Attention Deficit/Hyperactivity Disorder and Increased Engagement in Risk-Taking Behavior: The Role of Benefit Perception
Tali Spiegel and Yehdua Pollak*
The Seymour Fox School of Education, The Hebrew University of Jerusalem, Jerusalem, Israel
Attention deficit/hyperactivity disorder (ADHD) has been linked to higher engagement in risk-taking behavior (SRTB). The current study aims to establish the link between ADHD symptoms and SRTB in the general population and to examine whether an exaggerated perceived benefit of the positive outcomes of SRTB explains that link. A scale for measuring the frequency, likelihood, perceived benefit, and perceived risk of SRTB was developed. Young adult sexually active participants who did not have a stable partnership completed the above scale, as well as a scale of ADHD symptoms.
The level of ADHD symptoms positively correlated with the frequency and likelihood of SRTB, even when the overall level of sexual behavior was controlled for. ADHD symptoms also correlated with the perceived benefit of SRTB, but not with the perceived risk of SRTB. Mediation analysis confirmed an indirect pathway: ADHD symptoms predicted perceived benefit of SRTB, which in turn predicted increased likelihood to
engage in SRTB. These findings suggest a positive link between ADHD symptoms and SRTB in the general population, which is accounted for by an exaggerated perceived benefit of SRTB.
Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by inattention and/or hyperactivity/impulsivity and is associated with poor academic, social, occupational, financial, and health-related functioning (Faraone et al., 2015). People with ADHD tend to engage in risk-taking behaviors, defined as behaviors associated with a higher probability of undesirable outcomes (Boyer, 2006), such as significant physical injuries or financial loss. These risk-taking behaviors include, among others, substance use, smoking, reckless driving, and sexual
risk-taking behavior (SRTB) (Nigg, 2013). Frontiers in Psychology | www.frontiersin.org 1 May 2019 | Volume 10 | Article 1043 Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior Sexual risk-taking behavior may result in a variety of undesirable outcomes, including family conflicts, financial loss, and damaged reputation, but the two most commonly addressed concerns are unintended pregnancies and sexually transmitted diseases, such as HIV/AIDS (Turchik and Garske, 2009). SRTB involves having sex at an early age, having unprotected sex, and having multiple sexual partners (Martinez et al., 2011).
These health-threatening behaviors have been linked to drug and alcohol abuse, psychopathology, early parenthood, educational
problems, and convictions (Viner, 2005). A small number of studies have focused on the link between ADHD and SRTB. Prospective studies showed that childhood ADHD is associated with earlier sexual activity, a higher number of sexual partners, more sex outside of a relationship, more
sexually transmitted diseases, more partner pregnancies, and teenage parenthood (Barkley et al., 2006a; Flory et al., 2006;
Hosain et al., 2012; Sarver et al., 2014; Ostergaard et al., 2017). A relevant question is what may explain the link between
ADHD and SRTB. Individual differences associated with both ADHD and SRTB may have the potential to act as mediators.
Lifetime conduct disorder symptoms, which are closely related to ADHD, were found to contribute to the link between ADHD
and SRTB significantly (Barkley et al., 2006b; Ramos Olazagasti et al., 2013; Sarver et al., 2014). In another study, ADHD made
a unique contribution to STRB above and beyond conduct problems (Flory et al., 2006).
