The correlation between non-suicidal self-injury and mobile phone social media dependence in adolescents

doi:10.21203/rs.3.rs-4280256/v1

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The correlation between non-suicidal self-injury and mobile phone social media dependence in adolescents

https://doi.org/10.21203/rs.3.rs-4280256/v1

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Objective: To explore the correlation between non-suicidal self-injury behavior and mobile social media dependence in adolescents, and to provide reference for intervention of non-suicidal self-injury.

Methods: A total of 99 adolescents with non-suicidal self-injury behavior in our hospital from January 2022 to December 2023 were selected as the case group, and 97 healthy students were selected as the control group. Ottawa Self-injury Questionnaire, non-suicidal self-injury questionnaireand mobile phone social media dependence questionnaire were used for assessment, and Spearman correlation analysis was used to explore the correlation between the scores of Ottawa self-injury questionnaire, non-suicidal self-injury questionnaire and mobile phone social media dependence questionnaire.

Results: The total score of mobile phone social media dependence questionnaire, conflict and withdrawal scores of the study group were higher than those of the control group, the difference was statistically significant . The scores of the functional subscale of the Ottawa non-suicidal self-injury questionnaire in the case group were higher than those in the control group, and the difference was statistically significant. The scores of the five factors in the functional subscale of the Ottawa non-suicidal self-injury questionnaire , internal emotion regulation, social influence, external emotion regulation, sensation seeking and addiction characteristics, were positively correlated with the scores of the five factors in the mobile phone social media dependence questionnaire, salience, social promoting, compulsive, conflict and withdrawal (r=0.155-0.442). The scores of non-suicidal self-injury questionnaire were positively correlated with the conflict, withdrawal and total scores of the mobile phone social media dependence questionnaire (r=0.145-0.209). The factors influencing non-suicidal self-injury include education level, conflict.

Conclusion: There is a correlation between non-suicidal self-injury and mobile phone social media dependence in adolescents, which provides reference for the treatment of non-suicidal self-injury in the future.

Adolescent

Non-suicidal self-injury

mobile phone

Social media

Dependence

Non-suicidal self-injury (NSSI) refers to a series of direct, deliberate and repeated actions that do not commit suicide but do not lead to death, such as cutting, stabbing, bumping, scratching, etc.^{[1, 2]}. NSSI can run through all ages and is more common in adolescents and early young adults. Studies have shown that the lifetime prevalence of adolescents in the world is 5.5%-22.1%^[3–5]. For adolescents with mental disorders, the prevalence is even higher, with the prevalence of one-time NSSI reaching 60% and the prevalence of repeated NSSI reaching 50%^[6]. In China, studies have reported that the incidence of NSSI among middle school students is 27.4%, among which the highest incidence is 15.9% among adolescents aged 13–17^[7]. NSSI not only causes physical impairment, affects emotional functioning, interpersonal relationships and work and school performance, but also increases the risk of suicide. Suicide deaths in adolescents and early adulthood were strongly associated with NSSI experience^[8]. Adolescents with a history of NSSI are about three times more likely to commit suicide in the future than the general population ^[9]. NSSI is an important risk factor for suicide ^{[10, 11]}, the risk of suicidal behavior also increased with the increasing frequency of NSSI. Therefore, NSSI in adolescents has become a social public health problem that cannot be ignored.

With the deepening of research on NSSI, more and more evidence shows that NSSI is an addictive behavior in adolescents ^[12]. In recent years, studies on NSSI in adolescents suggest that NSSI is closely related to neural reward circuits. Compared with adolescents without NSSI, adolescents with NSSI showed increased activity in the striatal reaction-related brain areas ^[13]. The self-report of addiction experience of self-injurers showed that self-injurers knew the harm but still repeated it, had a sense of craving for self-injurious behavior, and their emotions were released after self-injurious behavior, and there was tolerance to self-injurious behavior. In addition, studies have shown that NSSI patients have changes in endogenous opioid peptides, and the levels of endorphins and dopamine in the brain increase after NSSI ^[14], while the endogenous opioid system is involved in regulating addictive behaviors, suggesting that NSSI in adolescents has certain addictive properties.

