Transdiagnostic Sample Research Articles

Transdiagnostic Predictors of Health-Related Quality of Life in Children with Autism and Epilepsy: A Cross-Sectional Study.

Background/Objectives: Our understanding of the transdiagnostic factors that influence health-related quality of life (HRQOL) in individuals with neurodivergent conditions is very sparse and highly siloed by diagnosis labels. Research on transdiagnostic predictors of HRQOL across neurodevelopmental conditions is needed to enable care models that address shared needs of neurodivergent individuals beyond diagnostic boundaries. Our objective was to identify transdiagnostic factors associated with HRQOL in children with autism, epilepsy, or comorbid autism/epilepsy. Methods: This cross-sectional study included 37 autistic and/or epileptic children (mean age = 9.2; SD = 3.9; boys = 28). Parents provided sociodemographic information and completed the following measures: Social Communication Questionnaire (measure of severity of autistic symptoms); Parenting Stress Index, Fourth Edition; Pediatric Quality of Life Inventory; and the Behavioral Assessment System for Children, Third Edition. Child intellectual functioning was measured using age-appropriate scales: the Wechsler Preschool and Primary Scale of Intelligence-Fourth Edition: Canadian or the Wechsler Intelligence Scale for Children-Fifth Edition: Canadian. Results: Higher autistic symptom severity (OR = 0.851 95% CI: 0.732-0.988, p = 0.034) and parenting stress (OR = 0.687 95% CI: 0.493-0.959, p = 0.027) were associated with poorer HRQOL. Full Scale IQ and adaptive skills showed trend level associations with HRQOL. Sociodemographic factors including maternal education, child sex, and child age as well as child diagnosis were not associated with HRQOL. Conclusions: In this transdiagnostic sample of children, autism symptom severity and parenting stress were shared predictors of HRQOL. Interventions targeting child autistic symptoms and parents' levels of stress could result in improved HRQOL in neurodivergent populations.

Camouflaging in neurodivergent and neurotypical girls at the transition to adolescence and its relationship to mental health: A participatory methods research study.

Adolescent girls with diagnoses of autism, ADHD and/or developmental coordination disorder (DCD) are at higher risk for mental health problems than boys with the same diagnoses and neurotypical girls. These girls are called neurodivergent here, though neurodivergence includes a broader range of diagnoses. One possible reason for this mental health disparity could be camouflaging, a coping strategy used more by girls. Camouflaging is when the individual pretends to be neurotypical, often involving substantial effort. This study aims to understand: (a) if the use of camouflaging has started by early adolescence, (b) how components of camouflaging (assimilation, masking, and compensation) present at this age, (c) if age predicts camouflaging and (d) what is the relationship with mental health. Participatory methods: A co-production team of 15 adult neurodivergent women co-producedthe project and ranked camouflaging as their most important research theme. Neurodivergent and neurotypical girls presented similarly on two components of camouflaging namely masking and compensation, components related to presenting in a socially acceptable way and mimicry. Groups differed on the assimilation component, which is related to trying to fit in and involves the feelings of pretending/acting. Age had a medium effect on camouflaging with higher levels of camouflaging observed in older girls. Camouflaging scores strongly predicted anxiety and depression scores in both groups. The use of camouflaging, specifically assimilation, is evident in a transdiagnostic sample of 11-14year old neurodivergent girls. Importantly, the strong relationship between camouflaging and poor mental health is present at this early age, substantiating the co-production team's insights.

Altered coupling relationships across resting-state functional connectivity measures in schizophrenia, bipolar disorder, and attention deficit/hyperactivity disorder.

