Ever since Charlie Goldsmith told the class last week that pie charts are a terrible way to convey information, my curiosity regarding data visualization approaches was piqued. The field of visualization is interesting to me. I believe this is also true for most people living in the information economy. Throughout our lives, info-graphics, charts, maps and diagrams depicting everything from bus routes to how our grades compare with others have bombarded us. We instinctively understand and trust visualized information, and we know when it’s done poorly.
Friedman (2008) suggests that the purpose of data analysis is to communicate data in a way that is clear and effective. It is far from new. The earliest forms of data visualization where maps, the oldest of which is thought to define the town of Konya, in modern day Turkey, dating back more than 8,000 years. The emergence of various forms of data visualization is well documented over the centuries (Friendly, 2009).
Data visualization isn’t without pitfalls, however. For example, Friedman argues that there is a tendency toward creating visually stimulating material that doesn’t carry sufficient usable information. On the other hand, Viegas and Wattenburg (2011) advocate making data “sexy” and engaging, as it increasingly becomes a public medium for disseminating knowledge, rather than a professional one. While the suggestion is certainly that visualized data should be both beautiful and informative, these visualization professionals seem to, at least partially, conceive of form and function as naturally inverse to each other.
Ebert, Favre and Peikert (2002) suggest another problem: the certainty of visualized data. When compared to statistical expressions, for example, data visualization has difficulty depicting the rate of uncertainty. To me, this speaks to the instinctive trust we have in graphics. Once something is displayed, and particularly on paper, it has a sense of finality that may not be representative of the fluidity of knowledge.
Ebert, Favre and Peikert (2002) also conceive of the notion of “data reduction;” the idea that in order to properly map, diagram, or otherwise display data, we must reduce it to it’s critical elements. The natural extension of this line of thought is that the displayed data is then missing concepts, which may create bias. Consider, for example, David McAndless’ (2008) example of military budgets. In the image labeled “War Chests,” the top 10 national defense budgets are listed. By this image, the United States is clearly seen as the largest spender. In fact, the box depicting US military spending is large enough to fit all the other budgets within it. If, however, we look at the graphic labeled “Big Spenders II,” we see defense spending as a percentage of GDP. Here, the US falls to 8th place. These sorts of biases could be exploited for political gain.
Given the limitations of data visualization, I still can’t help but be drawn to it as a form of knowledge translation. It’s simplicity and effectiveness as a tool cannot be understated. I also believe that the limitations it faces are common to other fields of knowledge translation. Many forms of expression have difficulty expressing certainty, and even statistics is somewhat inaccessible to those without training. Data reduction occurs with any kind of knowledge summarization. Indeed, the struggle between making a piece of knowledge engaging while keeping it informative is nearly universal. I believe that as we become more and more inundated with data, we will need more and more creative, effective ways to understand it, and data visualization will play a key role.
Ebert, D.; Favre, J.; Peikert, R. (2002). Data Visualization. Computers & Graphics 26(2). P 207-208. Retrieved from: http://www.sciencedirect.com.proxy.lib.sfu.ca/science/article/pii/S0097849302000511
Friedman, V. (2008) Data Visualization and Infographics. Smashing Magazine 1(14) , retrieved from: http://www.smashingmagazine.com/2008/01/14/monday-inspiration-data-visualization-and-infographics/
Friendly, M. (2009) Milestones in the history of thematic cartography, statistical graphics, and data visualization. York University. [electronic document]. Retrieved from: http://www.math.yorku.ca/SCS/Gallery/milestone/milestone.pdf
McAndless, D. (2008). Information is Beautiful: War Games. The Guardian. Retreived from http://www.theguardian.com/news/datablog/2010/apr/01/information-is-beautiful-military-spending
Viegas, F. & Wattenberg, M. (2011) How to Make Data Look Sexy. CNN. Retrieved from http://www.cnn.com/2011/OPINION/04/19/sexy.data/index.html?_s=PM:OPINION
Health Impact Assessment (HIA) is “a practical approach used to judge the potential health effects of a policy, programme or project on a population, particularly on vulnerable or disadvantaged groups” (WHO, 2013). The product of an HIA is a set of recommendations for decision-makers and stakeholders, which aim to enhance the proposal’s positive health effects and mitigate possible negative ones (WHO, 2013). A key underlying value of HIA, and also one of it’s strengths, is the engagement and involvement of stakeholders, including impacted communities, in the assessment and decision making process. Current developments in extractive sector HIA research provide a good reminder that HIA is meant to be a support tool for making shared-decisions among diverse stakeholders, and as such, could benefit from an update aimed at helping community members become more empowered and better informed. Promising research is underway.