Excessive SRTB may also result from higher engagement in sexual behavior in general, as extra sexual activity, when not in the context of a stable, monogamous relationship, increases the possibility of exposure to risky sexual intercourse. In the literature regarding ADHD and risk taking in driving, the measured level is usually controlled against the total exposure/driving time of the participant (Knouse et al., 2005; Vaa, 2014). However, to the
best of our knowledge, the studies concerning the link between ADHD and SRTB were performed without control against the total engagement in sexual behavior. The present study suggests observing SRTB through the prism of Weber’s behavioral decision theory (Weber et al., 2002). According to this version of a psychological risk–return theory, a choice to engage in risk-taking behavior should be analyzed in terms of benefit and risk, as they are subjectively perceived by the decision maker. Weber contends that people differ in the perceived level of risk and benefit they ascribe to the behavior. In addition, though to a lesser extent, they differ in the attitudes toward these perceptions (namely in the weight the perceived risk and benefit have on the choice to engage in the behavior). Individual differences in benefit and risk perceptions and attitudes lead to different levels of engagement in risktaking
behavior, i.e., higher benefit perception and attitude and/or lower risk perception and attitude account for the choice to engage in risk-taking behavior. A recent study examined whether the link between ADHD symptoms and the overall level of risk-taking behavior is explained by differences in benefit and risk perceptions and attitudes. The study found a positive correlation between ADHD symptoms and the level of benefit perception. Furthermore, a mediation analysis revealed an indirect pathway between ADHD and risk-taking behavior through increased benefit perception, suggesting that people with ADHD engage in risktaking behavior more often than controls, since they view the benefits of engaging in these risky behaviors as greater (Shoham et al., 2016). Therefore, the goal of the study presented here was to examine the association between ADHD and SRTB and the influence of the perceived benefit on this association. In order to measure SRTB, a questionnaire consisting of 15 risky sexual behaviors was assembled. For each behavior, the participants were asked to rate the frequency, likelihood, perceived benefit, and perceived risk of engagement in that behavior. The frequency section contained an additional item probing for the frequency of engagement in “sexual activity of any kind” (not only risky) to control for individual differences in general sexual activity. In this paper, we favored a dimensional approach for the conceptualization of ADHD and, thus, referred to ADHD as a continuous trait, based on mental health dimensional models (Coghill and Sonuga-Barke, 2012). According to the dimensional approach, people with ADHD represent the end of a continuum of the level of ADHD symptoms’ distribution, rather than a distinct clinical category (Levy et al., 1997). In line with this approach, the current study measured ADHD continuously based on symptoms level. Hence, the present study hypotheses were as follows: (1) ADHD symptoms in the general population would be positively associated with the engagement in SRTB, even after controlling for general sexual activity; (2) an indirect link between ADHDand SRTB would be found through the link between ADHD and benefit perception.
MATERIALS AND METHODS
The experiment was approved by the ethics committee of the Seymour Fox School of Education, at the Hebrew University. One-hundred thirty adults, aged 19–39, participated in the study, of which 10 participants were excluded for excessive missing values or contradictory responses (see below in the “Results” section). All participants were sexually active (had at least one intercourse over the past 6 months) and were not in a stable relationship. The participants were recruited through advertisements in the social media “Facebook,” by different experimenters and from two separated locations (Tel-Aviv and Jerusalem districts).
Protocol and Measurement
All participants filled out an online informed consent form and were given the opportunity to participate in a lottery to win 500 NIS (125 euros) by leaving an email address. The following questionnaires were completed by the participants:
The participants provided background information on age,
gender, education, religiousness level, and sexual orientation.
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Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
The Sexual Risk-Taking Behavior Scale (SRTB)
The Sexual Risk-Taking Behavior Scale (SRTB) (see Appendix 1)
consists of 15 risky sexual activities (such as, “anal sex without
the use of a condom,” “casual sex”). Inspired by Weber’s Domain-
Specific Risk-Taking (DOSPERT) scale assessment (Blais and
Weber, 2006), the SRTB measures the likelihood and frequency
of engaging in and the perceived benefits and risks of each of
the risky sexual behaviors using seven-point Likert scales for
likelihood and perception and an eight-point Likert scale for
frequency (likelihood: 1 = extremely unlikely, 7 = extremely
likely; benefit perception: 1 = no benefits, 7 = great benefits; risk
perception: 1 = not at all risky, 7 = extremely risky; frequency:
1 = never, 8 = at least once a day). The frequency scale measured
SRTB over the past year. In addition, in order to measure general
sexual activity, respondents were asked to indicate the frequency
they participated in “sexual activity of any kind.” Construct
validity was assessed via correlations between likelihood and
frequency measurements and between likelihood and perception
measurements. Additional validation was obtained by comparing
the risk perception scores of items that self-evidently differed in
the risk level (see the “Results” section).
The Adult ADHD Self-Report Scale (ASRS-V1.1)
(Kessler et al., 2005)
The Adult ADHD Self-Report Scale (ASRS-V1.1) (Kessler
et al., 2005) is a dimensional measure of ADHD symptoms.
