Validation of the Substance Use Risk Profile Scale (SURPS) and associated factors among adolescents in Chile

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Personality traits are key predictors of adolescent substance use. This study aimed to culturally adapt and validate the Substance Use Risk Profile Scale (SURPS) among Chilean adolescents and examine its associations with substance use and related beliefs. Methods. A cross-sectional study was conducted with 2,261 students aged 10–14 years from 13 schools in Santiago, Chile. Participants completed the SURPS and the EU-Dap questionnaire on substance use. Exploratory and confirmatory factor analyses evaluated internal structure and reliability, and logistic and linear regressions examined associations between personality traits, substance use, and beliefs. Results. The four-factor structure—Hopelessness, Anxiety Sensitivity, Impulsivity, and Sensation Seeking—was confirmed after removing two items with low loadings (< 0.40). Internal consistency was acceptable for the total scale (α = 0.80) and subscales (α = 0.67–0.88). Higher Hopelessness, Impulsivity, and Sensation Seeking were associated with lifetime tobacco, alcohol, and marijuana use (all p < 0.001), stronger positive and normative beliefs, and weaker refusal skills. Anxiety Sensitivity showed no significant associations. Conclusions. The Chilean SURPS demonstrated good reliability and validity, supporting its use as a brief, culturally appropriate tool for identifying personality-based risk pathways and informing selective prevention strategies in adolescent populations. Personality traits Substance use Adolescents Psychometrics INTRODUCTION Substance use and mental disorders are among the main contributors to disease among children and adolescents in the Americas region, representing 5.2% of the disability-adjusted life years (DALYs) and 17.2% of the years lived with a disability (YLD) in the population from 0 to 14 years ( 1 ). This high prevalence of substance use among adolescents is especially worrying because during adolescence crucial changes in the brain occur, and consequently substance use can affect the correct development of affect cognitive, behavioral, and mood functions ( 2 , 3 ). Furthermore, substance use during adolescence can affect severely the adulthood period, because it is known that the earlier life consumption begins, the greater the risk of dependence in the future ( 4 ). Since all of the consequences of substance use are severe, it is important to review the factors that increase the likelihood of having substance use problems among adolescents, which include family factors, community factors, school factors, peer factors and individual factors. Regarding family risk factors, we can mention that there is a higher vulnerability for developing substance use problems among adolescents with: a family history of substance use disorder, poor care from mothers during pregnancy ending up in prenatal exposure to alcohol and other drugs, lack of parental supervision and monitoring, coming from a single parent family, having family problems, poor parent-adolescent communication and positive parental attitudes towards drugs ( 5 , 6 ). Among community risk factors, we can mention the risk influence of laws and norms that are favorable to substance use, communities that have a greater availability of substances (e.g., more liquor or marijuana stores), living in neighborhoods with high rates of poverty and with less surveillance of public places ( 6 ). Regarding school associated risk factors we can highlight the role of academic failure, low commitment to school, low expectations for achievement and poor sense of belonging to the schools ( 5 , 6 ). In addition, peers can be an important risk influence among adolescents predicting later substance use, for example, having friends who engage in antisocial behavior, being friends with peers who use substances, etc. ( 5 , 6 ) Finally, individual risk factors are also relevant to engage in substance use, including aspects from perceptions such as, positive attitudes towards drugs, to personality traits, characterized by individuals who seek sensations, with higher impulsivity and aggressive or antisocial behavior ( 7 , 8 ). This personality traits risk profiles need to be identified and assessed with a validated instrument in order to prevent future substance use among adolescents. In 2009 Woicik and colleagues ( 9 ) developed and validated among adolescents and young adults, the Substance Use Risk Profile Scale (SURPS), an instrument that identifies four personality traits that have been shown to relate to vulnerability to substance use ( 9 , 10 ). Hopelessness, Anxiety-Sensitivity, Impulsivity and Sensation Seeking are these four personality profiles that can be identified, and they are representative of the four factor structure deduced from the original validation of the instrument ( 9 ). The SURPS is a self-administered questionnaire of 23 items, and has characteristics that can count as an advantage over the use of other instruments. First, it assesses four personality dimensions, avoiding users the administration of different instruments. Second, it is a brief questionnaire, which allows its use in large longitudinal studies and also may help adolescents to keep concentrate and not answered the questions randomly. And third, it allows identifying adolescents at risk for substance use without asking directly about drug use, which is important to avoid informative bias from the adolescents, and fourth, it has been translated and validated in several countries with good reports of its psychometric properties ( 10 , 11 ). It is important to highlight some of the psychometric properties reported by the authors in the first validation, where for example, internal consistencies for the four subscales were all adequate to good, reflecting that all of the items within each of the subscales acted as indicators of the same construct without redundancy ( 9 ). And also it is important to mention the psychometric properties of the only validity study available to the date among Spanish speaking adolescents, this study was conducted in Mexico ( 11 ), and also showed the four factor structure of the SURPS, but with the exception of item 22 which showed a factor loading less than 0.40 and consequently was excluded from their analysis. Regarding reliability, they found a good reliability, for example in the Hopelessness scale with a Cronbach's alpha value of 0.80. Chile is also a Spanish speaking country, but even if it is available the Mexican version of the SURPS, there is a still a need of having the SURPS validated in Chile because it is known that linguistic and cultural adaptations need to be assess in order to have a valid and reliable instrument in the Chilean adolescent population. Therefore, considering this knowledge gap the aims of this research were the following: ( 1 ) culturally adapt the SURPS questionnaire among early adolescents in Chile, ( 2 ) assess the validity of the internal factor structure of the subscales contained in the questionnaire, ( 3 ) assess the reliability of these subscales and ( 4 ) assess the possible associations between the four personality traits from the SURPS and substance use. MATERIAL AND METHODS Participants and procedure This cross-sectional study is embedded within a larger cluster randomized controlled trial (cRCT) evaluating the effectiveness of the Yo Sé Lo Que Quiero (Unplugged) school-based substance use prevention program in Chile (12). In the first step of this project, we conducted a cross-sectional study to validate the EU-DAP questionnaire (13) and the SURPS, which is presented here. The design and main procedures have been described in detail elsewhere (13). Participants were students in grades 5 to 8 (aged 10–14 years) attending 13 mixed-sex schools in Santiago, Chile, representing low, medium, and high socioeconomic levels according to the Chilean Educational Quality Agency classification (14). All eligible students were invited to participate, and those who provided parental consent and student assent completed the study questionnaires Of the selected schools, seven came from low socioeconomic levels with a total enrollment of 920 students from 5th to 8th grade, four came from middle socioeconomic levels with a total of 1,103 students, and two came from high socioeconomic levels with a total of 1,004 students. Therefore, a total of 3,027 students were eligible to participate and were invited. Of these, a total of 2,261 (74.7%) consented and responded to the questionnaire. Measures The European Drug Addiction Prevention Trial Questionnaire (EU-Dap) The European Drug Addiction Prevention Trial Questionnaire (EU-Dap) was used to assess sociodemographic characteristics, substance use prevalence (tobacco, alcohol, and marijuana), and substance-related beliefs and refusal skills. The EU-Dap has demonstrated adequate reliability and validity in previous European (15) and Latin American studies (13, 16). Only the sections relevant to the present analyses were included. The Substance Use Risk Profile Scale (SURPS) The Substance Use Risk Profile Scale (SURPS) is a brief self-report questionnaire designed to assess four personality traits associated with substance use risk. Its development and psychometric properties have been previously described (9). It has a total of 23 items that are representative of four dimensions: Hopelessness (n of items = 7; which are the following 1, 4,7, 13, 17, 20 and 23), Anxiety Sensitivity (n of items = 5; which are the following 8, 10, 14,18, 21); Impulsivity (n of items 5: which are the following 2, 5, 11, 15, 22) and Sensation Seeking (n of items = 6, which are the following 3, 6, 9, 12, 16, 19). These items are expressed on a 4 point Likert scale (1 = strongly disagree to 4 = strongly agree); and the items 1, 4,7, 13, 20 and 23 are reverse scored (9). Statistical Analysis Descriptive analyses were conducted to characterize the sample. Means, standard deviations, and 95% confidence intervals were calculated for continuous variables, while categorical variables were summarized using frequencies and percentages. The internal structure of the Substance Use Risk Profile Scale (SURPS) was examined using factor analytic techniques appropriate for ordinal data. Polychoric correlation matrices were computed (17), and item distributions were evaluated using skewness and kurtosis coefficients. Exploratory factor analysis (EFA) was performed to examine the latent structure of the scale. The number of factors to retain was determined using Horn’s parallel analysis (18), which compares observed eigenvalues with those obtained from random data matrices. Sampling adequacy for factor analysis was assessed using the Kaiser–Meyer–Olkin (KMO) measure (19). Item retention decisions were guided by factor loadings, with values ≥ 0.40 considered acceptable (20). Items with loadings below this threshold were considered for removal based on both statistical criteria and theoretical coherence with the underlying construct. Confirmatory factor analysis (CFA) was subsequently conducted to evaluate the fit of the final factor structure. Model fit was assessed using multiple complementary indices, including the root mean square error of approximation (RMSEA) (21, 22), standardized root mean square residual (SRMR) (22), comparative fit index (CFI) (22), normalized fit index (NFI)(23), goodness-of-fit index (GFI)(21), and adjusted goodness-of-fit index (AGFI) (21). Conventional cutoff criteria were applied to determine acceptable and good model fit. Internal consistency reliability was evaluated using McDonald’s omega coefficient (24), which provides a robust estimate of scale reliability for multidimensional instruments, alongside Cronbach’s alpha for comparability with previous studies. Associations between SURPS personality traits and substance-use outcomes were examined using regression models. Lifetime prevalence of tobacco, alcohol, and marijuana use was analyzed as dichotomous outcomes using logistic regression models, reporting odds ratios (ORs) with 95% confidence intervals. Lifetime prevalence was selected due to the low frequency of recent use outcomes in this age group. Associations between SURPS subscales and continuous cognitive and behavioral correlates—positive, negative, and normative beliefs about substance use, as well as refusal skills—were examined using linear regression models, reporting standardized regression coefficients (β) with 95% confidence intervals. Statistical significance was set at p < 0.05. Descriptive analyses, exploratory factor analyses, reliability estimates, and regression models were conducted using Stata version 15. Confirmatory factor analyses were performed using R version 3.5.0 with the lavaan package. Ethical considerations All evaluation data were collected in accordance with the Declaration of Helsinki with the approval of the ethics committee of the Universidad de los Andes (CEC201734, August 7th, 2018). Participation in the study involved three stages: First, school authorities were informed about the study, and written confirmation was requested to participate. Then, the parents were sent a letter with the study information and with form requiring written and informed consent. Finally, the students were informed about the study and asked to sign an agreement confirming their participation. Confidentiality and the freedom to withdraw from it at any time were assured throughout the study. Anonymous codes