The Future DSM committee wants to rebuild psychiatric diagnosis. But reorganizing how we describe psychopathology won’t get us closer to understanding the mechanisms underneath it.
Earlier this year, the American Journal of Psychiatry published what is essentially a strategic roadmap for the next phase of psychiatric classification. Led by María Oquendo, the Future DSM Strategic Committee outlines a series of ambitious goals: greater dimensionality in diagnosis, stronger integration with biological research, more attention to cultural context, and a shift toward continuously updated revisions rather than once-per-generation overhauls. The committee even proposes renaming the DSM from the Diagnostic and Statistical Manual to the Diagnostic and Scientific Manual (Oquendo et al., 2026), signaling an aspiration to align the system more explicitly with contemporary scientific knowledge.
In many ways, this vision reflects an important and overdue shift. The committee explicitly acknowledges several long-standing limitations of the DSM framework: that diagnostic categories do not map cleanly onto natural boundaries, that comorbidity is the rule rather than the exception, and that many psychiatric conditions are better understood as dimensions of functioning rather than discrete disease entities. These are points that researchers across multiple traditions have been making for decades.
Yet the roadmap also highlights a deeper issue that remains largely unresolved. Much of the proposed reform focuses on improving the structure of psychiatric description—that is, building more accurate ways of organizing and characterizing patterns of symptoms. What receives less attention is the equally important challenge of understanding the processes that generate those patterns in the first place.
Improving the map is valuable. But a map, no matter how well designed, is not the territory.
Improving the structure of psychopathology
One of the clearest strengths of the committee’s proposal is its recognition that categorical diagnosis has fundamental limitations. Since DSM-III, psychiatric disorders have largely been defined in binary terms: individuals either meet criteria for a disorder or they do not. But decades of empirical work have shown that psychological distress does not conform neatly to such boundaries. Symptoms overlap extensively across diagnostic categories, and individuals who meet criteria for one disorder frequently meet criteria for several others.
Dimensional approaches attempt to address this problem by describing psychopathology along continua of severity rather than through discrete categories. The committee highlights several prominent examples, including the Hierarchical Taxonomy of Psychopathology (HiTOP), which organizes symptoms into empirically derived hierarchies ranging from broad spectra such as Internalizing and Externalizing down to more specific components (Kotov et al., 2017, 2021).
he NIMH’s Research Domain Criteria initiative (RDoC) represents a complementary effort focused on neurobiological systems and behavioral functions.
These approaches represent meaningful progress. A dimensional taxonomy can provide a clearer picture of how symptoms cluster together across individuals and how different forms of distress relate to one another. In this sense, such frameworks help clarify the anatomy of psychopathology—the structural organization of psychological difficulties across populations.
But anatomy alone does not explain function.
Structure versus process
Understanding psychopathology ultimately requires more than describing how symptoms co-occur across people. It also requires understanding how those symptoms unfold within individuals over time.
Two individuals might receive nearly identical scores on a dimensional profile of internalizing psychopathology, yet the processes generating those difficulties may be entirely different. For one person, interpersonal conflict may trigger rumination, which intensifies depressed mood, leading to withdrawal that further exacerbates relationship problems. For another, sleep disruption might initiate anxiety that produces avoidance of work obligations, creating financial stress that feeds back into further anxiety.
From a dimensional perspective, these individuals may appear quite similar. From a process perspective, they are experiencing fundamentally different systems of dysfunction.
Research using intensive longitudinal designs increasingly demonstrates how heterogeneous these processes can be. When individuals’ experiences are sampled repeatedly in daily life—capturing fluctuations in mood, behavior, and context—and analyzed using person-specific statistical models, shared patterns across individuals often prove surprisingly limited. In one study of outpatients with personality disorders, the only dynamic association observed in a majority of individuals was the link between daily stress and negative affect (Wright et al., 2019). Most other relationships among emotions, behaviors, and functioning were highly individualized.
This growing body of work suggests that psychopathology may be better conceptualized not simply as positions on trait dimensions but as dynamic systems of interacting processes that differ from person to person (Wright & Woods, 2020).
The challenge of personalization
The committee’s roadmap repeatedly emphasizes the goal of “personalized treatment.” This is an important aspiration, but achieving it raises a technical issue that is rarely addressed directly.
Most psychological research relies on group-level analyses. Researchers measure symptoms across large samples and identify patterns that describe how variables relate across individuals. These findings provide valuable insights about population-level structure. However, they do not necessarily translate directly to processes within any particular person.
