Development of a synoptic MRI report for primary rectal cancer

As the recent collection of papers from the Quality Enhancement Research Initiative (QUERI) Series indicates, knowledge is leading to considerable action in the United States (U.S.) Department of Veterans Affairs (VA). The QUERI Series offers clinical researchers, implementation scientists, health systems, and health research funders from around the globe a unique window into the both the practice and science of implementation or knowledge translation (KT) in the VA. By describing successes and challenges as well as setbacks and disappointments, the QUERI Series is all the more useful. From the vantage point of Canadian KT researchers and officials at a national health research funding agency, we offer a number of observations and lessons that can be learned from QUERI. "Knowledge, if it does not determine action, is dead to us." Plotinus (Roman philosopher 205AD-270AD)     

Tailoring an intervention to the context and system redesign related to the intervention: A case study of implementing shared medical appointments for diabetes

Background

Health care organizations exert significant influence on the manner in which clinicians practice and the processes and outcomes of care that patients experience. A greater understanding of the organizational milieu into which innovations will be introduced, as well as the organizational factors that are likely to foster or hinder the adoption and use of new technologies, care arrangements and quality improvement (QI) strategies are central to the effective implementation of research into practice. Unfortunately, much implementation research seems to not recognize or adequately address the influence and importance of organizations. Using examples from the U.S. Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI), we describe the role of organizational research in advancing the implementation of evidence-based practice into routine care settings.

Methods

Using the six-step QUERI process as a foundation, we present an organizational research framework designed to improve and accelerate the implementation of evidence-based practice into routine care. Specific QUERI-related organizational research applications are reviewed, with discussion of the measures and methods used to apply them. We describe these applications in the context of a continuum of organizational research activities to be conducted before, during and after implementation.

Results

Since QUERI's inception, various approaches to organizational research have been employed to foster progress through QUERI's six-step process. We report on how explicit integration of the evaluation of organizational factors into QUERI planning has informed the design of more effective care delivery system interventions and enabled their improved "fit" to individual VA facilities or practices. We examine the value and challenges in conducting organizational research, and briefly describe the contributions of organizational theory and environmental context to the research framework.

Conclusion

Understanding the organizational context of delivering evidence-based practice is a critical adjunct to efforts to systematically improve quality. Given the size and diversity of VA practices, coupled with unique organizational data sources, QUERI is well-positioned to make valuable contributions to the field of implementation science. More explicit accommodation of organizational inquiry into implementation research agendas has helped QUERI researchers to better frame and extend their work as they move toward regional and national spread activities.     

Measuring persistence of implementation: QUERI Series

Background

We describe how we used the framework of the U.S. Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI) to develop a program to improve rates of diagnostic testing for the Human Immunodeficiency Virus (HIV). This venture was prompted by the observation by the CDC that 25% of HIV-infected patients do not know their diagnosis – a point of substantial importance to the VA, which is the largest provider of HIV care in the United States.

Methods

Following the QUERI steps (or process), we evaluated: 1) whether undiagnosed HIV infection is a high-risk, high-volume clinical issue within the VA, 2) whether there are evidence-based recommendations for HIV testing, 3) whether there are gaps in the performance of VA HIV testing, and 4) the barriers and facilitators to improving current practice in the VA. Based on our findings, we developed and initiated a QUERI step 4/phase 1 pilot project using the precepts of the Chronic Care Model. Our improvement strategy relies upon electronic clinical reminders to provide decision support; audit/feedback as a clinical information system, and appropriate changes in delivery system design. These activities are complemented by academic detailing and social marketing interventions to achieve provider activation.

Results

Our preliminary formative evaluation indicates the need to ensure leadership and team buy-in, address facility-specific barriers, refine the reminder, and address factors that contribute to inter-clinic variances in HIV testing rates. Preliminary unadjusted data from the first seven months of our program show 3–5 fold increases in the proportion of at-risk patients who are offered HIV testing at the VA sites (stations) where the pilot project has been undertaken; no change was seen at control stations.

