The current study addresses the lived experiences of individuals with multiple marginalized identities with sex education, adopting an intersectional queer theory approach. Queer adults (N=22) residing in Italy who live with chronic illness, disability and/or are neurodivergent, participated in online 2-hour semi-structured focus groups. We analyzed data using reflexive Thematic Analysis and identification of negative cases. The five identified themes were Assumed Heterosexuality, Erasure, Sex-Positive education, Validation, and Long journey to self-discovery. The findings call for a rethinking of sex education as an affirming space for multiple marginalized identities, with the purpose of eventually improving sexual health for all. In this perspective, sex education has the potential to become a space of validation and recognition, where diverse identities, bodies, and lived experiences are acknowledged and affirmed. Beyond these substantive findings, the study illustrates how attending to multiplicity throughout the research process can surface dimensions of experience, which are entangled rather than additive, that might otherwise go unnoticed.
Young people and their caregivers often encounter barriers to both awareness of and access to mental health and substance use health (MHSUH) services. Webinars represent an effective yet underutilized approach for delivering actionable, accessible, and stigma-reducing content to support help-seeking. We describe a multi-method planning process for developing a user-centered and evidence-informed webinar series aimed at improving MHSUH awareness and access among young people and caregivers.Five complementary methods informed the planning process: an environmental scan, Intervention Mapping (IM), virtual advisory council consultations, an online survey, and a virtual workshop with young people and caregivers. While each method contributed distinct insights, IM served as the integrative backbone, organizing findings from all methods within a coherent theoretical structure and aligning evidence, theory, and community input toward intervention design. An adapted help-seeking model and a logic model guided the structure and content of the series.Key findings identified help-seeking as a priority and under addressed topic, with young people and caregivers emphasizing interactivity, lived expertise and storytelling, practical navigation-focused content, and inclusive, culturally-responsive design. The integration of complementary methods provided breadth and depth across the planning process, while the iterative and participatory approach ensured planning decisions were progressively refined and grounded in the perspectives of the intended audience.This study demonstrates the value of a multi-method approach to intervention planning, showing how diverse inputs produce more comprehensive, credible, and responsive decisions than any single method alone. It contributes a transparent and replicable model that may inform future MHSUH initiatives and similar efforts.
Contemporary qualitative psychology increasingly embraces multiplicity, yet methodological frameworks remain designed for single-perspective analysis. Current approaches typically pursue integration, flattening rather than leveraging multiplicity. This commentary argues for computational scaffolding as infrastructure for coordinating multiple perspectives without reducing complexity to algorithmic simplicity. Computational scaffolding involves using computational tools to support, organise, and coordinate interpretive work across multiple perspectives, data sources, and time, whilst maintaining human interpretive control. Rather than replacing human interpretation, computational tools can help manage disagreement, temporal complexity, and multi-source data, reframing multiplicity as a fundamental feature of psychological phenomena requiring methodological support to leverage its explanatory potential.
This methodological article explores how grounded theory can guide adaptive qualitative design when researchers work with multiplicities in participant accounts, including diverse, shifting, and sometimes contrasting meanings. A study of Latvian return migration is used as an illustrative case. The empirical study began with in-depth interviews with 21 return migrants and focused on stress factors in the return process. As the analysis progressed, participants repeatedly described experiences related to psychological resources, coping, and resource mobilisation. This widened the initial analytic focus and raised questions about how these experiences should be interpreted within the developing grounded theory analysis. The article follows this analytic shift from early comparison to category refinement and to the modelling of relationships between return stress and psychological resources. Open interviewing, follow-up clarification, and a focus group with five additional participants were integrated into a single grounded theory process. The focus group included a discussion stage in which participants related preliminary categories to their own return experiences. The resulting conceptual model connected return stress to psychological tension and vulnerability, and to resource mobilisation and coping. The mobilisation of buffering mechanisms was identified as the core category. The article's methodological contribution is to specify how grounded theory procedures can be used to justify and report a change in analytic focus when multiplicities in participants' accounts shift the direction of category development. It argues that responsiveness to multiplicities can be reported by tracing how comparison, follow-up clarification, focus group discussion, and category refinement shaped the developing analysis while maintaining conceptual direction.
