, centralized health research data repositories. Efforts to improve participation should focus on enhancing the trustworthiness of such data repositories and developing layered strategies for communication with participants and with the public. Accordingly, personalized approaches for recruiting participants and transmitting information along with appropriate regulatory frameworks are required, which have important implications for current data management and informed consent procedures.

Improvements for research data repositories: The case of text spam

2021 ◽  
pp. 016555152199863
Author(s):  
Ismael Vázquez ◽  
María Novo-Lourés ◽  
Reyes Pavón ◽  
Rosalía Laza ◽  
José Ramón Méndez ◽  
...  
Keyword(s):  
Web Application ◽  
Research Data ◽  
Data Sets ◽  
Data Repositories ◽  
Software Applications ◽  
Public Data ◽  
Protection Mechanisms ◽  
Experimental Protocols ◽  
Learning Research ◽  
Processing Steps

Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the results of their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through other approximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements for the development of experimental protocols and test benches. This study has analysed a significant number of CS/ML ( Computer Science/ Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2) facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms for licencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application which implements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in the URL https://rdata.4spam.group to facilitate understanding of this study.

scholarly journals A Review on the Application and Limitations of Administrative Health Care Data for the Study of Acute Kidney Injury Epidemiology and Outcomes in Children

2021 ◽  
Vol 9 ◽  
Author(s):  
Emma H. Ulrich ◽  
Gina So ◽  
Michael Zappitelli ◽  
Rahul Chanchlani
Keyword(s):  
Health Care ◽  
Acute Kidney Injury ◽  
Administrative Data ◽  
Health Research ◽  
Validation Studies ◽  
Large Scale ◽  
Kidney Injury ◽  
Process Of Care ◽  
Data Repositories ◽  
Adults And Children

Administrative health care databases contain valuable patient information generated by health care encounters. These “big data” repositories have been increasingly used in epidemiological health research internationally in recent years as they are easily accessible and cost-efficient and cover large populations for long periods. Despite these beneficial characteristics, it is also important to consider the limitations that administrative health research presents, such as issues related to data incompleteness and the limited sensitivity of the variables. These barriers potentially lead to unwanted biases and pose threats to the validity of the research being conducted. In this review, we discuss the effectiveness of health administrative data in understanding the epidemiology of and outcomes after acute kidney injury (AKI) among adults and children. In addition, we describe various validation studies of AKI diagnostic or procedural codes among adults and children. These studies reveal challenges of AKI research using administrative data and the lack of this type of research in children and other subpopulations. Additional pediatric-specific validation studies of administrative health data are needed to promote higher volume and increased validity of this type of research in pediatric AKI, to elucidate the large-scale epidemiology and patient and health systems impacts of AKI in children, and to devise and monitor programs to improve clinical outcomes and process of care.

scholarly journals Smart Mask – Wearable IoT Solution for Improved Protection and Personal Health

2021 ◽  
Author(s):  
Jarkko Hyysalo ◽  
Sandun Dasanayake ◽  
Jari Hannu ◽  
Christian Schuss ◽  
Mikko Rajanen ◽  
...  
Keyword(s):  
Large Scale ◽  
Personal Data ◽  
Health Data ◽  
Future Research ◽  
Personal Health ◽  
Public Data ◽  
Research Problems ◽  
Health Related ◽  
Treatment Plans ◽  
And Control

<div> <div> <div> <p>The use of face masks is an important way to fight the COVID-19 pandemic. In this paper, we envision the Smart Mask, an IoT supported platform and ecosystem aiming to prevent and control the spreading of COVID-19 and other respiratory viruses. The integration of sensing, materials, AI, wireless, IoT, and software will help gathering of health data and health-related event detection in real time from the user as well as from their environment. In larger scale, with the help of AI-based analysis for health data it is possible to predict and decrease medical costs with accurate diagnoses and treatment plans, where comparison of personal data to large-scale public data enables drawing up a personal health trajectory, for example. Key research problems for smart respiratory protective equipment are identified in addition to future research directions. </p> </div> </div> </div>

scholarly journals Transparency and quality assessment of research data in post-Soviet area studies: The potential of an interactive online platform

