Sex and school type modified effects of depressive symptoms and screen use on substance use among adolescent in Taiwan: findings from a nation wide cross-sectional survey

doi:10.21203/rs.3.rs-1600016/v1

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Sex and school type modified effects of depressive symptoms and screen use on substance use among adolescent in Taiwan: findings from a nation wide cross-sectional survey

https://doi.org/10.21203/rs.3.rs-1600016/v1

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Background

Among Taiwanese adolescent, how depressive symptoms, screen use affect on substance use remains unclear. This study aimed to examine (1) the cross-sectional association between depressive symptoms, screen use and substance use ; and (2) the modified effects of sex and school type on those mentioned associations.

Methods

We analyzed 18,509 participants from the baseline survey of the Taiwan Adolescent to Adult Longitudinal Survey in 2015. The outcome was substance use including binge drinking, smoking, cigarette smoking and betel chewing. The main predictors were self-reported depressive symptoms and screen use. Multiple logistic regression was employed to estimate predictors, and a subgroup analysis was performed to assess effect modifications.

Results

Among 18509 participants, 6.4% reported binge drinking, 5.6% reported smoking, 4.4 % reported e-cigarette smoking, 5.0% reported betel chewing. After adjustments for covariates including sex, school type, BMI, skipping breakfast and social determinants, the associations of depressive symptoms, screen use on substance use were significant. Stratified results indicated that depressive symptoms and screen use employed diverse effects on substance use across subgroups based on sex and school types.

Conclusions

Depressive symptoms and screen use were notable factors positively associated with substance use among Taiwanese adolescents. The findings highlight the importance of strengthening public health interventions to monitor substance use, decrease depression, and screen use among adolescents.

Adolescents

binge drinking

smoking

e-cigarette

betel chewing

depressive symptoms

screen use.

According to the World Health Organization (WHO), the term adolescent was employed to mention a person aged from 10 to 19 years old. Adolescence basically includes two periods (i.e., young adolescent (10–14 year olds) and older adolescent (15–19 year olds) [1]. Adolescence is regarded as the life period between childhood and adulthood, which is an important stage of human development, including fast physical growth, sexual maturation, emotional, social, and cognitive development. It is an essential period to ensure good health establishment [2]. Mental health and substance use are the key components in the WHO guidelines for the health services elements and interventions for adolescents[3].

Nearly half mental health problems start by age 14, however, a majority of the disorders are neglected and untreated, which can lead to serious consequences in later years[3].Sadness and hopelessness are the most significant indicators to look for depression. While every adolescent is unhappy at some times, no one should be sad all of the time. Another key indicator of depression is low self-esteem. This is the attitude of the adolescent toward himself or herself, and he or she may feel foolish, unattractive, or worthless[4]. Previous studies reveal the association between depressive symptoms and increasing substance use among adolescents[5]. Meanwhile, association between screen use and substance use was less well understood[6], although research characterized that screen use significantly associated with depression[7, 8], and increased risk of overweight/obesity among adolescent[9].

In Taiwan, a recent Taiwan’s National Epidemiological Study of Child Mental Disorders screened that the weighted lifetime prevalence rates of overall mental disorders were 31.6% among children and young adolescents[10]. Recent study demonstrated that the proportion of screen time sedentary behavior was predominant and it related to increased frequency of unhealthy food consumption among adolescents[11]. Recent studies on the association of depressive symptoms, screen use, and substance use were rare, particularly on novel behavior such as e-cigarette smoking.

In this study, we hypothesized that depressive symptoms and screen use would positively associated binge drinking, smoking, e-cigarette smoking and betel chewing. After adjusting for other factors such as social determinants and stratified by sex and school type, we investigated the different effects among specify subgroups to indicate the priority sub population for future intervention suggestions.

