Assessment & Diagnosis

Journal of Counseling & Development October 2012 olume 90V 483 Dimensional and Cross-Cutting Assessment of the DSM-5 widespread social fears, it also ...

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Assessment & Diagnosis

Received 06/01/11 Revised 08/13/11 Accepted 09/05/11

Dimensional and Cross-Cutting Assessment in the DSM-5 K. Dayle Jones A significant proposed change to the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) that will significantly affect the way counselors diagnose mental disorders is the addition of dimensional assessments to the categorical diagnoses. The author reviews the current DSM’s (4th ed., text rev.; American Psychiatric Association, 2000) categorical classification system, describes the proposed dimensional and cross-cutting assessments, and provides implications about clinical utility and user acceptability of a dimensional diagnostic approach. Keywords: DSM-5, diagnosis, assessment, dimensional assessment, cross-cutting assessment

With the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; hereinafter referred to as the DSM when used in the general sense) set for release in May 2013, counselors are awaiting changes that may affect how they diagnose. A significant proposed change to the DSM-5 is the addition of dimensional assessments to the categorical diagnoses (American Psychiatric Association [APA], n.d.). The current edition of the DSM (4th ed., text rev.; DSMIV-TR; APA, 2000) uses a categorical classification system. A categorical diagnosis has only two values: the presence or absence of a disorder. Categorical diagnostic systems assume that mental disorders are discrete entities, with relatively homogeneous populations that display similar symptoms and attributes of a disorder. Because client populations are typically heterogeneous and do not fall neatly into diagnostic categories, this assumption has led to many problems and shortcomings with the categorical system (Regier, 2008). Problems such as excessive comorbidity, irresolvable boundary disputes, and excessive use of the not otherwise specified (NOS) categories have become endemic to the manual (First, 2010a, 2010b). To address the limitations of the DSM-IV-TR (APA, 2000) and improve clinical utility, the DSM-5 Task Force is proposing the addition of dimensional assessments to every categorical diagnosis in the DSM. Dimensional assessments are rating scales that measure frequency, duration, severity, or other characteristics of a disorder. The assessments provide additional information to assist counselors with diagnosis, treatment planning, and treatment monitoring. In addition to including dimensional assessments for individual disorders, the DSM-5 Task Force is also proposing cross-cutting assessments to measure diagnostic symptoms commonly seen in

clients, regardless of their presenting problem or subsequent diagnosis (APA, n.d.). The assessment is intended for use during an initial clinical interview to measure symptoms commonly seen and monitored in most clients (e.g., depressed mood, anxiety, and substance use) regardless of their initial presenting problems or diagnosis. To fully understand and utilize the proposed dimensional and cross-cutting assessments, counselors need to be knowledgeable about the difference between categorical and dimensional approaches to diagnostic classification. Research about diagnostic classification systems is scarce in the counseling literature; thus, the purpose of this article is to present information about the propounded DSM-5 dimensional and cross-cutting assessments. In this article, I review the DSM-IVTR’s (APA, 2000) categorical classification system, describe the proposed dimensional and cross-cutting assessments, and provide implications about clinical utility and user acceptability of a dimensional diagnostic approach.

The DSM Classification System The purpose of classification in the sciences is to guide the observation and interpretation of the natural world (Millon, 1991). Classification (i.e., taxonomy) is defined as the “activity of ordering or arranging objects into groups or sets on the basis of their relationships” (Sokal, 1974, p. 1116). Constructing a diagnostic classification system is a way of finding order for the otherwise complex, intricate, and unorderable phenomena of psychopathology. It also helps counselors communicate, select effective interventions, predict course and prognosis, and differentiate between disorders and nondisorders (First, 2010a).

K. Dayle Jones, Department of Educational and Human Sciences, University of Central Florida, Orlando. Correspondence concerning this article should be addressed to K. Dayle Jones, Department of Educational and Human Sciences, University of Central Florida, Orlando, PO Box 161250, Orlando, FL 32816-1250 (e-mail: [email protected]). © 2012 by the American Counseling Association. All rights reserved.

