Extended network analysis: from psychopathology to chronic illness

Health-related quality of life in severe hypersensitivity reactions: focus on severe allergic asthma and hymenoptera venom anaphylaxis-a cross-sectional study

Background

Growing evidence reveals the important role of clinical psychological factors in chronic-immune diseases. The aim of this study was to investigate Health-Related Quality of Life (HR-QoL), depression, anxiety, and alexithymia in patients with severe hypersensitivity reactions such as Severe Allergic Asthma (SAA) and Hymenoptera Venom Anaphylaxis (HVA).

Methods

The Short-Form Health Survey-36 (SF-36), the Beck Depression Inventory Questionnaire (BDI-II), the Hamilton Anxiety Rating Scale (HAM-A) and the Toronto Alexithymia Scale (TAS-20) were used to assess HR-QoL and clinical psychological features of patients with SAA and HVA.

Results

Overall, 78 patients were recruited. Patients with SAA (n = 35) reported lower scores for physical functioning [65 (58-75) vs. 90 (85-95); p = <0.001], role limitations due to physical health [25 (0-50) vs. 62 (50-75); p = 0.004], bodily pain [47.5 (41.1-61.3) vs. 55.5 (55-96); p = 0.001], general health [40 (30-60) vs. 70 (50-80); p = 0.0003] and social functioning [50 (37.5-62.5) vs. 62.5 (54.9-75); p = 0.007] while higher scores for depressive symptoms [14 (11-15.4) vs. (9.5 (6-15.4); p = 0.05)] compared to HVA patients (n = 43). All the dimensions of SF-36 were negatively correlated with anxiety (r from -0.26 to -0.66; p all < 0.01) and depressive symptoms (r from -0.44 to -0.73; p all < 0.001). Alexithymia was negatively correlated with vitality (r = -0.28; p = 0.02) and mental health (r = -027; p = 0.03). Additionally, patients with alexithymia (38% of participants) showed higher levels of depressive symptoms [9.5 (10-19) vs. 14 (6-13.9); p = 0.005] and anxiety levels [31 (27.9-35) vs. 24 (16-33.9); p = 0.02]; they also showed less vitality [40 (39.9-50) vs. 55 (50-60) p = 0.01], social functioning [50 (37.5-62.5) vs. 62.5 (50 vs. 75); p = 0.01] and mental health [48 (44-60) vs. 68 (56-76); p = 0.004].

Conclusion

Clinical psychological features due to severe hypersensitive reactions may contribute to the patient's perceived HR-QoL. Focused clinical psychological interventions should be promoted to improve the clinical management of such conditions.

The body of evidence of late-life depression: the complex relationship between depressive symptoms, movement, dyspnea and cognition

BACKGROUND

Physical symptoms play an important role in late-life depression and may contribute to residual symptomatology after antidepressant treatment. In this exploratory study, we examined the role of specific bodily dimensions including movement, respiratory functions, fear of falling, cognition, and physical weakness in older people with depression.

METHODS

Clinically stable older patients with major depression within a Psychiatric Consultation-Liaison program for Primary Care underwent comprehensive assessment of depressive symptoms, instrumental movement analysis, dyspnea, weakness, activity limitations, cognitive function, and fear of falling. Network analysis was performed to explore the unique adjusted associations between clinical dimensions.

RESULTS

Sadness was associated with worse turning and walking ability and movement transitions from walking to sitting, as well as with worse general cognitive abilities. Sadness was also connected with dyspnea, while neurovegetative depressive burden was connected with activity limitations.

DISCUSSION

Limitations of motor and cognitive function, dyspnea, and weakness may contribute to the persistence of residual symptoms of late-life depression.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable fit. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

A Laplacian regularized graph neural network for predictive modeling of multiple chronic conditions

BACKGROUND AND GOALS

One of the biggest difficulties facing healthcare systems today is the prevalence of multiple chronic diseases (MCC). Mortality and the development of new chronic illnesses are more likely in those with MCC. Pre-existing diseases and risk factors specific to the patient have an impact on the complex stochastic process that guides the evolution of MCC. This study's goal is to use a brand-new Graph Neural Network (GNN) model to examine the connections between specific chronic illnesses, patient-level risk factors, and pre-existing conditions.

METHODS

We propose a graph neural network model to analyze the relationship between five chronic conditions (diabetes, obesity, cognitive impairment, hyperlipidemia, and hypertension). The proposed model adds a graph Laplacian regularization term to the loss function, which aims to improve the parameter learning process and accuracy of the GNN based on the graph structure. For validation, we used historical data from the Cameron County Hispanic Cohort (CCHC).

