On the validity of the centrality hypothesis in cross-sectional between-subject networks of psychopathology

Abstract Background In the network approach to psychopathology, psychiatric disorders are considered networks of causally active symptoms (nodes), with node centrality hypothesized to reflect symptoms’ causal influence within a network. Accordingly, centrality measures have been used in numerous network-based cross-sectional studies to identify specific treatment targets, based on the assumption that deactivating highly central nodes would proliferate to other nodes in the network, thereby collapsing the network structure and alleviating the overall psychopathology (i.e., the centrality hypothesis). Methods Here, we summarize three types of evidence pertaining to the centrality hypothesis in psychopathology. First, we discuss the validity of the theoretical assumptions underlying the centrality hypothesis in psychopathology. We then summarize the methodological aspects of extant studies using centrality measures as predictors of symptom change following treatment, while delineating their main findings and several of their limitations. Finally, using a specific dataset of 710 treatment-seeking patients with posttraumatic stress disorder (PTSD) as an example, we empirically examine node centrality as a predictor of therapeutic change, replicating the approach taken by previous studies, while addressing some of their limitations. Specifically, we investigated whether three pre-treatment centrality indices (strength, predictability, and expected influence) were significantly correlated with the strength of the association between a symptom’s change and the change in the severity of all other symptoms in the network from pre- to post-treatment (Δnode-Δnetwork association). Using similar analyses, we also examine the predictive validity of two simple non-causal node properties (mean symptom severity and infrequency of symptom endorsement). Results Of the three centrality measures, only expected influence successfully predicted how strongly changes in nodes/symptoms were associated with change in the remainder of the nodes/symptoms. Importantly, when excluding the amnesia node, a well-documented outlier in the phenomenology of PTSD, none of the tested centrality measures predicted symptom change. Conversely, both mean symptom severity and infrequency of symptom endorsement, two standard non-network-derived indices, were found to be more predictive than expected influence and remained significantly predictive also after excluding amnesia from the network analyses. Conclusions The centrality hypothesis in its current form is ill-defined, showing no consistent supporting evidence in the context of cross-sectional, between-subject networks.

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Does Centrality in a Cross-Sectional Network Suggest Intervention Targets for Social Anxiety Disorder?

10.31234/osf.io/kx6y8 ◽

2018 ◽

Cited By ~ 1

Author(s):

Thomas Rodebaugh ◽

Natasha April Tonge ◽

Marilyn Piccirillo ◽

Eiko I Fried ◽

Arielle Horenstein ◽

...

Keyword(s):

Anxiety Disorder ◽

Social Anxiety ◽

Social Anxiety Disorder ◽

Partial Correlation ◽

State Of The Art ◽

Symptom Change ◽

Cross Sectional ◽

Network Analyses ◽

Treatment Data ◽

Item Properties

Objective: Network analysis allows us to identify the most interconnected (i.e., central) symptoms, and multiple authors have suggested that these symptoms might be important treatment targets. This is because change in central symptoms (relative to others) should have greater impact on change in all other symptoms. It has been argued that networks derived from cross-sectional data may help identify such important symptoms. We tested this hypothesis in social anxiety disorder. Method: We first estimated a state-of-the-art regularized partial correlation network based on participants with social anxiety disorder (N = 910) to determine which symptoms were more central. Next, we tested whether change in these central symptoms were indeed more related to overall symptom change in a separate dataset of participants with social anxiety disorder who underwent a variety of treatments (N = 244). We also tested whether relatively superficial item properties (infrequency of endorsement and variance of items) might account for any effects shown for central symptoms. Results: Centrality indices successfully predicted how strongly changes in items correlated with change in the remainder of the items. Findings were limited to the measure used in the network and did not generalize to three other measures related to social anxiety severity. In contrast, infrequency of endorsement showed associations across all measures. Conclusions: The transfer of recently published results from cross-sectional network analyses to treatment data is unlikely to be straightforward.