Discussion

This project demonstrates the early success of the application of the QUERI process to the development of a program to improve HIV testing rates. Preliminary unadjusted results show that the coordinated use of audit/feedback, provider activation, and organizational change can increase HIV testing rates for at-risk patients. We are refining our program prior to extending our work to a small-scale, multi-site evaluation (QUERI step 4/phase 2). We also plan to evaluate the durability/sustainability of the intervention effect, the costs of HIV testing, and the number of newly identified HIV-infected patients. Ultimately, we will evaluate this program in other geographically dispersed stations (QUERI step 4/phases 3 and 4).     

Lessons for non-VA care delivery systems from the U.S. Department of Veterans Affairs Quality Enhancement Research Initiative: QUERI Series

The U.S. Veterans Health Administration (VHA) may have a very different structure and function from the organizations and practices that provide medical care to most Americans, but those organizations and practices could learn a lot from the VHA's Quality Enhancement Research Initiative (QUERI). There are at least six topics of increasing importance for implementation research where QUERI experience should be of value to other non-VHA organizations, both within and external to the United States: 1) Researcher-clinical leader partnerships for care improvement; 2) Attention to culture, capacity, leadership, and a supportive infrastructure; 3) Practical economic evaluation of quality implementation efforts; 4) Human subject protection problems; 5) Sustainability of improvements; and 6) Scale-up and spread of improvements. The articles in Implementation Science's QUERI Series provide the details of those lessons for others who are willing to invest the time to translate them into their different settings.     

Advancing Ecosystem Science by Promoting Greater Use of Theory and Multiple Research Approaches in Graduate Education

Since the inaugural edition of Ecosystems was published in 1998, ecosystem science has undergone substantial changes including the development of new research methods and an increasing emphasis on collaborations across traditional academic boundaries. In response to this transformation, we reflect on the current state of theory in ecosystem science, and make recommendations for training the next generation of Ph.D.-level ecosystem scientists. Specifically, we call for increased integration of theory into ecosystem science and outline the utility of iterating between theory and data generated by observations, experiments, and quantitative models. We recommend exposing graduate students to these three major approaches for generating data and propose strategies that students, advisors, and departments can employ to ensure this exposure. Ultimately, a successful training program will provide students with an understanding of key theories related to ecosystem science and how they interact with data, an appreciation for the interconnectedness of approaches to scientific inference, and a well-developed skill set in at least one approach—thereby empowering them to confidently tackle our pressing environmental problems. Although this is a daunting list of goals, continuing to advance our understanding of how ecosystems function necessitates a rigorous and well-developed training program.     

新世纪中推动生物科学发展的“Bio-X”

近二年国际上正掀起建立以生物科学为中心的交叉学科研究中心或研究所等实体的热潮。其中最引入注目的是美国斯坦福大学以诺贝尔物理学奖获得者朱棣文教授等人组建的“Bio-X”研究中心。Bio-X中的Bio为生物学,X泛指物理学、化学、工程学、医学等其它学科,在新世纪到来之时,生物科学中有不少迅速发展的领域迫切需要多学科交叉共同研究和参与,特别是：后基因组、基于同步辐射的结构生物学、单分子测量、纳米技术、脑科学、生物医学工程等。     

Computational opportunities for remote collaboration and capacity building afforded by Web 2.0 and cloud computing

In this paper, we state our aims and aspirations for building a global network of likeminded people interested in developing and encouraging students in the field of computational biophysics (CB). Global capacity building efforts have uncovered local computational talent in virtually every community regardless of where the students reside. Our vision is to discover and encourage these aspiring investigators by suggesting ways that they and other "garage scientists" can participate in new science even if they have no access to sophisticated research infrastructure. We argue that participatory computing in the "cloud" is particularly suitable for CB and available to any budding computational biophysicist if he or she is provided with open-minded mentors who have the necessary skills and generosity. We recognize that there are barriers to the development of such remote collaborations, and we discuss possible pathways to overcome these barriers. We point out that this Special Issue of Biophysical Reviews provides a much-needed forum for the development of several specific applications of CB.     

