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Disquiet in Nosology: a Primer on an Emerging, Empirically Based Approach to Classifying Mental Illness and Implications For

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Disquiet in Nosology: a Primer on an Emerging, Empirically Based Approach to Classifying Mental Illness and Implications For CLINICAL TRAINING heterogeneous, higher-order constructs based on patterns of association. This method is hardly new: Thomas Disquiet in Nosology: APrimer on an Emerging, Moore in the 1930s analyzed the intercor- relations among 32 signs and symptoms Empirically Based Approach to Classifying related to psychosis to understand how they could be more parsimoniously Mental Illness and Implications for Training grouped into higher-order factors. Many others,notably Achenbach and colleagues Camilo J. Ruggero, Jennifer L. Callahan, Allison Dornbach-Bender, (Achenbach, 1966; Achenbach, Ivanova, & University of North Texas Rescorla, 2017), followedsuit with increas- ing sophistication and precision (Kotov, Jennifer L. Tackett, Northwestern University 2016). The most recent large-scale effort in this Roman Kotov, Stony Brook University movement toward empirically based clas- sification emerged in the spring of 2015. Forty scholarsworking in the area of quan- titative nosology started aconsortium Prevailing Mental Health rymple, 2015). Reliability is often too low (now close to 100 members) devoted to Nosologies:ACaution (Chmielewski, Clark, Bagby, &Watson, articulating an empirically based quantita- 2015; Regier et al., 2013), and evidence tive nosologyofmental illness. Their initial Paul Meehl (1986) warned more than 30 overwhelmingly suggests psychopathology proposed model—the Hierarchical Taxon- years ago of a“scientific malignancy” falls along acontinuum, with no clear omy of Psychopathology(HiTOP; Kotovet worth recalling: the tendency by some to zones of rarity (Wright et al., 2013). Finally, al., 2017)—provides amarked departure reify diagnoses, as thoughthe criteria that it is notalwaysclear from surveys how clin- from nosologysystems like DSM. operationalize adisorder in the Diagnostic ically useful clinicians find the prevailing andStatistical Manual of MentalDisorders nosology beyond its relevance for billing HiTOP: APrimer (DSM; APA, 2013) describe its essence. (First et al., 2018). 1 HiTOP’s empirically based model Diagnoses, instead, are open constructs. Despite these concerns, nosology remains awork in progress (remember Most of us, when pressed, easily acknowl- remains foundational for anyone whose Meehl’s admonitions!) and the consortium edge the difference. The core motivation work intersects with mental health (Blash- is actively working to revise the model as behind the National Institute of Mental field &Burgess, 2007). At minimum, it new evidence emerges (Krueger et al., Health’s Research Domain Criteria (Cuth- gives us alinguafranca to talk about symp- 2018), but major, replicated contours of bert &Insel, 2013) underscores this point. toms and how they present. But ideally it this nosology are already clear.The model Yet whennot pressed, too often the criteria would do so much more: it would guide is hierarchical, with homogenous signs, can slip into becoming the disorder. It ourtreatments, forecast the course of ill- would be unfair to blame DSM for this symptoms, and traits at the bottom. There ness, and create afoundation for research habit (cf. Kraemer, Kupfer, Clarke, are over 100 of these dimensions, andthey into the causes of illness (Mullins-Sweatt, Narrow, &Regier, 2012), yet its opera- consist of symptom components, such as Lengel &DeShong, 2016). For studentsin tionalization of criteria risks making us insomnia, and traits, such as submissive- training, DSM’s lexicon, and the assump- forget that articulating auseful mental ness. These are organized into higher- tions behind it, get woven into their cur- health nosologyremains ongoing. order components that are increasingly riculum and shape conceptualizations of Prevailing classification approaches broad until one reaches what is called the psychopathology (e.g., Amazon ranks have other problems. Disorders are pre- spectra level—of which there are six (i.e., DSM second in psychology reference sumed distinct, yet the predominance of Internalizing, Somatoform, Thought Dis- books,only behind the American Psycho- comorbidity raises obvious questions order, Disinhibited Externalizing, Antago- logical Association’s stylemanual). about the validity of their borders (e.g., nistic Externalizing, and Detachment). Brown, Campbell, Lehman, Grisham, & Next-GenerationApproach Above this, one can aggregate higher all the Mancill, 2001; Kessler, Chiu, Demler, & way up to ageneral factor (i.e., so-called “p- Walters, 2005; Ormeletal., 2015; Teesson, DSM’s hegemony over classification factor;” Caspi et al., 2014). Figure 1pre- Slade, &Mills, 2009). Or, categories can has overshadowed an acceleratingbody of