Identify depressive phenotypes by applying RDOC domains to the PHQ-9

Investigating the PHQ-9 With Mokken Scale Analysis and Cognitive Interviews

Scores on the Patient Health Questionnaire-9 (PHQ-9) are frequently used to assess depression both in research and in clinical practice. The aim was to examine the validity of the PHQ-9 sum score by using Mokken scale analysis (Study I) and cognitive interviews (Study II) on the Icelandic version of PHQ-9. A primary care sample of 618 individuals was used in Study I. The results indicate that the PHQ-9 items are not close enough to perfectly unidimensional for their sum score to accurately order people on the depression severity dimension. In Study II, the sample consisted of 53 individuals, with 28 having a history of depression and 25 not. The findings reveal a number of issues concerning respondents' use of the PHQ-9. No systematic differences were found in the results of the two groups. The PHQ-9 sum score should thus be interpreted and used with great care. We provide scale revision recommendations to improve the quality of PHQ-9.

Familial risk for depression is associated with reduced physical activity in young adults: evidence from a wrist-worn actigraphy study

Depression is characterized by reduced physical activity and sleep-wake cycle disturbances, often considered important features of the disease. While a few studies have suggested that self-reported reduced physical activity and sleep-wake cycle disturbances might both be linked to depression vulnerability, actigraphy-based measures in vulnerable samples remain largely unexplored. This study relied on actigraphy-based parameters to test whether these disturbances characterize depression vulnerability. Seven-day actigraphy data were collected from 20 (13 female) university students with a high vulnerability to depression, which was determined by the presence of a family history of the condition but no current symptoms, and 32 (21 female) controls with neither a family history of depression nor current depressive symptoms. Daily physical activity, namely gross motor activity, was quantified as average daily acceleration and time spent engaging in moderate-vigorous physical activity (MVPA). The sleep-wake cycle and circadian rhythms were assessed as total sleep duration per night (in hours), sleep within sleep period time (in hours), sleep efficiency (%), and relative amplitude (i.e., the difference between the activity during the day and the night, which reflects circadian rhythms amplitude). Results showed that individuals with a familial risk for depression exhibited reduced daily acceleration and time spent in MVPA relative to the control group, particularly on the weekend during their free time away from scheduled activities. On the other hand, the two groups were comparable in terms of sleep estimates. Taken together, reduced physical activity, but not sleep-wake disturbances, seem to be associated with vulnerability to depression and might be a viable target for identification and prevention efforts.

Identifying a stable and generalizable factor structure of major depressive disorder across three large longitudinal cohorts

The Patient Health Questionnaire 9 (PHQ-9) is the current standard outpatient screening tool for measuring and tracking the nine symptoms of major depressive disorder (MDD). While the PHQ-9 was originally conceptualized as a unidimensional measure, it has become clear that MDD is not a monolithic construct, as evidenced by high comorbidities with other theoretically distinct diagnoses and common symptom overlap between depression and other diagnoses. Therefore, identifying reliable and temporally stable subfactors of depressive symptoms could allow research and care to be tailored to different depression phenotypes. This study improved on previous factor analysis studies of the PHQ-9 by leveraging samples that were clinical (participants with depression only), large (N = 1483 depressed individuals in total), longitudinal (up to 5 years), and from three diverse (matching racial distribution of the United States) datasets. By refraining from assuming the number of factors or item loadings a priori, and thus utilizing a solely data-driven approach, we identified a ranked list of best-fitting models, with the parsimonious one achieving good model fit across studies at most timepoints (average TLI >= 0.90). This model categorizes the PHQ-9 items into four factors: (1) Affective (Anhedonia + Depressed Mood), (2) Somatic (Sleep + Fatigue + Appetite), (3) Internalizing (Worth/Guilt + Suicidality), (4) Sensorimotor (Concentration + Psychomotor), which may be used to further precision psychiatry by testing factor-specific interventions in research and clinical settings.

Abnormal changes of dynamic topological characteristics in patients with major depressive disorder

BACKGROUND

Most studies have detected abnormalities of static topological characteristics in major depressive disorder (MDD). However, whether dynamic alternations in brain topology are influenced by MDD remains unknown.