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Jones The DSM-IV-TR (APA, 2000) uses a categorical classification system that “divides mental disorders into types based on criterion sets with defining features” (p. xxxi). A categorical diagnosis has only two values: the presence or absence of a disorder. It assumes that members of a diagnostic group are relatively similar, having specific symptoms that reflect the particular diagnosis. Using this framework, counselors assess clients using a polythetic (i.e., checklist) approach, whereby a client must meet a minimum number of symptoms to receive a diagnosis. For example, to receive a diagnosis of major depressive episode, a client needs to meet at least five out of nine criteria. Categorical diagnostic classification models help unify a client’s pathology by integrating seemingly diverse elements or symptoms into a single, coordinated configuration (Millon, 1991). It is human nature to categorize; therefore, a categorical model allows clinicians to group together intricate and ambiguous diagnostic phenomena (Widiger & Coker, 2003). Furthermore, the current diagnostic categories, most being present over the past 20 to 30 years since the third and fourth editions of the DSM (APA, 1980, and APA, 1994, respectively), are considered historically well-established syndromes (Simonsen & Widiger, 2006). Therefore, they are familiar to most counselors and have long facilitated communication among mental health professionals. Most clinicians prefer categorical models because they are generally easier to use in making rapid diagnoses with numerous clients. However, researchers have long documented the shortcomings of categorical diagnostic models. Mental disorder categories are problematic and frustrating because they suggest a uniformity of diagnoses and homogeneity of pathology that seems rarely present in clients (Widiger & Coker, 2003). In fact, the reality is that client populations, although appearing to have similar clinical presentations, are highly heterogeneous (Regier, 2008). Moreover, categories often fail to identify or include significant aspects of symptomatology because they do not fit into the set of predetermined diagnostic characteristics (Millon, 1991). Therefore, the DSM-IV-TR (APA, 2000) routinely fails in the goal of guiding counselors to the presence of one specific disorder. As a result, the manual is replete with problems of excessive comorbidity, boundary disputes, and excessive use of the NOS categories.

Problems With the Current Classification System Excessive Co-Occurring Disorders The term co-occurring disorders (i.e., comorbidity) refers to the presence of multiple diagnoses or pathologies within the same individual. Epidemiologic and clinical studies have found extremely high rates of comorbidities among the DSM disorders. For example, Andrews, Slade, and Issakidis (2002) analyzed data from more than 10,000 participants in the Aus-

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tralian National Survey of Mental Health and Well-Being and found that 40% of the sample met the diagnostic criteria for more than one current disorder. Other studies have found that mood disorders are strongly comorbid with anxiety disorders (and vice versa; Kessler et al., 1996; Mineka, Watson, & Clark, 1998); anxiety disorders are highly comorbid with one another (Brown, Campbell, Lehman, Grisham, & Mancill, 2001; Magee, Eaton, Wittchen, McGonagle, & Kessler, 1996); and mood and anxiety disorders are comorbid with other types of psychopathology, such as substance use disorders, eating disorders, somatoform disorders, and personality disorders (Mineka et al., 1998; Widiger & Clark, 2000). It seems that diagnostic comorbidity is the norm rather than the exception (Widiger & Samuel, 2005). The existence of excessive diagnostic co-occurrence has been widely recognized as a significant limitation in the DSM. It brings to question whether the comorbidity is indeed the co-occurring presence of multiple mental disorders or the presence of one disorder that is being given multiple diagnoses (Widiger & Coker, 2003). It also challenges the validity of the diagnostic categories themselves, providing evidence that mental disorders are not discrete clinical entities (Kupfer, 2005; Kupfer, First, & Regier, 2002). Boundary Disputes A categorical classification approach works best when “members of a diagnostic class are homogeneous” and “there are clear boundaries between classes” (APA, 2000, p. xxxi). Yet many psychological constructs follow a continuous distribution; in other words, individuals with anxiety are not merely anxious or not anxious (with a clear boundary in between), they experience infinite degrees of anxiety (Fauman, 2002). Because mental disorders are neither homogeneous nor divided by clear boundaries, the DSM has a history of problematic and irresolvable boundary disputes. To attempt to reduce boundary problems and to fill the gaps in boundaries existing in diagnostic categories, previous editions of the DSM have added more diagnoses, subtypes, and specifiers. Examples are the addition of (a) Bipolar II disorder to fill the gap between Bipolar I and cyclothymia, (b) mixed anxiety-depressive disorder to account for subthreshold cases of mood and anxiety disorders, and (c) the generalized subtype for social phobia when the feared situation includes most social situations (Widiger & Coker, 2003; Widiger & Samuel, 2005). Notable ongoing boundary disputes include the distinction between oppositional defiant disorder, attention-deficit/ hyperactivity disorder, and conduct disorder; anorexia and bulimia; and hoarding as a symptom of obsessive-compulsive disorder, as a criterion of obsessive-compulsive personality disorder, or as a separate disorder. Sometimes the addition of new diagnoses or specifiers has created more boundary problems. For example, although the addition of the social phobia “generalized” specifier accounted for clients with

