Evolving symptom networks in relation to HIV-positive duration among people living with HIV: A network analysis

Features and Differences in Core Symptom Clusters in Home-Based Hospice Patients With Advanced Cancer: A Network Analysis

INTRODUCTION

Patients with terminal-stage cancer frequently experience multiple symptoms simultaneously. Little is known about how core symptom clusters differ in advanced-cancer patients with different survival expectancies receiving hospice care. To identify the core symptom clusters of hospice-care cancer patients with different survival expectancies and compare the features of their symptom networks.

METHODS

In this retrospective study, secondary data analysis was conducted. Records of 6946 patients with advanced cancer who received home-based hospice care service in a hospice center from April 2001 to December 2020 were collected and analyzed using network analysis.

RESULTS

This analysis included 6946 patients with advanced cancer receiving hospice care. In patients with survival expectancies of 0-6 months, loss of appetite was identified as the core symptom (rs = 4.03, rb = 5.21, rc = 2.63), and five symptom clusters were identified. Malnutrition was the core symptom in patients with survival expectancies of 6-12 months (rs = 2.83, rb = 2.43, rc = 0.93), and nine symptom clusters were identified. Wasting syndrome was the core symptom cluster in two groups. The network density of symptoms in patients with < 6 months of survival expectancy (91.99) was higher than in patients with 6-12 months (28.39).

CONCLUSIONS

Nutrition impact symptoms are the core symptoms for home-hospice care cancer patients with a survival period of 1 year or below. Moreover, hospice cancer patients with short survival expectancies have greater inter-symptom impact.

Exploring core and bridge symptoms in patients recovering from stroke: a network analysis

Background

Patients recovering from stroke experience a variety of symptoms that present as a synergistic and mutually reinforcing "symptom cluster," rather than as singular symptoms. In this study, we researched and systematic analyzed these symptom clusters, including core and bridge symptoms, to help determine the relationships between symptoms and to identify key symptom targets, providing a new approach for formulating precise symptom management interventions.

Methods

Convenience sampling was applied to select 432 stroke recovery patients treated in the Seventh People's Hospital of Changzhou City from August 1, 2023 to April 14, 2024. Subsequently, a cross-sectional survey was conducted using the General Information Questionnaire and Stroke Symptom Experience Scale to extract symptom clusters via exploratory factor analysis. Finally, the "qgraph" and "bootnet" packages in the R language were used to construct a network layout to describe the relationships between symptoms and calculate the centrality index.

Results

The average age of the 432 enrolled recovering stroke patients was 68.17 ± 12.14 years, including 268 males (62.04%) and 164 females (37.96%), none of whom underwent surgical intervention. Among this cohort, the 3 symptoms with the highest incidence rates were "limb weakness" (A2, 80.56%), "fatigue" (A5, 77.78%), and "limitations of limb movement" (A1, 68.06%). A total of 5 symptom clusters were extracted: the somatic activity disorder, mood-disorder-related, cognitive-linguistic dysfunction, somatic-pain-related, and foot dysfunction symptom clusters. In the symptom network, the 2 most common symptoms in terms of intensity and expected impact were "fatigue" (A5, rs = 1.14, re = 1.00) and "pessimism about the future" (B3, rs = 1.09, re = 1.02). The symptom with the strongest bridge intensity was "limb pain" (D1, rs = 2.64).

Conclusion

This study uses symptom network analysis to explore the symptoms of stroke patients during recovery, identifying core symptoms and bridge symptoms. Based on these findings, we can develop more targeted management plans to improve the accuracy and efficiency of interventions. Through this management approach, we can enhance treatment effectiveness, reduce unnecessary medication, lower adverse drug reactions, and optimize the allocation of medical resources.

