Network analysis of anxiety and depressive symptoms during the COVID-19 pandemic in older adults in the United Kingdom

The health crisis caused by COVID-19 in the United Kingdom and the confinement measures that were subsequently implemented had unprecedented effects on the mental health of older adults, leading to the emergence and exacerbation of different comorbid symptoms including depression and anxiety. This study examined and compared depression and anxiety symptom networks in two specific quarantine periods (June-July and November-December) in the older adult population in the United Kingdom. We used the database of the English Longitudinal Study of Aging COVID-19 Substudy, consisting of 5797 participants in the first stage (54% women) and 6512 participants in the second stage (56% women), all over 50 years of age. The symptoms with the highest centrality in both times were: "Nervousness (A1)" and "Inability to relax (A4)" in expected influence and predictability, and "depressed mood (D1"; bridging expected influence). The latter measure along with "Irritability (A6)" overlapped in both depression and anxiety clusters in both networks. In addition, a the cross-lagged panel network model was examined in which a more significant influence on the direction of the symptom "Nervousness (A1)" by the depressive symptoms of "Anhedonia (D6)", "Hopelessness (D7)", and "Sleep problems (D3)" was observed; the latter measure has the highest predictive capability of the network. The results report which symptoms had a higher degree of centrality and transdiagnostic overlap in the cross-sectional networks (invariants) and the cross-lagged panel network model of anxious and depressive symptomatology.

Exploring the dynamics of perioperative symptom networks in colorectal cancer patients: a cross-lagged panel network analysis

BACKGROUND

Colorectal cancer incidence is on the rise, necessitating precise symptom management. However, causal relationships among symptoms have been challenging to establish due to reliance on cross-sectional data. Cross-lagged panel network (CLPN) analysis offers a solution, leveraging longitudinal data for insight.

OBJECTIVE

We employed CLPN analysis to construct symptom networks in colorectal cancer patients at three perioperative time points, aiming to identify predictive relationships and intervention opportunities.

METHODS

We evaluated the prevalence and severity of symptoms throughout the perioperative period, encompassing T1 the first day of admission, T2 2-3 days postoperatively, and T3 discharge, utilizing the M. D. Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI). To identify crucial nodes in the network and explore predictive and interactive effects among symptoms, CLPNs were constructed from longitudinal data in R.

RESULTS

The analysis revealed a stable network, with disturbed sleep exhibiting the highest out-EI (outgoing expected influence) during T1. Distress had a sustained impact throughout the perioperative. Disturbed sleep at T1 predicted T2 bloating, fatigue, distress, and pain. T1 distress predicted T2 sadness severity. T2 distress primarily predicted T3 fatigue, disturbed sleep, changes in taste, and bloating. T2 shortness of breath predicted T3 changes in taste and loss of appetite. Furthermore, biochemical markers like RBC and ALB had notable influence on symptom clusters during T1→T2 and T2→T3, respectively.

CONCLUSION

Prioritizing disturbed sleep during T1 and addressing distress throughout the perioperative phase is recommended. Effective symptom management not only breaks the chain of symptom progression, enhancing healthcare impact, but also eases patient symptom burdens.

Longitudinal network relations between symptoms of problematic internet game use and internalizing and externalizing problems among Chinese early adolescents

OBJECTIVE

There has been growing evidence of comorbidity between problematic internet game use and internalizing and externalizing problems in young people. However, little is known about the directionality and gender differences in these longitudinal relations at the symptoms level in the framework of network theory among youth. This study estimated the longitudinal relations between the symptoms of problematic internet game use, internalizing and externalizing problems, and the gender differences of these relations in Chinese youth using cross-lagged panel network modeling (CLPN).

METHODS

A sample of 1269 Chinese youth (M age = 10.35 years) participated in this study semi-annually at two time points. CLPN analysis was used to calculate the network model of problematic internet game use and internalizing and externalizing problems to explore bridge symptoms and find transmission pathways between problematic internet game use and internalizing and externalizing problems.

RESULTS

The CLPN revealed significant gender differences. For boys, depressed mood, which leads to relationships turning sour in order to play online games, bridges the relations between internalizing symptoms and problematic internet game use. For girls, irritability is the central predictive symptom, causing a range of problems related to problematic internet game use, which can, in turn, lead to fights or feelings of worthlessness. However, the effect sizes for the pathways between problematic internet game use and internalizing/externalizing problems were relatively weak, and the comorbidity between their relations should not be over-interpreted.

CONCLUSIONS

The current findings provide new evidence for understanding the directional relationship between the central characteristics of problematic internet game use and internalizing and externalizing problems in boys and girls. Gender-specific interventions targeting the central symptoms of internalizing and externalizing problems and problematic internet game use can help mitigate the vicious cycle of comorbidity among adolescents.