The reporting of this study follows the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines [12] (Additional file 1)

Sample And Study Design

The study was a cross-sectional secondary analysis of data from the baseline survey in 2015 of Taiwan Adolescent to Adult Longitudinal Study (TAALS). The longitudinal nation-wide study employed a multistage, stratified area, probability sampling design to recruit participants from high schools. The methodology of the study has been described in detail elsewhere [13]. First-year students in junior high schools, senior high schools, vocational high schools were eligible for inclusion in the survey. Students who could not provide the informed consent form with their parents’ autographs were excluded from the survey. The TAALS final sample included 173 schools, 1473 class from which 6903 seventh graded students aged 13 years in junior high schools and 11742 tenth grade students aged 16 years in senior high schools and vocational high schools were selected. For this study, data on 18509 participants who fully responded to depressive symptoms questions was used to analyze. Chi-square tests for sample proportions were performed to confirm the representativeness and the similarity between respondents and non-respondents[13]. During an interview, information was collected on sociodemographic, lifestyle and physical activity, substance use, dietary behaviors, mental health, violence-related behaviors and experiences, sexual behaviors and attitudes, and social support. Ethics approval was approved by the Joint Institutional Review Board of Taipei Medical University, Taiwan (TMU-JIRB-201410043) [13].

Measures

Substance use

This study investigated adolescents’ binge drinking, cigarette smoking, e-cigarette smoking and betel chewing. We utilized the criterion of 5 drinks on one occasion for at least one day within the last 30 days to define binge drinking behavior in adolescents[14]. Cigarette and e-cigarette smoking was determined (yes/no) based on self-reported frequency of smoking during the last month[15]. Betel chewing behavior was dichotomously coded as betel chewers or never chewers based on the response “never chew betel nut ever”[16].

Depressive symptoms

Information on adolescent depressive sumptoms was collected during an on-site self-administered survey assisted with a class-based interview system. We analyzed responses to five questions from the Chinese version of the Center for Epidemiological Studies Short Depression Scale (CES-D) [13, 17], namely: How often have you felt this way during the past week (1) - I did not feel like eating; my appetite was poor; (2)- I had trouble keeping my mind on what I was doing; (3) - I felt depressed; (4) - I felt that everything I did was an effort.; (5)- I felt lonely (Cronbach’s α = 0.76). Each item rated a 4-point Likert-type scale ranging from 0:Rarely or none of the time (less than 1 day), 1:Some or a little of the time (1-2 days), 2:Occasionally or a moderate amount of time (3‐4 days), 3:All of the time (5‐7 days). The possible range is from 0 to 15, and a cutoff score of five or higher indicates the presence of depressive symptoms [17, 18].

Screen use

The question “How long have you spent watching TV, playing video games, using a computer, and playing with your mobile phone on average per day during the past seven days?” measured screen use. A cutoff value of two hours or more per day indicates the presence of screen use as “high”(≥ 2 hours per day) and “low” (< 2 hours per day) [8].

Controlling factors

We measured participants' weight (kg) and height (cm) to one decimal point by the digital scales to calculate BMI. The Taiwan Ministry of Health and Welfare classifies BMI status as "underweight" (BMI < 18.5), “normal” (18.5 ≥ BMI < 24), and “overweight or obese” (BMI ≥ 24) [19] according to a WHO Expert Consultation for Appropriate Body-Mass Index for Asian Populations [20]. We divided the frequency of skipping breakfast into two categories: "low" (0–2 times/week) and "high" (3 times/week) depending on how many times the participant reported these actions during the last week.

Socio determinants

Personal characteristics involved sex, age, and school type (junior high school, senior high school, or vocational high school) were determined using self-reported survey responses. The 4-point Likert-type responses to four statements, such as "My classmates/friends care about what happens to me" (range 4–16, cutoff value 8, Cronbach's = 0.90), indicated peer support. Responses to six items, such as "My school is a nice place to be" (range 6–24, cutoff value 12, Cronbach's = 0. 88), were used to determine school support. Being bullied experiences were determined based on responses to four items such as “A particular classmates/friends or group of students pushed, shoved, tripped, or picked fights with me”[21]. The highest education level attained by the parents was used to classify them as (1) junior high school graduate or below, (2) senior high school graduate, or (3) university graduate.

Statistical analysis

An analysis was performed in 2021. The TAALS study team assigned weights to weight variables in order to reduce bias caused by the survey design and differential non-response by individual participants[13]. Missing depressive symptoms records (136/18645 ~ 0.7%) were removed through selection, and no imputation was performed to replace a few missing values for other variables (Additional File 2).

We used the Chi-square tests for categorical variables to analyze the characteristics of participants, depressive symptoms, and substance use by sex and school type.

The logistic regression model was used to assess the association of depressive symptoms and screen use with substance use. Models stratified by sex and school type were employed to determine the associations in each population sub-group. Logistic regression models were mutually adjusted for BMI, skipping breakfast and socio determinants.

