| Literature DB >> 35222116 |
Cui Huang1,2,3, Qiuyu Yuan1,2,3, Menglin Ge1,2,3, Xuanlian Sheng1,2,3, Meng Yang1,2,3, Shengya Shi1,2,3, Panpan Cao1,2,3, Mengting Ye1,2,3, Ran Peng1,2,3, Ruochen Zhou1,2,3, Kai Zhang1,2,3, Xiaoqin Zhou1,2,3.
Abstract
The factors associated with non-suicidal self-injury (NSSI) of adolescents have been widely researched. However, the underlying mechanism of the relationship between childhood trauma and NSSI is limited. This study aimed to explore the risk factors for NSSI among Chinese adolescents. Our hypothesis was that psychological sub-health (PSH) played a mediating role between childhood trauma and NSSI. The Childhood Trauma Questionnaire, the Multidimensional Sub-health Questionnaire of Adolescent, and the self-report NSSI were used to measure childhood trauma, PSH, and NSSI. Structural equation model (SEM) was performed to verify our hypothesis. The results showed that 33.9% of the participants in our survey had engaged in NSSI in the past year. Adolescents who were left-behind children or in primary schools were more likely to engage in NSSI. Additionally, 56.2% of the participants had moderate to severe childhood trauma, and 26.1% of the participants had PSH. Furthermore, childhood trauma and PSH would increase the risk of NSSI by 2 times (B = 0.79, p < 0.01) and 5 times (B = 1.64, p < 0.01), respectively. SEM was established (p = 0.512) and the goodness-of-fit indices were examined (CMIN/DF = 0.892; GFI = 0.997; AGFI = 0.992; NFI = 0.991; RFI = 0.980; IFI = 1.00; TLI = 1.00; CFI = 1.00; RMSEA < 0.001). The SEM indicated that childhood trauma positively predicted NSSI both directly and indirectly through PSH. PSH has been confirmed to have partial mediating effects between childhood trauma and NSSI. The assessment of PSH may be an operable and effective method to screen and predict NSSI. Meanwhile, the intervention of childhood trauma and PSH may effectively prevent and reduce the occurrence of NSSI among adolescents.Entities:
Keywords: adolescent; childhood trauma; left-behind children; non-suicidal self-injury; psychological sub-health
Year: 2022 PMID: 35222116 PMCID: PMC8866574 DOI: 10.3389/fpsyt.2022.798369
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 4.157
Social demographic characteristics of adolescents.
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| Age | 12.68 (1.34) | 12.53 (1.35) | 12.75 (1.32) | −2.54 | 0.01 |
| Gender | 2.15 | 0.14 | |||
| Male | 391 (50.3%) | 123 (46.6%) | 268 (52.1%) | ||
| Female | 387 (49.7) | 141 (53.4%) | 246 (47.9%) | ||
| Grade | 6.34 | 0.01 | |||
| primary school | 352 (45.2%) | 136 (51.5%) | 216 (42.0%) | ||
| middle school | 426 (54.8%) | 128 (48.5%) | 298 (58.0%) | ||
| Accommodation type | 3.65 | 0.06 | |||
| Boarding student | 107 (13.8%) | 45 (17.0%) | 62 (12.1%) | ||
| Commuting student | 671 (86.2%) | 219 (83.0%) | 452 (87.9%) | ||
| Father's educational level | 0.83 | 0.36 | |||
| <9 years | 463 (59.5%) | 163 (61.7%) | 300 (58.4%) | ||
| ≥9 years | 315 (40.5%) | 101 (38.3%) | 214 (41.6%) | ||
| Mother's educational level | 0.38 | 0.54 | |||
| <9 years | 486 (62.5%) | 161 (61.0%) | 325 (63.2%) | ||
| ≥9 years | 292 (37.5%) | 103 (39.0%) | 189 (36.8%) | ||
| Left behind status | 5.75 | 0.02 | |||
| Yes | 366 (47.0%) | 140 (53.0%) | 226 (44.0%) | ||
| No | 412 (53.0%) | 124 (47.0%) | 288 (56.0%) | ||
| Siblings | 0.37 | 0.55 | |||
| Yes | 324 (41.6%) | 106 (40.2%) | 218 (42.4%) | ||
| No | 454 (58.4%) | 158 (59.8%) | 296 (57.6%) | ||
| Parents' marital status | 1.86 | 0.40 | |||
| Married | 644 (82.8%) | 212 (80.3%) | 432 (84.0%) | ||
| Parental divorce | 122 (15.7%) | 48 (18.2%) | 74 (14.4%) | ||
| Death of a parent | 12 (1.5%) | 4 (1.5%) | 8 (1.6%) | ||
| NSSI frequency | |||||
| <5 times a year | N/A | 73 (27.7%) | N/A | N/A | N/A |
| ≥5 times a year | N/A | 191(72.3%) | N/A | ||
Values are presented as number (%) or mean (standard deviation).
