ArticleJournal of medical systems2021
My Data, My Choice? - German Patient Organizations' Attitudes towards Big Data-Driven Approaches in Personalized Medicine. An Empirical-Ethical Study.
Article in Journal of medical systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Integration of Federated Learning and Blockchain in Health Care: Tutorial on Medical Data, Architectures, Privacy, Security, and Regulatory Compliance.Journal of medical Internet research · 2026Article
- Critical consideration towards broad consent by patient experts: results of a semi-structured interview study on the secondary use of medical data.BMC medical ethics · 2025Article
- The ethical aspects of human organ-on-chip models: A mapping review.Stem cell reports · 2025Review
- Digital Transformation in Patient Organizations: Interview and Focus Group Study.Journal of medical Internet research · 2025Article
- Between willingness and practice: a nationwide survey of 1,334 German patient organization members on user involvement in digital service development.Frontiers in digital health · 2025Article
- Patient Organizations' Digital Responses to the COVID-19 Pandemic: Scoping Review.Journal of medical Internet research · 2024Article
- Sharing of military Veterans' mental health data across Canada: A scoping review.Journal of military, veteran and family health · 2024Review
- Review
- Article
- Patients' perspectives on digital health tools.PEC innovation · 2023Article
- How can we deliver on the promise of precision medicine in oncology and beyond? A practical roadmap for action.Health science reports · 2023Article
- Attitudes of Patients With Chronic Heart Failure Toward Digital Device Data for Self-documentation and Research in Germany: Cross-sectional Survey Study.JMIR cardio · 2022Article
- A Topical Collection on ICT for Health Science Research - EFMI Special Topic Conference.Journal of medical systems · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Personalized medicine (PM) operates with biological data to optimize therapy or prevention and to achieve cost reduction. Associated data may consist of large variations of informational subtypes e.g. genetic characteristics and their epigenetic modifications, biomarkers or even individual lifestyle factors. Present innovations in the field of information technology have already enabled the procession of increasingly large amounts of such data ('volume') from various sources ('variety') and varying quality in terms of data accuracy ('veracity') to facilitate the generation and analyzation of messy data sets within a short and highly efficient time period ('velocity') to provide insights into previously unknown connections and correlations between different items ('value'). As such developments are characteristics of Big Data approaches, Big Data itself has become an important catchphrase that is closely linked to the emerging foundations and approaches of PM. However, as ethical concerns have been pointed out by experts in the debate already, moral concerns by stakeholders such as patient organizations (POs) need to be reflected in this context as well. We used an empirical-ethical approach including a website-analysis and 27 telephone-interviews for gaining in-depth insight into German POs' perspectives on PM and Big Data. Our results show that not all POs are stakeholders in the same way. Comparing the perspectives and political engagement of the minority of POs that is currently actively involved in research around PM and Big Data-driven research led to four stakeholder sub-classifications: 'mediators' support research projects through facilitating researcher's access to the patient community while simultaneously selecting projects they preferably support while 'cooperators' tend to contribute more directly to research projects by providing and implemeting patient perspectives. 'Financers' provide financial resources. 'Independents' keep control over their collected samples and associated patient-related information with a strong interest in making autonomous decisions about its scientific use. A more detailed terminology for the involvement of POs as stakeholders facilitates the adressing of their aims and goals. Based on our results, the 'independents' subgroup is a promising candidate for future collaborations in scientific research. Additionally, we identified gaps in PO's knowledge about PM and Big Data. Based on these findings, approaches can be developed to increase data and statistical literacy. This way, the full potential of stakeholder involvement of POs can be made accessible in discourses around PM and Big Data.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.