Sluggish Cognitive Tempo: Sociodemographic,Behavioral,and Clinical Characteristics in a Population of Catalan School Children

Abstract

Objective: The aims of the present study were to examine the presence of sluggish cognitive tempo (SCT) symptoms in children; associations of the symptoms with sociodemographic characteristics of the children; and relationships between SCT symptoms and symptoms of ADHD, dyslexia, academic performance, and behavioral problems. Method: We evaluated Catalan schoolchildren aged 7 to 10 years in Barcelona, 2012-2013. Parents filled out the SCT–Child Behavior Checklist (SCT-CBCL), the Strengths and Difficulties Questionnaire (SDQ), and a questionnaire concerning sociodemographic characteristics. Teachers completed the ADHD criteria of Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) (ADHD-DSM-IV), a list of dyslexia symptoms, and evaluated the children’s academic performance. SCT symptoms were studied as a continuous and dichotomous variable. Results: In all, 11% of the children in our sample scored above the clinical cut-off on the SCT-CBCL scale. We observed a higher rate of SCT symptoms in boys, children whose father was unemployed, those whose maternal educational level was lower, children with a high socioeconomic vulnerability index at home, those who reported maternal smoking during pregnancy and current second-hand smoke exposure at home, and children with an ADHD diagnosis. More SCT symptoms were associated with inattention symptoms, symptoms of dyslexia, academic problems, and emotional and peer relationship problems. Conclusion: We observed a higher prevalence of SCT symptoms in our sample than expected in the general population. While girls are less prone to SCT symptoms, some socioeconomic indicators, dyslexia, and inattention symptoms as well as exposure to smoking at home increase the risk of SCT and must be taken into account during assessments.

Keywords

sluggish cognitive tempo ADHD children impairment

Introduction

Participants with symptoms of sluggish cognitive tempo (SCT) are described as “slow,” “forgetful,” “drowsy,” “prone to daydreaming,” “lost in thought,” “unmotivated,” “in the clouds,” and “confused,” and perform poorly in some neuropsychological tests (Barkley, Grodzinsky, & DuPaul, 1992; Milich, Balentine, & Lynam, 2001). Two dimensions of SCT have been identified among American Hispanic populations: the cognitive dimension (“inconsistent alertness”) and the behavioral dimension (“slowness”; Fenollar Cortés, Servera, Becker, & Burns, 2017; Lee, Burns, Snell, & McBurnett, 2014). The first dimension (“inconsistent alertness”) includes daydreaming, fluctuations of alertness, absent-mindedness, and losing one’s train of thought. The second dimension (“Slowness”) consists of slow thinking, slow performance, and drowsiness. Becker, Lepolod, Burns, and Jarrett (2016), in a recent meta-analysis, suggest that SCT be evaluated as a transdiagnostic construct.

The study of SCT has mainly emerged from ADHD research (Carlson & Mann, 2002; McBurnett, Pfiffner, & Frick, 2001). Although 30% to 59% of patients with inattentive subtype ADHD (ADHD-I) show SCT symptoms, studies using exploratory and confirmatory factor analysis support the distinctiveness of SCT, compared with ADHD-I (Barkley, 2014; Carlson & Mann, 2002; McBurnett et al., 2001; Penny, Waschbusch, Klein, Corkum, & Eskes, 2009; Skirbekk, Hansen, Oerbeck, & Kristensen, 2011). In the only study of the prevalence of SCT to date, the authors found that some 6% of children exhibit highly severe SCT symptoms (above the 94th percentile) in a sample of 1,800 children aged from 6 to 17 years in the United States (Barkley, 2013).

