Отношения в семье, буллинг и потребление алкоголя подростками

Кроме того, в ходе исследования было выявлено, что вовлеченность в буллинг в качестве жертвы положительно и сильно связана с вовлечением в буллинг в качестве запугивающего. Этот факт дает повод задуматься над тем, чтобы в будущем включить в анализ опыт вовлеченность в буллинг как в качестве жертвы, так и в качестве запугивающего одновременно (bully-victim), потому что, видимо, один вид вовлеченности может провоцировать другой вид. Также интересно, что распространенность опыта запугивания выше, чем опыта жертвы для мальчиков и девочек. От 17% до 32% совершали различные виды запугиваний и агрессии как минимум 1-2 раза в месяц, в то время как от 11% до 25% подростков соглашались с фактами опыта жертвы , происходившими с ними как минимум 1-2 раза в месяц. Возможно, это связано с ограничением данного исследования - использовались только самоотчетные данные, которые, как и любые другие подобные данные, оставляют вероятность, что респонденты могли утаивать, отвечать так, как по их мнению от них ожидали, стесняться зафиксировать свой опыт.

В процессе исследования выяснилось: чем выше уровень привязанности в семье, тем реже подростки употребляют алкоголь. Вовлеченность в буллинг в качестве запугивающего опосредует связь между уровнем привязанности в семье и потреблением алкоголя подростками для мальчиков и для девочек, а вовлеченность в качестве жертвы - нет.



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Приложение 1

Часть вывода по модели CFA, используемая для анализа

model <- '

Family =~ v4 + v5 + v6 + v7

Victimization =~ v14_1 + v14_2 + v14_3 + v14_4

Perpetration =~ v13_1 + v13_2 + v13_3 + v13_4'

fit <- cfa(model, data)

summary(fit, fit.measures = TRUE)

lavaan 0.6-5 ended normally after 28 iterations

Estimator DWLS

Optimization method NLMINB

Number of free parameters 63

Number of observations 1821

Model Test User Model:

Standard Robust

Test Statistic 218.148 294.665

Degrees of freedom 51 51

P-value (Chi-square) 0.000 0.000

Scaling correction factor 0.789

Shift parameter 18.213

for the simple second-order correction

Model Test Baseline Model:

Test statistic 49313.564 20345.806

Degrees of freedom 66 66

P-value 0.000 0.000

Scaling correction factor 2.428

User Model versus Baseline Model:

Comparative Fit Index (CFI) 0.997 0.988

Tucker-Lewis Index (TLI) 0.996 0.984

Robust Comparative Fit Index (CFI) NA

Robust Tucker-Lewis Index (TLI) NA

Root Mean Square Error of Approximation:

RMSEA 0.042 0.051

90 Percent confidence interval - lower 0.037 0.046

90 Percent confidence interval - upper 0.048 0.057

P-value RMSEA <= 0.05 0.983 0.349

Robust RMSEA NA

90 Percent confidence interval - lower NA

90 Percent confidence interval - upper NA

Standardized Root Mean Square Residual:

SRMR 0.037 0.037

Parameter Estimates:

Information Expected

Information saturated (h1) model Unstructured

Standard errors Robust.sem

Latent Variables:

Estimate Std.Err z-value P(>|z|)

Family =~

v4 1.000

v5 1.049 0.030 35.248 0.000

v6 1.109 0.029 38.408 0.000

v7 0.934 0.026 36.521 0.000

Victimization =~

v14_1 1.000

v14_2 0.994 0.017 58.442 0.000

v14_3 0.942 0.017 54.908 0.000

v14_4 0.941 0.015 61.005 0.000

Perpetration =~

v13_1 1.000

v13_2 1.159 0.021 54.386 0.000

v13_3 1.073 0.017 64.689 0.000

v13_4 1.007 0.018 55.187 0.000

Covariances:

Estimate Std.Err z-value P(>|z|)

