What do these findings imply about providers' cognitive processing when assessing patient adherence? Recognizing that there is some variation across disciplines in the definitions of such terms, we use the following social psychological definitions, drawn from the IOM Unequal Treatment
refers to the process by which people use social categories (e.g., race, sex) as they acquire, process, and recall information about others (Institute of Medicine 2003
, p. 169). Faced with the task of making sense of a world filled with infinite detail, stereotypes operate as heuristic devices allowing individuals to organize information into familiar categories, albeit often in overly rigid or exaggerated ways (see also Byrd and Clayton 2003
, p. 525). Prejudice
refers to a specific type of stereotype—those with negative attitude or affect. In the words of Byrd and Clayton, prejudice refers to “an antipathy, felt or expressed, based upon a faulty generalization and directed toward a group as a whole or toward individual members of a group” (2003, p. 524). Finally, uncertainty
refers to the problems people sometimes encounter in the process of cognitively processing their social worlds; uncertainty occurs when social actors have difficulty cueing an appropriate or accurate stereotype, or when they use stereotypes unreliably (Balsa and McGuire 2003
; Institute of Medicine 2003
, p. 172).
Our results suggest that providers appear to use observable cues, race and age in particular, to make inferences about an individual patient's adherence, even though patient self-ratings do not vary with these factors. This is further supported by the finding that physician assessments do not vary with patient characteristics that are more difficult for them to observe. These findings are not consistent with the idea that patients simply convey their preferences and behaviors to providers and providers apply such information equally for all types of patients. In addition to reinforcing the view that providers' cognitive processing about adherence is important for clinical decision making, we offer some empirical evidence about which types of processing might play a role. If, for example, we had found that providers give systematically lower assessments of black patients as compared with white patients (assuming other relevant factors were adequately taken into account), we might have evidence of providers behaving with prejudice toward black patients (this would also require us to assume that patient assessments were reflections of true adherence behavior). Instead, we find significant variation in the absolute value of the difference between patients' and providers' assessments for black patients as compared with white patients. This result suggests a difference in distance
rather than one of direction
: providers are neither systematically above nor below black patients' self-ratings, but they are systematically farther away, compared to their ratings of nonblacks. This finding suggests that providers have greater uncertainty about the adherence of black patients. In practical terms, this uncertainty might suggest that providers have more difficulty communicating with certain types of patients.3
Beyond this, however, there is little we can conclude in terms of clearly supporting more specific cognitive processing theories that are sometimes used to understand health disparities. Our findings evoke, for example, Balsa and McGuire's (2001) Balsa and McGuire's (2003)
, Balsa and McGuire's (2005)
) work on statistical discrimination—a type of stereotyping wherein providers, uncertain how to characterize individuals belonging to specific groups, tend to use the group's average characteristics in evaluating any given individual. This theoretical perspective predicts that providers would be less extreme in their evaluations of black patients compared with whites, because they would tend toward their perception of the group's average. At the same time, our findings also evoke the complexity–extremity effect (Linville 1982
; Linville and Jones 1980
), which suggests that people tend to have more extreme evaluations (positive or negative) of others belonging to groups with whom they have had little exposure, and of whom they therefore have less complex cognitive understandings.4
This theoretical perspective implies findings that would be quite divergent from a statistical discrimination finding: rather than tending toward the mean of a group, assessments would be polarized. While either of these perspectives would be consistent with the greater distance between providers' and black patients' assessments that we observe, our findings as a whole leave us without distinct and mutually exclusive evidence for either theory.5
The patterns in our age results imply that providers do not appear to face the same uncertainty with young patients as they seem to for black patients. Because of various limitations of our study, we do not suggest these findings constitute clear evidence of provider prejudice against younger patients. We do, however, assert that future research examining cognitive processing and health outcomes would benefit from further exploration of various dimensions of bias, including the underlying types of cognitive processing, particularly with respect to age. Together, these findings imply a need for additional systematically coordinated, cross-disciplinary, creative work to build and execute a research agenda that would consider factors such as the following: What constitutes empirical evidence of provider prejudice, uncertainty, and stereotyping? What can we learn from the multiple disciplinary perspectives represented in this literature, and how can we better coordinate those efforts? What is the relationship of not only provider assessments, but also of patient self-assessments, to objective measures of health behavior? How will an understanding of relative differences contribute to a broader agenda of learning about cognitive processing?
This research has additional implications for understanding racial/ethnic health disparities. For example, the data permit an explicit comparison between an individual patient's self-rating of adherence and the physician's rating of that same patient. This improvement in data offers a first step in considering some underlying features of concordant versus discordant doctor–patient interaction.
Second, the results suggest that differences in beliefs about patient adherence might underlie some of the disparities in treatment decisions, at least in the context of diabetes patients. According to van Ryn and Fu (2003, p. 251)
, relatively little research has tested how providers' beliefs about patients' social behaviors influence their professional decision making. More fundamentally, however, we view this work as important because it functions as a theoretical antecedent to questions of how medical treatment decisions are made (see also Institute of Medicine 2003
, p. 173–4). What is lacking in many of these studies, and others asking similar questions focused on provider bias, are the sorts of systematic measures of provider assessments that we offer here.
Clearly, the present study has several limitations, including a small sample size from only two clinics, its focus on a single medical indication, and its lack of an objective measure of patient adherence. To build on this work, future research might consider multiple dimensions of adherence; compare patient and provider assessments of adherence or other aspects of health behavior; integrate more “objective” data such as lab measures or automated pill counts; study of mechanisms other than adherence that might lead to disparities in treatment; and examine illnesses other than diabetes.
Despite these limitations, our findings have important policy implications. The effectiveness of policies aimed at reducing disparities depends on correctly identifying and targeting their sources (Balsa and McGuire 2003
). Our work here contributes by offering empirical evidence that greater provider uncertainty about black patients' adherence, rather than prejudice or negative stereotypes about black patients' ability to adhere, might be responsible for racial disparities in diabetes treatment, to the extent that beliefs about adherence affect subsequent treatment decisions. Patients and providers may be doing the best they can given the information they have (Balsa and McGuire 2003
), and as a result, improving providers' abilities to assess blacks' adherence might improve outcomes more than trying to minimize or eliminate prejudice. This goal could be accomplished through a multilevel, comprehensive approach (Miller et al. 1997
; Roter et al. 1998
), part of which may involve giving providers incentives to spend more time with black patients, educating them about how to better elicit information from patients of different races, or encouraging them to implement more objective measures of patient adherence where possible. For age-based differences, which are characterized more by differences in direction rather than distance, policy implications might be more effectively aimed at understanding and changing negative attitudes about younger patients' adherence behaviors.