Decision support tools (DST) exist in abundance. They target all sorts of decision makers, claiming to support the making of all sorts of decisions. DSTs can help decision makers: gather and organize information and knowledge; better understand (“get a handle on”) the situation or context; formulate answers to “what if?” questions; analyze or narrow the field of choice; and/or visualize the data or problem space (University of Cambridge). In the health care realm, Patient Decision Aids are used to involve patients in decisions related to their own care (Ottawa Hospital Research Institute). Other DSTs target clinicians, such as Cochrane reviews, clinical practice guidelines, and condition-specific order sets. The Lives Saved Tool (LiST) is meant for health policy makers to aid in priority setting for service delivery models (Campbell, 2012). If there is a decision to be made, there seems to be a DST to help.
Health Impact Assessment (HIA) is a DST that has been highly promoted by the World Health Organization in recent years as a tool for health promotion and a way of improving health across sectors (WHO, 2013). It is a process used to systematically consider and predict the health consequences of various implementation options for policies, programs and projects (Kemm, 2008). As a DST, HIA is ideally carried out alongside a decision making process during the policy or program development stage instead of after a decision has already been made (Kemm, 2008). A number of HIA toolkits and methodologies exist, but the general procedure for HIA is described in this flowchart:
(Source: WHO HIA. http://www.who.int/hia/about/en/)
HIA is used to inform many kinds of shared decisions at local, national and global levels. The implementation of resource extraction developments is but one example. Mining projects can affect the health of impacted communities both directly and indirectly by causing rapid change in the local social-ecological contexts (Winkler et al, 2012). Along with mining companies and local/national governments, impacted communities are obviously important stakeholders in project related decisions. HIA is an important method for including them in the planning process and supporting their informed-decision-making, in theory. Often however, there are barriers preventing this from happening in practice, especially in low- and middle-income countries. These include “high levels of illiteracy, language barriers, cultural, demographic, gender and social differences between stakeholders” (Winkler et al, 2012). These barriers put into question how ‘shared’ the decision making process actually is in these situations, and undermine the utility and success of HIA.
In response to this shortcoming, ‘HIA visualization’ techniques are being developed as a tool to communicate complex information about large development projects to various stakeholders including communities in rural and remote areas, health authorities, and project staff (Winkler, 2012). The approach is to visually display quantitative information “so that the maximum information is conveyed in the simplest and most visual manner” (Krieger et al, 2012). This is meant to address the problem of HIA inaccessibility. Typical impact assessment reports are lengthy, technically complicated, and difficult for most stakeholders to understand (Krieger et al, 2012). Adaptable spacial-temporal HIA visualizations in the form of short videos and ‘supergraphics’ for mining, oil and gas, and water resources projects have been created. The researchers behind this work suggest that their experience shows that these ‘aids’ have facilitated communication and understanding of HIA findings among various concerned groups. They call for other researchers to build upon their work (Krieger et al, 2012; Winkler et al, 2012).
Campbell S. (2012). Knowledge Translation Curriculum. Canadian Coalition for Global Health Research: Ottawa. http://www.sandy-campbell.com/sc/Publications.html
Kemm J. (2008). HIA: An aid to political decision-making? Scandinavian Journal of Public Health, 36:785-788.
Krieger GR, et al. (2012). Enhancing Impact: Visualization of an intergrated impact assessment strategy. Geospacial Health, 6(2):303-306.
Ottawa Hospital Research Institute. Patient Decision Aids. http://decisionaid.ohri.ca/index.html
University of Cambridge. Institute for Manufacturing. Research: Decision Support Tools. http://www.ifm.eng.cam.ac.uk/research/dstools/
Winkler MS, et al. (2012). Health impact assessment of industrial development projects: a spacial-temporal visualization. Geospacial Health, 6(2):299-301.
World Health Organization. (2013). Health Impact Assessment. http://www.who.int/hia/about/en/
- Every year 350,000 trials have been identified by the Cochrane Collaboration and 10,000 of them are included in Medline. (Grol & Grimshaw, 2003). The example of importance of hand washing that Grol and Grimshaw used as a case is clear since the mid-1800s but this simple obviously necessary part of any health practice is still overlooked by health care practitioners! Two centuries passed and every year we experiment thousands and thousands trials in addition to probably much more thousands and thousands health related research. We are still struggling with this fact that how we can change behaviour of people based on our 200 years ago research finding.
- Prevention and Intervention studies is supposed to be the most practical part of public health research because they are designed “to inform, change attitudes and perceptions, modify social norms, transform social contexts, and alter policies that are facilitators or barriers to healthy behaviours” (Lawrence & Fortenberry, 2007). Also it is widely accepted that change behaviour should employ theories of behaviour in their development (Michie, Hardman, & Eccles, 2008) because interventions based on theoretical models are far more likely to succeed than programs that do not benefit from a theoretical model. (Lawrence & Fortenberry p. 24).
