A new paper in the Proceedings of the National Academy of Sciences argues that this moment of technological acceleration should be matched by methodological rigour. The authors—41 researchers spanning institutions globally—present an open, standardized vision for VR research designed to strengthen reproducibility while lowering barriers to participation for new labs. They connect VR’s promise to a central scientific bottleneck: inconsistent protocols, variable reporting, and limited sharing of the materials needed for replication.

The core proposal is an interactive checklist hosted at www.vrprotocols.org. Researchers can use it to ensure that their VR studies are run and reported according to the most up-to-date guidance in open behavioural research. The checklist is intended as a common language for authors, reviewers, and journal editors, reducing ambiguity about what qualifies as a sufficiently transparent and reproducible VR experiment.

Technically, the framework targets three practical failure points. First, interoperability: many VR studies remain “locked” to specific development engines, device ecosystems, and proprietary formats. By encouraging common engines, open standards, and clear licensing, the protocols aim to keep simulations usable as technology changes, and transportable between labs without rebuilding everything from scratch.

Second, procedural standardization: even small differences—like how participants are briefed or which measures define core constructs such as “presence”—can shift results. The authors specify baseline practices for shared measurement, ethics, accessibility, and safety, aiming to reduce variance unrelated to the experimental hypothesis.

Third, data sharing: reproducibility requires more than publishing outcomes. The protocols emphasize sharing VR assets and supporting code so other teams can run the simulation directly, rerun analyses, and verify behavioural effects under comparable conditions.

The paper’s broader argument is that VR may be uniquely suited to reproducibility. Unlike many physical laboratory designs, VR can function as a portable experimental laboratory, producing consistent participant experiences across locations—including scenarios as varied as remote labs and analogue mission settings. When the environment and procedures are carefully specified and distributed, replication becomes far more feasible.

Senior author Timothy D. Hubbard highlights that these protocols are meant to guide future study design and raise overall quality. The authors also describe their work as an initial step toward breaking paywalls and technological barriers, promoting open VR research that can scale across the behavioural sciences.

Subject of Research: People
Article Title: Creating common virtual ground: Protocols to democratize open VR research
News Publication Date: 30-Jun-2026
Web References: http://dx.doi.org/10.1073/pnas.2524991123; https://www.pnas.org/doi/epub/10.1073/pnas.2524991123; http://www.vrprotocols.org/; https://www.nature.com/articles/s41586-026-10203-5
References: Proceedings of the National Academy of Sciences, “Creating common virtual ground: Protocols to democratize open VR research” (DOI: 10.1073/pnas.2524991123)
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Keywords: virtual reality, open science, reproducibility, behavioural science, research protocols, interoperability, presence, data sharing, interoperability standards

Central to the findings is the undeniable role of communication skills and policy knowledge as catalysts for engagement. This resonance with prior research highlights the critical need to embed education and specialized training within the broader impact infrastructure. Despite accumulating evidence advocating for skill-building interventions, a mere 13% of current initiatives focus on enhancing researcher capabilities, and only a fraction of these have undergone rigorous evaluation. The study emphasizes the necessity for high-quality, evaluative training programs designed through experimental lenses, mirroring the progressive models proposed by scholars such as Crowley et al.

Strikingly, the analysis reveals a paradox regarding training opportunities: researchers with higher policy engagement tend to report fewer organizational training supports. This counterintuitive finding may signal a deficit in either the quantity or quality of available programs or could reflect a selection effect where already engaged researchers seek training less often. Notably, natural scientists and engineers seem particularly underserved, underscoring disciplinary disparities in access to or effectiveness of policy-related skill development. Such insights call for refined assessments of training impact and differentiated program design tailored to disciplinary contours.

Contrary to previously held beliefs, support teams and networking opportunities did not emerge as significant predictors of policy engagement within this German sample. This null result may be symptomatic of a systemic absence of dedicated support infrastructure, with median organizational support ratings notably low. Internationally, strategic leadership measures like support teams represent a marginal slice—approximately 13%—of the broader impact infrastructure, suggesting considerable room to expand these avenues. While networks and partnerships have shown promise, their transient, project-based funding models limit sustainable impact, underscoring the fragile scaffolding underlying collaborative efforts.

The role of tangible resources also surfaces as a decisive factor, particularly for resource-intensive disciplines. Natural scientists disproportionately benefit from additional staff, time, and funding—resources perceived as vital to sustaining policy engagement—while engineers lean on supportive leadership within their institutions. Senior researchers, juggling multidimensional responsibilities including managerial roles and external evidence requests, appear especially dependent on these intra-institutional supports. This nuanced resource dependency contrasts with the narrow scope of prior reviews, marking an important advancement in understanding structural enablers.

A brief yet profound exploration of the “Carl Sagan effect” reveals a novel dimension to the discourse on policy engagement stigma. Senior academics venturing into policymaking confront increased peer scrutiny compared to their junior counterparts, who seem shielded and even empowered by peer role models. This phenomenon, absent in the literature on industry or public engagement, may be unique to the political policy arena, reflecting deeply ingrained cultural norms and biases within academia. Moreover, differences between university-affiliated and non-university researchers illuminate distinct microcultures, with the former more susceptible to negative perceptions. Gendered experiences further complicate this landscape, as male researchers report heightened criticism relative to females when involved in policy engagement, pointing to evolving, yet unequal, normative shifts.