were generated to protect the identities of the participants. The data were collected from August to December 2018 by research assistants who were trained by the study coordinator. During the application of the questionnaire, the research assistants explained the objectives of the study, clarified the doubts of the students, and then asked for their agreement. RESULTS Sociodemographic characteristics of the sample A total of 2,261 students aged 10 to 14 years participated in the study. Slightly more than half of the participants were male (53.3% [95% CI: 51.3–55.4]), while 46.7% [95% CI: 44.6–48.7] were female (Table 1). Most of the students lived with their mother (94.0% [95% CI: 92.9–94.9]), followed by those living with their father (69.6% [95% CI: 67.5–71.5]) and siblings (87.3% [95% CI: 85.8–88.6]). Regarding socioeconomic background, 30.5% [95% CI: 28.7–32.4] of students attended schools classified as low socioeconomic level, 37.3% [95% CI: 35.3–39.3] as medium, and 32.2% [95% CI: 30.3–34.2] as high. In terms of school administrative dependency, 38.9% [95% CI: 36.9–40.9] attended public schools, 28.9% [95% CI: 27.1–30.8] subsidized schools, and 32.2% [95% CI: 30.3–34.2] private schools. The distribution of students by grade level was relatively balanced: 23.8% [95% CI: 22.1–25.6] were in 5th grade, 27.2% [95% CI: 25.4–29.1] in 6th grade, 24.9% [95% CI: 23.2–26.8] in 7th grade, and 24.0% [95% CI: 22.3–25.8] in 8th grade. The mean age increased as expected across grades, ranging from 10.7 years (SD = 0.65) in 5th grade to 13.8 years (SD = 0.74) in 8th grade. See Table 1. INSERT TABLE 1 Substance use prevalence As shown in Table 2, tobacco use in the last month was reported by 3.4% of students, 6.3% in the last year, and 11.2%for lifetime use. Alcohol use was higher, with 9.8% in the last 30 days, 22.6% in the last year, and 39.2% lifetime prevalence. Marijuana use was 2.7% in the last month, 4.5% in the last year, and 7.2% lifetime. Prevalence values were similar between males and females across all substances. INSERT TABLE 2 Exploratory factor analysis Table 3 presents the results of the exploratory factor analysis (EFA) of the SURPS. Four factors were identified, consistent with the theoretical dimensions of Hopelessness, Anxiety Sensitivity, Impulsivity, and Sensation Seeking. Most items showed adequate factor loadings above the 0.40 cutoff, confirming the expected structure of the scale. Items within Hopelessness loaded between 0.62 and 0.89, Anxiety Sensitivity between 0.47 and 0.63, Impulsivity between 0.52 and 0.73, and Sensation Seeking between 0.38 and 0.66. Two items—one from the Impulsivity subscale (item 22, loading = 0.32) and one from the Sensation Seeking subscale (item 6, loading = 0.38)—showed factor loadings below the 0.40 threshold. Overall, the distribution of skewness and kurtosis values indicated acceptable normality for all items, supporting the adequacy of the data for factor extraction. INSERT TABLE 3. Horn’s Parallel Analysis and explained variance Suppl. 1, Table 1 shows the results of Horn’s Parallel Analysis, which supported the extraction of four factors with eigenvalues greater than 1.0 (5.55, 4.85, 1.81, and 1.12), confirming the theoretical four-factor structure of the SURPS. As shown in Suppl. 1, Table 2, these four factors together accounted for 52% of the total variance after rotation, with the first factor explaining 22%, the second 11%, the third 10%, and the fourth 9%. These results further support the adequacy of a four-factor solution and its alignment with the original model proposed by Woicik et al. (2009). See Suppl. 1, Tables 1 and 2. Internal consistency Table 4 presents the internal reliability indices for the SURPS and its four subscales. The overall Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy was 0.87, indicating good suitability for factor analysis. The total SURPS scale showed acceptable internal consistency (ω = 0.75; α = 0.80). Among the subscales, Hopelessness demonstrated excellent reliability (ω = 0.89; α = 0.88), while Impulsivity (ω = 0.76; α = 0.75) and Sensation Seeking (ω = 0.71; α = 0.71) showed satisfactory values. The Anxiety Sensitivity subscale presented lower, though still acceptable, coefficients (ω = 0.68; α = 0.67). INSERT TABLE 4. Confirmatory Factor Analysis Table 5 summarizes the fit indices for the four-factor structure of the SURPS. The overall model demonstrated acceptable fit (RMSEA = 0.09; SRMR = 0.08; NFI = 0.96; NNFI = 0.96; CFI = 0.96; GFI = 0.97; AGFI = 0.96). Each of the four subscales— Hopelessness , Anxiety Sensitivity , Impulsivity , and Sensation Seeking —showed good to excellent model fit, with RMSEA values ranging from 0.01 to 0.03 and CFI, NFI, and NNFI all reaching or exceeding 0.99. INSERT TABLE 5. Associations with substance use and related beliefs Suppl. 2, Tables 1 to 5 present the associations between the SURPS subscales and substance use, as well as positive, negative, and normative beliefs about substance use and refusal skills. Higher total SURPS scores were significantly associated with greater odds of lifetime tobacco, alcohol, and marijuana use (all p < 0.001). Among subscales, Hopelessness , Impulsivity , and Sensation Seeking showed significant positive associations with all three substances, whereas Anxiety Sensitivity was not significantly related to any. Similarly, higher scores on Hopelessness and Impulsivity were associated with stronger positive beliefs and weaker negative beliefs about substance use, while Sensation Seeking showed smaller but still significant effects. For normative beliefs, all subscales except Anxiety Sensitivity showed positive associations across substances. Finally, all dimensions, particularly Hopelessness and Impulsivity , were negatively associated with refusal skills for tobacco, alcohol, and marijuana (all p < 0.001). See Suppl. 2, Tables 1-5. DISCUSSION In the present study, we evaluated the psychometric properties of the SURPS in a Chilean adolescent sample and explored its associations with substance‐use behaviour, beliefs and refusal skills. Our results indicated that the four‐factor structure (Hopelessness, Anxiety Sensitivity, Impulsivity and Sensation Seeking) was upheld in Confirmatory Factor Analysis, and internal consistency for the overall scale and most subscales was acceptable. Moreover, higher scores on the total SURPS and on the Hopelessness, Impulsivity and Sensation Seeking subscales were significantly associated with greater odds of lifetime tobacco, alcohol and marijuana use. In addition, these subscales showed consistent associations with more favourable positive substance‐use beliefs, less negative beliefs, stronger normative beliefs favouring use, and weaker refusal skills for each of the substances assessed. In contrast, the Anxiety Sensitivity dimension demonstrated weaker and non‐significant associations with both substance‐use outcomes and related cognitive variables. The findings of this study are consistent with previous validations of the Substance Use Risk Profile Scale (SURPS) conducted in different cultural and age contexts. Similar to the original study by Woicik et al (4) and subsequent replications in the United Kingdom (25), Canada (26), and Mexico (11), the four-factor structure comprising Hopelessness , Anxiety Sensitivity , Impulsivity , and Sensation Seeking was supported. Internal consistency indices were satisfactory for the total scale and for most subscales, with particularly high coefficients for Hopelessness , Impulsivity , and Sensation Seeking . These dimensions also showed the strongest and most consistent associations with lifetime tobacco, alcohol, and marijuana use, while Anxiety Sensitivity displayed weaker or non-significant relationships—an observation repeatedly reported in earlier validations. The present findings further corroborate the dual-pathway model proposed in the literature, in which personality risk traits predispose adolescents to substance use through distinct mechanisms (26). The Hopelessness dimension is thought to represent an internalizing, negative-affect pathway, whereby individuals use substances as a form of self-medication to cope with depressive mood, perceived failure, or low self-worth. This interpretation is consistent with prior longitudinal studies linking hopelessness to depressive symptoms and subsequent alcohol or drug use in adolescents. In contrast, Impulsivity and Sensation Seeking represent externalizing or reward-driven pathways characterized by heightened behavioural disinhibition, novelty-seeking, and sensitivity to positive reinforcement (25). The robust associations of these traits with substance use observed in our study align with extensive evidence showing that adolescents high in impulsivity or sensation seeking are more likely to initiate use earlier, experiment with multiple substances (27), and show stronger positive expectancies and weaker refusal skills (28). In addition, the pattern of associations with cognitive variables—namely, more positive and normative beliefs about substance use, fewer negative beliefs, and lower refusal skills—provides convergent validity for the Chilean adaptation. These findings suggest that personality risk traits influence both behavioural tendencies and cognitive appraisals related to substance use, reinforcing the theoretical coherence of the SURPS framework. From a measurement standpoint, two items—one from Impulsivity (“I feel I have to be manipulative to get what I want”) and one from Sensation Seeking (“I enjoy new and exciting experiences even if they are unconventional”)—displayed factor loadings below the 0.40 threshold and were removed from the final Confirmatory Factor Analysis. Similar findings have been reported in other adolescent adaptations of the SURPS (11, 25). Several explanations are possible. First, these items may have limited developmental relevance for younger adolescents, who may not fully identify with manipulative or overtly unconventional behaviours. Second, cultural norms in Chile, which emphasize social conformity, family cohesion, and interpersonal respect, may make endorsement of such behaviours less socially acceptable, reducing variability and leading to weaker factor saturation. Third, subtle differences in translation or contextual understanding could contribute to differential item functioning. The removal of these items improved model fit without compromising the conceptual integrity of the subscales, indicating that minor cultural and linguistic adjustments can enhance measurement precision while preserving theoretical validity. Overall, the present results confirm both the cross-cultural robustness and contextual adaptability of the SURPS. The replication of its four-factor structure and the strong external validity of most subscales demonstrate that the instrument is a reliable tool for identifying personality risk pathways for substance use among Chilean adolescents. At the same time, the minor modifications made in this study highlight the importance of culturally sensitive adaptation and developmental calibration to maintain the construct validity of personality-based risk assessment tools across diverse populations. Limitations Several limitations should be acknowledged when interpreting these findings. First, the study employed a cross-sectional design, which does not allow for causal inference regarding the temporal sequence between personality risk traits and substance-use behaviours. Longitudinal evidence has shown that personality profiles assessed by the SURPS can predict later onset and escalation of substance use (25, 26), suggesting that future studies in Chile should incorporate follow-up assessments to establish predictive validity over time. Second, all variables were based on self-reported data, which may be affected by recall bias or social desirability effects. Previous research indicates that adolescents often underreport substance use in self-administered surveys compared to biological verification (29) or collateral reports (30). Despite these limitations, self-report remains the most feasible and widely used method for large-scale school-based studies, particularly when anonymity is guaranteed. Third, although the sample was diverse in terms of school type and socioeconomic background, it was limited to a specific region of Chile. This may constrain generalizability to adolescents from other regions or cultural subgroups, as cross-national studies have shown that cultural norms (31, 32), religious affiliation (33), and socioeconomic factors (34, 35) can influence both personality expression and substance-use behaviours. Future research should include more geographically and culturally heterogeneous samples to enhance external validity. Fourth, two items—one from Impulsivity and one from Sensation Seeking —were removed due to low factor loadings (< 0.40). Although this adjustment improved model fit, it may also indicate potential measurement bias or differential item functioning linked to cultural interpretation or developmental appropriateness. Similar challenges have been documented in other adolescent validations of the SURPS (11, 25). Cross-cultural adaptation processes should therefore continue to evaluate whether certain item contents or phrasing require modification to ensure conceptual equivalence. Finally, while the study examined multiple cognitive and behavioural correlates of substance use, unmeasured confounders—such as peer influence, family functioning, parental monitoring, or comorbid psychopathology—may