RESULTS

Evaluating the Laplacian regularized GNN on data from 600 patients, we expanded our analysis from two chronic conditions to five chronic conditions. The proposed model consistently surpassed a baseline GNN model, achieving an average accuracy of ≥89% across all combinations. In contrast, the performance of the standard model declined more markedly with the addition of more chronic conditions. The Laplacian regularization provided consistent predictions for adjacent nodes, beneficial in cases with shared attributes among nodes.

CONCLUSIONS

The incorporation of Laplacian regularization in our GNN model is essential, resulting in enhanced node categorization and better predictive performance by harnessing the graph structure. This study underscores the significance of considering graph structure when designing neural networks for graph data. Future research might further explore and refine this regularization method for various tasks using graph-structured data.

A Network Analysis Study on the Structure and Gender Invariance of the Satisfaction with Life Scale among Spanish University Students

INTRODUCTION

The psychometric properties of the Satisfaction With Life Scale (SWLS) have been evaluated across numerous languages and population groups, primarily from a factor analysis perspective. In some studies, inconsistencies in structural invariance have been identified.

OBJECTIVE

This study aims to analyze the properties and gender invariance of the SWLS from a network analysis perspective.

METHOD

A total of 857 Spanish university students were obtained through a stratified random cluster sampling method in a cross-sectional survey design study. Descriptive analysis of the items, partial-correlation network, Bayesian network model estimation, and invariance analysis by gender were conducted.

RESULTS

The instrument did not exhibit any floor or ceiling effects. Each item can be considered univariately normally distributed, and all items clustered in a single and stable community. The partial-correlation network model and centrality measures were stable in the full sample and invariant across genders. Item 3 emerged as the most central node in the network with the highest predictability. The Bayesian network indicated that items 2 and 4 initiate the process, while item 5 acts as the sink, and items 1 and 3 act as mediators.

CONCLUSIONS

The SWLS can be used as a unidimensional measure, and the total score and relationships among items are stable and reliable. Any potential differences among genders cannot be associated with the functioning of the instrument. The predictability of every item was high, and the Bayesian network clearly identified different roles among the items.

The use of psychological network analysis in informal dementia care: an empirical illustration

Objective: Theoretical models in informal dementia care have been developed to understand how risk and protective factors interact to cause caregiver's distress. The development of psychological network analysis provides a rich complement to our current models, as explores how different variables (or nodes) are associated using graph theories. Methods: The present study explored the use of network analysis using data from 125 informal caregivers of their partner with dementia (PwD). The included variables were recipient's dependency, self-efficacy, conflict within the family, dyadic adjustment, and caregiver's distress. Results: The analysis suggests a complex network of interacting variables. The core variable was not the caregiver's distress but rather their dyadic adjustment with their PwD. Variables were associated with caregiver distress through a large array of direct and indirect pathways and were associated with each other in the form of an asymmetric spider's web.Conclusion: The results show the complex interplay of variables in a psychological network. The central role of distress suggests a complex and dynamic role, notably through a bidirectional influence with quality of interactions. In the same way, quality of interactions appeared as one of the strongest nodes, its connectivity suggesting a crucial role to consider in our models and interventions.

Psychometric Properties of the Peruvian Version of the MOS Scale for Social Support in Cancer Patients and Convergent Network with Quality of Life

Introduction

One of the key psychosocial factors that impact mental and emotional health is social support. While much research has been conducted on the role of social support in the lives of cancer patients, there is a lack of studies that consider populations who need specific tools to assess this concept.

Purpose

The aim of this study was to evaluate the psychometric properties of the MOS Social Support Scale (1991) in 499 Peruvian cancer patients between the ages of 18 and 87 (M= 46.30, SD = 15.747).

Methods

In this study, three models of the MOS were analyzed based on 19-item versions (four factor, second order and bifactor model).

Results

The results showed a better psychometric fit in the 19-item bifactor model with optimal fit indices through the structural equation method (SB-χ2/df = 1.94, CFI = 0.966, TLI= 0.955, SRMR = 0.038 and RMSEA = 0.058). Additionally, there was evidence of configural, metric and scalar invariance with this instrument according to the gender of the surveyed cancer patients. Convergent validity using a network analysis approach revealed positive associations between social support dimensions and quality of life.

Conclusion

Emotional support and positive interactions dimensions were found to be important interconnections in the overall network, as indicated by their greater centralities. Therefore, this instrument could be suggested as a reliable way to evaluate cancer patients and their perceived support.