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Self-Dislike and Sadness are Central Symptoms of Depression in College Students: A Network Analysis

10.31234/osf.io/fujmb ◽

2018 ◽

Author(s):

Michael C Mullarkey ◽

Rochelle A Stewart ◽

Tony T Wells ◽

Jason Shumake ◽

Christopher G Beevers

Keyword(s):

College Students ◽

Public Health Issue ◽

Depression Symptoms ◽

Symptom Change ◽

Cross Sectional ◽

Network Analyses ◽

Symptoms Of Depression ◽

Highly Correlated ◽

Single Time Point ◽

Time Point

Depression in college students is an important public health issue. There is growing recognition that some depression symptoms may have a more central role in the disorder than others. We use network analyses to identify the most central symptoms of depression in college students. In a cross-sectional network the BDI-SF was collected at a single time point (N = 10,005) and in a symptom change network the BDI-SF was collected at two time points separated on average by approximately two months (N = 700). In both samples, the most central depression symptoms were self-dislike and sadness. Centrality scores for the cross-sectional network were highly correlated (r = .86) with the centrality scores for the symptom change network. Self-dislike and sadness may have important roles in college student depression. Additional work experimentally targeting and changing these central symptoms is needed to determine whether they have a causal role in the disorder.

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Problems with centrality measures in psychopathology symptom networks: Why network psychometrics cannot escape psychometric theory

10.31234/osf.io/pg4mf ◽

2019 ◽

Cited By ~ 1

Author(s):

Michael Hallquist ◽

Aidan G.C. Wright ◽

Peter C. M. Molenaar

Keyword(s):

Latent Variables ◽

Factor Loading ◽

Centrality Measures ◽

Cross Sectional ◽

Network Analyses ◽

Psychometric Theory ◽

Centrality Metrics ◽

Psychopathology Symptom ◽

Weighted Combination ◽

Do So

Understanding patterns of symptom co-occurrence is one of the most difficult challenges in psychopathology research. Do symptoms co-occur because of a latent factor, or might they directly and causally influence one another? Motivated by such questions, there has been a surge of interest in network analyses that emphasize the putatively direct relationships among symptoms. In this critical paper, we highlight conceptual and statistical problems with using centrality measures in cross-sectional networks. In particular, common network analyses assume that there are no unmodeled latent variables that confound symptom co-occurrence. In simulations that include latent variables, we demonstrate that closeness and betweenness are vulnerable to spurious covariance among symptoms that connect subgraphs (e.g., diagnoses). Furthermore, strength is redundant with factor loading in several cases. Finally, if a symptom reflects multiple latent causes, centrality metrics reflect a weighted combination, undermining their interpretability in empirical data. Our results suggest that it is essential for network psychometric approaches to examine the evidence for latent variables prior to analyzing or interpreting symptom centrality. Failing to do so risks identifying spurious relationships or failing to detect causally important effects. Altogether, centrality measures do not provide solid ground for understanding the structure of psychopathology when latent confounding exists.

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Bereavement or Breakup: A Network Approach to Modeling Differential Pathways into Depression

10.31234/osf.io/38r4j ◽

2019 ◽

Author(s):

Julian Burger ◽

Margaret S. Stroebe ◽

Pasqualina Perrig-Chiello ◽

Henk A.W. Schut ◽

Stefanie Spahni ◽

...