- Lawrence & Fortenberry (2007) evaluate seven clusters of theoretical frameworks in the STD and HIV intervention studies. For instance, an important limitation of The Health Belief Model (HBM) that is categorized as one of the Cognitive Theories, is that this model “does not explain how perception of risk originate, nor does the model describe how health beliefs develop or persist over time” (p. 27). Again the authors’ criticism on another very popular framework in the intervention literature, Theory of Reasoned Action (TRA) is almost the same; although this model illustrates where to intervene among all related variables in the research, “it offers no specific guidance regarding how to implement intervention strategies” (ibid). The problem of these theories is not just lacking the “how-to” part, but the foundation of them which is based on the assumption that people make “rational choices” is hugely under question.
- However, here I see a controversy: “a theory is a systematic way of describing events and behaviours.” (p. 23). As Michie et al. (2008) conclude even when researchers use theory, “they end to use it to explain behaviour but not to change behaviour” (p. 663). They take an example of a systematic review conducted by Azjen of the application of the Theory of Planned Behaviour and show that the theory was “rarely used to design the intervention and was more frequently used as a background to understand he behaviour and to develop measures”. With the aim of filling the current gap of having no comprehensive list of techniques for behavioral change, Michie et al. (2008) conduct a research by reviewing reviews, brainstorming and extracting techniques in textbook. They generate a list of 53 behavioral change techniques with definitions and more 84 techniques without definitions, so they totally present a list of 137 behavioral change techniques. Then by using four specialists’ rating to the application of each technique for 11 behavior determents, they illustrate visually whether each technique can be applied for changing each determent of the behaviour. The figure shows that there is not much agreement among the specialists on the capability of identified techniques in changing behaviour.
- What is wrong with us as researchers and academicians? What are we doing really? Let’s look at the following table:
|World Hunger Statistics|
|Total number of children that die every year from hunger||1.5 million|
|Percent of world population considered to be starving||33%|
|Time between deaths of people who die from hunger||3.6 seconds|
|Total number of people in the world who suffer from hunger and malnutrition||800 million|
|Total number of people who do not have enough to eat||936 million people|
|Total percentage who do not have enough to eat who live in developing countries||98%|
|Total percentage of world’s hungry that live in 7 countries||65%|
|Number of people who died of hunger today||20,864|
|Total number of people who will die of hunger this year||7,615,360|
6. Sorry. I am too emotional to write #6.
Grol, R. & Grimshaw, J. (2003). “From the best evidence to best practice: effective implementation of change in patients’ care”, The Lancet, Vol 362, Oct. pp. 1255-1230.
Lawrence J. & Fortenberry, D. (2007). Behavioral interventions for STDs: Theoretical models and intervention methods. In S. O. Aral & J. M. Douglas (Eds.), Behavioral interventions for prevention and control of sexually transmitted diseases (pp. 23-59). New York: Springer.
Michie, S. et al. (2008). “From theory to intervention: Mapping theoretically delivered behavioral determinants to behavior change techniques”. Applied Psychology: An International Review, 57 (4). pp. 660-680.
World Hunger Statistics: http://www.statisticbrain.com/world-hunger-statistics/
Effective partnerships and knowledge translation (KT) are needed to encourage the ongoing inclusion of midwives in primary health care teams in Canada. Midwives are cost-efficient and effective members of any health care team, and may serve as brokers for knowledge translation (Tracy et al, 2013). However, there is resistance among health professionals, policy makers, and government and to fully embrace midwifery’s role in primary health care. Midwifery primary care focussing on nutrition, exercise and healthy breastfeeding with mothers is an important part of their work. Health promotion, an important component of public health, enables people to increase control over and improve their health (WHO, 1986). Education and informed choice (the mother makes the decisions about her care after being explained the choices by her midwife) are cornerstones of midwifery care, and are also part of health promotion. KT may increase knowledge among policy makers and local governments of the scope and abilities of midwives to play a role in primary health care teams.
To advance this change of practice, health systems decision-making can be enhanced by deliberative dialogues between members of the primary health care team, midwifery associations and regulatory bodies, community members, local government representatives and policy makers. Boyko et al (2012) have studied deliberative dialogue as a KT strategy and how it can support evidence-based decision-making. Key features of deliberative dialogue include an appropriate meeting environment, mix of participants and use of research evidence. Intended effects of the dialogue were to build mutual understanding, alternative ways of thinking about the problem, developing policy alternatives and health system capacity to make evidence-informed decisions (Boyko, 2012).
Lessons learned from KT around partnerships in a Canadian public health context may be perhaps be transposed to the midwifery and primary health team context. Knowledge from KT research may help us to know what works and what does not work to form and maintain effective partnerships that in turn, improve primary health care (Sibbald, 2012). There are many definitions of partnerships but some work better to increase capacities of teams. ‘Intra-partners’ involve partners from different domains working together to achieve a common goal. They can be professional in nature or partnerships between professionals, researchers and the community. Working with partners is thought to contribute to individual and community empowerment, and to lead to the use of research in decision making.
Partnerships have been found to be beneficial because they provide additional resources in time, personnel and funding (Sibbald, 2012). Health units in northern and remote areas need additional resources, including midwives who could share health promotion, maternal, infant and well woman education and clinical duties. Partnerships provide fresh ideas and an entrance to the community. A midwife partner in a rural health unit would make inroads to the community, because of her ability to work with women and their families, providing education and birthing assistance to parturient women.
