Prenatal Symptom Cluster of Psychopathology and Associations With Mindfulness and Rumination: A Network Analysis

Network analysis of PTSD symptoms following childbirth and comorbid conditions among women with sexual trauma history

PURPOSE

Women with a history of sexual trauma (ST) have heightened risk for postpartum psychopathology. Although ST increases risk for traumatic delivery and maternal psychopathology, knowledge of the functional connections among various psychiatric symptoms and complicated delivery remains limited.

METHODS

We used regularized partial correlation networks to examine connections between symptoms of childbirth-related PTSD (CB-PTSD), depression, anxiety, somatization, obsessive-compulsive disorder, and complicated delivery (e.g., presence of obstetric complications, preterm birth, advanced maternal age) in 1,916 postpartum women. We compared networks of women with and without a history of sexual trauma (nST = 958 and nNST = 958, respectively).

RESULTS

Complicated delivery in both groups connected with three CB-PTSD clusters: reexperiencing, avoidance, and negative alterations in cognition and mood. Network comparison tests revealed a significant difference in global strength invariance, but not network invariance. ST network CB-PTSD nodes were significantly more strongly interconnected as compared to those with no ST (NST). Conversely, stronger connections in the NST network were Mood with Anxiety and Avoidance with Somatic symptoms.

CONCLUSION

The ST group's stronger PTSD symptom coactivation may reflect differences in risk for the emergence of CB-PTSD for women with a history of ST.

Symptom clusters and symptom network analysis during immunotherapy in lung cancer patients

OBJECTIVE

This study analyzes symptoms in lung cancer patients undergoing immunotherapy to identify core symptom clusters through network analysis and lay a foundation for effective symptom management programs.

METHODS

The sample comprised 240 lung cancer patients receiving immunotherapy. Participants were assessed using the Memorial Symptom Assessment Scale. Exploratory factor analysis was used to extract symptom clusters, and network analysis using JASP 0.17.3 was performed to explore the centrality indices and density of the symptom network.

RESULTS

Five symptom clusters were identified, i.e., emotion-related, lung cancer-related, physical, skin, and neural symptom clusters, with a cumulative variance contribution rate of 55.819%. Network analysis revealed that sadness was the most intense symptom (rs = 2.189), dizziness was the most central symptom (rc = 1.388), and fatigue was the most significant bridging symptom (rb = 2.575).

CONCLUSION

This study identified five symptom clusters and a symptom network among lung cancer patients during immunotherapy. The network analysis's centrality indices and network density results can assist healthcare professionals in devising more precise symptom management strategies.

Mindfulness, work-family conflict, family-work conflict and depressive symptoms among nurses: A cross-sectional design

BACKGROUND

Work and family role conflict is a common source of stressors that affect nurses, leading to negative outcomes on their mental health, such as depressive symptoms, which affect nurses' job performance and patients' health outcomes. Mindfulness positively affected mental health, but its role in the relationship between role conflict and depressive symptoms was not previously examined.

PURPOSE

To examine the mediating role of mindfulness in the relationship between work-family conflict and family-work conflict with depressive symptoms among nurses.

METHODS

A descriptive cross-sectional design was used to collect data from a sample of 188 nurses from two large referral hospitals in northern and central Jordan. Data analysis was performed using Pearson correlation and macro PROCESS.

RESULTS

The mean score of depressive symptoms in our sample indicated that our sample is at risk for clinical depression. The bivariate correlation showed that depressive symptoms were significantly and negatively associated with work-family and family-work conflicts and significantly and positively associated with mindfulness. Both regression models explained 52% of the variance in depressive symptoms (F [6, 181] = 35.38, p < .001). The models also showed that mindfulness had a significant negative effect on depressive symptoms (t = -8.98, p < .001). The results of macro PROCESS indicated that mindfulness mediated the relationship between work-family conflict and family-work conflict with depressive symptoms.

CONCLUSION

Nurses are exposed to a number of stressors in their work environment, including long work hours and frequent exposure to traumatic events. The current study showed that mindfulness might play a role in mediating the relationship between family-work conflict and family-work conflict with depressive symptoms. Nurses, nurse managers and policymakers can work with healthcare organizations to promote nurses' work quality by controlling risk factors, such as depressive symptoms, and implementing strategies to mitigate these risks.

Pre-hospital symptom clusters and symptom network analysis in decompensated cirrhotic patients: A cross-sectional study

AIMS

To generate pre-hospital symptom networks, explore core, bridge and sentinel symptoms, identify pre-hospital symptom clusters and analyse relationship between influencing factors and symptom clusters in decompensated cirrhosis patients.

DESIGN

A cross-sectional study design using the Strengthening the Reporting of Observational Studies in Epidemiology checklist.