HIV symptom severity and associated factors among young people with HIV in Ghana

ABSTRACTAdolescents and young adults (young people) with HIV (YPWH) often struggle with treatment self-management. Many have symptoms due to HIV disease, medication side-effects, or comorbid conditions. Our study investigated the severity of HIV-related symptoms among YPWH aged 18-24 with detectable viral loads from an HIV clinic in Ghana (N = 60) and potential correlates of severity across a range of factors. Results indicated that YPWH currently experienced, on average, 13 symptoms (SD = 12.33). Six of the 10 most common symptoms were from two domains: fatigue and psychological. The most common symptoms were headaches (62%), weakness (53%), and fear/worries (52%). No differences were observed in number or severity of symptoms between youth based on HIV transmission status. Bivariate correlates of symptom severity were found with six that remained significant or approached significance in a multivariate model predicting severity: living with a parent/guardian, higher perceived access to HIV care, and higher treatment readiness were associated with lower severity while greater travel time to the HIV clinic, psychological distress, and more missed clinic appointments were associated with higher severity. Our findings suggest that interventions to address symptoms among YPWH should be multilevel and include strategies (e.g., telehealth, home care) to increase access to care.

Symptom network connectivity and interaction among people with HIV in China: secondary analysis based on a cross-sectional survey

BACKGROUND

The symptom burden in people with HIV (PWH) is considerable. Nonetheless, the identification of a central symptom, or bridge symptom, among the myriad symptoms experienced by PWH remains unclear. This study seeks to establish networks of symptom experiences within different clusters and investigate the relationships and interconnectedness between these symptoms in PWH.

METHODS

A multicenter, cross-sectional descriptive design was carried out in China over two periods: November 2021 to January 2022 and April 2022 to May 2022. A total of 711 PWH completed online questionnaires, providing information on demographics and the 27-item Self-Report Symptom Scale. The symptom network was analyzed using Network/Graph theory, allowing for the exploration of connections between physical, cognitive, and psychological symptoms. This analysis was based on data from a subset of 493 individuals out of the total 711 PWH.

RESULTS

A total of 493 PWH who exhibited symptoms out of a total of 711 PWH were analyzed. The average number of symptoms reported was 5.367. The most prevalent symptom was sleep disturbance (37.98%). In the node centrality analysis, a cognitive symptom, 'becoming confusing', emerged as the most central symptom with significant values for node centrality (strength = 1.437, betweenness = 140.000, closeness = 0.003). Fever was identified as the bridge symptom with the highest bridge strength (0.547), bridge closeness (0.053), lower bridge betweenness (23.000), and bridge expectedinfluence (0.285). Overall, our network displayed good accuracy and stability.

CONCLUSION

Early identification and assessment of the central or bridge symptoms should be emphasized in clinical practice. According to the findings from network analysis, healthcare providers should proactively explore intervention strategies or bundle care to alleviate the burden of symptoms and enable anticipatory care.

Contemporaneous symptom networks analysis in lymphoma patients during chemotherapy: protocol for a single-centre prospective cross-sectional study

BACKGROUND

Symptom networks offer a theoretical basis for developing personalised and precise symptom management strategies. However, symptom networks in lymphoma patients during chemotherapy have been rarely reported. This study intends to establish contemporaneous symptom networks in lymphoma patients during chemotherapy and explore the centrality indices and density in these symptom networks.

METHODS AND ANALYSIS

This is a single-centre prospective cross-sectional study. A total of 315 lymphoma patients admitted to the Lymphoma Department of Shanxi Bethune Hospital since 1 June 2024 will be selected as the study subjects. The patient-reported outcome measures of General Data Questionnaire and Lymphoma Symptom Assessment Scale will be assessed. R package will be used to construct a contemporaneous symptom network, explore the relationship between core and analysed symptoms and analyse the predictive role of network density on patient prognosis.

ETHICS AND DISSEMINATION

This study adheres to the principles of the Declaration of Helsinki and relevant ethical guidelines. Ethical approval has been obtained from Shanxi Bethune Hospital Ethics Committee (approval number: YXLL-2023-186). The final outcomes will be published in a peer-reviewed journal and disseminated through a conference.

Intrarelationships between suboptimal health status and anxiety symptoms: A network analysis

BACKGROUND

Suboptimal health status is a global public health concern of worldwide academic interest, which is an intermediate health status between health and illness. The purpose of the survey is to investigate the relationship between anxiety statuses and suboptimal health status and to identify the central symptoms and bridge symptoms.