Do adolescents with NSSI have other addictive behaviors based on the addictive attributes, such as psychoactive substance addiction, Internet addiction, etc.? At present, there are more and more studies on Internet use and adolescents' NSSI ^{[15, 16]}.Previous studies have shown a certain correlation between social media addiction and adolescents' NSSI. However, most of the current researches on social media are based on computer terminals ^{[17, 18]}. With the development of mobile Internet, the popularity of smart phones and the increase of mobile phone social applications, the use of mobile phone social media is becoming more and more widespread, and people's use and dependence on mobile phone social media is constantly increasing ^[19–21]. At present, there are many studies on mobile phone dependence and computer social media dependence, while there are few studies on mobile phone social media dependence. Compared with traditional social media, mobile phone social media has stronger immediacy, portability and interactivity, which increase use frequency of mobile social media, and also indicate the correlation between mobile phone dependence or computer terminal social media dependence and NSSI cannot simply be applied to mobile phone social media dependence.

Mobile phone social media dependence ^[22] refers to the use of specific social media on mobile phones, such as Tiktok, wechat, Weibo, QQ, etc., which is addicted, over-invested and difficult to control. With the increasing abundance of smartphone applications, teenagers spend more and more time using mobile social media every day, which also makes the phenomenon of dependence on mobile social media more and more common ^[23]. Excessive addiction to mobile social media, long-term exposure to mobile social media platforms, more opportunities to contact information about NSSI, more time exposure to network environment of communication and talk about self-injury.Then whether mobile phone social media dependence will increase the occurrence of non-suicidal self-injury in adolescents? whether there are more dependence on mobile phone social media among adolescents with NSSI? Is there a correlation between mobile phone social media and NSSI? This study attempts to explore the correlation between NSSI and mobile phone social media dependence in adolescents.

Participants

A total of 100 adolescents with non-suicidal self-injury behavior in our hospital from January 2022 to December 2023 were selected as the case group. The inclusion criteria were as follows: 1) patients who met the recommended diagnostic criteria for NSSI in Part III of the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5); 2) Aged between 13 and 24; 3) Patients who have the ability to complete the questionnaire; 4) Participate voluntarily and sign informed consent. At the same time, 100 healthy students matching the study group in age, education and gender were selected as the control group. Informed consent was obtained and signed by all patients or patient supervisors, and the study was approved by ethics committee of Tongde Hospital of Zhejiang Province.

Scales

The Ottawa self-injury inventory ^[24]: This inventory consists of a series of independent subscales assessing the intention and frequency of NSSI behavior, the motivation for initial and ongoing NSSI behavior, and addiction and other NSSI behavioral characteristics. This scale has a good measurement efficiency, and the factor analysis of the Wattawa NSSI functional subscale, which assesses the motivation of NSSI, found that it has four factors: internal emotion regulation, social influence, external emotion regulation, sensation seeking and addiction factor consisting of a one item. At present, the scale has been used in Chinese research.

Non-suicidal self-injury questionnaire^[25] : The questionnaire was compiled by Zheng Ying and revised by Feng Yu, including the time of NSSI and the degree of NSSI, with a total of 19 questions. The injury degree was divided into five grades: "no" to "extremely severe", with 1, 2, 3, 4 and 5 points respectively; the time of NSSI was divided into 0 times, 1 time, 2–4 times, ≥ 5 times, with 1, 2, 3 and 4 points successively. NSSI = time of NSSI x degree of NSSI. The Cronbachα coefficient of this questionnaire was 0.91.

Mobile phone social media dependence questionnaire ^[22]:The scale compiled by Wu Zuhong, uses 23 items to measure five dimensions of mobile phone dependence, including salience, social promoting, compulsive, conflict and withdrawal. Each question was scored on a 5-level scale (1 = very inconsistent, 5 = very consistent), with a higher total score indicating a higher degree of dependence on mobile social media. The internal consistency coefficient of the questionnaire was 0.937.

Obvervational index

Mobile phone social media dependence questionnaire scores of case group and control group. The case group and the control group four factors score on the functional subscale of the Ottawa self-injury questionnaire: internal emotion regulation, social influence, external emotion regulation, sensation seeking and addiction factor score. Ottawa self-injury questionnaire functional subscale score, non-suicidal self-injury behavior questionnaire score and mobile phone social media dependence questionnaire score correlation coefficient.

