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Article

Online Religious Involvement, Spiritual Support, Depression, and Anxiety during the COVID-19 Pandemic

by
Jieun Yoo
Department of Christian Education, Anyang University, Anyang 14028, Korea
Religions 2022, 13(11), 1052; https://doi.org/10.3390/rel13111052
Submission received: 17 October 2022 / Revised: 27 October 2022 / Accepted: 27 October 2022 / Published: 2 November 2022
(This article belongs to the Section Religions and Health/Psychology/Social Sciences)
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Abstract

:
A growing body of research has shown that religious involvement is related to individuals’ mental health outcomes. This study aimed to understand how online religious involvement impacts depression and anxiety mediated by spiritual support among Korean adults during the COVID-19 pandemic using structural equation modeling. The study also examined gender differences in the latent variables and pathways using a latent mean analysis and multigroup structural analysis. The results showed that Korean men had greater online religious involvement and spiritual support and less depression and anxiety than women. Further, it was found that the relationship between online religious involvement and depression was fully mediated by spiritual support only for Korean men, which suggests the importance of online religious involvement and spiritual support in predicting depressive symptoms during a pandemic.

1. Introduction

The relationship between religiosity, mental health, and well-being has been discussed for years; yet, these relations have been empirically examined only to some extent (George et al. 2002; Koenig et al. 2012; Lee and Newberg 2005; Thoresen and Harris 2004; Yoo 2017; You et al. 2019). Religious or spiritual support has proven beneficial to cope with stressful situations (Ai et al. 2005; Fiala et al. 2002) and enhance psychological outcomes (Balboni et al. 2007; You and Yoo 2016). While many studies have linked religiosity to mental health constructs, further studies are warranted on its association with depression and anxiety, which are among the most prevalent and debilitating mental disorders (McCullough and Larson 1999; Vasegh and Mohammadi 2007). Many studies have linked religiosity and depression, but anxiety has been relatively overlooked compared with depression (Shreve-Neiger and Edelstein 2004).
Since the rapid spread of COVID-19, social and economic activities have continued to decline worldwide. Concerns about the direct or indirect impact of the COVID-19 pandemic on mental health have emerged (Holmes et al. 2020). During the pandemic, researchers conducted many studies among various social groups, taking into account its impact on social and individual life (Kowalczyk et al. 2020; Algahtani et al. 2021; Głaz 2022). In the United States, there has been an increase in symptoms of anxiety or depressive disorders (Panchal et al. 2021), and similar results were presented in Korea (Bahk et al. 2021). In addition, the Korean government enforced social distancing rules in response to the pandemic. Religious institutions, such as churches or Buddhist temples, were asked to restrict gatherings to 20 or fewer people during the summer of 2020, and they are currently hosting 20% or less of their usual number of worship services (up until June 2021). Korean churches and temples had no choice but to provide online services or activities, and they are still doing so. Therefore, it is meaningful to explore the potential association between online religious involvement, spiritual support, depression, and anxiety among Korean adults owing to the COVID-19 pandemic.

