Patient Education and Counseling 50 (2003) 9–12
Some observations on provider–patient communication research Judith A. Hall∗ Department of Psychology, 125 NI, Northeastern University, Boston, MA 02115, USA
Abstract This article presents reflections on, and suggestions for, research on provider–patient communication. These include: (1) the need for more precise causal analysis, (2) considerations when doing moderator analysis, (3) the need to study values concordance between providers and patients, (4) the relative neglect of studying provider attitudes, emotions, and characteristics, (5) the potential value of studying providers’ sensitivity to their patients, and (6) the importance of studying patients’ impact on providers. Finally, the field is challenged to ask and answer the questions: why do we do this research and how is it being used? © 2003 Elsevier Science Ireland Ltd. All rights reserved. Keywords: Provider–patient relationships; Health communication; Satisfaction; Gender; Health status
1. Introduction Everyone now accepts the importance of provider–patient communication for patients’ health and well being. This acknowledgment is of major importance for medical education, for the organization of clinical settings, for the patients themselves, and for the research community. It is with the research community that this article is concerned. After several decades of studying provider–patient communication, we know a great deal about what goes on between providers and patients. Every so often it is good to reflect on our progress. In this article, I propose several areas for attention in this important field of study.
2. Causality issues It is expensive and time-consuming to do research in clinical settings, especially research that involves recording actual communication. It is also extremely hard to mount randomized experiments, especially those that would require healthcare providers, such as physicians, to allow their communication patterns or style to be dictated by researchers. The closest we have come to the latter is to conduct randomized studies of training physicians and medical students in communication skills. But a truly experimental science of provider behavior would involve
∗ Tel.: +1-617-373-3790; fax: +1-617-373-8714. E-mail address:
[email protected] (J.A. Hall).
persuading providers to vary their behavior systematically, at the behest of the researcher, and let the researcher track short-term and long-term consequences. Interestingly, while the training studies are never questioned in terms of ethicality, providers and patients alike might protest the idea of being guinea pigs in the experimental designs of behavioral scientists. Of course there is no ethical problem as long as the relative benefits of different manipulated behaviors are truly unknown, and indeed this is the rationale for conducting randomized controlled trials in clinical medicine. But adopting this ethical framework into behavioral studies is mostly still in the future, and the occasional experimental study of provider or patient behavior stands out against a sea of observational studies. In a meta-analysis of studies of patient satisfaction, only 14% of the studies were randomized studies in which changes in satisfaction could be traced to any kind of experimentally manipulated variable [1]. In a typical cross-sectional correlational design, it is fortunate if the investigator can include a few sociodemographic variables to use as covariates. But even with these in the analysis, the researcher is mostly left to spin stories about causal factors (usually those he or she personally favors). Most causation stories are simple linear stories, for example, “More information provision leads to greater satisfaction.” Our journals do not allow space for discussion of the causal complexity that might lurk behind this correlation. For example, how do we know that a confounded factor is not the true cause of the satisfaction, such as some other kind of physician behavior or some physician or patient characteristic? And what accounts for the greater information provision in the first place? Information provision is likely to be based
0738-3991/03/$ – see front matter © 2003 Elsevier Science Ireland Ltd. All rights reserved. doi:10.1016/S0738-3991(03)00072-7
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on a complex mix of provider individual differences (which may include the provider’s personal style, the provider’s knowledge of that particular medical condition, or how pressed for time the provider is at a given visit), along with patient attitudes and behavior such as asking for the information or showing a special appreciation or responsiveness when it is given. And how about reverse causation— could more satisfaction cause more information to be provided? It would be easy to tell this story. If both forward and backward causation are present, we have circular or reciprocal causation. Over time there could be other patterns. A better informed patient surely starts interacting in a different way, with the impact depending on how receptive the provider is to having a more activated and educated patient. Being more activated and educated on his or her condition may, in turn, have an impact on the patient’s satisfaction such that it will actually take a dip in the short run, owing to rising patient expectations and the role conflicts engendered when patients are empowered by knowledge [2]. Some associations are well enough documented that it is clearly time to switch from a descriptive to an explanatory mode. One example is research on why sicker patients are less satisfied with their physicians than are healthier patients [3], an association that is well established [4]. Because physicians like their sicker patients less than their healthier ones [5], one hypothesis is that physicians behave toward sicker patients in ways that hurt their satisfaction. On the other hand, a more direct path would be that sicker patients are dissatisfied with life in general (including their physicians), so that their physicians’ negative attitudes are not what produces dissatisfaction. Using causal modeling, it was found that being sicker was mostly associated with the more direct causal path, but for one behavior there was evidence that physician behavior played a role in reducing the satisfaction of sicker patients: physicians curtailed social conversation with sicker patients, which in turn seemed to have a negative impact on satisfaction [3]. There are still causal ambiguities; for example, this effect could stem either from physicians’ negative emotional response to sicker patients or from physicians’ curtailing social conversation in order to free time for talking about the sicker patients’ more extensive medical problems. But the example makes the point that more focus can profitably be brought to understanding causal patterns in medical interactions. Thus, we should be careful about assuming simple explanations just because a simple statistical association is all we have been able to measure in our study, and we should be careful about assuming complex explanations in the absence of empirical support. There is no easy way out of this dilemma; researchers who do simple correlational designs often do them because they feel stumped at how, in the real world, they could do it differently. But we must try, and if we cannot design studies according to our ideals, we can do a better job of acknowledging the causal uncertainties and possibilities.