That previous U.S. study revealed that a higher rate of SCT symptoms is associated with low levels of parental education, low annual household income, and higher parental unemployment (Barkley, 2013). Dimensional SCT symptoms are only modestly associated with the male sex, whereas individuals with high levels of SCT symptoms are more likely to be female (Becker et al., 2016). SCT symptoms showed a modest positive association with age (Becker et al., 2016). SCT shares comorbidity with internalization symptoms (symptoms of anxiety/depression), avoidance behavior, difficulties in self-regulation of negative emotions, social dysfunction, high levels of unhappiness, and low self-esteem (Barkley, 2012; Bauermeister, Barkley, Bauermeister, Martínez, & McBurnett, 2012; Becker, 2014; Becker & Langberg, 2013; Becker et al., 2016; Becker, Luebbe, Fite, Stoppelbein, & Greening, 2014; Burns, Servera, del Mar Bernad, Carrillo, & Cardo, 2013; Capdevila-Brophy et al., 2014; Carlson & Mann, 2002; Fenollar Cortés et al., 2017; Flannery, Becker, & Luebbe, 2014; Garner, Marceaux, Mrug, Patterson, & Hodgens, 2010; Lee et al., 2014; Penny et al., 2009; Schatz & Rostain, 2006). Finally, the association between SCT symptoms on the one hand and both externalizing symptoms and academic performance on the other is still not clear (Bauermeister et al., 2012; Fenollar Cortés et al., 2017; Flannery et al., 2014; Langberg, Becker, & Dvorsky, 2014; Marshall, Evans, Eiraldi, Becker, & Power, 2014).

To date, the prevalence of SCT symptoms in the general Spanish population has not been studied. We aimed to explore the prevalence of the set of SCT symptoms in a population of schoolchildren from Spain. We also aimed to test the association between SCT symptoms and sociodemographic, clinical, and behavioral determinants of SCT symptoms in this population.

Method

Participants

The BREATHE project was a longitudinal study of the association between air pollution and cognitive development conducted on 2,897 schoolchildren in 39 schools in Barcelona (Catalonia, Spain), from January 2012 to March 2013. A group of 263 children (roughly 10%), aged 7 to 10 years, were recruited to participate in a second phase of the BREATHE project (Pujol et al., 2016), including a comprehensive MRI evaluation. We distributed a four-item SCT questionnaire taken from the Child Behavior Checklist (Achenbach et al., 2008) to these 263 participants. A total of 183 (related to children aged from 7 to 10 years) questionnaires were returned completed (Figure 1). Differences between participants in the study of SCT symptoms (n = 183) and non-participants (n = 2,714) were studied (Supplementary Table 1; available at https://journals-sagepub-com.web.bisu.edu.cn/doi/suppl/10.1177/1087054716652477). We only found statistically significant differences between participants and non-participants in their maternal educational level (participants in the present study had higher maternal educational than non-participants).

Figure 1.

Flow diagram of recruiting sample.

The parents or legal guardians of all the children participating in the study signed the informed consent approved by the IMIM-Parc Salut Mar Ethical Committee (No. 2010/41221/I).

Outcome Measurement

The SCT-CBCL scale is included in the Achenbach Child Behavior Checklist and Teacher Report Form (Achenbach et al., 2008). SCT scores are obtained from Items 13 (“confused or seems to be in a fog”), 17 (“daydreams, or gets lost in his/her thoughts”), 80 (“stares blankly”), and 102 (“underactive, slow moving, or lacks energy”). Each of these items is scored from 0 to 2 (0 = not true [as far as you know]; 1 = somewhat or sometimes true; 2 = very true or often true). Thus, scores range from 0 to 8: higher scores mean more SCT symptoms. In our study, reported SCT-CBCL scores had an acceptable level of reliability (a Cronbach’s α score of .7).

Behavioral Measures

We used the Strengths and Difficulties Questionnaire (SDQ) to assess potential behavioral problems in our population of children (Goodman, 1997). The SDQ includes 25 questions organized into five separated subscales. They are used to evaluate emotional problems, conduct problems, hyperactivity/inattention, peer relationship problems, and pro-social behavior. Each subscale ranges from 0 to 10. The Total Difficulties scale is scored from 0 to 40 and is generated by summing the scores of all scales except the scale of pro-social behavior. Higher SDQ scores reflect more behavioral problems. The internal consistency of the replies to this questionnaire was acceptable (Cronbach’s α = .79).

