At the core of the PAINDIFF Network’s initiative lies the recognition that sex and gender profoundly influence physiological, psychological, and behavioral responses to pain. Despite this, historical and contemporary research has often either neglected these variables or treated them superficially, leading to data variability, poor reproducibility, and ultimately limited translatability from bench to bedside. To counteract these issues, the network advocates for five universal strategies that should be considered foundational in nearly every research undertaking involving biological subjects or human participants.

Foremost among these is the unequivocal recommendation to include both males and females as a standard practice in research protocols. This inclusivity is not merely about representation but about capturing the full spectrum of biological and experiential variance that sex and gender confer. The network highlights that excluding one sex invariably biases results and undercuts the generalizability of findings. A balanced inclusion ensures that discoveries are more reflective of the population’s true heterogeneity.

Complementing this, robust experimental designs must account for sex in procedures like randomization, counterbalancing, and testing order. These design elements are critical to mitigating confounding variables that might otherwise obscure sex-related effects. Randomly or alternately assigning participants or animals of different sexes to various conditions helps avoid systematic biases that could influence outcomes. The inclusion of sex as a variable in these foundational steps marks a substantial refinement in methodological rigor.

Moreover, when the central aim of a study involves discerning sex differences, the PAINDIFF Network underscores the importance of statistically powering these analyses appropriately. Underpowered studies risk missing or overstating differences, contributing further to the reproducibility crisis. This entails calculating sample sizes that are sufficiently large to detect meaningful interactions or contrasts between sexes, ensuring that the conclusions drawn hold firm under scrutiny.

Accurate and detailed reporting forms the backbone of scientific transparency and rigor. To this end, the network counsels researchers to provide explicit descriptions of experimental designs, especially outlining how sex and gender variables were incorporated. This includes detailing the methods used to classify subjects, controlling for sex-related confounds, and any sex-specific nuances in methodology. Such thoroughness not only aids replication but enables meta-analyses that can synthesize data across studies with confidence in variable comparability.

Finalizing these universal guidelines is the call for sex-disaggregated analysis and reporting—a practice that remains insufficiently adopted but is vital for uncovering nuanced biological insights. By separating data by sex, researchers can identify differential mechanisms, risks, or therapeutic responses that would be masked in aggregated datasets. This stratification empowers personalized approaches and more effective medical interventions.

Beyond these five cornerstone recommendations, the PAINDIFF Network addresses the distinct challenges and requirements in preclinical versus clinical research domains. For preclinical investigations, which commonly utilize animal models, three additional targeted strategies are outlined. These include considerations such as hormonal status control, appropriate model selection reflective of both sexes, and the incorporation of sex-specific endpoints to capture relevant biological phenomena accurately.

On the human clinical side, the network elaborates five further recommendations. These underscore the necessity to rigorously define and operationalize gender as a complex socio-cultural construct, distinct from biological sex, which modulates pain experiences and healthcare outcomes. Human studies are encouraged to embrace gender diversity, consider gender-related psychosocial factors, employ validated instruments to assess gender identity and roles, and ensure inclusive recruitment strategies that do not unintentionally marginalize underrepresented or non-binary groups.

Recognizing that systemic change demands coordinated action, the PAINDIFF Network also extends its recommendations to key stakeholders beyond the laboratory bench or clinic. Editors and reviewers of scientific journals are urged to demand rigorous sex- and gender-inclusive methodologies and transparent reporting as publication prerequisites, thereby influencing the cultural standards of scientific excellence and accountability. Funding bodies are called upon to prioritize and incentivize research that conscientiously integrates sex and gender variables, potentially tying grant approvals or renewals to adherence with these best practices.

Policymakers, too, have a pivotal role in shaping the broader biomedical research ecosystem. By embedding these recommended standards into regulatory frameworks and research oversight mechanisms, policymakers can ensure that scientific inquiry progresses equitably and with heightened relevance to all segments of the population. Such top-down reinforcement complements grassroots efforts within research communities, fostering a holistic environment conducive to systemic adoption.

The tangible benefits of embracing these comprehensive recommendations are manifold. Researchers can expect reductions in data variability that may otherwise stem from unaccounted sex and gender differences. Enhanced reproducibility will emerge from methodological transparency and appropriately powered analyses. Crucially, the translatability of findings will improve, bridging the critical gap between experimental discoveries and their application in diverse clinical populations with varied sex and gender profiles.