3. Looking for moderators Obviously, no correlation or causal path is always the same, regardless of when, where, and in whom it is measured. Therefore, researchers need to look for variations in personal and situational characteristics that are associated with different magnitudes of effect, in other words, moderator effects. If you determine, for example, that emotional support has a stronger relation to satisfaction among cancer patients than among healthy people having an annual check-up, you have uncovered a moderator. This would be an important finding but one which has its own causal ambiguity because a moderator is usually not itself an experimentally manipulated variable. Therefore, one might not be able to say exactly what caused this difference in strength of effect. In the example given, does emotional support better predict satisfaction in cancer patients because oncologists deliver emotional support better than other physicians do? Because cancer patients value emotional support more than other patients? Because the cancer patients were older, and older patients are easier to please? Because the cancer patients were women, and women especially value emotional support? Because the cancer patients’ emotional issues were different from those of other patients, and some emotional issues are more easy to talk about or resolve than others? With proper statistical controls one might resolve some of this ambiguity, but it remains a fact that a moderator analysis generally does not support strong causal inference. The search for moderators can be a small-scale endeavor—running subgroup analyses within one’s own study—or it can be a big endeavor, aiming to map the variations in effect size across a wide range of potential moderating variables. Meta-analysis is the best method for this latter endeavor, because of its capacity to encompass many studies and its ability to capture between-studies variation.
4. Looking at values concordance A natural outgrowth of looking at provider and patient factors that might influence the outcome of care is to look at both together. Although there are many dimensions and variables on which provider and patient could be matched or mismatched, one kind that should especially be studied is concordance between the provider and patient on values and expectations associated with their respective roles [6]. Surprisingly little research has moved in this direction, perhaps because of the relative difficulty of persuading the providers to be studied. If, as an example, both physicians’ and patients’ respective preferences for power sharing are measured, one might expect the best outcomes to follow when they have compatible preferences. On the other hand, perhaps optimal patient outcomes depend more on the physician’s than the patient’s preference. One can also imagine that the pattern is dynamic, with the patient’s preference influencing short-term results but the provider’s influencing
J.A. Hall / Patient Education and Counseling 50 (2003) 9–12
long-term results. Because the relationship is both negotiated and dynamic, the value of studying both participants’ values is obvious.
5. Studying providers There is a paradox here—it is often said that provider communication is studied more than patient communication. However, provider characteristics are studied much less than patient characteristics are. There are several reasons for this—a typical communication study only has a small number of providers, meaning individual differences in providers will not be fruitful to study, and in addition providers probably are not eager to be personally studied and to spend time filling in questionnaires about themselves. Furthermore, an assumption sometimes seems to be that only patients have emotions, attitudes, and characteristics (such as social class) that might influence the nature of communication. But, obviously, providers are human beings and not just professional machines, and therefore we need to know much more about how provider characteristics, such as gender, personality, and social attitudes, are reflected in the care they give and the outcomes of that care. The provider characteristic most studied so far is physician gender. A meta-analysis found that female doctors spend more time with their patients, talk more about emotional and psychosocial topics, engage in more partnershipbuilding, and engage in more positive verbal and non-verbal behaviors than male doctors do [7]. These behaviors are interesting because they are similar to those that predict more satisfaction, more adherence to medical regimens, and better clinical outcomes [8,9]. Another provider variable is personal liking for the patient [5,10,11]. Physicians do not like all their patients to the same degree, and patients have statistically significant accuracy in detecting how much they are liked. Furthermore, how much the physician likes the patient can predict the patient’s satisfaction a year later and also the likelihood that the patient has considered changing physicians. In addition, female physicians like their patients more than male physicians do, and patients like the physician more if the physician is female. Though physicians may be fully aware that they like some patients more than others, they are likely not aware of the extent to which this might be a force within the process of care.
