From R&R to DOI: Disseminating Your Research (Part I)

Dear TIP Readers,

In my last column, I explored the systemic pressures that shape academic publishing. We discussed the incentives and challenges that influence how scientific knowledge is (as well as should be) produced and published. Yet publishing a study, no matter how rigorous and/or innovative, is only one step in the scientific enterprise. A question, therefore, has stayed with me since writing that column: What happens after publication?

We often talk about creating impactful science, but impact depends on dissemination.1 As an I-O scientist–practitioner, I am of the belief that ensuring your research reaches the audiences who can use and/or benefit from it is as important as publishing it. Besides fellow researchers and practitioners, the target audience could be organizational leaders, policymakers, advocacy groups, journalists, or other stakeholders, depending on the scope and topic of the research. This realization led me to think beyond the mechanics of publication and toward the broader life cycle of research. So, in keeping with the purpose of this column, I turned to Dr. Piers Steel from the Haskayne School of Business at the University of Calgary. He thinks deeply about not only producing and synthesizing scientific knowledge but also making it easier for others to access and use it. And his insights on the topic of research dissemination are worth reading!

What Happens After Publication?

Although researchers typically discuss scientific knowledge and evidence, Dr. Steel seemed equally interested in how they could be shared and used. We connected during the 2026 SIOP annual conference when we discussed his dissemination efforts related to HubMeta, an open-source cloud-based platform that he and his colleagues developed with the goal of increasing the efficiency of meta-analytic research. His perspective shared during the session resonated with the theme of this column because dissemination is ultimately about more than publishing findings. With decades of experience conducting large-scale meta-analyses and developing tools designed to make scientific evidence easier to access and interpret, he shared his thoughts on the challenges and opportunities that come with disseminating one’s research, and I am excited to share them with you!

I began our conversation by asking when he first viewed dissemination as something distinct from publication. His answer took us back to 2007, when his dissertation research on procrastination (Steel, 2007) was published in Psychological Bulletin. A news release associated with the article generated substantial media interest, which led to a book deal. What followed was a much broader dissemination experience involving interviews, public lectures, book promotion, social media, and a website devoted to procrastination.

Dr. Steel confessed that his story was an ideal research-impact story. Yet, the experience made him aware of the limitation of the traditional dissemination model. Research continues to develop, but the publications through which we communicate it remain static. Think for a moment of the original work that may have been rigorous and appropriate given the tools available, but its findings could become incomplete or antiquated as the field continued to advance. Despite this, we may continue to consult the same publication as though the scientific conversation ended when it appeared. Dr. Steel’s work, therefore, has revolved around answering what exactly we should disseminate: individual studies or the evolving body of evidence to which those studies contribute? I think it is a very good question that many of us do not actively think about.

Research in the Plural

Dr. Steel is a meta-analysis expert, so we were bound to talk (a lot!) about systematic reviews and meta-analysis in the field of I-O psychology. Needless to say, a theme that “meta-analysis itself can be viewed as a dissemination mechanism” emerged from my interview. Rather than disseminating individual studies, he recommends disseminating accumulated evidence. This idea caused me to reconsider the unit of dissemination. We typically think about disseminating “our research,” by which we often mean the latest study we completed or article we published. But Dr. Steel repeatedly emphasized research in the plural. An individual study may contribute a useful piece of evidence, but it rarely provides the most complete or dependable answer to a scientific or practical question.

Systematic review and meta-analysis (SRMA) can fix this issue. Instead of asking an audience to interpret a collection of separate findings, SRMA organizes those findings into a cumulative representation of what the field knows. However, conventional SRMA has a limitation similar to that of individual research. Once published as a PDF, they too become fixed products. Additional studies may appear, but the published synthesis does not continuously incorporate them. Dr. Steel, therefore, described the need for “living meta-analyses” and searchable evidence repositories that can be updated as the underlying literature changes.