2019 ◽  
Vol 10 (2) ◽  
pp. 136-146 ◽  
Author(s):  
Andreas Heinrich ◽  
Felix Herrmann ◽  
Heiko Pleines
Keyword(s):  
Quality Assessment ◽  
Research Data ◽  
Current Data ◽  
Original Research ◽  
Data Repositories ◽  
Area Studies ◽  
The Social ◽  
Academic Publications ◽  
Data Transparency ◽  
Data Collections

The social sciences are increasingly addressing the quality of research data and debating ways to improve data transparency, that is, the availability of original research data to corroborate claims made in academic publications. This article offers a systematic discussion of related problems and challenges with the example of post-Soviet area studies. It goes on to examine ways to improve data transparency. Although the Internet has a huge potential for linking research with resulting publications and underlying data as well as for organizing a collective discussion around the research, current data repositories do not truly go beyond basic upload and download functions for datasets. With the example of the Discuss Data project, this article gives an overview of more elaborated features that can easily be implemented to improve the visibility and quality assessment of data collections. Finally, it discusses ethical concerns about data transparency related to privacy protection and copyrights.

scholarly journals Rapid Increase in Ownership and Use of Long-Lasting Insecticidal Nets and Decrease in Prevalence of Malaria in Three Regional States of Ethiopia (2006-2007)

2010 ◽  
Vol 2010 ◽  
pp. 1-12 ◽  
Author(s):  
Estifanos Biru Shargie ◽  
Jeremiah Ngondi ◽  
Patricia M. Graves ◽  
Asefaw Getachew ◽  
Jimee Hwang ◽  
...  
Keyword(s):  
Large Scale ◽  
Behavioural Change ◽  
Scale Up ◽  
Population Based ◽  
Malaria Prevalence ◽  
Change Communication ◽  
Net Use ◽  
Short Period ◽  
Llin Use ◽  
Long Lasting Insecticidal Nets

Following recent large scale-up of malaria control interventions in Ethiopia, this study aimed to compare ownership and use of long-lasting insecticidal nets (LLIN), and the change in malaria prevalence using two population-based household surveys in three regions of the country. Each survey used multistage cluster random sampling with 25 households per cluster. Household net ownership tripled from 19.6% in 2006 to 68.4% in 2007, with mean LLIN per household increasing from 0.3 to 1.2. Net use overall more than doubled from 15.3% to 34.5%, but in households owning LLIN, use declined from 71.7% to 48.3%. Parasitemia declined from 4.1% to 0.4%. Large scale-up of net ownership over a short period of time was possible. However, a large increase in net ownership was not necessarily mirrored directly by increased net use. Better targeting of nets to malaria-risk areas and sustained behavioural change communication are needed to increase and maintain net use.

scholarly journals Motives for withdrawal of participation in biobanking and participants’ willingness to allow linkages of their data

2021 ◽  
Author(s):  
Reinder Broekstra ◽  
Judith L. Aris-Meijer ◽  
Els L. M. Maeckelberghe ◽  
Ronald P. Stolk ◽  
Sabine Otten
Keyword(s):  
Decision Making ◽  
Data Linkage ◽  
Personal Data ◽  
Population Based ◽  
Future Research ◽  
Data Repositories ◽  
New Directions ◽  
Research Biobanks ◽  
Data Linkages ◽  
Improve Health

AbstractData repositories, like research biobanks, seek to optimise the number of responding participants while simultaneously attempting to increase the amount of data donated per participant. Such efforts aim to increase the repository’s value for its uses in medical research to contribute to improve health care, especially when data linkage is permitted by participants. We investigated individuals’ motives for participating in such projects and potential reasons for their withdrawal from participation in a population-based biobank. In addition, we analysed how these motives were related to various characteristics of the participants and their willingness to permit data linkage to their personal data for research. These questions were explored using a sample of participants in the Dutch Lifelines biobank (n = 2615). Our results indicated that motives for participation and withdrawal were premised on benefits or harm to society and to the individuals themselves. Although general values and trust both played key roles in participation, potential withdrawal and willingness to permit data linkage, they were differentially associated with motives for participation and withdrawal. These findings support and nuance previous findings by highlighting the distinctiveness and complexity of decision making regarding participation in or withdrawal from data donation. We suggest some new directions for improving recruitment, retention and safeguarding strategies in biobanking. In addition, our data provide initial evidence regarding how factors may relate with the probability that individuals will agree to data linkages, when controlling for their unique effects. Future research should further investigate how perceptions of harm and benefits may influence decision making on withdrawal of participation.

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