Utility of the Hierarchical Taxonomy of Psychopathology (HiTOP) System in Diverse, Underrepresented, and Epistemically Excluded Populations

The standard of diagnosing and categorizing mental disorders has long been based on a categorical approach, codified within the Diagnostic and Statistical Manual of Mental Disorders in the USA (e.g., DSM-5-TR; American Psychiatric Association, 2022) and the International Classification of Diseases in much of the world (e.g., ICD-11; World Health Organization, 2019). But this categorical approach has been criticized due to limited reliability, validity, and clinical utility (e.g., Conway et al., 2019; Widiger et al., 2018); the Hierarchical Taxonomy of Psychopathology (HiTOP) was introduced in 2017 as a potential solution to some of the DSM’s limitations (Kotov et al., 2017, 2022; Conway et al., 2021b; Ringwald et al., 2023). Briefly, the HiTOP model is a quantitatively-derived reorganization of the signs, symptoms, and traits reflective of mental illness based on their patterns of covariance and comorbidity. The result is a phenotypic hierarchy that conceptualizes the structure of psychopathology along increasingly broad/more aggregated dimensions based on the patterns of co-occurrences of those signs, symptoms, and traits (Caspi et al., 2014; Kotov et al., 2017, 2022). For readers new to the HiTOP model, we recommend consultation of The Clinical Psychologist’s Winter 2021 issue where Conway and colleagues (2021a) offer an introduction to the model.

Of particular relevance to this readership is literature related to clinical utility and clinicians’ perceptions of the HiTOP model. Research reveals a marked lack of participation in standard diagnostic processes in the mental health field, with providers largely using diagnosis as a means of billing insurance companies for services, and rarely offering diagnostic feedback to clients or applying a formal diagnostic classification system to inform treatment decisions (Cassels, 2017; Ruggero et al., 2019). One survey found that in a sample of over 6,000 USA healthcare workers, 55% denied incorporating the diagnostic manual into their practice at all, including 40% of surveyed psychologists (Cassels, 2017). Among mental health providers, there is evidence of extensive dissatisfaction with the DSM, and preliminary research suggests that clinicians prefer a dimensional approach—congruent with the HiTOP model—over the DSM and its categorical approach (Balling et al., 2023; Bornstein & Natoli, 2019; Hansen et al., 2019; Samuel & Widiger, 2011). For instance, in a recent study by Balling and colleagues (2023), a sample of 143 actively practicing clinicians (including 77.6% self-identified clinical psychologists) rated both the DSM and HiTOP approaches on seven indices of clinical utility. Among these clinicians, the dimensional HiTOP approach was rated more favorably when compared with the traditional, categorical DSM approach along the domains of 1) forming a treatment plan, 2) communicating with clients, 3) comprehensively describing psychopathology, 4) describing global functioning, and 5) ease of application. There was no  reference between HiTOP and the DSM for communicating with other mental health providers, and the DSM was not rated more favorable than HiTOP for any clinical utility outcome. These results replicated even in a subsample of clinicians who had never heard of the HiTOP model prior to the study. As the work of the HiTOP Consortium continues to expand and improve various facets of the model and its applicability for myriad purposes (e.g., clinical utility, improved measurement, etc.), another area of particular importance for the HiTOP model—and indeed any psychiatric classification system—is how the system aligns with values related to diversity, equity, inclusion, and justice (DEIJ). Our goal for this article is to offer a brief summary of the state of the literature relating the HiTOP framework to diverse, underrepresented, and epistemically excluded populations (Settles et al., 2020; i.e., those populations who are typically excluded from mainstream quantitative psychology foci based on race, ethnicity, nation of origin, immigration status, sexual orientation, gender identity, sex assigned at birth, age, socio-economic status, disability, and neurocognitive status). We briefly discuss some of the advantages of the model specifically with respect to diverse and underrepresented populations. We also discuss some limitations of the model and avenues for future improvement.

Advantages of HiTOP for Underrepresented Populations

Early Focus on Generalizability

In the development of the HiTOP model, particular focus was placed on examining data from multiple countries to estimate the generalizability of the patterns of covariation of various psychiatric disorders (i.e., the patterns that underlie the dimensions espoused within the HiTOP model). From this, there is strong support for cross-national generalizability of the internalizing and externalizing—and to a lesser extent the thought disorder—spectra, as well as some of the syndromes within these spectra (e.g., Caspi et al., 2014; Kessler et al., 2011; Krueger et al., 2003; de Jonge et al., 2018; Slade & Watson, 2006). However, such epidemiological data typically overrepresent dominant populations. Even large, nationally representative samples can be unsuitable for examinations of generalizability among relatively smaller sub-groups. For example, among psychiatric epidemiology samples within the US, the sample sizes of sexual and gender minority individuals are frequently so small that they preclude appropriate focus on this underrepresented populations. Thus, a more concerted effort must be placed onto examining how these purportedly universal dimensions operate among diverse populations.