Keyword(s):

Depressive Symptoms ◽

Graphical Models ◽

Contextual Factors ◽

Marital Disruption ◽

Depression Symptoms ◽

Depression Symptom ◽

Multiple Time ◽

Cross Sectional ◽

Network Analyses ◽

Within Subjects

Background: Prior network analyses demonstrated that the death of a loved one potentially precedes specific depression symptoms, primarily loneliness, which in turn links to other depressive symptoms. In this study, we extend prior research by comparing depression symptom network structures following two types of marital disruption: bereavement versus separation. Methods: We fitted two Gaussian Graphical Models to cross-sectional data from a Swiss survey of older persons (145 bereaved, 217 separated, and 362 married controls), and compared symptom levels across bereaved and separated individuals. Results: Separated compared to widowed individuals were more likely to perceive an unfriendly environment and oneself as a failure. Both types of marital disruption were linked primarily to loneliness, from where different relations emerged to other depressive symptoms. Amongst others, loneliness had a stronger connection to perceiving oneself as a failure in separated compared to widowed individuals. Conversely, loneliness had a stronger connection to getting going in widowed individuals. Limitations: Analyses are based on cross-sectional between-subjects data, and conclusions regarding dynamic processes on the within-subjects level remain putative. Further, some of the estimated parameters in the network exhibited overlapping confidence intervals and their order needs to be interpreted with care. Replications should thus aim for studies with multiple time points and larger samples. Conclusions: The findings of this study add to a growing body of literature indicating that depressive symptom patterns depend on contextual factors. If replicated on the within-subjects level, such findings have implications for setting up patient-tailored treatment approaches in dependence of contextual factors.

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Topological measures for identifying and predicting the spread of complex contagions

Nature Communications ◽

10.1038/s41467-021-24704-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Douglas Guilbeault ◽

Damon Centola

Keyword(s):

Social Networks ◽

Shortest Path ◽

Empirical Data ◽

Path Length ◽

Centrality Measures ◽

Social Phenomena ◽

Node Centrality ◽

Network Connectedness ◽

Topological Measures ◽

Definition Of

AbstractThe standard measure of distance in social networks – average shortest path length – assumes a model of “simple” contagion, in which people only need exposure to influence from one peer to adopt the contagion. However, many social phenomena are “complex” contagions, for which people need exposure to multiple peers before they adopt. Here, we show that the classical measure of path length fails to define network connectedness and node centrality for complex contagions. Centrality measures and seeding strategies based on the classical definition of path length frequently misidentify the network features that are most effective for spreading complex contagions. To address these issues, we derive measures of complex path length and complex centrality, which significantly improve the capacity to identify the network structures and central individuals best suited for spreading complex contagions. We validate our theory using empirical data on the spread of a microfinance program in 43 rural Indian villages.

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Clinical evaluation of pulmonary hypertension using patient-reported outcomes: a cross-sectional study

BMC Pulmonary Medicine ◽

10.1186/s12890-021-01416-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Miguel Ángel Amor-García ◽

Sara Ibáñez-García ◽

Xandra García-González ◽

Teresa Mombiela ◽

Cristina Villanueva-Bueno ◽

...

Keyword(s):

Quality Of Life ◽

Pulmonary Hypertension ◽

Clinical Evaluation ◽

Patient Reported Outcomes ◽

Specific Treatment ◽

Tertiary Hospital ◽

Functional Class ◽

Cross Sectional ◽

Patient Reported

Abstract Background Patients with pulmonary hypertension (PH) have progressive and disabling symptoms, as well as a burden of treatments and a difficult clinical evaluation that make health-related quality of life a particularly relevant endpoint in this disease. The objective of the study was to evaluate patient-reported outcomes of patients receiving specific treatment for PH in a tertiary hospital using a specific questionnaire (Cambridge Pulmonary Hypertension Outcome Review-CAMPHOR) in the pharmacy consultation. Methods A cross-sectional, observational, descriptive study was conducted. It included all patients receiving specific treatment for PH in a tertiary hospital in Madrid, Spain. The inclusion period comprised between August to December 2019. CAMPHOR questionnaires containing three domains: symptoms, activities and quality of life were completed by the patients at the pharmacy consultation. Demographic and clinical variables, including WHO Functional Class (WHO FC), PH-specific tests and hemodynamic parameters, were recorded. Non-parametric analyses to assess relations between variables and CAMPHOR domains were performed. Results Thirty-six patients consented to participate in the study and completed the questionnaire. Median scores for symptoms, activities, and quality of life domains were 5.5 (2.5–10), 8.0 (4.5–10.5) and 3.5 (1–7.5), respectively. Statistically significant differences were found in the three domains when comparing by WHO FC, in the activities domain for 6-m walking test and in the quality of life domain for patients who had emergency visits or hospitalizations in the last year. Conclusions The CAMPHOR questionnaire could be useful as a complementary test to achieve an integrated evaluation of PH patients, who could complete it easily during their routine pharmacy visits.

