Is It Time to Share Qualitative Research Data?

Publishing publicly available interview data: an empirical example of the experience of publishing interview data

In September 2021 I made a collection of interview transcripts available for public use under a CreativeCommons license through the Princeton DataSpace. The interviews include 39 conversations I had with gig workers at AmazonFlex, Uber, and Lyft in 2019 as part of a study on automation efforts within these organizations. I made this decision because (1) I was required to contribute to a publicly available data set as a requirement of my funding and (2) I saw it as an opportunity to engage in the collaborative qualitative science experiments emerging in Science and Technology studies. This article documents my thought process and step-by-step design decisions for designing a study, gathering data, masking it, and publishing it in a public archive. Importantly, once I decided to publish these data, I determined that each choice about how the study would be designed and implemented had to be assessed for risk to the interviewee in a very deliberate way. It is not meant to be comprehensive and cover every possible condition a researcher may face while producing qualitative data. I aimed to be transparent both in my interview data and the process it took to gather and publish these data. I use this article to illustrate my thought process as I made each design decision for this study in hopes that it could be useful to a future researcher considering their own data publishing process.

Reflection over compliance: Critiquing mandatory data sharing policies for qualitative research

Many journals are moving towards a 'Mandatory Inclusion of Raw Data' (MIRD) model of data sharing, where it is expected that raw data be publicly accessible at article submission. While open data sharing is beneficial for some research topics and methodologies within health psychology, in other cases it may be ethically and epistemologically questionable. Here, we outline several questions that qualitative researchers might consider surrounding the ethics of open data sharing. Overall, we argue that universal open raw data mandates cannot adequately represent the diversity of qualitative research, and that MIRD may harm rigorous and ethical research practice within health psychology and beyond. Researchers should instead find ways to demonstrate rigour thorough engagement with questions surrounding data sharing. We propose that all researchers utilise the increasingly common 'data availability statement' to demonstrate reflexive engagement with issues of ethics, epistemology and participant protection when considering whether to open data.

"I'm telling you my story, not publishing a blog": Considerations and suggestions on data sharing in qualitative health psychology research on sensitive topics

Qualitative research plays a pivotal role in health psychology, offering insights into the intricacies of health-related issues. However, the specificity of qualitative methodology presents challenges in adhering to standard open science principles, including data sharing. The guidelines to address these issues are limited. Drawing from the author's experience in conducting in-depth interviews with middle-aged and older adults regarding their sexuality, this article discusses various challenges in implementing data sharing requirements. It emphasizes factors like participants' reasonable reluctance to share in specific populations, the depth of personal information gleaned from comprehensive interviews, concerns surrounding potential data misuse both within and outside academic circles, and the complex issue of obtaining informed consent. A universal approach to data sharing in qualitative research proves impractical, emphasizing the necessity for adaptable, context-specific guidelines that acknowledge the methodology's nuances. Striking a balance between transparency and ethical responsibility requires tailored strategies and thoughtful consideration.

Re-use of research data in the social sciences. Use and users of digital data archive

The aim of this paper is to investigate the re-use of research data deposited in digital data archive in the social sciences. The study examines the quantity, type, and purpose of data downloads by analyzing enriched user log data collected from Swiss data archive. The findings show that quantitative datasets are downloaded increasingly from the digital archive and that downloads focus heavily on a small share of the datasets. The most frequently downloaded datasets are survey datasets collected by research organizations offering possibilities for longitudinal studies. Users typically download only one dataset, but a group of heavy downloaders form a remarkable share of all downloads. The main user group downloading data from the archive are students who use the data in their studies. Furthermore, datasets downloaded for research purposes often, but not always, serve to be used in scholarly publications. Enriched log data from data archives offer an interesting macro level perspective on the use and users of the services and help understanding the increasing role of repositories in the social sciences. The study provides insights into the potential of collecting and using log data for studying and evaluating data archive use.

A guide for social science journal editors on easing into open science

Journal editors have a large amount of power to advance open science in their respective fields by incentivising and mandating open policies and practices at their journals. The Data PASS Journal Editors Discussion Interface (JEDI, an online community for social science journal editors: www.dpjedi.org ) has collated several resources on embedding open science in journal editing ( www.dpjedi.org/resources ). However, it can be overwhelming as an editor new to open science practices to know where to start. For this reason, we created a guide for journal editors on how to get started with open science. The guide outlines steps that editors can take to implement open policies and practices within their journal, and goes through the what, why, how, and worries of each policy and practice. This manuscript introduces and summarizes the guide (full guide: https://doi.org/10.31219/osf.io/hstcx ).