It includes 18 items (9 items of inattention and 9 items of
hyperactivity/impulsivity) corresponding to the Diagnostic and
Statistical Manual of Mental Disorder, 4th ed. diagnostic criteria
of ADHD, each measured for its frequency on a Likert scale
ranging from 1 (never) to 5 (very often). The questionnaire
has high internal consistency (a = 0.88). The scale’s sensitivity
and specificity are 68.4 and 99.6%, respectively (Kessler et al.,
2005; Adler et al., 2006). The Hebrew version has high test–
retest reliability estimates (p = 0.6–0.9), high internal consistency
of a = 0.89, and sensitivity and specificity of 62.7 and 68%,
respectively (Zohar and Konfortes, 2010).
Sexual History and ADHD Diagnosis Questionnaire
In order to characterize the sample in terms of sexual history,
participants provided information on sexual debut, lifetime
number of sexual partners, history of sexually transmitted
diseases, and HIV tests. In addition, participants reported
on any history of a diagnosis of ADHD and the use of
medications to treat ADHD.
Total scores were calculated for each participant on each
questionnaire. Using Weber’s regression equation (Weber et al.,
2002), for each subject, we regressed the likelihood of engagement
in SRTB on the perceived benefit and perceived risk and
calculated the coefficients that index the individual attitudes
toward the perceived benefit and risk. Skewness and kurtosis
tests were conducted to examine the normality of the distribution
of the variables. For further covariation, we examined whether
there were any statistically significant associations between
demographic variables and the study variables.
To test the first hypothesis, a regression analysis of
the relations between ADHD symptoms and frequency of
SRTB was computed while controlling for the general sexual
activity variable. To test the second hypothesis, direct and
indirect effects of ADHD symptoms on the likelihood of
SRTB were calculated using the multiple mediation approach
and SPSS macro (PROCESS, Model 6) provided by Hayes
(2013). The significance of effects was tested via bootstrap
analysis (5,000 samples), which is commonly performed in
multiple mediator analyses, given its advantage of greater
statistical power without assuming multivariate normality in the
sampling distribution, assuming only the sample is representative
of the population. Statistical mediation is demonstrated via
a significant indirect effect (i.e., if the 95% bias-corrected
confidence interval for the parameter estimate does not
contain zero). All analyses were conducted using SPSS 25.0
including an SPSS macro designed for assessing multiple
Data from participants, which met the following criteria, were
not included in the analyses: (1) missing values exceeded 30%
in one or more of the scales (six participants). (2) Responses
contradicted each other (e.g., frequency of risky sexual behavior
exceeded the frequency of sexual behavior in general). When one
contradiction was observed, only the contradicting items were
removed from the database. When more than one contradiction
was observed, the entire data of the participant were removed
Participants were recruited from two locations: Tel Aviv and
Jerusalem districts (n = 33 and 87, respectively). Mean age of
the sample was 25.77 (4.33). The sample consisted of 72.5%
females; 90.8% of the participants had high education; 89.2% of
the sample identified as non-religious; and 92.5% identified as
heterosexual. Regarding diagnosis of and treatment for ADHD,
19.2% reported that they had been formally diagnosed with
ADHD, and 14.2% of the sample reported ever using medication
for ADHD. Regarding history of risky sexual behavior, 70.8%
reported having three or more partners so far, 45.0% have ever
been screened for STD with 5.0% of the sample found positive,
41.7% of the participants (or their partners) have ever used
“morning after” pills, and 5.0% had unintended pregnancy.
Reliability and Validity of the
Internal consistency indices of the likelihood, frequency, and
perception scales were in the acceptable to good range
(Cronbach’s alpha 0.78–0.88). Skewness and kurtosis tests were
used to confirm the normality of distribution. Skewness indices of
all scales, except for the frequency scale, were in the 1 to 1 range
(0.19, 0.35, 0.05, 0.19, 0.95, and 1.34 for likelihood, benefit
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Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
perception, benefit attitude, risk perception, risk attitude, and
frequency, respectively). Kurtosis indices of all scales, except for
the benefit attitude, risk attitude, and frequency scales, were in the
1 to 1 range (0.05, 0.35, 2.20, 0.01, 3.17, and 2.00 for likelihood,
benefit perception, benefit attitude, risk perception, risk attitude,
and frequency, respectively). As three out of six scales were
not normally distributed, further analyses were conducted using
Several analyses were conducted to support the
trustworthiness of the responses and the validity of the scales.