The rhizosphere: complex by design

The rhizosphere represents one of the most complex ecosystems on earth with almost every root on the planet expected to have a chemically, physically and biologically unique rhizosphere. Despite its intrinsic complexity, understanding the rhizosphere is vital if we are to solve some of the world’s most impending environmental crises such as sustainable food, fibre and energy production, preservation of water resources and biodiversity, and mitigation against climate change. One of the key challenges that faces rhizosphere ecologists is how to translate their fundamental research into practical real-world applications. In addition, they need to convince policy makers that consideration of the rhizosphere is vital in the formulation and implementation of any environmental policy relating to plant growth. This is highlighted by the recent biofuel and carbon debt debate whereby rhizosphere processes such as priming were largely ignored leading to destabilization of national policies. Recent advances in our understanding of the tangled web of rhizosphere interactions have been largely driven by technological innovations in analytical, bioinformatic and imaging tools, and this is likely to continue for the foreseeable future. However, there is also a critical need to incorporate this more reductionist information into mathematical models that are capable of incorporating the rhizosphere to allow simulation of plot- or landscape-level processes that are particularly relevant to policymakers. Consequently, as the multidisciplinary rhizosphere science community grows, there will be increasing need to both integrate scientific information and to subsequently convey this in an effective manner to stakeholders. If we can achieve this we will be in a good position to help prevent ongoing global environmental degeneration. These issues were addressed at the RHIZOSPHERE 2 International Conference which was held at Montpellier, France in August 2007. This special issue gathers some of the research presented during this major event.     

To Crowdfund Research,Scientists Must Build an Audience for Their Work

As rates of traditional sources of scientific funding decline, scientists have become increasingly interested in crowdfunding as a means of bringing in new money for research. In fields where crowdfunding has become a major venue for fundraising such as the arts and technology, building an audience for one''s work is key for successful crowdfunding. For science, to what extent does audience building, via engagement and outreach, increase a scientist''s abilities to bring in money via crowdfunding? Here we report on an analysis of the #SciFund Challenge, a crowdfunding experiment in which 159 scientists attempted to crowdfund their research. Using data gathered from a survey of participants, internet metrics, and logs of project donations, we find that public engagement is the key to crowdfunding success. Building an audience or “fanbase” and actively engaging with that audience as well as seeking to broaden the reach of one''s audience indirectly increases levels of funding. Audience size and effort interact to bring in more people to view a scientist''s project proposal, leading to funding. We discuss how projects capable of raising levels of funds commensurate with traditional funding agencies will need to incorporate direct involvement of the public with science. We suggest that if scientists and research institutions wish to tap this new source of funds, they will need to encourage and reward activities that allow scientists to engage with the public.     

Science‐Driven Restoration: A Square Grid on a Round Earth?

Is formal science necessarily an effective framework and methodology for designing and implementing ecological restoration programs? My experience as an ecologist in Hawaii suggests that even when scientific research programs are explicitly designed to guide and facilitate restoration, the culture of science, heterogeneity of nature, and real‐world complexities of implementing land management practices often limit the practical relevance of conventional scientific research. Although alternative models such as adaptive management and transdisciplinary science may facilitate research that more robustly models the real world, there is often little professional support or incentive to orient even these nonconventional research approaches toward actually solving on‐the‐ground problems. Thus, if one’s goal is to accomplish ecological restoration as quickly and efficiently as possible, a trial‐and‐error/intelligent tinkering–type approach might often be better than using more rigorous, data‐intensive scientific methodology. However, the sympatric implementation of ecological restoration and scientific research programs can lead to valuable synergies such as mutual logistical and financial support and the exchange of distinct forms of knowledge. The professional activities and mere presence of scientists can also greatly enhance a program’s prestige and visibility, which in turn can indirectly promote more and better ecological restoration. Improving our understanding of when formal science can directly assist restoration projects and when its value will more likely be synergistic and indirect could lead to better science, better ecological restoration, and better relationships between these two cultures.     

