Resilience of Chinese International Students in the UK during COVID-19: A Survey Dataset

Description

This dataset comprises anonymous survey responses from Chinese international students in the UK (n = 146), capturing their resilience, socio-demographic profiles, and social support networks. The data was collected across distinct temporal phases of the COVID-19 pandemic, specifically focusing on the intra-pandemic and post-pandemic periods to facilitate temporal analysis.

Steps to reproduce

mydata_1_new = read.csv("Rui Sun_dataset.csv") mydata_4 <- mydata_1_new mydata_logic_cols <- colnames(mydata_1_new) %>% str_replace("_\\d+$", "") colnames(mydata_4) <- mydata_logic_cols mydata_4 <- mydata_4 %>% pivot_longer( cols = matches("_(pre|after|dur|during|druing)_", ignore.case = FALSE), names_to = "indicator", values_to = "value" ) %>% mutate( time = tolower(stringr::str_match(indicator, "_(pre|after|dur|during|druing)_")[,2]), indicator = stringr::str_replace(indicator, "_(pre|after|dur|during|druing)_", "_") ) %>% mutate( time = ifelse(time == "during" | time == "druing", "dur", time) ) %>% pivot_wider(id_cols = c(ID:UKtime_length_month, time, Family_number, affected_times,City_size, Parent_edu,Hometown, Major), names_from = indicator, values_from = value) mydata_4$sum_resilience = rowSums(mydata_4[, c(27:43)], na.rm = TRUE) mydata_4_pre <- mydata_4 %>% filter(time == "pre") %>% arrange(ID) mydata_4_dur <- mydata_4 %>% filter(time == "dur") %>% arrange(ID) mydata_4_after <- mydata_4 %>% filter(time == "after") %>% arrange(ID) EF_1<- effectsize::hedges_g(mydata_4_dur$sum_resilience,mydata_4_pre$sum_resilience, adjust = T) EF_2<- effectsize::hedges_g(mydata_4_after$sum_resilience,mydata_4_dur$sum_resilience,adjust = T) mydata_4$Gender[which(mydata_4$Gender == 2)] <- 0 mydata_4$UKtime = gsub("\\D", "", mydata_4$UKtime_length_month) mydata_4$UKtime = as.numeric(mydata_4$UKtime) mydata_4$City_size = factor(mydata_4$City_size) mydata_4$City_size = relevel(mydata_4$City_size, ref = "London") mydata_4$Major = factor(mydata_4$Major) mydata_4$Major = relevel(mydata_4$Major, ref = "HSS") mydata_4$Hometown = factor(mydata_4$Hometown) mydata_4$Hometown = relevel(mydata_4$Hometown, ref = "1") mydata_4$Degree = factor(mydata_4$degree) mydata_4$Degree = relevel(mydata_4$degree, ref = "BA") model = lmer (sum_resilience ~ time_period + Major + Degree + City_size + Age + Gender + UKtime + returns + affects, data=mydata_4) EF_3 = pairs(emmeans(model, ~ time_period), effectsize="d")

Institutions

• University of Bristol

  England, Bristol

Categories

Licence