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Dimensional and Cross-Cutting Assessment of the DSM-5 widespread social fears, it also blurred the boundary with avoidant personality disorder. Excessive Use of NOS Categories To deal with the boundary problems of the existing diagnostic categories, clinicians often use the NOS categories (First, 2010a). The NOS diagnoses are often referred to as “catchall” categories that are generally used when a clinician has determined that a mental disorder is present, but the client fails to meet the criteria for one of the existing diagnostic categories (APA, 2000). Because the NOS categories are considered residual categories, the number of cases given NOS diagnoses should be modest in number (Fairburn et al., 2007). In reality, clinicians frequently use the NOS diagnosis. In fact, for some diagnostic categories such as mood disorders (APA, 2010), eating disorders (Fairburn et al., 2007), bipolar disorder (Cassano et al., 1999), and personality disorders (Wilberg, Hummelen, Pedersen, & Karterud, 2008), the NOS category is used at least as often as any of the specific classifications. Clinicians’ reliance on NOS diagnoses is well documented, particularly with cases involving subthreshold symptoms (i.e., when a client presents with symptoms below the cut points necessary for a diagnosis) and for clinically significant conditions that are not included in the DSM-IV-TR (APA, 2000; First, Frances, & Pincus, 2004). However, because the NOS categories provide only general information, their usage results in a significant loss of diagnostic information (First, 2010a).

Dimensional and Cross-Cutting Assessment Dimensional Assessments Excessive comorbidity, boundary disputes, and excessive use of the NOS categories undermine the hypothesis that DSM-defined disorders represent distinct entities. Instead, researchers have questioned whether disorders would be best classified as dimensions that exist along continuous distributions (Widiger, 2005; Widiger & Coker, 2003; Widiger & Samuel, 2005). Unlike the binary “yes–no” approach of the categorical model, the dimensional approach uses three or more ordered values (i.e., rating scales) to measure severity, intensity, frequency, duration, or other characteristics of given DSM categories. For example, symptom severity could be measured using a 4- or 5-point rating scale. The term dimensional is likely a misnomer for what is better described as ordinal. A dimensional system works better than categories when describing phenomena, such as psychiatric diagnoses, that are distributed continuously and do not have clear boundaries (Kraemer, Noda, & O’Hara, 2004). As an example of a dimensional assessment for the DSM-5, the DSM-5 Mood Disorder Work Group is considering using the Patient Health Questionnaire–9 (PHQ-9; Kroenke &

Spitzer, 2002) for major depressive disorder. The PHQ-9 is a nine-item self-report scale that reflects the nine symptoms of major depressive episode. It assesses symptom severity over a 2-week period using a 4-point scale: 0 = not at all, 1 = for several days, 2 = more than half the days, 3 = nearly every day. The respondent is asked, “Over the last two weeks, how often have you been bothered by any of the following problems?” Each item corresponds to depressive symptoms (e.g., “little interest or pleasure in doing things”; “feeling down, depressed or hopeless”; and “trouble falling or staying asleep”). Out of a possible 27 points, cut scores of 5, 10, 15, and 20 represent mild, moderate, moderately severe, and severe depression, respectively. Dimensional approaches may provide many benefits for diagnosis and clinical decision making. When psychopathology is viewed not only as absent or present, but also dimensionally, dimensional assessments have the potential to more richly convey clinical presentations than categorical diagnostic systems (Brown & Barlow, 2005). Adding measures of severity, frequency, and other features to diagnoses can also assist in determining the best therapeutic plan. It is important to note that the DSM-5 Task Force is not proposing to abandon the categorical diagnoses, but to add dimensional measures to supplement the categories (Regier, Narrow, Kuhl, & Kupfer, 2009). This way, the current categorical system remains intact. The principal goal of supplementing categorical diagnoses with dimensional assessment is to improve the clinical and scientific utility of the DSM-5, thereby providing clinicians with additional information for assessment, treatment planning, and treatment monitoring. Crossing-Cutting Assessments In addition to dimensional assessments for individual disorders, the DSM-5 Task Force is also proposing cross-cutting dimensional assessments. Cross-cutting assessments are not specific to any particular disorder; rather, they evaluate symptoms of high importance to nearly all clients in most clinical settings (APA, n.d.). The assessments are called crosscutting because they cut across the boundaries of any single disorder and represent symptoms commonly seen in clinical practices, regardless of a client’s subsequent diagnosis. They are designed to be administered to all clients at the initial evaluation to establish a baseline and on follow-up visits to monitor progress. The DSM-5 Task Force has chosen to use scales developed by the National Institutes of Health PatientReported Outcomes Measurement Information System, which has developed assessments for several clinical domains that the task force has deemed useful for cross-cutting assessments (APA, n.d.). The cross-cutting assessment consists of two levels. Level 1 assessments are self-report measures that evaluate such major clinical domains as depressed mood, anxiety, suicide risk, sleep disturbance, and substance use. Separate assess-