METHODS

This study recruited 26,010 participants aged <60 from a cross-sectional study in China in 2022. General Anxiety Disorder-7 (GAD-7) and suboptimal health status short form (SHSQ-9) were used to quantify the levels of anxiety and suboptimal health symptoms, respectively. The network analysis method by the R program was used to judge the central and bridge symptoms. The Network Comparison Test (NCT) was used to investigate the network differences by gender, place of residence, and age in the population.

RESULTS

In this survey, the prevalence of anxiety symptoms, SHS, and comorbidities was 50.7 %, 54.8 %, and 38.5 %, respectively. "Decreased responsiveness", "Shortness of breath", "Uncontrollable worry" were the nodes with the highest expected influence. "Irritable", "Exhausted" were the two symptom nodes with the highest expected bridge influence in the network. There were significant differences in network structure among different subgroup networks.

LIMITATIONS

Unable to study the causal relationship and dynamic changes among variables. Anxiety and sub-health were self-rated and may be limited by memory bias.

CONCLUSIONS

Interventions targeting central symptoms and bridge nodes may be expected to improve suboptimal health status and anxiety in Chinese residents. Researchers can build symptom networks for different populations to capture symptom relationships.

Network evolution of core symptoms after lung cancer thoracoscopic surgery:A dynamic network analysis

OBJECTIVES

To investigate relationships between various symptoms occurring 1-2 and 5-6 days following days after thoracoscopic surgery, to identify core symptoms, and to monitor changes in core symptoms over time following lung cancer thoracoscopic surgery.

METHODS

We evaluated symptoms using the Anderson Symptom Scale (Chinese version) and the Lung Cancer-Specific Symptoms Template in 214 lung cancer patients hospitalized in the Department of Thoracic Surgery of a provincial hospital in Jiangsu Province from March 2023 to September 2023. Data was collected at 1-2 days and 5-6 days postoperatively. Symptom networks were constructed for each time point, and centrality indicators were analyzed to identify core symptoms while controlling for influencing factors.

RESULTS

According to the network analysis, fatigue (rs = 26.00、rc = 0.05、rb = 1.02) had the highest strength, closeness, and betweenness in the symptom network 1-2 days after lung cancer surgery. At 5-6 days after surgery, shortness of breath (rs = 27.00) emerged as the symptom with the highest strength, fatigue (rc = 0.04) had the highest closeness, and cough (rb = 1.08) ranked highest in betweenness within the symptom network.

CONCLUSION

Fatigue stands out as the most core symptom in the network 1-2 days after lung cancer surgery. Shortness of breath, fatigue and cough are the most core symptoms in the symptom network 5-6 days after surgery. Therefore, clinical staff can improve the postoperative symptom experience of lung cancer patients by developing symptom management programmes tailored to these core symptoms.

Sentinel and networked symptoms in patients with breast cancer undergoing chemotherapy

PURPOSE

It was designed to identify the symptom clusters and sentinel symptoms among patients with breast cancer receiving chemotherapy at the community level, and to explore core and bridge symptoms at the global level.

METHODS

A cross-sectional survey was conducted using the MD Anderson Symptom Inventory. Patients with breast cancer receiving chemotherapy, recruited from the "Be Resilient to Breast Cancer" project between January 2023 and December 2023, were included in the study. Symptom clusters and their sentinel symptoms were identified using exploratory factor analysis and Apriori algorithm. Core and bridge symptoms were identified using network analysis.

RESULTS

A total of 468 patients with breast cancer participated in the current study. At the community level, three symptom clusters and their corresponding sentinel symptoms were identified: a gastrointestinal symptom cluster (with nausea as the sentinel symptom), a psycho-sleep-related symptom cluster (with distress as the sentinel symptom), and a neurocognition symptom cluster (with dry mouth as the sentinel symptom). At the global level, fatigue emerged as the core symptom, while disturbed sleep and lack of appetite as bridge symptoms.

CONCLUSION

Addressing nausea, distress, and dry mouth are imperative for alleviating specific symptom clusters at the community level. Furthermore, targeting fatigue, disturbed sleep, and lack of appetite are crucial to break the interactions among diverse symptoms at the global level.

