In 2020, the UK was one of the countries most affected by the pandemic. Despite the existence of cases since the last days of January, the British government released the state of containment by the end of March as they sought other alternatives such as acquiring herd immunity in the population (1). Along with these measures, the British government sought to be among the first to implement the COVID-19 vaccines, being distributed to high-risk groups such as older adults, their caregivers, and health care workers in early December (2). However, from September to December there was an increase in the number of infections due to a new strain of COVID-19, prompting the UK government to introduce social restriction measures to control the second wave outbreak (3). These measures involve continuing the state of quarantine, forced isolation, and lockdown in most European countries and around the world, as was the case during the first wave that lasted until the end of July (2).

Loneliness is defined as an unpleasant subjective perception resulting from poor interpersonal relationships, both in terms of the number of friends or companions, as well as the quality of the social ties established, so that the latter makes it easier to differentiate from objective isolation (4). The psychological effects of confinement during COVID-19 pandemic are still being studied, but some findings so far are concerning. Several systematic and longitudinal studies have linked the state of confinement to negative psychological effects such as stress, anxiety, and depression (5–8). Older adults are particularly vulnerable to these effects given their higher risk of contagion and fear of infection and death (9, 10). Additionally, home quarantines can lead to feelings of fear, insomnia, post-traumatic stress disorder, or distress in the absence of social connection and perceived social support, combined with the pandemic context of increased uncertainty and fatalistic news (11).

Depression is defined as an affective disorder that reduces vitality and involvement in activities that previously produced pleasure, accompanied by extreme tiredness, discouragement, and loss of meaning in life (12). Anxiety is an adaptive response that involves physiological and cognitive symptomatology to cope with states of restlessness and agitation in response to real or imagined danger (13). Both anxiety and depression are considered as responses to stressful events that produce biological and psychological changes in the organism (14). These disorders are considered the most common during old age because as time goes by and throughout the aging process people lose mobility, chronic and/or degenerative diseases appear, they show greater fragility and require the care of other people, which triggers negative emotional states (15, 16). This, coupled with higher levels of loneliness due to home quarantine in older adults, reinforces a higher degree of psychological vulnerability (17, 18).

A survey conducted in the UK during the onset of confinement revealed that 22.1% of subjects had depression and 21.6% had generalized anxiety, where these were the most common symptoms affecting mental health due to the COVID-19 outbreak (6). There is a strong correlation between the two variables because they share similar indicators such as loss of control, difficulty concentrating, and fear (19, 20). Generalized anxiety disorder implies a continuum with depression, such that people with this comorbidity will experience greater functional disability, worse prognosis and persistence of other diseases (8).

Recently, some authors have begun to reexamine psychopathology from a more dynamic perspective to explain that psychological constructs may be conceived as a network of multiple symptoms correlated with each other (21). A psychometric network consists of a set of nodes represented as psychological symptoms and edges for the relationship between such variables. Network analysis is a tool that facilitates the understanding of different psychological variables, their comorbidities, possible risk and protective factors, as well as the most central symptoms within the network structure (22). Thus, it is necessary to use complex interaction systems to examine the most significant symptoms and signs that are affected by the outbreak of COVID-19 and social isolation.

Although unpleasant feelings of isolation and lack of meaningful connections are known to be related to depressive and anxious symptoms, it is not known exactly in which direction these interconnected associations may occur in a network system, given the period of the first and second COVID-19 quarantine (11). Based on these periods of change during the pandemic, it is appropriate to examine this associative system of psychopathological variables using longitudinal network analysis. This perspective extends the application of other traditional network analysis methods by detecting complex and dynamic interactions across two or more temporal events through directed networks between symptoms (23); i.e., it allows to represent and identify those symptoms that are more predictive in a network based on established time points, so that it is possible to distinguish the symptoms that reinforce each other and maintain a certain symptomatology (24).

Given these characteristics, it may be applicable to understanding the variation in emotional and/or psychophysiological responses during different periods of COVID-19 quarantine in the UK. Therefore, the aim of this study was to examine and compare symptom networks of loneliness, depression, and anxiety in two specific quarantine periods in a population of older adults in the United Kingdom. Likewise, in accordance with previous findings on the overlapping nature of the variables (25, 26), we use the Clique Percolation Method (CPM) to examine symptoms that may belong to more than one community or overlap with it. From this, we sought to identify the most central measures that would allow the understanding of indirect associations between systems. Finally, we examined a longitudinal network structure that allowed us to represent the prediction and feedback between symptoms that may trigger certain dysfunctional symptomatological patterns manifesting in older adults during two critical periods of mandatory 2020 quarantine.

