Reducing diagnostic bias. (Practice).
Many counselor educators see greater diagnostic skill with the fourth edition of the Diagnostic and Statistical Manual of the American Psychiatric Association, Text Revised (American Psychiatric Association, 2000) as essential for enhanced professional credibility, career marketability, and third-party reimbursement (Fong, 1990, 1993; Foos, Ottens, & Hill, 1991; Geroski, Rogers, & Breen, 1997; Hohenshil, 1993, 1996). Most counselor education literature on the DSM has been focused on instructional approaches, clinical applications, and reconciliation with the traditional counseling focus on normal development (Hershenson, 1992, 1993; Hershenson & Strein, 1991; Ivey & Ivey, 1998). Along with learning about the DSM, counselors also need to learn how to achieve skill in its use.
Achieving skill with the DSM means learning how to diagnose accurately and reduce diagnostic inaccuracy or misdiagnosis (Hohenshil, 1993; Seligman, 1996). Reducing diagnostic bias is one way to reduce misdiagnosis (Cook, Warnke, & Dupuy, 1993; Furlong & Hayden, 1993). Diagnostic bias is defined by Sinecore-Guinn (1995) as an "error in judgment that counselors make when they collect and interpret information" (p. 18), and by Widiger and Spitzer (1991) as "a differential prevalence of either false-positive diagnoses ... and/or false-negative diagnoses" (p. 3). Greater skill with the DSM requires that counselors learn ways of overcoming diagnostic bias.
Bias is defined statistically as measurement error (Mertens, 1998). Widiger and Sptizer (1991) used a statistical definition of diagnostic bias in suggesting it is "deviation from an expected value" (p. 3). For instance, in 100 coin tosses, bias is expected if the number of heads or tails greatly exceeds a 50-50 ratio, the expected value. Widiger and Spitzer identified sampling, assessment, and criterion bias as risks to accurate diagnosis. The purpose of this article is to define, demonstrate, and discuss ways of reducing sampling, assessment, and criterion bias. First, definitions are presented of each form of diagnostic bias. Second, empirical demonstrations are provided of each form of diagnostic bias. A final section lists ways of reducing each of these forms of diagnostic bias, and implications for counselor training, research, and practice.
DIAGNOSTIC SAMPLING BIAS
Diagnostic sampling bias occurs when there are significant differences between a particular diagnostic sample and the population it is taken to represent (Garb, 1998; Gilovich, 1991). An example of diagnostic sampling bias is drawing conclusions about the gender of individuals with Post-Traumatic Stress Disorder (PTSD) on the basis of a sample taken from a veteran's hospital (Widiger & Spitzer, 1991). Because of the disproportionate number of men in that setting, conclusions about the gender of those with PTSD will be biased.
Demonstrations of Diagnostic Sampling Bias
DeGrandpre (1999) demonstrated diagnostic sampling bias in an examination of the ability of physicians to diagnose Attention Deficit Hyperactivity Disorder (ADHD) solely from observation of children in their offices. His results indicated that more than three of four children described as hyperactive by parents and teachers showed "exemplary behavior and no sign of hyperactivity in the [doctor's] office" (p. 133). This demonstrates how a non-representative sample of observations (i. e., only in a physician's office) can lead to misdiagnosis.
Researchers also demonstrated sampling bias in another study comparing clinical and community samples of children with a diagnosis of ADHD (Sharp, Walter, & Marsh, 1999). In referred samples, four to nine times more boys than girls received an ADHD diagnosis. However, in community samples, ratios as low as two to one have been found. This gender discrepancy between clinical and community samples raises questions about the representativeness of many clinical samples.
Wilke (1994) also demonstrated diagnostic sampling bias in research with women and alcohol abuse. She observed that, because the most research on alcohol abuse and treatment has focused on men, conclusions about treatment are inappropriate when applied to women. Because women with alcohol problems are less likely than men to drink in public, drink with others, become violent or aggressive, or to come into contact with the law, many of their alcohol problems go undiagnosed and untreated. This research demonstrates how over-generalizing from one group to another can lead to misdiagnosis.
The dramatic rise in the number of Multiple Personality Disorder (MPD) diagnoses made during the 1970s in the United States can also be seen as a demonstration of diagnostic sampling bias (Hacking, 1995; Ofshe & Watters, 1994; Spanos, 1994). The increased number of MPD diagnoses given to individuals in the United States did not occur elsewhere (Kutchins & Kirk, 1997). Therefore, some observers have concluded that the increase in the United States constituted a biased sample instead of reflecting an actual increase in the disorder (Hacking; Ofshe & Watters).