Reflexivity is a key principle for research integrity and while well-known in the qualitative literature, reflexivity has rarely been studied in the action of doing research. In a researching-the-researcher design, we explored how seven junior researchers interpreted and practiced reflexivity within an interview study. Using reflexive thematic analysis, we analysed researchers' concrete questions and responses in their interviewing, and their understanding of reflexivity as expressed in a post-research focus group. The researchers conceptualized reflexivity as an ongoing process of self-examination, encompassing their selves, lives, and lived worlds; demonstrating that a researcher's being in the world goes far beyond the research. Their definition of reflexivity depended on their stance on what we call the paradigmatic ‘objectivist-subjectivist spectrum’ (outlined in detail in the introduction), which led to marked differences in how and why researchers pursued specific reflexive actions. In action, they used different practices, from spontaneous to instructed and supervised, which were all aimed at managing the interrelatedness with the participants that had to be reinvented with each participant. Our findings emphasize reflexivity as an idiosyncratic, (inter)personal and continuous process, that should be explicated and refined individually and collectively both before and throughout the study, to avoid using the same word for very different actions. We recommend the systematic adoption of Reflexivity Labs, in which the benefit of collective reflexivity is maximised to encourage critical self-reflexivity and facilitate ethical research. From our findings, we iteratively derived nine (non-exhaustive) ‘key questions’ that can be used as starting points for readers' own reflexivity labs.
Researchers across psychology often interpret binary judgment data using raw accuracy scores that confound sensitivity with response bias and are influenced by unequal base rates. Signal detection theory (SDT) offers a principled alternative, yet most tutorials focus on single perceiver tasks and do not address the multilevel structure in interpersonal and behavioral research. This tutorial extends standard SDT applications by demonstrating how SDT parameters can be estimated within multilevel generalized linear models for dyadic and other crossed designs. The tutorial introduces SDT concepts, shows how to translate SDT parameters into probit mixed-model coefficients, and provides reproducible code for fitting these models with crossed perceiver and target effects. It also presents simulation-based guidance for study design. Finally, the tutorial includes a Shiny application for readers to explore these concepts interactively. Although demonstrated with romantic interest judgments, this workflow generalizes to any psychological domain involving binary decisions and multilevel data structures.
Abortion stigma is a complex phenomenon that can have serious consequences for those affected. Because women's experiences with abortion are highly heterogeneous, research methods are needed that can capture this complexity in a realistic and differentiated manner. Vignette studies offer a promising approach by depicting diverse life situations more comprehensively than conventional questionnaire items. In this paper, we present our seven-step, interdisciplinary process to create a vignette template that covers eight dimensions of women with unwanted pregnancies, such as relationship status, biographical reasons, material worries, and the total number of abortions. This template can be used to create 1152 combinations of vignettes.We tested the suitability of 150 vignettes in 15 sets on a sample of n = 498 and analyzed dropouts as well as careless responding behavior such as speeding and straightlining. N = 166 participants (33.3%) dropped out, but only 12,0% dropped out during the vignettes. Participants who positioned themselves politically in the center or on the right were particularly likely to drop out. Speeding and straightlining occurred in only 4.7%. We observed that speeding does not necessarily indicate poor data quality. We assume that some people have such strong opinions about abortion that they are not influenced by the vignettes. This may be an important finding in terms of attitude resistance.Overall, the vignettes proved to be suitable and can be used in a variety of studies, for example, for experimental studies, validations, or theory formation about complex relationships between stigma and life situations.
Experimental psychological research frequently relies on aggregating items, assuming that the effects of other variables remain constant across items. This assumption can lead to biased statistical inferences, most notably an inflated Type I error rate, as it disregards the random variability of item-specific effects. This paper highlights the potential biases that can arise from using aggregated scores. It shows the conditions under which effect-variant models, which treat both participants and items as random factors, are more appropriate than traditional aggregation approaches. We introduce the Aggregation Standard Error Inflation (ASEI), a novel metric designed to quantify the variance inflation associated with conventional aggregation methods and the related risks. Through a series of simulations and real data analyses, we show that neglecting item-specific variability in aggregated models increases Type I error rates, particularly in larger samples. The extent of this inflation can be effectively assessed using the ASEI. These findings highlight the importance of incorporating random variability across both items and participants to improve the validity of statistical inferences in psychological research that relies on questionnaires and scales.