Sibbald (2012) found that public health centers also formed community partnerships using integrated KT whose strength was based on trust, time and insider know-how.
Relationships are a key ingredient for effective knowledge translation. Integrated knowledge translation favouring a community centered participatory model, empowering individuals and increasing control of their health fits the role of midwives.
Partnerships are an essential feature of effective KT, and can transform practices or modes of intervention. Midwives could transform the way health units work with mothers or the interventions used in maternal infant care, such as the emphasis on personalized care and home visits. When midwives began to work with obstetricians teaching interdisciplinary courses, such as ALARM (Advances in Labour and Risk Management; SOGC) new knowledge was added to the course in handling some maternity concerns in physiological ways (such as the ‘Gaskin’ manoeuver to deliver a baby whose shoulders are stuck).
Knowledge translation on how to initiative, maintain and sustain partnerships may break down the barriers among health professions and encourage midwives to play a role as a full member of primary health care teams.
Advances in Labour and Risk (ALARM). SOGC. http://sogc.org/continuing-medical-education-cme/alarm/
Boyco J, Lavis J, Abelson J, Dobbins M, Carter N. (2012). Social Science & Medicine 75, 1938-1945.
Sibbald S, Kothari A, Rudman D, Dobbins M, Rouse M, Edwards N, Gore D. (2012). Partnerships in Public Health: Lessons from knowledge Translation and Program Planning. Western University. From the SelectedWorks of Anita Kothari. http://works.bepress.com/anita_kothari/29.
Tracy S, Hartz D, tracy M, Allen J, Forti A, Hall B, While J, Lainchbury A, Stapleton H, Beckmann M, Bisits A, Hommer C, Foureue M, Welsh A, Kildea S. (2013). Caseload midwifery care versus standard maternity care for women of any risk: M@NGO, a randomised controlled trial. The Lancet. Retrieved from http://dx.doi.org/10.1016/S0140-6736(13)61406-3
World Health Organization (1986). Ottawa Charter for Health Promotion. World Health Organization: First International Conference on Health Promotion, Ottawa, Canada.
You’ve got all the facts on your side, scientists are affirming your position, and you’ve identified a plan of action that paves the way to social change…but nobody will bite. What’s a person to do?
We’ve discussed the reasons for which the uptake of knowledge into practice isn’t consistent: information is poorly packaged; connections between knowledge producers and knowledge users are weak or non-existent. However, even if we manage to overcome these obstacles, ideology can block the way. It’s responsible for inaction (or poor action) on many pressing issues, such as climate change, poverty reduction, and sex education.
We can characterize approaches to sex education in the US as either comprehensive or abstinence only. Comprehensive sex education generally includes information about contraception use and reducing the risk of transmitting sexually transmitted infections (STIs). The catch is that this sort of sex education is morally objectionable to some people. Specifically, many social conservatives object to lessons that acknowledge or condone sex between unmarried individuals. These values have informed laws mandating abstinence-only sex education; presently, nineteen states have such legislation (Guttmacher Institute, 2013). Unfortunately, abstinence-only sex education fares poorly in terms of reducing unwanted outcomes when compared with comprehensive education (Kohler et al., 2008)
So, what to do? On the issue of climate change, Geoff Dembicki (2013) argues that climate activists need to reframe their rhetoric to better match the way in which conservatives see the world. Advocates for sex education might heed this advice and point to reductions in pregnancies that occur out of wedlock and a reduction in the number of abortions, which touch on two issues important to social conservatives.
Another option is to expand efforts to provide information online. This isn’t uncharted territory; there are already many online resources that provide comprehensive information about sexuality and sexual health. However, current efforts don’t appear to be sufficient. In a recent study of American youth aged 13-18, Mitchell et al. (2013, p. 6) found that only 19 percent of participants who identified as heterosexual accessed information about sexual health online. Of those, nearly half (46 percent) did so purely out of curiosity; an additional 43 percent cited privacy concerns as their primary motivation. What this suggests is that online materials may be of benefit to a wide swath of youth, including those who already receive comprehensive sex education. Taken together with Buhli et al.’s (2009) finding that much online sexual health information is of low quality, this points to an opportunity for public health practitioners to make new efforts to develop and promote online material.
These efforts might involve finding new ways to promote existing websites. Sex educators could attempt to piggyback on popular websites and platforms. The Khan Academy is a popular site that provides series of educational videos on a variety of subjects, many of which have been viewed hundreds of thousands of times. Public health practitioners might look to collaborate with this and other similar websites to incorporate content about sexual health and well-being.
Where resources permit, we should invest in targeted advertising on Google and social media platforms such as Facebook and Twitter. Other efforts could include developing material that requires engagement from the user. Rather then simply present facts, these websites might transform the material into games (see Kapp, 2012 for discussion of the “gamification” of education). Additionally, they might provide mechanisms by which youth could contribute their own content.
