International Journal of Qualitative Methods最新文献

{"title":"Working With Large Qualitative Datasets: Key Processes From an Implementation Study in a Complex Clinical Setting.","authors":"Marin Schmitt, Karen Kavanaugh, Karen Gralton, Rosemary White-Traut, Debra Brandon, Christina Rigby-McCotter, Kathleen Norr","doi":"10.1177/16094069261445335","DOIUrl":"10.1177/16094069261445335","url":null,"abstract":"<p><p>Collecting and analyzing qualitative research with large datasets is inherently complex and often difficult to convey in traditional manuscripts. Contemporary guidance on managing such datasets, especially those with multiple data sources, is limited. Implementation science, which studies and tests methods to promote uptake of evidence-based practices into routine use, often requires complex qualitative data and analysis and faces unique challenges. These challenges include multiple data collection time points and the need for rapid analysis and feedback to sites. In this paper we reflect on the data collection, management, and analysis of over 400 pieces of qualitative data from three different sources (semi-structured interviews, meeting minutes, and open-ended survey responses) as part of a large implementation study. The data discussed are derived from a type 3 Hybrid-design study of H-HOPE (Hospital to Home: Optimizing the Preterm Infant's Environment) in six diverse neonatal intensive care units (NICUs). We first thoroughly outline the methods our team used in collecting and analyzing our large qualitative dataset. We then discuss four key processes that aided our data collection, management, and analysis: structure and consistency, prompt responsive alterations to site specific procedures, an iterative and extensive analysis approach led by case summaries, and utilization of both an initial 'quick' and more in-depth traditional qualitative analysis approaches. Recommendations for future studies working with large qualitative data sets with multiple sources of data are discussed.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"25 ","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13348785/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148425521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"I make those in my imagination\": A guide to prioritizing children's agency and inclusion in research with the Make-and-Tell arts-based method.","authors":"Eline L Lenne","doi":"10.1177/16094069261462094","DOIUrl":"10.1177/16094069261462094","url":null,"abstract":"<p><p>Ongoing calls for more inclusive, child-centered research practices have led social work, psychology, and medical researchers to develop child-sensitive approaches when working with younger populations, especially disabled, neurodiverse, gender-creative, or other explicitly minoritized children. Using the theoretical frameworks of <i>being and becoming, growing sideways</i>, and <i>queer potentiality</i>, this article provides a practical guide for designing and implementing Make-and-Tell, an arts-based method that prioritizes children's agency and inclusivity. Drawing on two studies I conducted with children ages five to ten years old, many of whom were neurodiverse and all of whom identified as gender-creative, I outline step-by-step procedures, strategies for addressing common challenges, and reflections on ethical and practical considerations. This guide is intended to support researchers in creating child-oriented research protocols that accommodate the specific ages, abilities, and needs of participants.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"25 ","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13374731/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148473590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Contributions of Qualitative Methods to Real-Time Implementation Strategy Design: A Case Study Linking Justice Involved Individuals at Risk for HIV to Pre-exposure Prophylaxis.","authors":"Robin T Higashi, Timothy P Hogan, Emily C Repasky, Jessica Lee, M Brynn Torres, Julia L Marcus, Barry-Lewis Harris, Ank E Nijhawan, Douglas Krakower","doi":"10.1177/16094069261426142","DOIUrl":"10.1177/16094069261426142","url":null,"abstract":"<p><p>Pre-exposure prophylaxis (PrEP) exemplifies a medical advance that is highly efficacious in reducing an individual's risk of acquiring HIV. However, the use of PrEP remains considerably suboptimal in communities that could benefit from it most, especially in the southern United States where HIV infection rates are highest. We conducted a study using both qualitative methods and implementation science to develop and deploy a multicomponent implementation strategy to link individuals being released from jail to PrEP services in a southern US city. Implementation science supports the translation of evidence-based strategies from clinical knowledge to routine use; simultaneously, qualitative methodologies, given their emphasis on \"how\" to advance adoption, execution, and sustainment, are critical to implementation science. Our study design for supporting individuals along the \"jail-to-community continuum\" was rooted in the EPIS (Exploration-Preparation-Implementation-Sustainment) framework and the socioecological model. We began with iterative qualitative data collection involving semi-structured interviews, focus groups, and a community summit with formerly incarcerated individuals, jail clinicians and staff, and members of community organizations who work with justice involved individuals and those who provide PrEP and related services. Following rapid qualitative analysis, we drew on implementation mapping principles to create an action plan that guided the development of implementation strategies for PrEP. Our analysis plan will evaluate the feasibility, effectiveness, and sustainability of our multicomponent implementation strategy. We conclude by offering recommendations based on lessons learned and reflect on the synergistic relationship between qualitative methods and implementation science.