Exchanging words: Engaging the challenges of sharing qualitative research data

In January 2023, a new NIH policy on data sharing went into effect. The policy applies to both quantitative and qualitative research (QR) data such as data from interviews or focus groups. QR data are often sensitive and difficult to deidentify, and thus have rarely been shared in the United States. Over the past 5 y, our research team has engaged stakeholders on QR data sharing, developed software to support data deidentification, produced guidance, and collaborated with the ICPSR data repository to pilot the deposit of 30 QR datasets. In this perspective article, we share important lessons learned by addressing eight clusters of questions on issues such as where, when, and what to share; how to deidentify data and support high-quality secondary use; budgeting for data sharing; and the permissions needed to share data. We also offer a brief assessment of the state of preparedness of data repositories, QR journals, and QR textbooks to support data sharing. While QR data sharing could yield important benefits to the research community, we quickly need to develop enforceable standards, expertise, and resources to support responsible QR data sharing. Absent these resources, we risk violating participant confidentiality and wasting a significant amount of time and funding on data that are not useful for either secondary use or data transparency and verification.

Opportunities, challenges and tensions: Open science through a lens of qualitative social psychology

In recent years, there has been a focus in social psychology on efforts to improve the robustness, rigour, transparency and openness of psychological research. This has led to a plethora of new tools, practices and initiatives that each aim to combat questionable research practices and improve the credibility of social psychological scholarship. However, the majority of these efforts derive from quantitative, deductive, hypothesis-testing methodologies, and there has been a notable lack of in-depth exploration about what the tools, practices and values may mean for research that uses qualitative methodologies. Here, we introduce a Special Section of BJSP: Open Science, Qualitative Methods and Social Psychology: Possibilities and Tensions. The authors critically discuss a range of issues, including authorship, data sharing and broader research practices. Taken together, these papers urge the discipline to carefully consider the ontological, epistemological and methodological underpinnings of efforts to improve psychological science, and advocate for a critical appreciation of how mainstream open science discourse may (or may not) be compatible with the goals of qualitative research.

When open data closes the door: A critical examination of the past, present and the potential future for open data guidelines in journals

Opening data promises to improve research rigour and democratize knowledge production. But it also presents practical, theoretical, and ethical considerations for qualitative researchers in particular. Discussion about open data in qualitative social psychology predates the replication crisis. However, the nuances of this ongoing discussion have not been translated into current journal guidelines on open data. In this article, we summarize ongoing debates about open data from qualitative perspectives, and through a content analysis of 261 journals we establish the state of current journal policies for open data in the domain of social psychology. We critically discuss how current common expectations for open data may not be adequate for establishing qualitative rigour, can introduce ethical challenges, and may place those who wish to use qualitative approaches at a disadvantage in peer review and publication processes. We advise that future open data guidelines should aim to reflect the nuance of arguments surrounding data sharing in qualitative research, and move away from a universal "one-size-fits-all" approach to data sharing. This article outlines the past, present, and the potential future of open data guidelines in social-psychological journals. We conclude by offering recommendations for how journals might more inclusively consider the use of open data in qualitative methods, whilst recognizing and allowing space for the diverse perspectives, needs, and contexts of all forms of social-psychological research.

Reasons for qualitative psychologists to share human data

Qualitative data sharing practices in psychology have not developed as rapidly as those in parallel quantitative domains. This is often explained by numerous epistemological, ethical and pragmatic issues concerning qualitative data types. In this article, I provide an alternative to the frequently expressed, often reasonable, concerns regarding the sharing of qualitative human data by highlighting three advantages of qualitative data sharing. I argue that sharing qualitative human data is not by default 'less ethical', 'riskier' and 'impractical' compared with quantitative data sharing, but in some cases more ethical, less risky and easier to manage for sharing because (1) informed consent can be discussed, negotiated and validated; (2) the shared data can be curated by special means; and (3) the privacy risks are mainly local instead of global. I hope this alternative perspective further encourages qualitative psychologists to share their data when it is epistemologically, ethically and pragmatically possible.

A primer for choosing, designing and evaluating registered reports for qualitative methods

Registered reports are a publication format that involves peer reviewing studies both before and after carrying out research procedures. Although registered reports were originally developed to combat challenges in quantitative and confirmatory study designs, today registered reports are also available for qualitative and exploratory work. This article provides a brief primer that aims to help researchers in choosing, designing, and evaluating registered reports, which are driven by qualitative methods.