First, we compared ASRS mean scores between the participants
who reported having and not having an ADHD diagnosis. As
expected, the ASRS scores of the participants with a history of an
ADHD diagnosis were significantly higher [M = 3.14, SD = 0.70,
and M = 2.53, SD = 0.46, respectively, t(26.74) = 3.98, P < 0.001,
Hedges’ g = 1.19]. Next, we analyzed the responses to specific
items in the likelihood, frequency, and risk perception scales,
under the assumption that their associated level of risk differs
in an obvious way. Items 9a, b and 9c, d in the likelihood and
risk perception levels (and the corresponding items 11a, b and
11c, d in the frequency scale) refer to sex with a new partner and
differ in whether the sexual history of the partner is known. As
expected, the likelihood and frequency scores were lower, and the
risk perception score was higher when the history of the partner
was unknown (P < 0.001). Similarly, items 10a, b and 10c, d in
the likelihood and risk perception levels (and the corresponding
items 12a, b and 12c, d in the frequency scale) refer to regular but
non-committed sex and differ in whether the sexual history of
the partner is known. As expected, the likelihood and frequency
scores were lower, and the risk perception score was higher when
the history of the partner was unknown (P < 0.001).
Median and 25–75% values of the ASRS and SRTB scores are
presented in Table 1. A positive Spearman rho correlation was
found between the likelihood and frequency scales (r = 0.63,
P < 0.001). A regression analysis was conducted with the SRTB
likelihood score as the predicted variable, and both perception
and attitude score as predictors. This model accounted for 50%
of the variance in the SRTB likelihood score. As expected,
the benefit perception and attitude scores positively predicted
TABLE 1 | Descriptive statistics of ASRS and SRTB scales.
ASRS (mean item score) 2:58 2.28–3.06
Inattention 2:67 2.33–3.00
Hyperactivity 2:56 2.22–3.00
Frequency of engagement 1:63 1.34–1.94
Likelihood of engagement 3:06 2.35–3.62
Benefit perception 2:88 2.31–3.54
Risk perception 4:84 4.06–5.31
Perceived-benefit attitude 0:60 0.30–0.88
Perceived-risk attitude 0:30 0.50–0.10
N = 120 (87 females, 33 males); ASRS, Adult ADHD Self-Report Scale; SRTB,
sexual risk-taking behavior.
SRTB likelihood, whereas the risk perception and attitude
scores negatively predicted SRTB likelihood. A bootstrap analysis
revealed that benefit and risk perceptions scores, as well as the risk
attitude score, contributed to the prediction of SRTB likelihood
above and beyond all other variables (b = 0.59, 0.21, and 0.18,
respectively, 95% CIs did not include zero).
The correlations between the variables included in the hypotheses
and the demographic variables were examined. As presented
in Table 2, gender, age, religiousness, and sample location,
but not level of education, were significantly related to one
or more of the SRTB variables and were further controlled
for in later analyses. Of the various demographic variables,
gender was related to SRTB in the most consistent manner.
Female participants reported lower engagement in SRTB and
lower benefit perception, as well as higher risk perception
and risk aversion. As gender was related to SRTB scores in a
consistent manner, an exploratory analysis was conducted to
examine whether gender and ADHD interact in predicting SRTB.
Moderation analyses failed to show any significant interaction
between ADHD and gender in predicting the frequency,
likelihood, benefit, and risk perception, as well as perceived
benefit and risk attitudes [F(1,112) = 0.051, 0.019, 0.477, 0.665,
0.205, and 0.001, respectively, p 0.412, age, religiousness, sexual
orientation, and sample location covariated].
To test the first hypothesis, hierarchical linear regression was
conducted for analyzing the contribution of ADHD symptoms to
the prediction of the frequency of engagement in SRTB. Gender,
age, religiousness, sexual orientation, sample location, as well as
the frequency of general sexual activity were entered in the first
block, and the ASRS score was entered in a subsequent block.
The first block explained 44.6% of the variance in the SRTB
score, whereas the ASRS explained an additional 3.4% of the
variance, indicating a small effect size (f 2 = 0.035). Male gender,
general sexual activity, and ASRS score predicted SRTB above and
beyond all other predictors (see Table 3). Re-analyzing the same
model, this time with inattention and hyperactivity symptoms
separately entered into the second block, elicited similar results,
with neither symptom cluster predicting SRTB above and beyond
the other cluster.