Role of "external facilitation" in implementation of research findings: a qualitative evaluation of facilitation experiences in the Veterans Health Administration

Background

Facilitation has been identified in the literature as a potentially key component of successful implementation. It has not, however, either been well-defined or well-studied. Significant questions remain about the operational definition of facilitation and about the relationship of facilitation to other interventions, especially to other change agent roles when used in multi-faceted implementation projects. Researchers who are part of the Quality Enhancement Research Initiative (QUERI) are actively exploring various approaches and processes, including facilitation, to enable implementation of best practices in the Veterans Health Administration health care system – the largest integrated healthcare system in the United States. This paper describes a systematic, retrospective evaluation of implementation-related facilitation experiences within QUERI, a quality improvement program developed by the US Department of Veterans Affairs.

Methods

A post-hoc evaluation was conducted through a series of semi-structured interviews to examine the concept of facilitation across several multi-site QUERI implementation studies. The interview process is based on a technique developed in the field of education, which systematically enhances learning through experience by stimulating recall and reflection regarding past complex activities. An iterative content analysis approach relative to a set of conceptually-based interview questions was used for data analysis.

Findings

Findings suggest that facilitation, within an implementation study initiated by a central change agency, is a deliberate and valued process of interactive problem solving and support that occurs in the context of a recognized need for improvement and a supportive interpersonal relationship. Facilitation was described primarily as a distinct role with a number of potentially crucial behaviors and activities. Data further suggest that external facilitators were likely to use or integrate other implementation interventions, while performing this problem-solving and supportive role.

Preliminary Conclusions

This evaluation provides evidence to suggest that facilitation could be considered a distinct implementation intervention, just as audit and feedback, educational outreach, or similar methods are considered to be discrete interventions. As such, facilitation should be well-defined and explicitly evaluated for its perceived usefulness within multi-intervention implementation projects. Additionally, researchers should better define the specific contribution of facilitation to the success of implementation in different types of projects, different types of sites, and with evidence and innovations of varying levels of strength and complexity.     

Attitudes to biotechnology: estimating the opinions of a better-informed public

Public familiarity with basic scientific concepts and principles has been proposed as essential for effective democratic decision-making (Miller, 1998). Empirical research, however, finds that public 'scientific literacy' is generally low, falling well short of what normative criteria would consider 'acceptable.' This has prompted calls to better engage, educate and inform the public on scientific matters, with the additional, usually implicit assumption that a knowledgeable citizenry should express more supportive and favourable attitudes toward science. Research investigating the notion that 'to know science is to love it' has provided only weak empirical support and has itself been criticised for representing science and technology as a unified and homogenous entity. In practice, it is argued, how knowledge impacts on the favourability of attitudes will depend on a multiplicity of actors, not the least of which is the particular area of science in question and the technologies to which it gives rise (Evans & Durant, 1992). This article uses a new method for examining the knowledge-attitude nexus on a prominent area of 21st century science--biotechnology. The idea that greater scientific knowledge can engender change in the favourability of attitudes toward specific areas of science is investigated using data from the 2000 British Social Attitudes Survey and the 1999 Wellcome Consultative Panel on Gene Therapy. Together the surveys measure public opinion on particular applications of genetic technologies, including gene therapy and the use of genetic data, as well as more general attitudes towards genetic research. We focus our analysis on how two different measures of knowledge impact on these attitudes; one a more general measure of scientific knowledge, the other relating specifically to knowledge of modern genetic science. We investigate what impact these knowledge domains have on attitudes toward biotechnology using a regression-based modelling technique (Bartels, 1996; Althaus, 1998; Sturgis, 2003). Controlling for a range of socio-demographic characteristics, we provide estimates of what collective and individual opinion would look like if everyone were as knowledgeable as the currently best-informed members of the general public on the knowledge domains in question. Our findings demonstrate that scientific knowledge does appear to have an important role in determining individual and group attitudes to genetic science. However, we find no support for a simple 'deficit model' of public understanding, as the nature of the relationship itself depends on the application of biotechnology in question and the social location of the individual.     

Implementation science in resource-poor countries and communities

Background

Implementation science in resource-poor countries and communities is arguably more important than implementation science in resource-rich settings, because resource poverty requires novel solutions to ensure that research results are translated into routine practice and benefit the largest possible number of people.

