Network analysis of the Quick Inventory of Depressive Symptomatology: Reanalysis of the STAR*D clinical trial

Madhoo, Manisha; Levine, Stephen Z.

doi:10.1016/j.euroneuro.2016.09.368

Cited by 42 publications

(46 citation statements)

References 29 publications

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“…Therefore, a systematic review may provide a good main entrance to this field of studies. Although NA in certain cases provides expected results, like the fact that sadness is an almost ubiquitous central symptom in depression [42, 43, 52], the results of the present review supports the idea that NA adds information that the traditional classification models do not incorporate [88]. For instance, our review shows the potential capacity of NA in identifying unexpected associations between symptoms [28].…”

Section: Discussionsupporting

confidence: 63%

“…It was found that patients with persistent depression showed stronger associations between depressive symptoms than those in remission, supporting the idea that the strength of connections is associated to vulnerability [42]. Likewise, Madhoo and Levine [43] reported that the connectivity among symptoms significantly diminished after an intervention. Several studies have used ESM to collect time-series data in depressed participants, although, the outcomes assessed are heterogeneous.…”

Section: Resultsmentioning

confidence: 66%

“…Central nodes are largely interconnected to other nodes and their variations are more likely to affect the other nodes in the network. It has been proposed that identifying central nodes would be valuable in identifying important symptoms and in guiding which symptoms should be given priority in interventions [11, 16, 24, 38, 42, 43]. Moreover, centrality indexes may also be helpful in making predictions about recovery and prognosis.…”

Section: Discussionmentioning

confidence: 99%

“…For instance, our review shows the potential capacity of NA in identifying unexpected associations between symptoms [28]. In the case of depression, NA has shown that a low level of energy often emerges as a core symptom in mood-related disorders, which may predict the onset of major depression [52], albeit it is important to consider that the centrality of symptoms may vary at different time points through the course of the problem [43]. Though “fatigue” or “loss of energy” are not DSM symptoms, they emerged as central symptoms in depression [52] and bipolar patients [55].…”

Section: Discussionmentioning

confidence: 99%

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The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

Contreras

Nieto

Valiente

et al. 2019

Psychother Psychosom

307

214

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Background: Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. Methods: Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of “network analysis” with the terms “anxiety,” “affective disorders,” “depression,” “schizophrenia,” “psychosis,” “personality disorders,” “substance abuse” and “psychopathology.” Results: The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. Conclusions: A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

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Section: Discussionsupporting

confidence: 63%

Section: Resultsmentioning

confidence: 66%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

Contreras

Nieto

Valiente

et al. 2019

Psychother Psychosom

307

214

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“…Our study had several limitations as follows: First, the estimated network structures can change within the clinical course of depressive disorders. Reanalysis of the STAR*D clinical trial has reported that, whereas energy‐related symptoms are the most centrally situated at baseline, mood‐related symptoms are the most centrally situated at the end‐point . However, in our study, depressive disorder patients with any clinical course were included as study participants.…”

Section: Discussionmentioning

confidence: 99%

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)

Park

Jang

Xiang³

et al. 2020

Psychiatry Clin Neurosci

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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.

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Implications of the Network Theory for the Treatment of Mental Disorders

Schumacher,

Klein,

Elsaesser

et al. 2023

JAMA Psychiatry

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ImportanceConceptualizing mental disorders as latent entities has been challenged by the network theory of mental disorders, which states that psychological problems are constituted by a network of mutually interacting symptoms. While the implications of the network approach for planning and evaluating treatments have been intensively discussed, empirical support for the claims of the network theory regarding treatment effects is lacking.ObjectiveTo assess the extent to which specific hypotheses derived from the network theory regarding the (interindividual) changeability of symptom dynamics in response to treatment align with empirical data.Design, Setting, and ParticipantsThis secondary analysis entails data from a multisite randomized clinical trial, in which 254 patients with chronic depression reported on their depressive symptoms at every treatment session. Data collection was conducted between March 5, 2010, and October 14, 2013, and this analysis was conducted between November 1, 2021, and May 31, 2022.InterventionThirty-two sessions of either disorder-specific or nonspecific psychotherapy for chronic depression.Main Outcomes and MeasuresLongitudinal associations of depressive symptoms with each other and change of these associations through treatment estimated by a time-varying longitudinal network model.ResultsIn a sample of 254 participants (166 [65.4%] women; mean [SD] age, 44.9 [11.9] years), symptom interactions changed through treatment, and this change varied across treatments and individuals. The mean absolute (ie, valence-ignorant) strength of symptom interactions (logarithmic odds ratio scale) increased from 0.40 (95% CI, 0.36-0.44) to 0.60 (95% CI, 0.52-0.70) during nonspecific psychotherapy and to 0.56 (95% CI, 0.48-0.64) during disorder-specific psychotherapy. In contrast, the mean raw (ie, valence-sensitive) strength of symptom interactions decreased from 0.32 (95% CI, 0.28-0.36) to 0.26 (95% CI, 0.20-0.32) and to 0.09 (95% CI, 0.02-0.16), respectively. Changing symptom severity could be explained to a large extent by symptom interactions.Conclusions and RelevanceThese findings suggest that specific treatment-related hypotheses of the network theory align well with empirical data. Conceptualizing mental disorders as symptom networks and treatments as measures that aim to change these networks is expected to give further insights into the working mechanisms of mental health treatments, leading to the improvement of current and the development of new treatments.Trial RegistrationClinicalTrials.gov Identifier: NCT00970437

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Network analysis of the Quick Inventory of Depressive Symptomatology: Reanalysis of the STAR*D clinical trial

Cited by 42 publications

References 29 publications

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

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)

Implications of the Network Theory for the Treatment of Mental Disorders

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