Measurement invariance research is an additional quantitative method for arbitrating generalizability of the HiTOP model; this statistical method aims to assess whether a given measure assesses the same construct in the same way across different groupings. For example, measurement invariance could assess whether a self-report scale of psychiatric symptoms (e.g., the PHQ-9) possesses the same psychometric properties across different sociodemographic groupings (e.g., racial/ethnic identity). If the scale indeed measures the intended construct regardless of group membership, it would be invariant of that grouping and allow confidence that any group mean differences observed were to due to differences in the underlying construct and not, for instance, due to differences in psychometric properties of the measure. To date, measurement invariance research of the HiTOP model has been limited to US samples. But, within these data the internalizing and externalizing—and to a lesser extent thought disorder—dimensions have demonstrated invariance across such grouping as race/ethnicity, sexual orientation, age, and sex assigned at birth (Afzali et al., 2018; Eaton et al., 2012, 2013, 2021; He & Li, 2021). That is, group-based differences on these dimensions are not due to variable psychometric properties associated with group membership, but due to relative elevations in the dimensions themselves. This type of approach has previously highlighted how differences in endorsement of even a single item between sexual and gender minority and cisgender heterosexual individuals creates illusory mean-level differences on dimensions of interest (Asadi et al., 2024). Together, this empirical evidence suggests broad generalizability of some of the major dimensions within the HiTOP model within US samples, meaning that there is a level of trust that these dimensions are equivalent among underrepresented and marginalized populations, who are not typically the focal groups within mainstream psychopathology research.

Incorporating Social Determinants of Health

While generalizability research suggests that the dimensions within the HiTOP model apply widespread across diverse  populations, another advantage of the HiTOP approach is its congruence with determinants of health that are important for understanding psychiatric disparities among diverse and marginalized groups. Crucially, minority stress processes impact the signs, symptoms, and traits of mental disorders (Brooks, 1981; de Lange et al., 2022; Frost & Meyer, 2023; Hoy-Ellis, 2021; Sattler & Zeyen, 2021). That is, the stressful experiences that individuals who hold minoritized identities face predict psychiatric malaise of various forms. However, this literature becomes unwieldy for the researcher and clinician. Because of the myriad categorical disorders, the accumulated research that takes a disorder-specific approach results in a piecemeal narrative of how different minority stressors are related to each of hundreds of categorical psychiatric disorders. Rather than approaching an understanding of some of the fundamental determinants of health for marginalized populations from such a fragmented approach, a dimensional approach more congruent with the HiTOP model streamlines understanding of how social and contextual factors differentially impact minoritized populations. Minority stress processes—like racial discrimination (Rodriguez-Seijas et al., 2015) and rejection sensitivity (Cohen et al., 2016; Rodriguez-Seijas et al., 2019b)—affect myriad psychiatric domains. The HiTOP approach, therefore, helps to streamline these disparate, disorder-specific literatures into a coherent narrative (Eaton et al., 2021). Further, this appears congruent with advances in transdiagnostic intervention approaches both generally (Barlow et al., 2017) and specific to marginalized populations (Pachankis et al., 2019; Rodriguez-Seijas et al., 2019b). However, while we believe that the HiTOP approach holds promise for better conceptualizing the widespread deleterious effects of minority stress processes, it is notable that the empirical literature on this topic to date has remained relatively limited (Rodriguez-Seijas et al., 2023). Indeed, the number of formal studies examining these social determinants of health and various HiTOP domains can be counted on one hand at this time.