Methods

We reviewed the role of resources in the extant implementation science frameworks and literature. We analyzed opportunities for implementation science in resource-poor countries and communities, as well as threats to the realization of these opportunities.

Results

Many of the frameworks that provide theoretical guidance for implementation science view resources as contextual factors that are important to (i) predict the feasibility of implementation of research results in routine practice, (ii) explain implementation success and failure, (iii) adapt novel evidence-based practices to local constraints, and (iv) design the implementation process to account for local constraints. Implementation science for resource-poor settings shifts this view from “resources as context” to “resources as primary research object.” We find a growing body of implementation research aiming to discover and test novel approaches to generate resources for the delivery of evidence-based practice in routine care, including approaches to create higher-skilled health workers—through tele-education and telemedicine, freeing up higher-skilled health workers—through task-shifting and new technologies and models of care, and increasing laboratory capacity through new technologies and the availability of medicines through supply chain innovations. In contrast, only few studies have investigated approaches to change the behavior and utilization of healthcare resources in resource-poor settings. We identify three specific opportunities for implementation science in resource-poor settings. First, intervention and methods innovations thrive under constraints. Second, reverse innovation transferring novel approaches from resource-poor to research-rich settings will gain in importance. Third, policy makers in resource-poor countries tend to be open for close collaboration with scientists in implementation research projects aimed at informing national and local policy.

Conclusions

Implementation science in resource-poor countries and communities offers important opportunities for future discoveries and reverse innovation. To harness this potential, funders need to strongly support research projects in resource-poor settings, as well as the training of the next generation of implementation scientists working on new ways to create healthcare resources where they lack most and to ensure that those resources are utilized to deliver care that is based on the latest research results.

     

Can optimality models and an ‘optimality research program’ help us understand some plant–fungal relationships?

In this paper we suggest that the field of fungal ecology may benefit from the use of optimality models in the context of an ‘optimality research program’ (ORP). An ORP is a research program in the sense of modern philosopher of science Lakatos' [1978. The Methodology of Scientific Research Programmes: philosophical papers, vol. 1. Cambridge University Press, Cambridge] seminal work. An optimality research program has a lengthy history and record of success in the field of behavioural ecology, but has been seldom employed in fungal ecology. We discuss the ORP and provide some examples of how optimality models may be useful in fungal ecology. We suggest that such an approach may benefit experimental fungal ecologists by: providing a framework for organizing knowledge; generating hypotheses; helping in the planning of experiments; aiding in the interpretation of results; and directing the next steps of an experimental research program. We illustrate these benefits by sketching out how an ORP might be used to answer some fundamental questions about the interactions between host plants and arbuscular mycorrhizal fungi.     

Implementing an innovative consent form: the PREDICT experience

Background

This article describes the process used by the authors in developing an implementation intervention to assist VA substance use disorder clinics in adopting guideline-based practices for treating depression. This article is one in a Series of articles documenting implementation science frameworks and tools developed by the U.S. Department of Veterans Affairs (VA) Quality Enhancement Research Initiative (QUERI).

Methods

The process involves two steps: 1) diagnosis of site-specific implementation needs, barriers, and facilitators (i.e., formative evaluation); and 2) the use of multi-disciplinary teams of local staff, implementation experts, and clinical experts to interpret diagnostic data and develop site-specific interventions. In the current project, data were collected via observations of program activities and key informant interviews with clinic staff and patients. The assessment investigated a wide range of macro- and micro-level determinants of organizational and provider behavior.

Conclusion

The implementation development process described here is presented as an optional method (or series of steps) to consider when designing a small scale, multi-site implementation study. The process grew from an evidence-based quality improvement strategy developed for – and proven efficacious in – primary care settings. The authors are currently studying the efficacy of the process across a spectrum of specialty care treatment settings.     