contribute to the observed associations. Prior studies have shown that these contextual factors interact with personality-based vulnerabilities to predict adolescent substance use and related outcomes (25, 36, 37). Future work integrating multilevel or longitudinal designs could help disentangle these complex relationships. Implications The present findings have several implications for research, prevention, and public health practice. The Chilean adaptation of the SURPS provides a psychometrically sound and culturally relevant instrument to identify distinct personality-based risk pathways for substance use in early adolescence. Such screening tools can inform the development of selective and indicated prevention programs that tailor intervention strategies to individual profiles, as demonstrated in prior international trials (38, 39). For example, interventions targeting Hopelessness have incorporated cognitive restructuring and emotional regulation components, while those addressing Impulsivity and Sensation Seeking emphasize behavioural self-control, problem-solving, and alternative reinforcement activities (40). The current findings support the feasibility of applying this model in Latin American school settings, where personality-targeted prevention could complement universal education efforts and reduce the early onset of substance use. Moreover, the SURPS could serve as a screening and monitoring tool within national public health and school-based prevention frameworks, such as those coordinated by SENDA or the Ministry of Education, facilitating early identification of youth most at risk and enabling more cost-effective resource allocation. Finally, the study contributes to the growing cross-cultural validation literature on adolescent personality and substance use, highlighting the value of adapting theoretically grounded instruments to local contexts to enhance both scientific comparability and public health impact. Conclusions This study provides robust evidence supporting the reliability, factorial validity, and external correlates of the Chilean adaptation of the Substance Use Risk Profile Scale (SURPS) among early adolescents. The replication of its four-factor structure and the consistent associations between personality traits and substance-use behaviors underscore the instrument’s conceptual soundness and practical utility. The SURPS emerges as a culturally appropriate, psychometrically valid tool for identifying personality-based risk pathways that can guide early, selective prevention strategies within Chilean schools and broader Latin American contexts. Continued research should further refine item content, assess predictive validity through longitudinal designs, and evaluate the effectiveness of personality-targeted interventions informed by these profiles. Declarations Acknowledgements The authors thank the participating schools, students, and families for their valuable collaboration. We also acknowledge the support of the fieldwork team and data collectors from the Center for Student Mental Health at Universidad de los Andes. Funding This research was funded by the National Research and Development Agency [ANID]; Unique ID: Fondecyt Regular 1181724. The funding institution had no role in the study design, data collection, analysis, interpretation, or manuscript preparation. Conflict of interest The authors declare that they have no conflicts of interest relevant to this article. Ethical approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments. The study protocol was approved by the Ethics Committee of Universidad de los Andes (approval no. CEC201734, August 7th, 2018). Consent for publication Not applicable. Data availability The datasets generated and analyzed during the current study are not publicly available due to confidentiality agreements with participating schools but are available from the corresponding author on reasonable request. Author contributions J.G. conceived and designed the study, supervised data collection, and wrote the first draft of the manuscript. S.R. contributed to data collection. M.I.G. conducted statistical analyses and contributed to data interpretation. All authors read and approved the final manuscript. 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Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the Substance Use Risk Profile Scale. Alcohol Clin Exp Res. 2013;37 Suppl 1:E281-90. Malmberg M, Kleinjan M, Overbeek G, Vermulst AA, Lammers J, Engels RCME. Are there reciprocal relationships between substance use risk personality profiles and alcohol or tobacco use in early adolescence? Addictive Behaviors. 2013;38(12):2851-9. Leeman RF, Hoff RA, Krishnan-Sarin S, Patock-Peckham JA, Potenza MN. Impulsivity, sensation-seeking, and part-time job status in relation to substance use and gambling in adolescents. Journal of Adolescent Health. 2014;54(4):460-6. Delaney-Black V, Chiodo, L. M., Hannigan, J. H., Greenwald, M. K., Janisse, J., Patterson, G., Huestis, M. A., Ager, J., & Sokol, R. J. Just say "I don't": lack of concordance between teen report and biological measures of drug use. Pediatrics 2010;126(5):887-93. Jones JD, Scott JC, Calkins ME, Ruparel K, Moore TM, Gur RC, et al. Correspondence between adolescent and informant reports of substance use: Findings from the Philadelphia Neurodevelopmental Cohort. Addictive Behaviors. 2017;65:13-8. Girard R, Trinh CD, Schick MR, Spillane NS. The protective role of culture and family disapproval on substance use among American Indian adolescents. American Journal of Drug and Alcohol Abuse. 2025. Nasim A, Fernander A, Townsend TG, Corona R, Belgrave FZ. Cultural protective factors for community risks and substance use among rural african american adolescents. Journal of Ethnicity in Substance Abuse. 2011;10(4):316-36. Haber JR, Jacob T. Alcoholism risk moderation by a socio-religious dimension. Journal of Studies on Alcohol and Drugs. 2007;68(6):912-22. Kuzman M, Pejnović-Franelić I, editors. Adolescents' substance abuse experimentation. Paediatria Croatica, Supplement; 2010. Link TC. Adolescent substance use in Germany and the United States: A cross-cultural test of the applicability and generalizability of theoretical indicators. European Journal of Criminology. 2008;5(4):453-80. Edalati H, Doucet C, Conrod PJ. A Developmental Social Neuroscience Model for Understanding Pathways to Substance Use Disorders During Adolescence. Seminars in Pediatric Neurology. 2018;27:35-41. Escamilla I, Juan N, Benito A, Castellano-García F, Rodríguez-Ruiz F, Haro G. Substance Addiction in Adolescents: Influence of Parenting and Personality Traits. Brain Sciences. 2024;14(5). Conrod PJ, O'Leary-Barrett M, Newton N, Topper L, Castellanos-Ryan N, Mackie C, et al. Effectiveness of a selective, personality-targeted prevention program for adolescent alcohol use and misuse: a cluster randomized controlled trial. JAMA Psychiatry. 2013;70(3):334-42. Castellanos-Ryan N, Conrod PJ. Personality correlates of the common and unique variance across conduct disorder and substance misuse symptoms in adolescence. J Abnorm Child Psychol. 2011;39(4):563-76. Conrod PJ, Castellanos-Ryan N, Mackie C. Long-term effects of a personality-targeted intervention to reduce alcohol use in adolescents. J Consult Clin Psychol. 2011;79(3):296-306. Tables Table 1: Sociodemographic features of the sample. Variables n % or Mean [95% CI] or (SD) Gender Female 1055 46.7 [44.6-48.7] Male 1206 53.3 [51.3-55.4] Family Structure Lives with father 1416 69.6 [67.5-71.5] Lives with mother 2049 94.0 [92.9-94.9] Lives with siblings 1831 87.3 [85.8-88.6] Socioeconomic Level High 728 32.2 [30.3-34.2] Medium 843 37.3 [35.3-39.3] Low 690 30.5 [28.7-32.4] Type of School dependency Private 728 32.2 [30.3-34.2] Subsidized 654 28.9 [27.1-30.8] Public 879 38.9 [36.9-40.9] Class grade 5 th 539 23.8 [22.1-25.6] 6 th 615 27.2 [25.4-29.1] 7 th 564 24.9 [23.2-26.8] 8 th 543 24.0 [22.3-25.8] Age by Class grade 5 th 522 10.7 (0.65) 6 th 611 11.8 (0.72) 7 th 562 12.8 (0.73) 8 th 536 13.8 (0.74) Note: n = number of participants; CI = Confidence Interval; SD = Standard Deviation. Table 2: Substance use prevalence. Variables Total Females Males Tobacco use in the last month Grade n % [95% CI] n % [95% CI] n % [95% CI] 5 th 7 1.3 [0.6-2.7] 4 1.6 [0.6-4.1] 3 1.1 [0.3-3.3] 6 th 27 4.4 [3.0-6.3] 13 4.5 [2.6-7.6]] 14 4.3 [2.6-7.1] 7 th 16 2.8 [1.8-4.6] 8 3.1 [1.5-6.0] 8 2.6 [1.3-5.2] 8 th 25 4.7 [3.2-6.9] 14 5.9 [3.5-9.7] 11 3.8 [2.1-6.8] Total 75 3.4 [2.7-4.2] 39 3.7 [2.7-5.1] 36 3.0 [2.2-4.2] Tobacco use in the last year 5 th 12 2.3 [1.3-3.9] 5 1.9 [0.8-4.6] 7 2.5 [1.2-5.2] 6 th 27 4.4 [3.1-6.4] 9 3.2 [1.6-6.0] 18 5.6 [3.5-8.7] 7 th 30 5.4 [3.8-7.6] 13 5.0 [2.9-8.5] 17 5.6 [3.5-8.9] 8 th 72 13.7 [11.0-16.9] 43 17.9 [13.6-23.3] 29 10.1 [7.1-14.2] Total 141 6.3 [5.4-7.4] 70 6.7 [5.4-8.4] 71 6.0 [4.8-7.5] Lifetime tobacco use 5 th 28 5.3 [3.7-7.5] 14 5.5 [3.3-9.1] 14 5.1 [3.0-8.4] 6 th 46 7.5 [5.7-9.9] 15 5.2 [3.2-8.5] 31 9.5 [6.8-13.3] 7 th 60 10.7 [8.4-13.5] 29 11.2 [7.9-15.6] 31 10.3 [7.3-14.2] 8 th 115 21.7 [18.4-25.5] 65 27.1 [21.8-33.1] 50 17.3 [13.4-22.1] Total 249 11.2 [9.9-12.5] 123 11.8 [10.0-13.9] 126 10.6 [9.0-12.5] Alcohol use in the last 30 days 5 th 22 4.1 [2.7-6.2] 9 3.5 [1.8-6.6] 13 4.7 [2.7-7.9] 6 th 31 5.1 [3.6-7.1] 13 4.5 [2.6-7.7] 18 5.5 [3.5-8.6] 7 th 62 11.1 [8.7-14.0] 25 9.7 [6.6-13.9] 37 12.3 [9.1-16.6] 8 th 105 19.8 [16.7-23.5] 52 21.8 [17.0-27.5] 53 18.3 [14.2-23.2] Total 220 9.8 [8.7-11.2] 99 9.5 [7.9-11.4] 121 10.2 [8.6-12.0] Alcohol use in the last year 5 th 64 12.0 [9.5-15.0] 27 10.5 [7.3-14.9] 37 13.4 [9.8-17.9] 6 th 76 12.4 [10.0-15.3] 30 10.5 [7.4-14.6] 46 14.2 [10.8-18.4] 7 th 149 26.6 [23.1-30.4] 63 24.4 [19.5-30.0] 86 28.5 [23.7-33.8] 8 th 216 41.1 [36.9-45.3] 107 45.0 [38.7-51.3] 109 37.8 [32.4-43.6] Total 505 22.6 [20.9-24.4] 227 21.8 [19.4-24.5] 278 23.3 [21.0-25.8] Lifetime alcohol use 5 th 136 25.7 [22.1-29.6] 58 22.7 [18.0-28.3] 78 28.4 [23.3-34.0] 6 th 197 32.2 [28.6-36.1] 78 27.3 [22.4-32.7] 119 36.6 [31.5-42.0] 7 th 256 45.6 [41.5-49.8] 108 41.4 [35.5-47.5] 148 49.3 [43.7-55.0] 8 th 284 54.3 [50.0-58.5] 141 59.0 [52.6-65.1] 143 50.4 [44.5-56.2] Total 873 39.2 [37.2-41.3] 385 37.0 [34.1-40.0] 488 41.2 [38.4-44.0] Marijuana use in the last 30 days 5 th 9 1.7 [0.9-3.2] 4 1.6 [0.6-4.1] 5 1.8 [0.8-4.3] 6 th 12 2.0 [1.1-3.4] 4 1.4 [0.5-3.7] 8 2.5 [1.2-4.9] 7 th 12 2.2 [1.2-3.8] 3 1.2 [0.4-3.5] 9 3.0 [1.6-5.7] 8 th 27 5.1 [3.5-7.4] 14 5.9 [3.5-9.7] 13 4.5 [2.6-7.6] Total 60 2.7 [2.1-3.5] 25 2.4 [1.6-3.5] 35 3.0 [2.1-4.1] Marijuana use in the last year 5 th 10 1.9 [1.0-3.5] 5 2.0 [0.8-4.6] 5 1.9 [0.8-4.4] 6 th 21 3.4 [2.3-5.2] 7 2.4 [1.2-5.0] 14 4.3 [2.6-7.2] 7 th 27 4.8 [3.3-7.0] 10 3.9 [2.1-7.0] 17 5.7 [3.6-9.0] 8 th 41 7.8 [5.8-10.4] 21 8.8 [5.8-13.1] 20 6.9 [4.5-10.5] Total 99 4.5 [3.7-5.4] 43 4.1 [3.1-5.5] 56 4.8 [3.7-6.1] Lifetime marijuana use 5 th 14 2.7 [1.6-4.5] 4 1.6 [0.6-4.1] 10 3.7 [2.0-6.8] 6 th 35 5.7 [4.2-7.9] 10 3.5 [1.9-6.4] 25 7.8 [5.3-11.2] 7 th 42 7.6 [5.6-10.1] 19 7.3 [4.7-11.2] 23 7.8 [5.2-11.4] 8 th 69 13.0 [10.4-16.2] 37 15.4 [11.4-20.6] 32 11.1 [7.9-15.3] Total 160 7.2 [6.2-8.4] 70 6.7 [5.4-8.4] 90 7.7 [6.3-9.3] Note: n = number of participants; CI = Confidence Interval. Table 3: Exploratory Factor Analysis of SURPS. Nr Dimensions and corresponding items Mean SD Skewness Kurtosis Factor Loading Hopelessness 1 I am content 1.58 0.86 1.48 4.42 0.86 4 I am happy 1.56 0.85 1.52 4.49 0.89 7 I have faith that my future holds great promise 1.66 0.87 1.30 3.91 0.80 13 I feel proud of my accomplishments 1.63 0.88 1.36 3.99 0.82 17 I feel that I'm a failure 1.74 0.98 1.12 3.06 0.62 20 I feel pleasant 1.72 0.90 1.15 3.48 0.86 23 I am very enthusiastic about my future 1.62 0.90 1.38 3.95 0.80 Anxiety Sensitivity 8 It's frightening to feel dizzy or faint 2.76 1.05 -0.39 1.97 0.47 10 It frightens me when I feel my heart beat change 2.42 1.09 0.98 1.71 0.61 14 I get scared when I'm too nervous 2.62 1.04 -0.15 1.84 0.60 18 I get scared when I experience unusual body sensations 2.31 1.01 0.20 1.94 0.53 21 It scares me when I'm unable to focus on a task 2.32 1.05 0.23 1.85 0.63 Impulsivity 2 I often don't think things through before I speak 2.26 0.96 0.28 2.12 0.66 5 I often involve myself in situations that I later regret being involved in 2.20 1.00 0.34 2.01 0.52 11 I usually act without stopping to think 2.21 0.99 0.36 2.08 0.73 15 Generally, I am an impulsive person 2.36 1.05 0.19 1.83 0.66 22 I feel I have to be manipulative to get what I want 1.96 1.02 0.73 2.36 0.32 Sensation Seeking 3 I would like to sky dive 2.95 1.12 -0.63 1.98 0.66 6 I enjoy new and exciting experiences even if they are unconventional 2.76 1.04 -0.41 2.00 0.38 9 I like doing things that frighten me a little 2.72 1.02 -0.34 2.02 0.56 12 I would like to learn how to drive a motorcycle 2.81 1.13 -0.43 1.79 0.66 16 I am interested in experience for its own sake, even if it is illegal 1.72 0.95 1.16 3.26 0.50 19 I would enjoy hiking long distances in wild and uninhabited territory 2.43 1.12 0.07 1.63 0.66 Note: Nr = number of corresponding item; SD = Standard Deviation. Table 4: Internal reliability Number of Factors Number of Items KMO Omega Reliability Cronbach’s alpha SURPS 4 21 0.87 0.75 0.80 Hopelessness 1 7 0.91 0.89 0.88 Anxiety Sensitivity 1 5 0.79 0.68 0.67 Impulsivity 1 4 0.79 0.76 0.75 Sensation Seeking 1 5 0.81 0.71 0.71 Note: KMO = Kaiser-Meyer- Table 5: Confirmatory Factor Analysis indicators Indicator SURPS Hopelessness Anxiety Sensitivity Impulsivity Sensation Seeking Good fit Acceptable fit RMSEA 0.09 0.09 0.03 0.01 0.03 ≤0.05 ≤0.08 SRMR 0.08 0.05 0.02 0.01 0.02 ≤0.1 ≤0.1 NFI 0.96 0.99 1.00 1.00 1.00 ≥0.95 ≥0.90 NNFI 0,96 0.99 1.00 1.00 1.00 ≥0.97 ≥0.95 CFI 0.96 1.00 1.00 1.00 1.00 ≥0.97 ≥0.90 GFI 0.97 1.00 1.00 1.00 1.00 >0.95 >0.90 AGFI 0.96 0.99 0.99 1.00 0.99 >0.90 >0.90 Note: RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Root Mean Square Residual; NFI = Normalized Fit Index; NNFI = Normalized Fit Index; CFI = Comparative Adjustment Index; GFI = Goodness of Fit Index; AGFI = Adjusted Goodness of Fit Index. 