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

Gunzler, Douglas D.; Sehgal, Ashwini R.; Kauffman, Kelley; Davey, Christine Horvat; Dolata, Jacqueline; Figueroa, Maria; Huml, Anne M.; Pencak, Julie; Sajatovic, Martha

doi:10.1016/j.psychres.2020.112872

Cited by 14 publications

(13 citation statements)

References 41 publications

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“…Third, the two-factor model could be better interpreted as different symptomatic representation and subtypes of MDD than the unidimensional model [ 50 , 51 ]. A number of empirical studies used machine learning, genetic, and biological approaches to yield strong evidence in favor of MDD consisting of somatic and affective/cognitive factors, rather than one “depression” factor [ 51 – 53 ]. It is interesting that the best fitting model in this study contradicted the results of Elhai et al (2012), Petersen et al (2015) and Mordeno et al (2018).…”

Section: Discussionmentioning

confidence: 99%

“…The concentrating difficulties and psychomotor agitation/retardation loaded on the cognitive/affective factor in the current study. Papakostas (2013) reported that concentration difficulties and the psychomotor agitation/retardation symptoms reflected deficits in cognitive functions, and subsequent research using the Research Domain Criteria (RDoC) framework confirmed that these two symptoms should be classified in cognitive and sensorimotor systems [ 53 , 54 ]. Moreover, two recent CFA studies have found similar conclusions in adults with autism and in the general US population [ 55 , 56 ].…”

Section: Discussionmentioning

confidence: 99%

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

Wang

Cao

et al. 2021

BMC Psychiatry

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

Wang

Cao

et al. 2021

BMC Psychiatry

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“…Depression is a heterogeneous mental health issue rather than a single condition. 1,2 The DSM-5 identifies nine symptoms of major depressive disorder: (1) depressed mood, (2) anhedonia, (3) change in weight/ appetite, (4) insomnia/hypersomnia, (5) psychomotor agitation, (6) fatigue, (7) feelings of worthlessness, (8) concentration difficulty, and (9) recurrent suicidal ideation. 3 Depressed mood and anhedonia are core symptoms and diagnostic criteria for major depressive disorder.…”

Section: Introductionmentioning

confidence: 99%

“…6 Given the heterogeneity of depression, most rating assessment tools, such as the Patient Health Questionnaire (PHQ-9), are multifactorial and do not measure one underlying construct. 6 Recently, there has been an emerging effort to map nine items in the PHQ into the Research Domain Criteria (RDoC) model, 2 a research initative developed by the National Institute of Mental Health in the United States to conceptualize mental disorder symptoms and diagnoses as dysfunctions of brain circuitry that can be further linked to observable impairment. 7 The RDoC has been considered a transformative initative to facilitate health practitioners to better understand mechanisms underlying mental disorders and optimize mental health interventions and care resource allocation in public health.…”

Section: Introductionmentioning

confidence: 99%

“…8 Under the RDoC, depressive symptoms includes Negative Valence Systems and Externalizing (NVSE; anhedonia and depressed mood), Negative Valence Systems and Internalizing (NVSI; guilt and self-harm), Arousal and Regulatory Systems (ARS; sleep, fatigue, and appetite), and Cognitive and Sensorimotor Systems (CSS; concentration and psychomotor). 2 Older adults with different symptom clusters may display various care utilization patterns because different symptom clusters signal different types of functional impairment. A previous study found that individual depressive symptoms were differently associated with different domains of psychosocial functioning (e.g., home management, social activities) and that depressed mood and concentration problems had the largest associations with functioning impairment.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang¹,

Liu²,

Leung³

et al. 2021

Int J Geriat Psychiatry

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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 nonpsychiatric 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.

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

Zhou,

Zhu,

et al. 2024

Journal of Affective Disorders

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

Cited by 14 publications

References 41 publications

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

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

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

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

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