Dr. Steel’s comments about moving from static PDFs to searchable, continuously updated evidence repositories suggest an emerging view of dissemination where the product is not the article but the knowledge infrastructure surrounding it. It is especially important in an era of information overload as effective dissemination may depend less on producing more studies and more on creating systems that help audiences find and apply the evidence that already exists.

Role of AI in Dissemination

During our conversation, Dr. Steel described his journey from MetaBus (Bosco et al., 2017, 2020) to HubMeta and, more recently, Insight Core. MetaBus was an early effort to enable users to query meta-analytic evidence. HubMeta expanded the scale at which research findings and effect sizes could be extracted and synthesized. Insight Core represents another step in this progression by connecting a scientific evidence base with an AI-supported interface.

During the interview, Dr. Steel demonstrated this idea using a question about the relationship between conscientiousness and job performance. The system translated the question into scientific constructs, modeled the relationships among them, and generated an explanation based on an underlying empirical database. Note that the point here is not that AI can answer questions; instead, the point is that AI can generate more scientifically grounded answers when it is connected to a curated and synthesized body of evidence (rather than drawing indiscriminately from whatever information is most visible online). This distinction matters. The value of AI for dissemination does not lie only in making answers faster or more conversational but, in fact, in creating an accessible doorway into cumulative scientific evidence.

Dr. Steel described a future in which evidence is “baked into” the tools people already use. In the traditional dissemination model, someone must discover an article, access it, read it, understand it, remember it, and recognize when it is relevant. That is a demanding sequence. And tell me honestly how many people outside an academic community are likely to complete all those steps? An evidence-grounded AI system could potentially reverse that process. A person begins with a problem or question, and the system brings relevant science to that question. It could also communicate the same evidence differently depending on whether the user is a researcher, practitioner, student, organizational leader, policymaker, or member of the public.

To me, typically the process of dissemination is moving from microscopic work and evidence to a macroscopic level (either to a wider audience or different contexts), but his model of dissemination moves us in the reverse direction from the macro to the micro. And this sequence, from collective evidence to potentially personalized guidance, makes sense too.

Of course, this possibility raises its own questions. If AI becomes a catalyst of disseminating scientific evidence, we will need to take the governance of that evidence even more seriously. The quality of AI-assisted dissemination will depend on the quality of the scientific infrastructure beneath it.

Some Good Research Goes Nowhere

As we continued our conversation, we also discussed a less comfortable question as to why some excellent research fails to gain attention. To this, Dr. Steel noted that research, especially involving innovative or unconventional methods, sometimes fails to spread due to its difficulty in understanding and/or implementation. A technically strong contribution may remain relatively unused until researchers have access to software or tools that make it easier to apply. In such cases, the quality of the idea has not necessarily been the problem, but its accessibility was. That said, he added that dissemination is not solely governed by the accessibility or merit of an idea. Science is a social enterprise and therefore (whether we like admitting it or not) comes with politics.

It is not unusual that researchers at prestigious institutions or those whose names are already well known may find it easier to draw attention to their work. Conversely, research from an unfamiliar scholar may never be read closely enough for its quality to be recognized. Dr. Steel connected this pattern to the Matthew effect, that is, those who already possess visibility and resources are often more likely to receive more of them. Another plausible explanation for this pattern could be that, in a world where more research is available than any one person can reasonably read, well-established names and institutions can become shortcuts for deciding what deserves attention. We have discussed this topic in my previous column.

There may also be politics in what happens after publication. And this reality may be especially frustrating for graduate students and early-career researchers who do not yet have an established reputation and resources. Recognizing this issue helps explain why dissemination should be strategic. So, when I asked Dr. Steel for tips on strategy and practical recommendations, he began with a point that surprised me: Not all research needs to be disseminated widely.

