Pediatric Reporting of Genomic Results Study (PROGRESS): A mixed-methods, longitudinal, observational cohort study protocol to explore disclosure of actionable adult- and pediatric-onset genomic variants to minors and their parents

BACKGROUND: Exome and genome sequencing are routinely used in clinical care and research. These technologies allow for the detection of pathogenic/likely pathogenic variants in clinically actionable genes. However, fueled in part by a lack of empirical evidence, controversy surrounds the provision of genetic results for adult-onset conditions to minors and their parents. We have designed a mixed-methods, longitudinal cohort study to collect empirical evidence to advance this debate. METHODS: Pediatric participants in the Geisinger MyCode® Community Health Initiative with available exome sequence data will have their variant files assessed for pathogenic/likely pathogenic variants in 60 genes designated as actionable by MyCode. Eight of these genes are associated with adult-onset conditions (Hereditary Breast and Ovarian Cancer Syndrome (HBOC), Lynch syndrome, MUTYH-associated polyposis, HFE-Associated Hereditary Hemochromatosis), while the remaining genes have pediatric onset. Prior to clinical confirmation of results, pediatric MyCode participants and their parents/legal guardians will be categorized into three study groups: 1) those with an apparent pathogenic/likely pathogenic variant in a gene associated with adult-onset disease, 2) those with an apparent pathogenic/likely pathogenic variant in a gene associated with pediatric-onset disease or with risk reduction interventions that begin in childhood, and 3) those with no apparent genomic result who are sex- and age-matched to Groups 1 and 2. Validated and published quantitative measures, semi-structured interviews, and a review of electronic health record data conducted over a 12-month period following disclosure of results will allow for comparison of psychosocial and behavioral outcomes among parents of minors (ages 0-17) and adolescents (ages 11-17) in each group. DISCUSSION: These data will provide guidance about the risks and benefits of informing minors and their family members about clinically actionable, adult-onset genetic conditions and, in turn, help to ensure these patients receive care that promotes physical and psychosocial health. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03832985. Registered 6 February 2019

Potentially Identifying Variables Reported in 100 Qualitative Health Research Articles: Implications for Data Sharing and Secondary Analysis

There is a growing trend in social science research to share qualitative data in a repository for others to access. However, some researchers are reticent to share qualitative data. One major concern is how to de-identify qualitative data while maintaining adequate contextual detail to allow secondary users to meaningfully interpret de-identified data. To help inform discussions regarding qualitative data sharing, we reviewed 100 qualitative health science studies to determine what potentially identifying variables (PIVs) are reported in the published literature. There are relatively few PIVs reported in each qualitative study; the majority of studies (n=64) reported two or fewer PIVs. The most commonly reported PIVs were profession, sex or gender, and age. Our findings can help guide de-identification efforts going forward as presumably the PIVs that are most commonly reported provide essential contextual details that will also be needed by secondary users, while PIVs that are rarely reported may not provide essential contextual information for interpretation of data. This suggests it is possible to share qualitative data that are both de-identified and useful for secondary analysis. As data are shared, we recommend researchers mask study sites, as these may uniquely increase the chance of re-identification.In der sozialwissenschaftlichen Forschung gibt es einen wachsenden Trend, qualitative Daten in einem Repository für andere zugänglich zu machen. Einige Forscher*innen sind jedoch zurückhaltend, wenn es um die Weitergabe qualitativer Daten geht. Ein Hauptproblem für sie ist die Frage, wie anonymisiert und gleichzeitig ein angemessener Detailkontext beibehalten werden kann, damit Sekundärnutzer*innen Daten sinnvoll interpretieren können. Um die Diskussion über die gemeinsame Nutzung qualitativer Daten zu unterstützen, haben wir 100 qualitative gesundheitswissenschaftliche Studien darauf hin untersucht, welche potenziell identifizierenden Variablen (PIVs) berichtet wurden. In der Mehrheit der Studien (n=64) waren es relativ wenige, nämlich max. zwei PIVs. Die am häufigsten berichteten PIVs waren Beruf, Geschlecht oder Gender und Alter. Unsere Ergebnisse können als Orientierungshilfe für künftige De-Identifizierungsbemühungen dienen, da die am häufigsten berichteten PIVs vermutlich wesentliche kontextbezogene Details liefern, die auch von Sekundärnutzer*innen benötigt werden, während PIVs, die selten berichtet werden, möglicherweise keine wesentlichen kontextbezogenen Informationen für die Interpretation von Daten enthalten. Dies deutet darauf hin, dass es möglich ist, qualitative Daten weiterzugeben, die sowohl de-identifiziert als auch für Sekundäranalysen nützlich sind. Bei der Weitergabe von Daten empfehlen wir, die Studienorte zu maskieren, da diese die Wahrscheinlichkeit einer Identifizierung erhöhen können