The prevalence and intergroup comparison of childhood trauma and psychological sub-health state.
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| Childhood trauma | 41.07 (11.98) | 45.94 (12.81) | 38.57 (10.71) | −8.59 | <0.001 |
| Yes | 437 (56.2%) | 191 (72.3%) | 246 (47.9%) | ||
| No | 341 (43.8%) | 73 (27.7%) | 268 (52.1%) | ||
| Emotional abuse | 7.66 (3.49) | 9.09 (4.00) | 6.92 (2.94) | −9.18 | <0.001 |
| Physical abuse | 6.40 (2.89) | 7.13 (3.44) | 6.03 (2.49) | −6.44 | <0.001 |
| Sexual abuse | 5.80 (2.49) | 6.24 (3.03) | 5.58 (2.13) | −4.46 | <0.001 |
| Emotional neglect | 11.72 (4.75) | 13.07 (5.12) | 11.03 (4.35) | −5.15 | <0.001 |
| Physical neglect | 9.49 (3.25) | 10.42 (3.40) | 9.01 (3.06) | −5.47 | <0.001 |
| PSH state | 107.44 | <0.001 | |||
| Yes | 203 (26.1%) | 129 (48.9%) | 74 (14.4%) | ||
| No | 575 (73.9%) | 135 (51.1%) | 440 (85.6%) | ||
| Emotional symptoms | 33.01 (17.20) | 43.87 (19.79) | 27.43 (12.46) | −12.64 | <0.001 |
| Behavioral symptoms | 17.81 (10.23) | 23.88 (11.78) | 12.7 (7.66) | −12.08 | <0.001 |
| Social adaptation problems | 25.08 (12.36) | 31.51 (14.07) | 21.77 (9.88) | −10.56 | <0.001 |
Values are presented as number (%) or mean (standard deviation).
Associations between childhood trauma and psychological sub-health state (n = 778).
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| Childhood trauma | 1.00 | ||||||||
| Emotional abuse | 0.68 | 1.00 | |||||||
| Physical abuse | 0.56 | 0.48 | 1.00 | ||||||
| Sexual abuse | 0.42 | 0.31 | 0.40 | 1.00 | |||||
| Emotional neglect | 0.81 | 0.41 | 0.31 | 0.19 | 1.00 | ||||
| Physical neglect | 0.73 | 0.32 | 0.23 | 0.23 | 0.47 | 1.00 | |||
| PSH state | |||||||||
| Emotional symptoms | 0.42 | 0.48 | 0.25 | 0.17 | 0.26 | 0.30 | 1.00 | ||
| Behavioral symptoms | 0.42 | 0.49 | 0.26 | 0.20 | 0.24 | 0.31 | 0.82 | 1.00 | |
| Social adaptation problems | 0.41 | 0.44 | 0.27 | 0.20 | 0.25 | 0.31 | 0.80 | 0.77 | 1.00 |
Spearman correlation was used for statistical analysis;
p < 0.01.
Risk factors for NSSI (n = 778).
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| Left behind | 0.19 | 0.18 | 1.18 | 0.28 | 1.21 | 0.86 | 1.71 |
| Grade | 0.64 | 0.18 | 13.43 | <0.01 | 1.90 | 1.35 | 2.68 |
| PSH state | 1.64 | 0.19 | 78.00 | <0.01 | 5.15 | 3.58 | 7.40 |
| Childhood trauma | 0.79 | 0.18 | 20.11 | <0.01 | 2.20 | 1.56 | 3.10 |
| Constant | −2.02 | 0.20 | 103.80 | <0.01 | 0.13 | ||
The statistical analysis used binary logistic regression with the “Enter” method; CI, confidence interval; OR, odds ratio; SE, standard error; R.
Figure 1Structural equation model for all the participants. The numbers beside the arrows indicate standardized path coefficients. R2 represents squared multiple correlations. Probability level = 0.512; goodness-of-fit indices: CMIN/DF = 0.892; GFI = 0.997; AGFI = 0.992; NFI = 0.991; RFI = 0.980; IFI = 1.00; TLI = 1.00; CFI = 1.00; RMSEA < 0.001.
Direct, indirect, and total effects of the final structural model.
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| PSH state | Childhood trauma | 0.44 | 0.44 | 0.19 | |
| NSSI | Childhood trauma | 0.11 | 0.20 | 0.32 | 0.28 |
| PSH state | 0.47 | 0.47 |
Standardized coefficient estimates are presented; SMC, Squared multiple correlations;
p < 0.001.