This concerted movement toward inclusivity and rigor aligns with broader scientific imperatives advocating personalized medicine and precision health. Understanding how sex and gender intersect with genetic, environmental, and psychosocial factors to influence pain and other health outcomes is indispensable for developing tailored interventions. The PAINDIFF Network’s recommendations offer a pragmatic blueprint to integrate these dimensions, propelling research toward greater depth, accuracy, and social relevance.

Moreover, the network’s initiatives echo a growing recognition that sex and gender are inseparable from the biological and lived realities influencing health and disease. By transcending tokenistic or superficial treatment of these variables, biomedical research stands to uncover previously hidden mechanisms, identify novel therapeutic targets, and dismantle health disparities rooted in historical neglect.

Implementing these recommendations presents challenges, not least the need for increased resources, training, and cultural shifts within scientific communities. However, the potential rewards—in terms of scientific robustness, ethical integrity, and clinical impact—justify the investment. The PAINDIFF Network’s guidelines serve as both a call to action and a roadmap for transforming pain research and beyond, ensuring that future investigations are built upon foundations of equity, rigor, and inclusivity.

In sum, the incorporation of sex and gender as central, meticulously studied variables is not merely a nicety but a scientific necessity. The PAINDIFF Network’s comprehensive recommendations mark a pivotal moment, pioneering a framework that promises to elevate the quality and applicability of biomedical research globally. By embracing these guidelines, the scientific community will be better equipped to unravel the complex tapestry of factors shaping human health, ultimately leading to more effective and equitable therapies for all.

Subject of Research: Inclusion and study of sex and gender variables in pain research and biopsychosocial science.

Article Title: Recommendations for the inclusion and study of sex and gender in research.

Article References:
Finn, D.P., McGuire, B.E., Beggs, S. et al. Recommendations for the inclusion and study of sex and gender in research. Nat Neurosci (2025). https://doi.org/10.1038/s41593-025-02164-1

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41593-025-02164-1

These newly articulated guidelines emerge from Wiley’s meticulous engagement with over 40 in-depth interviews involving research authors, journal editors, and experts specialized in AI, research integrity, copyright, and permissions. Such a collaborative approach ensures the advisement is firmly rooted in the everyday realities of scientific inquiry and peer-reviewed publication processes. The guidelines fill a critical gap, delineating how AI should be used responsibly across the entire research lifecycle—from initial drafting and experimental design to data analysis and image generation—thereby fostering a culture of transparency and reproducibility.

A key feature of Wiley’s guidelines centers on stringent disclosure standards, imperative for maintaining scientific rigor and trust. These standards specify when and how researchers must openly acknowledge their use of AI tools in various stages, such as literature review, methodological framing, data collection, and manuscript drafting. Unlike previous perceptions that viewed AI disclosure as an impediment, Wiley reorients this practice as an empowering mechanism. It facilitates greater confidence among researchers, encouraging them to leverage AI’s capabilities responsibly while preserving the integrity and credibility of their scientific output.

Central to the peer review process, Wiley’s guidelines introduce robust confidentiality protections specifically aimed at preventing the unauthorized exposure of unpublished manuscripts to AI systems. By clearly prohibiting the uploading of sensitive, non-public content to AI platforms, the guidance establishes essential boundaries. Additionally, it provides nuanced recommendations for editors and reviewers on where AI applications are appropriate within the review workflow—striking a balance between innovation and the safeguarding of intellectual property and research confidentiality.

The issue of visual content integrity is another innovative domain tackled by Wiley’s framework. In an era where AI-generated and AI-edited images can blur the lines between factual evidence and conceptual illustration, Wiley mandates a strict prohibition on the use of AI-altered photographs in scientific journals. The guidelines make explicit distinctions, allowing conceptual images generated through AI while rigorously ensuring that images carrying evidentiary weight are verifiably accurate and authentic. This distinction is paramount to uphold the trustworthiness of visual data in the scientific record.

Moreover, the reproducibility of research findings—a cornerstone of the scientific method—is bolstered by Wiley’s directive encouraging transparency regarding the use of AI methodologies. By clarifying which AI applications necessitate disclosure, the guidelines provide researchers and reviewers with a clear rationale for assessing the impact of AI on study replicability. This contributes to the broader scientific endeavor of ensuring that conclusions drawn from AI-augmented analysis can be reliably reproduced and verified.

