Online Sexual Risk Behaviors in Adolescents: Roles of Attention-Deficit/Hyperactivity Disorder, Parenting Styles, and Reinforcement Sensitivity

Online Sexual Risk Behaviors in Adolescents: Roles of Attention-Deficit/Hyperactivity Disorder, Parenting Styles, and Reinforcement Sensitivity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Online Sexual Risk Behaviors in Adolescents: Roles of Attention-Deficit/Hyperactivity Disorder, Parenting Styles, and Reinforcement Sensitivity Wen-Jiun Chou, Cheng-Fang Yen, Ray C. Hsiao, Tai-Ling Liu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4965386/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background This study examined the associations of a diagnosis of attention-deficit/hyperactivity disorder (ADHD), the tendencies of behavioral inhibition and activation, and parenting styles with experiences of passive and active online sexual risk behaviors. Methods This study invited 176 adolescents with ADHD and 173 adolescents without ADHD and their parents to participate. The parents rated their parenting styles on the Parental Bonding Instrument. The adolescents self-reported their lifelong experiences of passive and active online sexual risk behaviors and their tendencies of behavioral inhibition and activation on the Behavior Inhibition System (BIS) and Behavior Approach System (BAS) Scales. The associations of the diagnosis of ADHD, parenting styles, and BIS and BAS constructs with online sexual risk behaviors were examined usingmultivariable logistic regression analysis. Results In total, 114 (32.7%) participants reported any passive form of online sexual risk behaviors, and 49 (14.0%) participants reported any active online sexual risk behaviors. Older age ( p = 0.007) and the fun-seeking construct of the BAS ( p = 0.037) were significantly associated with passive online sexual risk behaviors. Being male ( p = 0.011), older age ( p < 0.001), and the fun-seeking construct of the BAS ( p = 0.031) were significantly associated with active online sexual risk behaviors. The significant association between the fun-seeking seeking construct of the BAS and active online sexual risk behaviors was present in boys only. Conclusion High proportions of adolescents have experiences of online sexual risk behaviors. The factors related to online sexual risk behaviors should be considered in the development of intervention programs. Online risk behavior sex attention-deficit/hyperactivity disorder parenting style behavioral inhibition behavioral activation Background The proportion of adolescents using the Internet has increased. Through Internet use, adolescents can gain and be exposed to new ideas and knowledge, obtain social contact and support, and access health promotion messages and information [ 1 ]. However, the use of the Internet also has negative effects on individuals in terms of its impact on sleep, attention, and learning as well as its association with the increased incidence of obesity and mental health problems [ 1 , 2 ]. Online sexual risk behaviors are one of the common forms of online risk behaviors among adolescents [ 3 ]. Common online sexual risk behaviors include unwanted online sexual exposure, sexting, and exposure to pornography. Unwanted online sexual exposure is defined as being induced by others to talk about sex or share sexual personal information online or involuntarily engage in sexual behaviors [ 4 , 5 ]. A meta-analysis discovered that 20.3% of adolescents had experiences of unwanted sexual exposure online, and that 11.5% had faced unwanted sexual advances online [ 6 ]. Unwanted online sexual exposure can cause distress among adolescents, especially among younger adolescents and those induced to make offline contact [ 4 ]. Sexting is the electronic transmission of nude or semi-nude images as well as sexually explicit text messages [ 7 ]. Estimates indicate that approximately 12% of adolescents aged 10 to 19 years have ever sent a sexual photo to someone [ 8 ]. Studies have found that individuals who send or receive sexual messages often have comorbid internalizing problematic behaviors, addictive substance use, and impulsive behavior [ 9 – 11 ]. Young people who engage in sexting are more likely to consume addictive substances prior to sexual intercourse, have multiple sexual partners, and be involved in criminal activities [ 12 – 15 ]. Exposure to pornography and sexually explicit websites is also common among adolescents [ 16 ]. A meta-analysis revealed that young people who have accessed sexually explicit websites are more likely to engage in condomless sex [ 13 ]. Regular pornography watchers have a higher likelihood of exhibiting coercively sexual behaviors and engaging in sexual abuse [ 13 ]. A follow-up study revealed that adolescents exposed to online sexually explicit videos are 6.5 times more likely to engage in sexual harassment and assault over the next 36 months than are those who have not been exposed to such videos [ 17 ]. Adolescents with intensive exposure to online sexually explicit videos are also more likely to have social maladjustment and lower levels of social integration [ 18 ]. Previous studies have supported the importance of implementing interventions for reducing the risk of involvement in online sexual risk behaviors among adolescents. The factors related to online sexual risk behaviors should be identified, and these factors should be incorporated into the development of intervention programs. Certain demographic characteristics (e.g., older age and being female), behaviors regarding Internet use (e.g., regular Internet use, using Internet chat rooms, and interacting with strangers online), and having behavioral problems or experiencing adjustment difficulties in real life correlate with adolescents experiencing unwanted online sexual exposure [ 4 , 5 ]. According to ecological system theory [ 19 ], individual and environmental factors contribute to the occurrence of online sexual risk behaviors among adolescents. Regarding individual factors, studies have found that children and adolescents with a diagnosis of attention-deficit/hyperactivity disorder (ADHD) are more likely to be involved in sexual risk behaviors such as having early sexual intercourse, multiple sexual partners, and sex outside of regular relationships as well as developing sexually transmitted diseases than are those without ADHD [ 20 – 22 ]. ADHD is also a risk factor for the occurrence of problematic Internet use in adolescents [ 23 ]. However, one study examined sexting in adolescents with ADHD and found a similar likelihood of sexting between adolescents with ADHD and the general population [ 24 ]. On the basis of the aforementioned results, the current study proposed the following hypothesis: H1 Adolescents with ADHD are more likely to exhibit online sexual risk behaviors than are those without ADHD. The neuropsychological traits of reinforcement sensitivity, which are influenced by the behavioral activation system (BAS) and behavioral inhibition system (BIS), have been reported to increase the likelihood of engagement in risky behaviors such as Internet gambling [ 25 ], substance use [ 26 , 27 ], self-harm [ 28 ], and Internet addiction [ 29 , 30 ]. The reward responsiveness construct of the BAS involves the processes that control individuals’ tendency to experience positive emotions in response to rewards; the drive construct of the BAS involves individuals’ tendency to actively pursue goals; and the fun-seeking construct of the BAS involves individuals’ tendency to seek and impulsively engage in potentially rewarding activities [ 31 ]. The BIS is also involved in individuals’ expectations of feeling anxiety when confronted with cues for punishment [ 31 ]. The BIS and BAS was reported to be associated with sexual addiction [ 32 ]. On the basis of the aforementioned observations, the present study proposed the following hypotheses: H2a High BAS-reward-responsiveness, -drive, and -fun-seeking are positively correlated with online sexual risk behaviors. H2b High BIS is negatively correlated with online sexual risk behaviors. Parenting styles significantly affect the behavior of adolescents. A review revealed that adolescents raised in authoritative households consistently demonstrate more protective behaviors and fewer risk behaviors than adolescents from nonauthoritative households do [ 33 ]. Additionally, a meta-analysis revealed that positive parenting styles were significantly negatively related to problematic Internet use in adolescents [ 34 ]. A study found a significant association between parenting styles and premarital sexual debut in adolescents [ 35 ]. Considering the aforementioned findings, the present study proposed the following hypotheses: H3a Care/affection and authoritative parenting styles are negatively correlated with online sexual risk behaviors. H3b Overprotective parenting styles are positively correlated with online sexual risk behaviors. This cross-sectional survey study examined the associations of a diagnosis of ADHD, the tendencies of behavioral inhibition and activation, and parenting styles (i.e., care/affection, overprotection, and authoritarianism) with experiences of passive and active online sexual risk behaviors in adolescents. Methods Participants and procedures The study participants were adolescents with ADHD and typically developing (TD) adolescents without ADHD. This study enrolled adolescents with ADHD from six child psychiatry outpatient clinics of two hospitals in Taiwan. The inclusion criteria for adolescents with ADHD were as follows: (1) age 11–18 years and (2) having received a diagnosis of ADHD by a certified child psychiatrist in accordance with the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition ( DSM-5) [ 36 ]. Three child psychiatrists reviewed the medical records of adolescents with ADHD who visited the outpatient clinics between September 2022 and July 2023. Subsequently, at the outpatient clinics, we consecutively approached 190 adolescents with ADHD who met the inclusion criteria. The child psychiatrists interviewed the adolescents and their parents (or guardians) to determine whether they met any of the following exclusion criteria: having intellectual disability, autism spectrum disorder, major depressive disorder, bipolar disorder, schizophrenia, or any other cognitive deficit that could impede their understanding of the study purposes and completion of the research questionnaire. On the basis of the results of the interviews, 14 adolescents with ADHD were excluded because they had comorbid autism spectrum disorder ( n = 8), intellectual disability ( n = 5), or major depressive disorder ( n = 1). The child psychiatrists explained the study purposes and procedures to the remaining adolescents and invited them to participate