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This high prevalence of substance use among adolescents is especially worrying because during adolescence crucial changes in the brain occur, and consequently substance use can affect the correct development of affect cognitive, behavioral, and mood functions (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Furthermore, substance use during adolescence can affect severely the adulthood period, because it is known that the earlier life consumption begins, the greater the risk of dependence in the future (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSince all of the consequences of substance use are severe, it is important to review the factors that increase the likelihood of having substance use problems among adolescents, which include family factors, community factors, school factors, peer factors and individual factors. Regarding family risk factors, we can mention that there is a higher vulnerability for developing substance use problems among adolescents with: a family history of substance use disorder, poor care from mothers during pregnancy ending up in prenatal exposure to alcohol and other drugs, lack of parental supervision and monitoring, coming from a single parent family, having family problems, poor parent-adolescent communication and positive parental attitudes towards drugs (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Among community risk factors, we can mention the risk influence of laws and norms that are favorable to substance use, communities that have a greater availability of substances (e.g., more liquor or marijuana stores), living in neighborhoods with high rates of poverty and with less surveillance of public places (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Regarding school associated risk factors we can highlight the role of academic failure, low commitment to school, low expectations for achievement and poor sense of belonging to the schools (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). In addition, peers can be an important risk influence among adolescents predicting later substance use, for example, having friends who engage in antisocial behavior, being friends with peers who use substances, etc. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e) Finally, individual risk factors are also relevant to engage in substance use, including aspects from perceptions such as, positive attitudes towards drugs, to personality traits, characterized by individuals who seek sensations, with higher impulsivity and aggressive or antisocial behavior (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis personality traits risk profiles need to be identified and assessed with a validated instrument in order to prevent future substance use among adolescents. In 2009 Woicik and colleagues (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) developed and validated among adolescents and young adults, the Substance Use Risk Profile Scale (SURPS), an instrument that identifies four personality traits that have been shown to relate to vulnerability to substance use (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Hopelessness, Anxiety-Sensitivity, Impulsivity and Sensation Seeking are these four personality profiles that can be identified, and they are representative of the four factor structure deduced from the original validation of the instrument (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe SURPS is a self-administered questionnaire of 23 items, and has characteristics that can count as an advantage over the use of other instruments. First, it assesses four personality dimensions, avoiding users the administration of different instruments. Second, it is a brief questionnaire, which allows its use in large longitudinal studies and also may help adolescents to keep concentrate and not answered the questions randomly. And third, it allows identifying adolescents at risk for substance use without asking directly about drug use, which is important to avoid informative bias from the adolescents, and fourth, it has been translated and validated in several countries with good reports of its psychometric properties (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). It is important to highlight some of the psychometric properties reported by the authors in the first validation, where for example, internal consistencies for the four subscales were all adequate to good, reflecting that all of the items within each of the subscales acted as indicators of the same construct without redundancy (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnd also it is important to mention the psychometric properties of the only validity study available to the date among Spanish speaking adolescents, this study was conducted in Mexico (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), and also showed the four factor structure of the SURPS, but with the exception of item 22 which showed a factor loading less than 0.40 and consequently was excluded from their analysis. Regarding reliability, they found a good reliability, for example in the Hopelessness scale with a Cronbach's alpha value of 0.80.\u003c/p\u003e \u003cp\u003eChile is also a Spanish speaking country, but even if it is available the Mexican version of the SURPS, there is a still a need of having the SURPS validated in Chile because it is known that linguistic and cultural adaptations need to be assess in order to have a valid and reliable instrument in the Chilean adolescent population. Therefore, considering this knowledge gap the aims of this research were the following: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) culturally adapt the SURPS questionnaire among early adolescents in Chile, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) assess the validity of the internal factor structure of the subscales contained in the questionnaire, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) assess the reliability of these subscales and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) assess the possible associations between the four personality traits from the SURPS and substance use.\u003c/p\u003e"},{"header":"MATERIAL AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eParticipants and procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study is embedded within a larger cluster randomized controlled trial (cRCT) evaluating the effectiveness of the \u003cem\u003eYo S\u0026eacute; Lo Que Quiero\u003c/em\u003e (Unplugged) school-based substance use prevention program in Chile (12). In the first step of this project, we conducted a cross-sectional study to validate the EU-DAP questionnaire (13) and the SURPS, which is presented here. The design and main procedures have been described in detail elsewhere (13).\u003c/p\u003e\n\u003cp\u003eParticipants were students in grades 5 to 8 (aged 10\u0026ndash;14 years) attending 13 mixed-sex schools in Santiago, Chile, representing low, medium, and high socioeconomic levels according to the Chilean Educational Quality Agency classification (14). All eligible students were invited to participate, and those who provided parental consent and student assent completed the study questionnaires\u003c/p\u003e\n\u003cp\u003eOf the selected schools, seven came from low socioeconomic levels with a total enrollment of 920 students from 5th to 8th grade, four came from middle socioeconomic levels with a total of 1,103 students, and two came from high socioeconomic levels with a total of 1,004 students. Therefore, a total of 3,027 students were eligible to participate and were invited. Of these, a total of 2,261 (74.7%) consented and responded to the questionnaire.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe European Drug Addiction Prevention Trial Questionnaire (EU-Dap)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe European Drug Addiction Prevention Trial Questionnaire (EU-Dap) was used to assess sociodemographic characteristics, substance use prevalence (tobacco, alcohol, and marijuana), and substance-related beliefs and refusal skills. The EU-Dap has demonstrated adequate reliability and validity in previous European (15) and Latin American studies (13, 16). Only the sections relevant to the present analyses were included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Substance Use Risk Profile Scale (SURPS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Substance Use Risk Profile Scale (SURPS) is a brief self-report questionnaire designed to assess four personality traits associated with substance use risk. Its development and psychometric properties have been previously described (9). It has a total of 23 items that are representative of four dimensions: Hopelessness (n of items = 7; which are the following 1, 4,7, 13, 17, 20 and 23), Anxiety Sensitivity (n of items = 5; which are the following 8, 10, 14,18, 21); Impulsivity (n of items 5: which are the following 2, 5, 11, 15, 22) and Sensation Seeking (n of items = 6, which are the following 3, 6, 9, 12, 16, 19). These items are expressed on a 4 point Likert scale (1 = \u003cem\u003estrongly disagree\u003c/em\u003e to 4 = strongly agree); and the items 1, 4,7, 13, 20 and 23 are reverse scored (9).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive analyses were conducted to characterize the sample. Means, standard deviations, and 95% confidence intervals were calculated for continuous variables, while categorical variables were summarized using frequencies and percentages.\u003c/p\u003e\n\u003cp\u003eThe internal structure of the Substance Use Risk Profile Scale (SURPS) was examined using factor analytic techniques appropriate for ordinal data. Polychoric correlation matrices were computed (17), and item distributions were evaluated using skewness and kurtosis coefficients. Exploratory factor analysis (EFA) was performed to examine the latent structure of the scale. The number of factors to retain was determined using Horn\u0026rsquo;s parallel analysis (18), which compares observed eigenvalues with those obtained from random data matrices. Sampling adequacy for factor analysis was assessed using the Kaiser\u0026ndash;Meyer\u0026ndash;Olkin (KMO) measure (19).\u003c/p\u003e\n\u003cp\u003eItem retention decisions were guided by factor loadings, with values \u0026ge; 0.40 considered acceptable (20). Items with loadings below this threshold were considered for removal based on both statistical criteria and theoretical coherence with the underlying construct.\u003c/p\u003e\n\u003cp\u003eConfirmatory factor analysis (CFA) was subsequently conducted to evaluate the fit of the final factor structure. Model fit was assessed using multiple complementary indices, including the root mean square error of approximation (RMSEA) (21, 22), standardized root mean square residual (SRMR) (22), comparative fit index (CFI) (22), normalized fit index (NFI)(23), goodness-of-fit index (GFI)(21), and adjusted goodness-of-fit index (AGFI) (21). Conventional cutoff criteria were applied to determine acceptable and good model fit.\u003c/p\u003e\n\u003cp\u003eInternal consistency reliability was evaluated using McDonald\u0026rsquo;s omega coefficient (24), which provides a robust estimate of scale reliability for multidimensional instruments, alongside Cronbach\u0026rsquo;s alpha for comparability with previous studies.\u003c/p\u003e\n\u003cp\u003eAssociations between SURPS personality traits and substance-use outcomes were examined using regression models. Lifetime prevalence of tobacco, alcohol, and marijuana use was analyzed as dichotomous outcomes using logistic regression models, reporting odds ratios (ORs) with 95% confidence intervals. Lifetime prevalence was selected due to the low frequency of recent use outcomes in this age group.\u003c/p\u003e\n\u003cp\u003eAssociations between SURPS subscales and continuous cognitive and behavioral correlates\u0026mdash;positive, negative, and normative beliefs about substance use, as well as refusal skills\u0026mdash;were examined using linear regression models, reporting standardized regression coefficients (\u0026beta;) with 95% confidence intervals. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eDescriptive analyses, exploratory factor analyses, reliability estimates, and regression models were conducted using Stata version 15. Confirmatory factor analyses were performed using R version 3.5.0 with the \u003cem\u003elavaan\u003c/em\u003e package.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll evaluation data were collected in accordance with the Declaration of Helsinki with the approval of the ethics committee of the Universidad de los Andes (CEC201734, August 7th, 2018). Participation in the study involved three stages: First, school authorities were informed about the study, and written confirmation was requested to participate. Then, the parents were sent a letter with the study information and with form requiring written and informed consent. Finally, the students were informed about the study and asked to sign an agreement confirming their participation. Confidentiality and the freedom to withdraw from it at any time were assured throughout the study. Anonymous codes were generated to protect the identities of the participants. The data were collected from August to December 2018 by research assistants who were trained by the study coordinator. During the application of the questionnaire, the research assistants explained the objectives of the study, clarified the doubts of the students, and then asked for their agreement.