A Practical Guide for Improving Transparency and Reproducibility in Neuroimaging Research

Recent years have seen an increase in alarming signals regarding the lack of replicability in neuroscience, psychology, and other related fields. To avoid a widespread crisis in neuroimaging research and consequent loss of credibility in the public eye, we need to improve how we do science. This article aims to be a practical guide for researchers at any stage of their careers that will help them make their research more reproducible and transparent while minimizing the additional effort that this might require. The guide covers three major topics in open science (data, code, and publications) and offers practical advice as well as highlighting advantages of adopting more open research practices that go beyond improved transparency and reproducibility.     

Misconceptions in biology: a meta-synthesis study of research, 2000–2014

Abstract

Teachers need to be aware of biology misconceptions in their classrooms and how to address them. In response, researchers and science educators have suggested and examined effective practices to prevent and ameliorate misconceptions. An extensive review of the literature gives researchers and educators insights into trends, practices, and gaps in the misconceptions research and helps decide which issues to address and why. The current study shares how researchers in Turkey conduct a content analysis of published misconception research in Turkey by using a form. The analysis resulted in a meta-synthesis (thematic content analysis) that inventoried and compared the purposes, research methods, data collection instruments, and findings of the selected publications. Biology educators in other regions of the world can inform their practice by using this instrument and research methods to learn about trends and patterns in misconception research. Researchers will gain insights into effective methods that have been used to examine misconceptions and will be able to identify biology misconceptions that have been under-investigated and need further analysis.     

Study protocol of the YOU CALL - WE CALL TRIAL: impact of a multimodal support intervention after a "mild" stroke

Background

More than 60% of new strokes each year are "mild" in severity and this proportion is expected to rise in the years to come. Within our current health care system those with "mild" stroke are typically discharged home within days, without further referral to health or rehabilitation services other than advice to see their family physician. Those with mild stroke often have limited access to support from health professionals with stroke-specific knowledge who would typically provide critical information on topics such as secondary stroke prevention, community reintegration, medication counselling and problem solving with regard to specific concerns that arise. Isolation and lack of knowledge may lead to a worsening of health problems including stroke recurrence and unnecessary and costly health care utilization. The purpose of this study is to assess the effectiveness, for individuals who experience a first "mild" stroke, of a sustainable, low cost, multimodal support intervention (comprising information, education and telephone support) - "WE CALL" compared to a passive intervention (providing the name and phone number of a resource person available if they feel the need to) - "YOU CALL", on two primary outcomes: unplanned-use of health services for negative events and quality of life.

Method/Design

We will recruit 384 adults who meet inclusion criteria for a first mild stroke across six Canadian sites. Baseline measures will be taken within the first month after stroke onset. Participants will be stratified according to comorbidity level and randomised to one of two groups: YOU CALL or WE CALL. Both interventions will be offered over a six months period. Primary outcomes include unplanned use of heath services for negative event (frequency calendar) and quality of life (EQ-5D and Quality of Life Index). Secondary outcomes include participation level (LIFE-H), depression (Beck Depression Inventory II) and use of health services for health promotion or prevention (frequency calendar). Blind assessors will gather data at mid-intervention, end of intervention and one year follow up.

Discussion

If effective, this multimodal intervention could be delivered in both urban and rural environments. For example, existing infrastructure such as regional stroke centers and existing secondary stroke prevention clinics, make this intervention, if effective, deliverable and sustainable.

Trial Registration

ISRCTN95662526     

Freelancer

What long‐term changes can we expect, in how academic work is conducted and remunerated, in the post‐pandemic world? Subject Categories: S&S: Economics & Business, S&S: History & Philosophy of Science, S&S: Ethics