This problem is often described in terms of ergodicity (Molenaar, 2004): statistical relationships observed between individuals do not automatically generalize to the dynamics occurring within individuals over time. For example, while depression and anxiety may be positively correlated across people, the temporal relationship between these experiences within a given individual may differ substantially—or may not exist at all.
Dimensional diagnostic systems refine our understanding of betweenperson differences. But genuine personalization requires an additional step: collecting data within individuals across time and modeling the processes that characterize their unique patterns of experience.
In other words, dimensional classification improves description. Personalized understanding requires process modeling.
Emerging tools for dynamic assessment
Importantly, many of the tools needed to study psychopathology dynamically are already under development.
The HiTOP consortium has created comprehensive dimensional assessment instruments such as the HiTOP-SR (Simms et al., 2022). Digital assessment platforms like HiTOP-DAT allow clinicians to administer dimensional evaluations in clinical settings (Jonas et al., 2022). Ambulatory assessment instruments—including the Personality Dynamics Diary (Zimmermann et al., 2019) and related scale sets— enable researchers to measure psychological functioning repeatedly in daily life. Statistical tools such as GIMME allow researchers to estimate person-specific dynamic models while identifying shared features across individuals.
These developments suggest that the field is gradually acquiring the infrastructure needed to study psychopathology not only as a structural taxonomy but also as a set of dynamic processes unfolding in context.
Integrating such approaches into the broader conversation about DSM reform may therefore represent an important next step.
Personality, psychopathology, and function
Another question highlighted by dimensional models concerns the relationship between personality and psychopathology. A growing body of research shows that many of the broad spectra identified in HiTOP align closely with the major domains of personality described by the five-factor model (DeYoung et al., 2022; Widiger et al., 2019). Internalizing is closely related to neuroticism, detachment aligns with low extraversion, and aspects of externalizing reflect low agreeableness and conscientiousness.
These parallels raise a fundamental conceptual question: if personality traits and psychopathology occupy overlapping dimensional space, what distinguishes adaptive variation from clinical disorder?
Increasingly, researchers suggest that the distinction may lie not simply in extremity but in function—whether psychological processes remain flexible and responsive to situational demands or become rigid and maladaptive (Hopwood et al., 2022; Wright & Hopwood, 2022). This perspective again highlights the importance of examining dynamic processes rather than relying solely on static dimensional profiles.
Aligning structure, biology, and process
The committee also emphasizes the goal of integrating biological findings into psychiatric classification. This is a reasonable objective, but it raises an important sequencing issue. Progress in identifying biomarkers has been limited partly because the phenotypes used in research have often been poorly specified. If that is the case, refining those phenotypes—through clearer dimensional models and more precise behavioral characterization—may be a necessary precursor to meaningful biological integration.
For this reason, closer coordination between efforts to refine diagnostic structure and efforts to identify biological mechanisms may be especially important.
Moving forward
The Future DSM committee is attempting an extraordinarily difficult task: revising a classification system that must simultaneously serve clinicians, researchers, insurers, and policymakers. The fact that the committee is openly acknowledging the limitations of existing categories and inviting dialogue about alternatives is itself a significant step.
At the same time, the science of psychopathology has increasingly emphasized that mental disorders are not merely clusters of symptoms but dynamic patterns of functioning unfolding over time and across contexts. A diagnostic system that captures the structural organization of those patterns is valuable. But fully understanding—and ultimately treating—psychopathology will likely require integrating that structural knowledge with models of the processes that generate it.
A better map is an important beginning. But it is only the beginning of the much harder task of understanding the territory.