in the study. They were assured that their responses would remain confidential, and that their participation or nonparticipation would not influence their right to receive medical services. All 176 adolescents with ADHD agreed to participate in the study. TD adolescents (without ADHD) were recruited through online advertising. The inclusion criteria for TD adolescents were as follows: (1) age 11–18 years and (2) no diagnosis of ADHD, ASD, intellectual disability, autism spectrum disorder, major depressive disorder, bipolar disorder, schizophrenia, or any other cognitive deficit that could impede their understanding of the study purposes and completion of the research questionnaire. Child psychiatrists interviewed the adolescents and their parents (or guardians) to confirm that the adolescents were eligible for inclusion. Finally, 173 TD adolescents agreed to participate in the present study. Both the adolescents and their parents provided written informed consent prior to the commencement of assessments. The protocol of the present study was approved by the Institutional Review Boards of Kaohsiung Medical University Hospital (KMUHIRB-SV(I)-20200091) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (202101964A3C502). Measures Passive and active types of online sexual risk behaviors In this study, we assessed the participants’ lifetime experiences with seven passive types and four active types of online sexual risk behaviors. Seven items were adopted from previous studies to assess the participants’ passive types of online sexual risk behaviors [ 16 , 24 , 37 ], including being invited to talk about sex-related topics, being pressured to share private personal sex information, being invited to engage in sexual behaviors, receiving messages containing sexual content, receiving pictures or videos with sexual connotations, receiving semi-nude or fully nude pictures or videos, and viewing sexually explicit information or video content inadvertently. Moreover, four items were adopted from the previous studies to assess the participants’ active types of online sexual risk behaviors [ 16 , 24 ], including sending messages with sexual content to others, sending pictures or videos with sexual connotations to others, sending semi-nude or fully nude pictures or videos to others, and searching for sexually explicit information or watching pornography. Participants who answered “yes” to the items were considered to have passive or active types of online sexual risk behaviors. Reinforcement sensitivity The Chinese versions of the BIS and BAS Scales contain 20 items evaluated on a 4-point Likert scale; these scales assess participants’ self-reported sensitivity to BIS and the fun-seeking, drive reward, and responsiveness constructs of the BAS [ 31 , 38 – 40 ]. A higher total score on the subscales of the BIS and BAS Scales indicates a higher level of reinforcement sensitivity. The Chinese versions of the BIS and BAS Scales have been demonstrated to have high criterion and construct validity in the Taiwanese population [ 39 , 40 ]. In the present study, the Cronbach’s α of the four subscales ranged from 0.68 to 0.83. Parental Bonding Instrument The 25-item Chinese version of the Parental Bonding Instrument (PBI) is used to assess three parenting styles, including care/affection, overprotection, and authoritarianism, as perceived by adolescents [ 41 ]. Each item is rated on a 4-point Likert scale. A high score on the care/affection subscale indicates that adolescents perceive affection and warmth from their parents, whereas a low score indicates that adolescents perceive rejection or indifference from their parents. Overprotection indicates overprotective parenting and denial of adolescents’ psychological autonomy, whereas authoritarianism reflects the degree of authoritarian-quality parental control parents have over adolescents’ behaviors [ 42 ]. The reliability and validity of the Chinese version of the PBI were previously demonstrated [ 43 ]. In the present study, the Cronbach’s α values of the parent-reported care/affection, overprotection, and authoritarianism subscales were 0.78, 0.70, and 0.68, respectively. Data analysis Statistical analyses were performed using IBM SPSS Statistics, version 24.0 (IBM Corporation, Armonk, NY, USA). Chi-square and t tests were used to compare the demographics, parental styles on the PBI, reinforcement sensitivity on the BIS/BAS Scale, and passive and active types of online sexual risk behaviors of the adolescents with ADHD and TD adolescents. To assess whether the continuous variables examined in this study were normally distributed, absolute values of < 7 and < 3 for kurtosis and skewness, respectively, were applied as criteria [ 44 ]. The results did not reveal any significant deviation. The associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and tendencies of behavioral inhibition and activation with experiences of passive and active types of online sexual risk behaviors were examined using multivariate logistic regression analysis. Following the method of Baron and Kenny [ 45 ], we examined the moderating effects of demographics on the aforementioned associations. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). A p value of < 0.05 was considered to indicate significance. Results Table 1 presents the results of comparisons of the demographic characteristics, parental styles, and reinforcement sensitivity between the ADHD and non-ADHD groups. The score for the care/affection parenting style was higher in the non-ADHD group than in the ADHD group ( p < 0.001). The scores for the overprotective parenting style ( p = 0.003) and authoritarianism controlling parenting style ( p = 0.006) were higher in the ADHD group than in the non-ADHD group. The scores for the reward responsiveness subscale of the BAS were higher in the non-ADHD group than in the ADHD group ( p = 0.022), whereas no significant differences were observed in the scores for the BIS Scale and the drive and fun-seeking subscales of the BAS Scale between the ADHD and non-ADHD groups ( p > 0.05). Table 1 Demographics, parental styles, and reinforcement sensitivity (N = 349) Total ( n = 349) Non-ADHD ( n = 173) ADHD ( n = 176) t or χ 2 p Age (years), mean (SD) 13.7 (2.1) 13.7 (2.1) 13.7 (2.1) -0.149 0.881 Sex, n (%) Girls 64 (18.3) 32 (18.5) 32 (18.2) 0.006 0.939 Boys 285 (81.7) 141 (81.5) 144 (81.8) Parental styles on the PBI, mean (SD) Care/affection 38.9 (4.9) 40.2 (4.5) 37.7 (5.0) 4.824 < 0 .001 Overprotection 22.1 (3.1) 21.6 (3.0) 22.6 (3.1) -2.991 0.003 Authoritarianism controlling 11.2 (3.0) 10.7 (2.9) 11.6 (3.0) -2.790 0.006 Reinforcement sensitivity subscale of the BIS/BAS, mean (SD) BIS 14.2 (2.7) 14.0 (2.4) 14.3 (3.0) -1.013 0.312 Reward responsiveness subscale of the BAS 16.7 (2.6) 17.0 (2.1) 16.4 (3.0) 2.300 0.022 Drive subscale of the BAS 12.1 (2.3) 12.3 (2.2) 12.0 (2.4) 1.164 0.245 Fun seeking subscale of the BAS 10.8 (2.3) 10.8 (2.2) 10.8 (2.3) 0.013 0.990 ADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; PBI: Parental Bonding Instrument. [Table 1 inserted here] Table 2 provides the proportions of participants with experiences of online sexual risk behaviors and the results of a comparison of the online sexual risk behaviors between the ADHD and non-ADHD groups. In total, 114 (32.7%) participants reported any passive type of online sexual risk behavior, and 49 (14.0%) reported any active type of online sexual risk behavior. No significant differences were observed in the passive or active types of online sexual risk behaviors between the ADHD and non-ADHD groups ( p > 0.05). Table 2 Passive and active types of online sexual risk behaviors (N = 349) Total (n = 349) n (%) Non-ADHD (n = 173) n (%) ADHD (n = 176) n (%) χ 2 p Passive types of behaviors, n (%) Being invited to talk about sex-related topics 25 (7.2) 13 (7.5) 12 (6.8) 0.064 0.801 Being pressured to share private personal sex information 11 (3.2) 3 (1.7) 8 (4.5) 2.259 0.133 Being invited to engage in sexual behaviors 3 (0.9) 0 3 (1.7) -- 0.248 a Receiving messages containing sexual content 39 (11.2) 19 (11.0) 20 (11.4) 0.013 0.910 Receiving pictures or videos with sexual connotations 30 (8.6) 13 (7.5) 17 (9.7) 0.511 0.475 Receiving semi-nude or fully nude pictures or videos 20 (5.7) 10 (5.8) 10 (5.7) 0.002 0.968 Inadvertently viewing sexually explicit information or videos 85 (24.4) 44 (25.4) 41 (23.3) 0.216 0.642 Any 114 (32.7) 57 (32.9) 57 (32.4) 0.013 0.911 Active types of behaviors, n (%) Sending messages with sexual content to others 16 (4.6) 7 (4.0) 9 (5.1) 0.227 0.634 Sending pictures or videos with sexual connotations to others 6 (1.7) 2 (1.2) 4 (2.3) -- 0.685 a Sending semi-nude or fully nude pictures or videos to others 5 (1.4) 1 (0.6) 4 (2.3) -- 0.371 Searching for sexually explicit information or watching sex videos 40 (11.5) 21 (12.1) 19 (10.8) 0.155 0.694 Any 49 (14.0) 25 (14.5) 24 (13.6) 0.048 0.827 a : Fisher’s exact test [Table 2 inserted here] Table 3 lists the results of the examination of the associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and BIS and BAS constructs with the occurrence of passive types of online sexual risk behaviors among adolescents. The results for Model I indicated that older age was significantly associated with the occurrence of passive online sexual risk behaviors ( p = 0.007), whereas sex, diagnosis of ADHD, and parenting styles were not significantly associated with the occurrence of passive online sexual risk behaviors ( p > 0.05). The findings for Model II revealed that in addition to older age ( p = 0.007), the fun-seeking construct of the BAS was significantly associated with experiences of passive online sexual risk behaviors ( p = 0.037), whereas sex, diagnosis of ADHD, the BIS construct, and the reward responsiveness and drive constructs of the BAS were not significantly associated with experiences of passive online sexual risk behaviors ( p > 0.05). The interaction between age and the fun-seeking construct of the BAS was further included in Model III, and the results revealed that the interaction was not significantly associated with the occurrence of passive online sexual risk behaviors ( p > 0.05). Table 3 Multivariate logistic regression analysis of associations of ADHD, parenting styles, and behavioral inhibition and activation with passive online sexual risk behaviors Variables Passive online sexual risk behaviors Model I Model II Model IIII OR (95% CI) p OR (95% CI) p OR (95% CI) p Sex a 1.761 (0.926–3.349) 0.085 1.783 (0.929–3.422) 0.082 1.814 (0.943–3.491) 0.074 Age 1.170 (1.045–1.310) 0.007 1.170 (1.050–1.304) 0.005 0.805 (0.464–1.395) 0.439 ADHD 0.992 (0.612–1.609) 0.975 0.924 (0.580–1.473) 0.740 0.924 (0.579–1.475) 0.741 Affection/care parenting 1.019 (0.970–1.070) 0.454 -- -- -- -- Overprotection parenting 1.015 (0.939–1.098) 0.700 -- -- -- -- Authoritarian controlling parenting 1.002 (0.924–1.087) 0.962 -- -- -- -- BIS -- -- 1.084 (0.989–1.188) 0.086 1.089 (0.993–1.195) 0.071 BAS Reward responsiveness -- -- 0.988 (0.885–1.103) 0.826 0.988 (0.886–1.103) 0.835 BAS Drive -- -- 0.954 (0.851–1.070) 0.423 0.954 (0.851–1.069) 0.418 BAS Fun seeking -- -- 1.124 (1.007–1.255) 0.037 0.702 (0.353–1.394) 0.312 Age x BAS Fun seeking -- -- -- -- 1.035 (0.985–1.087) 0.175 a : girls as the reference ADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; CI: confidence interval; OR: odds ratio. [Table 3 inserted here] Table 4 provides the results of examination of the associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and BIS and BAS constructs with experiences of active types of online sexual risk behaviors among adolescents. The results for Model IV indicated that boys were more likely to demonstrate active types of online sexual risk behaviors than girls were ( p = 0.011). Older age was significantly associated with the occurrence of active online sexual risk behaviors ( p 0.05). The results for Model V revealed that in addition to sex ( p = 0.012) and older age ( p < 0.001), the fun-seeking construct of the BAS was significantly associated with experiences of active online sexual risk behaviors ( p = 0.031), whereas the diagnosis of ADHD, BIS constructs, and reward responsiveness and drive constructs of the BAS were not significantly associated with experiences of active online sexual risk behaviors ( p > 0.05). The interactions of sex and age with the fun-seeking construct of the BAS were further included in Model VI. The interaction between sex and the fun-seeking construct of the BAS was significantly associated with experiences of active online sexual risk behaviors ( p = 0.017). The significant association between the fun-seeking construct of the BAS and experiences of active online sexual risk behaviors was present for boys ( p = 0.008) but not for girls ( p > 0.05). Table 4 Multivariate logistic regression analysis of associations of ADHD, parenting styles, and behavioral inhibition and activation with active online sexual risk behaviors Variables Active online sexual risk behaviors Model IV Model V Model VI OR (95% CI) p OR (95% CI) p OR (95% CI) p Sex a 6.726 (1.547–29.238) 0.011 6.711 (1.525–29.527) 0.012 0.000 (0.000–0.216) 0.022 Age 1.418 (1.208–1.664) < 0.001 1.449 (1.241–1.691) < 0.001 2.451 (1.053–5.702) 0.037 ADHD 0.890 (0.453–1.747) 0.734 0.876 (0.455–1.686) 0.692 0.891 (0.459–1.727) 0.731 Affection/care parenting 1.016 (0.949–1.088) 0.655 -- -- -- -- Overprotection parenting 1.058 (.946–1.184) 0.321 -- -- -- -- Authoritarian controlling parenting 0.987 (0.880–1.107) 0.827 -- -- -- -- BIS -- -- 1.045 (0.921–1.186) 0.490 1.043 (0.919–1.184) 0.511 BAS Reward responsiveness -- -- 0.960 (0.824–1.118) 0.598 0.972 (0.834–1.133) 0.715 BAS Drive -- -- 0.920 (0.786–1.076) 0.297 0.916 (0.782–1.073) .279 BAS Fun seeking -- -- 1.185 (1.016–1.381) 0.031 0.597 (0.167–2.138) 0.428 Sex x BAS Fun seeking -- -- -- -- 3.969 (1.275–12.361) 0.017 Age x BAS Fun seeking -- -- -- -- 0.956 (0.891–1.027) 0.222 a : girls as the reference ADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; CI: confidence interval; OR: odds ratio. [Table 4 inserted here] Discussion The present study found that 32.7% of adolescents had experiences of passive online sexual risk behaviors and that 14.0% had experiences of active online sexual risk behaviors. Thus, high proportions of adolescents had experiences of online sexual risk behaviors. Because online sexual risk behaviors lead to mental health problems and other risk behaviors, health professionals should regularly assess online sexual risk behaviors among adolescents, and they should promote an understanding of the disadvantages of online sexual risk behaviors among adolescents and implement prevention strategies for the behaviors. The present study found that the fun-seeking construct of the BAS was significantly associated with the occurrence of both passive and active online sexual risk behaviors. Moreover, the significant association between the fun-seeking construct of the BAS and the occurrence of active online sexual risk behaviors was present for boys but not for girls. The fun-seeking construct of the BAS represents the tendency to seek stimuli and responses to proximal rewards [ 46 ]. Given that Internet use exposes individuals to various modes of stimulation and the receipt of rapid rewards, individuals with high BAS-fun-seeking are more likely to develop problematic Internet use [ 29 ]. A high Internet usage rate can increase the risk of exposure to unwanted online sexual invitation, sexting, and pornography among adolescents. Further, exploring sexual identity is one of the key developmental processes that occurs during adolescence [ 47 ]. Adolescents with high BAS-fun-seeking may actively search for sex-related materials and may interact with others online to satisfy their curiosity about sex. Subsequently, the risk of active online sexual risk behaviors increases among these adolescents. The results of the present study highlight the need for assessing adolescents’ BAS-fun-seeking tendency and developing a corresponding intervention for reducing the risk of online sexual risk behaviors among adolescents. The present study did not find significant associations of the drive and reward responsiveness constructs of the BAS and BIS construct with experiences of online sexual risk behaviors. The results of our study indicate that the associations of the BAS and BIS constructs with the occurrence of online sexual risk behaviors are complex, and further examination of the associations is warranted. Given that sexual risk behaviors and problematic Internet use are more likely to occur among individuals with ADHD [ 20 – 23 ], researchers have hypothesized that adolescents with ADHD are more likely to demonstrate online sexual risk behaviors. However, the present study did not find significant differences in the risk of online sexual risk behaviors between adolescents with and without ADHD. The present findings indicate that interventions should be implemented for reducing the risk of online sexual risk behaviors among adolescents in the general population. Parenting styles considerably affect parent–child interactions. For example, adolescents who experience the care/affection parenting style may be less resistant to discussing their online experiences with their parents, and they may accept their parents monitoring their Internet use. In the authoritative parenting style, parents can establish norms for managing their children’s Internet use. However, adolescents who have experienced overprotective parenting may lack the ability to make independent judgments when confronted with various messages on the Internet. Although the present study did not identify significant associations between parenting styles and online sexual risk behaviors among adolescents, parents have the crucial responsibility of educating their children regarding the negative impact of Internet use and regulating the time and content of their children’s Internet use. Thus, parents should learn essential parenting skills to help reduce the risk of their children’s involvement in online sexual risk behaviors. The present study has several limitations. First, we recruited adolescents with ADHD from outpatient clinics who were currently receiving pharmacological or psychological therapies. Adolescents without ADHD were recruited through an online advertisement. This difference in recruitment methods between the ADHD and non-ADHD groups could have introduced sampling bias into our research results. Whether the results of the present study can be generalized to adolescents with ADHD who do not visit outpatient clinics for medical help and adolescents who are not recruited through online advertisements should be further investigated. Second, given the cross-sectional design of the present study, the temporal associations of online sexual risk behaviors with other variables could not be determined. Third, participants’ self-reported data were collected in this study; therefore, single-rater and recall biases could not be fully controlled for in the analysis. To address this limitation, future studies should examine potential social desirability bias. In addition, obtaining information from multiple sources may confirm the accuracy of the present study data. Conclusion The present study results indicate that high proportions of adolescents have experiences of online sexual risk behaviors. Health professionals should regularly assess online sexual risk behaviors among adolescents, and they should promote an understanding of the disadvantages of online sexual risk behaviors among adolescents and should implement prevention strategies for these behaviors. The fun-seeking construct of the BAS was significantly associated with experiences of both passive and active online sexual risk behaviors. Health professionals should assess adolescents’ BAS-fun-seeking tendency and develop a corresponding intervention for reducing the risk of online sexual risk behaviors. Declarations Author contributions TLL Conceptualization, funding acquisition, investigation, and writing the original draft. WJC and RCH: Reviewing and editing the original draft. CFY: Designing the study, analyzing data, and writing the original draft. All authors contributed to the article and approved the submitted version. Funding This study was supported by grants from the Ministry of Science and Technology, Taiwan (MOST 111-2635-B-182A-004 and 112-2314-B-182A-030). Data availability Individual participant data that underlie the results reported in this article, after deidentifcation, will be made available to researchers who provide a methodologically sound proposal. Declarations Ethics approval and consent to participate The Institutional Review Boards of Kaohsiung Medical University (KMUHIRB-SV(I)-20200091) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (202101964A3C502) approved this study. The study procedures were conducted in adherence to the tenets of the Declaration of Helsinki. All participants provided written informed consent. Consent for publication All authors consent to the publication of this article. Competing interest The authors have no conflicts of interest relevant to this article. 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Sexting by high school students: An exploratory and descriptive study. Arch Sex Behav. 2013;42(1):15–21. Temple JR, Choi H. Longitudinal association between teen sexting and sexual behavior. Pediatrics. 2014;134(5):e1287–e1292. Stanley N, Barter C, Wood M, Aghtaie N, Larkins C, Lanau A, et al. Pornography, sexual coercion and abuse and sSexting in young people's intimate relationships: A European study. J Interpers Violence. 