Table 6.
Mediation of the effect of internet use on NSSI through mental disorders.
| Path A | Path B | Effect | SE | t | p | Bootstrapping 95% CI | |
|---|---|---|---|---|---|---|---|
|
Mediator variable: Affective disorder
Total effect |
1.335** p<.001 | .140** p<.001 | .183 | .074 | 2.487 | .013 | |
| Direct effect | −.005 | .068 | −.067 | .947 | |||
| Partial effect of control variables | |||||||
| Gender | 1.491** | .229 | 6.499 | <.001 | |||
| Age | −.069 | .086 | −.802 | .423 | |||
| Total indirect effect | .188* | .042 | .119,.284 | ||||
| Model summary: R = .375, R2 = .140, F3, 326 = 17.759, p <.001 | |||||||
|
Mediator variable: Anxiety disorder
Total effect |
1.905** p <.001 | .064** p <.001 | .183 | .074 | 2.487 | .013 | |
| Direct effect | .061 | .068 | .889 | .374 | |||
| Partial effect of control variables | |||||||
| Gender | 1.491** | .229 | 6.499 | <.001 | |||
| Age | −.069 | .086 | −.802 | .423 | |||
| Total indirect effect | .122* | .042 | .050,.220 | ||||
| Model summary: R = .375, R2 = .140, F3, 326 = 17.759, p <.001 | |||||||
|
Mediator variable: OCD
Total effect |
.155 p = .005 | .432** p <.001 | .183 | .074 | 2.487 | .013 | |
| Direct effect | .116 | .071 | 1.643 | .101 | |||
| Partial effect of control variables | |||||||
| Gender | 1.491** | .229 | 6.499 | <.001 | |||
| Age | −.069 | .086 | −.802 | .423 | |||
| Total indirect effect | .067 | .031 | .018,.114 | ||||
| Model summary: R = .375, R2 = .140, F3, 326 = 17.759, p <.001 | |||||||
|
Mediator variable: ADHD
Total effect |
.978** p <.001 | .101** p <.001 | .191 | .074 | 2.597 | .009 | |
| Direct effect | .092 | .075 | 1.229 | .220 | |||
| Partial effect of control variables | |||||||
| Gender | 1.482** | .230 | 6.453 | <.001 | |||
| Age | −.074 | .086 | −.858 | .392 | |||
| Total indirect effect | .099* | .029 | .053,.171 | ||||
| Model summary: R = .377, R2 = .142, F3, 324 = 17.867, p <.001 | |||||||
|
Mediator variable: CD and ODD
Total effect |
.788** p <.001 | .144** p <.001 | .191 | .074 | 2.597 | .009 | |
| Direct effect | .077 | .074 | 1.048 | .295 | |||
| Partial effect of control variables | |||||||
| Gender | 1.482** | .230 | 6.453 | <.001 | |||
| Age | −.074 | .086 | −.858 | .392 | |||
| Total indirect effect | .144* | .033 | .059,.191 | ||||
| Model summary: R = .377, R2 = .142, F3, 324 = 17.867, p <.001 | |||||||
|
Mediator variable: Alcohol abuse and dependence
Total effect |
.144 p = .036 | .352** p <.001 | .206 | .078 | 2.640 | .008 | |
| Direct effect | .155 | .075 | 2.074 | .038 | |||
| Partial effect of control variables | |||||||
| Gender | 1.582** | .237 | 6.670 | <.001 | |||
| Age | −.088 | .088 | −1.00 | .318 | |||
| Total indirect effect | .051 | .030 | .007,.124 | ||||
| Model summary: R = .396, R2 = .157, F3, 306 = 18.968, p <.001 | |||||||
|
Mediator variable: Psychoactive substance abuse and dependence
Total effect |
.201** p <.001 | .405** p <.001 | .188 | .073 | 2.565 | .011 | |
| Direct effect | .107 | .071 | 1.515 | .131 | |||
| Partial effect of control variables | |||||||
| Gender | 1.467** | .230 | 6.374 | <.001 | |||
| Age | −.070 | .086 | −.816 | .415 | |||
| Total indirect effect | .081* | .033 | .029,.163 | ||||
| Model summary: R = .374, R2 = .140, F3, 321 = 17.419, p <.001 | |||||||
|
Mediator variable: Psychotic disorder
Total effect |
.325** p <.001 | .356** p <.001 | .191 | .074 | 2.597 | .009 | |
| Direct effect | .075 | .068 | 1.105 | .270 | |||
| Partial effect of control variables | |||||||
| Gender | 1.482** | .230 | 6.453 | <.001 | |||
| Age | −.074 | .086 | −.858 | .392 | |||
| Total indirect effect | .116* | .037 | .056,.204 | ||||
| Model summary: R = .377, R2 = .142, F3, 324 = 17.867, p <.001 | |||||||
|
Mediator variable
Suicidality
Total effect |
.217** p <.001 | .686** p <.001 | .183 | .074 | 2.487 | .013 | |
| Direct effect | .034 | .065 | .524 | .601 | |||
| Partial effect of control variables | |||||||
| Gender | 1.491** | .229 | 6.499 | <.001 | |||
| Age | −.069 | .086 | −.802 | .423 | |||
| Total indirect effect | .149* | .046 | .072,.255 | ||||
| Model summary: R = .375, R2 = .140, F3, 326 = 17.759, p <.001 | |||||||
|
Mediator variable
Adjustment disorder
Total effect |
.118 p = .039 | .269** p <.001 | .196 | .076 | 2.569 | .010 | |
| Direct effect | .165 | .076 | 2.179 | .030 | |||
| Partial effect of control variables | |||||||
| Gender | 1.555** | .242 | 6.436 | <.001 | |||
| Age | −.069 | .089 | −.777 | .438 | |||
| Total indirect effect | .032 | .023 | .001,.096 | ||||
| Model summary: R = .391, R2 = .153, F3, 297 = 17.877, p <.001 |
**p <. 001.
*p <. 005.
Path A: The effect of the symptoms of internet use on comorbid mental disorders. Path B: The effect of the comorbid mental disorders on prevalence of NSSI.
Effect—unstandardized regression coefficients, SE—standard error of the unstandardized regression coefficients, Bootstrapping 95% CI—95% confidence interval, Number of bootstrap resample: 5,000.
Bonferroni correction was applied to the control for multiple comparison. (p = 0.05/10 = 0.005, p = 0.01/10 = 0.001).
This table shows the detailed statistical results of the 10 mediator models; in Table 7 there is a short summary about the direct and indirect effect of each psychopathological group we examined.