METHODS

An approach was proposed to capture the dynamic topological characteristics with sliding-window and graph theory for a large data sample from the REST-meta-MDD project.

RESULTS

It was shown that patients with MDD were characterized by decreased nodal efficiency of the left orbitofrontal cortex. The temporal variability of topological characteristics was focused on the left opercular part of inferior frontal gyrus, and the right part of middle frontal gyrus, inferior parietal gyrus, precuneus and thalamus.

LIMITATIONS

Future studies need larger and diverse samples to explore the relationship between dynamic topological network characteristics and MDD symptoms.

CONCLUSIONS

The results support that the altered dynamic topology in cortex of frontal and parietal lobes and thalamus during resting-state activity may be involved in the neuropathological mechanism of MDD.

Using the Research Domain Criteria as a framework to integrate psychophysiological findings into stress management and psychotherapy interventions

Research on the psychophysiology of stress is expanding rapidly, but the field lacks a clear integrative framework to help translate research findings into empirically supported stress interventions. The Research Domain Criteria (RDoC) is an excellent candidate to explore as a framework to integrate stress research. The RDoC framework is a dimensional, multi-modal approach to psychopathology proposed as an alternative to categorical approaches used by the International Classification of Diseases (ICD) and the Diagnostic and Statistical Manual (DSM). The goal of this paper is to explore the RDoC as a framework to integrate psychophysiology research into therapeutic interventions for stress. The RDoC consists of six domains: negative valence systems, positive valence systems, cognitive systems, social processes systems, arousal/regulatory systems, and sensorimotor systems, and provides an excellent structure for integrating information from multiple levels of functioning including physiology, behavior, and self-report, as well as genes, molecules, cells, and brain circuits. Integrating psychophysiological research on stress using the RDoC framework can direct and amplify stress management and psychotherapeutic interventions. First, the RDoC provides a clear foundation for conceptualizing the stress response in terms of important concepts such as allostasis and adaptation. In this perspective, the terms "allostatic response" or "adaptation response" are more descriptive terms than "stress response" in understanding bodily responses to life threats and challenges. Second, psychophysiological approaches can be used in the context of modalities such as biofeedback and mindfulness to both collect psychophysiological data and then integrate that data into a broader therapeutic framework. Heart rate variability (HRV) biofeedback is being used more frequently as part of a therapeutic intervention package with stress management and psychotherapy, and HRV data is also used to provide outcome evidence on the efficacy of treatment. Mindfulness practices are commonly used in combination with stress management and psychotherapy, and psychophysiological data (HRV, EEG, blood pressure, etc.) is often collected to explore and understand mind/body relationships. In conclusion, the lack of a clear framework to assess and understand mind/body functioning limits current stress research and interventions. The RDoC provides a strong framework to assess and integrate physiological and psychological data and improve stress interventions.

Differential Associations Between Depressive Symptom-Domains With Anxiety, Loneliness, and Cognition in a Sample of Community Older Chinese Adults: A Multiple Indicators Multiple Causes Approach

Background and Objectives

Depressive symptoms are common in older adults, and often co-occur with other mental health problems. However, knowledge about depressive symptom-domains and their associations with other conditions is limited. This study examined depressive symptom-domains and associations with anxiety, cognition, and loneliness.

Research Design and Methods

A sample of 3,795 participants aged 60 years and older were recruited from the community in Hong Kong. They were assessed for depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]), anxiety (Generalized Anxiety Disorder 7-item), loneliness (UCLA 3-item), and cognition (Montreal Cognitive Assessment 5-Minute Protocol). Summary descriptive statistics were calculated, followed by confirmatory factor analysis of PHQ-9. Multiple Indicators Multiple Causes analysis was used to examine the associations between mental health conditions in the general sample and subgroups based on depressive symptom severity.