Potential for Alleviating Diagnostic Bias

Clinical psychologists are generally aware of diagnostic bias associated with traditional diagnostic categories. Bias can manifest as a difference in the diagnostic labels applied to individuals based on their group membership rather than experienced psychopathology per se (e.g., Garb, 2021; Masuda et al., 2020). As examples, previous research demonstrates gender bias in the diagnostic criteria of various personality disorders (Jane et al., 2007; Morey, 2019), gender and ethnoracial bias related to eating disorder diagnoses among men or Black individuals (Gordon et al., 2006; Schoen et al., 2018), and ethnoracial disparities in diagnosing psychotic disorders (see literature review: Schwartz & Blankenship, 2014). The HiTOP approach might help alleviate diagnostic bias. Here we detail an example. There is evidence of racial diagnostic bias when accounting for psychotic and mood disorder symptoms through a DSM lens; Black individuals are likelier to receive psychotic disorderlabels with poorer prognosis (e.g., schizophrenia) compared with their White counterparts presenting with the same symptoms—who are likelier to be diagnosed with a mood disorder (e.g., major depressive disorders with psychotic features; Akinhanmi et al., 2018; Gara et al., 2019). By using a dimensional approach, congruent with the HiTOP model, however, the opportunity for diagnostic bias might be reduced. Indeed, data demonstrates that clinician biases are most evident in the final categorical diagnostic decision. Ratings of polythetic diagnostic criteria and dimensions of psychopathology appear less susceptible to clinician diagnostic bias related to a patient’s possession of a marginalized identity (Morey & Benson, 2016; Morey & Ochoa, 1989; Rodriguez-Seijas et al., in press). By conceptualizing the symptoms of Black and White individuals through (theoretically) identical latent constructs, and by adopting a dimensional approach that covers a few psychopathology dimensions regardless of an individuals’ presenting concern—rather than being dependent on the clinician to assess all of the hundreds of specific diagnostic categories or omit any others—it might be possible to better cover psychopathology across individuals regardless of sociodemographic grouping, helping to alleviate clinician bias.

Indeed, this is congruent with findings that categorical diagnostic disparities can be explained by a shared latent construct rather than varied, prolific disparities across categorical diagnoses (e.g., Eaton et al., 2021; Rodriguez-Seijas et al., 2019a). With a HiTOP framework, clinicians (and researchers) can consider bias at different levels of abstraction and across levels of the hierarchy, rather than collapsing this rich information into a single binary diagnosis. If there is evidence of reduced bias at certain levels, such as for the signs, symptoms, and traits of psychiatric illness, the validity of diagnostic determinations at those levels is more assured. Alternatively, if we translate hypotheses about the HiTOP model’s statistical generalizability to this question of diagnostic bias, it is possible that higher levels of the hierarchy may show the least bias while lower levels exhibit the most (i.e., Cicero & Ruggero, 2020; He & Li, 2021). Again, however, these claims that the HiTOP approach can alleviate bias are based on relatively limited data but a strong theoretical rationale. More empirical research specifically devoted to this topic is warranted.

Future Directions for HiTOP with respect to Underrepresented Populations

The HiTOP model does not address all potential criticisms of the DSM (or any classification system) in relation to DEIJ issues. For example, there lacks an examination of cause or context for a client’s psychiatric symptoms; the HiTOP consortium has aimed to remain agnostic regarding the etiology of psychopathology. A common sentiment among clinicians is the desire for a diagnostic approach that accounts for dynamic processes in treatment and unifies the objective outsider (“etic”) with the subjective insider (“emic”; Verona, 2021). Clinicians desire causes and context, but at present, no diagnostic model provides this—nor necessarily can. The HiTOP model also does not distinguish between cultural differences in the associated distress or impairment of symptoms, actual differences in psychiatric symptoms, nor biases in assessment methods. Further, the HiTOP model offers only a “deficit-focused” clinical assessment. The diagnostic information collected via HiTOP approach (and most gold-standard DSM assessments) lacks measurement of positive psychological constructs or psychological assets that might be crucial for case formulation and treatment planning. Given that marginalized or underrepresented groups are often over-pathologized (e.g., Eaton et al. 2021, Schwartz & Blankenship, 2014), it is even more important to acknowledge psychological strengths. Further, it is possible that behaviors considered forms of psychopathology might represent population-specific ways of adaptively responding to psychosocial stressors. These sorts of considerations reflect a broader conversation about the limitations of assessment and diagnosis in general. It would behoove the HiTOP consortium, as well as the developers, investors, or disseminators of any diagnostic system, to dedicate time to exploring how such processes and considerations might be integrated. Nonetheless, a major advantage of the HiTOP approach involves its ability to actively accommodate new and emerging research evidence. Thus, it is possible to strategically study many of these specific questions and concerns.