2018;33(19):2919–2944. Ybarra ML, Mitchell KJ, Hamburger M, Diener-West M, Leaf PJ. X-rated material and perpetration of sexually aggressive behavior among children and adolescents: is there a link? Aggress Behav. 2011;37(1):1–18. Mesch GS. Social bonds and internet pornographic exposure among adolescents. J Adolesc. 2009;32(3):601–618. Bronfenbrenner U. Developmental research, public policy, and the ecology of childhood. Child Dev. 1974;45 (1):1–5. Barkley RA, Fischer M, Smallish L, Fletcher K. Young adult outcome of hyperactive children: adaptive functioning in major life activities. J Am Acad Child Adolesc Psychiatry. 2006; 45(2):192–202. Flory K, Molina BS, Pelham WE Jr, Gnagy E, Smith B. Childhood ADHD predicts risky sexual behavior in young adulthood. J Clin Child Adolesc Psychol. 2006; 35(4):571–577. Sarver DE, McCart MR, Sheidow AJ, Letourneau EJ. ADHD and risky sexual behavior in adolescents: conduct problems and substance use as mediators of risk. J Child Psychol Psychiatry. 2014;55(12):1345–1353. Ko CH, Yen JY, Chen CS, Yeh YC, Yen CF. Predictive values of psychiatric symptoms for internet addiction in adolescents: a 2-year prospective study. Arch Pediatr Adolesc Med. 2009;163(10):937–943. Dawson AE, Wymbs BT, Evans SW, DuPaul GJ. Exploring how adolescents with ADHD use and interact with technology. J Adolesc. 2019;71:119–137. Rho MJ, Lee H, Lee TH, Cho H, Jung DJ, Kim DJ, et al. Risk factors for Internet gaming disorder: Psychological factors and Internet gaming characteristics. J Environ Res Public Health. 2017;15(1):40. Baumann MR, Oviatt D, Garza RT, Gonzalez-Blanks AG, Lopez SG, Alexander-Delpech P, et al. Variation in BAS-BIS profiles across categories of cigarette use. Addict Behav. 2014;39(10):1477–1483. Rieser NM, Shaul L, Blankers M, Koeter MWJ, Schippers GM, Goudriaan AE. The predictive value of impulsivity and risk-taking measures for substance use in substance dependent offenders. Front Behav Neurosci. 2019; 13:192. Ammerman BA, Kleiman EM, Jenkins AL, Berman ME, McCloskey MS. Using propensity scores to examine the association between behavioral inhibition/activation and nonsuicidal and suicidal self-injury. Crisis. 2017;38(4):227–236. Lu W-H, Chou W-J, Hsiao RC, Hu H-F and Yen C-F. Correlations of Internet addiction severity with reinforcement sensitivity and frustration intolerance in adolescents with attention-deficit/hyperactivity disorder: The moderating effect of medications. Front Psychiatry. 2019;10:268. Yen JY, Yen CF, Chen CS, Chang YH, Yeh YC, Ko CH. The bidirectional interactions between addiction, behaviour approach and behaviour inhibition systems among adolescents in a prospective study. Psychiatry Res. 2012;200:588–592. Gray JA. The neuropsychology of temperament. In: Strelau J, Angleitner A (eds) Explorations in temperament: international perspectives on theory and measurement. Plenum Press, New York, NY, 1991; pp. 105–128. Levi G, Cohen C, Kaliche S, Sharaabi S, Cohen K, Tzur-Bitan D, et al. Sexual addiction, compulsivity, and impulsivity among a predominantly female sample of adults who use the internet for sex. J Behav Addict. 2020;9(1):83–92. Newman K, Harrison L, Dashiff C, Davies S. Relationships between parenting styles and risk behaviors in adolescent health: an integrative literature review. Rev Lat Am Enfermagem. 2008;16(1):142–150. Niu X, Li JY, King DL, Rost DH, Wang HZ, Wang JL. The relationship between parenting styles and adolescent problematic Internet use: A three-level meta-analysis. J Behav Addict. 2023;12(3):652–669. Shongwe MC, Chung MH, Chien LY, Chang PC. Does parenting style moderate the relationship between parent-youth sexual risk communication and premarital sexual debut among in-school youth in Eswatini? PLoS One. 2021;16(1):e0245590. American Psychiatric Association. Diagnostic and statistical manual of mental disorders, 5th ed. Arlington American Psychiatric Association, Washington, DC, USA; 2013. Dönmez YE, Soylu N. The relationship between online sexual solicitation and Internet addiction in adolescents. J Child Sex Abuse. 2020; 29(8):911–923. Carver CS, White TL. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: The BIS/BAS Scales. J Pers Soc Psychol. 1994;67:319–333. Chen CH, Ko HC, Lu RB. Behavioral inhibition and activation systems: Male alcoholic patients with and without anxiety disorders. Taiwanese J Psychiatry (Taipei). 2005;19:119–127. Chou WJ, Liu TL, Yang P, Yen CF, Hu HF. Multi-dimensional correlates of Internet addiction symptoms in adolescents with attention-deficit/hyperactivity disorder. Psychiatry Res. 2015;225:122–128. Parker G. The Parental Bonding Instrument. A decade of research. Soc Psychiatry Psychiatr Epidemiol. 1990;25:281–282. Cox BJ, Enns MW, Clara IP. The Parental Bonding Instrument: confirmatory evidence for a three-factor model in a psychiatric clinical sample and in the National Comorbidity Survey. Soc Psychiatry Psychiatr Epidemiol. 2000;35:353–357. Gau SS, Shen HY, Chou MC, Tang CS, Chiu YN, Gau CS. Determinants of adherence to methylphenidate and the impact of poor adherence on maternal and family measures. J Child Adolesc Psychopharmacol. 2006;16:286–297. Lin CY, Luh WM, Cheng CP, Yang AL, Su CT, Ma HI. Measurement equivalence across child self-reports and parent-proxy reports in the Chinese version of the Pediatric Quality of Life Inventory Version 4.0. Child Psychiatry Hum Dev. 2013;44:583–590. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical consideration. J Pers Soc Psychol. 1986;51:1173–1182. Corr PJ. Reinforcement sensitivity theory (RST): Introduction. In: Corr PJ (ed) The reinforcement sensitivity theory of personality. Cambridge University Press, New York, NY. 2008; pp 1–43. Gemelli RJ. Normal child and adolescent development. American Psychiatric Publication Inc, Washington DC, USA; 1996. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4965386","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":355257349,"identity":"68669439-2486-4473-ab34-cfe3a5ef1abb","order_by":0,"name":"Wen-Jiun Chou","email":"","orcid":"","institution":"Chang Gung Memorial Hospital, Kaohsiung Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Wen-Jiun","middleName":"","lastName":"Chou","suffix":""},{"id":355257350,"identity":"bfcaf2a6-6879-40f2-b771-00824783477b","order_by":1,"name":"Cheng-Fang Yen","email":"","orcid":"","institution":"Kaohsiung Medical University Hospital, Kaohsiung Medical University","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Fang","middleName":"","lastName":"Yen","suffix":""},{"id":355257351,"identity":"3d113246-b05a-4ab8-bebe-944bc160e5b7","order_by":2,"name":"Ray C. Hsiao","email":"","orcid":"","institution":"University of Washington School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Ray","middleName":"C.","lastName":"Hsiao","suffix":""},{"id":355257352,"identity":"a23e9c64-58ab-49c3-9b41-7e9873b381ea","order_by":3,"name":"Tai-Ling Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYDCCA4zNDz4Y/KvnB3ESCojT0mY4o+BAgmQDSIsBUVoYGKR5PhxIMDgA4hGjhe/44QYDHoM7ecbnVyd+eGDAIM8vdgC/FskziQ0PJAyeFZvdeLtZAugww5mzE/BrMTiQ2GBgYMDMuO3G2Q0gLQkGtwlpOf+wAaiSmXHzjLObfxCn5UZig8QBg8OJG/h7txFni+SNh22GDQZpxhI3eLdZJBhIEPYL3/n0x4///LGR4+8/u/nmjwobeX5pAloQQAKsUoJY5SDAf4AU1aNgFIyCUTCSAACdyE6LJCpo5QAAAABJRU5ErkJggg==","orcid":"","institution":"Kaohsiung Medical University Hospital, Kaohsiung Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tai-Ling","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-08-23 15:57:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4965386/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4965386/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66303828,"identity":"d5bfe860-5bfa-4020-8c3a-0bf7a8a318ee","added_by":"auto","created_at":"2024-10-10 06:55:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":766565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4965386/v1/8e7981f4-2103-4824-9af6-903eb3f54535.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Online Sexual Risk Behaviors in Adolescents: Roles of Attention-Deficit/Hyperactivity Disorder, Parenting Styles, and Reinforcement Sensitivity","fulltext":[{"header":"Background","content":"\u003cp\u003eThe proportion of adolescents using the Internet has increased. Through Internet use, adolescents can gain and be exposed to new ideas and knowledge, obtain social contact and support, and access health promotion messages and information [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, the use of the Internet also has negative effects on individuals in terms of its impact on sleep, attention, and learning as well as its association with the increased incidence of obesity and mental health problems [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOnline sexual risk behaviors are one of the common forms of online risk behaviors among adolescents [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Common online sexual risk behaviors include unwanted online sexual exposure, sexting, and exposure to pornography. Unwanted online sexual exposure is defined as being induced by others to talk about sex or share sexual personal information online or involuntarily engage in sexual behaviors [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. A meta-analysis discovered that 20.3% of adolescents had experiences of unwanted sexual exposure online, and that 11.5% had faced unwanted sexual advances online [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Unwanted online sexual exposure can cause distress among adolescents, especially among younger adolescents and those induced to make offline contact [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSexting is the electronic transmission of nude or semi-nude images as well as sexually explicit text messages [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Estimates indicate that approximately 12% of adolescents aged 10 to 19 years have ever sent a sexual photo to someone [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Studies have found that individuals who send or receive sexual messages often have comorbid internalizing problematic behaviors, addictive substance use, and impulsive behavior [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Young people who engage in sexting are more likely to consume addictive substances prior to sexual intercourse, have multiple sexual partners, and be involved in criminal activities [\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExposure to pornography and sexually explicit websites is also common among adolescents [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A meta-analysis revealed that young people who have accessed sexually explicit websites are more likely to engage in condomless sex [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Regular pornography watchers have a higher likelihood of exhibiting coercively sexual behaviors and engaging in sexual abuse [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A follow-up study revealed that adolescents exposed to online sexually explicit videos are 6.5 times more likely to engage in sexual harassment and assault over the next 36 months than are those who have not been exposed to such videos [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Adolescents with intensive exposure to online sexually explicit videos are also more likely to have social maladjustment and lower levels of social integration [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Previous studies have supported the importance of implementing interventions for reducing the risk of involvement in online sexual risk behaviors among adolescents.