DIAGNOSTIC ASSESSMENT BIAS
Diagnostic assessment bias occurs when flaws in gathering or processing clinical information lead to misdiagnosis (Dawes, 2001; Falvey, 1992; Gambrill, 1990; Rabinowitz & Efron, 1997). Diagnosing someone solely on the basis of a previous clinician's assessment is an example of diagnostic assessment bias. The lack of a timely and comprehensive assessment can lead to diagnostic assessment bias and thus misdiagnosis.
Demonstration of Diagnostic Assessment Bias
One issue in the diagnostic assessment bias literature is errors in applying the diagnostic criteria (Rabinowitz & Efron, 1997). In one demonstration of this bias, Morey and Ochoa (1989) asked 291 psychiatrists and psychologists to complete a symptom checklist for a client whom they had diagnosed with a personality disorder. When the checklists were later correlated with the DSM criteria, nearly three of four clinicians had made mistakes in applying the diagnostic criteria. Kappa coefficients of agreement between clinicians' checklists and the DSM criteria varied from 0.09 to .59, indicating a poor-to-modest level of agreement (Babbe, 1998). These results demonstrate the pervasiveness of errors in applying diagnostic criteria.
Errors in applying the DSM criteria were also reported by Davis, Blashfield, and McElroy (1993). They asked 42 psychologists and 17 psychiatrists to read and diagnose case reports containing different combinations of the DSM-III-R criteria for Narcissistic Personality Disorder (NPD; APA, 1987). They found that 94% of the clinicians made mistakes applying the diagnostic criteria, and nearly one out of four clinicians made a diagnosis of NPD even if fewer than half the DSM criteria were met.
Rubinson, Asnis, Harkavy, and Freidman (1988) found clinicians making more mistakes of omission than of commission in applying the DSM criteria. Researchers sent 113 questionnaires to a random sample of clinicians asking them what criteria they used to make a diagnosis of Major Depression. The 54 questionnaires returned indicated that clinicians' most often erred by failing to use all the diagnostic criteria in their diagnostic decision making.
The fallibility of supplemental diagnostic assessment methods (e.g., psychometric instruments, structured interviews, psychological reports) is another issue in the literature on diagnostic assessment bias (Gambrill, 1990; Rabinowitz & Efron, 1997). Kosten and Rounsaville (1992) demonstrated this fallibility by showing that diagnoses made by clinicians using structured and semi-structured interviews often differed substantially from those made by panels of expert clinicians using more thorough information from medical records and patient and family interviews. Similar results have also been found when using objective or projective psychological test data to formulate diagnoses (Garb, 1998).
The fallibility of supplemental assessment methods was also demonstrated in a study that compared typical clinical approaches with several supplemental assessment methods in a group of adolescent psychiatric inpatients (Prinstein, Nock, & Spirito, 2001). Prinstein et al. found agreement among the various assessment methods was low to moderate (K = 0.21-0.49), and concluded that accurate assessment requires multiple methods that take into consideration the limitations of each.
Another issue in the diagnostic assessment bias literature is human information processing errors (Dawes, 2001; Falvey, 1992; Gambrill, 1990; Piattelli-Palmarini, 1994; Rabinowitz & Efron, 1997; Spengler, 2000; Spengler & Stromer, 1994; Turk & Salovey, 1988). Several of these errors have been identified. This discussion will focus on the four information-processing errors most likely to lead to assessment bias and misdiagnosis:
* Data availability and vividness
* Self-confirmatory bias
* Self-fulfilling prophecy
Stereotyping. Stereotyping refers to "special types of cognitive structures involved in categorizing individuals or social targets" (Abreu, 2001, p. 493). Stereotyping distorts the normal information-processing strategy of making judgments on the basis of the multidimensional resemblance of a case to an ideal example or prototype (Falvey, 1992; Garb, 1998; Gilovich, 1991; Lakoff, 1987;Turk & Salovey, 1988). In stereotyping, judgments are made on the basis of only one or a limited number of common features. Because of their incompleteness and inflexibility, stereotypes often lead to error, and clinical stereotypes often lead to misdiagnosis (Abreu; Falvey; Gambrill, 1990; Garb; Rabinowitz & Efron, 1997; Turk & Salovey).
One demonstration of how stereotyping can lead to misdiagnosis comes from a study in which 290 African-American and White psychiatrists of both genders diagnosed case summaries. The results indicated that "all four groups of psychiatrists seem to be influenced by the clients' sex and race" (Loring & Powell, 1988, p. 17). A similar study by Landrine (1989) reached the same conclusion. In her study of two proposed diagnoses, she found Sadistic Personality Disorder more often diagnosed in males, and Self Defeating Personality Disorder more often diagnosed in females.