\u0026nbsp;\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003eSociodemographic characteristics of the sample\u003c/h2\u003e\n\u003cp\u003eA total of 2,261 students aged 10 to 14 years participated in the study. Slightly more than half of the participants were male (53.3% [95% CI: 51.3\u0026ndash;55.4]), while 46.7% [95% CI: 44.6\u0026ndash;48.7] were female (Table 1). Most of the students lived with their mother (94.0% [95% CI: 92.9\u0026ndash;94.9]), followed by those living with their father (69.6% [95% CI: 67.5\u0026ndash;71.5]) and siblings (87.3% [95% CI: 85.8\u0026ndash;88.6]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding socioeconomic background, 30.5% [95% CI: 28.7\u0026ndash;32.4] of students attended schools classified as low socioeconomic level, 37.3% [95% CI: 35.3\u0026ndash;39.3] as medium, and 32.2% [95% CI: 30.3\u0026ndash;34.2] as high. In terms of school administrative dependency, 38.9% [95% CI: 36.9\u0026ndash;40.9] attended public schools, 28.9% [95% CI: 27.1\u0026ndash;30.8] subsidized schools, and 32.2% [95% CI: 30.3\u0026ndash;34.2] private schools.\u003c/p\u003e\n\u003cp\u003eThe distribution of students by grade level was relatively balanced: 23.8% [95% CI: 22.1\u0026ndash;25.6] were in 5th grade, 27.2% [95% CI: 25.4\u0026ndash;29.1] in 6th grade, 24.9% [95% CI: 23.2\u0026ndash;26.8] in 7th grade, and 24.0% [95% CI: 22.3\u0026ndash;25.8] in 8th grade. The mean age increased as expected across grades, ranging from 10.7 years (SD = 0.65) in 5th grade to 13.8 years (SD = 0.74) in 8th grade. See Table 1.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 1\u003c/p\u003e\n\u003ch2\u003eSubstance use prevalence\u003c/h2\u003e\n\u003cp\u003eAs shown in Table 2,\u0026nbsp;tobacco use in the last month\u0026nbsp;was reported by\u0026nbsp;3.4%\u0026nbsp;of students,\u0026nbsp;6.3%\u0026nbsp;in the last year, and\u0026nbsp;11.2%for lifetime use.\u0026nbsp;Alcohol use\u0026nbsp;was higher, with\u0026nbsp;9.8%\u0026nbsp;in the last 30 days,\u0026nbsp;22.6%\u0026nbsp;in the last year, and\u0026nbsp;39.2%\u0026nbsp;lifetime prevalence.\u0026nbsp;Marijuana use\u0026nbsp;was\u0026nbsp;2.7%\u0026nbsp;in the last month,\u0026nbsp;4.5%\u0026nbsp;in the last year, and\u0026nbsp;7.2%\u0026nbsp;lifetime. Prevalence values were similar between males and females across all substances.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 2\u003c/p\u003e\n\u003ch2\u003eExploratory factor analysis\u003c/h2\u003e\n\u003cp\u003eTable 3 presents the results of the exploratory factor analysis (EFA) of the SURPS. Four factors were identified, consistent with the theoretical dimensions of Hopelessness, Anxiety Sensitivity, Impulsivity, and Sensation Seeking. Most items showed adequate factor loadings above the 0.40 cutoff, confirming the expected structure of the scale. Items within Hopelessness loaded between 0.62 and 0.89, Anxiety Sensitivity between 0.47 and 0.63, Impulsivity between 0.52 and 0.73, and Sensation Seeking between 0.38 and 0.66.\u003c/p\u003e\n\u003cp\u003eTwo items\u0026mdash;one from the Impulsivity subscale (item 22, loading = 0.32) and one from the Sensation Seeking subscale (item 6, loading = 0.38)\u0026mdash;showed factor loadings below the 0.40 threshold. Overall, the distribution of skewness and kurtosis values indicated acceptable normality for all items, supporting the adequacy of the data for factor extraction.\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHorn\u0026rsquo;s Parallel Analysis and explained variance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSuppl. 1, Table 1 shows the results of Horn\u0026rsquo;s Parallel Analysis, which supported the extraction of\u0026nbsp;four factors\u0026nbsp;with eigenvalues greater than 1.0 (5.55, 4.85, 1.81, and 1.12), confirming the theoretical four-factor structure of the SURPS. As shown in Suppl. 1, Table 2, these four factors together accounted for\u0026nbsp;52% of the total variance\u0026nbsp;after rotation, with the first factor explaining 22%, the second 11%, the third 10%, and the fourth 9%. These results further support the adequacy of a four-factor solution and its alignment with the original model proposed by Woicik et al. (2009). See Suppl. 1, Tables 1 and 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInternal consistency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 presents the internal reliability indices for the SURPS and its four subscales. The overall Kaiser\u0026ndash;Meyer\u0026ndash;Olkin (KMO) measure of sampling adequacy was 0.87, indicating good suitability for factor analysis. The total SURPS scale showed acceptable internal consistency (\u0026omega; = 0.75; \u0026alpha; = 0.80). Among the subscales, \u003cem\u003eHopelessness\u003c/em\u003e demonstrated excellent reliability (\u0026omega; = 0.89; \u0026alpha; = 0.88), while \u003cem\u003eImpulsivity\u003c/em\u003e (\u0026omega; = 0.76; \u0026alpha; = 0.75) and \u003cem\u003eSensation Seeking\u003c/em\u003e (\u0026omega; = 0.71; \u0026alpha; = 0.71) showed satisfactory values. The \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e subscale presented lower, though still acceptable, coefficients (\u0026omega; = 0.68; \u0026alpha; = 0.67).\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConfirmatory Factor Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 summarizes the fit indices for the four-factor structure of the SURPS. The overall model demonstrated acceptable fit (RMSEA = 0.09; SRMR = 0.08; NFI = 0.96; NNFI = 0.96; CFI = 0.96; GFI = 0.97; AGFI = 0.96). Each of the four subscales\u0026mdash;\u003cem\u003eHopelessness\u003c/em\u003e, \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e, \u003cem\u003eImpulsivity\u003c/em\u003e, and \u003cem\u003eSensation Seeking\u003c/em\u003e\u0026mdash;showed good to excellent model fit, with RMSEA values ranging from 0.01 to 0.03 and CFI, NFI, and NNFI all reaching or exceeding 0.99.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eINSERT TABLE 5.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociations with substance use and related beliefs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSuppl. 2, Tables 1 to 5 present the associations between the SURPS subscales and substance use, as well as positive, negative, and normative beliefs about substance use and refusal skills. Higher total SURPS scores were significantly associated with greater odds of lifetime tobacco, alcohol, and marijuana use (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). Among subscales, \u003cem\u003eHopelessness\u003c/em\u003e, \u003cem\u003eImpulsivity\u003c/em\u003e, and \u003cem\u003eSensation Seeking\u003c/em\u003e showed significant positive associations with all three substances, whereas \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e was not significantly related to any. Similarly, higher scores on \u003cem\u003eHopelessness\u003c/em\u003e and \u003cem\u003eImpulsivity\u003c/em\u003e were associated with stronger positive beliefs and weaker negative beliefs about substance use, while \u003cem\u003eSensation Seeking\u003c/em\u003e showed smaller but still significant effects. For normative beliefs, all subscales except \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e showed positive associations across substances. Finally, all dimensions, particularly \u003cem\u003eHopelessness\u003c/em\u003e and \u003cem\u003eImpulsivity\u003c/em\u003e, were negatively associated with refusal skills for tobacco, alcohol, and marijuana (all \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001). See Suppl. 2, Tables 1-5.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn the present study, we evaluated the psychometric properties of the SURPS in a Chilean adolescent sample and explored its associations with substance‐use behaviour, beliefs and refusal skills. Our results indicated that the four‐factor structure (Hopelessness, Anxiety Sensitivity, Impulsivity and Sensation Seeking) was upheld in Confirmatory Factor Analysis, and internal consistency for the overall scale and most subscales was acceptable. Moreover, higher scores on the total SURPS and on the Hopelessness, Impulsivity and Sensation Seeking subscales were significantly associated with greater odds of lifetime tobacco, alcohol and marijuana use. In addition, these subscales showed consistent associations with more favourable positive substance‐use beliefs, less negative beliefs, stronger normative beliefs favouring use, and weaker refusal skills for each of the substances assessed. In contrast, the Anxiety Sensitivity dimension demonstrated weaker and non‐significant associations with both substance‐use outcomes and related cognitive variables.\u003c/p\u003e\n\u003cp\u003eThe findings of this study are consistent with previous validations of the Substance Use Risk Profile Scale (SURPS) conducted in different cultural and age contexts. Similar to the original study by Woicik et al (4) and subsequent replications in the United Kingdom (25), Canada (26), and Mexico (11), the four-factor structure comprising \u003cem\u003eHopelessness\u003c/em\u003e, \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e, \u003cem\u003eImpulsivity\u003c/em\u003e, and \u003cem\u003eSensation Seeking\u003c/em\u003e was supported. Internal consistency indices were satisfactory for the total scale and for most subscales, with particularly high coefficients for \u003cem\u003eHopelessness\u003c/em\u003e, \u003cem\u003eImpulsivity\u003c/em\u003e, and \u003cem\u003eSensation Seeking\u003c/em\u003e. These dimensions also showed the strongest and most consistent associations with lifetime tobacco, alcohol, and marijuana use, while \u003cem\u003eAnxiety Sensitivity\u003c/em\u003e displayed weaker or non-significant relationships\u0026mdash;an observation repeatedly reported in earlier validations.\u003c/p\u003e\n\u003cp\u003eThe present findings further corroborate the dual-pathway model proposed in the literature, in which personality risk traits predispose adolescents to substance use through distinct mechanisms (26). The \u003cem\u003eHopelessness\u003c/em\u003e dimension is thought to represent an internalizing, negative-affect pathway, whereby individuals use substances as a form of self-medication to cope with depressive mood, perceived failure, or low self-worth. This interpretation is consistent with prior longitudinal studies linking hopelessness to depressive symptoms and subsequent alcohol or drug use in adolescents. In contrast, \u003cem\u003eImpulsivity\u003c/em\u003e and \u003cem\u003eSensation Seeking\u003c/em\u003e represent externalizing or reward-driven pathways characterized by heightened behavioural disinhibition, novelty-seeking, and sensitivity to positive reinforcement (25). The robust associations of these traits with substance use observed in our study align with extensive evidence showing that adolescents high in impulsivity or sensation seeking are more likely to initiate use earlier, experiment with multiple substances (27), and show stronger positive expectancies and weaker refusal skills (28).\u003c/p\u003e\n\u003cp\u003eIn addition, the pattern of associations with cognitive variables\u0026mdash;namely, more positive and normative beliefs about substance use, fewer negative beliefs, and lower refusal skills\u0026mdash;provides convergent validity for the Chilean adaptation. These findings suggest that personality risk traits influence both behavioural tendencies and cognitive appraisals related to substance use, reinforcing the theoretical coherence of the SURPS framework.\u003c/p\u003e\n\u003cp\u003eFrom a measurement standpoint, two items\u0026mdash;one from \u003cem\u003eImpulsivity\u003c/em\u003e (\u0026ldquo;I feel I have to be manipulative to get what I want\u0026rdquo;) and one from \u003cem\u003eSensation Seeking\u003c/em\u003e (\u0026ldquo;I enjoy new and exciting experiences even if they are unconventional\u0026rdquo;)\u0026mdash;displayed factor loadings below the 0.40 threshold and were removed from the final Confirmatory Factor Analysis. Similar findings have been reported in other adolescent adaptations of the SURPS (11, 25). Several explanations are possible. First, these items may have limited developmental relevance for younger adolescents, who may not fully identify with manipulative or overtly unconventional behaviours. Second, cultural norms in Chile, which emphasize social conformity, family cohesion, and interpersonal respect, may make endorsement of such behaviours less socially acceptable, reducing variability and leading to weaker factor saturation. Third, subtle differences in translation or contextual understanding could contribute to differential item functioning. The removal of these items improved model fit without compromising the conceptual integrity of the subscales, indicating that minor cultural and linguistic adjustments can enhance measurement precision while preserving theoretical validity.