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Jones ments are available for adults and children. For example, the Level 1 assessment for adults asks clients, “During the past 2 weeks, how much have you been bothered by the following problems?” Sample items are “little interest or pleasure in doing things” (depressive symptoms); “feeling nervous, anxious, frightened, scared, or on edge” (anxiety); and “problems with sleep that affected your sleep quality overall” (sleep disturbance; APA, n.d.). Clients rate items on a 5-point scale ranging from 0 (none–not at all) to 4 (severe–nearly every day). If any Level 1 domain is rated as clinically significant, then clinicians complete the Level 2 clinician-rated follow-up measure to provide a more detailed assessment of the specific symptoms endorsed on the Level 1 measure (APA, n.d.). For example, if depression is indicated from the Level 1 assessment, the clinician would complete the Level 2 “Emotional Distress–Depression” assessment, which is an eight-item measure that uses a 5-point scale (1 = never, 5 = always) to evaluate such depressive symptoms as worthlessness, helplessness, and hopelessness. Benefits and Risks The dimensional classification approach offers some clear advantages over categorical models. For example, the purpose of any diagnostic system is not to say what is “normal” or “abnormal” (Kraemer, 2007, p. S8); yet, by using a binary categorical classification, that is essentially what is happening. In contrast, because dimensional scales assess disorders using three or more ordered values, they measure more than simply a disorder’s presence or absence. Furthermore, they yield a greater amount of clinical information and avoid the loss of information associated with a categorical assessment (Helzer, Bucholz, & Gossop, 2008; Watson, 2005). Dimensional models may also facilitate diagnosis of unusual or atypical cases (Millon, 1991). For example, among those who have a categorical diagnosis, there is variation in precursors (e.g., environmental exposures, age of onset, and premorbid characteristics), specific symptomatology, severity, response to treatment, and consequences (e.g., disability, impairment, and diminished quality of life; Kraemer, 2007). As an adjunct to categorical diagnoses, a dimensional assessment may identify important sources of heterogeneity among those who have a categorical diagnosis. Widiger and Samuel (2005) further speculated that “a dimensional model of classification could provide a more specific and individualized profile description of a patient’s psychopathology that may in turn have more differentiated and specific treatment implications” (p. 500). Therefore, dimensional assessments could help counselors document all of a client’s symptoms (including subthreshold levels of disorders), aid in developing more precise treatment plans, and monitor treatment progress and improvements even if the symptoms do not disappear completely. Objections have also been voiced about the proposed dimensional assessments. Because dimensional models involve

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assessing symptoms on a rating scale (rather than using a checklist approach), they are inherently more complex than diagnostic categories. Consequently, they have been criticized as being laborious and time consuming, and thus less useful than categorical systems for clinical practice (First, 2010a). Furthermore, changes in previous DSM editions have been, for the most part, incremental, consisting mostly of refinements to the existing diagnostic criteria and creations of a few new diagnoses and subtypes. Thus, adding dimensional and cross-cutting assessments would mean radical changes to diagnostic classes, individual disorders, and diagnostic assessment procedures (First, 2005). Because of clinicians’ unfamiliarity with dimensional approaches, a massive retraining effort would be required of all mental health professionals. Another criticism involves the scale development process of the new dimensional and cross-cutting assessments. Allen Frances (2010), chair of the DSM-IV Task Force, expressed concern that most of the 13 DSM-5 Work Groups were creating new dimensional assessments rather than choosing from the many hundreds of well-established rating scales that cover almost every aspect of psychopathology. The problem is the amount of time and work involved in scale development. It can take years to adequately develop a new scale. Items must be written, expert reviewed, and pilot tested. Then items have to be revised, tested again, and revised again, continuing in this way until enough validity and reliability evidence is obtained to support that the scale measures what it is intended to measure. The concern is whether the DSM-5 Task Force has time to develop psychometrically sound scales. Finally, it has not yet been decided how the numerical ratings of the dimensional assessments will be included in the categorical diagnostic coding system. Although it might be possible to convert the proposed dimensional assessments that are simple 5-point scales into severity specifiers and assign them fifth-digit codes (as in the case of major depressive disorder), many of the proposed dimensional assessments are too complex to be represented by a single digit code number. For example, the proposed personality disorders require the use of three separate dimensional assessments to make a diagnosis.