1.1. Religious Involvement, Spiritual Support, Depression, and Anxiety

While religious involvement is considered to encompass social and personal dimensions (Sloan et al. 1999), multidimensional aspects of religious involvement have been discussed, such as religious practices or lifestyles, belief in God, religious activities or behaviors, and religious values (Hall et al. 2008; Roth et al. 2012). Attendance at religious services, spiritual help-seeking, and the salience of religion in daily life have been used to measure general religious involvement (Schnittker 2001). Levin et al. (1995) proposed three dimensions of religious involvement by conceptualizing African American religious involvement: organizational religious involvement, such as attending religious services; non-organizational religious involvement, such as praying or reading the Bible; and subjective religious involvement, such as the importance of faith in daily lives.
Despite the growing interest in the association between religious involvement and subjective well-being, such as life satisfaction or happiness (Ellison 1991; Hadianfard 2005; Keshavarz et al. 2009; Swinyard et al. 2001; Wnuk and Marcinkowski 2014; Yoo 2017), research related to its psychological effects on mental disorders is relatively limited. Depression and anxiety are among the most common debilitating mental health outcomes (McCullough and Larson 1999; Vasegh and Mohammadi 2007). In Korea, depression ranked the highest among the risk factors for suicidal mortality for individuals in their 20s and 30s and ranked second for those in their 40s and 50s. Korea has the highest suicide rate among countries of the Organization for Economic Co-operation and Development (Statistics Korea 2016). Anxiety is also the leading cause of suicidal ideation and suicide attempts (Bolton et al. 2008; Kanwar et al. 2013; Lee et al. 2015) and one of the most prevalent mental disorders among Korean women (Cho et al. 2015; Lee et al. 2015). Along with depression, anxiety has been gradually increasing in Korea; as a result of the COVID-19 pandemic, anxiety levels and depression are expected to rise rapidly and have increased (Bahk et al. 2021).
Although the findings on the relationship between religious involvement and psychological distress were not altogether consistent across studies (Koenig 2012; Paine and Sandage 2017), it has been observed that religious involvement is negatively associated with depressive symptoms (Desrosiers and Miller 2007; Ellison and Flannelly 2009; Jansen et al. 2010; Koenig 2007; Mackenzie et al. 2000; Van Voorhees et al. 2008) and anxiety (Abdel-Khalek et al. 2019; Harris et al. 2002; Jansen et al. 2010; Leonardi and Gialamas 2009; Mackenzie et al. 2000; Zohra and Irshad 2012). Korean research also supported that religious involvement predicted lower levels of depression. For example, Kang and Cho (2013) showed that subjective religious activities and faith attitudes had a negative effect on depression among the Korean elderly. You et al. (2019) reported that engaging in worship attendance, prayer outside of religious services, and perceived religiousness were associated with lower levels of depression among Korean adults. Kang and Romo (2011) found that religious involvement, such as church engagement, was indirectly linked to less depressive symptoms among Korean American adolescents. In addition, some Korean studies found a negative association between religious involvement and anxiety (Han 2002; Lee et al. 2017).
Spiritual support is theoretically conceived as the support derived from an intimate connection with God (Maton 1989) or as a form of social support that alleviates stress and increases resilience through a relationship with God (Levin 1994). Spiritual support generally functions as a buffer against daily stress by producing appropriate coping mechanisms (Mackenzie et al. 2000). Perceived support from a higher power through religious involvement provides an interpretation of their stressful situations (Ai et al. 2005; Park and Cohen 1993) and enhances emotional support that leads to positive attitudes, which in turn is associated with better mental health (Ai et al. 2005; You and Yoo 2016). This cognitive and emotional process contributes to adaptive coping with negative life events. Thus, spiritual support through religious involvement is expected to be related to decreased depression and anxiety.
Previous studies have provided increasing evidence that religious involvement is negatively related to mental health outcomes, such as depression and anxiety. In addition, spiritual support from religious involvement is beneficial for coping with stressful situations and, in turn, enhances subjective well-being and decreases negative mental illness. However, empirical research on this relationship merits further exploration with respect to a sample of Korean adults. In particular, as online worship is becoming the new normal in Korea because of COVID-19, a study on the relationship between online religious involvement, spiritual support, depression, and anxiety is crucial.

1.2. The Present Study

Previous research has indicated that religious involvement is expected to influence depression and anxiety. It was found that individuals involved in religion rely on God to understand their stressful situations, and this belief might decrease their negative mental health outcomes. Therefore, this study aims to understand how online religious involvement influences depression and anxiety via spiritual support during the COVID-19 pandemic. Specifically, this study intends to investigate the relationship among four variables: online religious involvement, spiritual support, depression, and anxiety using a structural equation modeling (SEM) research design and a sample of Korean adults. Religious involvement, depression, and anxiety have also been reported differently according to gender, with rates among women reported higher than those for men in general (Andrade et al. 2003; Bahrami and Yousefi 2011; Hakamata et al. 2009; Lindemann 1996; Maier et al. 1999; McFarland 2010; Mirola 1999). Using a latent mean analysis (LMA) and multigroup structural model analysis, this study additionally aimed to examine gender differences in the values of all the variables and the pathways from online religious involvement to depression and anxiety via spiritual support. The results will provide insights to help researchers understand the online religious involvement that continues to influence and improve individuals’ mental health outcomes.