The ADHD status of each child was established using two separate criteria. First, parents were asked whether ADHD had been diagnosed by a clinician. Second, teachers were asked to complete the questionnaire in the ADHD Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV [ADHD-DSM-IV]; American Psychiatric Association [APA], 1994; APA, 2002) (ADHD Rating Scale-IV; DuPaul, Power, Anastopoulos & Reid, 1998). The ADHD-DSM-IV considers 18 symptoms categorized in two separate groupings: inattention (nine symptoms) and hyperactivity/impulsivity (nine symptoms). Each ADHD symptom is scored on a 4-point scale, depending on the frequency of its expression (0 = never or rarely; 1 = sometimes; 2 = often; 3 = very often). We used the inattentive and hyperactive/impulsive scales as continuous variables. Each scale ranges from 0 to 27; higher scores mean more ADHD symptoms. The internal consistency of the responses to this questionnaire in our study was acceptable (Cronbach’s α = .93).

Symptoms of Dyslexia and Academic Problems

Four items considered symptoms or indicators of dyslexia were used to detect the condition in the second-, third-, and fourth-grade primary schoolchildren (7-10 years of age). Yes/no answers were provided by teachers to the following questions: “makes a lot of mistakes in reading: omissions, substitutions, additions, inversion”; “has difficulties in reading comprehension (decoding difficulties)”; “when writing, makes many spelling mistakes compared with the rest of the class”; and “finds sequences difficult (months of the year, the seasons, the alphabet etc.).” Regarding academic problems, teachers answered the question “how would you rate the academic performance of this child?” with one of the following answers: 1 = poor; 2 = unsatisfactory; 3 = satisfactory; 4 = good; 5 = excellent. We recoded Options 3 to 5 as 0 (no academic problems) and option 0 or 1 as 1 (academic problems).

Sociodemographic Variables

Sociodemographic data including age, sex, parental educational levels (primary, secondary, and further/higher), parental occupation (self-employed/employed/unemployed), marital status (married, single, divorced/widowed), siblings at birth (yes/no), adopted children (yes/no), prematurity (yes/no), low birth weight (yes/no), maternal smoking during pregnancy (yes/no), and current second-hand smoke exposure at home (yes/no) were collected by the BREATHE baseline questionnaire, which was filled out by parents. In the same questionnaire, parents were asked whether their children had been clinically diagnosed with ADHD by a medical doctor. In addition, for each home address, we extracted the Urban Vulnerability Index, which is a measure of neighborhood socioeconomic status (SES) at the census-tract level (median area of 0.08 km² for the study area). This index is based on 21 indicators of urban vulnerability grouped into four themes that was developed based on the Spanish 2001 census data: sociodemographic vulnerability (five indicators), socioeconomic vulnerability (six indicators), housing vulnerability (five indicators), and subjective perception of vulnerability (five indicators).

Statistical Analysis

We initially calculated the prevalence of SCT in our study population considering the cut-off as all raw scores above in the 94th percentile, in accordance with previous general population studies (Barkley, 2012). Afterward, we considered the social, clinical, and behavioral determinants of SCT symptoms, using a two-step procedure. First, we performed bivariate analysis using analysis of variance (ANOVA), Student’s t test, or the chi-square test, depending on the type of variable. All variables that showed a p value < .10 were included in the final models. Then, all the variables selected from the bivariate analysis were included in multivariate regression analysis to study their association with SCT symptoms in a multivariate regression model. We used negative binomial regression to analyze the SCT symptoms as a continuous variable to account for overdispersion of the counting variables. All statistical analysis was carried out using STATA 12 software (Stata Corporation, College Station, Texas) (Stata Corp, 2011).

Results

In our study, 20 participants (11%) showed SCT symptoms above the 94th percentile (Figure 2). In the entire sample (N = 183), the mean (M) SCT score was 1.30 (and SD 1.59).

Figure 2.

Distribution of SCT symptoms.