Implications for Clinical Utility and User Acceptability The addition of dimensional and cross-cutting assessments to the DSM-5 has many implications for clinical utility and user acceptability. According to the DSM-5 Task Force, improving clinical utility is a top priority for the DSM revision (Regier et al., 2009). First, Pincus, et al. (2004) defined clinical utility as the “extent to which the DSM assists clinical decision makers in fulfilling the various clinical functions of a psychiatric classification system” (p. 947). They identified several functions of clinical utility, such as conceptualizing diagnostic entities; communicating information to clients, families, and other

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Dimensional and Cross-Cutting Assessment of the DSM-5 relevant parties; selecting effective treatments; and predicting future clinical management needs. Any change in the DSM that improves clinicians’ ability to more effectively achieve any of these functions can be said to improve clinical utility (First, 2010a). Because a major proposed renovation to the DSM-5 is the dimensional assessments, the assessments need to demonstrate clinical utility (First, Pincus, et al., 2004). Although field trials evaluating the DSM-5 dimensional assessments are currently under way, some have already concluded that a dimensional classification approach has more clinical utility because it provides a more complete description of a client’s presenting problem that will, in turn, help clinicians make better decisions about treatment interventions (Widiger & Samuel, 2005). Because the DSM is meant to be used by clinicians, an important aspect of clinical utility is user acceptability. User acceptability refers to the extent to which “a diagnostic system is used at all by its intended end population” (First, Pincus, et al., 2004, p. 949). Achieving user acceptability is critically important, because even if a classification system is theoretically sound, is valid, and provides perfect coverage, it can be completely worthless when it is not used at all or when it is used incorrectly (Verheul, 2005). Whether counselors will accept the proposed dimensional assessments is based upon the benefits exceeding the cost, especially in terms of complexity and time. Most counselors have intense time demands placed on them for seeing clients, treatment planning, and case management; thus, counselors may consider incorporating formal dimensional assessments within the diagnostic criteria as more laborious and not worth their time and effort, especially if those assessments are particularly complex and time consuming. If the proposed dimensional assessments are too complicated for counselors to use, then any purported benefits become a moot point. Introducing complex and potentially burdensome dimensional assessments, regardless of the benefits to best practice, is likely to fail without some plan to help counselors see the advantage of such changes. Counselors could be motivated to use the new dimensional scales by providing evidence that the scales help improve clinical outcome. Furthermore, it can be emphasized to counselors that the DSM-IV-TR (APA, 2000) diagnostic categories are not discrete, but, in fact, represent heterogeneous populations. Therefore, using dimensional assessments would help reduce the current categorical system problems of excessive comorbidity, boundary problems, and excessive use of the NOS categories. One of the best ways to improve user acceptability of the dimensional ratings would be to have them reflected in the diagnostic coding system (First, 2010a). Currently, the only time that clinicians routinely use dimensional specifiers in the DSM-IV-TR (APA, 2000) is for the severity ratings for

major depressive disorder and Bipolar I disorder, both of which are indicated in the fifth digit of the diagnostic code. Many other noncoded severity specifiers (e.g., specifiers for posttraumatic stress disorder, adjustment disorder, and obsessive-compulsive disorder) are largely ignored by clinicians (First, 2010b).