\u003c/p\u003e \u003cp\u003eThe factors related to online sexual risk behaviors should be identified, and these factors should be incorporated into the development of intervention programs. Certain demographic characteristics (e.g., older age and being female), behaviors regarding Internet use (e.g., regular Internet use, using Internet chat rooms, and interacting with strangers online), and having behavioral problems or experiencing adjustment difficulties in real life correlate with adolescents experiencing unwanted online sexual exposure [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. According to ecological system theory [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], individual and environmental factors contribute to the occurrence of online sexual risk behaviors among adolescents. Regarding individual factors, studies have found that children and adolescents with a diagnosis of attention-deficit/hyperactivity disorder (ADHD) are more likely to be involved in sexual risk behaviors such as having early sexual intercourse, multiple sexual partners, and sex outside of regular relationships as well as developing sexually transmitted diseases than are those without ADHD [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. ADHD is also a risk factor for the occurrence of problematic Internet use in adolescents [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, one study examined sexting in adolescents with ADHD and found a similar likelihood of sexting between adolescents with ADHD and the general population [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. On the basis of the aforementioned results, the current study proposed the following hypothesis:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH1\u003c/b\u003e Adolescents with ADHD are more likely to exhibit online sexual risk behaviors than are those without ADHD.\u003c/p\u003e \u003cp\u003eThe neuropsychological traits of reinforcement sensitivity, which are influenced by the behavioral activation system (BAS) and behavioral inhibition system (BIS), have been reported to increase the likelihood of engagement in risky behaviors such as Internet gambling [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], substance use [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], self-harm [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and Internet addiction [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The reward responsiveness construct of the BAS involves the processes that control individuals\u0026rsquo; tendency to experience positive emotions in response to rewards; the drive construct of the BAS involves individuals\u0026rsquo; tendency to actively pursue goals; and the fun-seeking construct of the BAS involves individuals\u0026rsquo; tendency to seek and impulsively engage in potentially rewarding activities [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The BIS is also involved in individuals\u0026rsquo; expectations of feeling anxiety when confronted with cues for punishment [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The BIS and BAS was reported to be associated with sexual addiction [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. On the basis of the aforementioned observations, the present study proposed the following hypotheses:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2a\u003c/b\u003e High BAS-reward-responsiveness, -drive, and -fun-seeking are positively correlated with online sexual risk behaviors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH2b\u003c/b\u003e High BIS is negatively correlated with online sexual risk behaviors.\u003c/p\u003e \u003cp\u003eParenting styles significantly affect the behavior of adolescents. A review revealed that adolescents raised in authoritative households consistently demonstrate more protective behaviors and fewer risk behaviors than adolescents from nonauthoritative households do [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Additionally, a meta-analysis revealed that positive parenting styles were significantly negatively related to problematic Internet use in adolescents [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. A study found a significant association between parenting styles and premarital sexual debut in adolescents [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Considering the aforementioned findings, the present study proposed the following hypotheses:\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3a\u003c/b\u003e Care/affection and authoritative parenting styles are negatively correlated with online sexual risk behaviors.\u003c/p\u003e \u003cp\u003e \u003cb\u003eH3b\u003c/b\u003e Overprotective parenting styles are positively correlated with online sexual risk behaviors.\u003c/p\u003e \u003cp\u003eThis cross-sectional survey study examined the associations of a diagnosis of ADHD, the tendencies of behavioral inhibition and activation, and parenting styles (i.e., care/affection, overprotection, and authoritarianism) with experiences of passive and active online sexual risk behaviors in adolescents.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and procedures\u003c/h2\u003e \u003cp\u003eThe study participants were adolescents with ADHD and typically developing (TD) adolescents without ADHD. This study enrolled adolescents with ADHD from six child psychiatry outpatient clinics of two hospitals in Taiwan. The inclusion criteria for adolescents with ADHD were as follows: (1) age 11\u0026ndash;18 years and (2) having received a diagnosis of ADHD by a certified child psychiatrist in accordance with the \u003cem\u003eDiagnostic and Statistical Manual of Mental Disorders, Fifth Edition\u003c/em\u003e (\u003cem\u003eDSM-5)\u003c/em\u003e [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Three child psychiatrists reviewed the medical records of adolescents with ADHD who visited the outpatient clinics between September 2022 and July 2023. Subsequently, at the outpatient clinics, we consecutively approached 190 adolescents with ADHD who met the inclusion criteria. The child psychiatrists interviewed the adolescents and their parents (or guardians) to determine whether they met any of the following exclusion criteria: having intellectual disability, autism spectrum disorder, major depressive disorder, bipolar disorder, schizophrenia, or any other cognitive deficit that could impede their understanding of the study purposes and completion of the research questionnaire. On the basis of the results of the interviews, 14 adolescents with ADHD were excluded because they had comorbid autism spectrum disorder (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8), intellectual disability (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5), or major depressive disorder (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1). The child psychiatrists explained the study purposes and procedures to the remaining adolescents and invited them to participate in the study. They were assured that their responses would remain confidential, and that their participation or nonparticipation would not influence their right to receive medical services. All 176 adolescents with ADHD agreed to participate in the study.\u003c/p\u003e \u003cp\u003eTD adolescents (without ADHD) were recruited through online advertising. The inclusion criteria for TD adolescents were as follows: (1) age 11\u0026ndash;18 years and (2) no diagnosis of ADHD, ASD, intellectual disability, autism spectrum disorder, major depressive disorder, bipolar disorder, schizophrenia, or any other cognitive deficit that could impede their understanding of the study purposes and completion of the research questionnaire. Child psychiatrists interviewed the adolescents and their parents (or guardians) to confirm that the adolescents were eligible for inclusion. Finally, 173 TD adolescents agreed to participate in the present study. Both the adolescents and their parents provided written informed consent prior to the commencement of assessments. The protocol of the present study was approved by the Institutional Review Boards of Kaohsiung Medical University Hospital (KMUHIRB-SV(I)-20200091) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (202101964A3C502).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eMeasures\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003ePassive and active types of online sexual risk behaviors\u003c/h2\u003e \u003cp\u003eIn this study, we assessed the participants\u0026rsquo; lifetime experiences with seven passive types and four active types of online sexual risk behaviors. Seven items were adopted from previous studies to assess the participants\u0026rsquo; passive types of online sexual risk behaviors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], including being invited to talk about sex-related topics, being pressured to share private personal sex information, being invited to engage in sexual behaviors, receiving messages containing sexual content, receiving pictures or videos with sexual connotations, receiving semi-nude or fully nude pictures or videos, and viewing sexually explicit information or video content inadvertently. Moreover, four items were adopted from the previous studies to assess the participants\u0026rsquo; active types of online sexual risk behaviors [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], including sending messages with sexual content to others, sending pictures or videos with sexual connotations to others, sending semi-nude or fully nude pictures or videos to others, and searching for sexually explicit information or watching pornography. Participants who answered \u0026ldquo;yes\u0026rdquo; to the items were considered to have passive or active types of online sexual risk behaviors.