Mediation analyses were conducted to test the second
hypothesis. The ASRS score served as a predictor, the risk and
benefit perceptions and attitudes as mediators, the likelihood
scores as the predicted variable, and gender, age, religiousness,
sexual orientation, sample location, as well as the frequency of
general sexual activity as covariates.
The path analysis in Figure 1 depicts the direct effects
and indirect pathways of the model. Together, the model
accounted for 54.6% of the variance in SRTB (P < 0.001). The
standardized regression coefficient between ADHD symptoms
and SRTB before considering mediators, and between ADHD
symptoms and benefit perception, was statistically significant.
The bootstrapped standardized indirect effect mediated by
benefit perception was significant and of moderate effect size. The
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Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
TABLE 2 | Spearman rho correlation between demographic variables and SRTB scales.
Sample location Gender Age Religiousness Education Sexual orientation
Frequency of engagement 0:237 0:195 0:228 0:138 0:029 0:259
Likelihood of engagement 0:076 0:231 0:080 0:267 0:006 0:153
Benefit perception 0:100 0:219 0:112 0:154 0:017 0:123
Risk perception 0:141 0:197 0:071 0:195 0:059 0:152
Perceived-benefit attitude 0:105 0:133 0:138 0:077 0:102 0:211
Perceived-risk attitude 0:060 0:210 0:202 0:126 0:014 0:022
SRTB, sexual risk-taking behavior; sample location was coded as 1 = Tel-Aviv district, 2 = Jerusalem district; gender was coded as 1 = male, 2 = female; religiousness
was coded as 1 = secular, 2 = traditional, 3 = Orthodox; sexual orientation was coded as 1 = heterosexual, 2 = not heterosexual. p < 0.05, p < 0.01.
indirect effects ofADHDsymptoms, mediated by risk perception,
risk attitude, and benefit attitude, were not significant. ADHD
symptoms did not predict SRTB after accounting for the indirect
effect (see Table 4 for coefficients and CIs).
The study focused on the relationship between ADHD
symptoms, engagement in SRTB, and perception and attitudes
regarding the outcomes of SRTB. The results of the current
study confirmed the following hypotheses: (a) the level of
ADHD symptoms in the general population correlates with
the frequency of engagement in SRTB even after controlling
for general engagement in sexual behavior; (b) a link between
ADHD and SRTB exists through the positive correlation of
ADHD and benefit perception.
TABLE 3 | Prediction of sexual risk-taking behavior.
1R2 B 95% CI
Age 0:00 0.03–0.02
Gender 0:21 0.40–0.03
Religiousness 0:06 0.17–0.05
Sexual orientation 0:21 0.03–0.64
Sample location 0:18 0.44–0.10
General sexual activity 0:22 0.15–0.28
Age 0:00 -0.02–0.03
Gender 0:24 0.42–0.05
Religiousness 0:06 0.15–0.05
Sexual orientation 0:13 0.07–0.49
Sample location 0:17 0.42–0.10
General sexual activity 0:21 0.15–0.27
ASRS 0:19 0.04-0.34
ASRS, Adult ADHD Self-Report Scale; SRTB, sexual risk-taking behavior. 95%
confidence interval does not contain zero.
ADHD and Increased SRTB
Self-reported ADHD symptoms predicted the self-reported reallife
frequency and the hypothetical likelihood of engagement
in SRTB. These findings are in agreement with other studies
documenting increased SRTB by people with ADHD (Barkley
et al., 2006a; Flory et al., 2006), as well as with studies reporting
correlation between the level of ADHD symptoms and SRTB in
the general population (Sarver et al., 2014; Marsh et al., 2015;
Isaksson et al., 2018).
The link between ADHD and increased engagement in SRTB
may be explained by increased overall engagement in sexual
behavior. To test this hypothesis, the reported frequency of
the general sexual activity was used as a covariate. ADHD
symptoms still predicted SRTB even after covariating for the
general sexual activity.
Importantly, the link between ADHD and risk-taking
behavior is not limited to SRTB. Numerous studies
consistently reported associations between ADHD and
higher engagement in other risk-taking behaviors, e.g.,
substance use, reckless driving, and gambling (for review,
see Nigg, 2013), with scales measuring overall levels of
risk-taking behavior (Pollak et al., 2016; Shoham et al.,
2016; Pollak et al., 2017), as well as with increased
risk taking on laboratory tasks (Mowinckel et al., 2015;
Dekkers et al., 2016).