Longitudinal relationships in the psychopathology of depressive symptoms in middle-aged and older adults in China

OBJECTIVES

To develop symptom networks and examine the longitudinal relationships of depressive symptoms among middle-aged and older adults in China.

METHOD

This study used three-wave data from the China Health and Retirement Longitudinal Study (2013 (T1), 2015 (T2), and 2018 (T3)). Depressive symptoms were measured by the 10-item Center for Epidemiologic Studies Depression Scale (CES-D). A multilevel vector autoregression model (VAR) was used to identify ten depressive symptoms dynamically interacting with each other over time.

RESULTS

A total of 3,558 participants were included in the final analysis. The strongest direct effects were 'D10: felt fearful' -> 'D6: felt everything I did was an effort' (β = 0.14). 'D10: felt fearful' reported the largest value of out-predictability (r = 0.064) and out-strength (r = 0.635). 'D3: felt depressed' reported the largest value of in-predictability (r = 0.077) and in-strength (r = 0.545). Substantial heterogeneity in the network may stem from an individual's sex and place of residence.

CONCLUSIONS

'Felt fearful' was the strongest predictor compared to the other nine depressive symptoms based on node centrality. Our study suggests that, after understanding the causes of fear, strategies to reduce fear should be incorporated into multimodal interventions for middle-aged and older adults with depressive symptoms.

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.

The relationship between alexithymia, depression, anxiety, and stress in elderly with multiple chronic conditions in China: a network analysis

Objective

This study aimed to construct a network structure to investigate the connections between alexithymia, depression, anxiety, and stress in Chinese older adults with multiple chronic conditions (MCC), identifying core and bridge symptoms, and comparing the network structure across different levels of alexithymia.

Methods

This study used a cross-sectional survey design and convenience sampling to recruit participants from six cities in Jiangsu Province. The study assessed the levels of alexithymia, depression, anxiety, and stress in older adults with MCC using the Toronto Alexithymia Scale (TAS-20) and the Depression Anxiety and Stress Scale-21 (DASS-21). Network analysis was performed using R language to identify core and bridge symptoms in the network and compare the network structure across different levels of alexithymia.

Results

A total of 662 participants were included in the analysis, including 395 men and 267 women. The mean age was 70.37 ± 6.92 years. The finding revealed that the "Difficulty Identifying Feelings" (DIF) node had the highest strength centrality (strength = 2.49) and predictability (rp = 0.76) in the network. The next highest strength centrality was observed for "Meaningless" (strength = 1.50), "Agitated" (strength = 1.47), "Scared" (strength = 1.42), and "No look forward" (strength = 0.75). They were identified as core symptoms. The bridge strength analysis identified "Panic," "Scared," "No wind down," "No initiative," and "No positive" as the bridge symptoms. There were notable differences in the overall network structure and specific connections between the groups with and without alexithymia (p < 0.05).

Conclusion

"DIF" is a core node in the network of older adults with MCC, indicating its significance as a potential target for psychological interventions in clinical practice. Preventing and mitigating bridge symptoms such as "panic," "Scared," "No wind down," "No initiative," and "No positive" can effectively impede the spread of symptom activation, thereby interrupting or severing the connections among comorbidities in older adults. Additionally, compared to non-alexithymia individuals, the psychological issues of older adults with alexithymia require prioritized intervention from healthcare professionals.

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.

Stress, Support, and Length of Diagnosis Among Women Living with HIV/AIDS in the Southern USA, During the COVID-19 Pandemic

Background

Health-related challenges caused and worsened by the global COVID-19 pandemic have proven broad and multifaceted, particularly for racial/ethnic minority women living with HIV (WLWH). The 2020 pandemic has affected the wellbeing and access to care for WLWH in Southeastern Florida, a region that experienced simultaneous high rates of COVID-19 and HIV. WLWH, over a short- or long-term period, likely utilize different coping mechanisms as they face these challenges.