Statistical analyses

SPSS17.0 statistical software was used for statistical analysis of the obtained data, and P value ≤ 0.05 was considered to be statistically significant.The gender, age, of the case group and control group were compared by t test/Chi-square test. T-test was used to compare the scores of the mobile phone social media dependence questionnaire between the case group and the control group, and T-test was used to compare the scores of the functional subscale of the Ottawa NSSI questionnaire between the case group and the control group. Spearman correlation analysis was performed on the scores of Ottawa self-injury questionnaire, non-suicidal self-injury questionnaire and mobile phone social media dependence questionnaire. Multiple linear regression analysis was conducted with the total score of non-suicidal non-suicidal self-injury questionnaire as the dependent variable, and sex, age, education level, five factors of mobile phone social media dependence questionnaire, salience, social promoting, compulsive, conflict and withdrawal as the independent variables.

Comparison of general data between the case group and the control group

A total of 200 scales were collected in this study, including 100 case group with 99 valid questionnaires, with an average age of 16.31 years old, including 4 males and 95 females, 15 undergraduate students, 34 high school students, 41 middle school students and 9 primary school students. There were 100 subjects in the control group with 97 valid questionnaires and an average age of 18.81, including 3 males, 94 females, 15 undergraduate students, 33 senior high school students, 41 junior middle school students and 8 primary school students. Comparison of general data between the two groups ( Table 1).

Table 1

Comparison of general data between the case group and the control group
		Case group (n = 99)	Control group (n = 97)	χ²/t	P
age		16.31 ± 3.374	15.62 ± 2.27	-1.69	0.093
sex	male	4(4.04%)	3(3.09%)	0.127	0.511
	female	95(95.96%)	94(96.91%)
education level	primary school students	9(9.09%)	8(8.25%)	83.99	0.000
	junior middle school students	41(41.41%)	41(42.27%)
	senior high school students	34(34.36%)	33(34.02%)
	undergraduate students	15(15.15%)	15(15.46%)
Non-suicidal self-injury questionnaire score		105.313 ± 63.245	22.567 ± 15.129	-12.538	0.000

Comparison of mobile phone social media dependence questionnaire scores between the case group and the control group

The total score of mobile social media dependence questionnaire, conflict and withdrawal scores of the research group were higher than those of the control group, and the differences were statistically significant (Table 2).

Table 2

Comparison of mobile social media dependence questionnaire scores between the study group and the control group
	Case group	Control group	t	P
alience	17.16 ± 4.61	16.24 ± 2.89	-1.679	0.095
social promoting	16.41 ± 4.40	15.49 ± 3.04	-1.698	0.091
compulsive	13.61 ± 3.78	13.02 ± 2.47	-1.281	0.202
conflict	17.28 ± 4.47^*	15.62 ± 3.14	-3.011	0.003
withdrawal	14.18 ± 3.52^**	12.91 ± 2.48	-2.925	0.004
Non-suicidal self-injury questionnaire total socre	78.65 ± 19.09^*	73.28 ± 11.45	-2.38	0.018

Comparison of scores on the Functional Subscale of the Ottawa NSSI Questionnaire between the case group and the control group

The scores of the functional subscale of the Ottawa NSSI Questionnaire in the study group were higher than those in the control group, and the four factors of internal emotion regulation, social influence, external emotion regulation, sensation seeking and addiction characteristics were all higher than those in the control group, with statistical significance (Table 3).

Table 3

Comparison of scores on the of Ottawa NSSI questionnaire between the case group and the control group
	Case group	Control group	t
internal emotion regulation	27.65 ± 7.40^**	9.04 ± 3.64	-22.249
social influence	15.64 ± 6.19^**	9.09 ± 3.88	-8.854
external emotion regulation	10.80 ± 3.69^**	3.49 ± 1.56	-17.968
sensation seeking	7.58 ± 3.62^**	3.39 ± 1.44	-10.591
addiction factor	22.56 ± 6.97^**	7.47 ± 2.42	-20.157
functional subscale total score	61.66 ± 16.18^**	25.02 ± 10.37	-18.83

Correlation analysis between functional subscale factor scores of Ottawa NSSI questionnaire and mobile phone social media dependence questionnaire factor scores

The scores of the four factors in the functional subscale of the Ottawa NSSI questionnaire: internal emotion regulation, social influence, external emotion regulation, sensation seeking and addiction characteristics, were positively correlated with the scores of the five factors in the questionnaire: alience, social promoting, compulsive, conflict and withdrawal (r = 0.155 ~ 0.442) (Table 4).