Table 1 shows the items at the descriptive level, where the depressive item of feeling lonely (D5) stands out with the highest score (M = 1.843, SD = 0.364), followed by depressed mood (D1; M = 1.84.5, SD = 0.371). The highest and lowest skewness and kurtosis values correspond to the items of difficulty in resting (A5) and feeling lonely (D5), respectively. On the other hand, in the item reliability assessment, the item-rest correlation indices proved to be >0.30, as expected (57).

In the two-waves contemporaneous network models (Figure 1), positive relationships between nodes were reported, where the relation between unhappiness (D4) and not enjoying life (D6; T1 r = 0.433; T2 r = 0.393) was the higher value, while the relation between trouble with relaxing (A4) and feeling excluded (L2; r = 0.0005) in time 1 (T1), and restless sleep (D3) with not enjoying life (D6; r = 0.002) in time 2 (T2) were the lowest values respectively. The explored clusters showed a coherent partitioning, while the percolated communities show that in Time 1 (T1), worry management (A2), trouble with relaxing (A4), and depressed mood (D1) items were overlapped by anxiety and depression communities; while the item of feeling lonely (D5) was overlapped by depression and loneliness communities; and unhappiness (D4) was overlapped by anxiety, depression and loneliness communities. Furthermore, in Time 2 (T2), feeling irritable (A6), depressed mood (D1), and restless sleep (D3) were overlapped by anxiety and depression communities, while feeling lonely (D5) and not enjoying life (D6) were overlapped by depression and loneliness communities. The CS-coefficient at time 1 (T1) and time 2 (T2) was CS = 0.75 for edge and strength stability.

At T1 the item of feeling nervous (A1) had the higher predictability (r2 = 0.60), while restless sleep (D3) had the lowest value (r2 = 0.18). Furthermore, at T2 the item of worry (A3) showed the higher predictability (r2 = 0.62), and restless sleep (D3) showed the lowest value (r2 = 0.20).

The network comparison test between T1 and T2 networks showed statistically significant differences only between the centrality indices of networks (p < 0.001); also, the adjacency matrices correlation coefficient showed linearity (rho = 0.86; p < 0.001), and in all of its centrality indices (p < 0.001).

Additionally, centrality indices are shown in Figure 2. At Time 1 the most central item was trouble with relaxing (A4; T1; EI1 = 1.162; EI2 = 2.152), and the lowest was restless sleep (D3; T1; EI1 = 0.479; EI2 = 0.932); while the higher bridge centrality was the item of depressed mood (D1; T1; BEI1 = 0.449; BEI2 = 0.901), the lowest bridge centrality 1-step was feeling unaccompanied (L1; BEI1 = 0.034) and bridge centrality 2-step was being afraid (A7; BEI2 = 0.293). On the other hand, at Time 2, some differences were founded, the highest one-step centrality was trouble with relaxing (A4; EI1 = 1.127) and two-step centrality was worry management (A2; EI2 = 2.170); the lowest centrality was restless sleep (D3; T2; EI1 = 0.499; EI2 = 0.974); while the highest bridge centrality 1-step was the depressed mood item(D1; T2; BEI1 = 0.478; BEI2 = 0.940) and the lowest were, in 1-step, feeling unaccompanied (L1; BEI1 = 0.057), and in 2-step, restlessness (A5; BEI2 = 0.315).

The temporal network shows cross-time effects from T1 to T2, most of the relationships were positive, except for being afraid (A7) predicted by not enjoying life (D6) that had a negative effect (β = −0.060). The highest relationships were on feeling isolated (L3) to feeling nervous (A1; β = 0.370), not enjoying life (D6) to feeling excluded (L2; β = 0.304), and feeling excluded (L2) to feeling nervous (A1; β = 0.284). In addition, all variables were autoregressive, except feeling nervous (A1), which did not show this characteristic, while feeling excluded (L2; β = 0.440) and not enjoying life (D6; β = 0.406) were the most autoregressive nodes. Furthermore, the regression model had excellent fit indices (CFI = 0.965; TLI = 0.965; SRMR = 0.010; RMSEA = 0.038) (Figure 3).

Finally, feeling nervous (A1) was the item more predicted at T2 (inPred = 0.544), and feeling isolated (L3) was the least predicted at T2 (inPred = 0.193). Furthermore, feeling isolated (L3) was the most predictive item at T1 (outPred = 0.193), while feeling nervous (A1) was the less predictive item at T1 (outPred = 0.000). This configures a direct predictive line from the feeling of loneliness to the enhancement of anxiety symptoms such as nervousness (Figure 4).