\u003c/p\u003e\n\u003cp\u003eOverall, the present results confirm both the cross-cultural robustness and contextual adaptability of the SURPS. The replication of its four-factor structure and the strong external validity of most subscales demonstrate that the instrument is a reliable tool for identifying personality risk pathways for substance use among Chilean adolescents. At the same time, the minor modifications made in this study highlight the importance of culturally sensitive adaptation and developmental calibration to maintain the construct validity of personality-based risk assessment tools across diverse populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral limitations should be acknowledged when interpreting these findings. First, the study employed a cross-sectional design, which does not allow for causal inference regarding the temporal sequence between personality risk traits and substance-use behaviours. Longitudinal evidence has shown that personality profiles assessed by the SURPS can predict later onset and escalation of substance use (25, 26), suggesting that future studies in Chile should incorporate follow-up assessments to establish predictive validity over time.\u003c/p\u003e\n\u003cp\u003eSecond, all variables were based on self-reported data, which may be affected by recall bias or social desirability effects. Previous research indicates that adolescents often underreport substance use in self-administered surveys compared to biological verification (29) or collateral reports (30). Despite these limitations, self-report remains the most feasible and widely used method for large-scale school-based studies, particularly when anonymity is guaranteed.\u003c/p\u003e\n\u003cp\u003eThird, although the sample was diverse in terms of school type and socioeconomic background, it was limited to a specific region of Chile. This may constrain generalizability to adolescents from other regions or cultural subgroups, as cross-national studies have shown that cultural norms (31, 32), religious affiliation (33), and socioeconomic factors (34, 35) can influence both personality expression and substance-use behaviours. Future research should include more geographically and culturally heterogeneous samples to enhance external validity.\u003c/p\u003e\n\u003cp\u003eFourth, two items\u0026mdash;one from \u003cem\u003eImpulsivity\u003c/em\u003e and one from \u003cem\u003eSensation Seeking\u003c/em\u003e\u0026mdash;were removed due to low factor loadings (\u0026lt; 0.40). Although this adjustment improved model fit, it may also indicate potential measurement bias or differential item functioning linked to cultural interpretation or developmental appropriateness. Similar challenges have been documented in other adolescent validations of the SURPS (11, 25). Cross-cultural adaptation processes should therefore continue to evaluate whether certain item contents or phrasing require modification to ensure conceptual equivalence.\u003c/p\u003e\n\u003cp\u003eFinally, while the study examined multiple cognitive and behavioural correlates of substance use, unmeasured confounders\u0026mdash;such as peer influence, family functioning, parental monitoring, or comorbid psychopathology\u0026mdash;may contribute to the observed associations. Prior studies have shown that these contextual factors interact with personality-based vulnerabilities to predict adolescent substance use and related outcomes (25, 36, 37). Future work integrating multilevel or longitudinal designs could help disentangle these complex relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present findings have several implications for research, prevention, and public health practice. The Chilean adaptation of the SURPS provides a psychometrically sound and culturally relevant instrument to identify distinct personality-based risk pathways for substance use in early adolescence. Such screening tools can inform the development of selective and indicated prevention programs that tailor intervention strategies to individual profiles, as demonstrated in prior international trials (38, 39). For example, interventions targeting \u003cem\u003eHopelessness\u003c/em\u003e have incorporated cognitive restructuring and emotional regulation components, while those addressing \u003cem\u003eImpulsivity\u003c/em\u003e and \u003cem\u003eSensation Seeking\u003c/em\u003e emphasize behavioural self-control, problem-solving, and alternative reinforcement activities (40). The current findings support the feasibility of applying this model in Latin American school settings, where personality-targeted prevention could complement universal education efforts and reduce the early onset of substance use. Moreover, the SURPS could serve as a screening and monitoring tool within national public health and school-based prevention frameworks, such as those coordinated by SENDA or the Ministry of Education, facilitating early identification of youth most at risk and enabling more cost-effective resource allocation. Finally, the study contributes to the growing cross-cultural validation literature on adolescent personality and substance use, highlighting the value of adapting theoretically grounded instruments to local contexts to enhance both scientific comparability and public health impact.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides robust evidence supporting the reliability, factorial validity, and external correlates of the Chilean adaptation of the Substance Use Risk Profile Scale (SURPS) among early adolescents. The replication of its four-factor structure and the consistent associations between personality traits and substance-use behaviors underscore the instrument\u0026rsquo;s conceptual soundness and practical utility. The SURPS emerges as a culturally appropriate, psychometrically valid tool for identifying personality-based risk pathways that can guide early, selective prevention strategies within Chilean schools and broader Latin American contexts. Continued research should further refine item content, assess predictive validity through longitudinal designs, and evaluate the effectiveness of personality-targeted interventions informed by these profiles.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the participating schools, students, and families for their valuable collaboration. We also acknowledge the support of the fieldwork team and data collectors from the Center for Student Mental Health at Universidad de los Andes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the National Research and Development Agency [ANID]; Unique ID: Fondecyt Regular 1181724.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe funding institution had no role in the study design, data collection, analysis, interpretation, or manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest relevant to this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki declaration and its later amendments. The study protocol was approved by the Ethics Committee of Universidad de los Andes (approval no. CEC201734, August 7th, 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed during the current study are not publicly available due to confidentiality agreements with participating schools but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.G. conceived and designed the study, supervised data collection, and wrote the first draft of the manuscript. S.R. contributed to data collection. M.I.G. conducted statistical analyses and contributed to data interpretation. All authors read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKohn R, Ali AA, Puac-Polanco V, Figueroa C, L\u0026oacute;pez-Soto V, Morgan K, et al. Mental health in the Americas: an overview of the treatment gap. Rev Panam Salud Publica. 2018;42:e165.\u003c/li\u003e\n\u003cli\u003eLebel C, Beaulieu C. Longitudinal development of human brain wiring continues from childhood into adulthood. J Neurosci. 2011;31(30):10937-47.\u003c/li\u003e\n\u003cli\u003eMeruelo AD, Castro N, Cota CI, Tapert SF. Cannabis and alcohol use, and the developing brain. Behav Brain Res. 2017;325(Pt A):44-50.\u003c/li\u003e\n\u003cli\u003eDegenhardt L, Stockings E, Patton G, Hall WD, Lynskey M. The increasing global health priority of substance use in young people. Lancet Psychiatry. 2016;3(3):251-64.\u003c/li\u003e\n\u003cli\u003ePatton GC, Sawyer SM, Santelli JS, Ross DA, Afifi R, Allen NB, et al. Our future: a Lancet commission on adolescent health and wellbeing. Lancet. 2016;387(10036):2423-78.\u003c/li\u003e\n\u003cli\u003eHarrop E, Catalano RF. Evidence-Based Prevention for Adolescent Substance Use. Child Adolesc Psychiatr Clin N Am. 2016;25(3):387-410.\u003c/li\u003e\n\u003cli\u003eGonz\u0026aacute;lvez MT, Espada JP, Guillon-Riquelme A, Secades R, Orgil\u0026eacute;s M. Association between personality traits and substance use in Spanish adolescents. Adicciones. 2016;28(2):108-15.\u003c/li\u003e\n\u003cli\u003eMemetovic J, Ratner PA, Gotay C, Richardson CG. Examining the relationship between personality and affect-related attributes and adolescents\u0026apos; intentions to try smoking using the Substance Use Risk Profile Scale. Addict Behav. 2016;56:36-40.\u003c/li\u003e\n\u003cli\u003eWoicik PA, Stewart SH, Pihl RO, Conrod PJ. The Substance Use Risk Profile Scale: a scale measuring traits linked to reinforcement-specific substance use profiles. Addict Behav. 2009;34(12):1042-55.\u003c/li\u003e\n\u003cli\u003eFern\u0026aacute;ndez-Calder\u0026oacute;n F, D\u0026iacute;az-Batanero C, Rojas-Tejada AJ, Castellanos-Ryan N, Lozano-Rojas \u0026Oacute; M. Adaptation to the Spanish population of the Substance Use Risk Profile Scale (SURPS) and psychometric properties. Adicciones. 2018;30(3):208-18.\u003c/li\u003e\n\u003cli\u003eRobles-Garc\u0026iacute;a R, Fres\u0026aacute;n A, Castellanos-Ryan N, Conrod P, G\u0026oacute;mez D, de Quevedo YDME, et al. Spanish version of the Substance Use Risk Profile Scale: factor structure, reliability, and validity in Mexican adolescents. Psychiatry Res. 2014;220(3):1113-7.\u003c/li\u003e\n\u003cli\u003eGaete J, Ram\u0026iacute;rez S, Gana S, Valenzuela D, Araya R. The Unplugged program in Chile (\u0026quot;Yo S\u0026eacute; Lo Que Quiero\u0026quot;) for substance use prevention among early adolescents: study protocol for a randomized controlled trial. Trials. 2022;23(1):76.\u003c/li\u003e\n\u003cli\u003eRam\u0026iacute;rez S, Gana S, Godoy MI, Valenzuela D, Araya R, Gaete J. Validation of the European Drug Addiction Prevention Trial Questionnaire (EU-Dap) for substance use screening and to assess risk and protective factors among early adolescents in Chile. PLOS ONE. 2021;16(10):e0258288.\u003c/li\u003e\n\u003cli\u003eAgencia de Calidad de la Educaci\u0026oacute;n. Metodolog\u0026iacute;a de construcci\u0026oacute;n de grupos socioecon\u0026oacute;micos pruebas SIMCE 2013 2013 [cited 2020 18 Jun]. Available from: http://archivos.agenciaeducacion.cl/Metodologia_de_Construccion_de_Grupos_Socioeconomicos_Simce_2013.pdf.\u003c/li\u003e\n\u003cli\u003eFaggiano F, Richardson C, Bohrn K, Galanti MR. A cluster randomized controlled trial of school-based prevention of tobacco, alcohol and drug use: the EU-Dap design and study population. Prev Med. 2007;44(2):170-3.\u003c/li\u003e\n\u003cli\u003ePrado MC, Schneider DR, Sa\u0026ntilde;udo A, Pereira AP, Horr JF, Sanchez ZM. Transcultural Adaptation of Questionnaire to Evaluate Drug Use Among Students: The Use of the EU-Dap European Questionnaire in Brazil. Subst Use Misuse. 2016;51(4):449-58.\u003c/li\u003e\n\u003cli\u003eHolgado\u0026ndash;Tello FP, Chac\u0026oacute;n\u0026ndash;Moscoso S, Barbero\u0026ndash;Garc\u0026iacute;a I, Vila\u0026ndash;Abad E. Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables. Quality \u0026amp; Quantity. 2010;44(1):153.\u003c/li\u003e\n\u003cli\u003eHorn JL. A RATIONALE AND TEST FOR THE NUMBER OF FACTORS IN FACTOR ANALYSIS. Psychometrika. 1965;30:179-85.\u003c/li\u003e\n\u003cli\u003eCerny BA, Kaiser HF. A Study Of A Measure Of Sampling Adequacy For Factor-Analytic Correlation Matrices. Multivariate Behav Res. 1977;12(1):43-7.\u003c/li\u003e\n\u003cli\u003eLloret-Segura S, Ferreres-Traver A, Hernandez-Baeza A, Tomas-Marco I. Exploratory item factor analysis: A practical guide revised and updated. Anales de Psicolog\u0026iacute;a. 2014;30(3):1151-69.\u003c/li\u003e\n\u003cli\u003eMacCallum RC, Hong S. Power Analysis in Covariance Structure Modeling Using GFI and AGFI. Multivariate Behav Res. 1997;32(2):193-210.\u003c/li\u003e\n\u003cli\u003eHarrington D. Confirmatory factor analysis: Oxford university press; 2009.\u003c/li\u003e\n\u003cli\u003eHu Lt, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal. 1999;6(1):1-55.\u003c/li\u003e\n\u003cli\u003eMcDonald R. Test Theory New York: Psychology Press; 2013 [cited 2020 18 Jun].\u003c/li\u003e\n\u003cli\u003eKrank M, Stewart SH, O\u0026apos;Connor R, Woicik PB, Wall AM, Conrod PJ. Structural, concurrent, and predictive validity of the Substance Use Risk Profile Scale in early adolescence. Addict Behav. 2011;36(1-2):37-46.\u003c/li\u003e\n\u003cli\u003eCastellanos-Ryan N, O\u0026apos;Leary-Barrett M, Sully L, Conrod P. Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the Substance Use Risk Profile Scale. Alcohol Clin Exp Res. 2013;37 Suppl 1:E281-90.\u003c/li\u003e\n\u003cli\u003eMalmberg M, Kleinjan M, Overbeek G, Vermulst AA, Lammers J, Engels RCME. Are there reciprocal relationships between substance use risk personality profiles and alcohol or tobacco use in early adolescence? Addictive Behaviors. 2013;38(12):2851-9.\u003c/li\u003e\n\u003cli\u003eLeeman RF, Hoff RA, Krishnan-Sarin S, Patock-Peckham JA, Potenza MN. Impulsivity, sensation-seeking, and part-time job status in relation to substance use and gambling in adolescents. Journal of Adolescent Health. 