Table 4

Correlation coefficient between functional subscale factor scores of Ottawa NSSI Questionnaire and mobile phone social media dependence questionnaire factor scores (r)
	alience	social promoting	compulsive	conflict	withdrawal	mobile phone social media dependence questionnaire total scores
internal emotion regulation	0.155^*	0.215^**	0.156^*	0.268^**	0.205^**	0.226^**
social influence	0.320^**	0.322^**	0.313^**	0.385^**	0.327^**	0.376^**
external emotion regulation	0.165^*	0.247^**	0.178^*	0.264^**	0.173^*	0.234^**
sensation seeking	0.311^**	0.412^**	0.314^**	0.442^**	0.380^**	0.421^**
addiction factor	0.195^**	0.265^**	0.211^**	0.317^**	0.262^**	0.282^**
functional subscale total score	0.241^**	0.302^**	0.243^**	0.353^**	0.279^**	0.321^**

Correlation analysis between non-suicidal self-injury questionnaire scores and mobile phone social media dependence questionnaire factors scores

The scores of non-suicidal self-injury questionnaire scores were positively correlated with the conflict and withdrawal factors and total scores of the mobile phone social media dependence questionnaire (r = 0.145 ~ 0.209) (Table 5).

Table 5

Correlation coefficient between non-suicidal self-injury questionnaire scores and mobile phone social media dependence questionnaire factors (r)
	alience	social promoting	compulsive	conflict	withdrawal	mobile phone social media dependence questionnaire total scores
Non-suicidal self-injury questionnaire total socre	0.069	0.123	0.081	0.209^**	0.160^*	0.145^*

Multiple linear regression analysis of influencing factors of NSSI

Multiple linear regression analysis was conducted with the total score of the Non-suicidal self-injury questionnaire as the dependent variable, and sex, age, education level, and the significance of the five factors of the questionnaire on mobile phone social media dependence:alience, social promoting, compulsive, conflict and withdrawal as the independent variables. The results showed that the factors affecting non-suicidal NSSI included education level, conflict (Table 6).

Table 6

Multiple linear regression analysis of factors influencing NSSI
	b	SE	Beta	t	P	Adj-R²
constant	41.354	54.804		0.755	0.451	0.07
age	-17.098	25.768	-0.048	-0.664	0.508
sex	4.921	2.679	0.217	1.837	0.068
education level	-23.251	9.016	-0.302	-2.579	0.011
alience	-3.283	2.055	-0.193	-1.597	0.112
social promoting	1.261	2.214	0.073	0.569	0.570
compulsive	-4.038	3.066	-0.197	-1.317	0.189
conflict	5.784	2.386	0.348	2.424	0.016
withdrawal	2.543	2.689	0.120	0.946	0.345

53.6% of the world's population use social media and spend an average of 2 hours and 25 minutes per day on social media ^[26]. With the development of mobile Internet, the popularity of smart phones and the increase of mobile social applications, the use of mobile terminal networks is becoming more and more widespread, and people's use and dependence on mobile phone social media is constantly increasing ^[27]. Teenagers, in particular, use smartphones more often than in the past and spend most of their time on social media [28].This study found that the total score of mobile phone social media dependence questionnaire of NSSI adolescents was higher than that of healthy adolescents, suggesting that NSSI adolescents have more dependence on mobile phone social media. Studies have reported that adolescents with self-harm use the Internet more frequently and are more active on social networks than those without self-harm ^[29]. High levels of Internet use, Internet addiction, and exposure to websites with self-harm or suicide content are particularly associated with suicidal behavior ^[30]. Online social networks have led to more and more people being exposed to and participating in NSSI. Teenagers are more likely to have NSSI when they receive negative information about NSSI on the Internet and acquire NSSI methods from videos shared on websites ^{[31, 32]}. Excessive addiction to mobile phone social media platforms, there are more opportunities to contact information about NSSI, more time exposed to communication and talk about NSSI environment. Studies have shown that positive emotions of NSSI adolescents are significantly reduced, negative emotions are significantly increased when exposed to relevant NSSI cues, and the desire for NSSI is also significantly increased ^[33].