Another demonstration of stereotyping leading to misdiagnosis came from a study in which 67 psychologists and psychology interns first made diagnoses of case histories, and then rated how closely those case histories were to a typical person showing symptoms consistent with that particular diagnosis (Garb, 1998). Participants' ratings indicated they believed the case histories were quite typical of those receiving a particular diagnosis; however, the correlations between their diagnoses and their ratings and the DSM criteria were low. This result suggests they had made their diagnostic judgments on the basis of clinical stereotypes rather than the DSM criteria.
Data availability and vividness. Data availability and vividness refers to categorizing something on the basis of its familiarity, ease of recall, or salience (Falvey, 1992; Piattelli-Palmarini, 1994; Spengler, 2000; Turk & Salovey, 1988). One demonstration of this information-processing error used a questionnaire to ask clinicians how they made a diagnosis of depression (Rubinson et al., 1988). The clinicians' reports indicated that they had used a subset of the DSM criteria they found most familiar, salient, or easiest to recall in formulating their diagnoses. A study by Robertson and Fitzgerald (1990) found similar results. They randomly assigned 47 counselors to view different videos of an actor portraying a depressed male. The only difference in the videos was the client's occupational and family role, which was categorized as either traditional or nontraditional. The results indicated counselors based their diagnostic judgments more on the available and vivid family and occupational role than on the less available and vivid signs and symptoms of a specific disorder.
A focus on data availability and vividness as a basis for diagnostic judgment can also lead to an under-emphasis on co-existing, but less available and vivid disorders (Spengler, 2000; Spengler & Stromer, 1994). This underemphasis on possible co-morbidity has been referred to as "diagnostic overshadowing" (Spengler & Stromer, p. 8) and occurs independent of practitioners' experience, expertise, theoretical proclivity or nature of the client's problems (Spengler & Stromer).
Data availability and vividness also explains how the phenomenon of Primacy Effects can contribute to misdiagnosis (Lake, 2000). Primacy Effects refer to how people are most influenced by the first information they receive about something (Gilovich, 1991). Sharps, Price, and Bence (1996) offer an empirical demonstration of this effect. They hypothesized that pictorial information would be less affected by the primacy effect than verbal or auditory information. To test their hypothesis, they presented 40 photos, sounds, and words to 70 participants. The results confirmed their hypothesis: Pictorial information was significantly less affected by the primacy effect than either sounds or words. However, given the large part played by words in diagnostic practice (there are few pictures in the DSM), this study demonstrates how primacy effects can contribute to misdiagnosis. Finally, basing diagnostic decisions on data availability and vividness can also lead to the neglect of base-rate data, or what is typical in a given population. Neglect of base-rate data in favor of other data such as personal clinical experience has long been associated with less accurate clinical judgments, including misdiagnosis (Falvey, 1992; Rabinowitz & Efron, 1997; Spengler, 2000).
Self-confirmatory bias. This error refers to categorizing something by focusing only on confirmatory information (Stromer, Boas, & Abadie, 1996). This error is demonstrated by counseling and counseling psychology students who first saw a video of an initial counseling session and then were asked to provide a list of questions they wanted to ask the client and explanations for their questions. The questions were then coded as to whether they sought confirmatory, disconfirmatory, or neutral client information. The results indicated 64% of the questions sought confirmatory information, 21% sought disconfirmatory information, and 15% sought neutral information (Haverkamp, 1993). A study by Pfeiffer, Whelan, and Martin (2000) obtained similar results.
Self-fulfilling prophecy. This error refers to acting on an expectation in a way that confirms it (Garb, 1998; Gilovich, 1991). Rosenhan (1973) provides probably the most notable demonstration of self-fulfilling prophecy connected to psychiatric diagnosis. He had 12 research confederates gain admission to psychiatric hospitals by complaining of auditory hallucinations. The 12 gave truthful answers to all questions except their name, occupation, and place of employment. Once admitted, none of the confederates complained of further symptoms. Nonetheless, all 12 were misdiagnosed as suffering from serious psychiatric disorder at discharge. Rosenhan demonstrates how a self-fulfilling prophecy can lead to misdiagnosis by showing how the hospital staff acted to confirm their expectation that individuals admitted to psychiatric hospitals have a diagnosable disorder by diagnosing them even in the face of information to the contrary.
