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Objective: Despite exome sequencing (ES) becoming increasingly incorporated into the prenatal setting, few studies have elucidated motivations for and trust in ES and genomic research among a diverse cohort of patients and their partners. Methods: This is a qualitative study that involved semi‐structured interviews with pregnant or recently pregnant individuals and their partners, interviewed separately, in the setting of ES performed through research for a fetal structural anomaly. All interview transcripts were coded thematically and developed by a multidisciplinary team. Results: Thirty‐five individuals participated, the majority of whom (66%) self‐identified as a racial or ethnic group underrepresented in genomic research. Many patients and their partners expressed trust in the healthcare system and research process and appreciated the extensive testing for information and closure. There were nonetheless concerns about data privacy and protection for individuals, including those underrepresented, who participated in genomic testing and studies. Conclusion: Our findings illustrate important elements of motivation, trust and concern related to prenatal ES performed in the research setting, taking into account the perspectives not only of diverse and underrepresented study participants but also partners of pregnant individuals. Key points: What's already known about this topic? Prenatal exome sequencing is increasingly utilized, yet little is known about motivations for and trust in this testing, particularly from patients underrepresented in genomic research. What does this study add? This study adds perspectives from diverse patients and partners regarding trust in prenatal exome sequencing.Participants expressed trust in healthcare and research, and recognized the utility of testing for information and closure. However, concerns have been raised about data privacy and protection for individuals of underrepresented races and ethnicities. [ABSTRACT FROM AUTHOR]

Background: Public health palliative care interventions are increasingly implemented, with growing recognition of the importance of building evidence to support their utility in end-of-life care. Previous efforts have focused on community outcomes. Aim: To examine the impact of public health palliative care on patterns of health service use at the end of life (primary) and explore which outcomes are being measured within this field of research (secondary). Design: Systematic review of studies reporting qualitative and quantitative data, analysed with a narrative synthesis method. Data sources: A systematic review conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta Analyses guideline was undertaken using six electronic databases (MEDLINE, CINAHL, EMBASE, PsycINFO, INFORMIT and COCHRANE) up to February 2020. Results: Searches yielded 2622 unique titles screened for eligibility, resulting in 35 studies measuring outcomes from a public health palliative care approach. Five (14%) studies assessed health system outcomes, and three reported some mixed evidence of impact, including reduced hospital emergency admissions, hospital bed days, hospital costs and increased home deaths. Most studies (86%) instead reported on conceptual (49%), knowledge (40%), programme participation (37%) and/or individual health outcomes (29%). Conclusion: The impact of public health palliative care is an evolving area of empirical inquiry with currently only limited evidence that it improves healthcare utilisation outcomes at the end of life, and limited focus on measurement of these outcomes. Further empirical studies are needed to support the reorientation of health services, which remains an important component in realising 'whole of system change' to bring about quality end-of-life care for all. [ABSTRACT FROM AUTHOR]

Background: Families whose child has unexplained intellectual or developmental differences often hope that a genetic diagnosis will lower barriers to community-based therapeutic and support services. However, there is little known about efforts to mobilize genetic information outside the clinic or how socioeconomic disadvantage shapes and constrains outcomes., Methods: We conducted an ethnographic study with predominantly socioeconomically disadvantaged families enrolled in a multi-year genomics research study, including clinic observations and in-depth interviews in English and Spanish at multiple time points. Coding and thematic development were used to collaboratively interpret fieldnotes and transcripts., Results: Thirty-two families participated. Themes included familial expectations that a genetic diagnosis could be translated into information, understanding, and assistance to improve the quality of a child's day-to-day life. After sequencing, however, genetic information was not readily converted into improved access to services beyond the clinic, with families often struggling to use a genetic diagnosis to advocate for their child., Conclusion: Families' ability to use a genetic diagnosis as an effective advocacy tool beyond the clinic was limited by the knowledge and resources available to them, and by the eligibility criteria used by therapeutic service providers' - which focused on clinical diagnosis and functional criteria more than etiologic information. All families undertaking genomic testing, particularly those who are disadvantaged, need additional support to understand the limits and potential benefits of genetic information beyond the clinic.

Purpose: This study aimed to understand broad data sharing decisions among predominantly underserved families participating in genomic research., Methods: Drawing on clinic observations, semistructured interviews, and survey data from prenatal and pediatric families enrolled in a genomic medicine study focused on historically underserved and underrepresented populations, this paper expands empirical evidence regarding genomic data sharing communication and decision-making., Results: One-third of parents declined to share family data, and pediatric participants were significantly more likely to decline than prenatal participants. The pediatric population was significantly more socioeconomically disadvantaged and more likely to require interpreters. Opt-in was tied to altruism and participants' perception that data sharing was inherent to research participation. Opt-out was associated with privacy concerns and influenced by clinical staff's presentation of data handling procedures. The ability of participants to make informed choices during enrollment about data sharing was weakened by suboptimal circumstances, which was revealed by poor understanding of data sharing in follow-up interviews as well as discrepancies between expressed participant desires and official recorded choices., Conclusion: These empirical data suggest that the context within which informed consent process is conducted in clinical genomics may be inadequate for respecting participants' values and preferences and does not support informed decision-making processes., Competing Interests: Conflict of Interest The authors declare no conflict of interest., (Copyright © 2021 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

As fetal gene therapies move from experimental animal models to human in utero phase I clinical trials, there is a need to consider the ethical, legal, and social implications. While fetal gene therapies are attracting more regulatory oversight than previous fetal interventions such as fetal surgery, old sociological questions should be applied to this new context. As health care pathways around fetal therapy are shaped by the ways in which a pregnant person and the fetus are constituted, and as risks and benefits are evaluated, we cannot afford to lose sight of long-term consequences, especially those pertaining to social inclusion., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Objectives: Well-being perception is seldom explored in schizophrenia patients. Recurrent limitations, such as the questionable applicability of gold standard definitions of health and well-being, and fewer tools available to assess well-being, are pronounced in this subpopulation. This cross-sectional study sought to explore potential clinical factors that may predict subjective well-being scores in chronic schizophrenia patients (N=142) receiving clozapine treatment., Methods: The Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS) was used to measure well-being. We correlated SWEMWBS scores and 27 clinically recognized factors, spanning socio-demographics, symptom severity scores, physical health diagnosis, clozapine side effects, habits and prescribed medication. Factors with a p<0.2 correlation were included as a predictors in a linear regression model., Results: Ten factors were included in the linear regression model, however only positive symptom severity was a significant predictor of SWEMWBS score (p<0.0001)., Conclusions: We suggest that greater levels of clinical attention given to positive symptoms compared with other symptoms and aspects of well-being, during biomedical treatment for chronic schizophrenia, may partially explain the finding that only positive symptoms significantly predicted patient perceptions of low well-being., (Copyright © 2016 Elsevier Inc. All rights reserved.)