|
| Main
| français
| CWHN home |
|
Download the PDF (395 KB, 20 Pages)
What Counts in Health Research? Who's Counted in Health Research? Making Research Count
|
|
Gender-Based Analysis: Beyond the Red Queen Syndrome Karen R. Grant, Associate Dean, Faculty of Arts and Associate Professor, Department of Sociology, University of Manitoba, and Researcher, National Network on Environments and Women’s Health This paper was prepared for the Gender-based Analysis Fair, January 2002, Ottawa.
The call for gender-based analysis (GBA) is not a new one. The Canadian International Development Agency pioneered the concept of GBA in the mid-1970s.[1] In 1995, the government of Canada adopted a policy requiring federal departments and agencies to use GBA to inform policies and legislation. Although some in government have been applying the techniques of GBA for a long time, this equityseeking strategy has been met with resistance in some quarters, and outright hostility in others. Early on, advocates saw GBA as a strategy to identify sources and consequences of inequalities between women and men. Since many of those inequalities still remain, the need for GBA continues, but putting such arguments forward is not always welcome. We still need GBA to determine whether programs, policies and laws work for equity, and, it follows, whether these programs, policies and laws work for women. In the context of the backlash against feminism, it seems
that what has been taking place in recent years is akin to
Alice’s encounter with the Red Queen in Alice Through the
Looking Glass:
This running faster and faster to stay in the same place—the Red Queen syndrome—seems to define equity work. We should move beyond this, if we can. What are the obstacles to doing so? First, it is not apparent that GBA or gender mainstreaming occurs in a systematic way right now. Indeed, Wendy Williams suggests that despite embracing GBA as a policy tool at the federal level and in some provinces, most policies have been developed without serious consideration of how women and men will be affected.[3] Second, too often it is assumed that GBA addresses women’s issues only. The whole point of GBA is to identify if and how programs and policies affect women and men similarly or differently—it is a question to be answered. Let me make my point through some examples. If we look at the area of health and health care, the need for a gender lens could not be clearer. Decades of research in the social sciences confirms that sex is one of the most fundamental sources of differentiation among human beings.[4] There are volumes of research that demonstrate the importance of sex as a determinant of health status.[5] For example, studies show that women have a higher blood alcohol content than men even when they consume the same amount of alcohol. This is true even when one holds body size constant. As well, research indicates that women are significantly more likely to develop lung cancer than their male counterparts who smoke the same amount of tobacco.[6] Drugs often produce different effects in men and women.[7] Findings such as these have led the Society for Women’s Health Research to advocate an approach they call "gender based biology," that is, scientific research dedicated to identifying "the biological and physiological differences between men and women."[8] As important as sex differences are (e.g., differences at the physiological, biochemical or genetic levels), social scientists have shown that there are also significant differences based on gender. That is, the different roles, responsibilities and activities prescribed for women and men, based on cultural conventions and expectations. These differences relate primarily to power— the relative possession or absence of it. Gender differences are evident in most areas of everyday life, hence the need to consider how programs, policies and laws affect women and men. Gender differences are evident in health behaviours, health care work and doctor-patient interactions, and are an enduring phenomenon in this society, and around the world. The importance of these differences has been recognized by federal/provincial/territorial ministers of health, and was highlighted in the Women’s Health Strategy of Health Canada, which identifies gender as one of the determinants of health.[9] To illustrate, consider the following key gender differences that make a difference in women’s health:
To date, most biomedical and clinical research has been conducted on men: it has been taken for granted that humans are male. Only because of legislation in the United States (but not in Canada) are women now routinely included in clinical studies. Even so, the United States General Accounting Office reports that there has been no change in the frequency of analysis of research results by sex, much less gender.[20] Canadian researchers found identical trends in their review of research studies and clinical trials at the University of Toronto.