Family ~~

Victimization -0.168 0.021 -8.154 0.000

Perpetration -0.129 0.020 -6.340 0.000

Victimization ~~

Perpetration 0.682 0.020 34.374 0.000



Приложение 2

Часть вывода по моделям SEM, используемая для анализа

model3 <-'

VictimizationNEW ~ b1 * FamilyNEW

AlcoholNEW ~ b2 * VictimizationNEW + b3 * FamilyNEW

direct := b3

indirect := b1*b2

total := b3 + (b1*b2)'

fit3 <-lavaan::sem(model3, data= data, group = "gender", se = "bootstrap")

summary(fit3, standardized = T, fit.measures = T)

lavaan 0.6-5 ended normally after 53 iterations

Estimator ML

Optimization method NLMINB

Number of free parameters 14

Number of observations per group:

0 700

1 1121

Model Test User Model:

Test statistic 0.000

Degrees of freedom 0

Test statistic for each group:

0 0.000

1 0.000

Model Test Baseline Model:

Test statistic 76.363

Degrees of freedom 6

P-value 0.000

User Model versus Baseline Model:

Comparative Fit Index (CFI) 1.000

Tucker-Lewis Index (TLI) 1.000

Loglikelihood and Information Criteria:

Loglikelihood user model (H0) -4098.847

Loglikelihood unrestricted model (H1) -4098.847

Akaike (AIC) 8225.694

Bayesian (BIC) 8302.794

Sample-size adjusted Bayesian (BIC) 8258.317

Root Mean Square Error of Approximation:

RMSEA 0.000

90 Percent confidence interval - lower 0.000

90 Percent confidence interval - upper 0.000

P-value RMSEA <= 0.05 NA

Standardized Root Mean Square Residual:

SRMR 0.000

Parameter Estimates:

Standard errors Bootstrap

Number of requested bootstrap draws 1000

Number of successful bootstrap draws 1000

Group 1 [0]:

Regressions:

Estimate Std.Err z-value

VictimizationNEW ~

FamilyNEW (b1) -0.038 0.018 -2.165

AlcoholNEW ~

VctmztNEW (b2) 0.340 0.105 3.245

FamilyNEW (b3) -0.292 0.064 -4.530

P(>|z|) Std.lv Std.all

0.030 -0.038 -0.072

0.001 0.340 0.117

0.000 -0.292 -0.187

Intercepts:

Estimate Std.Err z-value

.VictimizatnNEW 1.377 0.071 19.314

.AlcoholNEW 3.123 0.304 10.272

P(>|z|) Std.lv Std.all

0.000 1.377 3.301

0.000 3.123 2.566

Variances:

Estimate Std.Err z-value

.VictimizatnNEW 0.173 0.023 7.540

.AlcoholNEW 1.405 0.086 16.295

P(>|z|) Std.lv Std.all

0.000 0.173 0.995

0.000 1.405 0.948

Group 2 [1]:

Regressions:

Estimate Std.Err z-value

VictimizationNEW ~

FamilyNEW -0.058 0.019 -3.037

AlcoholNEW ~

VictimizatnNEW 0.066 0.077 0.858

FamilyNEW -0.282 0.060 -4.723

P(>|z|) Std.lv Std.all

0.002 -0.058 -0.078

0.391 0.066 0.027

0.000 -0.282 -0.155

Intercepts:

Estimate Std.Err z-value

.VictimizatnNEW 1.459 0.081 18.003

.AlcoholNEW 3.404 0.283 12.040

P(>|z|) Std.lv Std.all

0.000 1.459 2.939

0.000 3.404 2.776

Variances:

Estimate Std.Err z-value

.VictimizatnNEW 0.245 0.034 7.258

.AlcoholNEW 1.466 0.086 16.980

P(>|z|) Std.lv Std.all

0.000 0.245 0.994

0.000 1.466 0.975

Defined Parameters:

Estimate Std.Err z-value

direct -0.292 0.064 -4.528

indirect -0.013 0.008 -1.621

total -0.305 0.065 -4.705

P(>|z|) Std.lv Std.all

0.000 -0.292 -0.187

0.105 -0.013 -0.008

0.000 -0.305 -0.195

model4 <-'