At present, the HiTOP consortium has generated a preliminary self-report measure meant to assess the various dimensions of the HiTOP model, though it awaits experimental validation (Simms et al., 2022). At this time, there are plans to increasingly collect data from members of minoritized groups to inform future refinement of the measure and development of practical tools such as group-based norms. However, as highlighted by Verona (2021), assessment items that are necessary and informative for persons from marginalized groups may have already been eliminated during earlier phases of the measure development process. Approaching marginalized groups as an extension or focal group after model development is not exclusive to HiTOP but is—unfortunately—reflective of the prototypical approach to psychopathology theory, research, and treatment within dominant models (Settles et al., 2020; Rodriguez-Seijas et al., 2024). It is crucial to note that, like any diagnostic system, simply applying the HiTOP model to diverse populations is insufficient. Increased attention to the social, structural, and other determinants of health that shape the structure of “psychopathology” is crucial, as in any corner of the field. Future research within the consortium is tasked with assessing whether associations with ancillary components of the model actually vary across different populations. Further, integrating lived experience in assessment and diagnostic procedures is also critical; it would benefit any diagnostic approach to integrate members of all communities in the development process. Qualitative methods are particularly useful for such an objective. Consideration of personal expertise is invaluable for understanding context of “psychopathology,” as well as how diagnostic dimensions map onto social and structural forces. These will elevate and accelerate efforts to reduce bias and improve generalizability in diagnostic models. Further, quests for establishing generalizability must be paired with consideration that a universal model of psychopathology might not exist. This leads to the possibility of making appropriate and necessary adjustments to the HiTOP model to reflect the structure of psychopathology as it varies across groups. A reasonable question among the consortium is if there is only one HiTOP hierarchy, or many?

While the representation of marginalized populations remains somewhat limited, two characteristics are noteworthy of the HiTOP approach to psychopathology. Firstly, the consortium houses a workgroup specifically devoted to diversity, equity, and inclusion-related issues. As members of this DEI workgroup, we are collectively focused on increasing the empirical literature pertaining to many of the topics we discussed above. Secondly, the HiTOP model has been designed to be an active model that is amenable to change as novel evidence becomes accumulated (Forbes et al., 2024). Thus, we believe that the model inherently permits a level of plurality that might not be as easily accessible in traditional, categorical classification systems. So, it is wholly possible that signs, symptoms, and dimensions within the model might differ based on group membership or in their association with various social determinants of health. In our opinions, this level of plurality is entirely possible and can be accommodated within the model.

Conclusion

The generalizability of the HiTOP model remains in question for many groups. Available data offers some understanding of the generalizability of HiTOP based on race, ethnicity, nation of origin, age, sexual orientation, and gender identity. However, factors related to socio-economic status, disability, neurodiversity, and immigration status have received little to no attention in the literature. Further, the nuances within a given group are often lost in the available literature, such as erasing certain identities (e.g., intersex) or collapsing other marginalized groups together despite being distinct (e.g., treating trans, nonbinary, two-spirit, and genderqueer people as a homogenous group). Finally, focus remains on identity groupings themselves, rather than on the social and contextual factors that are responsible for these groupings in the first place (e.g., racism is the cause of race, and not the converse; Williams, 2019). At present, mainstream psychopathology literature incorporates little of this very complex nuance. Nonetheless, we believe that the HiTOP model shows promise for use among marginalized and systemically excluded clients, and more progress in necessary. The present article represents a high-level summary of some ideas presented by Rodriguez-Seijas and colleagues in our 2023 paper, “Diversity and the Hierarchical Taxonomy of Psychopathology (HiTOP).” We direct the reader to this publication for more detailed consideration of the application of the HiTOP model in diverse populations. For the clinician interested in incorporating HiTOP into their clinical practice, we recommend visiting the HiTOP Clinical Network page at https://www.hitop-system.org/the-clinical-network (HiTOP Consortium, 2024) where members of the HiTOP consortium have put together a multifaceted training program on the use of the HiTOP model for clinical purposes, including a module specific to using the model when considering diverse and marginalized populations. Audiences with a more clinical focus might also peruse the enlightening and ever-evolving implementation literature, including articles such as “Integrating the Hierarchical Taxonomy of Psychopathology (HiTOP) into Clinical Practice” (Ruggero et al., 2019), “Integrating Psychotherapy with the Hierarchical Taxonomy of Psychopathology (HiTOP)” (Hopwood et al., 2020), and, from the Clinical Psychologist, “The Hierarchical Taxonomy of Psychopathology (HiTOP): A Brief Introduction and Resource Guide for Clinical Psychologists” (Conway et al., 2021a).

by Caroline E. Balling, Jai Carmichael, Keanan J. Joyner, Holly F. Levin-Aspenson, James J. Li, & Craig Rodriguez-Seijas

References

Afzali, M. H., Sunderland, M., Carragher, N., & Conrod, P. (2017). The Structure of Psychopathology in Early Adolescence: Study of a Canadian Sample. The Canadian Journal of Psychiatry, 63(4), 223–230.