[21] This speaks to a very slow rate of change, even with legislation and accountability frameworks mandating change. It also highlights the enormous need for capacity building and education about sex and gender analysis. We are stymied not only by an unwillingness to consider how gender affects experiences, but also by how we might measure gender, and how we might measure the impact of programs and policies. Typically, when we consider the differences between women and men, we assume sex can be treated like any other variable, as if sex can be used as a proxy for gender. Another problem is that most programs and policies and the research that informs them, are almost totally gender neutral or gender insensitive. In studies into the provision of health services and the effects of health care reform on providers and recipients of care, women have, to a very large extent, been "overlooked, ignored or subsumed."[22] Consequently, it is difficult to ascertain exactly what consequences flow from policy changes. Gender insensitivity can occur in a few ways: we might fail to see if gender (not just sex) matters in how we analyze things, and in how we measure things. The Analysis Problem The Measurement Problem In research on health system performance, the limited range of indicators used provides an incomplete picture, if not a misrepresentation, of the effects of health care reforms. This is true in general, and in particular when it comes to experiences in which there are known gender effects or differences. And it is useful to remember that it will be difficult to say much about gender effects if we don’t ask the question or include appropriate measures. In an environment guided by evidence-based decision-making, the "best" evidence is usually defined as that which is "objective," quantifiable and replicable. As a consequence, many studies of health care focus on data collected through quantitative methods. The data of choice seems to be population-based administrative data from the health services system. "Qualitative research is often relegated to supplementary roles … such as planning or explaining quantitative research."[28] To illustrate the limitations of administrative data, consider the 1999 report by the MCHPE on hospital bed closures in Winnipeg. Brownell and Hamilton report that 727 (24%) beds were closed in Winnipeg hospitals in the period between 1992/93 and 1997/98.[29] What were the effects of this hospital downsizing? Hospitals cared for the same volume of patients with fewer beds by delivering care in different ways (e.g., by shifting care from inpatient to outpatient settings). As well, they report that the quality of care (measured rather crudely by hospital readmission rates) and the health of Winnipeggers (also measured rather crudely by premature mortality, that is, deaths before age 75) were unaffected by the bed closures. A recently published report by researchers at the Centre for Health Services and Policy Research in BC reached similar conclusions about the effects of hospital downsizing on elders’ health care utilization and mortality rates.[30] Sheps et al. conclude that there have been minimal adverse effects associated with the reduction in acute care services. This change in services coincides with public policy goals of (and citizen preferences for) shifting care "closer to home," and reserving longer-term hospital stays for those who are sicker. In an editorial regarding this BC study, Roos contends that all the media headlines about hospital downsizing and bed closures exaggerate the negative effects of this type of health care reform.[31] I would argue that the impact of health care reforms, and in particular the shift of health care from institutions to the community and the home, have—for the most part—gone unexamined. These reforms, which continue apace as governments cut their financial commitments to the health care system, affect everyone, but I believe that they affect women more than men. Women are on the frontlines at home and in institutions. If caring work is transferred home, then women by and large will have to assume those responsibilities in addition to, or perhaps in place of, their other responsibilities in their families and in the paid work force. Similarly, professional nurses and other allied health workers, the majority of whom are women, have experienced work intensification, injuries and burnout as a result of health reforms.[32] But by all counts, the gender effects of health care reform have been almost entirely ignored. We need to view health care policy through a gender lens— that is, to identify how and why experiences differ for women and men. Without answers to these and similar questions, we cannot even begin to assess the effects of health care reforms such as hospital downsizing. Chambliss has pointed out that, "no one has the luxury of a gender-free view of the world, and there is plenty of evidence that the genders see the world differently."[33] This is the heart of the matter. Most policy research ignores sex/gender, is silent on its significance as a determinant, or treats sex/gender as if it is less important than other characteristics such as socioeconomic status. We need to determine not that sex/gender matters so much as that it doesn’t matter before we dismiss the criticisms that many feminist researchers make about what gets measured and how. Until we do so, we are making policy decisions blinded to the possibility that sex and gender do matter—to women, and to men—and we may be advancing policies in ways that disadvantage some segments of the population. And we’ll keep running—like Alice and the Red Queen—but getting nowhere fast. National Network on Environments and Women’s Health NOTES |
| This page updated |