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eReinforcement sensitivity\u003c/h2\u003e \u003cp\u003eThe Chinese versions of the BIS and BAS Scales contain 20 items evaluated on a 4-point Likert scale; these scales assess participants\u0026rsquo; self-reported sensitivity to BIS and the fun-seeking, drive reward, and responsiveness constructs of the BAS [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. A higher total score on the subscales of the BIS and BAS Scales indicates a higher level of reinforcement sensitivity. The Chinese versions of the BIS and BAS Scales have been demonstrated to have high criterion and construct validity in the Taiwanese population [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In the present study, the Cronbach\u0026rsquo;s α of the four subscales ranged from 0.68 to 0.83.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eParental Bonding Instrument\u003c/h2\u003e \u003cp\u003eThe 25-item Chinese version of the Parental Bonding Instrument (PBI) is used to assess three parenting styles, including care/affection, overprotection, and authoritarianism, as perceived by adolescents [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Each item is rated on a 4-point Likert scale. A high score on the care/affection subscale indicates that adolescents perceive affection and warmth from their parents, whereas a low score indicates that adolescents perceive rejection or indifference from their parents. Overprotection indicates overprotective parenting and denial of adolescents\u0026rsquo; psychological autonomy, whereas authoritarianism reflects the degree of authoritarian-quality parental control parents have over adolescents\u0026rsquo; behaviors [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The reliability and validity of the Chinese version of the PBI were previously demonstrated [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. In the present study, the Cronbach\u0026rsquo;s α values of the parent-reported care/affection, overprotection, and authoritarianism subscales were 0.78, 0.70, and 0.68, respectively.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using IBM SPSS Statistics, version 24.0 (IBM Corporation, Armonk, NY, USA). Chi-square and \u003cem\u003et\u003c/em\u003e tests were used to compare the demographics, parental styles on the PBI, reinforcement sensitivity on the BIS/BAS Scale, and passive and active types of online sexual risk behaviors of the adolescents with ADHD and TD adolescents. To assess whether the continuous variables examined in this study were normally distributed, absolute values of \u0026lt;\u0026thinsp;7 and \u0026lt;\u0026thinsp;3 for kurtosis and skewness, respectively, were applied as criteria [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The results did not reveal any significant deviation. The associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and tendencies of behavioral inhibition and activation with experiences of passive and active types of online sexual risk behaviors were examined using multivariate logistic regression analysis. Following the method of Baron and Kenny [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], we examined the moderating effects of demographics on the aforementioned associations. The results are presented as odds ratios (ORs) and 95% confidence intervals (CIs). A \u003cem\u003ep\u003c/em\u003e value of \u0026lt;\u0026thinsp;0.05 was considered to indicate significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the results of comparisons of the demographic characteristics, parental styles, and reinforcement sensitivity between the ADHD and non-ADHD groups. The score for the care/affection parenting style was higher in the non-ADHD group than in the ADHD group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The scores for the overprotective parenting style (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) and authoritarianism controlling parenting style (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) were higher in the ADHD group than in the non-ADHD group. The scores for the reward responsiveness subscale of the BAS were higher in the non-ADHD group than in the ADHD group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.022), whereas no significant differences were observed in the scores for the BIS Scale and the drive and fun-seeking subscales of the BAS Scale between the ADHD and non-ADHD groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographics, parental styles, and reinforcement sensitivity (N\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-ADHD\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;173)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADHD\u003c/p\u003e \u003cp\u003e(\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;176)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003et\u003c/em\u003e or χ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years), mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.7 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.7 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.7 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.939\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e285 (81.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e141 (81.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e144 (81.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParental styles on the PBI, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCare/affection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38.9 (4.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.2 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37.7 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0 .001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverprotection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22.1 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.6 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e22.6 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthoritarianism controlling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11.2 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.7 (2.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11.6 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-2.790\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReinforcement sensitivity subscale of the BIS/BAS, mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14.2 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14.0 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.3 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReward responsiveness subscale of the BAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16.7 (2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.0 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.4 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrive subscale of the BAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12.1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.3 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.0 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFun seeking subscale of the BAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10.8 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10.8 (2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10.8 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.990\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; PBI: Parental Bonding Instrument.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e inserted here]\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides the proportions of participants with experiences of online sexual risk behaviors and the results of a comparison of the online sexual risk behaviors between the ADHD and non-ADHD groups. In total, 114 (32.7%) participants reported any passive type of online sexual risk behavior, and 49 (14.0%) reported any active type of online sexual risk behavior. No significant differences were observed in the passive or active types of online sexual risk behaviors between the ADHD and non-ADHD groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePassive and active types of online sexual risk behaviors (N\u0026thinsp;=\u0026thinsp;349)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;349) n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-ADHD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;173) n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADHD\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;176) n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePassive types of behaviors, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeing invited to talk about sex-related topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25 (7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.801\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeing pressured to share private personal sex information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.133\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeing invited to engage in sexual behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.248\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving messages containing sexual content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39 (11.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20 (11.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving pictures or videos with sexual connotations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving semi-nude or fully nude pictures or videos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.968\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInadvertently viewing sexually explicit information or videos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e85 (24.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e114 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57 (32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57 (32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActive types of behaviors, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSending messages with sexual content to others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9 (5.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSending pictures or videos with sexual connotations to others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.685\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSending semi-nude or fully nude pictures or videos to others\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSearching for sexually explicit information or watching sex videos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (11.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (12.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.694\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAny\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49 (14.