Psychiatric diagnoses are not mental processes: Wittgenstein on conceptual confusion

Unveiling the Structure in Mental Disorder Presentations

Importance

DSM criteria are polythetic, allowing for heterogeneity of symptoms among individuals with the same disorder. In empirical research, most combinations were not found or only rarely found, prompting criticism of this heterogeneity.

Objective

To elaborate how symptom-based definitions and assessments contribute to a distinct probability pattern for the occurrence of symptom combinations.

Design, Setting, and Participants

This cross-sectional study involved a theoretical argument, simulation, and secondary data analysis of 4 preexisting datasets, each consisting of symptoms from 1 of the following syndromes: posttraumatic stress disorder, depression, schizophrenia, and anxiety. Data were obtained from various sources, including the National Institute of Mental Health Data Archive and Department of Veteran Affairs. A total of 155 474 participants were included (individual studies were 3930 to 63 742 individuals in size). Data were analyzed between July 2021 and January 2024.

Exposure

For each participant, the presence or absence of each assessed symptom and their combination was determined. The number of all combinations and their individual frequencies were assessed.

Main Outcome and Measure

Probability or frequency of unique symptom combinations and their distribution.

Results

Among the 155 474 participants, the mean (SD) age was 47.5 (14.8) years; 33 933 (21.8%) self-identified as female and 121 541 (78.2%) as male. Because of the interrelation between symptoms, some symptom combinations were significantly more likely than others. The distribution of the combinations' probability was heavily skewed with most combinations having a very low probability. Across all 4 empirical samples, the 1% most common combinations were prevalent in a total of 33.1% to 78.6% of the corresponding sample. At the same time, many combinations (ranging from 41.7% to 99.8%) were reported by less than 1% of the sample.

Conclusions and Relevance

This study found that within-disorder symptom heterogeneity followed a specific pattern consisting of few prevalent, prototypical combinations and numerous combinations with a very low probability of occurrence. Future discussions about the revision of diagnostic criteria should take this specific pattern into account by focusing not only on the absolute number of symptom combinations but also on their individual and cumulative probabilities. Findings from clinical populations using common diagnostic criteria may have limited generalizability to the large group of individuals with a low-probability symptom combination.

Network Analysis-Based Disentanglement of the Symptom Heterogeneity in Asian Patients with Schizophrenia: Findings from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics

The symptom heterogeneity of schizophrenia is consistent with Wittgenstein's analogy of a language game. From the perspective of precision medicine, this study aimed to estimate the symptom presentation and identify the psychonectome in Asian patients, using data obtained from the Research on Asian Psychotropic Prescription Patterns for Antipsychotics. We constructed a network structure of the Brief Psychiatric Rating Scale (BPRS) items in 1438 Asian patients with schizophrenia. Furthermore, all the BPRS items were considered to be an ordered categorical variable ranging in value from 1-7. Motor retardation was situated most centrally within the BPRS network structure, followed by depressive mood and unusual thought content. Contrastingly, hallucinatory behavior was situated least centrally within the network structure. Using a community detection algorithm, the BPRS items were organized into positive, negative, and general symptom clusters. Overall, DSM symptoms were not more central than non-DSM symptoms within the symptom network of Asian patients with schizophrenia. Thus, motor retardation, which results from the unmet needs associated with current antipsychotic medications for schizophrenia, may be a tailored treatment target for Asian patients with schizophrenia. Based on these findings, targeting non-dopamine systems (glutamate, γ-aminobutyric acid) may represent an effective strategy with respect to precision medicine for psychosis.

Machine Learning-Based Definition of Symptom Clusters and Selection of Antidepressants for Depressive Syndrome