SPSS was used to conduct all of the analyses (version 25; IBM SPSS Statistic). To account for multiple testing, an alpha-level of 0.05 was employed throughout the study to test for statistical significance.

Overall, among 18509 analyzed samples, 8964 (48.4%) were male, and 9545 (51.6%) were female. In addition, there were 6846 (37.0%) junior high school students aged 13, 4783 (25.8%) senior high school students, and 6880 (37.2%) vocational high school students aged 16.

Proportion Of Substance Use, Depressive Symptoms And Screen Use Among Adolescents

Table 1 showed participants’ substance use, depressive symptoms and screen use compared by sex and age. Only 6.4% of participants reported binge drinking, 5.6% reported smoking, 4.4% reported E-cigarette smoking, 5.0% reported betel chewing. Nearly one-third of participants had depressive symptoms and more than a half of responses exhibited high screen use. Compared to males, females were more likely to present depressive symptoms (34.7% vs 28%, p < 0.001), but were less likely to engage in substance use. Compared to younger adolescents, the older ones were more likely to engage in all substance use, screen use, and depressive symptoms. Other characteristics of participants were represented in Additional File 3.

Table 1

Characteristics of participants by sex and age
Variables	Total (n = 18,509)	Male (n = 8,964)	Female (n = 9,545)	p	Older (n = 11,663)	Younger (n = 6,846)	p
Binge drinking, n (%)				< 0.001			< 0.001
Yes	1186 (6.4)	735 (8.2)	451 (4.7)		930 (8)	256 (3.7)
No	17,312 (93.6)	8223 (91.8)	9089 (95.3)		10728 (92)	6584 (96.3)
Smoking, n (%)				< 0.001			< 0.001
Yes	1030 (5.6)	780 (8.7)	250 (2.6)		835 (7.2)	195 (2.8)
No	17,472 (94.4)	8177 (91.3)	9295 (97.4)		10822 (92.8)	6650 (97.2)
E-cigarette smoking, n (%)				< 0.001			< 0.001
Yes	814 (4.4)	547 (6.1)	267 (2.8)		575 (4.9)	239 (3.5)
No	17891 (95.6)	8414 ( 93.9)	9277 (97.2)		11086 (95.1)	6605 (96.5)
Betel Chewing, n (%)				< 0.001			< 0.001
Yes	927 (5.0)	707 (7.9)	220 (2.3)		723 (6.2)	204 (3.0)
No	1757 (95.0)	8253 (92.1)	9325 (97.7)		10939 (93.8)	6639 (97)
Depressive symtoms, n (%)				< 0.001			< 0.001
Yes	5816 (31.4)	2506 (28)	3310 (34.7)		4074 (34.9)	1742 (25.4)
No	12,693 (68.6)	6458 (72)	6235 (65.3)		7589 (65.1)	5104 (74.6)
Screen use, n (%)				0.002			< 0.001
High	10,047 (54.4)	4960 (55.5)	5087 (53.4)		7114 (61.1)	2933 (43)
Low	8427 (45.6)	3980 (44.5)	4447 (46.6)		4533 (38.9)	3894 (57)

Association Between Depressive Symptoms, Screen Use And Substance Use

In adjusted logistic regression models (Table 2- Additional file 4), participants with depressive symptoms and screen use were more likely to report binge drinking, smoking, e-cigarette smoking, and betel chewing. The odds of occurring substance use were significantly higher in males than females. As for school type, compared to junior high school students, senior high school students were only significantly higher in binge drinking, meanwhile, a higher risk of acquiring substance use was observed among vocational high school students. The modified effects of sex and school type on the association between depressive symptoms, screen use, and substance use would be precisely present via further stratified results.