The results of this study showed that the scores of NSSI adolescents on the functional subscale of the Ottawa NSSI Questionnaire were higher than those of the control group, and the scores of the four factors of internal emotion regulation, social influence, external emotion regulation and regulation seeking were also higher than those of the control group, suggesting that NSSI adolescents often try to get others attention and release unbearable pressure through NSSI behaviors. To feel real through NSSI, individuals commit NSSI in order to relieve or solve interpersonal difficulties from negative sensory or cognitive states or to induce positive sensory states ^[34]. Over time, the frequency and severity of NSSI will increase in order to achieve the same effect ^[35]. NSSI is maintained through positive and negative experiences and social reinforcement processes that perpetuate NSSI and create a certain dependency^[36]. In recent years, studies suggest that NSSI has certain addictive properties ^[37], while studies on the mechanism of addictive attributes are mainly related to the reward circuit and endogenous opioid system. Neuroimaging studies have found that NSSI is closely related to reward circuits ^[38]. Compared with healthy adolescents, adolescents with NSSI present structural and functional abnormalities in brain regions related to reward circuits ^[39]. In addition, studies have found that the level of endogenous opioids in the cerebrospinal fluid of NSSI patients is abnormal, and after the implementation of NSSI, the negative emotions of patients are rapidly alleviated, while feelings of euphoria and satisfaction^[40]. And the opioid system plays a key role in addictive behavior. The above results suggest that NSSI among adolescents has certain addictive attributes from biological perspective, NSSI adolescents are more likely to have dependent behaviors such as mobile phone social media.

Regression analysis shows that in addition to the conflict factors of on mobile phones social media dependence questionnaire, education level also plays a certain role in influencing NSSI. The higher the education level, the lower the risk of NSSI, which is consistent with previous research results ^[41]. Low education level increases the risk of self-harm, possibly because the higher the education level, the better the mental health knowledge and the ability to cope with external stress^[42].

In summary, there is a correlation between adolescents NSSI and mobile phone social media dependence. However, this study is a cross-sectional study with a small sample size, and the results of this study need to be further verified in a large sample cohort study in the future, which can provide certain reference for the intervention of adolescents NSSI in the future.

Ethical Approval

The study was approved by ethics committee of Tongde Hospital of Zhejiang Province(ZTDLS2022YD020-JY).Informed consent was obtained and signed by all participants or participants supervisors. All participants statements on consent to participate and consent to publish are also required.

Funding

The research was funded by Zhejiang Provincial Health Commission without conflict of interest.

Author Contribution

Honghui Wei:Conceptualization, Design, Supervision, Funding, Investigation, Data collection, Writing-Original Draft, Critical reviewYing Zhang:Conceptualization, Design, Supervision, Investigation, Data collection, Writing-Original Draft, Critical reviewNingning Sun:Conceptualization, Design, Supervision, Investigation, Data collection, Writing-Original Draft, Critical reviewYue Wang:Conceptualization, Design, Supervision, Investigation, Data collection, Writing-Original Draft, Critical reviewYang Li:Conceptualization, Design, Supervision, Investigation, Data collection, Writing-Original Draft, Critical review