Methods

This analysis compared pandemic-related stress and support endorsed by participants attending an urban clinic in South Florida, from January through May 2021. Participants completed an adapted version of the Pandemic Stress Index (PSI). The items in the PSI assessed emotional distress, stigma, and support, and were dichotomized, as either "stress" or "support". Mann-Whitney U-test assessed differences in distributions of PSI scores (stress and support) comparing long-term survivors (≥10 years with an HIV diagnosis) to those more recently diagnosed (<10 years).

Results

The cohort consisted of 63 WLWH, aged 21-71 (Mean = 42 years±12.95). The group of WLWH were almost evenly split, with 50.8% having been diagnosed in the last 10 years (short-term survivors). The high-stress group endorsed lower levels of support, compared to the low-stress group. There was a non-significant trend of higher stress scores for short-term survivors, compared to long-term survivors; and, higher support scores for long-term survivors, compared to short-term survivors.

Conclusion

Results suggest a trend in long-term survivor WLWH endorsing lower stress and higher support; the contrary was found for their short-term survivor counterparts. Patterns in COVID-19 related stressors and maladaptive behaviors need further exploration to establish suitable interventions that address disparities within groups of WLWH.

Unraveling the central and bridge psychological symptoms of people living with HIV: A network analysis

Background

People living with HIV (PLWH) experience multiple psychological symptoms. Few studies have provided information on central and bridge psychological symptoms among PLWH. This information has implications for improving the efficiency and efficacy of psychological interventions. Our study aimed to identify the central and bridge psychological symptoms of PLWH and to explore the interconnectedness among symptoms and clusters.

Methods

Our study used data from the HIV-related Symptoms Monitoring Survey, a multisite, cross-sectional study conducted during 2017-2021. We used R to visualize the network of 16 symptoms and analyzed the centrality and predictability indices of the network. We further analyzed the bridge symptoms among the three symptom clusters.

Results

A total of 3,985 participants were included in the analysis. The results suggested that sadness had the highest strength (r S = 9.69) and predictability (70.7%) compared to other symptoms. Based on the values of bridge strength, feeling unsafe (r bs = 0.94), uncontrollable worry (r bs = 0.82), and self-abasement (r bs = 0.81) were identified as bridge symptoms. We also found a strong correlation between sadness and self-abasement (r = 0.753) and self-loathing and self-blame (r = 0.744).

Conclusion

We found that sadness was the central psychological symptom of PLWH, indicating that sadness was the center of the psychological symptom network from a mechanistic perspective and could be a target for intervention. Deactivating bridge symptoms, including "feeling unsafe," "self-abasement," and "uncontrollable worry," could be more effective in preventing symptom activation from spreading (e.g., one symptom activating another).

Barriers and facilitators to maintaining a high level of polypharmacy adherence in people living with HIV: A scoping review

Objectives: With the prolongation of life span and increasing incidence of comorbidities, polypharmacy has become a challenge for people living with HIV/AIDS (PLWH). This review aimed to identify barriers and facilitators to maintaining a high level of polypharmacy adherence in people living with HIV/AIDS. Methods: Nine electronic databases were searched for studies from 1996 to October 2021. Studies were included if they were conducted with adults living with HIV/AIDS and reported barriers and facilitators to maintaining a high level of polypharmacy adherence. This review presents a conceptual framework model to help understand the barriers and facilitators. Results: Twenty-nine studies were included. The majority of publications were observational studies. Eighty specific factors were identified and further divided into five categories, including individual factors, treatment-related factors, condition-related factors, healthcare provider-related factors, and socioeconomic factors, based on the multidimensional adherence model (MAM). Conclusion: Eighty factors associated with polypharmacy adherence among people living with HIV/AIDS were identified and grouped into five major categories. Healthcare providers can make decisions based on the five categories of relevant factors described in this paper when developing interventions to enhance polypharmacy adherence. It is recommended that medications be evaluated separately and that an overall medication evaluation be conducted at the same time to prevent inappropriate polypharmacy use.