Table 2

Association between depressive symptoms, screen time and substance use
Variables*	Binge drinking		Smoking		E-cigarette smoking		Betel chewing
Variables*	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p
Sex
Male	1.64 (1.43–1.89)	< 0.001	3.55 (2.99–4.23)	< 0.001	2.11 (1.77–2.51)	0	3.49 (2.92–4.16)	< 0.001
Female	Ref		Ref		Ref		Ref
School type
Vocational	2.75 (2.29–3.29)	< 0.001	3.59 (2.91–4.43)	< 0.001	1.52 (1.24–1.85)	0	2.3 (1.88–2.8)	< 0.001
Senior	1.38 (1.12–1.7)	0.003	1.29 (1-1.68)	0.053	0.85 (0.66–1.08)	0.174	1.24 (0.98–1.57)	0.077
Junior	Ref		Ref		Ref		Ref
Depressive symptoms
Yes	1.66 (1.45–1.92)	< 0.001	1.47 (1.26–1.72)	< 0.001	1.36 (1.15–1.62)	0	1.18 (1-1.39)	0.045
No	Ref		Ref		Ref		Ref
Screen use
High	1.58 (1.36–1.84)	< 0.001	1.53 (1.29–1.82)	< 0.001	1.31 (1.1–1.57)	0.003	1.23 (1.05–1.46)	0.013
Low	Ref		Ref		Ref		Ref
*Adjusted for BMI, Skipping Breakfast, Bullying Experience, Peer support, School support, Parental Education

Stratified Logistic Regression Models By Sex And School Type

Table 3 showed the association between depressive symptoms, screen use and substance use among females across school type (Additional file 5). Females junior high school students with depressice symptoms were more likely to engage in binge drinking (OR = 3.6, 95%CI:2.21–5.86), smoking (OR = 4.21, 95%CI: 1.95–9.07), e-cigarette smoking(OR = 2.11, 95%CI:1.21–3.67), and betel chewing (OR = 2.02, 95%CI:1.1–3.68). Among senior high school group screen use remarkablely associated with binge drinking (OR = 3.61, 95%CI: 2.12–6.16) and smoking (OR = 6.83, 95%CI: 2.36–19.78) but its association with E-cigarette smoking and betel chewing were not significant. Meanwhile, among vocational high school student, depressive symptoms and screen use were significantly asscociated with only binge drinking.

Table 3

Association between depressive symptoms, screen time and substance use among females across school type
Variables*	Binge drinking		Smoking		E-cigarette smoking		Betel chewing
Variables*	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p
Vocational High school
Depressive symptoms
Yes	1.54 (1.15–2.07)	0.004	1.16 (0.79–1.69)	0.46	1.1 (0.74–1.65)	0.64	1.17 (0.77–1.78)	0.47
No	Ref		Ref		Ref		Ref
Screen use
High	1.83 (1.25–2.67)	0.002	1.43 (0.89–2.29)	0.14	1.3 (0.8–2.1)	0.3	1.68 (0.98–2.88)	0.06
Low	Ref		Ref		Ref		Ref
Senior high school
Depressive symptoms
Yes	1.49 (0.92–2.39)	0.1	3.25 (1.46–7.23)	< 0.001	1.52 (0.83–2.76)	0.17	1.08 (0.51–2.32)	0.84
No	Ref		Ref		Ref		Ref
Screen use
High	3.61 (2.12–6.16)	< 0.001	6.83 (2.36–19.78)	< 0.001	1.16 (0.64–2.12)	0.63	1.2 (0.57–2.52)	0.63
Low	Ref		Ref		Ref		Ref
Junior high school
Depressive symptoms
Yes	3.6 (2.21–5.86)	< 0.001	4.21 (1.95–9.07)	< 0.001	2.11 (1.21–3.67)	0.01	2.02 (1.1–3.68)	0.023
No	Ref		Ref		Ref		Ref
Screen use
High	1.97 (1.22–3.17)	0.01	2.24 (1.06–4.76)	0.04	2.42 (1.38–4.27)	< 0.001	1.2 (0.67–2.15)	0.536
Low	Ref		Ref		Ref		Ref
*Adjusted for BMI, Skipping Breakfast, Bullying Experience, Peer support, School support, Parental Education

Associations between depressive symptoms, screen use and substance use among males across school types were shown in Table 4 (Additional File 6). In vocational high school group, the significant association between depressive symptoms and binge drinking, smoking and e-cigarette smoking were investigated. Meanwhile, screen use was significantly associated with binge drinking, smoking, and e-cigarette smoking among senior high school students. As for junior high school group, males with depressive symptoms were more likely to report binge drinking, and for those who participated in screen use were more likely to engage in smoking. No significant association related to betel chewing was observed across males subgroups.