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Optimized and Non-Optimized Personal Protective Equipment Use during the COVID-19 Pandemic in Thailand: A National Cross-Sectional Survey in a Resource-Limited Setting

Environmental Health Insights ◽

10.1177/11786302211013545 ◽

2021 ◽

Vol 15 ◽

pp. 117863022110135

Author(s):

Visal Moolasart ◽

Weerawat Manosuthi ◽

Varaporn Thienthong ◽

Uajai Jaemsak ◽

Winnada Kongdejsakda ◽

...

Keyword(s):

Personal Protective Equipment ◽

Negative Pressure ◽

Symptom Severity ◽

Univariate Analysis ◽

Education Level ◽

Health Concern ◽

Protective Equipment ◽

Global Public Health ◽

Cross Sectional ◽

Infection Control Program

Introduction: Coronavirus disease (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-COV2). COVID-19 is highly contagious, potentially fatal, and a global public health concern. Combining optimized personal protective equipment (PPE) use and hand hygiene is the best strategy for preventing COVID-19 in health care workers (HCWs). Methods: We conducted a national cross-sectional web-based survey of HCWs in the infection control program (IPC) in Thailand between May 5, 2020 and May 15, 2020. The primary objective was the prevalence of optimized PPE use amongst HCWs. The secondary objective was identification of the independent predictors of optimized PPE use. Results: We received a response from 46% of HCWs (756/1650), and all those who responded were nurse or HCWs who were registered in the IPC network. Five HCWs were excluded because of missing data, and 751 were included in the final analysis. The prevalences of PPE use were 22% (168/751) for optimized PPE use, 78% (583/751) for non-optimized PPE use, 35% (263/751) for PPE overuse, and 43% (320/751) for PPE underused. In univariate analysis, optimized PPE use was significantly associated with age, education level, knowledge of appropriate negative pressure room selection, and knowledge of apparently milder symptom severity in children than adults. In multivariate analysis, independent predictors of optimized PPE use were knowledge of appropriate negative pressure room selection (aOR = 1.95, 95% CI = 1.18-3.22), the difference in symptom severity between children and adults (aOR = 0.55, 95% CI = 0.37-0.81), and education level (aOR = 1.54, 95% CI = 1.04-2.27). Conclusion: The prevalence of optimized PPE use amongst HCWs was 22%. Independent predictors of optimized PPE use were COVID-19 knowledge-based factors and education level. Therefore, the continued education training program should be implemented to ensure maintenance of appropriate practices during the COVID-19 pandemic.

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Sex differences and correlates of poor glycaemic control in type 2 diabetes: a cross-sectional study in Brazil and Venezuela

BMJ Open ◽

10.1136/bmjopen-2018-023401 ◽

2019 ◽

Vol 9 (3) ◽

pp. e023401 ◽

Cited By ~ 5

Author(s):

Fernanda G Duarte ◽

Sandra da Silva Moreira ◽

Maria da Conceição C Almeida ◽

Carlos A de Souza Teles ◽

Carine S Andrade ◽

...