A primer for choosing, designing and evaluating registered reports for qualitative methods

Registered reports are a publication format that involves peer reviewing studies both before and after carrying out research procedures. Although registered reports were originally developed to combat challenges in quantitative and confirmatory study designs, today registered reports are also available for qualitative and exploratory work. This article provides a brief primer that aims to help researchers in choosing, designing, and evaluating registered reports, which are driven by qualitative methods.

Expanding the ethnographic toolkit: Using medical documents to include kinless older adults living with dementia in qualitative research

Ethnographic research with cognitively impaired older adults can be challenging, in part because cognitive impairment raises questions about the ability to provide informed consent. Relying on proxy consent is a commonly used strategy, but often excludes people with dementia who lack close kin (de Medeiros, Girling, & Berlinger, 2022). In this paper, we describe how we have analyzed existing research data from a well-established and ongoing prospective cohort study, the Adult Changes in Thought Study, along with unstructured text from the medical records of participants who had no living spouse or adult children when they developed dementia, as a way of studying the circumstances, life trajectories, caregiving resources, and care needs of this vulnerable and difficult-to-research group. In this article, we detail this methodology, exploring what can and cannot be gleaned from it, what the ethical implications may be, and how and whether this type of research can be considered ethnographic. In conclusion, we argue that collaborative interdisciplinary research using existing, longitudinal research data and text from medical records deserves to be considered as a potentially useful addition to the ethnographic toolkit. We anticipate that this is a methodology that could be applied more broadly, and paired with more traditional ethnographic methods, might be one way to make research with this population more inclusive.

“One button in my pocket instead of the smartphone”: A methodological assemblage connecting self-research and autoethnography in a digital disengagement study

In this article we present a “methodological assemblage” and technological prototype connecting autoethnography to the practices of self-research in personal science. As an experimental process of personal data gathering, one of the authors used a low-tech device for the active registration of events and their perception, in a case study on disengaging from his smartphone. For the visualization of this data the other author developed a novel treatment of fieldnotes in analytic autoethnography through an open source, interactive notebook. As a proof of concept, we provide a detailed description of the corresponding protocol and prototype, also making available the notebook source code and the quantitative-qualitative open dataset behind its visualization. This highly personalized methodological assemblage represents a technological appropriation that combines self-research and autoethnography—two disciplinary perspectives that share a type of inquiry based on situated knowledge, departing from personal data as empirical basis. Despite recent autoethnographic literature on the phenomenon of self-tracking and the Qualified Self, our contribution addresses a lack of studies in the opposite direction: how the practice of self-research mediated by technology can lead to bridges with digital autoethnography, validating their hybrid combination. After addressing diverse conceptual, ontological and methodological similarities and differences between personal science and autoethnography, we contextualize the case study of digital disengagement and provide a detailed description of the developed self-protocol and the tools used for data gathering.

Qualitative data sharing practices in clinical trials in the UK and Ireland: towards the production of good practice guidance

Background: Data sharing enables researchers to conduct novel research with previously collected datasets, thus maximising scientific findings and cost effectiveness, and reducing research waste. The value of sharing, even de-identified, quantitative data from clinical trials is well recognised with a moderated access approach recommended. While substantial challenges to sharing quantitative data remain, there are additional challenges for sharing qualitative data in trials. Incorporating the necessary information about how qualitative data will be shared into already complex trial recruitment and consent processes proves challenging. The aim of this study was to explore whether and how trial teams share qualitative data collected as part of the design, conduct, analysis, or delivery of clinical trials. Methods: Phase 1 involved semi-structured, in-depth qualitative interviews and focus groups with key trial stakeholder groups including trial managers and clinical trialists (n=3), qualitative researchers in trials (n=9), members of research funding bodies (n=2) and trial participants (n=1). Data were analysed using thematic analysis. In Phase 2, we conducted a content analysis of 16 participant information leaflets (PIL) and consent forms (CF) for trials that collected qualitative data. Results: Three key themes were identified from our Phase 1 findings: ' Understanding and experiences of the potential benefits of sharing qualitative data from trials', 'Concerns about qualitative data sharing', and ' Future guidance and funding'. In phase 2, the PILs and CFs received revealed that the benefits of data sharing for participants were only explained in two of the study documents. Conclusions: The value of sharing qualitative data was acknowledged, but there are many uncertainties as to how, when, and where to share this data. In addition, there were ethical concerns in relation to the consent process required for qualitative data sharing in trials. This study provides insight into the existing practice of qualitative data sharing in trials.