Brown RC, Plener PL. Non-suicidal Self-Injury in Adolescence. Curr Psychiatry Rep. 2017;19(3):20. 10.1007/s11920-017-0767-9. PMID: 28315191; PMCID: PMC5357256.
Gao Y, Wang Y, Wang Z, Ma M, Li H, Wang J, Liu J, Qian H, Zhu P, Xu X. Family intimacy and adaptability and non-suicidal self-injury: a mediation analysis. BMC Psychiatry. 2024;24(1):210. 10.1186/s12888-024-05642-1. PMID: 38500067; PMCID: PMC10946147.
Swannell SV, Martin GE, Page A, Hasking P, St John NJ. Prevalence of nonsuicidal self-injury in nonclinical samples: systematic review, meta-analysis and meta-regression. Suicide Life Threat Behav. 2014;44(3):273–303. 10.1111/sltb.12070. Epub 2014 Jan 15. PMID: 24422986.
Lim KS, Wong CH, McIntyre RS, Wang J, Zhang Z, Tran BX, Tan W, Ho CS, Ho RC. Global Lifetime and 12-Month Prevalence of Suicidal Behavior, Deliberate Self-Harm and Non-Suicidal Self-Injury in Children and Adolescents between 1989 and 2018: A Meta-Analysis. Int J Environ Res Public Health. 2019;16(22):4581. 10.3390/ijerph16224581. PMID: 31752375; PMCID: PMC6888476.
Liu RT, Scopelliti KM, Pittman SK, Zamora AS. Childhood maltreatment and non-suicidal self-injury: a systematic review and meta-analysis. Lancet Psychiatry. 2018;5(1):51–64. doi: 10.1016/S2215-0366(17)30469-8. Epub 2017 Nov 28. PMID: 29196062; PMCID: PMC5743605.
Kaess M, Parzer P, Mattern M, Plener PL, Bifulco A, Resch F, Brunner R. Adverse childhood experiences and their impact on frequency, severity, and the individual function of nonsuicidal self-injury in youth. Psychiatry Res. 2013;206(2–3):265–72. 10.1016/j.psychres.2012.10.012. Epub 2012 Nov 16. PMID: 23159195.
Wang C, Zhang P, Zhang N. Adolescent mental health in China requires more attention. Lancet Public Health. 2020;5(12):e637. 10.1016/S2468-2667(20)30094-3. PMID: 33271076.
Castellví P, Lucas-Romero E, Miranda-Mendizábal A, Parés-Badell O, Almenara J, Alonso I, Blasco MJ, Cebrià A, Gabilondo A, Gili M, Lagares C, Piqueras JA, Roca M, Rodríguez-Marín J, Rodríguez-Jimenez T, Soto-Sanz V, Alonso J. Longitudinal association between self-injurious thoughts and behaviors and suicidal behavior in adolescents and young adults: A systematic review with meta-analysis. J Affect Disord. 2017;215:37–48. Epub 2017 Mar 12. PMID: 28315579.
Vega D, Sintes A, Fernández M, Puntí J, Soler J, Santamarina P, Soto À, Lara A, Méndez I, Martínez-Giménez R, Romero S, Pascual JC. Review and update on non-suicidal self-injury: who, how and why? Actas Esp Psiquiatr. 2018;46(4):146–55. Epub 2018 Jul 1. PMID: 30079928.
Ribeiro JD, Franklin JC, Fox KR, Bentley KH, Kleiman EM, Chang BP, Nock MK. Self-injurious thoughts and behaviors as risk factors for future suicide ideation, attempts, and death: a meta-analysis of longitudinal studies. Psychol Med. 2016;46(2):225–36. Epub 2015 Sep 15. PMID: 26370729; PMCID: PMC4774896.
Kiekens G, Hasking P, Boyes M, Claes L, Mortier P, Auerbach RP, Cuijpers P, Demyttenaere K, Green JG, Kessler RC, Myin-Germeys I, Nock MK, Bruffaerts R. The associations between non-suicidal self-injury and first onset suicidal thoughts and behaviors. J Affect Disord. 2018;239:171–9. Epub 2018 Jun 30. PMID: 30014957.
Guo Z, Liu Y, Wang C, Li S, Yu L, Wu W, You X, Zhang Y, Teng Z, Zeng Y. Exploring the association of addiction-related genetic factors with non-suicidal self-injury in adolescents. Front Psychiatry. 2023;14:1126615. 10.3389/fpsyt.2023.1126615. PMID: 37065902; PMCID: PMC10102595.
Poon JA, Thompson JC, Forbes EE, Chaplin TM. Adolescents' Reward-related Neural Activation: Links to Thoughts of Nonsuicidal Self-Injury. Suicide Life Threat Behav. 2019;49(1):76–89. 10.1111/sltb.12418. Epub 2018 Jan 19. PMID: 29349794; PMCID: PMC7184534.
Bresin K, Gordon KH. Endogenous opioids and nonsuicidal self-injury: a mechanism of affect regulation. Neurosci Biobehav Rev. 2013;37(3):374–83. 10.1016/j.neubiorev.2013.01.020. Epub 2013 Jan 20. PMID: 23339875.