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"25 ","pages":""},"PeriodicalIF":7.2,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13128100/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147822129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generative AI in Qualitative Research and Related Transparency Problems: A Novel Heuristic for Disclosing Uses of AI","authors":"Kyle M. L. Jones","doi":"10.1177/16094069251404329","DOIUrl":"https://doi.org/10.1177/16094069251404329","url":null,"abstract":"Generative Artificial Intelligence (AI) tools, particularly large language models (LLMs), are rapidly transforming qualitative data analysis by offering unprecedented speed and scale. However, this integration introduces significant challenges to methodological transparency due to the algorithmic opacity of these “black-box” systems and their hidden decision points. Traditional qualitative reporting guidelines predate generative AI and lack specific guidance for disclosing AI usage. This paper addresses this critical gap by introducing a novel heuristic framework that poses 20 questions across five key themes: The Research Team, Participant Interaction, Study Design, Data Practices, and Data Analysis, providing disclosure actions for each. This framework blends and augments existing frameworks, aligning with principles to guide researchers in meticulously documenting their AI-mediated analytic choices. Methodologically, the framework advances the field by requiring explicit reporting on: the roles of AI tools and the AI literacy of the human research team; AI’s involvement in participant communication, informed consent processes, and safeguards for sensitive demographic data; the alignment of AI tools with theoretical frameworks, their influence on sampling strategies, and discussions during IRB review; data storage, AI’s role in data creation (e.g., synthetic data, transcription, interview protocols), and its assistance in determining data saturation and participant checking; and the precise contributions of AI to coding and thematic categorization, alongside detailed documentation of iterative human-AI interactions and prompts used. By fostering rigorous audit trails and comprehensive documentation, the framework aims to maximize transparency, ensure methodological rigor, and uphold ethical standards in AI-augmented qualitative inquiry, thereby enhancing the credibility of findings.","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147904839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"D <i>eco</i> lonizing the Soil, D <i>eco</i> lonizing the Soul: Gothic Black Feminism and the Ecological Mirror","authors":"Monyae A. Kerney, Natalie Malone","doi":"10.1177/16094069251396872","DOIUrl":"https://doi.org/10.1177/16094069251396872","url":null,"abstract":"The current study employed interpretative phenomenological analysis and Gothic Black feminist thought to examine how nonbinary Black womxn (NBBW) in the United States conceptualize their gendered-racial identity and experiences in relation to nature. We recruited N = 11 participants using purposive sampling. Participants completed individual semi-structured qualitative interviews and photo elicitation to better understand how nature reflected and connected to their gendered-racial identity. Results comprised seven co-constructed themes referred to as the Seven Ecological Wisdoms: (1) Wisdom 1: Tripartite Consciousness and the Multidimensionality of Being, (2) Wisdom 2: Boundlessness and the Expansivity of Existence, (3) Wisdom 3: Seasonal Transformation and the Fluidity of Change (sub-wisdoms: Seasonal Transformation and Constant State of Flow), (4) Wisdom 4: The Deep Dive of Self-Discovery, (5) Wisdom 5: Hardship and Perseverance, (6) Wisdom 6: The Complexities of Community (sub-wisdoms: Community in Balance and The Imbalance of Power, Provision, and Reciprocal Care) and (7) Wisdom 7: Diversity is Naturally Occurring. Implications advocate for the integration of nature via a Gothic Black feminist framework to nuance how US Black womxn’s gendered-racial experiences are conceptualized and addressed in decolonial research and practice.","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147891486","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attentiveness as a Methodological Approach for Including Community Partners in Qualitative Health Data Analysis","authors":"Vishnu Subrahmanyam, Elise Smith","doi":"10.1177/16094069251332428","DOIUrl":"https://doi.org/10.1177/16094069251332428","url":null,"abstract":"Health science funding agencies incentivize qualitative community-based research to promote inclusion and better address the health of historically exploited or excluded communities. However, in this paper, we demonstrate that such incentivizing may result in an exercise where minimal inclusion requirements are sought to expedite the research process while proper methods for community inclusion in qualitative health research are limited. Researchers may choose to recruit from vulnerable populations and include community representatives in advisory capacities but exclude the same vulnerable populations from participating in less convenient parts of the research process such as data analysis and interpretation. We argue that this is unethical as it undervalues community participation and serves to reify oppressive power structures that community-based participatory research (CBPR) strives to move away from. In this paper, we draw from feminist ethics and science and technology studies (STS) of care to introduce attentiveness as an analytic that modifies the relationships between researchers and community partners within all steps of research in ways that foreground community expertise and lived experience to produce transformative biomedical research based in health justice. First, we highlight the ethical rationales for community inclusion in qualitative data analysis through meaningful inclusion and epistemic justice, and provide researchers within CBPR normative grounding to support their methodological practice. Second, we describe attentiveness and demonstrate how inclusion within CBPR can be modified to generate novel ways of working with community partners during qualitative data analysis. Attentiveness thus bears significant epistemic potential in reworking longstanding qualitative research practices in CBPR that emphasize health justice.","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147915240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting Inclusivity in Research: Lessons From Four Group Concept Mapping Studies","authors":"Juping Yu, Megan Elliott, Molly Curtis, David Pontin, Sarah Wallace, C Wallace","doi":"10.1177/16094069251329732","DOIUrl":"https://doi.org/10.1177/16094069251329732","url":null,"abstract":"Many key groups of people (e.g., older people, disabled people and minoritised people) are at risk of being excluded from research, which will affect the generalisability, quality, relevance, and integrity of the research findings and conclusions. However, ways of making research more inclusive have not been adequately explored. Appropriate strategies to maximise the participation of marginalised populations with diverse viewpoints, expertise, and