Akinhanmi, M. O., Biernacka, J. M., Strakowski, S. M., McElroy, S. L., Balls Berry, J. E., Merikangas, K. R., Assari, S., McInnis, M. G., Schulze, T. G., LeBoyer, M., Tamminga, C., Patten, C., & Frye, M. A. (2018). Racial disparities in bipolar disorder treatment and research: a call to action. Bipolar Disorders, 20, 506–514.

American Psychiatric Association (APA). (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev.). Washington, DC.

Asadi, S., Cunningham, T. J., Morgan, T. A., Zimmerman, M., & Rodriguez-Seijas, C. (2024). Examining measurement invariance in the Personality Inventory for DSM-5 Brief Form across sexual and gender minority status. Assessment, 31(3), 678-697.

Balling, C. E., South, S. C., Lynam, D. R., & Samuel, D. B. (2023). Clinician Perception of the Clinical Utility of the Hierarchical Taxonomy of Psychopathology (HiTOP) System. Clinical Psychological Science, 11, 1108-1121.

Barlow, D. H., Farchione, T. J., Bullis, J. R., Gallagher, M. W., Murray-Latin, H., Sauer-Zavala, S., Bentley, K. H., Thompson-Hollands, J., Conklin, L. R., Boswell, J. F., Ametaj, A., Carl, J. R., Boettcher, H. T., & Cassiello-Robbins, C. (2017). The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders Compared With Diagnosis-Specific Protocols for Anxiety Disorders: A Randomized Clinical Trial. JAMA Psychiatry, 74, 875–884.

Bornstein, R. F., & Natoli, A. P. (2019). Clinical utility of categorical and dimensional perspectives on personality pathology: A meta-analytic review. Personality Disorders: Theory, Research, and Treatment, 10, 479–490.

Brooks, V. R. (1981). Minority Stress and Lesbian Women. Lexington, MA: Lexington Books.

Cassels, C. (2017, August 16). One third of psychiatrists not using DSM-5. Medscape. Retrieved October 18, 2021, from https://www.medscape.com/viewarticle/830099.

Caspi, A., Houts, R. M., Belsky, D. W., Goldman-Mellor, S. J., Harrington, H., Israel, S., Meier, M. H., Ramrakha, S., Shalev, I., Poulton, R., & Moffitt, T. E. (2014). The p factor: One general psychopathology factor in the structure of psychiatric disorders?. Clinical Psychological Science, 2, 119–137.

Cicero, D., & Ruggero, C. (2020). Commentary– Opening a can of worms: The importance of testing the measurement invariance of hierarchical models of psychopathology – a commentary on He and Li (2020). Journal of Child Psychology and Psychiatry, 62, 299-302.

Widiger, T. A., & Simonsen, E. (2005). Alternative dimensional models of personality disorder: Finding a common ground. Journal of Personality Disorders, 19, 110–130.

Cohen, J. M., Feinstein, B. A., Rodriguez-Seijas, C., Taylor, C. B., & Newman, M. G. (2016). Rejection Sensitivity as a Transdiagnostic Risk Factor for Internalizing Psychopathology Among Gay and Bisexual Men. Psychology of Sexual Orientation and Gender Diversity, 3, 259–264.

Conway, C., Anderson, G., Larrazabal, M., Martin Lopez, M., & Williams, A. (2021a). The Hierarchical Taxonomy of Psychopathology (HiTOP): A Brief Introduction and Resource Guide for Clinical Psychologists. The Clinical Psychologist, 74, 5–10.

Conway, C. C., Forbes, M. K., Forbush, K. T., Fried, E. I., Hallquist, M. N., Kotov, R., … Eaton, N. R. (2019). A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research. Perspectives on Psychological Science, 14, 419–436.