Sedgwick R, Epstein S, Dutta R, Ougrin D. Social media, internet use and suicide attempts in adolescents. Curr Opin Psychiatry. 2019;32(6):534–41. 10.1097/YCO.0000000000000547. PMID: 31306245; PMCID: PMC6791504.
John A, Glendenning AC, Marchant A, Montgomery P, Stewart A, Wood S, Lloyd K, Hawton K. Self-Harm, Suicidal Behaviours, and Cyberbullying in Children and Young People: Systematic Review. J Med Internet Res. 2018;20(4):e129. 10.2196/jmir.9044. PMID: 29674305; PMCID: PMC5934539.
O'Reilly M, Dogra N, Whiteman N, Hughes J, Eruyar S, Reilly P. Is social media bad for mental health and wellbeing? Exploring the perspectives of adolescents. Clin Child Psychol Psychiatry. 2018;23(4):601–13. Epub 2018 May 20. PMID: 29781314.
Berryman C, Ferguson CJ, Negy C. Social Media Use and Mental Health among Young Adults. Psychiatr Q. 2018;89(2):307–314. 10.1007/s11126-017-9535-6. PMID: 29090428.
Matar Boumosleh J, Jaalouk D. Depression, anxiety, and smartphone addiction in university students- A cross sectional study. PLoS ONE. 2017;12(8):e0182239. 10.1371/journal.pone.0182239. PMID: 28777828; PMCID: PMC5544206.
Cha SS, Seo BK. Smartphone use and smartphone addiction in middle school students in Korea: Prevalence, social networking service, and game use. Health Psychol Open. 2018;5(1):2055102918755046. 10.1177/2055102918755046. PMID: 29435355; PMCID: PMC5802650.
Abi-Jaoude E, Naylor KT, Pignatiello A. Smartphones, social media use and youth mental health. CMAJ. 2020;192(6):E136–41. 10.1503/cmaj.190434. PMID: 32041697; PMCID: PMC7012622.
Wu ZH. A study on questionnaire design and characteristics of College students' mobile phone social media dependence [D]. Chongqing: Southwest University; 2014.
Zhang YL, Li S, Yu GL. The relationship between error anxiety and cognitive failure in college students: the mediating role of mobile social media dependence. Chin J Clin Psychol. 2019;28(1):67–81.
Zhang F, Cloutier PF, Yang H, Liu W, Cheng W, Xiao Z. Non-suicidal self-injury in Shanghai inner bound middle school students. Gen Psychiatr. 2019;32(4):e100083. 10.1136/gpsych-2019-100083. PMID: 31552387; PMCID: PMC6738666.
Feng Y. The relationship between adolescents' self-injurious behaviors and individual emotional factors and family environment factors. Central China Normal University; 2008.
Doan LP, Le LK, Nguyen TT, Nguyen TTP, Le MNV, Vu GT, Latkin CA, Ho CSH, Ho RCM, Zhang MWB. Social Media Addiction among Vietnam Youths: Patterns and Correlated Factors. Int J Environ Res Public Health. 2022;19(21):14416. 10.3390/ijerph192114416. PMID: 36361288; PMCID: PMC9656938.
Spina G, Bozzola E, Ferrara P, Zamperini N, Marino F, Caruso C, Antilici L, Villani A. Children and Adolescent's Perception of Media Device Use Consequences. Int J Environ Res Public Health. 2021;18(6):3048. 10.3390/ijerph18063048. PMID: 33809591; PMCID: PMC8002029.
Bozzola E, Spina G, Agostiniani R, Barni S, Russo R, Scarpato E, Di Mauro A, Di Stefano AV, Caruso C, Corsello G, Staiano A. The Use of Social Media in Children and Adolescents: Scoping Review on the Potential Risks. Int J Environ Res Public Health. 2022;19(16):9960. 10.3390/ijerph19169960. PMID: 36011593; PMCID: PMC9407706.
Memon AM, Sharma SG, Mohite SS, et al. The role of online social networking on deliberate self-harm and suicidality in adolescents: A systematized review of literature. Indian J Psychiatry. 2018;60(4):384–92. 10.4103/psychiatry.IndianJPsychiatry_414_17.
Marchant A, Hawton K, Stewart A, et al. A systematic review of the relationship between internet use, self-harm and suicidal behaviour in young people: The good, the bad and the unknown. PLoS ONE. 2017;12(8):e0181722. 10.1371/journal.pone.0181722.