The current polythetic and operational criteria for major depression inevitably contribute to the heterogeneity of depressive syndromes. The heterogeneity of depressive syndrome has been criticized using the concept of language game in Wittgensteinian philosophy. Moreover, “a symptom- or endophenotype-based approach, rather than a diagnosis-based approach, has been proposed” as the “next-generation treatment for mental disorders” by Thomas Insel. Understanding the heterogeneity renders promise for personalized medicine to treat cases of depressive syndrome, in terms of both defining symptom clusters and selecting antidepressants. Machine learning algorithms have emerged as a tool for personalized medicine by handling clinical big data that can be used as predictors for subtype classification and treatment outcome prediction. The large clinical cohort data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D), Combining Medications to Enhance Depression Outcome (CO-MED), and the German Research Network on Depression (GRND) have recently began to be acknowledged as useful sources for machine learning-based depression research with regard to cost effectiveness and generalizability. In addition, noninvasive biological tools such as functional and resting state magnetic resonance imaging techniques are widely combined with machine learning methods to detect intrinsic endophenotypes of depression. This review highlights recent studies that have used clinical cohort or brain imaging data and have addressed machine learning-based approaches to defining symptom clusters and selecting antidepressants. Potentially applicable suggestions to realize machine learning-based personalized medicine for depressive syndrome are also provided herein.

An alternative approach to future diagnostic standards for major depressive disorder

During the period extending from 1780 to 1880, the conceptualization of melancholia changed from an intellectual to a mood model. The modern view of depression, based on Kraepelinian dualism, has reflected changes in opinion on psychiatric taxonomy of individual melancholia. From the point of view of an "operational revolution," the diagnostic criteria for major depressive disorder in the Diagnostic and Statistical Manual of Mental Disorders, 3rd edition (DSM-III) were based on a neoKraepelinian approach rooted in disease essentialism. In the revision process from the DSM-IV to the DSM-5, a combined dimensional and categorial approach was used. In the DSM-5, the diagnostic criteria for major depressive disorder are polythetic and operational in approach reflecting the heterogeneity of major depressive disorder. Although 227 different symptom combinations fulfilling the diagnostic criteria for major depressive disorder can be theoretically calculated, certain symptom combinations are more prevalent than others in real clinical situations. The heterogeneity of these operational criteria for major depressive disorder have been criticized in a manner informed by the Wittgensteinian analogy of the language game. Herein, our network analysis proposes a novel perspective on the psychopathology of major depressive disorder. The novel approach suggested here may lay the foundation for a redefinition of the traditional taxonomy of depression.

Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards

The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.

The Centrality of Depression and Anxiety Symptoms in Major Depressive Disorder Determined Using a Network Analysis

BACKGROUND

Comorbid anxiety symptoms are highly prevalent and closely linked with poorer treatment outcomes, chronicity, and hospitalization in major depressive disorder (MDD). Our study aimed to estimate the network of depression and anxiety symptoms that was developed based on a sample of MDD patients.

METHODS

We constructed a network of the 21 Beck Depression Inventory (BDI) symptoms and 21 Beck Anxiety Inventory (BAI) symptoms in 223 patients with MDD who were beginning psychiatric treatment. In addition, each of the depression and anxiety symptoms was considered to be an ordered categorical variable ranging in value from 0 to 3.

RESULTS

The three depression symptoms including loss of energy, loss of interest, and worthlessness and the seven anxiety symptoms including faintness or lightheadedness, feeling of choking, feeling scared, fear of the worst happening, nervousness, inability to relax, and feeling shaky were identified as the ten most central nodes within a network of depression and anxiety symptoms. The inter-connection between irritability and nervousness was a strong trans-diagnostic edge within the network of depression and anxiety symptoms.

LIMITATIONS

Because our study was designed in a cross-sectional manner, the networks were estimated undirectionally.

CONCLUSIONS

Our findings show that depression symptoms are not more central than anxiety symptoms within an estimated network structure of symptoms in patients with MDD. Moreover, the inter-connection between irritability and nervousness may suggests a probable trans-diagnostic association in MDD symptomatology.

Network analysis of the depressive symptom profiles in Asian patients with depressive disorders: Findings from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD)

AIM

We aimed to estimate the network structures of depressive symptoms using network analysis and evaluated the geographic regional differences in theses network structures among Asian patients with depressive disorders.

METHODS

Using data from the Research on Asian Psychotropic Prescription Patterns for Antidepressants (REAP-AD), the network of the ICD-10 diagnostic criteria for depressive episode was estimated from 1174 Asian patients with depressive disorders. The node strength centrality of all ICD-10 diagnostic criteria for a depressive episode was estimated using a community-detection algorithm. In addition, networks of depressive symptoms were estimated separately among East Asian patients and South or Southeast Asian patients. Moreover, networks were estimated separately among Asian patients from high-income countries and those from middle-income countries.

