## [1] 5025
## [1] 41.42826
## [1] 14.22494
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 3 x 3
## `factor(ageCat)` n percent
## <fct> <int> <dbl>
## 1 18 - 35 years 2098 41.8
## 2 36 - 50 years 1550 30.8
## 3 >51 years 1377 27.4
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 2 x 3
## `factor(gender)` n percent
## <fct> <int> <dbl>
## 1 female 3059 60.9
## 2 male 1966 39.1
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 6 x 3
## `factor(education)` n percent
## <fct> <int> <dbl>
## 1 bachelor 352 7
## 2 doctoral 97 1.93
## 3 high school 2834 56.4
## 4 master or eqvivalent 1602 31.9
## 5 no formal education 6 0.12
## 6 primary school 134 2.67
## `summarise()` ungrouping output (override with `.groups` argument)
## # A tibble: 3 x 3
## `factor(educationCat)` n percent
## <fct> <int> <dbl>
## 1 primary school 140 2.79
## 2 secondary school 2834 56.4
## 3 university 2051 40.8
## [1] 63
## `summarise()` regrouping output by 'Education' (override with `.groups` argument)
item = worst_trauma + gender perspective
## $`Overall prevalence`
## x n proportion lower upper conf.level
## 2 3448 4961 0.695 0.682 0.708 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 1604 2362 0.679 0.66 0.698 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 1571 2207 0.712 0.692 0.731 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.000000 NA NA
## male 1.048405 1.008824 1.089356
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 0.01588339 0.01594399 0.01732955
##
##
## $`Bayes factor`
## [1] "BF10 = 1.25"
Prevalence of certain type of trauma - frequency based on item worst_trauma / + comparison from the gender perspective
## $Overall
## Without trauma exposure
## 30.14
## Family member/very close friend died
## 15.02
## Life-threatening accident
## 10.19
## Life-threatening illness
## 9.64
## Partner/date, etc. physically harmed you
## 7.67
## Parent/caregiver physically harmed you
## 6.05
## Fire or explosion
## 3.77
## Natural disaster
## 3.55
## Childhood: touched your private body parts
## 2.24
## Present when someone was killed, injured, assaulted
## 2.16
## Threatened with a weapon
## 2.10
## Exposure to toxic substance
## 1.70
## Physical force/weapon used in robbery or mugging
## 1.54
## Physical force used to have sex
## 1.40
## Physical force/threat to try to have sex
## 1.25
## Other situation: seriously injured / life in danger
## 0.63
## You caused injury, harm, death
## 0.60
## Repeated exposure to vivid trauma details
## 0.33
## Death, injury, fight (as a part of job)
## 0.03
##
## $Female
## Without trauma exposure
## 31.69
## Family member/very close friend died
## 16.08
## Partner/date, etc. physically harmed you
## 10.94
## Life-threatening illness
## 8.45
## Parent/caregiver physically harmed you
## 6.70
## Life-threatening accident
## 6.64
## Childhood: touched your private body parts
## 3.70
## Natural disaster
## 3.49
## Fire or explosion
## 2.91
## Physical force used to have sex
## 2.29
## Physical force/threat to try to have sex
## 2.17
## Threatened with a weapon
## 1.65
## Present when someone was killed, injured, assaulted
## 1.16
## Exposure to toxic substance
## 0.90
## Physical force/weapon used in robbery or mugging
## 0.80
## You caused injury, harm, death
## 0.18
## Other situation: seriously injured / life in danger
## 0.11
## Repeated exposure to vivid trauma details
## 0.11
## Death, injury, fight (as a part of job)
## 0.02
##
## $Male
## Without trauma exposure
## 28.49
## Life-threatening accident
## 13.98
## Family member/very close friend died
## 13.88
## Life-threatening illness
## 10.92
## Parent/caregiver physically harmed you
## 5.35
## Fire or explosion
## 4.68
## Partner/date, etc. physically harmed you
## 4.17
## Natural disaster
## 3.61
## Present when someone was killed, injured, assaulted
## 3.23
## Threatened with a weapon
## 2.58
## Exposure to toxic substance
## 2.56
## Physical force/weapon used in robbery or mugging
## 2.32
## Other situation: seriously injured / life in danger
## 1.17
## You