Resting-state functional connectivity (rsFC) measures have enjoyed significant success in discovering the neuropathological characteristics of schizophrenia (SZ), bipolar disorder (BD), and attention deficit/hyperactivity disorder (ADHD). However, it is unknown whether and how the spatial and temporal coupling relationships across rsFC measures would be altered in these psychiatric disorders. Here, resting-state fMRI data were obtained from a transdiagnostic sample of healthy controls (HC) and individuals with SZ, BD, and ADHD. We used Kendall's W to compute volume-wise and voxel-wise concordance across rsFC measures, followed by group comparisons. In terms of the spatial coupling, both SZ and BD individuals exhibited decreased volume-wise concordance compared with HC. Regarding the temporal coupling, SZ individuals showed decreased voxel-wise concordance in the right lateral occipital cortex relative to HC. BD individuals exhibited decreased voxel-wise concordance in the bilateral basal forebrain and bilateral superior/middle temporal gyrus compared to HC. Additionally, correlation analyses demonstrated positive associations of voxel-wise concordance in the left basal forebrain with negative symptoms including alogia and affective flattening in pooled SZ and BD individuals. Our findings of distinct patterns of spatial and temporal decoupling across rsFC measures among SZ, BD, and ADHD may provide unique insights into the neuropathological mechanisms of these psychiatric disorders.

Impaired contour object perception in psychosis.

Contour integration, the process of joining spatially separated elements into a single unified line, has consistently been found to be impaired in schizophrenia. Recent work suggests that this deficit could be associated with psychotic symptomatology, rather than a specific diagnosis such as schizophrenia. Examining a transdiagnostic sample of participants with psychotic psychopathology, we obtained quantitative indices of contour perception in a psychophysical behavioral task. We also measured responses during an analogous task using ultra-high field (7T) functional MRI. We found impaired contour discrimination performance among people with psychotic psychopathology (PwPP, n = 63) compared to healthy controls (n = 34) and biological relatives of PwPP (n = 44). Participants with schizophrenia (n = 31) showed impaired task performance compared to participants with bipolar disorder (n = 18). FMRI showed higher responses in the lateral occipital cortex of PwPP compared to controls. Using task-based functional connectivity analyses, we observed abnormal connectivity between visual brain areas during contour perception among PwPP. These connectivity differences only emerged when participants had to distinguish the contour object from background distractors, suggesting that a failure to suppress noise elements relative to contour elements may underlie impaired contour processing in PwPP. Our results are consistent with impaired contour integration in psychotic psychopathology, and especially schizophrenia, that is related to cognitive dysfunction, and may be linked to impaired functional connectivity across visual regions.

Examining Dimensionality and Item-Quality of the Eating Disorder Examination Questionnaire in Individuals With Eating Disorders Using Item Response Theory Analysis.

The Eating Disorder Examination Questionnaire (EDE-Q) is a widely-used measure of eating-disorder symptoms. However, inconsistent replication of the subscale structure raises concern about validity. To provide a rigorous test of the EDE-Q's dimensionality and item-quality, we applied modern and classical test theory approaches to data obtained from a large, transdiagnostic sample of people with clinical eating disorders. We analyzed data from 1197 individuals (Mage = 27.9 years, SD = 10.08, 95% female) with various eating disorders, who had been assessed for treatment at a specialized program. Exploratory analyses (including Parallel Analyses), Confirmatory Factor Analyses (CFA) and graded-response Item Response Theory (IRT) analyses, were conducted with Mplus. Factor analyses showed inappropriate fit to the original EDE-Q subscales, as well as for alternative 1,2,3, and 4-factor solutions. Parallel analyses suggested a one-dimensional structure as best fit. IRT analyses showed substantial variability in EDE-Q-item quality and indicated that five items (fear of weight gain, feeling fat, desire to lose weight, importance of weight, importance of shape) were most pertinent to determining severity. The construct validity of the five EDE-Q items was confirmed by a CFA, showing excellent fit. Our results suggest that EDE-Q scores are best interpreted as spanning a one-factor continuum. IRT results suggest that some items are more pertinent than others for determining eating-disorder severity. Results could be useful for establishing short EDE-Q versions, such as a five-item version, which, in turn, would be helpful for measurement-based clinical practice and for data-collection in epidemiological and experimental studies.

Generalizable and replicable brain-based predictions of cognitive functioning across common psychiatric illness.

A primary aim of computational psychiatry is to establish predictive models linking individual differences in brain functioning with symptoms. In particular, cognitive impairments are transdiagnostic, treatment resistant, and associated with poor outcomes. Recent work suggests that thousands of participants may be necessary for the accurate and reliable prediction of cognition, questioning the utility of most patient collection efforts. Here, using a transfer learning framework, we train a model on functional neuroimaging data from the UK Biobank to predict cognitive functioning in three transdiagnostic samples (ns = 101 to 224). We demonstrate prediction performance in all three samples comparable to that reported in larger prediction studies and a boost of up to 116% relative to classical models trained directly in the smaller samples. Critically, the model generalizes across datasets, maintaining performance when trained and tested across independent samples. This work establishes that predictive models derived in large population-level datasets can boost the prediction of cognition across clinical studies.