RESULTS

Persistent sadness, fatigue, and loss of interest were the most centrally situated within the network of depressive symptoms in Asian patients with depressive disorders overall. A community-detection algorithm estimated that when excluding psychomotor disturbance as an outlier, the other nine symptoms formed the largest clinically meaningful cluster. Geographic and economic variations in networks of depressive symptoms were evaluated.

CONCLUSION

Our findings demonstrated that the typical symptoms of the ICD-10 diagnostic criteria for depressive episode are the most centrally situated within the network of depressive symptoms. Furthermore, our findings suggested that cultural influences related to geographic and economic distributions of participants could influence the estimated depressive symptom network in Asian patients with depressive disorders.

Reduced awareness of surroundings is the most central domain in the network structure of posttraumatic stress disorder symptoms

Backgroud: Network models suggest that co-occurring symptoms are conceptualized as a syndrome due to interactions, rather than a categorical entity with an underlying common cause.Aim: Our study aimed to examine the network structure and centrality of Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV posttraumatic stress disorder (PTSD) symptoms, including essential and associated features.Methods: We constructed a network structure of 21 intertwined symptoms, evaluated with the Clinician-Administered PTSD Scale (CAPS), in 249 PTSD patients who have been exposed to various types of traumatic events (73% being traffic or other accidents) and were beginning psychiatric treatment. In addition, we estimated the centrality of the 21 symptoms through network analysis. Each of the symptoms was defined as ordered-categorical variables.Results: The network, with 21 symptoms, demonstrated a strong correlation among difficulty concentrating, reduced awareness of surroundings, and derealization. In addition, reduced awareness of surroundings was estimated as the most central symptom, whereas inability to recall important aspects of trauma was estimated as the least central symptom in the subjects. A community-detection analysis estimated that the 21 PTSD symptoms were organized into three clinically meaning clusters.Conclusion: Although dissociative features have been defined as associative symptoms rather than essential symptoms for the DSM diagnostic criteria, reduced awareness of surroundings may be regarded as the most central symptom in patients in the early phase of PTSD. Thus, evaluation and intervention for dissociative features may be needed in clinical practice and studies on PTSD.

Symptom-based selection of antidepressants

Most evidence-based pharmacological guidelines recommend selective serotonin reuptake inhibitors, serotoninnorepinephrine reuptake inhibitors, norepinephrine-dopamine reuptake inhibitors or norepinephrine and specific serotonin antidepressants as the first-line treatment for major depression. Since the clinical factors associated with treating patients with depression are relatively complex, it can be challenging to apply the recommendations of evidence-based medicine verbatim. Furthermore, the diagnostic criteria of major depressive disorders, which are defined in a polythetic and operational manner, inevitably result in their heterogeneity. Studies have inferred that depressive syndrome may be connected with “family resemblance” rather than being shared with a neurobiological essence. Therefore, the symptom-based selection of antidepressants can be supported by a network analysis that provides a novel perspective on the symptom structure of major depression. The symptom-based treatment algorithm suggests treatment options that can be applied to the symptoms that are included in and excluded from the diagnosis criteria of major depressive disorder. The symptom-based selection of antidepressants and other psychotropic agents involves matching the deconstructed symptoms of depression to the specific neuroanatomical regions and neurotransmitters. This ensures timely and optimized treatment options for patients with depression.

Diagnostic Issues of Depressive Disorders from Kraepelinian Dualism to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition

