Social Science Research/Statistics on Religion

Social Science Research Statistics on Religion International Migration Trends Human Activities as a Cause of Climate Change The study https://pmc.ncbi.nlm.nih.gov/articles/PMC7211021, titled "Traumatic Life Experiences and Religiosity in Eight Countries - PMC," examines the relationship between traumatic life experiences and religiosity in eight countries: the United States, Brazil, China, India, Indonesia, Russia, Thailand, and Turkey. The dataset with the corresponding R code can be downloaded from OSF Registries here: https://osf.io/3d58w/files/osfstorage . Jong J, Baimel A, Ross R, McKay R, Bluemke M, Halberstadt J. Traumatic life experiences and religiosity in eight countries. Sci Data. 2020 May 8;7(1):140. doi: 10.1038/s41597-020-0482-y. PMID: 32385303; PMCID: PMC7211021. Regarding religiosity, the study selected these countries to maximize religious diversity. The main religious affiliations, according to the data collected in the study, include: Brazil: predominantly Christian (69.3%) China: predominantly non-religious/atheist/agnostic (71.3%) India: predominantly Hindu (72.7%) Indonesia: predominantly Muslim (68.3%) Russia: predominantly Christian (69.8%) Thailand: predominantly Buddhist (86.8%) Turkey: predominantly Muslim (80.5%) United States: Non-religious (48.8%) and Christian (39.8%) as the main groups Measures of Religiosity The study used several measures of religiosity, including self-description as religious and spiritual, specific religious affiliation, and the Supernatural Belief Scale (SBS), a measure of religious behavior developed by Jong and Halberstad and consisting of 6 items: There is an omnipotent spiritual being and omniscient, whom we might call God. There are spiritual beings, who can be good or evil, like angels or demons. Every human being has a spirit or soul separate from the physical body. There is a sort of afterlife. Beyond the physical, there is a spiritual realm. Supernatural events that have no scientific explanation (e.g., miracles) can occur, and the following ratings can be given: −4 = Strongly Disagree, 0 = Neither Agree nor Disagree, 4 = Strongly Agree The average SBS by religious affiliation is as follows for a sample of 908 respondents who passed all attention checks: #Loading data and libraries into R library(dplyr) df <- read.csv("NegativeLifeExp_Data.csv") df <- df %>% filter(CHECK==0) df %>% group_by(AFFILIATION) %>% summarise(mean_SBS=mean(SBS)) %>% arrange(desc(mean_SBS)) AFFILIATION mean_SBS 1 Sikh 3.33 2 Muslim 3.30 3 Christian 2.70 4 Other/Syncretic 2.21 5 Hindu 2.06 6 Jain 2 7 Jewish 1.87 8 Buddhist 1.56 9 Agnostic -0.371 10 None -0.442 11 Taoist/Confucian -1.78 12 Atheist -2.57 Religiosity and Death Anxiety The article mentions that two measures of death anxiety were included in the study: the Death Anxiety Questionnaire (DAQ) developed by Conte, Weiner, and Plutchik and the Existential Death Anxiety Scale (EDAS) developed by Jong and Halberstadt. Some questions in the DAQ are: "Does death worry you? Does the idea of ​​dying before you've done everything you wanted to do bother you? Does it worry you that you might be very ill before you die?", and in the EDAS are: "The thought of my own death scares me. I'm disturbed by the fact that one day I won't be alive anymore. The finality of death scares me. My own mortality disturbs me. The thought of being dead fills me with terror, etc." Calculating the Pearson correlation index between the SBS and the DAQ or EDAS, we note that there is no correlation, so it is not true that increasing death anxiety increases religiosity: cor.test (df$SBS, df$EDAS, use = "complete.obs") Pearson's product-moment correlation data: df$SBS and df$EDAS t = -0.9459, df = 906, p-value = 0.3445 alternative hypothesis: true correlation is not equal to 0 95 percent confidence interval: -0.09627248 0.03371845 sample estimates: cor -0.03140983 Since the p-value is >0.05, the null hypothesis holds and there is no correlation between SBS and EDAS at 95%. For DAQ and SBS, the correlation is very weak: cor (df$SBS, df$DAQ, use = "complete.obs") 0.08894459 The highest death anxiety scores are in agnostics, Christians, Muslims, and Buddhists: df %>% group_by(AFFILIATION) %>% summarise(mean_EDAS=mean(EDAS)) %>% arrange(desc(mean_EDAS)) AFFILIATION mean_EDAS 1 Agnostic -0.404 2 Christian -0.524 3 Buddhist -0.564 4 None -0.772 5 Muslim -0.808 6 Atheist -0.868 7 Other/Syncretic -1.13 8 Jewish -1.14 9 Hindu -1.18 10 Jain -1.62 11 Taoist/Confucian -2.94 12 Sikh -3.33 AFFILIATION mean_DAQ 1 Muslim 3.80 2 Christian 3.78 3 Buddhist 3.74 4 Taoist/Confucian 3.7 5 Agnostic 3.57 6 Other/Syncretic 3.54 7 Jewish 3.32 8 Hindu 3.29 9 Atheist 3.22 10 Sikh 2.87 11 Jain 2.8 Religiosity and Traumatic Life Experiences The article mentions a "Traumatic Life Experiences Inventory" as a 29-item measure of experiences. Traumatic life experiences. Survey participants indicated whether each of the 29 events in the inventory had ever happened to them. Some examples are: "Have you ever been unemployed for a long time when you wanted to work? Have your parents ever divorced or separated? Has your home ever been destroyed or severely damaged by arson, an accident, or a natural disaster? Have you ever had a serious life-threatening event, been seriously injured, or been disabled by an accident or natural disaster? etc." Calculating the correlation between SBS and the aforementioned 29 items, a medium-low correlation ranging from 10% to 27% is noted, therefore there is a certain correlation between religiosity and traumatic life experiences: cor(df$SBS, df[,15:43], use = "complete.obs") LE1 LE2 LE3 LE4 LE5 LE6 LE7 [1,] 0.1096997 0.2401077 0.2655676 0.2596936 0.1581559 0.2510264 0.1918595 LE8 LE9 LE10 LE11 LE12 LE13 LE14 [1,] 0.2723351 0.2250479 0.2387649 0.2509116 0.2275492 0.2142313 0.2416819 LE15 LE16 LE17 LE18 L19 LE20 LE21 [1,] 0.1971282 0.2110591 0.2221137 0.2603752 0.2764116 0.2136593 0.2646487 LE22 LE23 LE24 LE25 LE26 LE27 LE28 [1,] 0.1960728 0.2649845 0.2231542 0.1795036 0.2580262 0.2302522 0.2680907 LE29 [1,] 0.1418037 Religiosity and volunteering in religious institutions Calculating the correlation between SBS and the variable RELBEH4 corresponding to "Volunteering at religious institutions" shows a 39.74% correlation, with greater interest from Sikhs, Jains, Hindus, etc.: cor(df$SBS, df$RELBEH4, use = "complete.obs") df %>% group_by(AFFILIATION) %>% summarise(mean_Volunteering=mean(RELBEH4)) %>% arrange(desc(mean_Volunteering)) 0.3974833 AFFILIATION media_Volunteering 1 Sikh 8 2 Jain 5.5 3 Hindu 3.46 4 Jewish 3.11 5 Buddhist 2.84 6 Muslim 2.74 7 Christian 2.17 8 Taoist/Confucian 2 9 Other/Syncretic 1.59 10 Agnostic 0.289 11 None 0.253 12 Atheist 0.114