2. Methods

2.1. Procedure and Participants

The participants were students from a Protestant-affiliated college and adult members from ten local churches in South Korea. A total of 210 Korean adults participated in this study’s research survey via a Google survey form (https://forms.gle/oKEKE8XfoXgv5YqLA, accessed on 17 October 2021) between 2 March 2021, and 2 April 2021, when the government’s restrictions (e.g., when the ban on social gatherings of five or more people and a limit of 20% (or less) on the regular number of worships at religious facilities) were enforced. Participants’ age ranged from 18 to 74 years, and the mean age was 26.4 (SD = 10.81). The sample consisted of 138 (65.7%) women and 72 (34.3%) men. Participants comprised 176 (83.8%) Protestants, four (1.9%) Buddhists, three (1.4%) Catholics, two (1.0%) other religions, and 25 (11.9%) non-religious affiliations. Participants were identified as having the following educational status: one (0.5%) middle school diploma, five (2.4%) high school diploma, 150 (71.4%) college, 24 (11.4%) college degrees, and 30 (14.3%) graduate degrees. A total of 167 (79.5%) participants identified themselves as single, 42 (20.0%) were married, and one (0.5%) was widowed.

2.2. Measurement

2.2.1. Online Religious Involvement

Online religious involvement was assessed using the revised Multidimensional Measure of Religious Involvement Scale (MMRI; Levin et al. 1995). The revised MMRI measures three aspects of participants’ religious involvement online. Organizational religious involvement was assessed with one item (e.g., “How often do you attend online religious services during COVID-19?”). Participants reported on a 5-point scale (1 = never; 2 = one to three times a year; 3 = four to nine times a year; 4 = one to three times a month; 5 = at least once a week). Non-organizational religious involvement was assessed with one item (e.g., “How often do you pray or do religious activities outside of religious services online during COVID-19?). Participants reported on a 5-point scale (1 = never; 2 = about once a month; 3 = about once a week; 4 = about once a day; 5 = several times daily). Subjective religious involvement was measured with one item (e.g., “In general, how important is your faith or spiritual beliefs as a source of strength in your day-to-day life via online religious activities during COVID-19?”). Participants reported using a 4-point scale (1 = not at all important; 2 = not too important; 3 = fairly important; 4 = very important). Each item was coded such that higher values indicated higher online religious involvement. For the current sample, Cronbach’s alpha was 0.70.

2.2.2. Spiritual Support

Spiritual support was measured using the spiritual support scale (SSS; Ai et al. 2005). This twelve-item measure (e.g., “Care from God provides me with peace and contentment in times of uncertainty”) assesses perceived support derived from a relationship with God through online religious involvement. Items are rated on a 4-point Likert scale (1 = strongly disagree and 4 = strongly agree). Each item was coded such that higher values indicated higher spiritual support. For the current sample, Cronbach’s alpha was 0.98.

2.2.3. Depression

Depression was measured using the Center for Epidemiology Studies Depression Scale (CES-D; Radloff 1977). This 20-item measure (e.g., “During the past week, I was bothered by things that usually don’t bother me”) assesses depressive symptomatology in the general population during the past week. Participants rated their answers on a 4-point Likert scale (1 = not at all and 4 = 5–7 times). The total score was calculated by reverse coding the positively worded items and combining all item scores. Each item was coded such that higher values indicated more depressive symptoms. For the current sample, Cronbach’s alpha was 0.93.