experience are needed to enable them to make meaningful contributions. In this article, we draw lessons from four case studies that used Group Concept Mapping (a type of participatory, consensus research to generate agreement around a topic of interest within a group, community or society). We reflect on how our research was adapted to engage people with diverse needs (e.g., older/frail people, disabled people, people with language barriers, bilingual participants, and people lacking digital skills) in research. This paper highlights the importance of participatory, time and resources, ethical, and intersectionality considerations to enable marginalised populations to be heard and make significant contributions to research.","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147890381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applying Realist Retroduction to EHR-Based Clinical Decision Support Tool Development.","authors":"Suzanne Morrissey, Arwen Bunce, Jenna Donovan, Brenda McGrath, Laura Gottlieb, Maura Pisciotta, Shelby Watkins, Rachel Gold","doi":"10.1177/16094069251326415","DOIUrl":"https://doi.org/10.1177/16094069251326415","url":null,"abstract":"<p><p>The application of realist-informed approaches to implementation research can produce answers to why, for whom and under what circumstances social determinants of health interventions work. In the context of a study to develop and test EHR-based clinical decision support tools that suggest adjusting care plans in response to patient-reported financial, housing, food, transportation, and utilities insecurity, the authors applied an innovative use of realist principles in a bounded, mid-study task. This paper demonstrates how realist retroduction can be applied in intervention development processes. Retroduction proved useful in identifying the often intangible clinical needs and preferences that affected decision support tool desirability and use, which then guided the revision of five tools prior to a formal trial. This paper illustrates how data from the study development phases were put in service of retroductive steps that, through the identification of tentative program theories, guided revision of the pilot electronic tools to better meet clinic needs in the study trial phase. Applying retroductive thinking to establish what may be more or less effective under real-world conditions before participants are recruited is a productive, pragmatic form of researcher/stakeholder co-design that seeks to achieve results without wasting clinical teams' time.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12380379/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144974595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"\"We Have a Ways to Go, but I Think You've Taken the Steps to Get Us There\": Engaging Community Partners in Qualitative Analysis Using the RADaR Technique.","authors":"Analay Perez, Alexandra E Harper, M Miaisha Mitchell, Daphne C Watkins, Linda Cottler, Sergio Aguilar-Gaxiola, Susan L Murphy","doi":"10.1177/16094069251328163","DOIUrl":"10.1177/16094069251328163","url":null,"abstract":"<p><p>Community-engaged research is an approach that helps foster partnerships between community members and researchers by incorporating community members across multiple stages of the research study. In doing so, researchers can gain a deeper understanding of the insider perspective. One area that has received limited attention is the process of engaging community members in qualitative data analysis. To overcome this limitation, we outline how we implemented and adapted the Rigorous and Accelerated Data Reduction (RADaR) technique to explore learners' perceptions and experiences of a tailored research best practices training for Community Health Workers and Promotoras. We reflect on the strengths and challenges of using the RADaR technique in community-engaged research and provide a list of considerations for researchers engaging in a similar process. We also incorporate the community partner's perspectives on engaging in qualitative data analysis. This article provides a step-by-step approach for engaging community partners in the qualitative data analysis process, particularly using the RADaR technique, as a strategy for enhancing research quality and mitigating the power imbalance between researchers and communities.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12365954/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144974621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Responsible Sharing of Qualitative Research Data: Insights From a Pioneering Project in the United States.","authors":"Heidi A Walsh, Meredith V Parsons, Jessica Mozersky, Aditi Gupta, Albert M Lai, Annie B Friedrich, James M DuBois","doi":"10.1177/16094069251329607","DOIUrl":"10.1177/16094069251329607","url":null,"abstract":"<p><p>Qualitative research data, such as data from focus groups and in-depth interviews, are increasingly made publicly available and used by secondary researchers, which promotes open science and improves research transparency. This has prompted concerns about the sensitivity of these data, participant confidentiality, data ownership, and the time burden and cost of de-identifying data. As more qualitative researchers (QRs) share sensitive data, they will need support to share responsibly. Few repositories provide qualitative data sharing guidance, and currently, researchers must manually de-identify data prior to sharing. To address these needs, our QDS team worked to identify and reduce ethical and practical barriers to sharing qualitative research data in health sciences research. We developed specific QDS guidelines and tools for data de-identification, depositing, and sharing. Additionally, we developed and tested Qualitative Data Sharing (QuaDS) Software to support qualitative data de-identification. We assisted 28 qualitative health science researchers in preparing and de-identifying data for deposit in a repository. Here, we describe the process of recruiting, enrolling, and assisting QRs to use the guidelines and software and report on the revisions we made to our processes and software based on feedback from QRs and curators and observations made by project team members. Through our pilot project, we demonstrate that qualitative data sharing is feasible and can be done responsibly.</p>","PeriodicalId":48220,"journal":{"name":"International Journal of Qualitative Methods","volume":"24 ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12577765/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145432878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}