In the bivariate analysis, we found more SCT symptoms in boys, children whose father was unemployed, those whose maternal educational level was lower, children living in areas with a high socioeconomic vulnerability index, children reportedly exposed to smoking during pregnancy, children currently exposed to tobacco at home, and also children with a clinical diagnosis of ADHD (Tables 1 and 2). In addition (Figure 3), we compared the distribution of SDQ subscales, and (Figure 4) ADHD-DSM-IV, symptoms of dyslexia, and academic problems according to high (>94th percentile) and normal SCT symptoms. We found that children showing higher SCT symptoms scored significantly higher than those in the normal range for the emotional problems, hyperactivity/inattention, and peer relationship problems SDQ subscales. In addition, children with higher SCT symptoms showed significantly higher inattentive and hyperactive symptomatology (ADHD-DSM-IV), more symptoms of dyslexia, and more academic problems than children in the normal range.

Table 1.

Distribution of SCT Symptoms and Sociodemographic Data.

	% (n)	SCTM (SD)	p
Sex
Girls	47.4 (87)	1.01 (1.36)	.019
Boys	52.6 (96)	1.55 (1.74)	.019
Siblings at birth
Yes	78.8 (142)	1.4 (1.65)	.126
No	21.1 (41)	0.94 (1.18)	.126
Adopted
Yes	7.2 (167)	1.3 (1.31)	.975
No	92.7 (13)	1.28 (1.60)	.975
Marital status
Married	89.0 (162)	1.27 (1.50)	.568
Single, divorced, or widowed	10.9 (21)	1.50 (1.78)	.568
Paternal educational level
Primary or less	10.6 (19)	2.1 (1.87)	.149
Secondary	30.1 (54)	1.45 (1.70)
University education	59.2 (106)	1.06 (1.42)
Paternal occupation
Self-employed	31.6 (58)	1.39 (1.81)	.056
Employed	58.9 (108)	1.22 (1.44)
Unemployed	9.8 (17)	1.54 (1.97)
Maternal educational level
Primary or less	9.8 (18)	1.89 (2.14)	.006
Secondary education	20.9 (38)	1.66 (1.85)
University education	69.1 (125)	1.1 (1.36)
Maternal occupation
Self-employed	16.6 (31)	1.35 (1.55)	.364
Employed	65.6 (120)	1.16 (1.51)
Unemployed	17.6 (32)	1.86 (1.86)
Socioeconomic vulnerability
Low vulnerability	32.8 (60)	1.1 (1.58)	.057
Medium vulnerability	45.9 (84)	1.14 (1.37)
High Vulnerability	21.3 (39)	1.91 (1.87)

Note. SCT = sluggish cognitive tempo.

Table 2.

Distribution of SCT Symptoms; and Clinical History and Tobacco Exposure.

	% (n)	SCTM (SD)	p
Prematurity
Yes	7.6 (14)	1.92 (2.33)	.925
No	92.4 (169)	1.26 (1.54)	.925
Low birth weight (2,500 g)
Yes	9.4 (17)	1.91 (2.22)	.168
No	90.6 (156)	1.25 (1.53)	.168
Maternal smoking during pregnancy
Yes	9.8 (17)	2.83 (2.2)	<.001
No	90.2 (166)	1.18 (1.5)	<.001
Current second-hand smoke exposure at home
Yes	12.4 (22)	2 (1.69)	.059
No	87.6 (161)	1.24 (1.56)
Overweight (BMI > 25)
Yes	28 (51)	1.46 (1.55)	.391
No	72 (132)	1.21 (1.59)	.391
ADHD diagnosis^a
Yes	5.5 (10)	3.1 (2.02)	<.001
No	94.5 (173)	1.19 (1.50)	<.001

Note. SCT = sluggish cognitive tempo; BMI = body mass index.

Diagnosis reported by parents and performed by a clinician.

Figure 3.

Strengths and Difficulties Questionnaire and significant associations with symptoms of SCT (as a categorical variable: high SCT vs. low SCT).

Figure 4.

Inattention and hyperactive symptoms from ADHD-DSM-IV list, dyslexia symptoms, academic performance, and significant associations with SCT symptoms (as a categorical variable: high SCT vs. low SCT).