2.2.4. Anxiety

Anxiety was measured using the Generalized Anxiety Disorder Scale-7 (GAD-7; Spitzer et al. 2006). This seven-item measure (e.g., “Over the last 2 weeks, how often have you been bothered by following problems? Feeling nervous, anxious, or on the edge?”) assessed general anxiety symptoms. Participants rated their answers on a 4-point Likert scale (1 = not at all and 4 = 5–7 times). Each item was coded such that higher values indicated higher anxiety levels. Cronbach’s alpha for the current sample was 0.90.

2.3. Data Analysis

For the analysis, Predictive Analytics SoftWare (PASW) 18.0 was used for general descriptive statistics, reliability, and correlation analysis of the variables, whereas AMOS 18.0 was used for SEM. SEM examines the direct and indirect relationships suggested by the structural model. A structural model was set with online religious involvement as a predictor, spiritual support as its outcome, and depression and anxiety as the final outcome of the entire structural model. In addition, this study conducted an LMA and multigroup structural analysis to find differences between male and female groups (Hong et al. 2003). The analyses were performed using the maximum likelihood estimates. Model fit was evaluated using the following criteria: ratio chi-square statistics/degrees of freedom (χ²/df), the fitness index, one absolute model fit criterion (root-mean-square error of approximation, RMSEA), two relative model fit criteria (Tucker–Lewis index, TLI, and the comparative fit index, CFI). As the chi-squared test (∆χ² test) is highly sensitive to sample size, the model fit was measured using RMSEA, TLI, and CFI (Hu and Bentler 1999). Values lower than 0.08 for RMSEA and values over 0.9 for TLI and CFI were considered acceptable (Hu and Bentler 1999; Kim et al. 2009).

3. Results

3.1. Descriptive Statistics

Table 1 shows a summary of the correlations, mean values, standard deviations, skewness, and kurtosis of online religious involvement, spiritual support, depression, and anxiety. Significant correlations were found among the study variables. The correlation coefficients between online religious involvement and spiritual support were positive for both groups. The correlation coefficients between online religious involvement and depression and anxiety were significantly negative for men but not for women. Depression and anxiety were positively correlated in both groups. These findings confirmed that there were gender differences in the relationships between online religious involvement, spiritual support, depression, and anxiety. According to the guidelines for severe non-normality (i.e., skewness within ±2; kurtosis within ±4) (Byrne 2010; Kim et al. 2009), the assumption of normality was met for all variables.

3.2. Construct Validity Test and Fitness Test of the Model

Convergent validity refers to the extent of correlations between the measurement instruments of one latent variable. Methods to assess convergent validity include construct reliability (CR) and average variance extracted (AVE) (Fornell and Larcker 1981; Hair et al. 2010). CR values above 0.7 and AVE values above 0.5 are acceptable. Convergent validity was acceptable because the values of CR were 0.906 for spiritual support, 0.866 for depression, 0.912 for anxiety, and close to 0.7 (0.644) for online religious involvement. The AVE values were 0.583–0.736 in this study. Moreover, discriminant validity is acceptable because the AVE for each construct is greater than its shared variance (i.e., squared correlation) (Fornell and Larcker 1981). The model showed an acceptable fit based on the chi-squared test and the fitness indices TLI, CFI, and RMSEA (χ² (df = 583, N = 210) = 1102.126, p = 0.000, TLI = 0.934, CFI = 0.939, RMSEA = 0.046).

3.3. Construct Equivalence Test

A comparison was conducted in all measurement models to measure the four latent variables to test configural invariance. The fit of the baseline model (Model 1) showed acceptable fit indices (χ² (df = 366, N = 210) = 679.525, p = 0.000, TLI = 0.915, CFI = 0.926, RMSEA = 0.064) (see Table 2). The metric invariance has invariance restriction and identical factor coefficients on variables for the male and female groups. To verify metric invariance, the χ² values and the degree of freedom of the metric invariance model (Model 2) were compared with configural invariance (the baseline model). The difference between the χ² values of the baseline model and the metric invariance model was statistically significant at α = 0.05 (∆χ² (17, N = 210) = 24.619). However, the fit indices for metric invariance were not worse than those for configural invariance (∆TLI = 0.002, ∆RMSEA = −0.001), and metric invariance was supported. The next step was to test scalar invariance. The scalar invariance model (Model 3) was not supported because the difference in χ² values between Models 2 and 3 was statistically significant at α = 0.05 (∆χ² (21, N = 210) = 45.289). However, the fit indices for scalar invariance were not worse than those for metric invariance (∆TLI = −0.002, ∆RMSEA = 0.001), and the scalar invariance model (Model 3) was accepted (Kim et al. 2009). Therefore, the measurement tool used in this study could be applied equally to both female and male groups. The mean differences in this study reflect real differences in the latent variables.