caused injury, harm, death
## 1.06
## Childhood: touched your private body parts
## 0.68
## Repeated exposure to vivid trauma details
## 0.57
## Physical force used to have sex
## 0.45
## Physical force/threat to try to have sex
## 0.26
## Death, injury, fight (as a part of job)
## 0.05
## $`Overall prevalence`
## x n proportion lower upper conf.level
## 2 1416 3438 0.412 0.395 0.429 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 721 1614 0.447 0.422 0.471 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 593 1577 0.376 0.352 0.4 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.000000 NA NA
## male 0.841993 0.773715 0.9153869
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 5.054621e-05 5.629414e-05 5.881079e-05
##
##
## $`Bayes factor`
## [1] "BF10 = 323.57"
item based on sum of “trauma_disease”, “trauma_disaster”, “trauma_accident”, “trauma_explosion”, “trauma_toxic”, “trauma_robbery”, “trauma_death”,“trauma_sexual1”, “trauma_sexual2”,“trauma_abuse”,“trauma_child”,“trauma_physical”, “trauma_gun”,“trauma_death2”, “trauma_other” = answer is scored as 1 -> and 2 or more = multiple trauma
## `summarise()` ungrouping output (override with `.groups` argument)
## $Table
##
## 0 1 2 3 4 5 6 7 8 9 10 11 12 14 15
## 1492 1181 838 535 292 182 112 64 30 18 15 6 2 1 3
##
## $`Descriptives overall`
## # A tibble: 1 x 2
## `Mean of traumas survived` `SD of traumas survived`
## <dbl> <dbl>
## 1 1.83 1.99
##
## $`Descriptives by gender`
## # A tibble: 2 x 3
## gender `Mean of traumas survived` `SD of traumas survived`
## <fct> <dbl> <dbl>
## 1 female 1.73 1.92
## 2 male 1.93 2.05
## # A tibble: 1 x 4
## ch_malt1_perc ch_malt2_perc ch_malt3_perc ch_malt4_perc
## <svystat> <svystat> <svystat> <svystat>
## 1 3.283751 17.43964 8.987381 3.179921
relationship between child maltreatment and incidence of certain trauma - “trauma_sexual1”, “trauma_sexual2”, “trauma_physical”, “trauma_gun”. Pozriet specificky na vztah trauma 4 s “trauma_sexual1”, “trauma_sexual2”.
## Ignored 15 rows containing missing observations.
## $cor
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: 0.242 [0.222 0.262]
## p-value: 0.000
##
##
## $bf
## [1] "BF10 = 3.33e+65"
## Ignored 19 rows containing missing observations.
## $cor
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: 0.206 [0.186 0.226]
## p-value: 0.000
##
##
## $bf
## [1] "BF10 = 6.6e+46"
## Ignored 16 rows containing missing observations.
## $cor
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: 0.305 [0.286 0.324]
## p-value: 0.000
##
##
## $bf
## [1] "BF10 = 9.86e+102"
## Ignored 21 rows containing missing observations.
## $cor
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: 0.176 [0.156 0.196]
## p-value: 0.000
##
##
## $bf
## [1] "BF10 = 7.39e+31"
analysis based only on trauma-exposed sample
Total sample and by gender
## $`Overall PTSD prevalence`
## x n proportion lower upper conf.level
## 2 789 4961 0.159 0.149 0.17 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 427 2362 0.181 0.165 0.197 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 299 2207 0.135 0.121 0.15 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.7501397 0.6537416 0.8577728
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 2.841215e-05 3.043286e-05 3.503629e-05
##
##
## $`Bayes factor`
## [1] "BF10 = 346.58"
Prevelance of certain symptoms domain - DSM-5 algorithm (criterium B - re-experiencing = one symptoms scored 2 or higher from items PCL1-PCL5 is necessary; criterium C - avoidance = one symptoms 2 or higher from PCL6 and PCL7 is necessary; criterium D - NACM = 2 symptoms scored 2 or higher from PCL8-PCL14; criterium E - AAR = 2 symptoms scored 2 or higher from PCL15-PCL20)
## $`Overall Reexperiencing prevalence`
## x n proportion lower upper conf.level
## 2 1529 4961 0.308 0.295 0.321 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 827 2362 0.35 0.331 0.37 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 582 2207 0.264 0.245 0.283 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.7531511 0.6878982 0.8228097
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 2.440368e-10 2.613765e-10 3.199868e-10