Keyword(s):

Type 2 Diabetes ◽

Glycaemic Control ◽

Treatment Guidelines ◽

Specific Treatment ◽

Nationwide Survey ◽

Haemoglobin A1c ◽

Cross Sectional ◽

Factors Associated ◽

Adherence To Diet

ObjectiveExamine whether glycaemic control varies according to sex and whether the latter plays a role in modifying factors associated with inadequate glycaemic control in patients with type 2 diabetes (T2D) in Brazil and Venezuela.Design, setting and participantsThis was a cross-sectional, nationwide survey conducted in Brazil and Venezuela from February 2006 to June 2007 to obtain information about glycaemic control and its determinants in patients with diabetes mellitus attending outpatient clinics.Main outcome measuresHaemoglobin A1c (HbA1c) level was measured by liquid chromatography, and patients with HbA1c ≥7.0% (53 mmol/mol) were considered to have inadequate glycaemic control. The association of selected variables with glycaemic control was analysed by multivariate linear regression, using HbA1c as the dependent variable.ResultsA total of 9418 patients with T2D were enrolled in Brazil (n=5692) and in Venezuela (n=3726). They included 6214 (66%) women and 3204 (34%) men. On average, HbA1c levels in women were 0.13 (95% CI 0.03 to 0.24; p=0.015) higher than in men, after adjusting for age, marital status, education, race, country, body mass index, duration of disease, complications, type of healthcare, adherence to diet, adherence to treatment and previous measurement of HbA1c. Sex modified the effect of some factors associated with glycaemic control in patients with T2D in our study, but had no noteworthy effect in others.ConclusionsWomen with T2D had worse glycaemic control than men. Possible causes for poorer glycaemic control in women compared with men include differences in glucose homeostasis, treatment response and psychological factors. In addition, sex modified factors associated with glycaemic control, suggesting the need to develop specific treatment guidelines for men and women.

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Patient-reported experience and outcomes from orthodontic treatment

Journal of Orthodontics ◽

10.1177/1465312520904377 ◽

2020 ◽

Vol 47 (2) ◽

pp. 107-115

Author(s):

Elizabeth Bradley ◽

Andrew Shelton ◽

Trevor Hodge ◽

David Morris ◽

Hilary Bekker ◽

...

Keyword(s):

Secondary Care ◽

Orthodontic Treatment ◽

Clinical Care ◽

Patient Treatment ◽

Cross Sectional Survey ◽

Cross Sectional ◽

Fixed Appliance ◽

Treatment Experience ◽

Patient Reported ◽

Pre Treatment

Objective: To measure patient-reported impact of orthodontic treatment in terms of pre-treatment concerns, treatment experience and treatment outcome. Setting: Four sites in Yorkshire, including two secondary care settings (Leeds Dental Institute and St Luke’s Hospital, Bradford) and two specialist orthodontic practices. Design: Cross-sectional survey. Participants: NHS orthodontic patients (aged 12+ years) who have completed comprehensive orthodontic treatment, excluding orthognathic surgery and craniofacial anomalies. Methods: Participants were opportunistically identified by the direct clinical care team during scheduled appointments and those eligible were invited to participate. Data were collected using the Orthodontic Patient Treatment Impact Questionnaire (OPTIQ), a validated 12-item measure with questions relating to pre-treatment experience, impact of treatment and outcome from treatment. Results: Completed questionnaires for analysis included 120 from primary care and 83 from secondary care. The most common pre-treatment concerns were alignment (89%) and being embarrassed to smile (63%). The most common expectations from orthodontic treatment were improved confidence to eat (87%) and smile (72%) in front of others, improved appearance of teeth (85%) and reduced teasing/bullying (63%). Only 67% respondents recalled receiving written information and the lowest recall related to retainer type and length of retention. The most commonly reported complications were sore mouth (68%), fixed appliance breakage (61%) and gingivitis (39%). Treatment caused greatest impact in relation to pain, limitations in eating and effect on speech. Overall satisfaction with orthodontic treatment was reported by 96% of respondents, 87% would have orthodontic treatment again (if needed) and 91% would recommend treatment to a friend. Conclusions: The OPTIQ is a useful patient-reported tool to identify pre-treatment concerns and expectations, treatment experience and outcome. Orthodontic treatment leads to high levels of satisfaction.

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