Although still two years away, my looming “retirement” from university employment is inevitably going to herald a major change of life. “Of course, you''ll become ‘Emeritus’”, most colleagues have opined. My answer to all of them has been a firm “No. I''ll become a freelancer”. The concept of a freelance scientist is obviously so alien to most of them that they invariably change the subject immediately. However, my gut feeling is that in 20 years or less, almost all of us will be freelancers of some kind.The COVID‐19 pandemic has altered the world of work in very obvious ways. There has been much talk of how the changes are likely to carry over to the future, even if more traditional patterns will probably reassert themselves in the short to medium term. Working from home, conducting meetings remotely, not wasting days travelling between continents for a few precious hours of face‐time and being free to structure workdays around our own priorities: these are the most obvious novelties that many believe will continue long after the effects of the pandemic on health and wealth have faded. But I have a slightly different take.Major disruptive events of worldwide import—world wars, global economic slumps, cataclysmic volcanic eruptions and pandemics—have often been harbingers of profound social change. This is not only due to their direct and immediate effects, but more so because the disruption accelerates and facilitates changes that were already happening. In the case of COVID‐19, one may place in this category the demise of cash, the rise of streaming services in place of live entertainment, online grocery shopping and even virtual dating. Another is paying people to stay home and do nothing, otherwise known as the universal basic income (or, in the USA, “stimulus cheques”).Inefficient practices in academia are equally ripe for change. Why bother with classes for 500 first‐year students when a much better edition of the lecture by an expert communicator is available on the internet? What’s the use of an ageing PhD advisor 20 years away from bench science, who struggles to guide the next generation of experimentalists in the lab, when the expertise of a plethora of specialists can easily be accessed online? What’s the value in published papers that are read by fewer people than wrote them? Or in seminars delivered to a roomful of attentive postdocs and PhD students who lack the courage or the time to address even a single question to the speaker?Yes, there is still great value in small‐group teaching and mentorship, in the creative verve of a close‐knit laboratory team, and in good writing and oratory: but the required skills are already different from those in which we were schooled. Thus, even if I do not hold in my palm the crystal ball to predict exactly which changes will happen and how fast, I believe that our traditional jobs are going to melt away very fast in the post‐pandemic world. Universities and research institutes may still exist, but I expect that their practices will be different, reshaped by rational need more than by tradition. Today’s academic science is already quite unlike that of 1920, but it has evolved so slowly during that century—spanning a much longer time period than the lifetime of a scientific career—that we barely perceive the changes that have occurred. In contrast, the changes now afoot will certainly happen much faster, especially since the funds to support the current “inefficient” model are likely to diminish rapidly.So, I predict that university teaching and science communication in general will be the first to evolve into freelance activities, where universities will invite bids from individuals or their agents and award commissions on a fee‐paying basis rather than using salaried employees. But these are not the only component parts of academia facing such a shake‐up. The practices of laboratory science are also likely to be rebuilt. When discussing with colleagues how research might be undertaken on a freelance basis, they usually raise issues such as bricks and mortar and the complex infrastructure that is needed to sustain cutting‐edge research, especially in the life sciences: how, they ask, could a freelancer access state‐of‐the‐art imaging, mass spectrometry or DNA sequencing? How could their acquisition of such expensive hardware possibly be financed, especially if they had to somehow acquire it personally and set it up in the garage or carry it around with them?But the answers to these questions are already evident in the practices of some major research agencies, most notably in Europe’s pioneering funder of single‐investigator grants for blue‐skies science, the European Research Council (ERC). The ERC already treats its awardees as freelancers, in the sense that it encourages them to shop around for the most attractive venue in which to embed and implement their research project. The quest for the best host institution takes place not only at the preparatory step of an ERC application: it also happens after the grant is awarded, since the grant money is considered inherently portable and can even be moved later on from one institution to another. This encourages potential host universities to compete for providing the best research environment, in which many factors come into play, not just but not least, the quality of its research infrastructure. How well it supports, rather than burdens its staff with administrative tasks, the nature of its recruitment and personnel policies, how it handles relocation issues for incoming researchers and their families, what opportunities it provides for further training in relevant skills and career development: these are just some of the factors in play.In recent years, universities have seen their primary role in this process as encouraging their own tenured or tenure‐track staff to apply for ERC grants. But I foresee the emphasis shifting increasingly to investigators who seek out universities that can make the most appealing offer, whilst universities and government agencies standing behind them will shape their policies so as to remain competitive. Moreover, in such a landscape there is no reason why a scientist cannot operate research projects on multiple sites if this offers the most convenient arrangement. The tools for remote meetings and cloud computing to which we have all become accustomed mean that there is no longer any need for a research group to be located in one building or even in one country, to operate efficiently as a team.At the same time, many of the tasks involved in running a research institute or department can be efficiently outsourced to the most competitive bidder—to be assessed on the basis of value‐for‐money, not just minimum cost. As a society, we should be asking ourselves why we continue to waste the talents of highly specialized scientists on performing admin tasks for which they are neither properly trained nor motivated, instead of just engaging a smart‐software developer. Why should we fund creative thinkers to undertake laboratory projects in host institutions that do not have the required state‐of‐the‐art facilities to perform them? Or allocate budgets that are so pared down that grantholders cannot even afford to purchase such services elsewhere? Why should we expect them to make do with poorly paid trainees instead of a team of professionals? And why should we continue to organize research in pyramid structures where everything depends on commands from the top, where all findings are announced using an institutional slide template, where colleagues elsewhere are considered as untrustworthy “competitors”, and where credit for individual creativity is usurped by seniors who barely know the contents of the papers they “write”?In the “old system”, we have all gotten used to making do with sub‐optimal working arrangements and grumbling about them, whilst considering them an immutable fact of life. But I envisage a time coming soon where we scientists will have the edge in reshaping the market for teaching and research in a way that is much more to our liking and properly aligned with our skills. At the same time, our individual success in accomplishing our professional goals will have a direct effect on our income and job satisfaction, and steer us towards activities where our talents are most effectively deployed. In short, I believe that we, as freelance scientists, will be much more firmly in control of science in the future and that time is not far off.     