Conway, C. C., Krueger, R. F., & HiTOP Consortium Executive Board. (2021b). Rethinking the Diagnosis of Mental Disorders: Data-Driven Psychological Dimensions, Not Categories, as a Framework for Mental-Health Research, Treatment, and Training. Current Directions in Psychological Science, 30, 151-158.

de Jonge, P., Wardenaar, K. J., Lim, C. C. W., Aguilar-Gaxiola, S., Alonso, J., Andrade, L. H., Bunting, B., Chatterji, S., Ciutan, M., Gureje, O., Karam, E. G., Lee, S., Medina-Mora, M. E., Moskalewicz, J., Navarro-Mateu, F., Pennell, B. E., Piazza, M., Posada-Villa, J., Torres, Y., Kessler, R. C., … Scott, K. (2018). The cross- national structure of mental disorders: results from the World Mental Health Surveys. Psychological Medicine, 48, 2073–2084.

de Lange, J., Baams, L., van Bergen, D. D., Bos, H. M. W., & Bosker, R. J. (2022). Minority stress and suicidal ideation and suicide attempts among LGBT adolescents and young adults: A meta-analysis. LGBT Health, 9, 222–237.

Forbes, M. K., Ringwald, W. R., Allen, T., Cicero, D. C., Clark, L. A., DeYoung, C. G., Eaton, N., Kotov, R., Krueger, R. F., Latzman, R. D., Martin, E. A., Naragon- Gainey, K., Ruggero, C. J., Waldman, I. D., Brandes, C., Fried, E. I., Goghari, V. M., Hankin, B., Sperry, S., . . .Wright, A. G. C. (2024). Principles and procedures for revising the hierarchical taxonomy of psychopathology. Journal of Psychopathology and Clinical Science, 133(1), 4–19.

Eaton, N. R., Keyes, K. M., Krueger, R. F., Balsis, S., Skodol, A. E., Markon, K. E., Grant, B. F., & Hasin, D. S. (2012). An invariant dimensional liability model of gender differences in mental disorder prevalence: evidence from a national sample. Journal of Abnormal Psychology, 121, 282–288.

Eaton, N. R., Keyes, K. M., Krueger, R. F., Noordhof, A., Skodol, A. E., Markon, K. E., Grant, B. F., & Hasin, D. S. (2013). Ethnicity and psychiatric comorbidity in a national sample: evidence for latent comorbidity factor invariance and connections with disorder prevalence. Social Psychiatry and Psychiatric Epidemiology, 48, 701–710.

Eaton, N. R., Rodriguez-Seijas, C., & Pachankis, J. E. (2021). Transdiagnostic Approaches to Sexual- and Gender-Minority Mental Health. Current Directions in Psychological Science, 30, 510-518.

Frost, D. M., & Meyer, I. H. (2023). Minority stress theory: Application, critique, and continued relevance. Current Opinion in Psychology, 51, 101579.

Gara, M. A., Minsky, S., Silverstein, S. M., Miskimen, T., & Strakowski, S. M. (2019). A Naturalistic Study of Racial Disparities in Diagnoses at an Outpatient Behavioral Health Clinic. Psychiatric Services, 70, 130–134.

Garb, H. N. (2021). Race bias and gender bias in the diagnosis of psychological disorders. Clinical Psychology Review, 90, 102087.

Gordon, K. H., Brattole, M. M., Wingate, L. R., & Joiner, T. E. (2006). The impact of client race on clinician detection of eating disorders. Behavior Therapy, 37, 319–325.

Hansen, S. J., Christensen, S., Kongerslev, M. T., First, M. B., Widiger, T. A., Simonsen, E., & Bach, B. (2019). Mental health professionals’ perceived clinical utility of the ICD-10 vs. ICD-11 classification of personality disorders. Personality and Mental Health, 13, 84–95.

He, Q., & Li, J. J. (2021). Factorial invariance in hierarchical factor models of mental disorders in African American and European American youths. Journal of Child Psychology and Psychiatry, 62, 289-298.

HiTOP Consortium. (2024). HiTOP Clinical Network. Retrieved January 1, 2024, from https://www.hitop-system.org/the-clinical-network

Hopwood, C. J., Bagby, R. M., Gralnick, T., Ro, E., Ruggero, C., Mullins-Sweatt, S., Kotov, R., Bach, B., Cicero, D. C., Krueger, R. F., Patrick, C. J., Chmielewski, M., DeYoung, C. G., Docherty, A. R., Eaton, N. R., Forbush, K. T., Ivanova, M. Y., Latzman, R. D., Pincus, A. L., … Zimmermann, J. (2020). Journal of Psychotherapy Integration, 30, 477–497.