I do not believe that more, better quality education alone is enough to ensure good sexual health for all youth. Sex education efforts will not be sufficient if we do not also address problems that pose barriers to sexual health and well-being such as stigma and poverty (Lichtenstein, 2003). However, under the current circumstances, online sex education can play a useful role.
Buhi, E. R., Daley, E. M., Oberne, A., Smith, S. A., Schneider, T., & Fuhrmann, H. J. (2010). Quality and accuracy of sexual health information web sites visited by young people. Journal of adolescent health, 47(2), 206-208.
Dembicki, G. (2013). How to talk to a conservative about climate change. Retrieved from http://thetyee.ca/News/2013/07/29/Conservatives-and-Climate-Change/
Guttmacher Institute. (2013). State policies in brief: Sex and HIV education. Retrieved from http://www.guttmacher.org/statecenter/spibs/spib_SE.pdf
Kapp, K. M. (2012). The gamification of learning and instruction: game-based methods and strategies for training and education. Retrieved from http://library.books24x7.com.proxy.lib.sfu.ca/
Kohler, P. K., Manhart, L. E., & Lafferty, W. E. (2008). Abstinence-only and comprehensive sex education and the initiation of sexual activity and teen pregnancy. Journal of Adolescent Health, 42(4), 344-351.
Lichtenstein, B. (2003). Stigma as a barrier to treatment of sexually transmitted infection in the American deep south: issues of race, gender and poverty. Social Science & Medicine, 57(12), 2435-2445.
Mitchell, K. J., Ybarra, M. L., Korchmaros, J. D., & Kosciw, J. G. (2013). Accessing sexual health information online: use, motivations and consequences for youth with different sexual orientations. Health education research, Advance online publication.
 The authors note that a much larger percentage of LGBTQ-identifying youth used the Internet to access information about sexual health. They argue that this is because LGBTQ youth may lack other places to which they can turn.
Reflections on the evidence integration triangle and its application to STD/HIV prevention interventions
The evidence integration triangle (EIT) model provides “a simple framework [that depicts] the complex multilevel contextual factors affecting the integration of scientific knowledge into practical applications” (Glasgow, Green, Taylor, & Strange, 2012, p. 647). Glasgow et al. (2012) characterize many current knowledge translation models as overly complex, academic, and/or time-consuming for users of knowledge, and note that their EIT framework is easily applicable and suitable in numerous and diverse contexts (Glasgow et al., 2012, pp. 646-647).
The EIT model employs a three-pronged approach that integrates an intervention program/policy, a participatory implementation process, and practical progress measures as three angles in a triangle. In the centre of this triangle are evidence and stakeholders, signifying the importance of these dual aspects in bringing evidence and policy closer together. The authors further note the significance of taking into account and properly addressing multilevel contexts. Finally, the relationship between the three prongs or angles necessitates feedback at all levels of the process (Glasgow et al., 2012, p. 647).
Perhaps the most crucial component of knowledge translation theories and frameworks is their applicability to and extent of use in real-life contexts. Although, it is understood that theory is by its very nature abstract (St. Lawrence & Fortenberry, 2007, pp. 23-24), the significance of the ability for frameworks to incorporate real-life situations cannot be overlooked. In particular, despite the EIT framework’s intention to offer a simple, uniform, and comprehensive method through which KT strategy can be viewed, as well as its usefulness in considering the factors that may affect and be affected by intervention implementation, some issues arise that also demonstrate certain shortfalls of the model in its entirety. In considering the EIT model, the following complexities are discovered.
Overall, the EIT model seems somewhat overly simplistic and abstract in its overall goal of providing a framework through which to view KT strategy. The triangle appears to have limited practical application in that it is difficult to apply to real-life contexts due to the lack of clear steps and processes. Furthermore, it is lacking an explanation of how each prong can affect and be affected by the other prongs, as well as how the evidence and stakeholders relate to the three prongs individually and as a whole. Most importantly, it doesn’t describe how multilevel context affects the process of the KT strategy (triangle), and how, due to the nature of the context as constantly changing, it doesn’t include sustainability of the intervention as a necessary component.
A variety of interventions have been suggested to prevent the spread of STDs/HIV, with backgrounds from a myriad of disciplines, though St. Lawrence and Fortenberry (2007) posit that such recommendations have fallen short of producing credibility and effectiveness as a method of best practice (St. Lawrence & Fortenberry, 2007). Although the authors describe in detail the different types of behavioural interventions that have been deployed in the fight against STDs/HIV, application of the EIT framework to these interventions evidence significant gaps. For example, the EIT model cannot account for the complexities of the relationships between stakeholder groups, particularly when vulnerable and/or hidden populations are involved, such as those most at risk of acquiring STDs/HIV. Further, the complexities of culture and society are neglected to the extent that the model lacks explanation of how they affect the KT strategy apart from simple including them within the multilevel context feature. Moreover, St. Lawrence and Fortenberry are quick to mention that interventions are lacking in “a thorough statistical evaluation demonstrating their effectiveness” (St. Lawrence & Fortenberry, 2007, p. 24), which may support the idea that certain interventions are more difficult to evaluate effectively than others. As the spread of STDs/HIV pose threats to the health and safety of communities, any intervention that has demonstrated efficacy must also be sustainable. (For more on implementation science in HIV/AIDS research, see resources.)