ADHD Symptoms and SRTB-Related
Risk/Benefit Perceptions and Attitudes
According to the behavioral decision theory (Weber et al.,
2002), a psychological risk–return model, risk and return
are subjectively evaluated. According to this model, SRTB
in ADHD cases may be explained by a less negative/more
positive attitude, or weight given to risk and return, respectively,
but also by differences in subjective evaluation of risk and
return, i.e., risk and benefit perception. We used Weber’s
behavioral decision theory to operationalize risk and benefit
perception and attitude. Perceptions were measured directly
by asking participants to rate the magnitude of risk and
benefit they ascribe to different SRTBs, whereas attitudes
were calculated by regressing the likelihood of engagement in
SRTB on perceptions.
A main finding of the current study is that ADHD
symptoms correlate with the perception of the benefits
associated with SRTB. Mediation analysis supported a model,
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Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
FIGURE 1 | Path analysis portraying the direct and indirect pathways predicting the likelihood of sexual risk-taking behavior (SRTB). Values reflect standardized
regression coefficients of the indirect effects and of the direct effect (after considering other mediators) of Adult ADHD Self-Report Scale (ASRS) on SRTB. The
significance of effects was tested via a 5,000-sample bootstrap analysis (the effect is considered significant if the 95% bias-corrected confidence interval for the
parameter estimate does not contain zero). The covariates of age, gender, religiousness, sexual orientation, sample location, and the frequency of general
engagement in sexual behavior are not shown for visual clarity. N = 120 (87 females, 33 males). 95% confidence interval does not contain zero.
TABLE 4 | The direct and indirect pathways of the link between the ASRS score and the likelihood of engagement in SRTB.
Model R2 Indirect effect Direct effect
Benefit perception Risk perception Perceived-benefit attitude Perceived-risk attitude
ASRS 54.6 0.081 0.017 0.020 0.030 0.102
95% CI [0.007, 0.171] 95% CI [0.010, 0.063] 95% CI [0.009, 0.064] 95% CI [0.084, 0.009] 95% CI [0.039, 0.243] ASRS, Adult ADHD Self Report Scale; SRTB, sexual risk-taking behavior. 95% confidence interval does not contain zero.
according to which the link between ADHD symptoms and
SRTB is indirect through the link between ADHD and
higher benefit perception. The indirect pathways, through
benefit attitude, risk perception, and risk attitude, were not
significant. These findings are in accord with a recent study
demonstrating that ADHD symptoms correlate with increased
benefit perception of the positive outcomes of widespread
risk-taking behavior, but not with the risk perception of the
negative outcomes of risk-taking behavior (Shoham et al., 2016).
Importantly, given the cross-sectional nature of this study, it
should be highlighted that the supported mediation model
is only statistical. Further research may use a longitudinal
design, which enables examining whether the link between
ADHD and SRTB is stable across time and whether there
is evidence for temporal precedence, which are important
conditions of causality.
The investigation of the mechanisms underlying SRTB among
people with ADHD has important clinical implications.
Specifically, it informs prescriptive research with the goal of
helping people with ADHD to optimize their sexually related
decision-making and counter their engagement in dangerous
sexual activities. Our findings suggest that interventions
aimed at reducing SRTB in adults should include measures
of their ADHD symptoms as well as their perceptions of
the benefits (and risks) of engaging in SRTB. Interventions
may be devised considering the research, which would deal
with external regulation and strategies that consider the
This study has several limitations: The sample size was not big
enough to further examine factors that affect the link between
ADHD and SRTB. The convenience sampling resulted in an
over-representation of women and of individuals with higher
education and with a history of ADHD diagnosis. However, the
degree of education did not correlate with risk measures. In
addition, engagement in SRTB was assessed using self-report,
which was not validated by a collateral report.
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Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
This study was carried out in accordance with the
recommendations of the Declaration of Helsinki with written
informed consent from all subjects. All subjects gave written
informed consent in accordance with the Declaration of
Helsinki. The protocol was approved by the ethics committee
of the Seymour Fox School of Education, at The Hebrew
University of Jerusalem.
TS and YP designed the study and analyzed the data. TS
collected the data and wrote the manuscript. YP reviewed and
revised the manuscript.