Hoy-Ellis, C. P. (2023). Minority Stress and Mental Health: A Review of the Literature. Journal of Homosexuality, 70, 806–830.

Jane, J. S., Oltmanns, T. F., South, S. C., & Turkheimer, E. (2007). Gender bias in diagnostic criteria for personality disorders: an item response theory analysis. Journal of Abnormal Psychology, 116, 166–175.

Kessler, R. C., Ormel, J., Petukhova, M., McLaughlin, K. A., Green, J. G., Russo, L. J., Stein, D. J., Zaslavsky, A. M., Aguilar-Gaxiola, S., Alonso, J., Andrade, L., Benjet, C., de Girolamo, G., de Graaf, R., Demyttenaere, K., Fayyad, J., Haro, J. M., Hu, C.y, Karam, A., Lee, S., … Ustün, T. B. (2011). Development of lifetime comorbidity in the World Health Organization world mental health surveys. Archives of General Psychiatry, 68, 90–100.

Kotov, R., Krueger, R., Watson, D., Achenbach, T., Althoff, R., Bagby, M., … Zimmerman, M. L. (2017). The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies. Journal of Abnormal Psychology, 126, 454–477.

Kotov, R., Cicero, D. C., Conway, C. C., DeYoung, C. G., Dombrovski, A., Eaton, N. R., First, M. B., Forbes, M. K., Hyman, S. E., Jonas, K. G., Krueger, R. F., Latzman, R. D., Li, J. J., Nelson, B. D., Regier, D. A., Rodriguez-Seijas, C., Ruggero, C. J., Simms, L. J., Skodol, A. E., Waldman, I. D., … Wright, A. G. C. (2022). The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research. Psychological Medicine, 52, 1666–1678.

Krueger, R. F., Chentsova-Dutton, Y. E., Markon, K. E., Goldberg, D., & Ormel, J. (2003). A cross-cultural study of the structure of comorbidity among common psychopathological syndromes in the general health care setting. Journal of Abnormal Psychology, 112, 437–447.

Masuda, A., Qinaʻau, J., Juberg, M., Martin, T. (2020). Bias in the Diagnostic and Statistical Manual 5 and Psychopathology. In: Benuto, L., Duckworth, M., Masuda, A., O’Donohue, W. (eds) Prejudice, Stigma,Privilege, and Oppression. Springer, Cham.

Morey, L. C. (2019). Interdiagnostician Reliability of the DSM-5 Section II and Section III Alternative Model Criteria for Borderline Personality Disorder. Journal of Personality Disorders, 1–33.

Morey, L. C., & Benson, K. T. (2016). An investigation of adherence to diagnostic criteria, revisited: Clinical diagnosis of the DSM-IV/DSM-5 Section II personality disorders. Journal of Personality Disorders, 30(1), 130-144.

Morey, L. C., & Ochoa, E. S. (1989). An investigation of adherence to diagnostic criteria: Clinical diagnosis of the DSM-III personality disorders. Journal of Personality Disorders, 3(3), 180-192.

Pachankis, J. E., McConocha, E. M., Reynolds, J. S., Winston, R., Adeyinka, O., Harkness, A., Burton, C. L., Behari, K., Sullivan, T. J., Eldahan, A. I., Esserman, D. A., Hatzenbuehler, M. L., & Safren, S. A. (2019). Project ESTEEM protocol: A randomized controlled trial of an LGBTQ-affirmative treatment for young adult sexual minority men’s mental and sexual health. BMC Public Health, 19, 1086.

Schoen, E., Brock, R., & Hannon, J. (2018). Gender bias, other specified and unspecified feeding and eating disorders, and college students: a vignette study. Eating Disorders, 27, 291–304.

Slade, T., & Watson, D. (2006). The structure of common DSM-IV and ICD-10 mental disorders in the Australian general population. Psychological Medicine, 36, 1593–1600.

Ringwald, W. R., Forbes, M. K., & Wright, A. G. (2023). Meta-analysis of structural evidence for the Hierarchical Taxonomy of Psychopathology (HiTOP) model. Psychological Medicine, 53, 533-546.

Rodriguez-Seijas, C., Burton, C. L., & Pachankis, J. E. (2019b). Transdiagnostic Approaches to Improve Sexual Minority Individuals’ Co-occurring Mental, Behavioral, and Sexual Health. In J. E. Pachankis & S. A. Safren (Eds.), Handbook of Evidence-Based Mental Health Practice with Sexual and Gender Minorities (pp. 457–476). Oxford University Press.