Are we ready to share qualitative research data? Knowledge and preparedness among qualitative researchers, IRB Members, and data repository curators

Data sharing maximizes the value of data, which is time and resource intensive to collect. Major funding bodies in the United States (US), like the National Institutes of Health (NIH), require data sharing and researchers frequently share de-identified quantitative data. In contrast, qualitative data are rarely shared in the US but the increasing trend towards data sharing and open science suggest this may be required in future. Qualitative methods are often used to explore sensitive health topics raising unique ethical challenges regarding protecting confidentiality while maintaining enough contextual detail for secondary analyses. Here, we report findings from semi-structured in-depth interviews with 30 data repository curators, 30 qualitative researchers, and 30 IRB staff members to explore their experience and knowledge of QDS. Our findings indicate that all stakeholder groups lack preparedness for QDS. Researchers are the least knowledgeable and are often unfamiliar with the concept of sharing qualitative data in a repository. Curators are highly supportive of QDS, but not all have experienced curating qualitative data sets and indicated they would like guidance and standards specific to QDS. IRB members lack familiarity with QDS although they support it as long as proper legal and regulatory procedures are followed. IRB members and data curators are not prepared to advise researchers on legal and regulatory matters, potentially leaving researchers who have the least knowledge with no guidance. Ethical and productive QDS will require overcoming barriers, creating standards, and changing long held practices among all stakeholder groups

Enabling qualitative research data sharing using a natural language processing pipeline for deidentification: Moving beyond HIPAA Safe Harbor identifiers

OBJECTIVE: Sharing health research data is essential for accelerating the translation of research into actionable knowledge that can impact health care services and outcomes. Qualitative health research data are rarely shared due to the challenge of deidentifying text and the potential risks of participant reidentification. Here, we establish and evaluate a framework for deidentifying qualitative research data using automated computational techniques including removal of identifiers that are not considered HIPAA Safe Harbor (HSH) identifiers but are likely to be found in unstructured qualitative data. MATERIALS AND METHODS: We developed and validated a pipeline for deidentifying qualitative research data using automated computational techniques. An in-depth analysis and qualitative review of different types of qualitative health research data were conducted to inform and evaluate the development of a natural language processing (NLP) pipeline using named-entity recognition, pattern matching, dictionary, and regular expression methods to deidentify qualitative texts. RESULTS: We collected 2 datasets with 1.2 million words derived from over 400 qualitative research data documents. We created a gold-standard dataset with 280K words (70 files) to evaluate our deidentification pipeline. The majority of identifiers in qualitative data are non-HSH and not captured by existing systems. Our NLP deidentification pipeline had a consistent F1-score of ∼0.90 for both datasets. CONCLUSION: The results of this study demonstrate that NLP methods can be used to identify both HSH identifiers and non-HSH identifiers. Automated tools to assist researchers with the deidentification of qualitative data will be increasingly important given the new National Institutes of Health (NIH) data-sharing mandate

Assessing clinical research coordinator knowledge of good clinical practice: An evaluation of the state of the art and a test validation study

This paper describes the development and validation of a new 32-item test of knowledge of good clinical practice (GCP) administered to 625 clinical research coordinators. GCP training is mandated by study sponsors including the US National Institutes of Health. The effectiveness of training is rarely assessed, and the lack of validated tests is an obstacle to assessment. The GCP knowledge test was developed following evaluation of two existing widely used GCP tests to ensure it accurately reflects the content of current training. The final GCP knowledge test demonstrated good reliability