2014;54(4):460-6.\u003c/li\u003e\n\u003cli\u003eDelaney-Black V, Chiodo, L. M., Hannigan, J. H., Greenwald, M. K., Janisse, J., Patterson, G., Huestis, M. A., Ager, J., \u0026amp; Sokol, R. J. Just say \u0026quot;I don\u0026apos;t\u0026quot;: lack of concordance between teen report and biological measures of drug use. Pediatrics 2010;126(5):887-93.\u003c/li\u003e\n\u003cli\u003eJones JD, Scott JC, Calkins ME, Ruparel K, Moore TM, Gur RC, et al. Correspondence between adolescent and informant reports of substance use: Findings from the Philadelphia Neurodevelopmental Cohort. Addictive Behaviors. 2017;65:13-8.\u003c/li\u003e\n\u003cli\u003eGirard R, Trinh CD, Schick MR, Spillane NS. The protective role of culture and family disapproval on substance use among American Indian adolescents. American Journal of Drug and Alcohol Abuse. 2025.\u003c/li\u003e\n\u003cli\u003eNasim A, Fernander A, Townsend TG, Corona R, Belgrave FZ. Cultural protective factors for community risks and substance use among rural african american adolescents. Journal of Ethnicity in Substance Abuse. 2011;10(4):316-36.\u003c/li\u003e\n\u003cli\u003eHaber JR, Jacob T. Alcoholism risk moderation by a socio-religious dimension. Journal of Studies on Alcohol and Drugs. 2007;68(6):912-22.\u003c/li\u003e\n\u003cli\u003eKuzman M, Pejnović-Franelić I, editors. Adolescents\u0026apos; substance abuse experimentation. Paediatria Croatica, Supplement; 2010.\u003c/li\u003e\n\u003cli\u003eLink TC. Adolescent substance use in Germany and the United States: A cross-cultural test of the applicability and generalizability of theoretical indicators. European Journal of Criminology. 2008;5(4):453-80.\u003c/li\u003e\n\u003cli\u003eEdalati H, Doucet C, Conrod PJ. A Developmental Social Neuroscience Model for Understanding Pathways to Substance Use Disorders During Adolescence. Seminars in Pediatric Neurology. 2018;27:35-41.\u003c/li\u003e\n\u003cli\u003eEscamilla I, Juan N, Benito A, Castellano-Garc\u0026iacute;a F, Rodr\u0026iacute;guez-Ruiz F, Haro G. Substance Addiction in Adolescents: Influence of Parenting and Personality Traits. Brain Sciences. 2024;14(5).\u003c/li\u003e\n\u003cli\u003eConrod PJ, O\u0026apos;Leary-Barrett M, Newton N, Topper L, Castellanos-Ryan N, Mackie C, et al. Effectiveness of a selective, personality-targeted prevention program for adolescent alcohol use and misuse: a cluster randomized controlled trial. JAMA Psychiatry. 2013;70(3):334-42.\u003c/li\u003e\n\u003cli\u003eCastellanos-Ryan N, Conrod PJ. Personality correlates of the common and unique variance across conduct disorder and substance misuse symptoms in adolescence. J Abnorm Child Psychol. 2011;39(4):563-76.\u003c/li\u003e\n\u003cli\u003eConrod PJ, Castellanos-Ryan N, Mackie C. Long-term effects of a personality-targeted intervention to reduce alcohol use in adolescents. J Consult Clin Psychol. 2011;79(3):296-306.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Sociodemographic features of the sample.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e% or Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[95% CI] or (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e1055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e46.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[44.6-48.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e1206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e53.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[51.3-55.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eFamily Structure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eLives with father\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e1416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e69.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[67.5-71.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eLives with mother\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e2049\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e94.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[92.9-94.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eLives with siblings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e1831\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e87.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[85.8-88.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eSocioeconomic Level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[30.3-34.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e37.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[35.3-39.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e30.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[28.7-32.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eType of School dependency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e32.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[30.3-34.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eSubsidized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e28.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[27.1-30.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003ePublic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e879\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e38.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[36.9-40.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eClass grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[22.1-25.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e27.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[25.4-29.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[23.2-26.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e543\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e24.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e[22.3-25.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.7308%;\"\u003e\n \u003cp\u003eAge by Class grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e(0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e11.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e(0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e562\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e(0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 41.7308%;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12.8846%;\"\u003e\n \u003cp\u003e536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18.0769%;\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.3077%;\"\u003e\n \u003cp\u003e(0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: n = number of participants; CI = Confidence Interval; SD = Standard Deviation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 2: Substance use prevalence.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 147px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 139px;\"\u003e\n \u003cp\u003eFemales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 150px;\"\u003e\n \u003cp\u003eMales\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTobacco use in the last month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003eGrade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e% [95% CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e% [95% CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003en\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e% [95% CI]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.3 [0.6-2.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.6 [0.6-4.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.1 [0.3-3.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.4 [3.0-6.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.5 [2.6-7.6]]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.3 [2.6-7.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.8 [1.8-4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.1 [1.5-6.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.6 [1.3-5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.7 [3.2-6.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.9 [3.5-9.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.8 [2.1-6.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e3.4 [2.7-4.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.7 [2.7-5.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.0 [2.2-4.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTobacco use in the last year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.3 [1.3-3.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.9 [0.8-4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.5 [1.2-5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.4 [3.1-6.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.2 [1.6-6.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.6 [3.5-8.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.4 [3.8-7.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.0 [2.9-8.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.6 [3.5-8.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e13.7 [11.0-16.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e17.9 [13.6-23.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.1 [7.1-14.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e6.3 [5.4-7.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e6.7 [5.4-8.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e6.0 [4.8-7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eLifetime tobacco use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.3 [3.7-7.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.5 [3.3-9.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.1 [3.0-8.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e7.5 [5.7-9.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.2 [3.2-8.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e9.5 [6.8-13.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e10.7 [8.4-13.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e11.2 [7.9-15.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.3 [7.3-14.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e21.7 [18.4-25.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e27.1 [21.8-33.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e17.3 [13.4-22.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e11.2 [9.9-12.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e11.8 [10.0-13.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.6 [9.0-12.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAlcohol use in the last 30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.1 [2.7-6.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.5 [1.8-6.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.7 [2.7-7.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.1 [3.6-7.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.5 [2.6-7.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.5 [3.5-8.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e11.1 [8.7-14.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e9.7 [6.6-13.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e12.3 [9.1-16.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e19.8 [16.7-23.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e21.8 [17.0-27.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e18.3 [14.2-23.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e9.8 [8.7-11.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e9.5 [7.9-11.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.2 [8.6-12.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eAlcohol use in the last year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e12.0 [9.5-15.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.5 [7.3-14.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e13.4 [9.8-17.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e12.4 [10.0-15.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e10.5 [7.4-14.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e14.2 [10.8-18.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e26.6 [23.1-30.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e24.4 [19.5-30.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e28.5 [23.7-33.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e41.1 [36.9-45.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e45.0 [38.7-51.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e37.8 [32.4-43.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e22.6 [20.9-24.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e21.8 [19.4-24.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e23.3 [21.0-25.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eLifetime alcohol use\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e25.7 [22.1-29.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e22.7 [18.0-28.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e28.4 [23.3-34.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e32.2 [28.6-36.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e27.3 [22.4-32.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e36.6 [31.5-42.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e45.6 [41.5-49.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e41.4 [35.5-47.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e49.3 [43.7-55.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e54.3 [50.0-58.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e59.0 [52.6-65.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e143\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e50.4 [44.5-56.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e873\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e39.2 [37.2-41.