Table 3 presents the multivariate associations between SCT symptoms and those sociodemographic, clinical, and behavioral determinants significantly associated with SCT symptoms in the bivariate analysis. In fully adjusted models, we found a higher risk of SCT symptoms in children living in areas with a high socioeconomic vulnerability index (incidence rate ratio [IRR] = 2.34; 95% confidence interval [95% CI] [1.50, 3.66]; p < .001), children with higher emotional problems (IRR = 1.19; 95% CI [1.02, 1.38]), hyperactive problems (IRR = 1.30; 95% CI [1.13, 1.50]), peer relationship problems (IRR = 1.26; 95% CI [1.08, 1.47]), children with higher inattentive symptomatology (IRR = 1.03; 95% CI [1.01, 1.06]), and children with dyslexia symptoms (IRR = 1.20; 95% CI [1.04, 1.38]). We also found a marginally increased risk of SCT symptoms in those children currently exposed to tobacco at home (IRR = 1.80; 95% CI [1.05, 3.06]; p = .032).

Table 3.

Fully Adjusted Associations Between SCT Symptoms and SDQ Scales, Hyperactivity, Inattention and Dyslexia Symptoms, Academic Performance, Sociodemographic Data, and Medical History.

	IRR	95% CI	p
Sex (ref. male)	0.80	[0.56, 1.13]	.202
Maternal educational level (ref. primary or less than primary)
Secondary	1.50	[0.81, 2.78]	.198
University	1.63	[0.85, 3.12]	.139
Paternal occupation (ref. self-employed)
Employed	1.27	[0.86, 1.88]	.230
Unemployed	1.05	[0.57, 1.90]	.880
Socioeconomic vulnerability index (ref. low vulnerability)
Medium vulnerability	1.17	[0.77, 1.78]	.456
High vulnerability	2.34	[1.50, 3.66]	<.001
Maternal smoking during pregnancy (ref. no)	1.32	[0.78, 2.24]	.304
Current second-hand smoke exposure at home (ref. no)	1.80	[1.05, 3.06]	.032
ADHD diagnosis (ref. no)	1.20	[0.60, 2.32]	.611
Emotional problems (SDQ)	1.19	[1.02, 1.38]	.023
Hyperactivity/inattention (SDQ)	1.30	[1.13, 1.50]	<.001
Peer relationship problems (SDQ)	1.26	[1.08, 1.47]	.003
Inattention symptoms (ADHD-DSM-IV)	1.03	[1.01, 1.06]	.007
Dyslexia symptoms	1.20	[1.04, 1.38]	.010
Academic problems (ref. no academic problems)	0.97	[0.57, 1.64]	.899

Note. SCT = sluggish cognitive tempo; SDQ = strengths and difficulties; IRR = Incidence rate ratio; CI = Confidence interval; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV).

Discussion

We analyzed our data using the same principles as the most recent studies in this field: SCT as a suite of symptoms and its characteristics independently of ADHD (Barkley, 2012, 2013). The results of our study indicate an SCT prevalence of 11%. Moreover, SCT symptoms are significantly associated with a high socioeconomic vulnerability index, current second-hand smoke exposure at home, inattentive symptoms (assessed by ADHD-DSM-IV), symptoms of dyslexia, and emotional and peer relationship problems (assessed by SDQ).

In our study, we found that 11% of the participants presented a high level of SCT symptoms. This prevalence is higher than a previous study that was carried out in American children (6%; Barkley, 2013). It remains unclear why the prevalence in our sample is higher, although one reason could be the characteristics of our sample, which is more limited in age (7-10 years) than the previous study (including 6-17 years of age; Barkley, 2013). SCT symptoms are usually detected at an age when demands made by the environment (academic and social) start to increase, and at which parents are more sensitive to such demands.

Among the different sociodemographic determinants included in the present analysis, a high socioeconomic vulnerability index is associated with SCT symptoms. Previous studies found SCT symptoms in adults and their relation with low socioeconomic status (Barkley, 2012). It is possible that the parents of our sample show SCT symptoms. Our results follow the same lines as previous studies (Barkley, 2013, 2014; Becker, Langberg, Luebbe, Dvorsky, & Flannery, 2014; Becker, Luebbe, et al., 2014; Marshall et al., 2014; Moruzzi, Rijsdijk, & Battaglia, 2014) in showing that psychosocial problems have a greater influence on SCT symptoms than on ADHD symptoms. As concluded in the only twin study that examined genetic and environmental contributions to SCT and ADHD, SCT symptoms are somewhat more influenced than either inattention or hyperactivity-impulsivity by non-shared environmental factors (Moruzzi et al., 2014). More research is needed to elucidate the etiology of SCT, attending to biologically based contributions as well as possible environmental factors.