Alexithymia and asthma: a systematic review

Growing evidence from scientific research elucidates the important role of alexithymia in chronic immune diseases. This Review aims to explore the presence of alexithymia in patients affected by asthma and clarify its associations with other involved psychological and physical factors. In January 2023, according to PRISMA guidelines, a systematic search using PubMed and Scopus was conducted. Twenty-six studies were eligible based on inclusion criteria. Alexithymia was significantly present in asthma patients, with most studies reporting a higher prevalence (from 9 to 62.8%) than in control groups (approximately 10%). The coexistence of asthma and alexithymia was associated with a worse quality of life, psychiatric comorbidity, poor symptom control, and difficulty in recognizing exacerbations of the disease. These results suggest that alexithymia can negatively impact the management of asthma. For this reason, we recommend an accuracy assessment in clinical settings and the implementation of psychological interventions to promote the emotional and physical wellbeing of asthmatic patients.

COVID-19 Vaccine for Children: Vaccination Willingness of Parents and Its Associated Factors—A Network Analysis

Different COVID-19 vaccines have been approved for underage children, so parents and caregivers currently face the decision of whether to vaccinate their children against COVID-19 or not. Due to the rather moderate vaccine acceptance among parents across different countries, the objective of the present study was to investigate the relationship between different psychological, demographic, and behavioral factors related to the acceptance of the COVID-19 vaccine for underage children among parents. In particular, vaccination attitudes, whether parents have been vaccinated against COVID-19 themselves, COVID-19 fear, attitude towards COVID-19 policy measures, governmental trust, subjective level of information, perceived risk of disease progression, and perceived risk of vaccine side effects were the variables of interest. The study adopted a cross-sectional study design, and the sample consisted of 2405 participants. A network analysis was conducted to investigate the associations and interconnection among these variables. The results showed that, in particular, compliance, confidence in the safety of vaccines, whether parents have been vaccinated against COVID-19 themselves, trust in the governmental system, fear of COVID-19, and the parents’ age were directly related to the acceptance of the COVID-19 vaccine for children. To increase compliance and confidence in the vaccines’ safety among parents, promotion campaigns should provide more information concerning the vaccines’ safety, particularly for younger parents who are not vaccinated against COVID-19 themselves.

Depressive and anxiety symptoms in patients with COPD: A network analysis

BACKGROUND

Individuals with Chronic Obstructive Pulmonary Disease (COPD) often develop anxiety and depression, which worsen illness management and prognosis. Physical and psychological symptoms, contextual and illness-related factors display complex reciprocal interactions, which give rise to heterogeneous presentations. Examining the patterns of association between specific physical and psychological symptoms in patients with COPD may help to focus on the precision of the patient-centred care.

RESEARCH QUESTION

We used network analyses to examine the links between symptoms of COPD, depression and anxiety.

METHODS

Data from 1587 individuals with COPD from the COPDGene study were included. We estimated a Bayesian Gaussian Graphical Model to highlight the unique associations between symptoms of COPD (assessed with the COPD Assessment Test), depression and anxiety (assessed with the Hospital Anxiety and Depression Scale (HADS), while examining the role of sociodemographic characteristics, lung function tests, and health status.

RESULTS

Unique Variable Analysis reduced 14 HADS items to Tension/worry (chronic anxiety), Fear/panic (acute anxiety), Restlessness, Anhedonia, Sadness and Slowing. In network analyses, chest-tightness was related to acute anxiety, while cough and weakness were connected with core depressive symptoms (sadness and lack of pleasure). Chronic anxiety was linked with acute anxiety and depressive symptoms. Findings were confirmed accounting for the role of confounders, including lung function, sex, ethnicity and lifestyle factors. A simulation based on our model yielded distinct predictions about anxiety and depression in two participants with similar COPD severity, but different symptom profiles.

CONCLUSION

Network analyses highlighted specific associations between symptoms of COPD, depression and anxiety. Accounting for symptom-level interactions may help to promote personalized treatment approaches.

Clinical Study of Serum Serotonin as a Screening Marker for Anxiety and Depression in Patients with Type 2 Diabetes

Over time, studies have shown the importance of determining serotonin levels to diagnose somatic and psychiatric disorders. There are theoretical premises and practical ways to achieve a subtle correlation between the existence of comorbid psychiatric disorders and somatic diseases caused by the changes observed in serotonin levels. The present study, classified as retrospective and quantitative, provides evidence for determining the serotonin levels in patients with diabetes and anxiety or depression. A total of 48 patients with diabetes type 2 were enrolled in the study. Blood glucose level, glycated haemoglobin, and serum serotonin were noted, and they completed Hamilton A and Beck Depression Inventory questionnaires. We found robust correlations between serum serotonin and blood glucose (Sig. = 0.008), serum serotonin and HbA1c (Sig. = 0.007), serum serotonin and anxiety (Sig. = 0.000), and serum serotonin and depression (Sig. = 0.000). It is also noteworthy that women recorded extreme values higher than men for glycated haemoglobin (95% confidence interval: 6.92–7.79 in women and 6.30–7.23 in men). In conclusion, using serotonin as a marker of the mentioned diseases in clinical practice is of significant utility, considering the benefits in terms of the evolution and prognosis of comorbidities in patients with type 2 diabetes and anxiety and depressive symptoms.