3.4. Latent Mean Analysis

As configural, metric, and scalar invariance assumptions were all verified, an LMA was carried out to check gender differences in the four latent variables (i.e., online religious involvement, spiritual support, depression, and anxiety). The female group was fixed as the reference group, and the latent mean value of the male group presented the mean differences between the male and female groups. There was a significant difference in all variables (see Table 3). While the male group had a higher latent mean value than the female group in online religious involvement (0.431) and spiritual support (0.569), the female group had higher values for depression (0.356) and anxiety (0.427). When Cohen’s d effect size was computed, the homogeneity of variance assumption was supported (∆χ² (4, N = 210) = 14.126, p = 0.000, ∆TLI = −0.001, ∆RMSEA = 0.001) according to the TLI, RMSEA, and χ2 difference tests comparing Models 3 and 4 (see Table 2). If the value of Cohen’s d effect is less than 0.2, equal to 0.5, or greater than 0.8, each value is understood as small, medium, or large, respectively, according to Cohen’s guidelines (Cohen 1988; Hong et al. 2003). Thus, the values of d were computed using the common standard deviations and ranged from 0.53 to 0.95. There were medium or greater differences between men and women in all variables.

3.5. Multigroup Structural Model Analysis

Multigroup structural model analysis was conducted to compare the differences between the groups. The results of fitness of the path model revealed that the model had a good fit with the current data (χ² (df = 383, N = 210) = 704.144, p = 0.000, TLI = 0.917 CFI = 0.924, RMSEA = 0.063). The parameter estimates for both groups are presented in Table 4. To find the significant differences between path coefficients that might exist in both groups, five models with equality constraints on the five path coefficients in the model were compared with the baseline model. The model fit remained almost unchanged (see Table 5), even if the equality constraint was applied to all path coefficients (χ² (df = 388, N = 210) = 718.534, p = 0.000, TLI = 0.915, CFI = 0.926, RMSEA = 0.064). There were no statistically significant differences in the equality constraints on each path between the two groups. Online religious involvement had a positive influence on spiritual support for both groups, and there were no significant differences in the path between the female and male groups. Spiritual support had a negative influence on depression in men. Spiritual support had no significant influence on depression or anxiety in women. Figure 1 shows the model with equality constraints on path coefficients.