The United Kingdom was one of the countries with the highest number of infections during the beginning of the first wave of COVID-19 because the authorities expected herd immunity to develop in its entire population; however, as the number of infected people increased, they imposed a state of mandatory social isolation by the end of March as a control measure (1). During the months of September to December, a second wave occurred as a result of a new variant of the virus that led to a state of confinement (3). Of all age groups, older adults experience the greatest risk and vulnerability to COVID-19 symptoms due to the comorbidities of advanced age (58). They were also exposed to high levels of worry, anxiety, distress, sleep difficulties, feelings of loneliness, and depressive symptomatology due to fear of contracting the virus, fear of death, and involuntary social isolation (9, 10, 59, 60).

Regarding the first objective of the study, the estimated network during the first evaluation stage (June–July 2020) showed that anxiety symptoms were the most important (higher centrality), where item A4 (difficulty to relax) and item A1 (nervous or anxious) stood out. These results could be attributed to a stronger connection with the somatic symptoms of restlessness (A5) and generalized fear (A7). This could lead to an increased state of nervousness and difficulty relaxing in response to the rise in infections, contributing to higher levels of anxiety due to the increase in infections, hospitalizations and deaths due to COVID-19 (61), which is greater given the perception of belonging to an at-risk and more vulnerable population. Difficulty relaxing (A4) has been one of the most influential symptoms in previous network research involving symptoms of anxiety and depression during the initial pandemic stage of 2020 in adults in Asia, North America, and Europe (62–65). This finding was similar also in another study in UK adults during the first quarantine social restriction, which included overlapping symptoms of distress and loneliness (26).

As for the network analysis with the second wave data (November–December 2020), in addition to the anxious symptoms with greater centrality of the first wave, item A3 (overconcern) and item A2 (lack of control of worry) also stood out, which were more connected to each other. At the beginning of this period, obligatory quarantine was reinstated, and the elderly became the first to be isolated in the face of heightened infection alarm, in fact, over one million people had been infected in the UK (66). In this confinement, older adults were again more exposed to media and social networks that provided more fatalistic news related to the global pandemic (e.g., new variants of COVID-19), and were more aware of the perceived risk of death from the loss of a family member or friend (67). In addition, in early December, the UK started vaccinating the elderly in the UK as they were considered a vulnerable population (3), which triggered further distress due to existing controversies and conspiracy news about vaccination that reinforced further uncertainty and anxiety about possible side effects and lack of confidence about the benefits of the vaccine (68–70). Therefore, it was evident that older adults who were assessed during the second wave were still experiencing a tendency to worry in an exaggerated way and with difficulties in controlling worry. The latter anxious symptom has also been previously reported as one of the most central among interacting systems of anxious and depressive symptomatology in young and older adults during the pandemic (65, 71–73).

For the second objective, it is shown that the symptom of depressive state (D1) was the most directly and indirectly interconnected (bridging symptom) in both networks. These results are similar to other studies that considered psychological distress symptomatology in Chinese university students during the COVID-19 pandemic (71, 74, 75). Such a symptom may reinforce the influential comorbidity between the symptoms of the three communities, specifically it has a stronger direct connection with the symptom of lack of control over worry (A2) and exclusion (L2). People who feel socially excluded often experience negative emotions to the point of triggering depressive symptoms, such as feelings of sadness, anger, and decreased self-esteem (76–78). In addition, all of these symptoms increase worry about daily activities, which leads to an increase in symptoms of generalized anxiety. Several network studies during the pandemic reveal an association between these anxious symptoms and an increased depressive state (65, 74), indeed, a recent study by Tao et al. (71) indicates that lack of control over worry and depressed mood are more influential in the manifestation of psychological distress symptomatology in later stages of the pandemic. Studies have reported that adults older than 50 years report greater physical health problems, especially those with a diagnosis of depression (79). People with these comorbidities may present somatic and physiological symptoms that reinforce a greater degree of fatigue, lack of energy, and insomnia (80).

Another of the common results of both networks is the recognition of feeling lonely (D5), which is intertwined between the domains of depression and loneliness. Although this indicator is of an emotional nature, it is more closely related to symptoms of social loneliness, especially lack of companionship (L1). Other network studies found that perceived loneliness was more strongly related to depressive state in adults residing in Switzerland (81), while Feiten et al. (82) found that social withdrawal is connected with the emotional state of sadness. Given that high levels of loneliness have been reported during the first two waves of confinement in the UK in conjunction with depressive symptoms, this may reflect that the loss of social connectedness linked to social loneliness leads to less social engagement. Indeed, this interpersonal distancing often persists after the confinement state as a state of chronic loneliness (83) in the face of increased perceived social isolation, which has been shown to contribute to higher rates of morbidity and mortality (84, 85). It is especially of greater interest in older adults who find themselves with little social companionship, as loneliness is related to some harmful health behaviors such as poor diet, physical inactivity, alcohol consumption, and smoking (86).