METHODS

Demographical, physiological, psychological and sociological characteristics and the pre-hospital symptoms of 292 decompensated cirrhotic patients were collected from October 2021 to March 2023 in China. Frequencies, percentages, means, standard deviations, independent samples t-tests, one-way analysis of variance, exploratory factor analysis, multiple stepwise regression analysis and network analysis were used for data analysis.

RESULTS

'I don't look like myself' and itching were core and bridge symptoms, while bloating and lack of energy were sentinel symptoms in decompensated cirrhotic patients. Monthly family income, anxiety, depression, social support and disease duration influenced the neuropsychological symptom cluster, with worrying as the strongest predictor symptom. Influential factors for cirrhosis-specific symptom cluster included Child-Pugh class, monthly family income, disease duration, anxiety and depression, with itching being the strongest predictor symptom. Monthly family income, disease duration and depression were influential factors for gastrointestinal symptom cluster, with loss of appetite as the strongest predictor symptom.

CONCLUSIONS

Neuropsychological, cirrhosis-specific and gastrointestinal symptom clusters were formed in decompensated cirrhotic patients. Through network analysis, direct connections between symptoms, symptom clusters and their influencing factors were revealed, thereby offering clinicians a foundation for effectively managing patients' pre-hospital symptoms.

IMPACT

Decompensated cirrhosis patients commonly have multiple symptoms, while the management of pre-hospital symptoms is often suboptimal. This study identified neuropsychological, cirrhosis-specific, gastrointestinal symptom clusters and recognized core, bridge and sentinel symptoms in these patients. It also revealed the most prominent symptoms within each cluster. This provides insight into the hierarchy of symptoms, improving symptom management in decompensated cirrhosis.

PATIENT AND PUBLIC INVOLVEMENT

There was no patient or public involvement.

Identifying care problem clusters and core care problems of older adults with dementia for caregivers: a network analysis

Background

A shift in research interest from separate care problem to care problem clusters among caregivers of people living with dementia may contribute to a better understanding of dementia care. However, the care problems network among caregivers of people living with dementia are still unknown. This study aimed to identify care problem clusters and core care problems, and explore demographic variables associated with these care problem clusters among caregivers of people living with dementia.

Methods

Participants were recruited through memory clinics and WeChat groups. The principal component analysis was applied to identify care problem clusters. The network analysis was conducted to describe the relationships among care problems and clusters. Multiple linear models were used to explore the associated factors for the occurrence of the overall care problems and top three central care problem clusters.

Results

A total of 1,012 carer-patient pairs were included in the analysis. Nine care problem clusters were identified. In the entire care problem network, "deterioration in activities of daily living" was the most core care problem cluster across the three centrality indices, followed by "verbal and nonverbal aggression" and "loss of activities of daily living." Variables including marital status, years of dementia diagnosis, number of dementia medication type, and caregiver's educational attainment were associated with the prevalence of these three care problem clusters.

Conclusion

Our study suggests that there is a need to evaluate care problem clusters for the improvement of care problem management among people living with dementia. It is particularly important to include assessment and treatment of core care problem as an essential component of the dementia care.

Exploration of symptom clusters during hemodialysis and symptom network analysis of older maintenance hemodialysis patients: a cross-sectional study

BACKGROUND

Symptom networks can provide empirical evidence for the development of personalized and precise symptom management strategies. However, few studies have established networks of symptoms experienced by older patients on maintenance hemodialysis. Our goal was to examine the type of symptom clusters of older maintenance hemodialysis patients during dialysis and construct a symptom network to understand the symptom characteristics of this population.

METHODS

The modified Dialysis Symptom Index was used for a cross-sectional survey. Network analysis was used to analyze the symptom network and node characteristics, and factor analysis was used to examine symptom clusters.

RESULTS

A total of 167 participants were included in this study. The participants included 111 men and 56 women with a mean age of 70.05 ± 7.40. The symptom burdens with the highest scores were dry skin, dry mouth, itching, and trouble staying asleep. Five symptom clusters were obtained from exploratory factor analysis, of which the clusters with the most severe symptom burdens were the gastrointestinal discomfort symptom cluster, sleep disorder symptom cluster, skin discomfort symptom cluster, and mood symptom cluster. Based on centrality markers, it could be seen that feeling nervous and trouble staying asleep had the highest strength, and feeling nervous and feeling irritable had the highest closeness and betweenness.

CONCLUSIONS

Hemodialysis patients have a severe symptom burden and multiple symptom clusters. Dry skin, itching, and dry mouth are sentinel symptoms in the network model; feeling nervous and trouble staying asleep are core symptoms of patients; feeling nervous and feeling irritable are bridge symptoms in this symptom network model. Clinical staff can formulate precise and efficient symptom management protocols for patients by using the synergistic effects of symptoms in the symptom clusters based on sentinel symptoms, core symptoms, and bridge symptoms.