Psychobiographies of social change agents: Introduction to the Special Issue

This Special Issue of Journal of Personality, focused on psychobiographies of social change agents, aims to make contributions to the field in terms of content, method, and process. The content of the issue is focused on understanding people who powerfully impact their world, from eminent global leaders to everyday change agents. The contributions to the Special Issue are unified by their adoption of psychobiographical methods, though as a set they offer both excellent representations of common psychobiographical approaches as well as vital innovations in this tradition. The process of curating this Special Issue sought to make several interventions in typical practices, including the cultivation of an intentional community of scholars representing both experienced and fledgling psychobiographers, the pursuit of a relational approach to publishing, and the adoption of open science practices. Psychobiography has an important role to play in contemporary personality psychology and we hope this Special Issue will itself serve as a foundation for continued innovation in the field.

A qualitative investigation of the phenomenology of muscle dysmorphia: Part 1

Muscle dysmorphia (MD) is a psychological disorder defined by preoccupation with one's perceived lack of muscularity and/or leanness, causing significant functional impairment. Studies of individuals with diagnosed MD are rare and no large-scale qualitative studies of the disorder exist. We conducted a qualitative study exploring the lived experiences of 29 individuals with diagnosed MD. Using reflexive thematic analysis, we generated five themes capturing the core features of MD. We identified two distinct phenotypes of MD: a "muscular/lean phenotype" focused on both gaining muscle and remaining lean, and a "muscular phenotype" with a sole preoccupation of increasing muscle mass. Participants also described their physique goals as never-obtained "moving goalposts", differed in their desire for muscularity versus leanness, and experienced fluctuations in body dissatisfaction during "cutting" versus "bulking" phases, and pre- versus post-workout. Almost all participants reported avoiding public body exposure and compulsively mirror-checking. Most were rigorous dieters who meticulously tracked their caloric and macronutrient intake, and were obsessive about meeting protein targets. Disruptions to dieting and training were often minimised by compromising their social lives. Low self-esteem appeared a predisposing factor for MD, while social comparison, body image distortion, and integration of MD into one's self-identity may represent maintaining factors. Additional clinically valuable insights into MD's phenomenology are discussed in detail.

Understanding Sexual Assault Survivors’ Perspectives on Archiving Qualitative Data: Implications for Feminist Approaches to Open Science

The open science movement has framed data sharing as necessary and achievable best practices for high-quality science. Feminist psychologists have complicated that narrative by questioning the purpose of data sharing across different paradigms, methodologies, and research populations. In these debates, the academic community has centered the needs and voices of researchers, and participants’ perspectives are largely missing from this literature. In this study, we sought to understand how research participants feel about sharing qualitative data on a sensitive subject—sexual victimization. As part of a participatory action research project, we conducted qualitative interviews with sexual assault survivors about their post-assault help-seeking experiences. The federal funding agency that supported this project requires researchers to archive de-identified data in a national data repository (the National Archive of Criminal Justice Data [NACJD]). All participants consented to archiving data, and the vast majority expressed positive views about data sharing because they wanted to help other survivors. Participants emphasized that our participatory action research approach and our stated goal of helping survivors were important considerations in their decisions regarding data sharing. Researchers should obtain informed consent from their participants for data sharing/archiving, and discuss their dissemination plans during the informed consent process.

Advances in transparency and reproducibility in the social sciences

Worries about a "credibility crisis" besieging science have ignited interest in research transparency and reproducibility as ways of restoring trust in published research. For quantitative social science, advances in transparency and reproducibility can be seen as a set of developments whose trajectory predates the recent alarm. We discuss several of these developments, including preregistration, data-sharing, formal infrastructure in the form of resources and policies, open access to research, and specificity regarding research contributions. We also discuss the spillovers of this predominantly quantitative effort towards transparency for qualitative research. We conclude by emphasizing the importance of mutual accountability for effective science, the essential role of openness for this accountability, and the importance of scholarly inclusiveness in figuring out the best ways for openness to be accomplished in practice.