Table 4

Association between depressive symptoms, screen time and substance use among males across school type
Variables*	Binge drinking		Smoking		E-cigarette smoking		Betel chewing
Variables*	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p	OR (95% CI)	p
Vocational High school
Depressive symptoms
Yes	1.48 (1.17–1.86)	< 0.001	1.37 (1.1–1.71)	0.01	1.45 (1.09–1.93)	0.01	1.03 (0.8–1.32)	0.82
No	Ref		Ref		Ref		Ref
Screen use
High	1.22 (0.95–1.56)	0.12	1.16 (0.92–1.47)	0.21	1.02 (0.75–1.37)	0.92	1.23 (0.95–1.59)	0.12
Low	Ref		Ref		Ref		Ref
Senior high school
Depressive symptoms
Yes	1.58 (1.05–2.39)	0.03	1.25 (0.77–2.02)	0.37	1.07 (0.62–1.84)	0.8	1.29 (0.85–1.98)	0.24
No	Ref		Ref		Ref		Ref
Screen use
High	1.59 (1.07–2.37)	0.02	1.81 (1.12–2.91)	0.02	1.76 (1.06–2.94)	0.03	1.16 (0.78–1.73)	0.46
Low	Ref		Ref		Ref		Ref
Junior high school
Depressive symptoms
Yes	1.73 (1.09–2.76)	0.02	1.39 (0.85–2.28)	0.19	1.18 (0.75–1.84)	0.48	1.29 (0.85–1.98)	0.24
No	Ref		Ref		Ref		Ref
Screen use
High	1.1 (0.72–1.7)	0.65	1.74 (1.1–2.76)	0.02	1.26 (0.86–1.86)	0.24	1.16 (0.78–1.73)	0.46
Low	Ref		Ref		Ref		Ref
*Adjusted for BMI, Skipping Breakfast, Bullying Experience, Peer support, School support, Parental Education

This study objectively determined the associations of depressive symptoms and screen use on substance use among Taiwanese adolescents. Our findings provided the updated patterns of binge drinking, smoking, e-cigarette smoking and betel chewing in adolescents, highlighting the significances of depressive symptoms and screen use after adjust skipping breakfast and socio determinants. Our research contributed to current knowledge regarding health consequences of substance use that develop in early adolescence and remain throughout a lifetime [3]. Furthermore, we stratified the individuals into subgroups to reveal how sex and school type modify the association between depressive symptoms and screen use on substance use.

Substance use was reciprocally related to depressive symptoms. Previous studies demonstrated that binge alcohol consumption would cause depressive symptoms through cohort obsevations [22]and animal model experiments[23]. In reverse, the mechanisms that might explain the comorbidity of depressive symptoms and substance use disorders including binge drinking are the self-medication hypothesis[24] and the neurobiological system[25]. The complicated temporal relationship on depressive symptoms leading to substance use is supported by some studies while other do not[24, 26–30]. In Taiwan, previous cross-sectional studies characterized the relation of substance use with depressive symptoms[31] and loneliness[32].

Binge drinking has been particularly influenced by the drinking behaviors of fathers and peer groups, and the relationship of students with their peer groups[33, 34]. A growing trends of being exposed to alcohol advertising through social media platforms, which may result in the promotion of drinking among younger age groups[35]. A follow-up research among Taiwanese middle school children (aged 13–14 years) found that exposure to alcohol advertisements on TV, the Internet, or radio was related with greater drinking initiation or an increased risk of occasional drinking[36]. Our findings that females were more likely to engage in screen use than males may support the contrast trends of binge drinking across gender[35].

Smoking behavior surveys of high school student were annually conducted in Taiwan since 1993. Compared to national GYTS results in 2015, our findings indicated that the prevalence of smoking was higher, meanwhile, e-cigarette smoking was slightly lower[37]. The differences might be due to the proportion of the study sample's vocational and senior high school students. A recent Taiwan SimSmoke modeling study demonstrated the decreasing trends of cigarette smoking in the general population. However, e-cigarette smoking seemed to increase according to recent GYTS findings[38]. The main driving factor of vaping which would be considered as “friends are smoking”[37] may relate to our significant factor as screen use which commonly associated with social network interaction among Asian students[39].

Adolescence betel chewers were early observed since the 1990s in central and south Taiwan [40–45]. This behavior was characterized that it begins at age 12 [42], grows with increasing age and will be sustained in adulthood[41]. The first betel chewing of high school students was considered an imitation from a family member (father/grandfather)[42] or a curious experiment under friend/classmate pressure[41]. Previous studies found smoking and alcohol drinking in many betel chewers, particularly smoking[41–45]. Other related factors were ethnic, rural/urbal, occupation[40]. Nevertheless, our findings found no significant difference in betel chewing across regions and ethnicity among adolescents. On the other hand, Taiwan successfully raised public awareness on areca/betel quid hazards and decreasing betel chewing rates on oral cancer prevention among adults over 18 [46]. However, betel chewing was not integrated on Global School based Student Health Survey[47] in Taiwan. Recently, the TAALS was a rare comprehensive survey on monitoring betel chewing[13]. Our findings may attract attention to other novel risk factors of betel chewing which were the rising of depressive symptoms and screen use.