Cerebellar-Prefrontal Connectivity Predicts Negative Symptom Severity Across the Psychosis Spectrum.

Negative symptom severity predicts functional outcome and quality life in people with psychosis. However, negative symptoms are poorly responsive to antipsychotic medication and existing literature has not converged on their neurobiological basis. Previous work in small schizophrenia samples has observed that lower cerebellar-prefrontal connectivity is associated with higher negative symptom severity and demonstrated in a separate neuromodulation experiment that increasing cerebellar-prefrontal connectivity reduced negative symptom severity. We sought to expand this finding to test associations between cerebellar-prefrontal connectivity with negative symptom severity and cognitive performance in a large, transdiagnostic sample of individuals with psychotic disorders. In this study, 260 individuals with psychotic disorders underwent resting-state MRI and clinical characterization. Negative symptom severity was measured using the Positive and Negative Symptoms Scale, and cognitive performance was assessed with the Screen for Cognitive Impairment in Psychiatry. Using a previously identified cerebellar region as a seed, we performed seed to whole brain analyses and regressed connectivity against negative symptom severity, using age and sex as covariates. Consistent with prior work, we identified relationships between higher cerebellar-prefrontal connectivity and lower negative symptom severity (r=-0.17, p=.007). Higher cerebellar-prefrontal connectivity was also associated with better delayed verbal learning (r=.13, p=.034). Our results provide further evidence supporting the relationship between cerebellar-prefrontal connectivity and negative symptom severity and cognitive performance. Larger, randomized, sham-controlled neuromodulation studies should test if increasing cerebellar-prefrontal connectivity leads to reductions in negative symptoms in psychosis.

Transdiagnostic Anxiety-Related Increases in Information Sampling are Associated With Altered Valuation.

Excessive information sampling in psychiatric patients characterized by high trait anxiety has been inconsistently linked with alterations in inferential and valuation processes. Methodological limitations could account in part for these inconsistencies. To address this, computational models of inference and valuation were applied to data collected from a transdiagnostic sample of adults with and without an anxiety or compulsive disorder using a version of the beads task with enhanced experimental controls. Participants diagnosed with an anxiety or compulsive disorder (n = 35) and healthy controls (n = 23) completed the beads task with three majority-to-minority ratios of blue versus green beads (60:40, 75:25, 90:10). First, a Bayesian belief-updating model was fit to quantify the iterative process by which new information (bead color) and prior beliefs were integrated to influence current beliefs about jar identity. Next, a parameterized partially observable Markov decision process model was used to parse the contribution of value-based decisions to sampling behavior and included a relative subjective cost parameter, Csub , for each bead-ratio condition. Higher trait anxiety was associated with more draws-to-decision, most robustly in the 90:10 bead-ratio condition. Only relative subjective cost of sampling decisions, and not inferential differences in weighting of new or old information, satisfactorily accounted for this relation. Specifically, lower Csub(0.9) was associated with more trait anxiety and more draws-to-decision. In a condition with high objective evidence strength, transdiagnostic trait-anxiety-related increases in information sampling were explained by a cost-benefit analysis where relatively higher subjective cost was assigned to an incorrect guess, highlighting valuation as a potential treatment target for future research.

Differential effects of trait-like emotion regulation use and situational emotion regulation ability across the affective and anxiety disorders spectrum: a transdiagnostic examination