References
DeYoung, C. G., Chmielewski, M., Clark, L. A., Condon, D. M., Kotov, R., Krueger, R. F., Lynam, D. R., Markon, K. E., Miller, J. D., Mullins-Sweatt, S. N., Samuel, D. B., Sellbom, M., South, S. C., Thomas, K. M., Watson, D., Watts, A. L., Widiger, T. A., & Wright, A. G. C. (2022). The distinction between symptoms and traits in the Hierarchical Taxonomy of Psychopathology (HiTOP). Journal of Personality, 90 (1), 20–33. https://doi.org/10.1111/jopy.12593
Hopwood, C. J., Wright, A. G. C., & Bleidorn, W. (2022). Person– environment transactions differentiate personality and psychopathology. Nature Reviews Psychology, 1, 55–63. https://doi.org/10.1038/s44159-021-00004-0
Jonas, K. G., Stanton, K., Simms, L., Mullins-Sweatt, S. N., Gillett, D., Dainer, E., Nelson, B. D., Kotov, R., Cicero, D., & Ruggero, C. (2022). HiTOP Digital Assessment and Tracker (HiTOP-DAT) manual. https://osf.io/8hngd/ Kotov, R., Krueger, R. F., Watson, D., Achenbach, T. M., Althoff, R. R., Bagby, R. M., Brown, T. A., Carpenter, W. T., Caspi, A., Clark, L. A., Eaton, N. R., Forbes, M. K., Forbush, K. T., Goldberg, D., Hasin, D., Hyman, S. E., Ivanova, M. Y., Lynam, D. R., Markon, K., … Zimmerman, M. (2017). The Hierarchical Taxonomy of Psychopathology (HiTOP): A dimensional alternative to traditional nosologies. Journal of Abnormal Psychology, 126 (4), 454–477. https://doi.org/10.1037/abn0000258
Kotov, R., Krueger, R. F., Watson, D., Cicero, D. C., Conway, C. C., DeYoung, C. G., Eaton, N. R., Forbes, M. K., Hallquist, M. N., Latzman, R. D., Mullins-Sweatt, S. N., Ruggero, C. J., Simms, L. J., Waldman, I. D., Waszczuk, M. A., & Wright, A. G. C. (2021). The Hierarchical Taxonomy of Psychopathology (HiTOP): A quantitative nosology based on consensus of evidence. Annual Review of Clinical Psychology, 17, 83–108. https://doi.org/10.1146/annurev-clinpsy-081219-093304
Molenaar, P. C. M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement, 2 (4), 201–218. https://doi.org/10.1207/s15366359mea0204_1
Oquendo, M. A., Abi-Dargham, A., Alpert, J. E., Benton, T. D., Clarke, D. E., Compton, W. M., Drexler, K., Fung, K. P., Kas, M. J. H., Malaspina, D., O’Keefe, V. M., Öngür, D., Wainberg, M. L., Yonkers, K. A., Yousif, L., & Gogtay, N. (2026). Initial strategy for the future of DSM. American Journal of Psychiatry. Advance online publication. https://doi.org/10.1176/appi.ajp.20250878
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. https://doi.org/10.1177/10731911211015309 Vize, C. E., & Wright, A. G. C. (2024). Translating the transdiagnostic: Aligning assessment practices with research advances. Assessment, 31 (1), 199–215. https://doi.org/10.1177/10731911231194996
Widiger, T. A., Sellbom, M., Chmielewski, M., Clark, L. A., DeYoung, C. G., Kotov, R., Krueger, R. F., Lynam, D. R., Miller, J. D., Mullins-Sweatt, S., Samuel, D. B., South, S. C., Tackett, J. L., Thomas, K. M., Watson, D., & Wright, A. G. C. (2019). Personality in a hierarchical model of psychopathology. Clinical Psychological Science, 7 (1), 77–92. https://doi.org/10.1177/2167702618797105
Wright, A. G. C., Gates, K. M., Arizmendi, C., Lane, S. T., Woods, W. C., & Edershile, E. A. (2019). Focusing personality assessment on the person: Modeling general, shared, and person specific processes in personality and psychopathology. Psychological Assessment, 32 (4), 502–515. https://doi.org/10.1037/pas0000617
Wright, A. G. C., & Hopwood, C. J. (2022). Integrating and distinguishing personality and psychopathology. Journal of Personality, 90 (1), 5–19. https://doi.org/10.1111/jopy.12671
Wright, A. G. C., Ringwald, W. R., & Zimmermann, J. (2025). Measuring psychopathology in daily life. Clinical Psychological Science, 13 (3), 649–663. https://doi.org/10.1177/21677026241291549
Wright, A. G. C., & Woods, W. C. (2020). Personalized models of psychopathology. Annual Review of Clinical Psychology, 16, 49–74. https://doi.org/10.1146/annurev-clinpsy-102419-125032
Zimmermann, J., Woods, W. C., Ritter, S., Happel, M., Masuhr, O., Jaeger, U., Spitzer, C., & Wright, A. G. C. (2019). Integrating structure and dynamics in personality assessment: First steps toward the development and validation of a personality dynamics diary. Psychological Assessment, 31 (4), 516–531. https://doi.org/10.1037/pas0000625