Because the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) was mainly influenced by the neo-Kraepelinian approach, its categorical approach to defining mental disorders has been criticized from the viewpoint of etiological neutrality. In the context of bridging the gap between "presumed etiologies-based symptomatology" and "identifiable pathophysiological etiologies," the content in 5th edition, the DSM-5, has been revised to incorporate a combination of categorical and dimensional approaches. The most remarkable change of note regarding the diagnostic classification of depressive disorders in the DSM-5 is the splitting of mood disorders into bipolar disorders and depressive disorders, which is in accordance with the deconstruction of the Kraepelinian dualism for psychoses. The transdiagnostic specifiers "with mixed features," "with psychotic features," and "with anxious distress" are introduced to describe the relationships of depressive disorders with bipolar disorders, schizophrenia, and generalized anxiety disorder, respectively, in a dimensional manner. The lowering of the diagnostic threshold for major depressive disorder (MDD) may be caused by the addition of "hopelessness" to the subjective descriptors of depressive mood and the elimination of "bereavement exclusion" from the definition of MDD. Since the heterogeneity of MDD is equivalent to the Wittgensteinian "games" analogy, the different types of MDD are related not by a single essential feature but rather by "family resemblance." Network analyses of MDD symptoms may therefore need further review to elucidate the connections among interrelated symptoms and other clinical elements.

Karl Jaspers' General Psychopathology (Allgemeine Psychopathologie) and Its Implication for the Current Psychiatry

Karl Jaspers is a psychiatrist, philosopher, and humanist. In 1913, he published the General Psychopathology (GP; Allgemeine Psychopathologie), the first edition. Despite the passage of one hundred years after the GP was published, GP still has a potential value to present a phenomenological and comprehensive viewpoint for psychiatry to overcome Kraepelinian-biological absolutism. The philosophical backgrounds of a Jaspersian phenomenological sense have been related to both the transcendence and the immanence roots. Partly under the influence of a Husserlian distinction between the natural and phenomenological attitudes, a rigid distinction between explanation and understanding has been proposed as the proper epistemological method in Jaspers' GP. Further, the fact that a distinction between process and development has been presented as the psychical phenomenon is understandable. The integrated and comprehensive viewpoint establishment for the state of "Babylonian confusion of tongues" in German psychiatry as well as the newly initiating phenomenological trend in psychiatry have been the legacies of Jaspers' GP. Moreover, the common theoretical backgrounds may be shared by the Jaspersian sense and humanitarian approaches in Korean psychiatry. Also, the Jaspersian sense may help the current molecular psychiatry to have a chance to overcome its solipsism and limitations.

Classification of Psychiatric Disorders

Because of the poor link between psychiatric diagnosis and neurobiological findings, it is difficult to classify mental disorders. The changes made to psychiatric diagnostic systems over the years can be understood in terms of "practical conservatism." The Diagnostic and Statistical Manual of Mental Disorders (DSM)-I and DSM-II were theoretically supported by the psychoanalytic and psychodynamic approach. Subsequently, psychiatric diagnoses of this kind were opposed by the anti-psychiatry movement, as well as by the findings of the Rosenhan experiment. Thus, the DSM-III revolution contained more empiricism, aligning psychiatry with biomedicine. Psychiatric diagnoses are classified and defined in terms of Kraepelinian dualism, using a categorical approach. The empirical trend was continued in the DSM-IV. To overcome the limitations of current psychiatric diagnostic systems and integrate fundamental genetic, neurobiological, behavioral, environmental, and experimental components into psychiatry, the Research Domain Criteria (RDoC) were established. To overcome the limitations of the categorical approach, psychiatrists have considered adopting a dimensional approach. However, their efforts were frustrated in the DSM-5 revision process. Thus, the DSM-5 is characterized by the rearrangement of psychiatric diagnoses, the partial adoption of a dimensional approach, the introduction of new diagnoses, and harmonization with the International Classification of Diseases.

How many different symptom combinations fulfil the diagnostic criteria for major depressive disorder? Results from the CRESCEND study

BACKGROUND

The polythetic nature of major depressive disorder (MDD) in DSM- IV and DSM-5 inevitably leads to diagnostic heterogeneity.

AIMS

This study aimed to identify the number of depressive symptom combinations actually fulfilling the DSM-IV diagnostic criteria that can be found in Korean MDD patients and the relative frequencies of each combination.

METHODS

Using the data from the Clinical Research Center for Depression (CRESCEND) study in South Korea, we enrolled 853 MDD patients diagnosed using DSM-IV and scored as 8 or more on the Hamilton Depression Rating Scale (HAMD). Descriptive statistical analyses were performed to reveal the degree of diagnostic heterogeneity of the MDD.