Results

A 4-factor model based on the Research Domain Criteria showed the best model fit of PHQ-9 (χ2/df = 10.63, Root-Mean-Square Error of Approximation = 0.05, Comparative Fit Index = 0.96, Tucker-Lewis Index = 0.93). After adjusting for demographics, 4 depressive symptom-domains were differentially associated with anxiety, loneliness, and cognition across different depression severity groups. The Negative Valance Systems and Internalizing domain (NVS-I; guilt and self-harm) were consistently associated with anxiety (β = 0.45, 0.44) and loneliness (β = 0.11, 0.27) regardless of depression severity (at risk/mild vs moderate and more severe, respectively, all p < .001).

Discussion and Implications

The consistent associations between the NVS-I domain of depression with anxiety and loneliness warrant attention. Simultaneous considerations of depressive symptom-domains and symptom severity are needed for designing more personalized care.

Clinical Trials Registration Number

NCT03593889.

Mood and anxiety disorders within the Research Domain Criteria framework of Positive and Negative Valence Systems: a scoping review

Introduction

While a growing body of research is adopting Research Domain Criteria (RDoC)-related methods and constructs, there is still a lack of comprehensive reviews on the state of published research on Positive Valence Systems (PVS) and Negative Valence Systems (NVS) in mood and anxiety disorders consistent with the RDoC framework.

Methods

Five electronic databases were searched to identify peer-reviewed publications covering research on "positive valence" and "negative valence" as well as "valence," "affect," and "emotion" for individuals with symptoms of mood and anxiety disorders. Data was extracted with a focus on disorder, domain, (sub-) constructs, units of analysis, key results, and study design. Findings are presented along four sections, distinguishing between primary articles and reviews each for PVS, NVS, and cross-domain PVS and NVS.

Results

A total of 231 abstracts were identified, and 43 met the inclusion criteria for this scoping review. Seventeen publications addressed research on PVS, seventeen on NVS, and nine covered cross-domain research on PVS and NVS. Psychological constructs were typically examined across different units of analysis, with the majority of publications incorporating two or more measures. Molecular, genetic, and physiological aspects were mainly investigated via review articles, primary articles focused on self-report, behavioral, and, to a lesser extent, physiological measures.

Conclusions

This present scoping review shows that mood and anxiety disorders were actively studied using a range of genetic, molecular, neuronal, physiological, behavioral, and self-report measures within the RDoC PVS and NVS. Results highlight the essential role of specific cortical frontal brain structures and of subcortical limbic structures in impaired emotional processing in mood and anxiety disorders. Findings also indicate overall limited research on NVS in bipolar disorders and PVS in anxiety disorders, a majority of self-report studies, and predominantly observational studies. Future research is needed to develop more RDoC-consistent advancements and intervention studies targeting neuroscience-driven PVS and NVS constructs.

Factor Analysis of the Beck Depression Inventory-II and Long-Term Hematopoietic Stem Cell Transplantation Survival Using the Research Domain Criteria Framework

The presence of depressive symptoms prior to hematopoietic stem cell transplantation (HSCT) is a common experience, with long-term impacts on survival. Using the National Institute of Mental Health Research Domain Criteria (RDoC) framework, this study sought to characterize depressive symptoms in patients prior to HSCT through exploratory factor analysis and to determine whether depressive factors were significant predictors of long-term survival. Individuals were included in the study if they were preparing to undergo HSCT and endorsed depressive symptoms measured by the Beck Depression Inventory-II (BDI-II). Patients were scheduled to undergo transplantation between 2005 and 2010. Survival analyses were conducted in 2022 to assess long-term outcomes. The primary outcomes were exploring the factor structure of the BDI-II and conducing univariate and multivariate Cox regression analyses of depression symptoms and known demographic and disease characteristics that impact survival. Of the 695 participants included in the study, most were male, middle aged (mean age, 55.08 ± 11.75 years), white, and married. Exploratory factor analysis revealed a 4-factor structure consisting of "negative valence systems: internalizing" (eg, worthlessness, guilt), "arousal and threat" (eg, agitation, irritability), "arousal and regulatory systems" (eg, loss of energy, fatigue), and "negative valence systems: externalizing" (eg, loss of pleasure, loss of interest). Univariate survival analyses identified age, sex, disease type, acute graft-versus-host disease (GVHD), and negative valence systems: externalizing as significant predictors of survival. Transplant type, chronic GVHD, performance status, and the other 3 depression factor structures were not significant in univariate models. In the multivariate model, older age (hazard ratio [HR], 1.031; 95% confidence interval [CI], 1.021 to 1.041; P < .001) and presence of negative valence systems: externalizing symptoms (HR, 1.132; 95% CI, 1.030 to 1.244; P = .010) were significant predictors of shorter survival. Additionally, individuals diagnosed with acute leukemia were significantly more likely to have shorter survival compared to those with other disease types, including amyloidosis (HR, .362; 95% CI, .229 to .575; P < .001) and non-Hodgkin lymphoma (HR, .526; 95% CI, .349 to .793; P = .002). Exploratory factor analysis of depressive symptoms mapped well onto the RDoC constructs. Loss of pleasure and loss of interest, two key components of depression, were predictive of shorter survival. Exploration of key components of depression rather than the total depression score may provide important prognostic information for long-term survivorship and may help inform future and more individualized care.