Here, we investigated the association of different emotion regulation (ER) indices with symptom severity across a large transdiagnostic sample of patients with emotional disorders (cross-sectional approach) and the predictive validity these ER indices have for the outcome of routine care CBT (longitudinal approach). We assessed the trait-like use of adaptive (reappraisal) and maladaptive (suppression, externalizing behaviors) ER strategies via questionnaire as well as the situational ability to regulate emotions with an experimental ER paradigm. Psychopathology was assessed dimensionally using the depression, anxiety, and stress scale. Cross-sectionally symptom severity was predicted by less trait-like use of adaptive and more trait-like use of maladaptive ER strategies, but no associations were found for situational ER ability. This association was more pronounced for depression and stress symptoms rather than anxiety symptoms. In a striking dissociation, the longitudinal analyses revealed the reverse picture: Better situational ER ability, but not trait-like use of ER strategies was associated with less symptom severity after the CBT treatment. Our data argues in favor of a distinction between trait-like and situational ER abilities in individuals with emotional disorders, highlighting challenges in applying adaptive ER strategies in daily life despite demonstrating intact ER skills in experimental settings. Our findings also inform transdiagnostic models of psychopathology and suggest that distress/depression rather than anxiety symptomatology to be driving forces for the occurrence of ER deficits across the depression/anxiety disorders spectrum.

The Trauma-Related Voices Model: An Integration of Auditory Verbal Hallucinations and Posttraumatic Stress.

Many trauma-affected voice hearers report comorbid posttraumatic stress and voices (auditory verbal hallucinations) that are directly (voices repeat phrases spoken by perpetrators) or indirectly (voice content and trauma are thematically similar) related to their trauma. Models of PTSD and positive symptoms of psychosis are insufficient in explaining the comorbidity between PTSD and voices, and interventions based on these models have limited effectiveness in treating voices. This study presents a model that generates novel research into the factors underlying trauma-related voices that may inform effective interventions. Maintaining factors from existing models of PTSD and positive symptoms were combined into an integrative model of trauma-related voices. Theorised relationships between factors were used to identify possible differential pathways to direct and indirect voices. An integrative, trauma-related voices (TRV) model was developed that identifies multiple causal pathways to trauma-related voices. A future research agenda is proposed to test novel hypotheses based on the integrative model. The TRV model is a practical tool for complex case conceptualisation and generates novel hypotheses that may inform more effective treatments. Future studies are needed to test elements of the TRV model and should recruit transdiagnostic samples with diverse posttraumatic stress and voice hearing symptoms.

Evaluating state-based network dynamics in anhedonia

Anhedonia is a transdiagnostic clinical syndrome associated with significant clinical impairment. In spite of this, a clear network-level characterization of anhedonia does not yet exist. The present study addressed this gap in the literature by taking a graph theoretical approach to characterizing state-based (i.e., reward anticipation, rest) network dynamics in a transdiagnostic sample of adults with clinically significant anhedonia (n = 77). Analyses focused on three canonical brain networks: the Salience Network (SN), the Default Mode Network (DMN) and the Central Executive Network (CEN), with hypotheses focusing on the role of saliency-mapping in anhedonia. Contrary to hypotheses, no significant relation was found between the SN and anhedonia symptom severity. Exploratory results revealed a significant association between anhedonia severity and DMN reorganization from rest to reward anticipation. Specifically, greater anhedonia severity was associated with less reward-related reorganization. This finding suggests that anhedonia severity may be associated with DMN hyposensitivity, such that individuals with more severe anhedonia may have a difficult time disengaging from their internal world in the context of potentially rewarding experiences. Although preliminary, this finding challenges the centrality of the SN in anhedonia severity and suggests the importance of the DMN. Clinical implications and future directions are explored.

Psychotic symptoms associated increased CpG methylation of metabotropic glutamate receptor 8 gene in Chinese Han males with schizophrenia and methamphetamine induced psychotic disorder: a longitudinal study

Methamphetamine use can produce psychotic symptoms almost indistinguishable from schizophrenia (SCZ). Variation in DNA methylation may be closely implicated in the etiology and longitudinal development of psychiatric disorders. However, the relationship between psychotic symptoms, functional disability, and DNA methylation is still unclear. This study consists of three periods: discovery, validation, and follow-up. In the discovery stage, we employed genome-wide DNA methylation profiling (Illumina 450K) in peripheral blood mononuclear cells to test whether DNA methylation associates with psychotic symptoms and function state in representative SCZ and methamphetamine-induced psychotic disorder (MIP) patients. Then, we found seven differentially methylated regions/genes (DMRs, in UBA6, APOL3, KIF17, MLLT3, GRM8, CSNK1E, SETDB1) overlapping with genetic variants reported in previous studies of psychosis. In the validation stage, we compared the above-mentioned seven genes by MethLight qPCR method in Chinese Han males (N = 109 SCZ patients, N = 99 methamphetamine use disorder with MIP patients, N = 150 methamphetamine use disorder without MIP patients, N = 282 normal controls, age range: 18–50 years). GRM8 showed robustly altered methylation, which has passed rigorous filtration in subsequent validation, suggesting a remarkable contribution to SCZ and MIP. In addition, hypermethylation of GRM8 showed a significant association with the total scores of the Positive Negative Syndrome Scale and WHO disability assessment schedule II in both baseline and follow-up periods. Our findings suggest that increased CpG methylation in the promoter of GRM8 is a potential candidate epigenetic biomarker of psychotic symptoms in transdiagnostic samples of SCZ and MIP.