Initially, that statement seemed to challenge the very premise of this column. I wondered as to why we spent two-thirds of our conversation discussing dissemination only to conclude that some research does not require it. But his point was not that research should remain hidden. It was that broad exposure should not be confused with purposeful dissemination. He noted, “putting a research poster on a billboard would make it visible to many people, but would that make it useful to them? Probably not!” The idea is that dissemination is not successful simply because more people encounter the research. The key question, therefore, we should ask ourselves is who needs to know about our research.

For researchers seeking to disseminate within the scientific community, Dr. Steel recommended identifying the specific scholars who would benefit from the findings and contacting them directly with a personalized explanation of why the research may be relevant to their work. For nonacademic audiences, the same principle applies. Researchers should identify organizations, professional groups, advocacy communities, policymakers, or other stakeholders who are already interested in the problem being studied. This recommendation views dissemination as targeted communication. Based on our conversation, I believe researchers could begin by asking five questions that will help them develop their dissemination strategy.

1. Who needs to know about my research?
2. Why would the findings matter to them?
3. What recommendation(s) or which specific piece of information do they need from my research?
4. How and where do they typically seek such recommendations or information?
5. When or in exactly which conditions would the evidence be most useful to them?

The last question deserves particular attention. Near the end of our conversation, Dr. Steel compared dissemination to reaching people at the moment and/or the context when information becomes relevant. Research may arrive too early, too late, or in a place where the intended audience would never think of looking for it. Timing and context are, therefore, part of dissemination. For example, telework research and adoption had been growing, but the pandemic turned it into a broadly implemented practice.

Build a Resource

Another recommendation from Dr. Steel was to develop a topic-centered online presence. A researcher could create a website, interactive tool, or other accessible resources that bring together the broader evidence on a specialized topic, with a goal of becoming useful to a community. Dr. Steel used his work on procrastination as an example. His website offered information and resources that attracted people interested in the topic while also providing a place for his own work. I found this suggestion important, because building a resource gives people an easy access to it.

Plan for Dissemination Earlier

As our conversation was nearing its end, I shared a realization that had been developing throughout the interview. Perhaps dissemination should not be an afterthought. If we wait until an article is published to ask who might benefit from it, we may have missed opportunities to involve those audiences in selecting the right research questions or developing useful outputs.

My conversation with him reiterated the idea that publication is only the beginning of a scientific contribution. Taken together, here is what I learned:

• Think beyond the individual study. When possible, help audiences understand what the accumulated evidence suggests.
• Identify who needs to know. A specific and relevant audience may matter more than the largest possible audience.
• Explain why the research matters to that audience. Do not require readers to make the connection themselves.
• Match the format to the user. An academic article, executive summary, website, practitioner guide, or interactive tool may serve different purposes and resonate differently with different audiences.
• Build relationships around the problem. Dissemination is more effective when researchers engage with the communities connected to their work.
• Become a resource on the topic. Do not limit dissemination to promoting one study at a time.
• Consider fellow researchers sharing the same or similar research interests as allies. Build relationships with them to collectively advance the research and scientific practice in those topic areas.

Last,

• Think about dissemination while conducting the research. The intended use and audience should not be discovered after publication.

Accessible Dissemination

Our conversation yielded a list of questions that one should ask, perhaps sequentially, when developing their research dissemination plan. Some of them are:

• Is the journal article the most useful final format, or might my target audience also need my research in a different format (e.g., a summary report, tool, website, training resource)?
• In case of a journal publication, will my research findings be trapped behind a paywall? What can I do to address this issue (e.g., making a preprint available)?
• And will any technical terms used in the published article make my findings inaccessible to the people who need them? How do I address this issue (e.g., providing glossary, using footnotes)?

Speaking of technical terms, I recently came across two resources that can be useful for researchers but in slightly different ways. The Plain Language Association International (PLAIN), which is a leading international membership organization for plain language, offers a practical style guide and examples for learning clear-writing principles. And the plain-language guide series on digital.gov is especially useful if you are writing for a public or federally linked communications.