Rethinking the risk for depression using the RDoC: A psychophysiological perspective

Considering that the classical categorical approach to mental disorders does not allow a clear identification of at-risk conditions, the dimensional approach provided by the Research Domain Criteria (RDoC) is useful in the exploration of vulnerability to psychopathology. In the RDoC era, psychophysiological models have an important role in the reconceptualization of mental disorders. Indeed, progress in the study of depression vulnerability has increasingly been informed by psychophysiological models. By adopting an RDoC lens, this narrative review focuses on how psychophysiological models can be used to advance our knowledge of the pathophysiological mechanisms underlying depression vulnerability. Findings from psychophysiological research that explored multiple RDoC domains in populations at-risk for depression are reviewed and discussed. Future directions for the application of psychophysiological research in reaching a more complete understanding of depression vulnerability and, ultimately, improving clinical utility, are presented.

Disentangling self-reported fatigue, depression, and cognitive impairment in people with multiple sclerosis

BACKGROUND

Fatigue is a common problem among people with multiple sclerosis (MS) and can have a negative effect on mental, physical, and social function. Self-reported measures of MS fatigue are often operationalized as a multi-dimensional symptom. However, questions remain about how best to account for the multi-dimensional aspects of self-reported fatigue and whether these aspects are distinct entities. Thus, the purpose of this study was to explore the overlap and distinctions between self-reported measures of the severity and impact of fatigue, between mental and physical fatigue, and between mental fatigue, depressive symptoms, and cognitive impairment.

METHODS

An observational study was conducted with 289 participants with MS . The questionnaires were the Unidimensional Fatigue Impact Scale (UFIS), the Chalder Fatigue Scale (CFS), the Fatigue Scale for Motor and Cognitive Functions (FSMC), the Multiple Sclerosis Neuropsychological Screening Questionnaire (MSNSQ), and the Quality of Life in Neurological Disorders short form for depression (Neuro-QoL). Spearman's correlation coefficient was used to examine the bivariate correlations between composite and subscale scores. Exploratory structural equation modeling (ESEM) was used to determine the factor structure under a pre-specified number of factors to retain in the modeling of multiple items across questionnaires and examine model fit. Subsequently for poor fitting models in an iterative procedure to determine a better fitting multidimensional model, we posited a bifactor confirmatory factor analysis model.

RESULTS

The bivariate correlation analysis revealed that subscales from the same questionnaire measuring different aspects of fatigue had the highest correlations (r = 0.61-0.68), subscales from different questionnaires measuring the same aspect of fatigue had the next highest correlations (r = 0.43-0.60), and subscales from different questionnaires measuring different aspects of fatigue had the lowest correlations (r = 0.34-0.40). Bifactor models with a general fatigue factor and subdomains pertaining to impact, severity, and mental and physical fatigue had relatively good model fits compared to models omitting the subdomains. However, an ESEM model using subscales from the CFS and FSMC fit poorly and did not adequately identify separate factors for mental and physical fatigue. An ESEM model with separate factors for self-reported mental fatigue, depressive symptoms, and cognitive impairment was a good fit.