Psychological measurement traditionally summarizes multi-item responses using scalar scores that discard information about how individuals distribute emphasis across indicators. This paper introduces Competitive Salience–Reconstruction (CSR), a latent measurement framework that decomposes responses into volume, a scalar capturing overall intensity, and salience, a vector capturing relative allocation across indicators. The within-person decomposition is geometric and applies to any nonnegative response profile, whereas between-person patterns contain two layers: a baseline layer induced by bounded response support and a directional layer reflecting systematic differences in salience allocation across individuals. CSR explicitly separates these layers. Salience is defined as an estimand through self-consistent reconstruction, while classical sum scores emerge as a special case retaining only volume. Simulations characterize the baseline layer and confirm that CSR recovers directional structure with appropriate sensitivity and specificity. An empirical illustration using a self-selected online extraversion dataset identifies directional-layer structure beyond the bounded-support baseline: individuals with similar trait levels differed systematically in the behavioral facets they emphasized. The CSR measurement model provides a principled framework for separating support-induced baseline structure from substantively meaningful directional heterogeneity.
Co-operative inquiry is a research method that enables researchers to harness the transformative potential of research for social change through work in multi-disciplinary teams, with multiple knowledge paradigms, and multiple research approaches. Through a midpoint critical reflection on Warming the Whare, a three-year co-operative inquiry, we explore the potential and benefits of harnessing multiplicities in this method. Warming the Whare partners with two urban perinatal mental health services working together to build system readiness for transgender-inclusive perinatal mental health services in Aotearoa New Zealand. Our approach uniquely centres Indigenous knowledge about LGBTQIA + wellbeing, alongside transgender parents’ lived experience. Reflection on our inquiry is organised in three themes: valuing multiple ways of knowing, working across multiple sites, and learning through multiple data sources. Within these themes we critically explore the rationales, as well as the challenges encountered, across the first two phases of our inquiry. While work with multiplicities can add complexity, we argue that embracing multiplicities also multiplies the transformative potential of co-operative inquiry. Specifically, through contributions to social justice and decolonising research processes. We conclude by affirming the important role of incorporating continuous reflection about capacity, resources, and impact into the co-operative inquiry phases to ensure work with multiplicities is effective and sustainable.
Conventional research ethics, rooted in procedural compliance, often prove inadequate for the relational and political complexities of justice-oriented qualitative inquiry. This article challenges these limitations by introducing and developing the concept of ‘Restorative Love Praxis’, a feminist, decolonial framework that positions love not as a sentiment, but as a rigorous political commitment to justice. Grounded in Black and Global Majority feminist scholarship, the praxis is explained through four interconnected dimensions: Ethical Relationality, Reciprocal Care, Critical Reflexivity, and Collective Commitment. Drawing on the authors’ doctoral research journeys: Participatory Action Research with racially minoritised domestic abuse survivors in the UK and ethnographic account of rape survivors and their families in India, the paper provides concrete examples of this praxis in action.The article first critiques procedural ethics frameworks, then develops the concept of Restorative Love Praxis, and finally illustrates its application through reflexive scenes from doctoral fieldwork. It illustrates how love, as an embodied method and praxis, guides research relationships, navigates institutional friction, and fosters accountability beyond extractive models. We argue that Restorative Love Praxis moves beyond ‘do no harm’ towards an active ethic of epistemic healing and reparative engagement. This framework offers a vital reorientation for researchers, positioning restorative love as the foundation of rigorous and transformative knowledge production.