PerpetrationNEW ~ b1 * FamilyNEW

AlcoholNEW ~ b2 * PerpetrationNEW + b3 * FamilyNEW

direct := b3

indirect := b1*b2

total := b3 + (b1*b2)'

fit4 <-lavaan::sem(model4, data= data, group = "gender", se = "bootstrap")

summary(fit4, standardized = T, fit.measures = T)

lavaan 0.6-5 ended normally after 50 iterations

Estimator ML

Optimization method NLMINB

Number of free parameters 14

Number of observations per group:

0 700

1 1121

Model Test User Model:

Test statistic 0.000

Degrees of freedom 0

Test statistic for each group:

0 0.000

1 0.000

Model Test Baseline Model:

Test statistic 121.143

Degrees of freedom 6

P-value 0.000

User Model versus Baseline Model:

Comparative Fit Index (CFI) 1.000

Tucker-Lewis Index (TLI) 1.000

Loglikelihood and Information Criteria:

Loglikelihood user model (H0) -4487.128

Loglikelihood unrestricted model (H1) -4487.128

Akaike (AIC) 9002.255

Bayesian (BIC) 9079.355

Sample-size adjusted Bayesian (BIC) 9034.878

Root Mean Square Error of Approximation:

RMSEA 0.000

90 Percent confidence interval - lower 0.000

90 Percent confidence interval - upper 0.000

P-value RMSEA <= 0.05 NA

Standardized Root Mean Square Residual:

SRMR 0.000

Parameter Estimates:

Standard errors Bootstrap

Number of requested bootstrap draws 1000

Number of successful bootstrap draws 1000

Group 1 [0]:

Regressions:

Estimate Std.Err z-value

PerpetrationNEW ~

FamilyNEW (b1) -0.135 0.030 -4.567

AlcoholNEW ~

PrptrtNEW (b2) 0.358 0.090 4.000

FamilyNEW (b3) -0.256 0.065 -3.953

P(>|z|) Std.lv Std.all

0.000 -0.135 -0.193

0.000 0.358 0.160

0.00 -0.256 -0.164

Intercepts:

Estimate Std.Err z-value

.PerpetratinNEW 1.916 0.127 15.142

.AlcoholNEW 2.906 0.319 9.108

P(>|z|) Std.lv Std.all

0.000 1.916 3.518

0.000 2.906 2.387

Variances:

Estimate Std.Err z-value

.PerpetratinNEW 0.286 0.024 12.003

.AlcoholNEW 1.389 0.084 16.504

P(>|z|) Std.lv Std.all

0.000 0.286 0.963

0.000 1.389 0.937

Group 2 [1]:

Regressions:

Estimate Std.Err z-value

PerpetrationNEW ~

FamilyNEW -0.089 0.027 -3.266

AlcoholNEW ~

PerpetratinNEW 0.191 0.068 2.783

FamilyNEW -0.269 0.060 -4.520

P(>|z|) Std.lv Std.all

0.001 -0.089 -0.099

0.005 0.191 0.094

0.000 -0.269 -0.148

Intercepts:

Estimate Std.Err z-value

.PerpetratinNEW 1.729 0.113 15.246

.AlcoholNEW 3.171 0.284 11.157

P(>|z|) Std.lv Std.all

0.000 1.729 2.852

0.000 3.171 2.586

Variances:

Estimate Std.Err z-value

.PerpetratinNEW 0.364 0.036 10.093

.AlcoholNEW 1.454 0.084 17.219

P(>|z|) Std.lv Std.all

0.000 0.364 0.990

0.000 1.454 0.967

Defined Parameters:

Estimate Std.Err z-value

direct -0.256 0.065 -3.951

indirect -0.049 0.017 -2.812

total -0.305 0.063 -4.823

P(>|z|) Std.lv Std.all

0.000 -0.256 -0.164

0.005 -0.049 -0.031

0.000 -0.305 -0.195

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