A Content Analysis of 100 Qualitative Health Research Articles to Examine Researcher-Participant Relationships and Implications for Data Sharing

We conducted a qualitative content analysis of health science literature (N = 100) involving qualitative interviews or focus groups. Given recent data sharing mandates, our goal was to characterize the nature of relationships between the researchers and participants to inform ethical deliberations regarding qualitative data sharing and secondary analyses. Specifically, some researchers worry that data sharing might harm relationships, while others claim that data cannot be analyzed absent meaningful relationships with participants. We found little evidence of relationship building with participants. The majority of studies involve single encounters (95%), lasting less than 60 min (59%), with less than half of authors involved in primary data collection. Our findings suggest that relationships with participants might not pose a barrier to sharing some qualitative data collected in the health sciences and speak to the feasibility in principle of secondary analyses of these data.

Qualitative Data Sharing: Participant Understanding, Motivation, and Consent

Expectations to share data underlying studies are increasing, but research on how participants, particularly those in qualitative research, respond to requests for data sharing is limited. We studied research participants' willingness to, understanding of, and motivations for data sharing. As part of a larger qualitative study on abortion reporting, we conducted interviews with 64 cisgender women in two states in early 2020 and asked for consent to share de-identified data. At the end of interviews, we asked participants to reflect on their motivations for agreeing or declining to share their data. The vast majority of respondents consented to data sharing and reported that helping others was a primary motivation for agreeing to share their data. However, a substantial number of participants showed a limited understanding of the concept of "data sharing." Additional research is needed on how to improve participants' understanding of data sharing and thus ensure fully informed consent.

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.

Data Curation Implications of Qualitative Data Reuse and Big Social Research

Objective: Big social data (such as social media and blogs) and archived qualitative data (such as interview transcripts, field notebooks, and diaries) are similar, but their respective communities of practice are under-connected. This paper explores shared challenges in qualitative data reuse and big social research and identifies implications for data curation. Methods: This paper uses a broad literature search and inductive coding of 300 articles relating to qualitative data reuse and big social research. The literature review produces six key challenges relating to data use and reuse that are present in both qualitative data reuse and big social research—context, data quality, data comparability, informed consent, privacy & confidentiality, and intellectual property & data ownership. Results: This paper explores six key challenges related to data use and reuse for qualitative data and big social research and discusses their implications for data curation practices. Conclusions: Data curators can benefit from understanding these six key challenges and examining data curation implications. Data curation implications from these challenges include strategies for: providing clear documentation; linking and combining datasets; supporting trustworthy repositories; using and advocating for metadata standards; discussing alternative consent strategies with researchers and IRBs; understanding and supporting deidentification challenges; supporting restricted access for data; creating data use agreements; supporting rights management and data licensing; developing and supporting alternative archiving strategies. Considering these data curation implications will help data curators support sounder practices for both qualitative data reuse and big social research.

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.

A study protocol of qualitative data sharing practices in clinical trials in the UK and Ireland: towards the production of good practice guidance

Background: Data sharing enables researchers to conduct novel research with previously collected data sets, thus maximising scientific findings and cost effectiveness, and reducing research waste. The value of sharing anonymised data from clinical trials is well recognised with a moderated access approach recommended. While substantial challenges to data sharing remain, there are additional challenges for qualitative data. Qualitative data including videos, interviews, and observations are often more readily identifiable than quantitative data. Existing guidance from UK Economic and Social Research Council applies to sharing qualitative data but does not address the additional challenges related to sharing qualitative data collected within trials, including the need to incorporate the necessary information and consent into already complex recruitment processes, with the additional sensitive nature of health-related data. Methods: Work package 1 will involve separate focus group interviews with members of each stakeholder group: trial managers, clinical trialists, qualitative researchers, members of research funding bodies and trial participants who have been involved in qualitative research. Data will be analysed using thematic analysis and managed within QSR NVivo to enhance transparency. Work package 2 will involve a documentary analysis of current consent procedures for qualitative data collected as part of the conduct of clinical trials. We will include documents such as participant information leaflets and consent forms for the qualitative components in trials. We will extract data such as whether specific clauses for data sharing are included in the consent form. Content analysis will be used to analyse whether and how consent is being obtained for qualitative data sharing. Conclusions: This study will provide insight into the existing practice of sharing of qualitative data in clinical trials and the current issues and opportunities, to help shape future research and development of guidance to encourage maximum learning to be gained from this valuable data.