Essentially, the EIT framework can be useful and is a good start to the process of considering KT strategy, though that is exactly the point: that it is useful for preliminary consideration, but should not be employed without incorporation of other factors within and without the process. Importantly, we must recognize that certain issues in the public health field, such as STD/HIV prevention or illicit drug use, pose complex challenges to the health and safety of communities and cannot always be neatly categorized into a three-pronged approach for knowledge sharing.
Glasgow, R. E., Eckstein, E. T., & ElZarrad, M. K. (2013). Implementation science perspectives and opportunities for HIV/AIDS research: Integrating science, practice, and policy. Journal of Acquired Immune Deficiency Syndromes, 63(S1), S26-S31.
Glasgow, R. E., Green, L. W., Taylor, M. V., & Strange, K. C. (2012). An evidence integration triangle for aligning science with policy and practice. American Journal of Preventive Medicine, 42(6), 646-654.
St. Lawrence, J. S. & Fortenberry, J. S. (2007). Behavioral interventions for STDs: Theoretical models and intervention methods. In S. O. Aral & J. M. Douglas (Eds.), Behavioral interventions for prevention and control of sexually transmitted diseases (pp. 23-59). New York: Springer.
I am sure most of us have had the experience of having to sit through a bad meeting, or maybe several dozen (or several hundred?). In any case, we are probably well acquainted with the experience of sitting in a room filled with thoughtful, experienced people with the aim of generating ideas on how to solve a problem or plan a program only to end up achieving nothing more than scheduling the next meeting.
Having my own bad associations with the word “brainstorming”, I read Scott G. Isaksen’s Review of Brainstorming Research (1998) with a lot of interest. I found myself becoming increasingly convinced that brainstorming could be useful – if people did it right. Two ideas stood out for me as I read the article.
One is the idea that brainstorming as a process differentiates itself by attempting to remove criticism and instead just focus on generating lots of ideas, including ones that might be particularly out-there. Isaksen mentions how A.F. Osborn, who wrote about brainstorming beginning in the 1940s, referred to most groups being oriented towards evaluation, which Osborn called “driving with the brakes on” (Isaksen, 1998, p. 4). I related to this a lot as I have found myself in many meetings that seem to have focused solely on finding reasons why things will not work.
The other idea is that brainstorming research should not focus on whether groups are more creative than individuals, but rather since brainstorming was conceptualized as a group activity, the focus should be on getting groups to work together to generate better ideas (Isaksen, 1998). I liked this idea as I think it reflects the reality that in most workplaces, people work in groups much of the time. In the health sciences, we are very familiar with working in multi-disciplinary groups set up to capitalize on people’s various strengths and knowledge bases.
While Isaksen does a good job defending criticisms of brainstorming in the literature, he mostly focuses on how these critiques do not actually capture what brainstorming is. The question still remains though, what evidence is there that it does work even if we follow the rules set out by Osborn, especially considering our own personal experiences of brainstorming failure?
Isaksen writes about the important role of the facilitator in brainstorming and about how groups need to be trained to brainstorm. This idea of facilitation seems to come up often in the readings on deliberation and dialogue. It seems there is a real need for well-trained facilitators. In the readings on knowledge brokers (Conklin et al., 2013; Ward et al., 2009), I found that much of what their work entailed was making groups come together to share ideas productively, so maybe the solution lies in them.
I also like the idea of using a technique like Dotmocracy or Photovoice (Downey et al., 2009) to get people more engaged in problem-solving and decision-making processes. In a way, the innovative approaches of these techniques take some of the pressure off having to sit around a table and feel that your idea is being judged. Although, they might not be the best fit for a workplace setting where the same small groups of people are meeting often, I think they do bring up interesting ideas on the need for creativity in how we even go about bringing people together to brainstorm.
I am interested to know what others think. Have you had good experiences with brainstorming? Does success/failure all lie in the facilitator? Have you tried innovative techniques to get groups to work together more productively?
Conklin, J., Luck, E., Harris, M. and Stolee, P. (2013). Knowledge brokers in a knowledge network: the case of Seniors Health Research Transfer Network knowledge brokers. Implementation Science 8:7.
Downey, L.H., Ireson, C.L., and Scutchfield, F.D. (2009). The Use of Photovoice as a Method of Facilitating Deliberation. Health Promotion Practice 10, 3: 419-427.
Isaksen, S. G. (1998, June). A review of brainstorming research: Six critical issues for inquiry. Creative Problem Solving Group, Monograph #302.