Development of a resource guide to help patients receive appropriate care

After 10 years researching physician wrongdoing (i.e., sexual violations, improper prescribing, and unnecessary procedures), we developed a resource guide to help patients receive appropriate care and respond to inappropriate care. We gathered evaluative patient feedback, engaged physicians, and disseminated the guide. It is available at beforeyourvisit.org

Barriers and facilitators to qualitative data sharing in the United States: A survey of qualitative researchers

Qualitative health data are rarely shared in the United States (U.S.). This is unfortunate because gathering qualitative data is labor and time-intensive, and data sharing enables secondary research, training, and transparency. A new U.S. federal policy mandates data sharing by 2023, and is agnostic to data type. We surveyed U.S. qualitative researchers (N = 425) on the barriers and facilitators of sharing qualitative health or sensitive research data. Most researchers (96%) have never shared qualitative data in a repository. Primary concerns were lack of participant permission to share data, data sensitivity, and breaching trust. Researcher willingness to share would increase if participants agreed and if sharing increased the societal impact of their research. Key resources to increase willingness to share were funding, guidance, and de-identification assistance. Public health and biomedical researchers were most willing to share. Qualitative researchers need to prepare for this new reality as sharing qualitative data requires unique considerations

Perceived barriers to assessing understanding and appreciation of informed consent in clinical trials: A mixed-method study

INTRODUCTION: Participants and research professionals often overestimate how well participants understand and appreciate consent information for clinical trials, and experts often vary in their determinations of participant\u27s capacity to consent to research. Past research has developed and validated instruments designed to assess participant understanding and appreciation, but the frequency with which they are utilized is unknown. METHODS: We administered a survey to clinical researchers working with older adults or those at risk of cognitive impairment ( RESULTS: We found that using a validated assessment of consent is relatively uncommon, being used by only 44% of researchers who had an opportunity. Factors that predicted adoption of validated assessments included not seeing the study sponsor as a barrier, positive attitudes toward assessments, and being confident that they had the resources needed to implement an assessment. The perceived barriers to adopting validated assessments of consent included lack of awareness, lack of knowledge, being unsure of how to administer such an assessment, and the burden associated with implementing this practice. CONCLUSIONS: Increasing the use of validated assessments of consent will require educating researchers on the practice and emphasizing very practical assessments, and may require Institutional Review Boards (IRBs) or study sponsors to champion the use of assessments

A randomized implementation trial to increase adoption of evidence-informed consent practices

INTRODUCTION: Several evidence-informed consent practices (ECPs) have been shown to improve informed consent in clinical trials but are not routinely used. These include optimizing consent formatting, using plain language, using validated instruments to assess understanding, and involving legally authorized representatives when appropriate. We hypothesized that participants receiving an implementation science toolkit and a social media push would have increased adoption of ECPs and other outcomes. METHODS: We conducted a 1-year trial with clinical research professionals in the USA ( RESULTS: Participants who engaged more with the toolkit were more likely to have tried to implement an ECP during the trial than participants less engaged with the toolkit or the active control group. However, there were no significant differences in the adoption of ECPs, intention to adopt, or positive attitudes. Participants reported the toolkit and social media push were satisfactory, and participating increased their awareness of ECPs. However, they reported lacking the time needed to engage with the toolkit more fully. CONCLUSIONS: Using an implementation science approach to increase the use of ECPs was only modestly successful. Data suggest that having institutional review boards recommend or require ECPs may be an effective way to increase their use

Chapter Mapping Jewish Identities

Through a comparion of etnographic research in the UK and Brazil, this chapter has examined now changing scientific and medical understandings regarding the origin, genealogical history and patrimony of the so-called Ashkenazi mutations have been diversely taken up and put to use in clinical/research contexts. It has explored the very differing differing differing consequences this can have for the way health care practitioners, scientists, patients and their families engage with and incorporate knowledge about hereditary BRCA mutations into scientific narratives, clinical practices and understandings of clinical/familial risk and identity