Classification of psychosis spectrum disorders using graph convolutional networks with structurally constrained functional connectomes

This article considers the problem of classifying individuals in a dataset of diverse psychosis spectrum conditions, including persons with subsyndromal psychotic-like experiences (PLEs) and healthy controls. This task is more challenging than the traditional problem of distinguishing patients with a diagnosed disorder from controls using brain network features, since the neurobiological differences between PLE individuals and healthy persons are less pronounced. Further, examining a transdiagnostic sample compared to controls is concordant with contemporary approaches to understanding the full spectrum of neurobiology of psychoses. We consider both support vector machines (SVMs) and graph convolutional networks (GCNs) for classification, with a variety of edge selection methods for processing the inputs. We also employ the MultiVERSE algorithm to generate network embeddings of the functional and structural networks for each subject, which are used as inputs for the SVMs. The best models among SVMs and GCNs yielded accuracies >63%. Investigation of network connectivity between persons with PLE and controls identified a region within the right inferior parietal cortex, called the PGi, as a central region for communication among modules (network hub). Class activation mapping revealed that the PLE group had salient regions in the dorsolateral prefrontal, orbital and polar frontal cortices, and the lateral temporal cortex, whereas the controls did not. Our study demonstrates the potential usefulness of deep learning methods to distinguish persons with subclinical psychosis and diagnosable disorders from controls. In the long term, this could help improve accuracy and reliability of clinical diagnoses, provide neurobiological bases for making diagnoses, and initiate early intervention strategies.

Assessing social anhedonia in a transdiagnostic sample: Insights from a computational psychiatry lens.

Anhedonia, a reduced ability to experience positive affect and seek rewards, is present across many psychiatric disorders, notably among individuals who experienced trauma. Within the social domain, anhedonia manifests as an altered sense of belonging and social isolation and is associated with poorer clinical outcomes. Yet, mechanistic operationalizations of social anhedonia are lacking, limiting our understanding of the relationship between these mechanisms and affective symptoms. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. To address these questions, we developed a social reward exploration task which was administered to a transdiagnostic sample of trauma-exposed Veterans (N = 33) while they underwent functional magnetic resonance imaging. The goal was to maximize compliments from two unknown partners, as participants were told these partners selected compliments based on seeing their picture. A Bayesian reinforcement learning modeling approach was used to extract cognitive and neural markers of compliment (reward) exploration. Higher social connectedness (β = 0.51; 95 % CI=[0.11,0.94]) and anxiety (β = 0.57; 95 % CI=[0.13,1.00]) were independently associated with more model-based choices of the partner they anticipated to be most complimenting. In the dorsal anterior cingulate cortex (ACC; z = 3.89, p .001) and left inferior parietal lobule (z = 3.96, p .001), neural responses to reward prediction errors (RPE) were more positive in response to compliment relative to non-compliment outcomes. Greater positive RPE ACC activation was associated with lower anxiety (β = −0.51; 95 % CI=[−0.99,−0.10]. Computational approaches to social reinforcement learning can help identify important neurocognitive differences in social reward sensitivity among individuals with complex affective profiles, such as trauma-exposed individuals. Understanding these differences may help develop new prediction and treatment tools for social anhedonia.

Symptom network analysis of parent-child depression and anxiety in treatment-seeking youth.

