Sometimes it feels like my entire life has been spent behind a computer. From studying to writing essays to working on my research, I spend a lot of time on my own staring at a blinking cursor. As much as this is a reality of my studies in biostatistics and epidemiology, I cannot help but feel I am missing an integral part of the health sciences academic experience. That is collecting data and interacting with the subjects of my research. I rarely encounter people who are not either fellow academics or students. I am beginning to wonder what it is like in that big, bright world outside the ivory tower?
I recently had the opportunity to glimpse at this world when I shadowed a fellow graduate student and former clinical lead with the Portland Hotel Society in the Downtown Eastside (DTES) of Vancouver. His work involved a project on which my supervisor and research lab had done the statistical analysis. It was a unique opportunity for me to see the neighbourhood and people behind the de-identified statistical IDs I use for modeling. His responsibilities included running an arm of the study that provided housing interventions, including both managerial and counseling work, for homeless residents of the DTES.
He worked with these people on a one-to-one basis, planning treatment regimes for both mental and health services using a strong, team-based approach. This, ultimately, could not be more different than what I do. The world of collecting data, which is a rather cold way of saying providing services and working with participants, is the entire basis of my work. I could not run a statistical analysis without that data, yet I rarely get the chance to understand the circumstances of how it is collected. More importantly, I have few opportunities to understand the people the data represents. I keenly felt this reality during my shadowing time.
A far more interesting looking tower than my own metaphorical one. © emilyrempel 2013
As I discovered, working with the participants could be a nine-to-five job but with the added caveat of extended hours for emergencies. The stark reality is that you need to be available when people die, often not within normal working hours. I have no concept of this type of stress. When I asked what that felt like, I received the expected response, not at all pleasant. There are however mental health strategies in place for this type of work including flexible hours, staff activities and vacation time. I realize, as typing this, that these emergencies faced by clinical staff are the very same numbers I see in a statistical database as censoring dates, or time of leaving the cohort. That is something I will take away from the experience with a slightly heavy heart. As I walked around the DTES during my shadowing, several people stopped us whether to catch up, chat or request help. It was amazing, the connections I saw, this work is definitely not done while staring at a blinking cursor.
As I reflect on this experience my most central question is how important is it that I know these “real-world” realities? Does it matter for statistical modeling? I hope that the answer is yes. It brings me back to the idea of multidisciplinarity. We need to understand more than our own training to develop effective multidisciplinary teams (Choi & Pak, 2006). I try to represent real-world health phenomena with biostatistical models. I must know the context of the problem in order to create reliable analyses. As well, understanding the inequities of our world is important to me personally. I work in this field because I care about health at the population level, particularly for those most vulnerable to poor health. I am sure as I progress in my career I will have more opportunities to work outside of a computer lab. To extend my initial metaphor, I wonder in the meantime what champion will release me from this locked tower? Luckily no actual chains exist and that champion, I imagine, will be my own ardent effort to fight against the idea that I am only a “numbers person”. Escape from the tower requires that I simply push through the door.
Please enjoy this clichéd photo of a literal unbarred door. © emilyrempel 2013
- Choi, B.C.K. & Pak A.W.P. (2006). “Multidisciplinarity, interdisciplinarity, and transdisciplinarity in health research, services, education and policy: 1. Definitions, objectives, and evidence of effectiveness.” Clinical and Investigative Medicine, 29, 351-364.
- Holton, S.A. (2002). “Why an ivory tower?” The National Teaching & Learning Forum. 11(3), 1-12.
This week’s readings included a call from Glasgow et al. (2012) for a greater community role in the knowledge production process. This necessitates opening up academic research to community participation, as well as including lay understandings and wisdom in our definition of knowledge. The assumption seems to be that if only academics and policymakers were more welcoming then the community would happily meet them in the middle. This may not be the case. Many of the forces that serve to create and maintain health inequities may also place constraints on community participation.
The articles we read this week explore neither what is meant by community participation, nor the ethical and logistic issues inherent in community participation in research. Accordingly, I would like to propose several questions so that we might begin to unpack the idea of community participation.
We might start by asking: What do we mean by community? On which attributes are we basing our definition? The definition of community we adopt should be grounded in the aims of our study or intervention. We might define a community geographically. We may equally refer to imagined communities, such as those based on ethnicity. Furthermore, there is the question of deciding who is and is not part of a community; membership may be decided by self-identification or imposed by others (the researcher, the state).
Having defined a community, we may then ask: Who speaks for these communities? Those who are speaking may not necessarily represent the views of their fellow community members. This leads us to consider whether we are engaging with a diverse cross-section of the community, or simply those members whom we find accessible.
On the subject of engagement: Does our model of community engagement mean placing a greater burden (economic or social) on communities that may already be under considerable stress? Certain communities may not be so keen on working with institutions that have historically played the role of the oppressor (and may continue to do so). Indigenous peoples in Canada have expressed consternation at perpetually being the subject of research (see Castellano, 2004 for further discussion). Indeed, targeting “at risk” communities can prove stigmatizing (Frohlich et al., 2012). Each new publication marking Indigenous communities as unhealthy and each intervention aimed at improving their lot only contributes to widely held stereotypes about indigenous peoples in Canada.
With these concerns in mind, we must pursue mechanisms that aim to temper power imbalances between researchers, health promoters, and community members. This is essential given that many public health initiatives concern communities that society marginalizes.
I understand that for the sake of brevity a journal article cannot examine every pertinent issue in depth. Nonetheless, I find it discouraging that none of the articles we read this week explicitly addressed these issues, even in passing. In the interest of treating community participation in a more than cursory fashion, I suggest we take up some of these questions and explore their implications for research and practice.
Castellano, M. B. (2004). Ethics of Aboriginal research. Journal of Aboriginal Health, 99, 98-114.
Frohlich, K. L., Poland, B., & Sareck, M. (2012). Contrasting entry points for intervention in health promotion practice: situating and working with context. Health Promotion in Canada: Critical Perspectives on Practice, 102.
Glasgow, R. E., Green, L. W., Taylor, M. V., & Stange, K. C. (2012). An evidence integration triangle for aligning science with policy and practice. American journal of preventive medicine, 42(6), 646-654.