A study protocol of qualitative data sharing practices in clinical trials in the UK and Ireland: towards the production of good practice guidance

Background: Data sharing enables researchers to conduct novel research with previously collected data sets, thus maximising scientific findings and cost effectiveness, and reducing research waste. The value of sharing anonymised data from clinical trials is well recognised with a moderated access approach recommended. While substantial challenges to data sharing remain, there are additional challenges for qualitative data. Qualitative data including videos, interviews, and observations are often more readily identifiable than quantitative data. Existing guidance from UK Economic and Social Research Council applies to sharing qualitative data but does not address the additional challenges related to sharing qualitative data collected within trials, including the need to incorporate the necessary information and consent into already complex recruitment processes, with the additional sensitive nature of health-related data. Methods: Work package 1 will involve separate focus group interviews with members of each stakeholder group: trial managers, clinical trialists, qualitative researchers, members of research funding bodies and trial participants who have been involved in qualitative research. Data will be analysed using thematic analysis and managed within QSR NVivo to enhance transparency. Work package 2 will involve a documentary analysis of current consent procedures for qualitative data collected as part of the conduct of clinical trials. We will include documents such as participant information leaflets and consent forms for the qualitative components in trials. We will extract data such as whether specific clauses for data sharing are included in the consent form. Content analysis will be used to analyse whether and how consent is being obtained for qualitative data sharing. Conclusions: This study will provide insight into the existing practice of sharing of qualitative data in clinical trials and the current issues and opportunities, to help shape future research and development of guidance to encourage maximum learning to be gained from this valuable data.

Research Participant Views regarding Qualitative Data Sharing

We found no studies in the United States that explored research participants' perspectives about sharing their qualitative data. We present findings from interviews with 30 individuals who participated in sensitive qualitative studies to explore their understanding and concerns regarding qualitative data sharing. The vast majority supported sharing qualitative data so long as their data were deidentified and shared only among researchers. However, they raised concerns about confidentiality if the data were not adequately deidentified and about misuse by secondary users if data were shared beyond the research community. These concerns, though, did not deter them from participating in research. Notably, participants hoped their data would be shared and may have expected or assumed this was already happening. While many could not recollect details about data-sharing plans for studies in which they participated, they trusted researchers and institutions to appropriately handle data sharing. If individuals view data sharing as an extension or integral part of their participation in qualitative research, then researchers may have a stronger obligation to share qualitative data than previously thought. Guidelines and tools to assist researchers and institutional review board members in ethical and responsible qualitative data sharing are urgently needed.

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.

Qualitative Data Management and Analysis within a Data Repository

Data repositories can support secure data management for multi-institutional and geographically dispersed research teams. Primarily designed to provide secure access, storage, and sharing of quantitative data, limited focus has been given to the unique considerations of data repositories for qualitative research. We share our experiences of using a data repository in a large qualitative nursing research study. Over a 27-month period, data collected by this 15-member team from 83 participants included photos, audio recordings and transcripts of interviews, and field notes. The data repository supported the secure collection, storage, and management of over 1,800 files with data. However, challenges were introduced during analysis that required negotiations about the structure and processes of the data repository. We discuss strengths and limitations of data repositories, and introduce practical strategies for developing a data management plan for qualitative research, which is supported through a data repository.

Examining Data Repository Guidelines for Qualitative Data Sharing

Qualitative data provide rich information on research questions in diverse fields. Recent calls for increased transparency and openness in research emphasize data sharing. However, qualitative data sharing has yet to become the norm internationally and is particularly uncommon in the United States. Guidance for archiving and secondary use of qualitative data is required for progress in this regard. In this study, we review the benefits and concerns associated with qualitative data sharing and then describe the results of a content analysis of guidelines from international repositories that archive qualitative data. A minority of repositories provide qualitative data sharing guidelines. Of the guidelines available, there is substantial variation in whether specific topics are addressed. Some topics, such as removing direct identifiers, are consistently addressed, while others, such as providing an anonymization log, are not. We discuss the implications of our study for education, best practices, and future research.

Communication in pediatric oncology: State of the field and research agenda

From the time of diagnosis through either survivorship or end of life, communication between healthcare providers and patients or parents can serve several core functions, including fostering healing relationships, exchanging information, responding to emotions, managing uncertainty, making decisions, and enabling patient/family self-management. We systematically reviewed all studies that focused on communication between clinicians and patients or parents in pediatric oncology, categorizing studies based on which core functions of communication they addressed. After identifying gaps in the literature, we propose a research agenda to further the field.