##
##
## $`Bayes factor`
## [1] "BF10 = 34777549.06"
## $`Overall Avoidance prevalence`
## x n proportion lower upper conf.level
## 2 1394 4961 0.281 0.269 0.294 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 746 2362 0.316 0.297 0.335 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 537 2207 0.243 0.226 0.262 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.7714793 0.7009618 0.8477517
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 5.578511e-08 6.449156e-08 6.981516e-08
##
##
## $`Bayes factor`
## [1] "BF10 = 170839.42"
## $`Overall NACM prevalence`
## x n proportion lower upper conf.level
## 2 1313 4961 0.265 0.252 0.277 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 677 2362 0.287 0.268 0.305 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 532 2207 0.241 0.223 0.259 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.8413218 0.7626529 0.9267365
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 0.0004881805 0.0005488564 0.0005563021
##
##
## $`Bayes factor`
## [1] "BF10 = 28.62"
## $`Overall AAR prevalence`
## x n proportion lower upper conf.level
## 2 1226 4961 0.247 0.235 0.259 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 653 2362 0.276 0.258 0.295 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 476 2207 0.216 0.199 0.233 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.7801146 0.7027917 0.8636102
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 1.876977e-06 2.136909e-06 2.290528e-06
##
##
## $`Bayes factor`
## [1] "BF10 = 5495.09"
## Overall Female Male
## PCL1 0.270 0.279 0.249
## PCL2 0.178 0.195 0.150
## PCL3 0.181 0.189 0.162
## PCL4 0.318 0.313 0.310
## PCL5 0.240 0.251 0.217
## PCL6 0.245 0.255 0.222
## PCL7 0.200 0.198 0.191
## PCL8 0.198 0.192 0.193
## PCL9 0.211 0.215 0.195
## PCL10 0.193 0.195 0.179
## PCL11 0.231 0.247 0.202
## PCL12 0.213 0.231 0.183
## PCL13 0.210 0.216 0.191
## PCL14 0.184 0.191 0.166
## PCL15 0.228 0.233 0.209
## PCL16 0.170 0.144 0.185
## PCL17 0.260 0.264 0.244
## PCL18 0.246 0.256 0.223
## PCL19 0.255 0.268 0.229
## PCL20 0.234 0.234 0.221
## t is large; approximation invoked.
## $`t-test`
##
## Design-based t-test
##
## data: ptsd ~ traumaAndMaltreated
## t = 21.004, df = 4960, p-value < 2.2e-16
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 13.69161 16.50975
## sample estimates:
## difference in mean
## 15.10068
##
##
## $BF
## [1] "BF10 = 7.72e+157"
comparison of trauma vs non-trauma group based on item worst_trauma in depression, anxiety, dissociation, alcohol use, insomnia
## $`t-test`
##
## Design-based t-test
##
## data: depression ~ traumaBinary
## t = 13.074, df = 4882, p-value < 2.2e-16
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 1.844614 2.495212
## sample estimates:
## difference in mean
## 2.169913
##
##
## $BF
## [1] "BF10 = 1.26e+45"
## $`t-test`
##
## Design-based t-test
##
## data: anxiety ~ traumaBinary
## t = 7.9783, df = 4960, p-value = 1.828e-15
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 0.6857626 1.1324222
## sample estimates:
## difference in mean
## 0.9090924
##
##
## $BF
## [1] "BF10 = 6.72e+12"
## $`t-test`
##
## Design-based t-test
##
## data: dissociation ~ traumaBinary
## t = 4.8768, df = 4960, p-value = 1.112e-06
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 0.7779971 1.8235362
## sample estimates:
## difference in mean
## 1.300767
##
##
## $BF
## [1] "BF10 = 7532.98"
## $`t-test`
##
## Design-based t-test
##
## data: alcohol ~ traumaBinary
## t = 4.5097, df = 4960, p-value = 6.642e-06
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 0.3764503 0.9551985
## sample estimates:
## difference in mean
## 0.6658244
##
##
## $BF
## [1] "BF10 = 10729.15"
## $`t-test`
##
## Design-based t-test
##
## data: insomnia ~ traumaBinary
## t = 9.2474, df = 4960, p-value < 2.2e-16
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## 1.066698 1.640477
