Resilience Mediates the Relationship Between Loneliness and Depression in Young Adults After the Death of a Parent Due to COVID-19

, it can be concluded that


INTRODUCTION
Currently, almost all parts of the world are facing Corona Virus Disease 19 , this virus was first detected on November 17, 2019, in China, precisely in Wuhan, and since March 9, 2020, the World Health Organization (WHO) has determined this virus to be pandemic (Fuadi & Irdalisa, 2020;Putri, 2020). Indonesia is one of 216 countries with confirmed cases of COVID-19. The COVID-19 case first appeared in Indonesia on March 2, 2020, anduntil October 26, 2021, it is known that 4,953,246 deaths have occurred due to Covid-19 worldwide (Kusuma et al., 2021;Wardana et al., 2023). Meanwhile, 143,270 deaths have occurred in Indonesia. In Indonesia, national data has recorded that more than 11 thousand children have lost their parents due to Covid-19 (Azizah et al., 2023;Haq et al., 2021). The outbreak of the Covid-19 virus has also caused anxiety in the community and has hurt the mental health of those who experience it (Ilpaj & Nurwati, 2020;Maulida et al., 2020). The large number of deaths due to the pandemic and the existence of policies for social distancing or keeping a distance can make the grieving process very difficult. Individuals cannot share their sorrow and grief with family, friends, or others (Aeni, 2021;Maulidya, 2021;Saputra et al., 2021).
In general, coping with the death of a parent is difficult for some people, especially for someone who lives with their parents. In Indonesia, individuals generally live with their parents until adulthood. Collective Indonesian culture emphasizes that each individual is responsible for his family, especially his parents (Cahayatiningsih et al., 2022;Enjelvestia & Parebong, 2021). A child should respect and serve his parents. One form of respect is caring for them when they are old (Djatmiko & Surjaningrum, 2022). Suppose an adult child experiences the loss of a parent due to death. In that case, this condition will greatly affect the individual's mental health, such as the emergence of stress, anxiety, and depression (Harjuna & Rafiq, 2022;Milawati & Widyastuti, 2023). Depression is a complex disorder involving cognitive, behavioral, and affective components (Jhonet et al., 2022;Ratunuman et al., 2021). One of the symptoms of depression is recurrent thoughts of suicide or attempts to commit suicide or self-harm. Individuals with depressive symptoms tend to take risks (Antari et al., 2022;Lempang et al., 2021).
Several things, including loneliness, can influence depression experienced by a person. Loneliness is a condition in which a person experiences boredom, anxiety, unhappiness, and dissatisfaction with the social relationships they have, so lonely individuals will not be involved in any social activities (Fathoni & Listiyandini, 2021;Sagita & Hermawan, 2020). Lonely individuals will tend to see suffering as a reality that does not change and not want to make efforts to improve their condition (Indriani & Raharjo, 2023;Widiani et al., 2022). In addition, lonely individuals perceive their loneliness as a difficulty rather than an opportunity for growth (Aditiono et al., 2022;Muttaqin & Hidayati, 2022). Therefore depressive symptoms can appear in individuals who experience loneliness (Tanzil et al., 2022). In the tragedy of the Covid-19 pandemic, loneliness in individuals can arise due to the loss of someone they love, such as a partner or parent.
Loneliness and depression experienced by individuals can be overcome by developing resilience. It is because resilience is a personal quality that allows a person to develop in the face of adversity (Faradisa et al., 2023;Maulidia et al., 2022). Individuals with good resilience can adapt their body, mind, and spirit to current life circumstances, so the higher their resilience, the lower the loneliness felt (Rachmawati et al., 2019;Ramadanti & Herdi, 2022). Loneliness and depression can be mediated by resilience because, in everyday life, resilience can overcome various difficulties, tragedies, and other negative events, so that the individual can reduce the possibility of mental health problems (Cao & Liu, 2020;Zhao et al., 2018). In addition, maximizing resilience can reduce loneliness and facilitate the recruitment of the emotional and psychological resources needed to manage aspects of life that can lead to depressive symptoms (Chasanah & Wijaya, 2023;Rohmadani & Winarsih, 2022). Individual resilience helps overcome and mediate stressors (e.g., loneliness and depression) (Tunliu et al., 2019).