Conclusion The DSM-5 Task Force has proposed adding a dimensional approach to the current categorical diagnostic classification system. Researchers have long cited the many limitations of categorical diagnoses, including excessive comorbidity, irresolvable boundary problems, and excessive use of the NOS categories. It is thought that adding dimensional assessments to the categorical diagnoses will reduce these problems, as well as improve clinical utility. Cross-cutting assessments that measure diagnostic symptoms commonly seen in clients, regardless of their presenting problem or subsequent diagnosis, are also being proposed. Dimensional classification offers some advantages over categorical diagnostic systems, such as yielding more clinical information, identifying sources of heterogeneity among those who have a specific categorical diagnosis, and identifying subthreshold levels of disorders. All of these advantages can help with treatment planning and monitoring treatment progress. Critics of the proposed dimensional assessments identify complexity, extensive clinician training requirements, and the lack of recording procedures as disadvantages of the approach. Furthermore, some have expressed concerns about the scale development process and whether the APA Task Force is able to develop new dimensional assessments with strong psychometric support. Dimensional and cross-cutting assessments have implications for clinical utility. Because these assessments provide a more complete description of a client’s presenting problem, they may provide more information for treatment planning and progress monitoring. A critical component of clinical utility is user acceptability. Concern has been expressed about the potential complexity and additional time burden of the dimensional assessments placed on already busy clinicians. If the proposed assessments are too complicated and time consuming for counselors to use, the assessments may be used incorrectly or not at all.

References American Psychiatric Association. (1980). Diagnostic and statistical manual of mental disorders (3rd ed.). Washington, DC: Author. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., text rev.). Washington, DC: Author.

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Jones American Psychiatric Association. (2010). Recommended changes in ‘depressive disorder not otherwise specified’ (Code 311). Arlington, VA: Author. American Psychiatric Association. (n.d.). Cross-cutting dimensional assessment in DSM-5. Retrieved from http://www.dsm5.org/ ProposedRevisions/Pages/Cross-CuttingDimensionalAssessmentinDSM-5.aspx Andrews, G., Slade, T., & Issakidis, C. (2002). Deconstructing current comorbidity: Data from the Australian National Survey of Mental Health and Well-Being. British Journal of Psychiatry, 181, 306–314. doi:10.1192/bjp.181.4.306 Brown, T. A., & Barlow, D. H. (2005). Dimensional versus categorical classification of mental disorders in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders and beyond: Comment on the special section. Journal of Abnormal Psychology, 114, 551–556. Brown, T. A., Campbell, L. A., Lehman, C. L., Grisham, G. R., & Mancill, R. B. (2001). Current and lifetime comorbidity of the DSM-IV anxiety and mood disorders in a large clinical sample. Journal of Abnormal Psychology, 110, 585–599. Cassano, G. B., Dell’Osso, L., Frank, E., Miniati, M., Fagiolini, A., Shear, K., . . . Maser, J. (1999). The bipolar spectrum: A clinical reality in search of diagnostic criteria and an assessment methodology. Journal of Affect Disorders, 54, 319–328. doi:10.1016/ S0165-0327(98)00158-X Fairburn, C., Cooper, Z., Bahn, K., O’Connor, M., Doll, H., & Palmer, R. (2007). The severity and status of eating disorder NOS: Implications for DSM-V. Behaviour Research and Therapy, 45, 1705–1715. Fauman, M. A. (2002). Study guide to the DSM-IV-TR. Washington, DC: American Psychiatric Publishing. First, M. B. (2005). Clinical utility: A prerequisite for the adoption of a dimensional approach in DSM. Journal of Abnormal Psychology, 114, 560–564. First, M. B. (2010a). Clinical utility in the revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM). Professional Psychology: Research and Practice, 41, 465–473. First, M. B. (2010b). Paradigm shifts and the development of the Diagnostic and Statistical Manual of Mental Disorders: Past experiences and future aspiration. The Canadian Journal of Psychiatry, 55, 692–700. First, M. B., Frances, A., & Pincus, H. A. (2004). DSM-IVTR guidebook. Washington, DC: American Psychiatric Publishing. First, M., Pincus, H., Levine, J., Williams, J., Ustun, B., & Peele, R. (2004). Clinical utility as a criterion for revising psychiatric diagnoses. American Journal of Psychiatry, 161, 946–954. Frances, A. (2010, May 7). Rating scales: DSM5 bites off far more than it can chew. Psychiatric Times. Available from http://www. psychiatrictimes.com/dsm-5/content/article/10168/1565517