Identifying subtypes of HIV/AIDS-related symptoms in China using latent profile analysis and symptom networks

The identification of subgroups of people living with HIV in China based on the severity of symptom clusters and individual symptoms is crucial to determine group-specific symptom management strategies. Participants reported 27 highly prevalent HIV/AIDS-related symptoms. Latent profile analysis based on symptom severity was used to identify person-centered subtypes of HIV/AIDS-related symptoms. Symptom networks were compared among subgroups identified by latent profile analysis. A total of 2927 eligible people living with HIV (PWH) were included in the analysis. Five profiles were identified: "Profile 1: all low symptom severity" (n₂ = 2094, 71.54%), "Profile 2: medium symptom severity with syndemic conditions" (n₃ = 109, 3.72%), "Profile 3: medium symptom severity with low functional status" (n₁ = 165, 5.64%), "Profile 4: medium symptom severity in transitional period" (n₄ = 448, 15.31%), and "Profile 5: all high symptom severity" (n₅ = 111, 3.79%). Except for Profile 1 and Profile 5, the symptom severity was similar among the other three profiles. Profiles 1 (2.09 ± 0.52) and 4 (2.44 ± 0.66) had the smallest ∑s values, and Profiles 2 (4.38 ± 1.40) and 5 (4.39 ± 1.22) had the largest ∑s values. Our study demonstrates the need for health care professionals to provide PWH with group-specific symptom management interventions based on five profiles to improve their physical and psychological well-being. Future studies should be conducted in different contexts using different symptom checklists to further validate our results.

Exploring bridge symptoms in HIV-positive people with comorbid depressive and anxiety disorders

BACKGROUND

The prevalence of comorbid depressive and anxiety disorders in people living with HIV (PLWH) is high. However, it is unclear which symptom is the bridge symptom between depression and anxiety in PLWH. This study aimed to develop symptom networks for depression and anxiety and explore the bridge symptoms and interconnectedness between these disorders in PLWH with comorbid depressive and anxiety disorders.

METHODS

A multisite, hospital-based cross-sectional study was conducted from March 2020 to November 2021. Depression and anxiety were measured with the Hospital Anxiety and Depression Scale. We visualized the symptom network using the qgraph package and computed the bridge expected influence of each node. The GLASSO layout was used to generate undirected association networks.

RESULTS

A total of 2016 individuals were included in the analysis. In the anxiety cluster, "not feeling relaxed" had the highest bridge expected influence and strength (r_{bridge expected influence} = 0.628, r_strength = 0.903). In the depression cluster, "not feeling cheerful" was identified as having a high bridge expected influence (r_{bridge expected influence} = 0.385). "Not feeling cheerful" and "not feeling relaxed" were the strongest edges across the depression and anxiety clusters (r = 0.30 ± 0.02).

CONCLUSIONS

Healthcare professionals should take note when PLWH report severe bridge symptoms. To enhance the levels of perceived cheerfulness and relaxation, positive psychology interventions could be implemented.

Contemporaneous symptom networks of multidimensional symptom experiences in cancer survivors: A network analysis

BACKGROUND

Symptom networks can provide empirical evidence for the development of personalized and precise symptom management strategies. However, few studies have explored the symptom networks of multidimensional symptom experiences in cancer survivors. The objectives of this study were to generate symptom networks of multidimensional symptom experiences in cancer survivors and explore the centrality indices and density in these symptom networks METHODS: Data from 1065 cancer survivors were obtained from the Shanghai CANcer Survivor (SCANS) Report. The MD Anderson Symptom Inventory was used to assess the prevalence and severity of 13 cancer-related symptoms. We constructed contemporaneous networks with all 13 symptoms after controlling for covariates.

RESULTS

Distress (r_s  = 9.18, r_c  = 0.06), sadness (r_s  = 9.05, r_c  = 0.06), and lack of appetite (r_s  = 9.04, r_c  = 0.06) had the largest values for strength and closeness. The density of the "less than 5 years" network was significantly different from that of the "5-10 years" and "over 10 years" networks (p < 0.001). We found that while fatigue was the most severe symptom in cancer survivorship, the centrality of fatigue was lower than that of the majority of other symptoms.

CONCLUSION

Our study demonstrates the need for the assessment of centrality indices and network density as an essential component of cancer care, especially for survivors with <5 years of survivorship. Future studies are warranted to develop dynamic symptom networks and trajectories of centrality indices in longitudinal data to explore causality among symptoms and markers of interventions.