Several studies that have been conducted previously reveal that building family resilience after the death of a husband due to Covid-19 requires the ability to survive and rise from deteriorating conditions face new situations, encourage the recovery process so that you can learn lessons and have a sense of optimism for the next family life (Lefia & Raihana, 2023). The results of other studies reveal that the higher the social support a person receives, the higher the resilience of survivors of Covid-19 (Wardana et al., 2023). The results of further research revealed that loneliness experienced by a person would increase the likelihood of depression (Aran et al., 2019). Based on some of the results of these studies, it can be said that resilience possessed by a person will be able to build self-confidence and inspire enthusiasm in living life. In previous research, no studies specifically discussed the Relationship between loneliness and depression mediated by resilience in young adults after the death of their parents due to Covid 19. So this research focused on this study to examine the relationship between loneliness and depression-mediated resilience in young adults after the death of a parent from Covid-19.

METHOD
This research belongs to the type of correlational quantitative research. In this study, participants were recruited using a non-probability sampling technique. This technique was carried out because the population in this study was not fully known. The sampling technique used in this study was purposive sampling, which is based on certain criteria. The number of participants in this study was 105 participants, with the criteria of participants in this study being young adults with an age range of 20 to 40 years, having lost a parent (father/mother) due to Covid-19, participants participating in the study voluntarily, and are citizens. Indonesian (WNI). Data collection in the study was carried out using the method of observation, interviews, and questionnaires, with the research instrument in the form of a questionnaire divided into four parts, the first being a questionnaire used to measure depression, loneliness and a questionnaire measuring resilience. The data obtained in the study were then analyzed using the statistical package for service solution (SPSS) application. The data analysis in this study will be carried out using the classical assumption test, namely the normality test, heteroscedasticity test, linearity, and multicollinearity. Next is a descriptive test. Then proceed with the correlation test, and the last is the mediation test using PROCESS.

Result
The research analysis was carried out through the assumption test and analysis of the research hypothesis. The assumption test in this study consisted of a normality test, a linearity test, a heteroscedasticity test, and a multicollinearity test. Meanwhile, hypothesis testing was carried out through a correlation test for loneliness and depression, a correlation test for resilience and depression, a correlation test for resilience and loneliness, and a mediation test for resilience on the Relationship between loneliness and depression. First, the assumption test in the study begins with carrying out the data normality test. The normality test was conducted to see whether this study's data distribution was normal. The data was declared normally distributed if the significance was greater than 0.05. In this study, initially, the researcher used the One Sample Kormogorov-Smirnov Test with the Asymptotic Technique to test the normality of the variables of loneliness, depression, and resilience. From the analysis results, it was found that of the three variables, only the resilience variable had a normal distribution P = 0.147 > 0.05. Details of the data can be seen in Table 1. Because the variables of loneliness and depression do not have normal data when using the Asymptotic Technique, the normality test is continued using the Monte Carlo Technique for the variables of Loneliness and Depression. The results show that the lonely and depression variables are normally distributed with values for P = 0.232 > 0.05 (loneliness) and P = 0.262 (depression). Details of the data can be seen in Table 2. Thus, the three variables are normally distributed, and testing the Relationship between the study variables uses parametric statistics. After the data normality test results were obtained, the analysis continued with the linearity test, which was used to determine whether the research variables had a linear relationship. The two research variables are said to meet the linearity assumption if the p-value> 0.05 and vice versa. The linearity test in this study used the compare means test technique presented in Table 3.