A multisite study of youth resilience in contexts of severe climate change and economic stress in Canada and South Africa began with a common set of health-related research questions, then employed a range of individual and group approaches to qualitative data collection. Our expectation was that the choice of method (individual interview or group activity using visual and arts-based methods) would elicit different culturally-based narratives to explain the protective processes that help youth cope in stressed environments. While decolonizing methodologies holds promise for better understanding emic perspectives of wellbeing, our goal was to investigate whether changing the way data is collected could influence the quality of what is discovered. While adaptation often benefits research by making it culturally relevant, it also raises questions: (1) Are emerging findings merely artifacts of the choice of methodology, limiting (or expanding) possible explanations for psychological phenomena? (2) How does the sociocultural lens of participants shape their response to the methodology itself? Using examples from the multisite mixed methods Resilient Youth in Stressed Environments (RYSE) study, we found, contrary to our expectations, that the sociocultural context of participants exerted far more influence on their descriptions of the protective processes associated with resilience than the methodology that was used. Youth from more collectivist cultures referenced collectivist processes more often than young people from individualistic cultures, regardless of whether the methodology employed emphasized individual or group accounts of the phenomena under study. In the conclusion, we discuss the implications of our findings for the design of multi-site cross-cultural research.
Artificial intelligence (AI) has the potential to quickly process large amounts of qualitative data and return results. Investigators conducting qualitative psychological research have examined how well AI can analyze text data and have found general consistency with human qualitative analysis but a lack of interpretive depth. Although quality of AI in qualitative research is important in appraising AI, ethical considerations are often overlooked. Researchers have little guidance regarding the ethics of AI in qualitative research. Therefore, the aim of this article is to provide a framework for the ethical considerations of AI use. The article includes a brief primer on AI use in qualitative research, but the focus is on ethical considerations for qualitative researchers contemplating or using AI in qualitative research, members and staff of institutional review boards (IRB) and research ethics boards, and reviewers of proposals and manuscripts. We propose a set of ethical questions for AI in qualitative research pertaining to: sensitivity of the data and the data management plan, de-identification, data transmission, AI assistants in software, data storage on AI servers, internal AI systems, training and model development, biases, reproducibility, and integrity, informed consent, and societal ethical issues. This article provides information about the current state of AI and ethical considerations to make more informed decisions about the potential benefits and risk of using AI in qualitative research.
Contemporary psychometric research is increasingly characterized by parallel developments in latent variable modelling and network psychometrics. Despite their shared goals, these approaches are rarely integrated within a single construct validation framework, limiting opportunities for methodological triangulation and robust inference. In the present study, we demonstrate a complementary psychometric workflow based on exploratory factor analysis (EFA), exploratory graph analysis (EGA), confirmatory factor analysis (CFA), construct validation, and measurement invariance testing to evaluate construct dimensionality and applicability. This approach is illustrated using the Metacognitions Questionnaire–30 (MCQ-30) as a substantive case study. Using data from 3999 participants across student and general population samples, we examined convergence between factor-analytic and network-based dimensionality estimates, assessed item stability and structural consistency, and evaluated construct, incremental, and measurement invariance across demographic and symptom severity groups. Results showed strong convergence between EFA and EGA in identifying a correlated five-dimensional structure, which was subsequently supported in CFA. Measurement invariance was established across age, gender, and anxiety and depression severity groups, enabling meaningful latent mean comparisons. Rather than offering a scale-specific validation, this study demonstrates how integrating latent variable and network psychometric approaches can strengthen construct validation, enhance transparency, and improve the robustness of measurement conclusions. The proposed framework provides a practical illustration for psychological researchers seeking to evaluate dimensionality and measurement equivalence across diverse contexts, highlighting the complementarity between common factor and network psychometric modelling.
Conducting qualitative research with families raises many unique ethical issues. In this paper, two researchers with decades of experience conducting research with families invite and engage with common ethical issues that uniquely confront qualitative family researchers. Ethical concerns related to respondents in family systems including consent, assent, remuneration, transparency about roles/responsibilities, duty of notification, and disclosure and family privacy are discussed, with the authors providing suggestions and illustrations from their prior work. Students new to research as well as seasoned researchers may benefit from the discussed strategies for conducting ethical research when conducting qualitative interviews with families.