In the first network, it is identified that the unhappiness measure (D4) is intertwined in the three network communities. This finding using the Clique Percolation method has been used in previous studies where symptoms and feelings interact which may be intertwined (87, 88) and partially aligns with another previous finding that identified the cross overlap of the symptom of sadness (unhappiness) between depression and anxiety in psychiatric patients (87). The network results obtained are more reliable compared to previous work with overlapping psychopathological symptomatology network that reported negative relationships between anxiety and depression symptoms, and even some symptoms did not correspond to any symptomatological community (26, 87).

In this first network it is also recognized that a greater number of symptoms are identified with the anxiety domain, which includes the symptom related to sleep problems (D3). Within the DSM-5 Mental Disorders Manual, such symptom is recognized as one of the diagnostic criteria for generalized anxiety disorder (GAD) (89). Therefore, it can be considered as a transdiagnostic symptom and of greater anxious impact produced by the first months of mandatory quarantine in older adults (90), which is more closely linked to difficulty relaxing (A4; higher expected influence and anxiety/depression overlap) in the first network. These findings are in line with previous studies pointing to the interaction of such symptoms in the network (26, 87), even in network outcomes where such symptoms are central (72, 91).

Additionally, in the second network we identified that the symptom of sleep difficulties (D3) presented a cross grouping within the structure of anxiety and depression, which indicated its more comorbid manifestation during the period of the second quarantine. Insomnia and difficulty initiating sleep have been reported to be related to symptoms of worry and depression in older adults (82). This finding has been evidenced in studies conducted in the last quarter of 2020, after the first wave, where the symptom of sleep problems was identified as the most interconnected measure in psychometric networks comprised of symptoms of anxiety, insomnia, and depression (62, 91).

Another difference in this network, was the unique membership of the unhappiness symptom (D4) in the depression community. This was likely a result of the re-implementation of lockdown measures, leading to increased feelings of dissatisfaction brought about by renewed social isolation and a perceived loss of freedom (92). This outcome was strengthened because the occurrence of unhappiness was linked with depressive emotions (D1). In this way, it could support previous research that highlights the connection between unhappiness and a depressive state in adults who had chronic conditions (93) and in pregnant Latina women (94).

On the other hand, we detected that the networks representing both waves showed a noticeable sequence of stronger and similar associative patterns: from the item of feeling lonely (D5), which reinforced the symptom of feeling depressed (D1), which interacted with other depressive indicators such as anhedonia (items D2 and D7) and difficulty to rest (D3), until connecting with the anxiety symptom of difficulty to relax (A4), which reinforced other anxious manifestations. It is likely that these findings denote a greater sense of emotional vulnerability that reinforced other psychophysiological symptoms more characteristic of anxiety in those older adults who felt a greater need for companionship during the COVID-19 quarantine period. This makes sense if we consider that this period originated disruptive events such as family estrangement and the adoption of new self-care health measures, events for which many older adults were not prepared to face, or even imply new burdens to pre-existing ailments or other difficulties (95, 96).

Finally, for the third objective, we identified the longitudinal network that included the variables during the two pandemic waves, we observed a clear influence directed toward the anxious symptom of nervousness (A1), mainly from the depressive symptom of difficulties to enjoy life (D6), which activated both the loneliness items about feeling excluded (L2) and apart from others (L3), and these in turn had a stronger direct effect on the nervousness symptom. These effects are similar to other reports that indicate that the prolongation and typical limitations of quarantine made the increase of symptoms linked to anhedonia more likely (97), while this state of low motivation propitiated a greater sense of helplessness, to the point of having the sensation of being alone or remaining distant from others (98).

In summary, it was evident that for the June-July stage network, anxiety symptoms were of greater centrality, where item A4 (difficulty in relaxing) and item 1 (nervous or anxious) stood out. Moreover, the network analysis of the second wave (November–December) found that in addition to the anxious symptoms with the highest centrality of the first wave, item A3 (overworrying) and item A2 (lack of control of worry) also stood out, which were more connected to each other. Similarly, the symptom of depressive state (D1) was reported to be the most directly and indirectly interconnected symptom (bridging symptom) in both networks. Another common finding in both networks is the cross-identification of the symptom of feeling lonely (D5) in the depression and loneliness domain. Finally, when identifying the longitudinal network that included the variables during the two pandemic waves, we observed a clear influence directed toward the anxious symptom of nervousness (A1), mainly the depressive symptom of difficulties in enjoying life (D6), which activated both the loneliness items about feeling excluded (L2) and apart from others (L3), and these in turn had a stronger direct effect on the nervousness symptom.

Publicly available datasets were analyzed in this study. This data can be found at: https://www.elsa-project.ac.uk/.

Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.

CR-V and AG contributed to the conceptualization, formal analysis, and drafting of the manuscript. MD and DH assisted in data curation and preparation of the original draft. JS have contributed to the research and writing of the manuscript. All authors have read and accepted the published version of the manuscript.