The data in Table 3 shows a significant linear relationship between the variables of loneliness, resilience, and depression. It is because the sig value > 0.05. The third analysis is the heteroscedasticity test which was carried out to know whether the variables' variance is the same or not the same. The testing technique uses a scatter plot by showing that the data spread above and below or around the numbers, the data does not collect only above or below it, the spread of the data does not form a wavy pattern widening then narrowing and widening again, and the distribution of data is not patterned. Based on the dependent variable, namely depression, and the independent variables, loneliness and resilience, a scatterplot that meets all the criteria is obtained. In more detail, the data distribution can be seen in Figure  1. After the results of the heteroscedasticity test were obtained, the analysis continued with the multicollinearity test, which was carried out to see whether or not there was a high correlation between the independent variables in a multiple linear regression model. If there is a high correlation between the independent variables, the relationship between the independent and dependent variables is disrupted (Ghozali, in Setiawati, 2021). This condition can be seen from the Tolerance value > 0.10. No collinearity relationship or VIF (Variance Infation Factor) <10 means the collinearity level can be tolerated. The results of the multicollinearity test show that loneliness and resilience have a Tolerance value of > 0.817 (Tolerance > 0.10) and a VIF value of 1.224 (VIF < 10). Thus it can be interpreted that there is no multicollinearity among the dependent variables. More detailed results of the multicollinearity test can be seen in Table 4. Second, after obtaining all the results of the assumption test, the research analysis is then continued with the analysis of the research hypothesis, which begins with a correlation test of loneliness and depression. Because the three variables in this study are normally distributed, the correlation test uses Pearson Correlation. Correlation test results between loneliness and depression show that r (105) = 0.617, p = 0.000 <0.05. Therefore, it can be concluded that there is a positive relationship between the variables of loneliness and depression. Due to the positive direction of the Relationship, this means that the higher the loneliness, the higher the depression. Details of the data can be seen in Table 5.

Relationship
Correlation Coefficient (r) Sig (2-Tailed) Loneliness and Depression 0.615 0.000 The next analysis is the correlation test of resilience and depression. The correlation test results between resilience and depression showed that r (105) = -0.412, p = 0.000 <0.05. These results explain a significant negative relationship between resilience and depression. The Relationship indicates that the higher the resilience, the lower the level of depression. Details of the data can be seen in Table 6. Furthermore, the correlation test results for resilience and loneliness show that r (105) = -0.426, p = 0.000 <0.05. These results explain a significant negative relationship between resilience and loneliness. The results are significant because p < 0.05, while the negative Relationship indicates that the higher the resilience, the lower the level of loneliness and vice versa. Details of the data can be seen in Table 7. The final hypothesis test analysis is the resilience mediation test on the Relationship between loneliness and depression through the analysis of the simple mediation model 4 PROCESS v 4.1 developed by Andrew F. Hayes. In testing this hypothesis, if the p-value <0.05 means there is a significant relationship between these variables, then if there is a positive coefficient (β), it means a positive relationship between the variables. If the coefficient (β) is negative, variables have a negative relationship. The results of the hypothesis testing that has been done can be seen in Table 8. Based on the Table 8, the results show that loneliness (X) significantly affects resilience (M). The results obtained are β = -0.430, p = 0.000 <0.05. The magnitude of the effect of loneliness (X) on resilience (M) is 18.3%, R2 = 0.183. It can be concluded that these two variables have a negative relationship, which means that the higher the loneliness, the lower the resilience. Furthermore, it is known that loneliness (X) can significantly affect depression (Y) β = 0.646, p = 0.000 <0.05. The magnitude of the influence between loneliness (X) on depression (Y) is 37.9%, R2 = 0.379. It can be concluded that the two variables have a positive relationship, which means that the higher the loneliness, the higher the depression.
After the mediator variable, namely resilience (M), is controlled, the Relationship between loneliness (X) and depression (Y) becomes significant. This is known based on the value of β = 0.564, p = 0.000 <0.05. Meanwhile, if loneliness (X) is controlled, then there is also a significant influence between resilience (M) on depression (Y) β = -0.191, p = 0.000 <0.05. The magnitude of the effect of resilience as a mediator of loneliness on depression is 40.6%, R2 = .406, p = 0.000 <.05, with an effect size of 0.078. The path of the mediation analysis that researchers have carried out can be seen in Figure 2.
From the Figure 2, it is known that the direct effect in this study was 0.564. The direct effect is the effect of exposure to the results of the absence of the mediator variable. This study shows the influence between loneliness and depression without resilience as a mediator variable. Then, it is also known that the indirect effect in this study is 0.082. Indirect effect or indirect effect is the effect of exposure to results that work through mediators. In this study, what is meant is the effect of loneliness and depression when the variable resilience is included as a mediator.