Este trabajo tiene por objetivo situar la lógica abductiva como fundamento de la práctica psicoanalítica lacaniana. La lógica abductiva, formulada por Charles Sanders Peirce, se presenta como un proceso de generación de hipótesis ante fenómenos inesperados, lo que permite una articulación con el concepto de inconsciente, de transferencia y de interpretación psicoanalítica. Tomamos como referencia la lógica abductiva para demostrar cómo su uso en la operación analítica permite mantener vivo el vacío que funda el trabajo de invención de saber en la experiencia discursiva del psicoanálisis. La pregunta guía es ¿Cómo los fundamentos de la abducción se hacen presentes en la operación psicoanalítica lacaniana? No es un trabajo teórico, sino un esfuerzo de argumentar usos de la abducción en la práctica analítica. Se utiliza un enfoque metodológico cualitativo basado en el análisis de contenido y una revisión crítica de referencias bibliográficas. Se concluye que la lógica abductiva no solo es fundamental en la interpretación analítica y en la dinámica de la transferencia, sino que también, al permitir abordar lo real sin reducirlo a categorías preestablecidas, sostiene al psicoanálisis. Abstract This work aims to place abductive logic as the foundation of Lacanian psychoanalytic practice. Abductive logic, formulated by Charles Sanders Peirce, is presented as a process of generating hypotheses in the face of unexpected phenomena, which allows an articulation with the concept of unconscious, transfer and psychoanalytic interpretation. We take abductive logic as a reference to demonstrate how its use in analytical operation allows us to keep alive the void that founds the work of invention of knowledge in the discursive experience of psychoanalysis. The guiding question is how are the fundamentals of abduction present in the Lacanian psychoanalytic operation? It is not a theoretical work, but an effort to argue uses of abduction in analytical practice. A qualitative methodological approach based on content analysis and a critical review of bibliographic references is used. It is concluded that the abductive logic is not only fundamental in the analytical interpretation and in the dynamics of the transfer, but also, by allowing to address the real without reducing it to pre-established categories, supports psychoanalysis.
This critical commentary examines the multifaceted challenges of obtaining informed consent in psychological research involving children. Traditional consent models i.e., relying on proxy consent such as school and parent/guardian consent methods often fail to account for children's agency, voice and their evolving capacities, cultural contexts, and the power dynamics inherent in adult-child relationships. Drawing upon researcher experiences and integrating perspectives from existing literature, the paper critiques traditional consent models that often overlook children's agency and the socio-cultural contexts influencing consent processes. It highlights the limitations of standardised consent procedures, the role of proxies and the impact of institutional ethics boards. The commentary advocates for a more nuanced, participatory approach that recognises children as active contributors to research, emphasising the need for culturally sensitive, iterative consent processes that align with ethical best practices.
This paper focuses on multilevel growth models with longitudinal measurement variance and bivariate growth processes via structural equation modeling. First, we introduce and demonstrate an application of a bivariate multilevel growth structural equation model with measurement invariance, including model output and fit information, along with considerations for competing parameterizations. Second, we present a small-scale simulation investigating how sample size affects the accuracy of the parameter estimation that will be helpful for applied and methodological research with interest in using and developing these models further. As expected, the parameter and standard error estimation became more precise as sample sizes increased although the estimation was accurate, on average, across sample size conditions. Recommendations for applied users, methodological researchers, and general future research with these models are discussed.
This article explores the ethical and procedural challenges associated with the payment of sex workers who engage in research. Our reflections are built upon a study exploring peer-to-peer support services for sex workers and highlight common ethical, institutional and sector-wide policies associated with researching vulnerable and marginalised groups. Through our analysis, we argue that institutional ethics ‘at a distance’ - particularly those concerning payment methods and amounts to co-researchers and participants - inadvertently re-stigmatises, paternalises and exacerbates ethical and personal risks associated with participating in the research itself. This paper draws on the relationship between vulnerability, risk and stigma to understand the function and impact of the institutional ethical processes which are common across a range of disciplines, with a particular focus on psychology and the social sciences. By uncritically positioning sex workers within broader understandings of ‘vulnerability’ and ‘risky’ or ‘at risk’ groups, we argue that institutional processes of additional risk management inadvertently reproduce the marginalisation and personal risks they seek to avert. This leads us to question the relationship between institutional ‘ethical’ procedures across the university sector and the ethics of the personal outcomes they produce. We advocate for the adoption of responsive and co-produced ethical policies and guidance on payment methods and amounts. Such positioning should be reflective of those seen in medical research and premised on a feminist ethic of care, promoting a more liberalised, flexible and inclusive approach to participant payment.