6. Physicians’ sensitivity to patients The concept of sensitivity is embedded within the concept of humane and patient-centered care. A sensitive physician might pick up on emotional difficulties, on the existence of a hidden agenda, on the presence of physical pain, on signs of domestic or substance abuse, and on the patient’s responses to the physician. Nevertheless, sensitivity to
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patients is not a topic that has received much investigation. DiMatteo et al. [12,13] gave physicians a standardized test of ability to interpret non-verbal cues. Those scoring higher had patients who were more satisfied and more adherent to their appointment schedules. This research strongly suggests that physicians vary in their interpersonal sensitivity toward their patients and this is a process that demands more direct study. We need to develop methods for assessing sensitivity in the clinical visit so that we can study how sensitivity translates into effective behavior toward patients and whether different physician characteristics predict sensitivity. A great deal of non-clinical research has shown that women are, on average, more interpersonally sensitive than men are [14]. Is this also true among physicians, and could the liking effects I just mentioned be due to female physicians being more sensitive to their patients’ expressions and feelings?
7. Patients influence providers, too Nearly always, researchers are concerned with one direction of causality—how providers influence patients. But what about the other way? There is no one-way street in an interpersonal situation. A physician’s behavior can be influenced by his or her own attitudes and characteristics, but also by the characteristics and the behavior of the patient. The patient’s health status, discussed earlier, is one domain where either a patient characteristic (poor health) or patient behavior (negativity resulting from poor health) might have an impact on the physician’s behavior. Studies on physician gender also suggest this. Patients talk differently to male and female physicians [15]. Mostly, the patient behaviors match those which male and female physicians engage in—for example, female physicians speak more positively, and patients speak more positively to female physicians. This is a situation ripe with causal possibilities, one of which is that patients produce the physician gender difference in the first place. In other words, patients’ expectancies for how male and female physicians will behave (based on gender stereotypes of women as more interpersonally oriented and democratic than men) may be reflected in the patients’ behavior, and physicians may then reciprocate in kind, thus producing differences in how male and female physicians behave. Speculative though this is, it brings us back to the starting point of this article, which is that entertaining and testing different causal possibilities must become a high priority in research on provider–patient communication.
8. What is it all for? When reviewing studies of patients’ satisfaction with care some 15 years ago [1], I asked why researchers conduct so much satisfaction research and what the results were actually
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being used for. This question can be asked about all research on provider–patient communication. In a field that justifies itself on grounds of practical relevance, we cannot simply be scholars and we cannot speak only to one another. Clearly, society values this research because it supports the thousands of researchers who do it, the journals they publish in, the conferences they put on, and so on. But why? In my opinion, this is not a trivial question and unfortunately the answer is not easy to find. As we all know, most scholarly research falls into oblivion as soon as it is published; some proliferation of research may happen simply because researchers do not know what has already been done. Sometimes a piece of research catches on in citations, or is scooped up by a meta-analyst who is able to make an integrative statement. Integrative statements are good, but they still beg the question of why? Who or what is the integration for? If we want our research to be used in medical education, how can we make sure that it does? If we want our research to help consumers deal with their providers, or to help providers know more about communication and its consequences, how can we make that happen? If the goal is to help health maintenance organizations and hospitals deliver the best quality care, how do we accomplish that? This is a collective discussion that I hope takes place.
9. Conclusion This has not been a review of either the general literature on provider–patient communication or the literature on cancer in particular. Such reviews have been done [16–18]. My purpose was to highlight some directions in which research could profitably go. All of the issues I have raised should, in principle, be relevant to communication with patients no matter what their diagnosis. There are, of course, issues not discussed here that are likely to be especially relevant to patients who have cancer, such as the breaking of bad news, negotiating treatment alternatives, and dealing with disfigurement. Considering that what physicians mainly do with their patients is talk, one cannot emphasize too strongly the importance of studying communication processes. Depending on the research question at hand, communication may be studied in its own right, descriptively, or it may serve as an outcome, a predictor, a mediator of a process, or a moderator of relationships among other variables. It is important to
take all of these approaches in tackling this crucial area of study.
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