sents portions of the model, reprinted and have markedheterogeneity,such thattwo research happening in the wings of mental revised with permission. individuals with the same diagnosis have health, largely driven by psychologists: How does this differ from the DSM? entirely different sets of symptoms (Clark, quantitative nosology. At its core, this With traditional nosology, symptoms Watson, &Reynolds, 1995; Hasler, approach creates adata-driven, empirically related to depression, generalized anxiety Drevets, Manji, &Charney, 2004; Zimmer- based classification. It starts with diverse disorder, and social phobia, to take one man, Ellison, Young, Chelminski, &Dal- arrays of highly homogenous signs and example, constitute three putatively dis- symptoms of mental health problems (e.g., tinct categories of mental illness. In con- dysphoric mood). Statistical procedures trast, with HiTOP they all fall under the like factor analyses and hierarchical rubric of an internalizing spectrum. A 1This can be debated, of course agglomerative clustering are then used to provider can focus on this higher-level (see Wakefield, 2004). organize elements into increasingly more spectrum, recognizing that all three syn- 208 the Behavior Therapist CLASSIFYING MENTAL ILLNESS dromes share elements. Or, one can cas- HiTOP May AdvanceResearch align with models like HiTOP compared to cade down the model, with, for example, andTreatment traditional nosology (Conway et al., 2019). depression and generalized anxiety symp- HiTOP also proposes potentially toms coalescingunder a“distress” subfac- HiTOP proposes to accelerate mental greater clinically utility (Ruggero et al., tor and social phobiahewing more closely health research (Conwayetal., 2019). Use 2018). Dimensions are more reliable than to a“fear” subfactor. Or one can cascade of continuous dimensions, as opposed to traditional categories (e.g., 15% increased even further down, focusing on highly categories, has well-known benefits for sta- reliability in meta-analyses; Markon, homogenous symptoms or traits, such as tistical power of research to detect effects Chmielewski, &Miller,2011) and may be suicidality. (Cohen, 1983). Compared to categorical preferred over categories by clinicians Unlike DSM, HiTOP does not delineate phenotypes, dimensionalones double the (Morey, Skodol, &Oldham,2014). More- a“one size fitsall” boundary between “ill- power to predict avariety of clinical out- over,HiTOP higher-level spectra may have ness” and “not illness,” afeature supported comes (Kotov et al., 2019) and produce increased prognostic power, for example predicting suicide attempts, future psy- by years of taxometric research (Haslam, more “hits” in genetic research(Otowa et chopathology and other clinical outcomes Holland &Kuppens, 2012). Rather,clinical al., 2016),for example. more than disorder-specific variation alone decisions areguided by rangesofseverity But the hierarchical structureinand of (Eaton et al., 2013; Kim &Eaton, 2015). on each dimension of the model. Until itself provides anovel frameworkfor pur- HiTOP may also better align with treat- work validates these in different popula- suing pathophysiologies. Mechanisms, or ment planning. Early evidence suggests outcomes, may operate at different levels of tions, theycan remain statistical (e.g., 2SD clinician-prescribing practices track more below the mean), such as with intelligence this mental illness hierarchy, from broad closely to aHiTOP-based model compared testing, or can be tailored to the needs and and diffuse effectstomorenarrow and spe- to aDSM one (Waszczuk et al., 2017). Sim- resources available within agiven setting or cific ones.HiTOP’s hierarchy provides one ilarly, emerging trandiagnostic approaches population.Kotov et al. (2017) reviews evi- map to different levels that may be relevant, to the treatment of mental health (e.g., dence supporting the model, while Rug- and at minimum new phenotypic targets Barlow et al., 2017) align well with HiTOP’s gero et al. (2018) provides adescription of on which to test proposed mechanisms. conceptualization of upper-level spectra its integration into clinical care. Already, work in genetics, neurobiology, that share featuresand potential etiologies. and psychosocial contexts point to how Finally,HiTOP providesflexibility to adapt recent findings in these fields may better clinical ranges based on their purpose, Fig. 1.HiTOP model (reformatted and revised with permission from Kotov et al., 2017). Note.Not all of the model components, traits and related disorders are presented. September • 2019 209 RUGGERO ET AL. ratherthan requiring one-size-fits-all cut- treatment planning instruction, the HiTOP suffer shortcomings, including reification, offs common to DSM, removing from model was briefly reviewed, again drawing less than desired reliability, and questions nosology their reification that are not some content from the expert slides,
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