Lehrer, J. (2012, January 30). Groupthink: The brainstorming myth. The New Yorker. Retrieved from: http://www.newyorker.com/reporting/2012/01/30/120130fa_fact_lehrer?currentPage=6
Ward, V., House, A., and Hamer, S. (2009). Knowledge brokering: the missing link in the evidence to action chain? Evidence & Policy 5,3: 267-79.
Why doesn’t anyone get it? The age-old question scientists have been forgetting to ask for centuries. A mental models approach attempts to get to the bottom of this through describing and assessing beliefs of particular groups about an issue. This is particularly interesting in the context of climate change a field of research that seems to continually struggle to sell itself to the masses despite scientific evidence which begs the question, what are we doing wrong? To help answer this question, a mental model is a representation of how people understand how something works- an aspect that we have read is often taken for granted in streamlined attempts at stakeholder engagement. The idea behind a mental models approach being that if you take a moment to assess the understanding that individuals or groups have in the first place you will be better equipped to intercept false understandings of a problem at their source, such as climate change (CRED, 2009).
The classic example of an inaccurate mental model in the field of climate change is the false perception many hold that the hole in the ozone is connected to climate change, said hole allowing more solar radiation to enter or escape thus warming or cooling the planet. This leads to the perception that banning aerosol cans solves climate change for example. Once such a model is identified however, advocates for global action on climate change can address it directly to correct this flawed logic (CRED, 2009). Other examples I stumbled upon include using a mental models approach to assess the communication of occupational health risks in machine shops which helped to understand disconnects between how workers receive information vs. how they would like to receive information and frustration from experts at the inability to convey risk successfully (not unlike the frustration of scientists at convincing naysayers that climate change needs to be addressed)(Nicol and Hurrell, 2008) . Another resource management study used a consensus analysis method in partnership with a mental models approach to better understand the level of consensus in 2 stakeholder groups around key players, causes, consequences, and priorities related to water use and management (Stone-Jovicich, 2011). Approaching a problem without making the assumption that the other groups involved have the same understanding of the problem is so often skimmed over and I think academics and scientists are highly prone to frustrations upon realizing that their understanding of the world is far different from the average Joe’s (my grad student self included!).
Approaching situations such as stakeholder engagement with the assumption that you can’t assume anything is a habit that can only strengthen the success of participatory processes, though it is a challenging shift to make in practice. I myself can think of plenty of examples from my everyday life when assessing the mental model of my audience before acting or speaking would have come in handy, especially in cross-cultural contexts. Continuing to assume that everyone around me is a critically thinking equity-minded public health conscious individual doesn’t get me much besides frustration so why not shift my approach? Old habits die hard but I’d like to think that recognizing them is half (a third? part of?) the battle.
Center for Research on Environmental Decisions (CRED). (2009). The Psychology of Climate Change Communication. Available at: http://guide.cred.columbia.edu/index.html
Nicol, A.M. and Hurrell A.C. (2008). Exploring Knowledge Translation in Occupational Health using the Mental Models approach: A case study of machine shops. Available at: https://circle.ubc.ca/bitstream/handle/2429/30876/SRA-ESREL_paper_FINAL_2008-06-03.pdf?sequence=1
Stone-Jovicich, S.S. et al. (2011). Using Consensus Analysis to Assess Mental Models about Water Use and Management in the Crocodile River Catchment, South Africa. Ecology and Society, 16 (1): 45. Available at: http://www.ecologyandsociety.org/vol16/iss1/art45/
This past week in class we participated in a ‘Dotmocracy’ exercise. For those of you unfamiliar with Dotmocracy it is a group consensus building tool that is most effective when used with large groups (Diceman, 2010). Invented by a Canadian, Jason Diceman, in 2004 to promote participatory democracy the tool is similar to a cumulative voting system, where Diceman acknowledges he drew his inspiration (Diceman, 2010). I highly recommend that anyone looking to understand the process more clearly to consult the Dotmocracy handbook, as well as all the complimentary information available at the dotmocracy.org website.
To those people familiar with the process, or those of you that participated this week, it is part of the role of the facilitator to not only promise a report but also make all the results public. As promised here are the results of our Dotmocracy:
Our question: What actions can be taken to improve the experience of Graduate Students in your faculty?
Number of Participants: 10
Answers generated: 10
Top five ideas (ranked by level of agreement):
(1) Grouped idea: More opportunities for faculty-student social events (this was posted on two sheets)
(2) Zumba classes for students
(3) Mentorship groups set up for students learn about and apply for funding
(4) Maximum class sizes reduced
(5) More bright study spaces
Based on the number of ideas generated with such a small group of students, it is clear that students have ideas and strong commitments to making suggestions about ways to improve the Graduate experience. Due to the limited number of students involved in the exercise I would recommend that this process be set up for students to engage in outside the classroom. Setting up a Dotmocracy wall for a two-week period in Blusson Hall could generate many ideas, as well as help prioritize what action the students would most often agree too. Therefore the conclusion of this exercise is to expand the session and make it open to all Grad students in an out-of meeting session.
