A scoping review of distributed ledger technology in genomics: thematic analysis and directions for future research

Beyene, Mikael; Toussaint, Philipp A; Thiebes, Scott; Schlesner, Matthias; Brors, Benedikt; Sunyaev, Ali

doi:10.1093/jamia/ocac077

Cited by 15 publications

(9 citation statements)

References 58 publications

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“…Because we only collected the 500 most recent comments, the majority of these can be dated to 2021. However, the DTC genetic testing market has and continues to evolve and change rapidly [ 1 , 2 , 7 , 14 ]. Future research should thus consider a temporal analysis of DTC genetic testing videos and comments to investigate if the market changes also affected user discourse and attitudes.…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, consumers taking multiple DTC genetic tests found themselves receiving different results depending on the service provider [ 8 ]. Another concern often discussed by researchers and consumers is the potential sharing and reselling of genetic data (eg, to pharmaceutical companies) and the resulting implications on genetic privacy, including genetic data access to insurance companies, employers, law enforcement agencies, or malicious entities like hackers [ 9 - 14 ]. Although many consumers perceive these practices as unfair, low prices and potential genetic insights often outweigh the aforementioned concerns [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

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Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments

Toussaint¹,

Renner²,

Lins³

et al. 2022

JMIR Infodemiology

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Background With direct-to-consumer (DTC) genetic testing enabling self-responsible access to novel information on ancestry, traits, or health, consumers often turn to social media for assistance and discussion. YouTube, the largest social media platform for videos, offers an abundance of DTC genetic testing–related videos. Nevertheless, user discourse in the comments sections of these videos is largely unexplored. Objective This study aims to address the lack of knowledge concerning user discourse in the comments sections of DTC genetic testing–related videos on YouTube by exploring topics discussed and users' attitudes toward these videos. Methods We employed a 3-step research approach. First, we collected metadata and comments of the 248 most viewed DTC genetic testing–related videos on YouTube. Second, we conducted topic modeling using word frequency analysis, bigram analysis, and structural topic modeling to identify topics discussed in the comments sections of those videos. Finally, we employed Bing (binary), National Research Council Canada (NRC) emotion, and 9-level sentiment analysis to identify users' attitudes toward these DTC genetic testing–related videos, as expressed in their comments. Results We collected 84,082 comments from the 248 most viewed DTC genetic testing–related YouTube videos. With topic modeling, we identified 6 prevailing topics on (1) general genetic testing, (2) ancestry testing, (3) relationship testing, (4) health and trait testing, (5) ethical concerns, and (6) YouTube video reaction. Further, our sentiment analysis indicates strong positive emotions (anticipation, joy, surprise, and trust) and a neutral-to-positive attitude toward DTC genetic testing–related videos. Conclusions With this study, we demonstrate how to identify users' attitudes on DTC genetic testing by examining topics and opinions based on YouTube video comments. Shedding light on user discourse on social media, our findings suggest that users are highly interested in DTC genetic testing and related social media content. Nonetheless, with this novel market constantly evolving, service providers, content providers, or regulatory authorities may still need to adapt their services to users' interests and desires.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments

Toussaint¹,

Renner²,

Lins³

et al. 2022

JMIR Infodemiology

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“…The lack of compatibility between different DLT systems [ 168 ] adds to the fragmentation of the space. The Hyperledger project seeks to overcome these challenges by providing several DLT frameworks that can be customized and integrated for various organizational needs, including health care and genomics research programs [ 59 , 169 , 167 ].…”

Section: Informed Consent Managementmentioning

confidence: 99%

Future-proofing genomic data and consent management: a comprehensive review of technology innovations

Oliva,

Kaphle,

Reguant

et al. 2024

GigaScience

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Genomic information is increasingly used to inform medical treatments and manage future disease risks. However, any personal and societal gains must be carefully balanced against the risk to individuals contributing their genomic data. Expanding our understanding of actionable genomic insights requires researchers to access large global datasets to capture the complexity of genomic contribution to diseases. Similarly, clinicians need efficient access to a patient’s genome as well as population-representative historical records for evidence-based decisions. Both researchers and clinicians hence rely on participants to consent to the use of their genomic data, which in turn requires trust in the professional and ethical handling of this information. Here, we review existing and emerging solutions for secure and effective genomic information management, including storage, encryption, consent, and authorization that are needed to build participant trust. We discuss recent innovations in cloud computing, quantum-computing-proof encryption, and self-sovereign identity. These innovations can augment key developments from within the genomics community, notably GA4GH Passports and the Crypt4GH file container standard. We also explore how decentralized storage as well as the digital consenting process can offer culturally acceptable processes to encourage data contributions from ethnic minorities. We conclude that the individual and their right for self-determination needs to be put at the center of any genomics framework, because only on an individual level can the received benefits be accurately balanced against the risk of exposing private information.

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“…In diesem Zusammenhang bedarf es insbesondere mehr Forschung zur Dezentralität von DiGA, zum Beispiel zu dezentralem Daten- und Rechtemanagement mithilfe von emergenten Internet-basierten Technologien, wie z. B. Blockchain [ 41 ].…”

Section: Entwicklungspotenzial Von Digaunclassified

Digitale Gesundheitsanwendungen (DiGA) im Spannungsfeld von Fortschritt und Kritik

Schlieter,

Kählig,

Hickmann

et al. 2023

Bundesgesundheitsbl

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ZusammenfassungIm Dezember 2019 wurden in Deutschland Digitale Gesundheitsanwendungen (DiGA) in die Regelversorgung aufgenommen und können somit durch die gesetzlichen Krankenkassen erstattet werden, um PatientInnen bei der Behandlung von Erkrankungen oder Beeinträchtigungen zu unterstützen. Inzwischen gibt es 48 DiGA (Stand: Oktober 2023) im Verzeichnis des Bundesinstituts für Arzneimittel und Medizinprodukte (BfArM), die vor allem in den Bereichen mentale Gesundheit, Hormone und Stoffwechsel sowie Muskeln, Knochen und Gelenke eingesetzt werden. In diesem Artikel beschreibt die Fachgruppe „Digital Health“ der Gesellschaft für Informatik e. V. (GI) die aktuellen Entwicklungen rund um die DiGA sowie das derzeitige Stimmungsbild zu Themen wie Nutzerzentrierung, Akzeptanz von PatientInnen und Behandelnden sowie Innovationspotenzial. Zusammenfassend haben DiGA in den letzten 3 Jahren eine positive Entwicklung in Form eines langsam steigenden Angebots verschiedener DiGA und Leistungsbereiche erfahren. Nichtsdestotrotz sind in einigen Bereichen noch erhebliche regulatorische Weichenstellungen notwendig, um DiGA langfristig in der Regelversorgung zu etablieren. Zentrale Herausforderungen bestehen u. a. in der Nutzerzentrierung oder in der nachhaltigen Verwendung der Anwendungen.

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A scoping review of distributed ledger technology in genomics: thematic analysis and directions for future research

Cited by 15 publications

References 58 publications

Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments

Direct-to-Consumer Genetic Testing on Social Media: Topic Modeling and Sentiment Analysis of YouTube Users' Comments

Future-proofing genomic data and consent management: a comprehensive review of technology innovations

Digitale Gesundheitsanwendungen (DiGA) im Spannungsfeld von Fortschritt und Kritik

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