This work was supported by an internal grant of
the Authority for Research and Development, The
Hebrew University of Jerusalem. The funding source
had no involvement in study design; in the collection,
analysis and interpretation of data; in the writing of
the report; and in the decision to submit the article
The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fpsyg.
Adler, L. A., Spencer, T., Faraone, S. V., Kessler, R. C., Howes, M. J., Biederman,
J., et al. (2006). Validity of pilot Adult ADHD self-report scale (ASRS) to
rate adult ADHD symptoms. Ann. Clin. Psychiatry 18, 145–148. doi: 10.1080/
Barkley, R. A., Fischer, M., Smallish, L., and Fletcher, K. (2006a). Young adult
outcome of hyperactive children: adaptive functioning in major life activities.
J. Am. Acad. Child Adolesc. Psychiatry 45, 192–202. doi: 10.1097/01.chi.
Barkley, R. A., Murphy, K. R., O’Connell, T., Anderson, D., and Connor, D. F.
(2006b). Effects of two doses of alcohol on simulator driving performance in
adults with attention-deficit/hyperactivity disorder. Neuropsychology 20, 77–87.
Blais, A. R., and Weber, E. U. (2006). A Domain-Specific Risk-Taking (DOSPERT)
scale for adult populations. Judgm. Decis. Making J. 1, 33–47.
Boyer, T. W. (2006). The development of risk-taking: a multi-perspective review.
Dev. Rev. 26, 291–345. doi: 10.1016/j.dr.2006.05.002
Coghill, D., and Sonuga-Barke, E. J. (2012). Annual research review: categories
versus dimensions in the classification and conceptualisation of child
and adolescent mental disorders—implications of recent empirical study.
J. Child Psychol. Psychiatry 53, 469–489. doi: 10.1111/j.1469-7610.2011.
Dekkers, T. J., Popma, A., Agelink van Rentergem, J. A., Bexkens, A., and Huizenga,
H. M. (2016). Risky decision making in attention-deficit/hyperactivity disorder:
a meta-regression analysis. Clin. Psychol. Rev. 45, 1–16. doi: 10.1016/j.cpr.2016.
Faraone, S. V., Asherson, P., Banaschewski, T., Biederman, J., Buitelaar, J. K.,
Ramos-Quiroga, J. A., et al. (2015). Attention-deficit/hyperactivity disorder.
Nat. Rev. Dis. Primers 1:15020. doi: 10.1038/nrdp.2015.20
Flory, K., Molina, B. S., Pelham, W. E., Gnagy, E., and Smith, B. (2006). Childhood
ADHDpredicts risky sexual behavior in young adulthood. J. Clin. Child Adolesc.
Psychol. 35, 571–577. doi: 10.1207/s15374424jccp3504_8
Hayes, A. F. (2013). Introduction to Mediation, Moderation, and Conditional
Process Analysis: a Regression-Based Approach. New York, NY: Guilford
Hosain, G. M., Berenson, A. B., Tennen, H., Bauer, L. O., and Wu, Z. H.
(2012). Attention deficit hyperactivity symptoms and risky sexual behavior in
young adult women. J. Womens Health 21, 463–468. doi: 10.1089/jwh.2011.
Isaksson, J., Stickley, A., Koposov, R., and Ruchkin, V. (2018). The danger
of being inattentive—ADHD symptoms and risky sexual behaviour in
Russian adolescents. Eur Psychiatry 47, 42–48. doi: 10.1016/j.eurpsy.2017.
Kessler, R. C., Adler, L., Ames, M., Demler, O., Faraone, S., Hiripi, E., et al. (2005).
The World health organization adult ADHD self-report scale (ASRS): a short
screening scale for use in the general population. Psychol. Med. 35, 245–256.
Knouse, L. E., Bagwell, C. L., Barkley, R. A., and Murphy, K. R. (2005).
Accuracy of self-evaluation in adults with ADHD: evidence from a
driving study. J. Atten. Disord. 8, 221–234. doi: 10.1177/108705470528
Levy, F., Hay, D. A.,McStephen, M., Wood, C., and Waldman, I. (1997). Attentiondeficit
hyperactivity disorder: a category or a continuum? Genetic analysis of
a large-scale twin study. J. Am. Acad. Child Adolesc. Psychiatry 36, 737–744.
Marsh, L. E., Norvilitis, J. M., Ingersoll, T. S., and Li, B. (2015). ADHD
symptomatology, fear of intimacy, and sexual anxiety and behavior among
college students in China and the United States. J. Atten. Disord. 19, 211–221.