CONCLUSIONS

The working study hypothesis that fatigue constructs would be moderately correlated yet distinct entities was generally supported by the results of the study. However, we found that our hypothesized separation into a latent dimension existed only when the items or subscales came from the same questionnaire, in which case their level of specificity in terms of target, action, context, and time elements for measuring fatigue were consistent. The implications for the principle of compatibility in measuring self-reported MS fatigue are discussed.

Associations between depressive symptom clusters and care utilization and costs among community-dwelling older adults

OBJECTIVES

Whether and how symptom clusters are associated with care utilization remains understudied. This study aims to investigate the economic impact of symptom clusters.

METHODS

We conducted cross-sectional analyses of data collected from 3255 older adults aged 60 years and over in Hong Kong using the Patient Health Questionnaire-9 and the Client Service Receipt Inventory to measure depressive symptoms and service utilization to calculate 1-year care expenditure. Based on Research Domain Criteria framework, we categorized depressive symptoms into four clusters: Negative Valance Systems and Externalizing (NVSE; anhedonia and depression), Negative Valance Systems and Internalizing (guilt and self-harm), Arousal and Regulatory Systems (sleep, fatigue, and appetite), and Cognitive and Sensorimotor Systems (CSS; concentration and psychomotor). Two-part models were used with four symptom clusters to estimate economic impacts on care utilization.

RESULTS

Core affective symptoms had the largest economic impact on non-psychiatric care expenditure; a one-point increase in NVSE was associated with USD$ 571 additional non-psychiatric care expenditure. The economic impacts of CSS on non-psychiatric care expenditure was attenuated when the severity level of NVSE was higher.

CONCLUSIONS

Our findings highlight the importance of understanding economic impacts on care utilization based on symptom profiles with a particular emphasis on symptom combinations. Policymakers should optimize care allocation based on older adults' depressive symptom profiles rather than simply considering their depression sum-score or the severity defined by cut-off points.

The factor structure of major depressive symptoms in a sample of Chinese earthquake survivors

BACKGROUND

Experiencing natural disasters is associated with common mental disorders including major depressive disorder (MDD). However, the latent structure of MDD is widely debated, and few studies tested the MDD factor structure in Chinese natural disaster survivors. Therefore, the aim of the current study was to evaluate the factorial validity of the Patient Health Questionnaire-9 (PHQ-9) for DSM-5 major depressive disorder (MDD) symptoms in Chinese earthquake survivors.

METHOD

Participants were 1058 Chinese earthquake survivors. Self-reported measures included the PHQ-9 and the Short-Form Health Survey (SF-36). Confirmatory factor analysis (CFA) and structural equation modelling (SEM) was used to examine the latent structure of MDD and the associations between latent factors of MDD and different domains of health-related quality of life (HRQoL), respectively.

RESULTS

In the current sample, the model consisted of somatic and cognitive/affective (non-somatic) factors demonstrated significantly better fit than the other competing MDD models (χ² = 173.89, df = 26, CFI = 0.986, TLI = 0.981, RMSEA = 0.073, BIC = 18,091.13). Further SEM analyses indicated that the non-somatic factor was significantly related to both physical (β = - 0.362, p < .01) and psychosocial HRQoL (β = - 0.773, p < .01), while the somatic factor was a uniquely predictor of physical HRQoL (β = - 0.336, p < .01). Furthermore, we found the somatic factor partially mediated the relationship between the cognitive/affective factor and physical HRQoL (all ps < .05).

CONCLUSIONS

The MDD symptoms was best captured by a two-factor model comprised of somatic and cognitive/affective factors in Chinese natural disaster survivors. The two MDD factors were differentially associated with physical and psychosocial HRQoL, and the cognitive/affective factor associated physical HRQoL partially through the somatic factor. The current findings increase our understanding of latent structure of MDD symptoms, and carry implications for assessment and intervention of post-disaster mental health problems.