Youth of parents who are experiencing psychopathology are more likely to develop emotional concerns, and these mental health symptoms can have a deleterious impact on parents' mental health. However, the relationship between the presentation of specific symptoms in parents and youth is infrequently examined. Symptom network analysis is an analytic approach that is increasingly being used to better understand the relationship of symptoms within and between disorders and can also be used to examine symptom relations within a dyad. The present study used symptom network analysis to examine bidirectional relationships among depressive and anxiety psychopathology in a transdiagnostic sample of treatment-seeking youth and their primary caregiver. Parental anhedonia and child worthlessness exhibited the greatest centrality within the network, suggesting that these may act as risk and maintenance factors for parent-child psychopathology and may be important intervention targets. Findings support the use of symptom network analysis to inform an understanding of the complex relationships among parent and child depressive and anxiety symptoms. Future research should consider the use of network analytic methods to examine the temporal relationships between parent and child psychopathology and to inform joint parent-child interventions for those with internalizing concerns. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Insulin Resistance, Temperament and Personality Traits Are Associated with Anhedonia in a Transdiagnostic Sample.

Anhedonia constitutes a core symptom of major depressive disorder (MDD) mediating the ultimate goal of MDD treatment: functional remission. Anhedonia is also present in other clinical populations, including patients with chronic pain. Recent data links anhedonia to insulin resistance (IR). Some researchers have underlined a different dimension of anhedonia as a temperament/personality trait. The objective of this post-hoc analysis was to explore the links between anhedonia (main outcome) and (1) IR, (2) temperamental, personality, and schizotypy traits (exposures). The study population included patients with MDD, fibromyalgia, and healthy controls. Participants were split into groups: (1) insulin resistant (IR[+] n = 69, HOMA-IR ≥ 2.1) and (2) insulin sensitive (IR[-] n = 69, HOMA-IR < 2.1). Anhedonia was significantly higher in the IR[+] group than the IR[-] group. IR was a predictor of higher anhedonia levels. IR[+] vs. IR[-] participants showed higher levels of anxiety and lower levels of hyperthymic affective temperaments, as well as conscientiousness and emotional stability personality traits. Depressive, irritable, and anxious temperaments, cognitive disorganization, and introvertive anhedonia positively predicted anhedonia, while hyperthymic temperament, conscientiousness, extraversion, and emotional stability traits negatively predicted anhedonia. IR partially mediated the relationship between depressive temperament and anhedonia. In sum, IR, affective temperaments, and personality traits are predictors of anhedonia.

Network state dynamics underpin basal craving in a transdiagnostic population.

Emerging fMRI methods quantifying brain dynamics present an opportunity to capture how fluctuations in brain responses give rise to individual variations in affective and motivation states. Although the experience and regulation of affective states affect psychopathology, their underlying time-varying brain responses remain unclear. Here, we present a novel framework to identify network states matched to an affective experience and examine how the dynamic engagement of these network states contributes to this experience. We apply this framework to investigate network state dynamics underlying basal craving, an affective experience with important clinical implications. In a transdiagnostic sample of healthy controls and individuals diagnosed with or at risk for craving-related disorders (total N = 252), we utilized connectome-based predictive modeling (CPM) to identify brain networks predictive of basal craving. An edge-centric timeseries approach was leveraged to quantify the moment-to-moment engagement of the craving-positive and craving-negative subnetworks during independent scan runs. We found that dynamic markers of network engagement, namely more persistence in a craving-positive network state and less dwelling in a craving-negative network state, characterized individuals with higher craving. We replicated the latter results in a separate dataset, incorporating distinct participants (N = 173) and experimental stimuli. The associations between basal craving and network state dynamics were consistently observed even when craving-predictive networks were defined in the replication dataset. These robust findings suggest that network state dynamics underpin individual differences in basal craving. Our framework additionally presents a new avenue to explore how the moment-to-moment engagement of behaviorally meaningful network states supports our affective experiences.

A Transdiagnostic Network Analysis of Childhood Trauma and Psychopathology.

