Evidence map›Paper›PMID 33616768›Full record

ArticleJournal of medical systems2021

My Data, My Choice? - German Patient Organizations' Attitudes towards Big Data-Driven Approaches in Personalized Medicine. An Empirical-Ethical Study.

Carolin Martina Rauter, Sabine Wöhlke, Silke Schicktanz

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Article
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  3. Review
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  5. Article
  6. Article
  7. Sharing of military Veterans' mental health data across Canada: A scoping review.Journal of military, veteran and family health · 2024
    Review
  8. Journal of military, veteran and family health · 2024
    Review
  9. Article
  10. Article
  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Carolin Martina RauterDepartment of Medical Ethics and History of Medicine, University Medical Center Göttingen, Göttingen, Germany. c.rauter@stud.uni-goettingen.de.ORCID http://orcid.org/0000-0001-7521-1337
Sabine WöhlkeDepartment of Medical Ethics and History of Medicine, University Medical Center Göttingen, Göttingen, Germany.
Silke SchicktanzDepartment of Medical Ethics and History of Medicine, University Medical Center Göttingen, Göttingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

AttitudeBig DataOwnershipEmpirical ResearchHumansInterviews as TopicPrecision MedicineBig dataEmpirical ethicsInterviewsPatient organizationsPersonalized medicineStakeholder

Identifiers

PMID33616768
PMCPMC7900081

What OpenQuestion holds

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Registered trials

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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.