Rodriguez-Seijas, C., Eaton, N. R., & Pachankis, J. E. (2019a). Prevalence of psychiatric disorders at the intersection of race and sexual orientation: Results from the National Epidemiologic Survey of Alcohol and Related Conditions-III. Journal of Consulting and Clinical Psychology, 87, 321-331.

Rodriguez-Seijas, C., Li, J. J., Balling, C., Brandes, C., Bernat, E., Boness, C. L., Forbes, M. K., Forbush, K. T., Joyner, K. J.,Krueger, R. F., Levin-Aspenson, H. F., Michelini, G., Ro, E., Rutter, L., Stanton, K., Tackett, J. L., Waszczuk, M., & Eaton, N. R. (2023). Diversity and the Hierarchical Taxonomy of Psychopathology (HiTOP). Nature Reviews Psychology, 1-13.

Rodriguez-Seijas, C., McClendon, J., Wendt, D. C., Novacek, D. M., Ebalu, T., Hallion, L. S., Hassan, N. Y., Huson, K., Spielmans, G. I., Folk, J. B., Khazem, L. R., Neblett, E. W., Cunningham, T. J., Hampton-Anderson, J., Steinman, S. A., Hamilton, J. L., & Mekawi, Y. (2024). The Next Generation of Clinical-Psychological Science: Moving Toward Anti-Racism. Clinical Psychological Science, 12, 526-546.

Rodriguez-Seijas, C., Stohl, M., Hasin, D. S., & Eaton, N. R. (2015). Transdiagnostic Factors and Mediation of the Relationship Between Perceived Racial Discrimination and Mental Disorders. JAMA Psychiatry, 72, 706.

Rodriguez-Seijas, C., Warren, M., Vupputuri, P., & Hawthorne, S. (accepted for publication). Bias in the diagnosis of borderline personality disorder among sexual and gender minority persons: Results from a vignette-based experiment. Clinical Psychological Science. Postprint doi: https://doi.org/10.31234/osf.io/7z3xb

Ruggero, C. J., Kotov, R., Hopwood, C. J., First, M., Clark, L. A., Skodol, A. E., Mullins-Sweatt, S. N., Patrick, C. J., Bach, B., Cicero, D. C., Docherty, A., Simms, L. J., Bagby, R. M., Krueger, R. F., Callahan, J. L., Chmielewski, M., Conway, C. C., De Clercq, B., Dornbach-Bender, A., Eaton, N. R., … Zimmermann, J. (2019). Integrating the Hierarchical Taxonomy of Psychopathology (HiTOP) into clinical practice. Journal of Consulting and Clinical Psychology, 87, 1069–1084.

Samuel, D. B., & Widiger, T. A. (2011). Clinicians’ use of personality disorder models within a particular treatment setting: A longitudinal comparison of temporal consistency and clinical utility. Personality and Mental Health, 5, 12–28.

Sattler, F. A., & Zeyen, J. (2021). Intersecting identities, minority stress, and mental health problems in different sexual and ethnic groups. Stigma and Health, 6, 457–466.

Schwartz, R. C., & Blankenship, D. M. (2014). Racial disparities in psychotic disorder diagnosis: A review of empirical literature. World Journal of Psychiatry, 4, 133–140.

Settles, I. H., Warner, L. R., Buchanan, N. T., & Jones, M. K. (2020). Understanding psychology’s resistance to intersectionality theory using a framework of epistemic exclusion and invisibility. Journal of Social Issues, 76, 796–813.

Simms, L. J., Wright, A. G. C., Cicero, D., Kotov, R., Mullins-Sweatt, S. N., Sellbom, M., Watson, D., Widiger, T. A., & Zimmermann, J. (2022). Development of Measures for the Hierarchical Taxonomy of Psychopathology (HiTOP): A Collaborative Scale Development Project. Assessment, 29(1), 3–16.

Stanton, K., Khoo, S., McDonnell, C. G., Villalongo Andino, M., Sturgeon, T., & Aasen, L. (2023). An Initial Investigation of the Joint Classification of Hypomania- and Neurodevelopmental Disorder-Relevant Dimensions Within the Hierarchical Taxonomy of Psychopathology. Assessment, 30, 414-432.

Verona, E. (2022). Assessment of HiTOP Constructs Across the Population: A Commentary on the HiTOPMeasure Development Project. Assessment, 29, 88-92.