4. Discussion

An increasing number of studies have reported on the relationship between religiosity and mental health outcomes (George et al. 2002; Koenig et al. 2012; Lee and Newberg 2005; Mackenzie et al. 2000; Thoresen and Harris 2004; Yoo 2017; You et al. 2019). However, no previous empirical study has investigated the effect of online religious involvement on depression and anxiety via spiritual support. The present study, therefore, aimed to understand the relationship between online religious involvement, spiritual support, depression, and anxiety using SEM on a Korean adult sample. Specifically, the theoretical model fit to two groups (females and males) was applied using LMA and multigroup structural analysis.
LMA found that the mean values of online religious involvement and spiritual support for Korean men were higher than for women, which is not consistent with previous studies (Mirola 1999; Zhang 2010), and mean values of depression and anxiety for men were lower than those for women, supporting previous studies (Andrade et al. 2003; Bahrami and Yousefi 2011; Hakamata et al. 2009; Lindemann 1996; Maier et al. 1999). In general, women reported a higher proportion of religious involvement. In the United States and other countries, more women practiced religious behaviors, such as praying daily and attending religious services and consider religion more important than men (Pew Research Center 2016a; Stark 2002). In addition, Korean research supports the notion that women have more religious affiliations than men (Oh 2015). However, the findings of the current study suggest that Korean women engaged in religious services and activities in online contexts less than Korean men.
The gender gap in religiosity has been explained by multiple factors from various domains, such as biological, psychological, sociological, and economic aspects (Oh 2015; Pew Research Center 2016b; de Vaus and McAllister 1987; Woodhead 2012). According to Trzebiatowska and Bruce (2012), workforce participation might reduce religious involvement. Women are traditionally more religious than men because of their relatively low participation rate in economic activities or less coercion due to their structural position in their society. The COVID-19 pandemic plunged most countries into recessions in 2020, and South Korea’s unemployment rate rose to its highest in January 2021 since 1999 (Nikkei Asia 2021). As Korean men did not gain security in workforce participation due to unemployment, it is possible to explain that more Korean men participated in online religious activities. In addition, men participate and engage more than women in online communities, such as the Q&A website stackoverflow.com (Vasilescu et al. 2012), whereas women had more academic success in online learning (Price 2006; Rovai and Baker 2005). Thus, a further detailed study to determine the different gender gaps in online religious involvement is needed.
A multigroup structural model analysis showed that online religious involvement had a significant indirect effect on depression through the mediation of spiritual support for the male group. There was a positive and strong influence of online religious involvement on spiritual support for both groups, but there was no gender difference in the pathway. Online religious involvement had no direct or indirect effect on anxiety via spiritual support for either group. Korean males were more involved in online religious activities than women, which negatively affected depression through spiritual support mediation. However, their online religious involvement does not directly or indirectly affect anxiety.
This result indicated that there was a negative relationship between religious involvement and depression, which is consistent with previous studies (Desrosiers and Miller 2007; Ellison and Flannelly 2009; Jansen et al. 2010; Koenig 2007; Mackenzie et al. 2000; Van Voorhees et al. 2008). This finding still revealed the importance of spiritual support through online religious involvement regarding depression among Korean men. To enhance the mental health of Korean men—specifically, to decrease depression during the pandemic—religious activities through online religious service tools are required. Therefore, Protestant Church leaders in Korea must focus on online religious involvement to promote the mental health of their male members. It is also necessary to think of evangelical classes and church programs for men online. However, future research is needed to determine why this does not apply to anxiety.
This study was meaningful because it was the first to examine the relationship between online religious involvement and mental health disorders such as depression and anxiety in Korean adults. However, this study has several limitations. First, it may be difficult to generalize the findings because the sample mostly consisted of young Korean adults. It might be interesting if further studies investigate the relationship with various age groups, especially the elderly, who are more religious. Second, the sample was predominantly Protestant Christians. This result may be difficult to apply to other religions. Future research should consider a wider range of participants’ religious orientations to increase the generalizability of the association.
The results of this study may provide implications for psychological or counseling approaches toward depression in Korean men. This study supports several previous studies related to the negative association between religious involvement and depression. These findings show that religious involvement is associated with specific mental disorders and also provide information to counselors, mental health professors, and religious leaders. In addition, spiritual support from online religious involvement is found to serve as a protective factor against depression in Korean Christian men but not against anxiety. Thus, future investigations should examine whether increasing spiritual support can be effective within psychological or counseling approaches.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the author.

Conflicts of Interest

The author declares no conflict of interest.

