Attitudes toward genomics and precision medicine

DuBois, James M.; Antes, Alison L.; English, Tammy; Parsons, Meredith; Baldwin, Kari

doi:10.1017/cts.2021.774

Cited by 5 publications

(5 citation statements)

References 35 publications

(51 reference statements)

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“…Divisions of opinion and groups of individuals that hold different configurations of attitudes towards gene editing may also have important consequences for future medical practice, for example in precision medicine applications (DuBois et al, 2021) and genetic counselling. Discussions of best practice in genetic counselling have highlighted the need for evidence based practices (Bowles Biesecker and Marteau, 1999) and how practice needs to change in response to the growing number of gene-based healthcare tools (Schupmann et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…providing information but not seeking to influence patients) (Arribas-Ayllon and Sarangi, 2014; Costal Tirado et al, 2017;Elwyn, 2000) and genetic counselling services should work with a peoplecentred philosophy (e.g., Costal Tirado et al, 2017). Studies such as ours are valuable since they explore concerns and attitudes towards the broader topic area (DuBois et al, 2021) and the methodology could be adopted to focus on practice-specific concerns..…”

Section: Discussionmentioning

confidence: 99%

“…Tirado et al, 2017). Studies such as ours are valuable since they explore concerns and attitudes towards the broader topic area (DuBois et al, 2021) and the methodology could be adopted to focus on practice-specific concerns.…”

Section: Discussionmentioning

confidence: 99%

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Heterogeneous attitudinal profiles towards gene editing: Evidence from latent class analysis

2022

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Advances in gene-editing technology have important implications for the treatment and prevention of disease. Accordingly, it is important to understand public perceptions towards gene editing, as the public’s willingness to endorse gene editing may be as important as technological breakthroughs themselves. Previous research has almost exclusively examined attitudes towards gene editing on specific issues, but has not addressed how attitudes towards gene editing across a range of issues coalesce in individuals: that is, the degree to which discrete, heterogeneous attitudinal profiles exist versus a simple support/oppose continuum. Here, we addressed this issue using latent class analysis on data from The Pew Research Center ( N = 4726; US residents) across a wide range of gene-editing topics. We found that attitudes towards gene editing cohere into 10 distinct latent classes that showed some evidence of a support/oppose continuum, but also for clear qualitative differences between each class, even with support or oppose classes, on a number of issues. The most opposed classes significantly differed from the supporter classes in age, sex, political ideology and self-rated knowledge. These findings provide evidence that attitudes towards gene editing are heterogeneous and public discourse, as well as policy making need to consider a range of arguments when evaluating this technology.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Heterogeneous attitudinal profiles towards gene editing: Evidence from latent class analysis

2022

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Section: Discussionmentioning

confidence: 99%

“…The attitude scale used in this study could be improved with additional questions about specific elements of genomic research and genetic testing, such as funding or social justice issues. Thus, there is a need, and a movement in current research, to develop and validate high-quality measures of genomic knowledge, attitudes, and behavior [49,50] The originality of some of our measures of knowledge and behaviors may make interpretation more difficult. For example, we surveyed participants about behaviors they already performed as well as their intentions to perform them in the future.…”

Section: Limitations Of This Studymentioning

confidence: 99%

Challenges in Improving Genomic Literacy: Results from National and Regional Surveys of Genomic Knowledge, Attitudes, Concerns, and Behaviors

Jaeger

Hellwig

Schiavoni

et al. 2022

Preprint

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Purpose: Information about genomics is increasingly available to mainstream society, with more and more emphasis on using genomic information to make health care decisions. To determine how prepared people are to use this knowledge to make critical health-related decisions, we assessed the public's level of genomic literacy and whether this knowledge affects their engagement in behaviors related to genomics, such as getting genetic testing. Methods: A survey assessing perceived and actual knowledge, attitudes, concerns, sources of information, and behaviors related to genomics was administered to national and regional samples of participants. A hierarchical linear regression tested whether knowledge and attitudes predicted engagement in behaviors related to genomics. Results: Participants had good basic knowledge of genetics, though they were less familiar with the term "the human genome". They also displayed positive attitudes towards genomic research, despite expressing many concerns. Both greater knowledge and more positive attitudes significantly and independently predicted greater engagement in genetic testing and other related proactive health behaviors. Conclusion: Knowledge and concerns about genomics impact the public's ability and willingness to obtain genetic testing and engage in other proactive health behaviors. The public's genomic literacy could be enhanced by integrating their knowledge (e.g of DNA) with broader concepts (e.g. the human genome and genomics) and how they relate to health. Future research is needed on interventions that do this, to improve the public's genomic literacy through relationships that build trust

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Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare

Sisk,

Antes,

Lin

et al. 2024

Learning Health Systems

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ObjectivesPatient engagement is critical for the effective development and use of artificial intelligence (AI)‐enabled tools in learning health systems (LHSs). We adapted a previously validated measure from pediatrics to assess adults' openness and concerns about the use of AI in their healthcare.Study DesignCross‐sectional survey.MethodsWe adapted the 33‐item “Attitudes toward Artificial Intelligence in Healthcare for Parents” measure for administration to adults in the general US population (AAIH‐A), recruiting participants through Amazon's Mechanical Turk (MTurk) crowdsourcing platform. AAIH‐A assesses openness to AI‐driven technologies and includes 7 subscales assessing participants' openness and concerns about these technologies. The openness scale includes examples of AI‐driven tools for diagnosis, prediction, treatment selection, and medical guidance. Concern subscales assessed privacy, social justice, quality, human element of care, cost, shared decision‐making, and convenience. We co‐administered previously validated measures hypothesized to correlate with openness. We conducted a confirmatory factor analysis and assessed reliability and construct validity. We performed exploratory multivariable regression models to identify predictors of openness.ResultsA total of 379 participants completed the survey. Confirmatory factor analysis confirmed the seven dimensions of the concerns, and the scales had internal consistency reliability, and correlated as hypothesized with existing measures of trust and faith in technology. Multivariable models indicated that trust in technology and concerns about quality and convenience were significantly associated with openness.ConclusionsThe AAIH‐A is a brief measure that can be used to assess adults' perspectives about AI‐driven technologies in healthcare and LHSs. The use of AAIH‐A can inform future development and implementation of AI‐enabled tools for patient care in the LHS context that engage patients as key stakeholders.

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Attitudes toward genomics and precision medicine

Cited by 5 publications

References 35 publications

Heterogeneous attitudinal profiles towards gene editing: Evidence from latent class analysis

Heterogeneous attitudinal profiles towards gene editing: Evidence from latent class analysis

Challenges in Improving Genomic Literacy: Results from National and Regional Surveys of Genomic Knowledge, Attitudes, Concerns, and Behaviors

Validating a novel measure for assessing patient openness and concerns about using artificial intelligence in healthcare

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