RESULTS

This study identified 119 different depressive symptom combinations. The most common combination consisted of all nine depressive symptom profiles, and nine different combinations were each present in more than 3% of the patients.

CONCLUSION

The findings support the criticism that the diagnosis of MDD is not based on a single mental process, but on a set of 'family resemblances'.

Clinical Significance of the Number of Depressive Symptoms in Major Depressive Disorder: Results from the CRESCEND Study

Our study aimed to establish the relationship between the number of depressive symptoms and the clinical characteristics of major depressive disorder (MDD). This would enable us to predict the clinical significance of the number of depressive symptoms in MDD patients. Using data from the Clinical Research Center for Depression (CRESCEND) study in Korea, 853 patients with DSM-IV MDD were recruited. The baseline and clinical characteristics of groups with different numbers of depressive symptoms were compared using the χ(2) test for discrete variables and covariance (ANCOVA) for continuous variables. In addition, the scores of these groups on the measurement tools were compared by ANCOVA after adjusting the potential effects of confounding variables. After adjusting the effects of monthly income and history of depression, a larger number of depressive symptoms indicated higher overall severity of depression (F [4, 756] = 21.458, P < 0.001) and higher levels of depressive symptoms (F [4, 767] = 19.145, P < 0.001), anxiety symptoms (F [4, 765] = 12.890, P < 0.001) and suicidal ideation (F [4, 653] = 6.970, P < 0.001). It also indicated lower levels of social function (F [4, 760] = 13.343, P < 0.001), and quality of life (F [4, 656] = 11.975, P < 0.001). However, there were no significant differences in alcohol consumption (F [4, 656] = 11.975, P < 0.001). The number of depressive symptoms can be used as an index of greater illness burden in clinical psychiatry.

The Dangers of Posthumous Diagnoses and the Unintended Consequences of Facile Associations: Jeffrey Dahmer and Autism Spectrum Disorders

Posthumous diagnoses are not uncommonly given to notorious public and historical figures by applying retrospectively, and typically in the absence of the individual being diagnosed, contemporary diagnostic criteria. Although this may be relatively easy and free of consequences when it concerns clear-cut medical conditions, it may have unintended repercussions in the case of psychiatric disorders by creating myths and perpetuating stigma. The case of serial killer Jeffrey Dahmer is a typical example where a somewhat facile and almost syllogistic application of perhaps over-inclusive criteria may have contributed to the legend of solitary murderers as possibly suffering from an autism spectrum condition. Although there may be an understandable human need to explain abominable and heinous behaviors, the lack of the possibility to verify a diagnostic theory and the ill-advised attempt to make a diagnosis fit may de facto be the basis of prejudice and profiling that do not correspond to clinical reality. Although there is no doubt that the brain is the organ of behavior, the authors caution against a budding neo-Lombrosian approach to crime and criminality and against the all too common use of widely differing terms in the study of deviance, such as crime, delinquency, and aggression, the operational use of which, often used interchangeably even in association studies, often erroneously leads to further confusion.

Knowledge and Attitude of 851 Nursing Personnel toward Depression in General Hospitals of Korea

Our study aimed to examine the knowledge and attitude of nursing personnel toward depression in general hospitals of Korea. A total of 851 nursing personnel enrolled at four university-affiliated general hospitals completed self-report questionnaires. Chi-square tests were used to compare the knowledge and attitude of registered or assistant nurses toward depression. In addition, binary logistic regression analysis was used to adjust for the following confounders: age-group and workplace. Registered and assistant nurses differed in their knowledge and attitude toward depression. The proportion of rational and/or correct responses were higher in registered nurses than assistant nurses for the following: constellation of depressive symptoms defined by DSM-IV (adjusted odds ratio [aOR], 3.876; P<0.001); suicide risk in depression recovery (aOR, 3.223; P=0.001) and psychological stress as a cause of depression (aOR, 4.370; P<0.001); the relationship between chronic physical disease and depression (aOR, 8.984; P<0.001); and other items. Our results suggest that in terms of the biological model of depression, the understanding of registered nurses is greater than that of assistant nurses. Moreover, specific psychiatric education programs for nursing personnel need to be developed in Korea. Our findings can contribute to the development of a general hospital-based model for early detection of depression in patients with chronic medical diseases.