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Religions 13 01052 g001 550
Figure 1. Final model estimation with standardized coefficients. Note: F and M mean female and male, respectively. Significant (* p < 0.05, *** p < 0.001) path coefficients are shown with bold lines; non-significant path coefficients are shown with dotted lines.
Figure 1. Final model estimation with standardized coefficients. Note: F and M mean female and male, respectively. Significant (* p < 0.05, *** p < 0.001) path coefficients are shown with bold lines; non-significant path coefficients are shown with dotted lines.
Religions 13 01052 g001
Table
Table 1. Correlations, Mean Values, Standard Deviations, Skewness, and Kurtosis of Variables.
Table 1. Correlations, Mean Values, Standard Deviations, Skewness, and Kurtosis of Variables.
Variables1234
1. Online Religious Involvement10.708 **0.151 *0.097
2. Spiritual Support0.680 **10.0540.047
3. Depression−0.224 *−0.382 **10.763 **
4. Anxiety−0.252 *−0.360 **0.678 **1
M(SD)3.60(0.821)3.85(1.138)1.78(0.697)1.85(0.744)
Skewness−0.647−1.1150.5390.511
Kurtosis−0.6210.4900.3340.334
Note: * p < 0.05, ** p < 0.01. The top half of the table shows the correlation matrix for females, and the bottom half shows the matrix for males.
Table
Table 2. Fit indices for construct equivalence Tests.
Table 2. Fit indices for construct equivalence Tests.
Modelχ²dfpTLICFIRMSEA
Configural invariance (baseline model): Model 1679.5253660.0000.9150.9260.064
Metric invariance: Model 2704.1443830.0000.9170.9240.063
Metric & scalar invariance: Model 3749.4334040.0000.9150.9180.064
Metric, scalar, & factor variance invariance: Model 4763.5594080.0000.9140.9160.065
Table
Table 3. Results of latent mean analysis.
Table 3. Results of latent mean analysis.
Latent VariablesFemale (n = 138)Male (n = 72)Effect SizeTotal M
Latent MMLatent MM
Online Religious Involvement03.4900.431 ***3.8190.693.603
Spiritual Support03.6760.569 ***4.1910.533.852
Depression01.8220.356 ***1.7260.951.789
Anxiety01.8930.427 ***1.7670.951.850
Notes: The latent mean values for the female group were set to zero. *** p < 0.001.
Table
Table 4. Parameter estimates for female and male groups (model with equality constraint on factor loading).
Table 4. Parameter estimates for female and male groups (model with equality constraint on factor loading).
ParameterFemaleMale
Online Religious Involvement → Spiritual Support1.089 ***(0.809)0.857 ***(0.771)
Online Religious Involvement → Depression0.236(0.325)0.154(0.165)
Online Religious Involvement → Anxiety0.175(0.219)−0.014(−0.014)
Spiritual Support → Depression−0.110(−0.204)−0.435 *(−0.518)
Spiritual Support → Anxiety−0.077(−0.131)−0.336(−0.365)
Notes: Parameter estimates are unstandardized coefficients. Standardized coefficients are given in parentheses. * p < 0.05, *** p < 0.001.
Table
Table 5. Comparison of female and male group differences between the baseline model and models with equality constraints on the path coefficients.
Table 5. Comparison of female and male group differences between the baseline model and models with equality constraints on the path coefficients.
Path with Equality Constraint on Path CoefficientΔdfΔχ²ΔTLI
Online Religious Involvement → Spiritual Support11.9210.000
Online Religious Involvement → Depression10.0930.000
Online Religious Involvement → Anxiety10.4090.000
Spiritual Support → Depression12.2750.000
Spiritual Support → Anxiety11.1820.000
All constrained514.3890.001
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Yoo, J. Online Religious Involvement, Spiritual Support, Depression, and Anxiety during the COVID-19 Pandemic. Religions 2022, 13, 1052. https://doi.org/10.3390/rel13111052

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Yoo J. Online Religious Involvement, Spiritual Support, Depression, and Anxiety during the COVID-19 Pandemic. Religions. 2022; 13(11):1052. https://doi.org/10.3390/rel13111052

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Yoo, Jieun. 2022. "Online Religious Involvement, Spiritual Support, Depression, and Anxiety during the COVID-19 Pandemic" Religions 13, no. 11: 1052. https://doi.org/10.3390/rel13111052

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Yoo, J. (2022). Online Religious Involvement, Spiritual Support, Depression, and Anxiety during the COVID-19 Pandemic. Religions, 13(11), 1052. https://doi.org/10.3390/rel13111052

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