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24 (13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003ea\u003c/sup\u003e: Fisher\u0026rsquo;s exact test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e inserted here]\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e lists the results of the examination of the associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and BIS and BAS constructs with the occurrence of passive types of online sexual risk behaviors among adolescents. The results for Model I indicated that older age was significantly associated with the occurrence of passive online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), whereas sex, diagnosis of ADHD, and parenting styles were not significantly associated with the occurrence of passive online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The findings for Model II revealed that in addition to older age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.007), the fun-seeking construct of the BAS was significantly associated with experiences of passive online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), whereas sex, diagnosis of ADHD, the BIS construct, and the reward responsiveness and drive constructs of the BAS were not significantly associated with experiences of passive online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The interaction between age and the fun-seeking construct of the BAS was further included in Model III, and the results revealed that the interaction was not significantly associated with the occurrence of passive online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis of associations of ADHD, parenting styles, and behavioral inhibition and activation with passive online sexual risk behaviors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003ePassive online sexual risk behaviors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel II\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel IIII\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.761\u003c/p\u003e \u003cp\u003e(0.926\u0026ndash;3.349)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.783\u003c/p\u003e \u003cp\u003e(0.929\u0026ndash;3.422)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.814\u003c/p\u003e \u003cp\u003e(0.943\u0026ndash;3.491)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.170\u003c/p\u003e \u003cp\u003e(1.045\u0026ndash;1.310)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.170\u003c/p\u003e \u003cp\u003e(1.050\u0026ndash;1.304)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.805\u003c/p\u003e \u003cp\u003e(0.464\u0026ndash;1.395)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003cp\u003e(0.612\u0026ndash;1.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003cp\u003e(0.580\u0026ndash;1.473)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.924\u003c/p\u003e \u003cp\u003e(0.579\u0026ndash;1.475)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.741\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAffection/care parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.019\u003c/p\u003e \u003cp\u003e(0.970\u0026ndash;1.070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverprotection parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.015\u003c/p\u003e \u003cp\u003e(0.939\u0026ndash;1.098)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthoritarian controlling parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.002\u003c/p\u003e \u003cp\u003e(0.924\u0026ndash;1.087)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.962\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.084\u003c/p\u003e \u003cp\u003e(0.989\u0026ndash;1.188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.089\u003c/p\u003e \u003cp\u003e(0.993\u0026ndash;1.195)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Reward responsiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003cp\u003e(0.885\u0026ndash;1.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.988\u003c/p\u003e \u003cp\u003e(0.886\u0026ndash;1.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Drive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003cp\u003e(0.851\u0026ndash;1.070)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.954\u003c/p\u003e \u003cp\u003e(0.851\u0026ndash;1.069)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.418\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Fun seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.124\u003c/p\u003e \u003cp\u003e(1.007\u0026ndash;1.255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.702\u003c/p\u003e \u003cp\u003e(0.353\u0026ndash;1.394)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge x BAS Fun seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.035\u003c/p\u003e \u003cp\u003e(0.985\u0026ndash;1.087)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e: girls as the reference\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; CI: confidence interval; OR: odds ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e inserted here]\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides the results of examination of the associations of the demographic characteristics, diagnosis of ADHD, parenting styles, and BIS and BAS constructs with experiences of active types of online sexual risk behaviors among adolescents. The results for Model IV indicated that boys were more likely to demonstrate active types of online sexual risk behaviors than girls were (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011). Older age was significantly associated with the occurrence of active online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas the diagnosis of ADHD and parenting styles were not significantly associated with the occurrence of active online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The results for Model V revealed that in addition to sex (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.012) and older age (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the fun-seeking construct of the BAS was significantly associated with experiences of active online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.031), whereas the diagnosis of ADHD, BIS constructs, and reward responsiveness and drive constructs of the BAS were not significantly associated with experiences of active online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The interactions of sex and age with the fun-seeking construct of the BAS were further included in Model VI. The interaction between sex and the fun-seeking construct of the BAS was significantly associated with experiences of active online sexual risk behaviors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.017). The significant association between the fun-seeking construct of the BAS and experiences of active online sexual risk behaviors was present for boys (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) but not for girls (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analysis of associations of ADHD, parenting styles, and behavioral inhibition and activation with active online sexual risk behaviors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eActive online sexual risk behaviors\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel IV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel V\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eModel VI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.726\u003c/p\u003e \u003cp\u003e(1.547\u0026ndash;29.238)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.711\u003c/p\u003e \u003cp\u003e(1.525\u0026ndash;29.527)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003cp\u003e(0.000\u0026ndash;0.216)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.418\u003c/p\u003e \u003cp\u003e(1.208\u0026ndash;1.664)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.449\u003c/p\u003e \u003cp\u003e(1.241\u0026ndash;1.691)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.451\u003c/p\u003e \u003cp\u003e(1.053\u0026ndash;5.702)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADHD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003cp\u003e(0.453\u0026ndash;1.747)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003cp\u003e(0.455\u0026ndash;1.686)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003cp\u003e(0.459\u0026ndash;1.727)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAffection/care parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.016\u003c/p\u003e \u003cp\u003e(0.949\u0026ndash;1.088)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverprotection parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.058\u003c/p\u003e \u003cp\u003e(.946\u0026ndash;1.184)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthoritarian controlling parenting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.987\u003c/p\u003e \u003cp\u003e(0.880\u0026ndash;1.107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.045\u003c/p\u003e \u003cp\u003e(0.921\u0026ndash;1.186)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.043\u003c/p\u003e \u003cp\u003e(0.919\u0026ndash;1.184)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Reward responsiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003cp\u003e(0.824\u0026ndash;1.118)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003cp\u003e(0.834\u0026ndash;1.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Drive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.920\u003c/p\u003e \u003cp\u003e(0.786\u0026ndash;1.076)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.916\u003c/p\u003e \u003cp\u003e(0.782\u0026ndash;1.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBAS Fun seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.185\u003c/p\u003e \u003cp\u003e(1.016\u0026ndash;1.381)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003cp\u003e(0.167\u0026ndash;2.138)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex x BAS Fun seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.969\u003c/p\u003e \u003cp\u003e(1.275\u0026ndash;12.361)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge x BAS Fun seeking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e--\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003cp\u003e(0.891\u0026ndash;1.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003csup\u003ea\u003c/sup\u003e: girls as the reference\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eADHD: attention-deficit/hyperactivity disorder; BAS: Behavior Approach System; BIS: Behavior Inhibition System; CI: confidence interval; OR: odds ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e[Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e inserted here]\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study found that 32.7% of adolescents had experiences of passive online sexual risk behaviors and that 14.0% had experiences of active online sexual risk behaviors. Thus, high proportions of adolescents had experiences of online sexual risk behaviors. Because online sexual risk behaviors lead to mental health problems and other risk behaviors, health professionals should regularly assess online sexual risk behaviors among adolescents, and they should promote an understanding of the disadvantages of online sexual risk behaviors among adolescents and implement prevention strategies for the behaviors.