## sample estimates:
## difference in mean
## 1.353587
##
##
## $BF
## [1] "BF10 = 3.11e+19"
Prevalence risky behavior started or become worse after trauma - frequency of item risky_after_trauma
## $`Overall prevalence of risky behavior after trauma`
## x n proportion lower upper conf.level
## 2 1158 2144 0.54 0.519 0.561 0.95
##
## $Female
## x n proportion lower upper conf.level
## 2 564 1000 0.564 0.533 0.595 0.95
##
## $Male
## x n proportion lower upper conf.level
## 2 545 1053 0.518 0.487 0.548 0.95
##
## $`Odds ratio`
## $`Odds ratio`$measure
## NA
## risk ratio with 95% C.I. estimate lower upper
## female 1.0000000 NA NA
## male 0.9185338 0.847738 0.9939109
##
## $`Odds ratio`$p.value
## NA
## two-sided midp.exact fisher.exact chi.square
## female NA NA NA
## male 0.03701654 0.03759361 0.04105595
##
##
## $`Bayes factor`
## [1] "BF01 = 1.03"
Latent correlations
## PTSD =~ PCL1 + PCL2 + PCL3 + PCL4 + PCL5 + PCL6 + PCL7 + PCL8 + PCL9 + PCL10 + PCL11 + PCL12 + PCL13 + PCL14 + PCL15 + PCL16 + PCL17 + PCL18 + PCL19 + PCL20
## Depression =~ QIDS1 + QIDS2 + QIDS3 + QIDS4 + QIDS5 + QIDS6 + QIDS7 + QIDS8 + QIDS9 + QIDS10 + QIDS11 + QIDS12 + QIDS13 + QIDS14 + QIDS15 + QIDS16
## $`Model fit`
## chisq.scaled pvalue.scaled cfi.scaled tli.scaled rmsea.scaled
## 1263.090 0.000 0.900 0.896 0.036
## srmr bic
## 0.042 283716.468
##
## $`Latent correlation`
## [1] 0.65
##
## $BF_10
## [1] Inf
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 354.714 122.000 0.000 0.943 0.941
## rmsea.scaled srmr bic
## 0.024 0.036 204216.878
##
## $`Latent correlation`
## [1] 0.639
##
## $BF_10
## [1] Inf
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 213.767 92.000 0.000 0.914 0.922
## rmsea.scaled srmr bic
## 0.020 0.041 251559.237
##
## $`Latent correlation`
## [1] 0.502
##
## $BF_10
## [1] 1.107596e+194
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 218.592 83.000 0.000 0.905 0.905
## rmsea.scaled srmr bic
## 0.022 0.055 235734.279
##
## $`Latent correlation`
## [1] 0.517
##
## $BF_10
## [1] 4.285428e+191
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 277.191 113.000 0.000 0.933 0.932
## rmsea.scaled srmr bic
## 0.021 0.044 234666.136
##
## $`Latent correlation`
## [1] 0.217
##
## $BF_10
## [1] 2.317654e+28
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 528.735 124.000 0.000 0.901 0.897
## rmsea.scaled srmr bic
## 0.031 0.047 220364.122
##
## $`Latent correlation`
## [1] 0.56
##
## $BF_10
## [1] 2.507844e+234
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 682.401 117.000 0.000 0.943 0.938
## rmsea.scaled srmr bic
## 0.038 0.032 177592.470
##
## $`Latent correlation`
## [1] 0.41
##
## $BF_10
## [1] 2.434339e+128
## $`Model fit`
## chisq.scaled df.scaled pvalue.scaled cfi.scaled tli.scaled
## 551.826 113.000 0.000 0.942 0.938
## rmsea.scaled srmr bic
## 0.034 0.032 180351.497
##
## $`Latent correlation`
## [1] -0.043
##
## $BF_10
## [1] 0.3591995
## $`t-test`
##
## Design-based t-test
##
## data: resilience ~ traumaBinary
## t = 0.51537, df = 1952, p-value = 0.6064
## alternative hypothesis: true difference in mean is not equal to 0
## 95 percent confidence interval:
## -0.3691221 0.6324966
## sample estimates:
## difference in mean
## 0.1316873
##
##
## $BF
## [1] "BF01 = 14.25"
Multiple trauma - item based on the sum of “trauma_disease”, “trauma_disaster”, “trauma_accident”, “trauma_explosion”, “trauma_toxic”, “trauma_robbery”, “trauma_death”,“trauma_sexual1”, “trauma_sexual2”,“trauma_abuse”,“trauma_child”,“trauma_physical”, “trauma_gun”,“trauma_death2”, “trauma_other” = answer is scored as 1 -> and 2 or more = multiple trauma)
## Ignored 2121 rows containing missing observations.
## $Correlation
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: -0.074 [-0.114 -0.034]
## p-value: 0.008
##
##
## $BF
## [1] "BF01 = 4.1"
Correlation between multiple trauma and distress_trauma
## Ignored 116 rows containing missing observations.
## $Correlation
##
## Weighted Pearson's Correlation Coefficient
##
## estimate [95% CI]: 0.139 [0.114 0.164]
## p-value: 0.000
##
##
## $BF
## [1] "BF10 = 1.22e+14"