Psychiatric comorbidities suggest that symptoms overlap across different diagnoses; the transdiagnostic network approach is valuable for studying psychopathology. Childhood trauma is a common transdiagnostic risk factor for psychiatric disorders, but the complex relationship between childhood trauma and psychopathology has seldom been investigated using a large cross-sectional transdiagnostic sample. This study recruited 869 patients with different diagnoses, including 418 schizophrenia, 215 bipolar disorder, and 236 major depressive disorder. Participants completed psychiatric interviews and self-report questionnaires. We constructed dimension- and item-level Least Absolute Shrinkage and Selection Operator-based (LASSO) networks to explore the relationship between childhood trauma, psychopathology, and duration of illness. Moreover, we constructed directed acyclic graphs (DAGs) to tentatively clarify the potential directions of associations among these variables. Network Comparison Tests (NCTs) were conducted for different diagnostic groups and gender-stratified groups. The transdiagnostic LASSO networks showed that different types of childhood trauma exerted distinct impacts on various psychopathological dimensions. Emotional abuse was linked to depressive symptoms, physical abuse to excited symptoms, sexual abuse to positive and disorganized symptoms, emotional neglect to depressive symptoms and motivation and pleasure (MAP) deficits factor of negative symptoms, and physical neglect to MAP factor. The DAG findings generally concurred with the LASSO network. The NCT showed comparable networks. Our findings suggest that childhood trauma is significantly associated with the development of psychopathology across different diagnostic groups. The affective pathway model suggests that early identification and tailored interventions would be needed for people with a history of childhood trauma.

Predictors of psychosocial impairment in a transdiagnostic sample: Unique effects of repetitive negative thinking

BackgroundRepetitive negative thinking (RNT) is a transdiagnostic process involving perseverative, unproductive, and uncontrollable thoughts. Although RNT may impede adaptive psychosocial functioning by prolonging negative mood states, strengthening cognitive biases, and preventing effective problem-solving, the extent to which RNT is associated with risk for poor psychosocial outcomes is unclear. Given that this has clear transdiagnostic treatment implications, the present study aimed to isolate the unique relationship of RNT with social functioning and life satisfaction in a mixed clinical and non-clinical sample. MethodsIn 201 mid-to-later life adult participants (27 with primary diagnoses of bipolar disorder, 84 with major depressive disorder, and 90 healthy volunteers), we measured RNT, social functioning, life satisfaction, trait rumination, DSM-5 diagnoses, depressive symptoms, manic symptoms, cognitive control performance, and global cognitive functioning. ResultsLinear regression models revealed that RNT, but not rumination, was significantly associated with poorer social functioning (β = 0.42 p < .001) and reduced life satisfaction (β = −0.42, p < .001) after controlling for clinical and cognitive covariates. LimitationsLimited demographic diversity, cross-sectional design, self-reporting of outcomes. ConclusionsResults suggest that RNT may confer risk for key psychosocial outcomes during middle to later adulthood, over and above the effects of clinical and cognitive variables and independent of diagnostic status. Findings lend support to the notion of RNT as a transdiagnostic process and suggest that RNT may be an important therapeutic target for adults with poor social functioning and/or reduced life satisfaction.

Narrative identity disturbances in psychopathology: An ecologically valid transdiagnostic framework.

This article presents an ecologically valid transdiagnostic framework regarding narrative identity disturbances in psychopathology. Problems with self and identity are distressing, disruptive to everyday functioning, and central to theoretical models of recovery. Yet these problems are sorely understudied, in part due to differences in concepts, theories, and measurement models across disorder-specific literatures. Disorder-specific theories are useful for understanding the etiology of disturbances to self and identity. However, while root causes may vary across disorders, their effects on explicit, conscious, reflective experience share important transdiagnostic parallels. These problems affect the extended sense of self as an individual with memories, a present identity, and future expectancies. By extension, these problems are developmental, reflecting an ever-evolving conception of oneself across the life course. Finally, these problems are contextual and intersubjective, constructed over time through interactions with others in the family, community, and society. A unified transdiagnostic model for reflective self-disturbances should therefore be idiographic and grounded in developmental and personality theory, with a strong emphasis on ecological validity. Narrative identity is emerging as a coherent, cross-cutting framework for understanding problems with self and identity across diagnostic boundaries. Important current research directions include transdiagnostic samples and clinical control groups; more diverse samples; expanding on the latent structure of narrative identity in clinical populations, and developing new assessment techniques to supplement trained raters. These directions will further enhance narrative identity's utility for idiographic, developmental, and ecologically valid clinical research. (PsycInfo Database Record (c) 2024 APA, all rights reserved).