\u003c/p\u003e \u003cp\u003eThe present study found that the fun-seeking construct of the BAS was significantly associated with the occurrence of both passive and active online sexual risk behaviors. Moreover, the significant association between the fun-seeking construct of the BAS and the occurrence of active online sexual risk behaviors was present for boys but not for girls. The fun-seeking construct of the BAS represents the tendency to seek stimuli and responses to proximal rewards [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Given that Internet use exposes individuals to various modes of stimulation and the receipt of rapid rewards, individuals with high BAS-fun-seeking are more likely to develop problematic Internet use [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. A high Internet usage rate can increase the risk of exposure to unwanted online sexual invitation, sexting, and pornography among adolescents. Further, exploring sexual identity is one of the key developmental processes that occurs during adolescence [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Adolescents with high BAS-fun-seeking may actively search for sex-related materials and may interact with others online to satisfy their curiosity about sex. Subsequently, the risk of active online sexual risk behaviors increases among these adolescents. The results of the present study highlight the need for assessing adolescents\u0026rsquo; BAS-fun-seeking tendency and developing a corresponding intervention for reducing the risk of online sexual risk behaviors among adolescents. The present study did not find significant associations of the drive and reward responsiveness constructs of the BAS and BIS construct with experiences of online sexual risk behaviors. The results of our study indicate that the associations of the BAS and BIS constructs with the occurrence of online sexual risk behaviors are complex, and further examination of the associations is warranted.\u003c/p\u003e \u003cp\u003eGiven that sexual risk behaviors and problematic Internet use are more likely to occur among individuals with ADHD [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], researchers have hypothesized that adolescents with ADHD are more likely to demonstrate online sexual risk behaviors. However, the present study did not find significant differences in the risk of online sexual risk behaviors between adolescents with and without ADHD. The present findings indicate that interventions should be implemented for reducing the risk of online sexual risk behaviors among adolescents in the general population.\u003c/p\u003e \u003cp\u003eParenting styles considerably affect parent\u0026ndash;child interactions. For example, adolescents who experience the care/affection parenting style may be less resistant to discussing their online experiences with their parents, and they may accept their parents monitoring their Internet use. In the authoritative parenting style, parents can establish norms for managing their children\u0026rsquo;s Internet use. However, adolescents who have experienced overprotective parenting may lack the ability to make independent judgments when confronted with various messages on the Internet. Although the present study did not identify significant associations between parenting styles and online sexual risk behaviors among adolescents, parents have the crucial responsibility of educating their children regarding the negative impact of Internet use and regulating the time and content of their children\u0026rsquo;s Internet use. Thus, parents should learn essential parenting skills to help reduce the risk of their children\u0026rsquo;s involvement in online sexual risk behaviors.\u003c/p\u003e \u003cp\u003eThe present study has several limitations. First, we recruited adolescents with ADHD from outpatient clinics who were currently receiving pharmacological or psychological therapies. Adolescents without ADHD were recruited through an online advertisement. This difference in recruitment methods between the ADHD and non-ADHD groups could have introduced sampling bias into our research results. Whether the results of the present study can be generalized to adolescents with ADHD who do not visit outpatient clinics for medical help and adolescents who are not recruited through online advertisements should be further investigated. Second, given the cross-sectional design of the present study, the temporal associations of online sexual risk behaviors with other variables could not be determined. Third, participants\u0026rsquo; self-reported data were collected in this study; therefore, single-rater and recall biases could not be fully controlled for in the analysis. To address this limitation, future studies should examine potential social desirability bias. In addition, obtaining information from multiple sources may confirm the accuracy of the present study data.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe present study results indicate that high proportions of adolescents have experiences of online sexual risk behaviors. Health professionals should regularly assess online sexual risk behaviors among adolescents, and they should promote an understanding of the disadvantages of online sexual risk behaviors among adolescents and should implement prevention strategies for these behaviors. The fun-seeking construct of the BAS was significantly associated with experiences of both passive and active online sexual risk behaviors. Health professionals should assess adolescents\u0026rsquo; BAS-fun-seeking tendency and develop a corresponding intervention for reducing the risk of online sexual risk behaviors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTLL Conceptualization, funding acquisition, investigation, and writing the original draft. WJC and\u0026nbsp;RCH: Reviewing and editing the original draft. CFY: Designing the study, analyzing data, and writing the original draft. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the Ministry of Science and Technology, Taiwan (MOST 111-2635-B-182A-004 and 112-2314-B-182A-030).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndividual participant data that underlie the results reported in this article, after deidentifcation, will be made available to researchers who provide a methodologically sound proposal.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations Ethics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Review Boards of Kaohsiung Medical University (KMUHIRB-SV(I)-20200091) and Chang Gung Memorial Hospital, Kaohsiung Medical Center (202101964A3C502) approved this study. The study procedures were conducted in adherence to the tenets of the Declaration of Helsinki.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAll participants provided written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no conflicts of interest relevant to this article.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eReid Chassiakos YL, Radesky J, Christakis D, Moreno MA, Cross C, Council on Communication and Media. Children and adolescents and digital media. Pediatrics. 2016;138(5):e20162593.\u003c/li\u003e\n\u003cli\u003eJorgenson AG, Hsiao RC, Yen CF. Internet Addiction and Other Behavioral Addictions. 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American Psychiatric Publication Inc, Washington DC, USA; 1996.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Online risk behavior, sex, attention-deficit/hyperactivity disorder, parenting style, behavioral inhibition, behavioral activation","lastPublishedDoi":"10.21203/rs.3.rs-4965386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4965386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study examined the associations of a diagnosis of attention-deficit/hyperactivity disorder (ADHD), the tendencies of behavioral inhibition and activation, and parenting styles with experiences of passive and active online sexual risk behaviors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study invited 176 adolescents with ADHD and 173 adolescents without ADHD and their parents to participate. The parents rated their parenting styles on the Parental Bonding Instrument. The adolescents self-reported their lifelong experiences of passive and active online sexual risk behaviors and their tendencies of behavioral inhibition and activation on the Behavior Inhibition System (BIS) and Behavior Approach System (BAS) Scales. The associations of the diagnosis of ADHD, parenting styles, and BIS and BAS constructs with online sexual risk behaviors were examined usingmultivariable logistic regression analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn total, 114 (32.7%) participants reported any passive form of online sexual risk behaviors, and 49 (14.0%) participants reported any active online sexual risk behaviors. Older age (\u003cem\u003ep\u003c/em\u003e= 0.007) and the fun-seeking construct of the BAS (\u003cem\u003ep\u003c/em\u003e = 0.037) were significantly associated with passive online sexual risk behaviors. Being male (\u003cem\u003ep\u003c/em\u003e = 0.011), older age (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001), and the fun-seeking construct of the BAS (\u003cem\u003ep\u003c/em\u003e = 0.031) were significantly associated with active online sexual risk behaviors. The significant association between the fun-seeking seeking construct of the BAS and active online sexual risk behaviors was present in boys only.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh proportions of adolescents have experiences of online sexual risk behaviors. The factors related to online sexual risk behaviors should be considered in the development of intervention programs.\u003c/p\u003e","manuscriptTitle":"Online Sexual Risk Behaviors in Adolescents: Roles of Attention-Deficit/Hyperactivity Disorder, Parenting Styles, and Reinforcement Sensitivity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-24 08:13:51","doi":"10.21203/rs.3.rs-4965386/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"98dbd041-570a-4503-a79c-03646e221c4c","owner":[],"postedDate":"September 24th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-10T06:54:38+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-24 08:13:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4965386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4965386","identity":"rs-4965386","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}