Jay Flynn, Executive Vice President and General Manager for Research & Learning at Wiley, emphasized the transformative nature of these standards. He highlighted Wiley’s commitment to an inclusive development process that partnered closely with the research community to create tools that both facilitate innovation and protect scholarly integrity. Flynn underlined that these AI guidelines are not merely rules but foundational frameworks that will serve all stakeholders—authors, reviewers, editors, and readers—in navigating the complex interplay between AI technology and scientific publishing.

The timing of Wiley’s guidelines corresponds with an accelerated adoption of AI across the research publishing landscape. As AI continues to permeate workflows globally, Wiley’s framework stands as a potential model not only for publishers but also for institutions and funding agencies seeking responsible AI governance. Notably, Wiley advocates against the automatic rejection of manuscripts based on AI use; instead, editorial evaluation should prioritize research quality, transparency, and adherence to ethical standards. Disclosure is positioned as a routine and constructive practice rather than a punitive measure.

To further empower researchers, these guidelines include practical examples and workflow integration strategies that demonstrate how AI tools can be incorporated ethically and effectively. This approach demystifies AI’s role in research rather than obscure it behind jargon or overly broad regulations. Decision-making frameworks embedded within the guidelines assist editors and peer reviewers in consistently and fairly evaluating AI-assisted works, fostering a more equitable review environment.

Wiley’s initiative forms part of a wider commitment to support the scientific community as it navigates the opportunities and challenges brought on by AI-driven transformation. Earlier this month, Wiley launched the Wiley AI Gateway, a platform designed to integrate peer-reviewed research access within AI-powered workflows, underscoring the company’s drive to innovate scholarship infrastructure. Parallel to this, Wiley’s ongoing ExplanAItions study delivers continuous insights into researchers’ evolving perspectives and needs regarding AI, enabling Wiley to keep its policies adaptive and relevant.

Crucially, Wiley anchors these operational developments within a set of core AI principles, reinforcing ethical considerations and transparency in AI deployment across all its products and services. This comprehensive strategy reflects Wiley’s vision to not only adopt AI advances but to shape their integration in a way that respects the values underpinning scholarly communication and scientific discovery. The result is a pioneering blueprint for AI’s role in research that combines technological advancement with steadfast commitment to academic integrity.

As the scientific publishing industry grapples with the implications of AI, Wiley’s guidelines offer a beacon of clarity, responsibility, and pragmatism. By addressing pressing concerns such as disclosure, confidentiality, image integrity, and reproducibility, this framework contributes to a more transparent and trustworthy scholarly ecosystem. It empowers researchers to harness AI’s transformative potential while safeguarding the quality and reliability of scientific knowledge that society depends upon.

The broader implications of Wiley’s proactive stance extend beyond the immediate scope of publishing. This leadership encourages a culture of responsible AI usage that can inform policy development across academia and industry alike. As AI technologies evolve rapidly, the principles and practical rules established in this seminal framework will serve as enduring touchstones ensuring that innovation is coupled with ethical stewardship in the pursuit of knowledge.

In summation, Wiley’s release of detailed, research-specific AI guidelines represents a pivotal moment at the intersection of AI and scientific communication. It sets a high bar for integrating cutting-edge tools without compromising the foundational values of research rigor and transparency. This initiative not only addresses urgent community needs but also charts a forward-looking course for the scholarly ecosystem, inspiring confidence that AI can be harnessed responsibly to accelerate discovery and societal progress.

Subject of Research: Responsible and intentional use of AI in scientific research and publishing
Article Title: Wiley Sets New Standards for Responsible AI Use in Scientific Research and Publishing
News Publication Date: Not specified
Web References:

• Comprehensive AI Guidelines: https://www.wiley.com/publish/article/ai-guidelines/
• ExplanAItions Study: https://www.wiley.com/en-us/about-us/ai-resources/ai-study/
• AI Guidelines for Book Authors: https://www.wiley.com/en-us/publish/book/resources/ai-guidelines/
• Wiley AI Gateway: https://www.wiley.com/en-gb/solutions-partnerships/ai-solutions/
• Core AI Principles: https://www.wiley.com/en-us/about-us/ai-resources/principles/

Keywords: Academic publishing, Scientific publishing, Scientific community, Scientific approaches, Academic ethics