Kyunghee (1996) also demonstrated self-fulfilling prophecy by showing how some teachers' views of intelligence influenced their predictions of academic performance. Teachers first took a test to identify whether they saw intelligence as static or as malleable. The teachers were then told about a student referred for counseling because of adjustment problems, were asked to grade that student's math assignment, and then to predict how well that student would do academically. The results indicated that teachers with a static view of intelligence offered biased predictions that confirmed their original views of intelligence.
DIAGNOSTIC CRITERION BIAS
Diagnostic criterion bias occurs when diagnostic criteria are "more valid for one group than for another" (Garb, 1998, p. 233). Making diagnostic judgments based on a White-male standard of adjustment has been viewed as diagnostic criterion bias (Cook et al., 1993; Russell, 1994; Tavris, 1992). Because of the greater social challenges women and minorities face, using a White-male standard of adjustment is seen as prejudicial, an example of diagnostic criterion bias (Caplan, 1995; Russell; Tavris; Wilke, 1994). For example, Cook et al. refer to the "male-based norms" (p. 312) used as a basis for determining mental health in the DSM, and Caplan rejected the DSM diagnosis of "Premenstrual Dysphoric Disorder" (APA, 1994, p. 717), because of its bias against women.
Demonstration of Diagnostic Criterion Bias
Broverman, Broverman, Clarkson, Rosendrantz, and Vogel (1970), in probably the most publicized study of criterion bias, demonstrated how clinicians viewed typical male traits (i. e., independent, forceful, domineering) as more closely associated with a healthy adult than they did typical female traits (i. e., nurturing, deferential, reserved). This study demonstrated diagnostic criterion bias by showing how a prejudice towards typical male traits over female traits can cause misdiagnosis.
The issue of homosexuality in the DSM is another example of diagnostic criterion bias (Caplan, 1995; Kirk & Kutchins, 1992; Kutchins & Kirk, 1997; Tavris, 1992). Homosexuality was included as one of the Sexual Deviations in the first edition of the DSM, and listed as a separate diagnosis in DSM-H (APA, 1952). In the 12 years between publication of the DSM-II and the DSM-III, a debate occurred over whether homosexuality was a diagnosable condition (Caplan; Kutchins & Kirk). Subsequently, the DSM-III included only homosexuality that troubled the individual (Ego-Dystonic Homosexuality) as a diagnosis, and 7 years later the diagnosis was eliminated altogether (APA, 1980; APA, 1987; Kutchins & Kirk). The inclusion and elimination of homosexuality as a diagnosis in the DSM has been in large measure attributed to awareness of the criterion bias inherent in the diagnosis (Kutchins & Kirk; Tavris).
Pollack, Martin, and Langebucher (2000) also demonstrated diagnostic criterion bias when they examined the correspondence among diagnostic criteria for alcohol use disorders (AUDs) in a group of teenagers across three editions of the DSM. More than 400 youth from mental health clinics and the community participated. AUDs were determined through a structured interview designed for the DSM and altered to reflect each successive edition. The results indicated moderate to good correspondence in the diagnostic criteria for alcohol dependence, and poor correspondence on the diagnostic criteria for alcohol abuse. Pollack et al. concluded that there remains a lack of consensus about the diagnostic criteria for alcohol disorders in the DSM. Their findings demonstrate how shifting diagnostic criteria can lead to misdiagnosis.
REDUCING MISDIAGNOSIS DUE TO DIAGNOSTIC BIAS
Strategies for Reducing Diagnostic Sampling Bias
Reducing misdiagnosis due to diagnostic sampling bias requires counselors to consider how insufficient, nonrepresentative data can lead to misdiagnosis. Counselors can do the following to reduce diagnostic sampling bias:
1. Cultivate mental habits to counter tendencies to make "too much from too little" (Gilovich, 1991, p. 29). Ask yourself, for instance, "How might nonrepresentative diagnostic data be biasing my diagnostic judgment?"
2. Pay attention to how your work setting may bias your diagnostic judgments.
3. Focus on the atypical aspects of a case because doing so may help you detect ways it is not typical of a particular diagnosis (Morrow & Deidan, 1992).
Reducing Misdiagnosis due to Diagnostic Assessment Bias
Reducing misdiagnosis due to diagnostic assessment bias requires counselors to develop ways of assuring proper collection and processing of clinical information. Counselors can do the following to minimize diagnostic assessment bias:
1. Adhere with all the DSM diagnostic criteria, and keep current about revisions.
2. Consider the possibility of co-morbidity as a guard against the diagnostic overshadowing bias (Spengler & Stromer, 1994).
3. Take the time to consider different diagnostic possibilities. Recent research indicates that delaying diagnostic judgments improves their accuracy and reduces the influence of primacy effects (Hill & Ridley, 2001; Morrow & Deidan, 1992).