Meanwhile, the total effect is the sum of the two channels (direct and indirect) or the sum of the direct effects and all indirect effects contained in this study. Based on the results of the analysis, it is known that the resilience coefficient as a mediator is 0.082 with an LLCI value of 0.002 and a ULCI value of 0.1741 because the BootLLCI and BootULCI ranges do not include a value of zero (0), it can be concluded that the estimation is significant and a mediating effect occurs. However, in this study, there was partial mediation because the effect of loneliness on depression, which was previously significant (before the resilience variable), became still significant after including the resilience variable. In other words, loneliness and depression can be related directly without going through a mediating variable (resilience).

Discussion
Based on the results of the data analysis that has been done, it can be seen that the resilience that exists in a person influences feelings of loneliness and depression levels after losing a parent. These results then explain that resilience has the potential to reduce levels of loneliness and subsequently reduce depression. It is because resilience is the ability that a person has to deal with various problems, and this resilience can be seen through the attitude shown when a person adapts and finds solutions to the problems faced (Cao & Liu, 2020;Zhao et al., 2018). In everyday life, someone with good resilience will show attitudes based on seven important aspects, such as emotion regulation, related to one's ability to control one's emotions and act positively. Impulse control is related to one's ability to delay or control bad behavior. Optimism related to individual expectations and beliefs about overcoming difficulties encountered, clause analysis, empathy, and self-efficacy as indicated by an attitude of the belief that one will be able to overcome various problems, as well as achievement as indicated by an attitude of daring to try new things to get the best results (Aniyatuzzulfah et al., 2022;Chasanah & Wijaya, 2023;Rohmadani & Winarsih, 2022).
Self-resilience is very much needed by teenagers who have lost their parents after the Covid-19 pandemic. Through resilience, a person can develop the ability to think positively and reduce the possibility of depression (Faradisa et al., 2023;Maulidia et al., 2022). As we all know, the Covid-19 pandemic has negatively impacted people's lives. One of them is the emergence of many symptoms of depression caused by the loss of loved ones and the emergence of feelings of loneliness due to the implementation of social distancing policies (Antari et al., 2022;Lempang et al., 2021). During the time of the spread of the Covid-19 pandemic virus, the social distancing policy was considered one of the right solutions to reduce the spreading of the virus.
This policy caused many people to experience depression because they had to remain silent for a long time (Tanzil et al., 2022). Depression is when a person experiences prolonged sadness, losing interest in activities usually carried out in everyday life (Fathoni & Listiyandini, 2021;Sagita & Hermawan, 2020). A person who is depressed generally shows an attitude of being easily sad/angry, easily discouraged, and excessive worry about something (Indriani & Raharjo, 2023;Widiani et al., 2022). One of the factors that causes depression is the emergence of a feeling of loneliness.
During the spread of the Covid-19 pandemic virus, many teenagers had to lose their parents because they were infected with a virus outbreak. It is this sudden loss of parents which then creates a feeling of loneliness in the child. Loneliness is generally indicated by a condition where a person experiences boredom, anxiety, unhappiness, and dissatisfaction with the social relationships they have so that lonely individuals will not be involved in any social activities (Rachmawati et al., 2019;Ramadanti & Herdi, 2022). Lonely individuals will tend to see suffering as a reality that does not change and not want to try to improve their condition (Faradisa et al., 2023;Maulidia et al., 2022). So that resilience is needed to reduce loneliness and depression among adolescents who have lost their parents.
The results obtained in this study are in line with the results of previous research, which also revealed that building family resilience after the death of a husband due to Covid-19 requires the ability to survive and rise from deteriorating conditions, face new situations, encourage the recovery process so that you can learn lessons and have a sense of optimism for further family life (Lefia & Raihana, 2023). The results of other studies reveal that the higher the social support a person receives, the higher the resilience of survivors of Covid-19 (Wardana et al., 2023). The results of further research revealed that