Besides these resources, I suggest skimming through the following couple of resources that spell out dissemination. I found them incredibly insightful as, in my case, the value of research work is its utilization (as much as its publication).

• Although set in a human service agency context, the Osterling and Austin (2008) article describes factors related to dissemination and utilization of research.
• If policy makers are your target audience, the Ashcraft et al. (2020) systematic review could be helpful.

It is my understanding that, in comparison to the research in education and healthcare, which include multiple resources of dissemination, I-O psychology has none (although some may argue that SIOP, especially TIP, offers guidance on this topic to some extent). It’d be great if we as a field could work toward a framework or look outside of our field for successful dissemination models/frameworks. Additionally, we should actively discuss how we could make our research useful to our target audience.

Continuing This Topic Into the Next Column

My conversation with Dr. Steel reinforced the idea that publication is only the beginning of a scientific contribution. Knowledge must be accessible if it is to influence future research and practice. Yet accessibility raises another challenge. As the audience for I-O psychology expands, we must learn to communicate evidence in ways that remain both engaging and accurate. My next column will, therefore, focus on a related but separate challenge: how researchers can translate that evidence for people who may never read a research paper. In other words, how do we make research more accessible to a wider audience without oversimplifying it? Is it even possible?

As the potential audience for I-O psychology grows, so does the responsibility to communicate research in ways that are understandable without sacrificing nuance. To explore that tension, I turned to someone who has spent much of his career translating organizational research for broader audiences, Dr. Adam Grant, who is the Saul P. Steinberg professor of Management and professor of Psychology at the Wharton School, University of Pennsylvania.

Dr. Grant has arguably become one of the most successful examples within the I-O community of translating I-O and management research for broad audiences through various media/formats. I am sure he has repeatedly faced the challenge of accessible dissemination. And I am hoping that interviewing him would provide insights from someone who has successfully brought I-O psychology into the mainstream. Note that I acknowledge that his experiences may not generalize to most of us because very few scholars have his platform, resources, visibility, and/or communication skills. Therefore, rather than asking how every researcher can become the next Adam Grant, my hope is to understand his approach that may help us communicate more effectively with wider audiences.

So, stay tuned!

Author Note

Share your comments, feedback, or your “publication stories” by emailing Bharati Belwalkar or reaching out via LinkedIn.

I acknowledge using Microsoft Copilot for editorial support; however, the interview transcript analysis and insights are original.

Notes

1 Although from the public health field, the Green et al. (2009, p. 152) article offers a simple yet comprehensive definition of dissemination as “the conscious effort to spread new knowledge, policies, and practices to target audiences or the public at large.”

Reference

Ashcraft, L. E., Quinn, D. A., & Brownson, R. C. (2020). Strategies for effective dissemination of research to United States policymakers: a systematic review. Implementation Science, 15(1), 89.

Bosco, F. A., Field, J. G., Larsen, K. R., Chang, Y., & Uggerslev, K. L. (2020). Advancing meta-analysis with knowledge-management platforms: Using metaBUS in psychology. Advances in Methods and Practices in Psychological Science, 3(1), 124-137.

Bosco, F. A., Uggerslev, K. L., & Steel, P. (2017). MetaBUS as a vehicle for facilitating meta-analysis. Human Resource Management Review, 27(1), 237-254.

Green, L. W., Ottoson, J. M., Garcia, C., & Hiatt, R. A. (2009). Diffusion theory and knowledge dissemination, utilization, and integration in public health. Annual Review of Public Health, 30(1), 151-174.

Osterling, K. L., & Austin, M. J. (2008). The dissemination and utilization of research for promoting evidence-based practice. Journal of evidence-based social work, 5(1-2), 295-319.

Steel, P. (2007). The nature of procrastination: a meta-analytic and theoretical review of quintessential self-regulatory failure. Psychological Bulletin, 133(1), 65.