Biernesser C, Sewall CJR, Brent D, et al. Social Media Use and Deliberate Self-Harm Among Youth: A Systematized Narrative Review. Child Youth Serv Rev. 2020;116:105054. 10.1016/j.childyouth.2020.105054. Epub 2020 May 29.
Nesi J, Burke TA, Lawrence HR, et al. Online Self-Injury Activities among Psychiatrically Hospitalized Adolescents: Prevalence, Functions, and Perceived Consequences. Res Child Adolesc Psychopathol. 2021;49(4):519–31. 10.1007/s10802-020-00734-4.
Riquino MR, Reese SE, Garland EL. Assessing Attentional Bias Toward Nonsuicidal Self-Injury Cues in Young Adults with Histories of Engaging in Self-Harm. Child Adolesc Soc Work J. 2021;38:641–50. https://doi.org/10.1007/s10560-020-00692-2.
Zetterqvist M. The DSM-5 diagnosis of nonsuicidal self-injury disorder: a review of the empirical literature. Child Adolesc Psychiatry Ment Health. 2015;9:31. 10.1186/s13034-015-0062-7. PMID: 26417387; PMCID: PMC4584484.
Liu RT. Characterizing the course of non-suicidal self-injury: A cognitive neuroscience perspective. Neurosci Biobehav Rev. 2017;80:159–65. 10.1016/j.neubiorev.2017.05.026. Epub 2017 Jun 1. PMID: 28579492; PMCID: PMC5705419.
Worley J. Self-Injury as an Addictive Disorder. J Psychosoc Nurs Ment Health Serv. 2020;58(6):13–6. 10.3928/02793695-20200513-03.
Hui C, Jiansong Z. Research progress on addiction characteristics of non-suicidal self-injury behaviors. Chin J Psych. 2022;55:5. 10.3760/cma.j.cn113661-20210921-00130.
Chen X, Chen H, Liu J, Tang H, Zhou J, Liu P, Tian Y, Wang X, Lu F, Zhou J. Functional connectivity alterations in reward-related circuits associated with non-suicidal self-injury behaviors in drug-naïve adolescents with depression. J Psychiatr Res. 2023;163:270–7. Epub 2023 May 21. PMID: 37244065.
Ando A, Reichl C, Scheu F, Bykova A, Parzer P, Resch F, Brunner R, Kaess M. Regional grey matter volume reduction in adolescents engaging in non-suicidal self-injury. Psychiatry Res Neuroimaging. 2018;280:48–55. Epub 2018 Aug 10. PMID: 30149362.
]Stanley B, Sher L, Wilson S, Ekman R, Huang YY, Mann JJ. Non-suicidal self-injurious behavior, endogenous opioids and monoamine neurotransmitters. J Affect Disord. 2010;124(1–2):134–40. 10.1016/j.jad.2009.10.028. Epub 2009 Nov 25. PMID: 19942295; PMCID: PMC2875354.
Li B, Allebeck P, Burstöm B, Danielsson AK, Degenhardt L, Eikemo TA, Ferrari A, Knudsen AK, Lundin A, Manhica H, Newton J, Whiteford H, Flodin P, Sjöqvist H, Agardh EE. Educational level and the risk of mental disorders, substance use disorders and self-harm in different age-groups: A cohort study covering 1,6 million subjects in the Stockholm region. Int J Methods Psychiatr Res. 2023;32(4):e1964. Epub 2023 Feb 17. PMID: 36802082; PMCID: PMC10698815.
Polimanti R, Ratanatharathorn A, Maihofer AX, Choi KW, Stein MB, Morey RA, Logue MW, Nievergelt CM, Stein DJ, Koenen KC, Gelernter J, Psychiatric Genomics Consortium Posttraumatic Stress Disorder Working Group. Association of Economic Status and Educational Attainment With Posttraumatic Stress Disorder: A Mendelian Randomization Study. JAMA Netw Open. 2019;2(5):e193447. 10.1001/jamanetworkopen.2019.3447. PMID: 31050786; PMCID: PMC6503495.

No competing interests reported.

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The correlation between non-suicidal self-injury and mobile phone social media dependence in adolescents

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Abstract

Introduction

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Participants

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Obvervational index

Statistical analyses

Results

Comparison of general data between the case group and the control group

Multiple linear regression analysis of influencing factors of NSSI

Discussion

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References

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