Martinez, G., Copen, C. E., and Abma, J. C. (2011). Teenagers in the United States:
sexual activity, contraceptive use, and childbearing, 2006–2010 national survey
of family growth. Vital Health Stat. 23, 1–35.
Mowinckel, A. M., Pedersen, M. L., Eilertsen, E., and Biele, G. (2015). A metaanalysis
of decision-making and attention in adults with ADHD. J. Atten.
Disord. 19, 355–367. doi: 10.1177/1087054714558872
Nigg, J. T. (2013). Attention-deficit/hyperactivity disorder and adverse
health outcomes. Clin. Psychol. Rev. 33, 215–228. doi: 10.1016/j.cpr.2012.
Ostergaard, S. D., Dalsgaard, S., Faraone, S. V., Munk-Olsen, T., and Laursen,
T. M. (2017). Teenage parenthood and birth rates for individuals with and
without attention-deficit/hyperactivity disorder: a nationwide cohort study.
J. Am. Acad. Child Adolesc. Psychiatry 56, 578.e3–584.e3. doi: 10.1016/j.jaac.
Pollak, Y., Oz, A., Neventsal, O., Rabi, O., Kitrossky, L., and Maeir, A. (2016).
Do adolescents with attention-deficit/hyperactivity disorder show risk seeking?
Disentangling probabilistic decision making by equalizing the favorability
of alternatives. J. Abnorm. Psychol. 125, 387–398. doi: 10.1037/abn000
Pollak, Y., Poni, B., Gershy, N., and Aran, A. (2017). The role of parental
monitoring in mediating the link between adolescent ADHD symptoms and
risk-taking behavior. J. Atten. Disord. doi: 10.1177/1087054717725875 [Epub
ahead of print].
Ramos Olazagasti, M. A., Klein, R. G., Mannuzza, S., Belsky, E. R., Hutchison,
J. A., Lashua-Shriftman, E. C., et al. (2013). Does childhood attentiondeficit/
hyperactivity disorder predict risk-taking and medical illnesses in
adulthood? J. Am. Acad. Child Adolesc. Psychiatry 52, 153–162. doi: 10.1016/
Sarver, D. E., McCart, M. R., Sheidow, A. J., and Letourneau, E. J. (2014). ADHD
and risky sexual behavior in adolescents: conduct problems and substance use
as mediators of risk. J. Child Psychol. Psychiatry 55, 1345–1353. doi: 10.1111/
Frontiers in Psychology | www.frontiersin.org 7 May 2019 | Volume 10 | Article 1043
Spiegel and Pollak ADHD and Sexual Risk-Taking Behavior
Shoham, R., Sonuga-Barke, E. J., Aloni, H., Yaniv, I., and Pollak, Y. (2016). ADHDassociated
risk taking is linked to exaggerated views of the benefits of positive
outcomes. Sci. Rep. 6:34833. doi: 10.1038/srep34833
Turchik, J. A., and Garske, J. P. (2009). Measurement of sexual risk taking among
college students. Arch. Sex. Behav. 38, 936–948. doi: 10.1007/s10508-008-
Vaa, T. (2014). ADHD and relative risk of accidents in road traffic: a meta-analysis.
Accid. Anal. Prev. 62, 415–425. doi: 10.1016/j.aap.2013.10.003
Viner, R. (2005). Co-occurrence of adolescent health risk behaviors
and outcomes in adult life: findings from a national birth cohort.
J.Adolesc. Health 36, 98–99. doi: 10.1016/j.jadohealth.2004.1
Weber, E. U., Blais, A. R., and Betz, N. E. (2002). A domain-specific risk-attitude
scale: measuring risk perceptions and risk behaviors. J. Behav. Decis.Making 15,
263–290. doi: 10.1002/bdm.414
Zohar, A. H., and Konfortes, H. (2010). Diagnosing ADHD in Israeli adults:
the psychometric properties of the Adult ADHD Self Report Scale (ASRS) in
Hebrew. Isr. J. Psychiatry Relat. Sci. 47, 308–315.
Conflict of Interest Statement: The authors declare that the research was
conducted in the absence of any commercial or financial relationships that could
be construed as a potential conflict of interest.
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*Tali Spiegel is the Co-Founder of LD-Calc