486

Helzer, J. E., Bucholz, K. K., & Gossop, M. (2008). A dimensional option for the diagnosis of substance dependence in DSM-V. In J. E. Helzer, H. C. Kraemer, R. F. Krueger, H. U. Wittchen, P. J. Sirovatka, & D. A. Regier (Eds.), Dimensional approaches in diagnostic classification: Refining the research agenda for DSM-V (pp. 19–34). Washington, DC: American Psychiatric Association. Kessler, R. C., Nelson, C. B., McGonagle, K. A., Liu, J., Swartz, M., & Blazer, D. G. (1996). Comorbidity of DSM-III-R major depressive disorder in the general population: Results from the U.S. National Comorbidity Survey. British Journal of Psychiatry, 168(Suppl. 30), 17–30. Kraemer, H. C. (2007). DSM categories and dimensions in clinical and research contexts. International Journal of Methods in Psychiatric Research, 16(S1), S8–S15. Kraemer, H. C., Noda, A., & O’Hara, R. (2004). Categorical versus dimensional approaches to diagnosis: Methodological challenges. Journal of Psychiatric Research, 38, 17–25. Kroenke, K., & Spitzer, R. L. (2002). The PHQ-9: A new depression diagnostic and severity measure. Psychiatric Annals, 32, 1–7. Kupfer, D. J. (2005). Dimensional models for research and diagnosis: A current dilemma. Journal of Abnormal Psychology, 114, 557–559. Kupfer, D. J., First, M. B., & Regier, D. E. (2002). Introduction. In D. J. Kupfer, M. B. First, & D. E. Regier (Eds.), A research agenda for DSM-V (pp. xv–xxiii). Washington, DC: American Psychiatric Association. Magee, W. J., Eaton, W. W., Wittchen, H.-U., McGonagle, K. A., & Kessler, R. C. (1996). Agoraphobia, simple phobia, and social phobia in the National Comorbidity Survey. Archives of General Psychiatry, 53, 159–168. Millon, T. (1991). Classification in psychopathology: Rationale, alternatives, and standards. Journal of Abnormal Psychology, 100, 245–261. Mineka, S., Watson, D., & Clark, L. A. (1998). Comorbidity of anxiety and unipolar mood disorders. Annual Review of Psychology, 49, 377–412. Regier, D. (2008). Dimensional approaches to psychiatric classification. In J. E. Helzer, H. C. Kraemer, R. F. Krueger, H. U. Wittchen, P. J. Sirovatka, & D. A. Regier (Eds.), Dimensional approaches in diagnostic classification: Refining the research agenda for DSM-V (pp. xvii–xxiii). Washington, DC: American Psychiatric Association. Regier, D. A., Narrow, W. E., Kuhl, E. A., & Kupfer, D. J. (2009). The conceptual development of DSM-V. American Journal of Psychiatry, 166, 645–650. doi:10.1176/appi. ajp.2009.09020279 Simonsen, E., & Widiger, T. A. (2006). Introduction. In T. A. Widiger, E. Simonsen, P. J. Sirovatka, & D. A. Regier (Eds.), Dimensional models of personality disorders: Refining the research agenda for DSM-V (pp. xxv–xxxii). Washington, DC: American Psychiatric Association.

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Dimensional and Cross-Cutting Assessment of the DSM-5 Sokal, R. R. (1974, September 27). Classification: Purposes, principles, progress, prospects. Science, 185, 1115–1123. doi:10.1126/ science.185.4157.1115 Verheul, R. (2005). Clinical utility of dimensional models for personality pathology. Journal of Personality Disorders, 19, 283–302. Watson, D. (2005). Rethinking the mood and anxiety disorders: A quantitative hierarchical model for DSM-V. Journal of Abnormal Psychology, 114, 522–536. Widiger, T. A. (2005). A dimensional model of psychopathology. Psychopathology, 38, 211–214. Widiger, T. A., & Clark, L. A. (2000). Toward DSM-V and the classification of psychopathology. Psychological Bulletin, 126, 946–963.

Widiger, T. A., & Coker, L. A. (2003). Mental disorders as discrete clinical conditions: Dimensional versus categorical classification. In M. Hersen & S. M. Turner (Eds.), Adult psychopathology and diagnosis (pp. 3–35). Hoboken, NJ: Wiley. Widiger, T. A., & Samuel, D. B. (2005). Diagnostic categories or dimensions? A question for the Diagnostic and Statistical Manual of Mental Disorders–Fifth Edition. Journal of Abnormal Psychology, 114, 494–504. doi:10.1037/0021843X.114.4.494 Wilberg, T., Hummelen, B., Pedersen, G., & Karterud, S. (2008). A study of patients with personality disorder not otherwise specified. Comprehensive Psychiatry, 49, 460–468.

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