4. Use a sign and symptom checklist as part of a standard assessment to assure that all the DSM criteria for a particular disorder have been considered.
5. Complete a "balance sheet" (Arnoult & Anderson, 1988, p. 209) of the pros and cons of a particular diagnosis to guard against confirmatory bias.
6. Base diagnostic decisions on multiple, sound assessment instruments to reduce misdiagnosis due to fallible assessment methods (Turk & Salovey, 1988).
7. Write down your expectations about clients to make them explicit and thereby reduce the likelihood of self-fulfilling prophecies (Morrow & Deidan, 1992).
Reducing Diagnostic Criterion bias
Reducing diagnostic criterion bias requires counselors to keep in mind the strengths and limitations of the DSM and the diagnostic process. Despite its flaws, successive editions of the DSM have achieved increased increments in reliability and validity of many diagnostic categories (Nathan & Langenbucher, 1999). In order to reduce misdiagnosis due to diagnostic criterion bias counselors can do the following:
1. Keep in mind the role social factors play in the development of psychiatric diagnostic criteria and be aware of how the DSM favors some groups over others (Kirk & Kutchins, 1992; Kutchins & Kirk, 1997).
2. Follow all ethical and legal mandates for professional practice regarding diagnosis (Garb, 1998).
3. Take advantage of all available DSM training, with a particular emphasis on how to use the DSM in a way sensitive to the needs of a diverse, multicultural society (Aderibigbe & Pandurangi, 1995; Rogler, 1992).
IMPLICATIONS FOR COUNSELOR TRAINING AND PROFESSIONAL PRACTICE
There are several implications in this article for counselor training and professional practice. First, training in key social-science concepts should precede DSM training in counselor curricula, because understanding key social-science concepts promotes critical inquiry (Arnoult & Anderson, 1988; Dawes, 2001; Lehman, Lempert, & Nisbett, 1988). Counseling students should understand at minimum the concepts of representative sampling, reliability and validity, correlation, and the logic of base-rates before taking coursework in the DSM.
Second, counselors must have in-depth information about the current scientific standing of the DSM (Nathan & Langenbucher, 1999). This information is essential for counselors to make informed decisions about its use in their professional practice. Being ill informed about the scientific status of the DSM invites either overconfidence or cynicism and corresponding risk of misdiagnosis (Rentoul, 1995).
Third, counselors must be able to distinguish sound from unsound assessment instruments and practices (Falvey, 1992; Widiger & Spitzer, 1991). They must understand the importance of a comprehensive assessment and how to reach rational conclusions from data (Dawes, 2001; Gambrill, 1990; Garb, 1998; Rabinowitz & Efron, 1997). Counselors should also be cautious about the predictive power of tests and other assessment instruments and should be taught different assessment methods for different professional settings and circumstances (Gambrill; Garb).
Fourth, counselor education coursework should include a detailed review of the human information processing errors related to clinical practice (Rabinowitz & Efron, 1997; Rentoul, 1995). That review should include the four errors identified in this article and any cognitive errors future research identifies as relevant to diagnostic decision making.
Fifth, coursework in the DSM should include both "conventional and sociohistorical" (Sampson, 1991, p. 3) perspectives on psychiatric diagnosis (Ivey & Ivey, 1999; Rentoul, 1995). Whereas in the former, diagnostic categories are viewed as representing objective entities, in the latter they are viewed as socially constructed (Gergen, 1994; Leeds-Hurwitz, 1995). These two perspectives can provide a conceptual framework for helping students appreciate the social and scientific aspects of the DSM and help produce a deeper, more sophisticated understanding of the DSM and the diagnostic process (Rentoul).
Practicing counselors will benefit from creating a work environment where careful use of the DSM is supported (Gambrill, 1990; Turk & Salovey, 1988). They will also benefit from implementing a number of practices, including being alert for the three forms of bias discussed here, and any preconceptions they bring to their diagnostic practice (Rabinowitz & Efron, 1997). Creating opportunities to receive feedback from peers on diagnostic decisions is also an important way of furthering diagnostic skill and practice and of reducing misdiagnosis (Garb, 1998). Implementing these suggestions should help reduce misdiagnosis due to diagnostic bias and help enhance professional counselors' credibility, marketability, and opportunities for reimbursement.
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Jerry E. McLaughlin, Ph.D., is an assistant professor, Department of Counselor Education and Counseling Psychology, Western Michigan University, Traverse City MI. Email firstname.lastname@example.org
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|Author:||McLaughlin, Jerry E.|
|Publication:||Journal of Mental Health Counseling|
|Date:||Jul 1, 2002|
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