Coexisting service-related factors preceding suicide: a network analysis

OBJECTIVES

The overall objective was to analyse service-related factors involved in the complex processes that precede suicide in order to identify potential targets for intervention.

DESIGN AND SETTING

Explorative network analysis study of post-suicide root cause analysis data from Swedish primary and secondary healthcare.

PARTICIPANTS

217 suicide cases reported to the Swedish national root cause analysis database between 2012 and 2017.

PRIMARY AND SECONDARY OUTCOME MEASURES

A total of 961 reported incidents were included. Demographic data and frequencies of reported deficiencies were registered. Topology, centrality indices and communities were explored for three networks. All networks have been tested for robustness and accuracy.

RESULTS

Lack of follow-up, evaluations and insufficient documentation issues emerged as central in the network of major themes, as did the contributing factors representing organisational problems, failing procedures and miscommunication. When analysing the subthemes of deficiencies more closely, disrupted treatments and staffing issues emerged as prominent features. The network covering the subthemes of contributing factors also highlighted discontinuity, fragile work structures, inadequate routines, and lack of resources and relevant competence as potential triggers. However, as the correlation stability coefficients for this network were low, the results need further investigation. Four communities were detected covering nodes for follow-up, evaluation, cooperation, and procedures; communication, documentation and organisation; assessments of suicide risk and psychiatric status; and staffing, missed appointments and declined treatment.

CONCLUSION

The results of this study suggest that healthcare providers may improve patient safety in suicide preventive pathways by taking active measures to provide regular follow-ups to patients with elevated suicide risk. In some cases, declined or cancelled appointments could be a warning sign. Tentative results show organisational instability, in terms of work structure, resources and staffing, as a potential target for intervention, although this must be more extensively explored in the future.

The future of burn care from a complexity science perspective

Healthcare is undergoing a profound technological and digital transformation and has become increasingly complex. It is important for burns professionals and researchers to adapt to these developments which may require new ways of thinking and subsequent new strategies. As Einstein has put it: 'We must learn to see the world anew'. The relatively new scientific discipline "Complexity science" can give more direction to this and is the metaphorical open door that should not go unnoticed in view of the burn care of the future. Complexity sciences studies 'why the whole is more than the sum of the parts'. It studies how multiple separate components interact with each other and their environment and how these interactions lead to 'behavior of the system'. Biological systems are always part of smaller and larger systems and exhibit the behavior of adaptivity, hence the name complex adaptive systems. From the perspective of complexity science, a severe burn injury is an extreme disruption of the 'human body system'. But this disruption also applies to the systems at the organ and cellular level. All these systems follow principles of complex systems. Awareness of the scaling process at multilevel helps to understand and manage the complex situation when dealing with severe burn cases. The aim of this paper is to create awareness of the concept of complexity and to demonstrate the value and possibilities of complexity science methods and tools for the future of burn care through examples from preclinical, clinical, and organizational perspective in burn care.

Network Analysis of Depressive Symptomatology in Underweight and Obese Adults

BACKGROUND

Depressive symptoms can affect people's quality of life and social environment. In addition, in severe situations, they can lead to suicidal behaviors.

OBJECTIVE

This study aimed to analyze the differences in depressive symptoms in underweight and obese Peruvian adults.

METHODS

A cross-sectional study was carried out based on secondary data obtained from the Instituto Nacional de Estadística e Informática (INEI), Lima, Peru. A sample of 10 053 participants was considered, of which 55.96% were women. Two Gaussian plot models were estimated and the levels of depressive symptomatology were compared between the 2 groups (adults with underweight and obese).

RESULTS

A total of 1510 (15.02%) were underweight adults and 8543 (84.98%) were obese adults. There were differences in the reporting of depressive symptoms in the underweight group; the most central items were "Depressed mood" (PH2), "Tiredness/low energy" (PH4), and "Psychomotor difficulties" (PH8).

CONCLUSION

This study provides new evidence on the dynamic relationship between depressive symptoms according to the body mass index categories (underweight and obese) assessed.

El análisis de redes en la investigación clínica

En el número 1 del volumen 69 de la presente revista se publicó un estudio que evaluó los niveles del burnout en residentes de medicina en Colombia y que evidenció el impacto que puede causar este síndrome en quienes lo padecen.1 El burnout es una respuesta a los problemas emocionales e interpersonales que se presentan en el trabajo y en la cual intervienen sentimientos de agotamiento, actitud indiferente, percepción de incompetencia ante la falta de recursos para afrontar las responsabilidades, insatisfacción y baja autoestima.