This study has several methodological limitations. First, because this was a cross-sectional study, the findings cannot be used to indicate the temporal relationship. Second, based on questionnaire responses, measurements of both substance use and depressive symptoms would contain bias. Nonetheless, our effort in applying a class – based interview system [13] might reduce the bias of self-administration surveys mentioned in previous works [48]. Third, some factors related to depressive symptoms, for instance, mental health literacy, emotion self-regulation[49], were not adjusted in our analysis.

Our research has several strengths. This study's nationwide sampling offered a representative and consistent sample of Taiwan's adolescent population. Compared to previouse studies, a novel is e-cigarette smoking integrated in models. Adolescent demographics showed diverse social determinants, and subtance use stratified by school types. The stratified results enable the development of customized health promotion strategies for each subgroup.

The findings of this study showed that depressive symptoms, screen use were positively associated with binge drinking, smoking, e-cigarette smoking among Taiwanese adolescents. Secondary results highlighted the notable significance of depressive symptoms and screen use on binge drinking and smoking in junior and senior high school females students. Further heatlh education and promotion programs should be modified and aimed to specify target population.

BMI

Body mass index

CES-D

Center for Epidemiologic Studies Depression Scale

GYTS

Global Youth Tobacco Survey

Odd ratios

TAALS

Taiwan Adolescent to Adult Longitudinal Study

WHO

World Health Organization

- Ethics approval and consent to participate

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Taipei Medical University—Joint Institutional Review Board (TMU—JIRB) no. 201410043. Informed consent was obtained from all participants involved in the study and their parents. Both parents and students had to provide informed consent form before partici- pating in the investigation.

- Consent for publication

Not applicable.

- Availability of data and materials

The data that support the findings of this study are available from the Taiwan Health Promotion Administration, but are restricted for research use only. The data are not publicly available. Data are available from the authors upon reasonable request and with permission of the Taiwan Health Promotion Administration. To request data from this study, please contact Professor Hung-Yi Chiou, email: [email protected]; tel: +886-2-2736-1661 ext. 6512.

- Competing interests

The authors declare that they have no competing interests.

- Funding

This research received no external funding.

- Authors' contributions

Conceptualization, CB, Y-WC and H-YC.; methodology, CB, L-YL and H-YC.; validation, L-YL, Y-WC and H-YC.; formal analysis, CB and C-JL; investigation, CB and C-JL; resources H-YC; data curation CB and H-YC; Supervision: Y-WC, L-YL, and H-YC; writing original draft preparation, CB and L-YL; writing—review and editing, Y-WC, L-YL, and H-YC. All authors have read and agreed to the published version of the manuscript.

- Acknowledgements

The authors thank the Taiwan Health Promotion Administration for collecting the data and providing access to their database for this study.

- Authors' information

¹Ph.D. Program in Global Health and Health Security, College of Public Health, Taipei Medical University, Taipei City, Taiwan.²Department of Health Communication and Education, Quang Ninh Provincial Center for Disease Control (CDC) in Vietnam, Quang Ninh, Vietnam. ³Department of Leisure Industry and Health Promotion, National Taipei University of Nursing and Health Sciences, Taipei City, Taiwan. ⁴School of Public Health, College of Public Health, Taipei Medical University, Taipei City, Taiwan. ⁵Institute of Population Health Sciences, National Health Research Institutes, Miaoli County, Taiwan. ⁶Department of Public Health, Kaohsiung Medical University, Kaohsiung, Taiwan.

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Sex and school type modified effects of depressive symptoms and screen use on substance use among adolescent in Taiwan: findings from a nation wide cross-sectional survey

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Abstract

Background

Methods

Sample And Study Design

Measures

Statistical analysis

Results

Proportion Of Substance Use, Depressive Symptoms And Screen Use Among Adolescents

Association Between Depressive Symptoms, Screen Use And Substance Use

Stratified Logistic Regression Models By Sex And School Type

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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