As suggested by Diceman (2010) a Dotmocracy session can extend for days or weeks or even without a planned end. The process can take place in a common space, and although may need some experienced facilitators, the process can continue basically self-managed. As for students in the faculty of health sciences this would be best done in the graduate student lounge. As pointed out by Diceman (2010) we could have people take part without having to worry about competing schedules, gather large comments from the student body, it would need only a few minutes for people take part, and it wouldn’t require a meeting time. The disadvantages would be that people might not take the activity very seriously or benefit from the interactions of fellow participants (Diceman, 2010).
To follow-up on the session that we had, there were few questions that could not respond to. One of the questions was around voting irregularities. When participants mark (vote) on a particular sheet they are required to sign their name, however at stated in the handbook “It is not uncommon for participants to forget to sign, especially if this is their first time using Dotmocracy. It is your judgement call whether there are more dots than signatures because of fraudulent dotting, or forgetful participants.” (Diceman, 38). I wanted to note that in our exercise there were no voting irregularities.
In closing I would also like to reflect on some of the aspects of facilitation which would have improved this process. First of all I think that some preamble about the purpose of collecting the information may have helped contextualize the question for participants, and people may have answered more specifically if they knew who the results were going to be directed towards. There was also a two ideas that were very similar, participants were unsure how to manage these duplicates, and so more instruction on the process would have helped to address this issue as well. This would have been a good pilot session, with the next steps leading to a full on Dotmocracy with the student body.
I am examining a ‘systems thinking’ framework tool to use in the current implementation of a sepsis prevention and treatment demonstration project in two rural Bangladesh hospitals.
Dr Kitson, a nursing professor from Australia, explains that most theories about knowledge translation use a linear theory, with a cause and effect model (Rogers’ Diffusion of Innovations) which does not work for people and stake-holders involved in change processes. In both low and high resource country health systems, significant organizational and technological changes with their corresponding behavioural and practice changes are not dynamic, easy to implement processes. It is prudent to look for other frameworks and guided efforts to expedite and facilitate needed system changes. Kitson’s (2009) article describes one such framework.
‘Systems thinking’ involves shifting the cause and effect linear thinking to a more complex system of how organizational change occurs in health care settings. The author proposes that factors relating to social, organizational and economic contexts influence the adoption of new knowledge. The importance of inter-relationships between people in all levels and the context of the health care system is stressed. Shift to systems thinking is a change towards seeing inter-relationships and processes of change rather than concrete moments of change. An innovation systems thinking knowledge translation tool is enabled by an expert facilitator working with individuals and teams in the wider system to change factors needed to adopt new practices.
The author notes that the health system is a complex entity, but does not work like a machine. Knowledge translation on its own is not enough to make changes, but relies on local autonomy experienced by individuals, teams and the unit involved in the change. Key stakeholders need to be involved and individuals must understand the new piece of knowledge being introduced and accept it. They need to be able to make informed decisions about using the knowledge, and to negotiate relations with others in their system. Resources to sustain the changes or improvements in practice are an important part of the equation.
According to Graham et al (2006), Knowledge translation’s primary purpose is to address the gap between what is known from research and knowledge synthesis and how this is manifested in practice. This definition is the one primarily used in the Canadian Institutes of Health Research (2005) but it does not indicate how the system responds to new information, how the interaction occurs, or how the knowledge is moved from researcher to practitioner or user. Kitson (2009) explores how the concepts of ideas, people, relationships, context, outcomes and process differ in traditional KT and in ‘systems thinking’ innovation. The process of synthesizing and adopting information is complex and needs to be enacted at multiple levels. Using ‘systems thinking’ can give us a more realistic perspective of how organizational change occurs.
The author describes the introduction of innovation into systems that are under-developed, where the individuals feel that they are victims and do not have control over their environment, have fixed attitudes and beliefs, and exhibit apathy. While using this framework to implement changes in rural Bangladesh hospitals, mid-level providers must increase their autonomy and control over the environment, and the involvement of stakeholders must be promoted.
Canadian Institutes of Health Research. http://www.cihr-irsc.gc.ca/e/39033.html
Graham I, Logan J. Harrison M, Straus S, Tetroe J, Caswell W, Robinson N.(2006). Lost in Translation: Time for a Map? Journal of Continuing Education in the Health Professions. (26)13-24.
Kitson A. (2009). The need for systems change; reflections on knowledge translation and organizational change. Journal of Advanced Nursing. 65, 217-28. Doi:10.1111/j.1365-2648.2008.04864x
National Collaboration Center for Methods and Tools (2013). Integrating Knowledge translation and systems thinking for organizational change. Hamilton, On: McMaster University. Retrieved from: http://www.nccmt.ca/registry/view/eng/203.html
Rogers, E. (1983) Diffusion of innovations. New York : Free Press ; London : Collier Macmillan.