Let's Make Gender Diversity in Data Science a Priority Right from the Start

The emergent field of data science is a critical driver for innovation in all sectors, a focus of tremendous workforce development, and an area of increasing importance within science, technology, engineering, and math (STEM). In all of its aspects, data science has the potential to narrow the gender gap and set a new bar for inclusion. To evolve data science in a way that promotes gender diversity, we must address two challenges: (1) how to increase the number of women acquiring skills and working in data science and (2) how to evolve organizations and professional cultures to better retain and advance women in data science. Everyone can contribute.Every March we celebrate both International Women’s Day and Women’s History Month. These annual celebrations remind us that through our current individual and collective behavior, all stakeholders can influence how gender-diverse our future history is likely to be. This is especially important in data science, an emerging science, technology, engineering, and math (STEM) field that is a critical driver for 21st century innovation.Data science focuses on the extraction of knowledge from data. It is a STEM discipline, but requires skills not yet widely taught in STEM disciplines: Skills in managing large datasets, novel analysis and inference approaches, rigorous statistical analysis, new ways to convey outcomes, and more. A recent McKinsey Report [1] indicates that the United States alone will need 1.5 million more data-savvy professionals and 140,000–190,000 more professionals with deep analytic skills by 2020. Helping to create and nurture a broad pool of individuals with data science skills is critical to addressing this growing need and will require intentional action.The emergent field of data science offers the opportunity to narrow the gender gap in STEM (in which only 13% of the engineering workforce and 25% of the computer and mathematical sciences workforce are women [2]) by making diversity a priority early on. In addition to this being the right thing to do, it is the smart thing to do: studies show that companies with employees characterized by diverse inherent traits (traits you were born with) and acquired traits (traits you gain from experience) are 45% more likely to report a growth in market share over the previous year, and 70% more likely to report capture of a new market [3]. Companies with diverse executive boards show higher returns on equity [4]. In short, diversity is a competitive asset in the private sector. In addition, increased diversity in STEM fields, including data science, is a national research and education priority [5].What better time, with increased focus on data science in the public sector, emerging educational curricula and focus within universities, and greater need within the private sector, to foster greater inclusivity and gender diversity? What can we do now to grow data science in a way that reflects the gender diversity and potential for innovation of the greater society?To evolve data science in a way that makes it a rewarding and sustainable career choice for women, we need to address two challenges: how can we increase the number of women acquiring skills and working in data science, and how can we evolve organizations and professional cultures to better retain and advance women in data science?