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e37.0 [34.1-40.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e488\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e41.2 [38.4-44.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eMarijuana use in the last 30 days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.7 [0.9-3.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.6 [0.6-4.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.8 [0.8-4.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.0 [1.1-3.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.4 [0.5-3.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.5 [1.2-4.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.2 [1.2-3.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.2 [0.4-3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.0 [1.6-5.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.1 [3.5-7.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.9 [3.5-9.7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.5 [2.6-7.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.7 [2.1-3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.4 [1.6-3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.0 [2.1-4.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eMarijuana use in the last year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.9 [1.0-3.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.0 [0.8-4.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.9 [0.8-4.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e3.4 [2.3-5.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e2.4 [1.2-5.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.3 [2.6-7.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.8 [3.3-7.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.9 [2.1-7.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e5.7 [3.6-9.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e7.8 [5.8-10.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e8.8 [5.8-13.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e6.9 [4.5-10.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e4.5 [3.7-5.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.1 [3.1-5.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e4.8 [3.7-6.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eLifetime marijuana use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e5\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.7 [1.6-4.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e1.6 [0.6-4.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.7 [2.0-6.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e6\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e5.7 [4.2-7.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e3.5 [1.9-6.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e7.8 [5.3-11.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e7\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e7.6 [5.6-10.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e7.3 [4.7-11.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e7.8 [5.2-11.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e8\u003csup\u003eth\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e13.0 [10.4-16.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e15.4 [11.4-20.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e11.1 [7.9-15.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 181px;\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 40px;\"\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e7.2 [6.2-8.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 43px;\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e6.7 [5.4-8.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e7.7 [6.3-9.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: n = number of participants; CI = Confidence Interval.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Table 3: Exploratory Factor Analysis of SURPS.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"888\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003eNr \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eDimensions and corresponding items \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003eSkewness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eKurtosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003eFactor Loading\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHopelessness\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI am content\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI am happy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e4.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI have faith that my future holds great promise\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI feel proud of my accomplishments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI feel that I\u0026apos;m a failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI feel pleasant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI am very enthusiastic about my future\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnxiety Sensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eIt\u0026apos;s frightening to feel dizzy or faint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eIt frightens me when I feel my heart beat change\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI get scared when I\u0026apos;m too nervous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI get scared when I experience unusual body sensations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eIt scares me when I\u0026apos;m unable to focus on a task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eImpulsivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI often don\u0026apos;t think things through before I speak\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI often involve myself in situations that I later regret being involved in\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI usually act without stopping to think\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eGenerally, I am an impulsive person\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI feel I have to be manipulative to get what I want\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.32\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensation Seeking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI would like to sky dive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI enjoy new and exciting experiences even if they are unconventional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI like doing things that frighten me a little\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI would like to learn how to drive a motorcycle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI am interested in experience for its own sake, even if it is illegal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 475px;\"\u003e\n \u003cp\u003eI would enjoy hiking long distances in wild and uninhabited territory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: Nr = number of corresponding item; SD = Standard Deviation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4: Internal reliability\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eNumber of Factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003eNumber of Items\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eKMO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003eOmega\u003c/p\u003e\n \u003cp\u003eReliability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003eCronbach\u0026rsquo;s alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eSURPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eHopelessness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eAnxiety Sensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eImpulsivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eSensation Seeking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: KMO = Kaiser-Meyer-\u003c/p\u003e\u003cp\u003eTable 5: Confirmatory Factor Analysis indicators\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eIndicator\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eSURPS\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eHopelessness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003eAnxiety Sensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003eImpulsivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003eSensation Seeking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eGood fit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003eAcceptable fit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026le;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026le;0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eSRMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026le;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026le;0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026ge;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026ge;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0,96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026ge;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026ge;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026ge;0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026ge;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026gt;0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eAGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 89px;\"\u003e\n \u003cp\u003e\u0026gt;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: RMSEA = Root Mean Square Error of Approximation; SRMR = Standardized Root Mean Square Residual; NFI = Normalized Fit Index; NNFI = Normalized Fit Index; CFI = Comparative Adjustment Index; GFI = Goodness of Fit Index; AGFI = Adjusted Goodness of Fit Index.\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Personality traits, Substance use, Adolescents, Psychometrics","lastPublishedDoi":"10.21203/rs.3.rs-8663600/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8663600/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003ePersonality traits are key predictors of adolescent substance use. This study aimed to culturally adapt and validate the Substance Use Risk Profile Scale (SURPS) among Chilean adolescents and examine its associations with substance use and related beliefs.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted with 2,261 students aged 10\u0026ndash;14 years from 13 schools in Santiago, Chile. Participants completed the SURPS and the EU-Dap questionnaire on substance use. Exploratory and confirmatory factor analyses evaluated internal structure and reliability, and logistic and linear regressions examined associations between personality traits, substance use, and beliefs.\u003c/p\u003e\u003ch2\u003eResults.\u003c/h2\u003e \u003cp\u003eThe four-factor structure\u0026mdash;Hopelessness, Anxiety Sensitivity, Impulsivity, and Sensation Seeking\u0026mdash;was confirmed after removing two items with low loadings (\u0026lt;\u0026thinsp;0.40). Internal consistency was acceptable for the total scale (α\u0026thinsp;=\u0026thinsp;0.80) and subscales (α\u0026thinsp;=\u0026thinsp;0.67\u0026ndash;0.88). Higher Hopelessness, Impulsivity, and Sensation Seeking were associated with lifetime tobacco, alcohol, and marijuana use (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), stronger positive and normative beliefs, and weaker refusal skills. Anxiety Sensitivity showed no significant associations.\u003c/p\u003e\u003ch2\u003eConclusions.\u003c/h2\u003e \u003cp\u003eThe Chilean SURPS demonstrated good reliability and validity, supporting its use as a brief, culturally appropriate tool for identifying personality-based risk pathways and informing selective prevention strategies in adolescent populations.\u003c/p\u003e","manuscriptTitle":"Validation of the Substance Use Risk Profile Scale (SURPS) and associated factors among adolescents in Chile","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-23 16:24:56","doi":"10.21203/rs.3.rs-8663600/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-16T05:00:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-06T14:05:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T21:45:19+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-27T05:23:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"60999417657098092375209543619841072180","date":"2026-02-26T10:49:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"237674297822107753638115170542770566131","date":"2026-02-18T19:45:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290866704309552893074527872871370311844","date":"2026-02-18T02:53:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"255825669199342810192899434094811114210","date":"2026-02-17T12:45:28+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-17T11:50:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-16T14:05:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-28T04:55:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-27T17:21:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-01-27T17:13:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b03fd9e-88d4-46c2-9fe2-84716aea6361","owner":[],"postedDate":"February 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T05:09:57+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-23 16:24:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8663600","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8663600","identity":"rs-8663600","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}