Incentives, both career-based and financial, emerge as pivotal motivators predominantly for social scientists and senior researchers. Despite evidence validating their efficacy, such incentives remain underleveraged within institutional recognition schemes. German universities notably reward policy engagement sparingly, mainly favoring professors, with only a handful explicitly integrating such criteria into performance appraisals. On the global stage, reward mechanisms, including impact prizes, constitute a scant 3% of the impact infrastructure, and none have undergone systematic evaluation. These gaps spotlight untapped potentials for aligning researchers’ extrinsic motivations with institutional objectives.

Perhaps the most compelling discovery is the dominance of mission-driven motivation in prompting policy engagement. Researchers propelled by a sense of duty, identity, and a commitment to problem-solving stand out as the most consistent predictors of active involvement. This aligns with broader conceptualizations of pro-social or moral motivation, suggesting that impactful policy engagement is as much an ethical endeavor as a professional one. Strategies aiming to bolster researcher participation would do well to resonate with these intrinsic values rather than relying solely on instrumental incentives.

Interestingly, the research highlights a negative association between the so-called “gold” motivator—driven by financial gains and resource acquisition—and policy engagement. Contrasting with findings from broader external engagements, this suggests that researchers prioritizing monetary benefits may divert their attention to more lucrative industry partnerships rather than policy advising. This delineation hints at a complex matrix of engagement choices influenced by perceived returns and personal values, emphasizing the need for nuanced policy infrastructures that appreciate these motivational differentials.

Challenging conventional wisdom, this study finds female researchers significantly more likely to engage with policymakers compared to males. This finding diverges from most prior research, aligning instead with emerging dissenting studies and recent global gender reports in science policy engagement. The implication here extends beyond mere representation—female researchers may bring distinct perspectives or relational approaches that enrich policy dialogues. This revelation invites deeper exploration into gendered dynamics of science communication and influence.

Age and academic status reaffirm their roles as salient predictors, with more senior researchers typically enjoying greater access and credibility in policymaking circles. Policymaker preferences for seasoned experts contribute to this phenomenon, creating systemic biases that may inadvertently marginalize younger, potentially innovative voices. Recognizing the untapped potential of early-career researchers, especially in emerging fields like AI, various initiatives like the U.S. National Academies’ New Voices program seek to amplify these underrepresented contributors, signaling a shift toward more inclusive advisory ecosystems.

Beyond individual attributes, organizational context plays a decisive role. Non-university research institutions notably outperform universities in fostering policy engagement, offering more supportive environments across multiple dimensions—administrative backing, reduced teaching burdens, and cultural acceptance. Surprisingly, differences in teaching obligations do not fully explain these disparities, indicating that institutional culture and infrastructure are powerful determinants in enabling policy interaction. This insight challenges assumptions about academic workloads being the primary barrier and encourages a closer examination of organizational climates.

Together, these findings paint a complex tapestry where behavioural science illuminates pathways to enhance the impact infrastructure essential for effective science-policy interface. By integrating comprehensive behavioural components—capability, opportunity, and motivation—this study sets a new standard for disentangling the multifaceted predictors of engagement. Its implications urge funders, universities, and policymakers to rethink and recalibrate existing support mechanisms, placing emphasis on tailored training, resource allocation, stigma reduction, and alignment with intrinsic motivators.

With the global urgency for evidence-based policy intensifying, fostering robust and inclusive researcher engagement is not merely desirable but imperative. This research invites the academic community to transcend traditional silos, embrace innovative behavioural insights, and cultivate environments where researchers of all genders, disciplines, and career stages can thrive as indispensable contributors to societal decision-making. As the frontiers of impact infrastructure expand, this study serves as a beacon, guiding stakeholders toward more effective and equitable collaborations at the nexus of science and policy.

The future of impact infrastructure lies in its adaptability—its ability to recognize diverse researcher motivations, dismantle stigma, and provide meaningful incentives and supports. By leveraging these nuanced insights and forging experimental, evidence-driven interventions, the academic ecosystem can redefine policy engagement from an exceptional activity to a normative and celebrated dimension of scholarly identity. In doing so, the science-policy landscape will be better equipped to tackle pressing global challenges through informed, inclusive, and impactful research partnerships.

Subject of Research: Key predictors of researchers’ policy engagement analyzed through a behavioural science framework focusing on capability, opportunity, and motivation.

Article Title: Improving impact infrastructure: key predictors of researchers’ policy engagement based on behavioural science

Article References:
Canino, H., Antonopoulou, V., D’Lima, D. et al. Improving impact infrastructure: key predictors of researchers’ policy engagement based on behavioural science. Humanit Soc Sci Commun 12, 1509 (2025). https://doi.org/10.1057/s41599-025-05793-w

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