Surprisingly, we did not find significant differences in dimensional symptoms of SCT associated with sex, although such a relationship was previously described (Becker et al., 2016). We only found differences in the bivariate analysis (boys > girls); although these differences did not remain statistically significant in the multivariate models.

This is the first study that found an association between SCT symptoms and both tobacco use during pregnancy and tobacco exposure at home at the age of the SCT symptom assessment; although only the positive association with current second-hand smoke exposure at home remained significant in the multivariate regression analysis. Previous studies suggested different mechanisms to explain the neurotoxic effects associated with tobacco exposure, particularly during pregnancy, as a period of increased vulnerability for the development of the child (Buka, Shenassa, & Niaura, 2003; Olds, 1998; Weitzman, Byrd, Aligne, & Moss, 2002). Active maternal smoking during pregnancy has been associated with a higher risk of behavioral disorders in children. These disorders range from personality temperament, neuropsychiatric outcomes such as attention disorders (ADHD) and conduct disorder (CD), to lowered cognitive capacities (Huizink & Mulder, 2006; Linnet et al., 2003; Weitzman et al., 2002).

We observed that children with a high degree of SCT symptoms also presented emotional problems, peer relationship problems, and hyperactive and inattentive symptomatology (assessed by ADHD-DSM-IV as well as by SDQ). These findings are in agreement with previous studies that report consistent correlations between SCT and symptoms of internalization (anxiety/depression), social isolation, reduced information processing, and social avoidance (in questionnaires filled in both by parents and teachers; Buka et al., 2003; Carlson & Mann, 2002; Milich et al., 2001; Penny et al., 2009; Schatz & Rostain, 2006; Skirbekk et al., 2011). These findings are independent of symptoms of ADHD. Finally, we also found a positive association between dyslexia symptoms and SCT symptoms. These findings are consistent with a previous study that reported a positive association between SCT symptoms and learning disorders (Camprodon-Rosanas et al., 2016).

Evidence indicates that SCT can overlap with ADHD (Barkley, 2013); but it is also now clear that SCT symptoms are empirically distinct from symptoms of ADHD (Barkley, 2012, 2013). In the study of American children (Barkley, 2013), more than half (59%) of the SCT cases also exhibited ADHD. The overlap was mostly with ADHD DSM-IV subtypes that exhibit significant inattention symptoms, rather than with the hyperactivity-impulsivity type. Furthermore, in our study, we also found higher inattention symptoms in the SCT group. However, one previous study suggested that SCT symptoms were independent of ADHD symptoms (Barkley, 2013, 2014; Becker et al., 2016). Because of this apparent overlap, further research is warranted to develop better tools to disentangle pure SCT from ADHD symptomatology.

The present study is affected by a number of limitations. One of the main limitations is that we found that participants in the present study had a higher level of maternal educational than non-participants. Therefore, the generalizability of our findings may be affected by selection bias in that those children who participated in our study were different from those who did not participate (but were participants of the BREATHE study) with respect to maternal educational level. However, the Urban Vulnerability Index at the home address was not associated with school participation in the present study, which might suggest that socioeconomic status was less likely to be a major predictor of participation. Another potential limitation of the present study is the scale that we used to assess SCT symptoms. We used SCT-CBCL, which is a short scale derived from just four items. These four SCT-CBCL items represent four symptoms that have also been assessed in other studies using different questionnaires (Becker, Langberg, et al., 2014; Hartman, Willcutt, Rhee, & Pennington, 2004; McBurnett et al., 2001; Skirbekk et al., 2011). The SCT-CBCL scale has shown moderate to high positive correlations with more extensive scales of SCT symptoms (Penny et al., 2009). In addition, SCT-CBCL is capable of differentiating SCT symptoms from the lists of symptoms associated with ADHD, oppositional defiant disorder, anxiety, and scales of depression (Burns et al., 2013). In addition, the internal consistency (estimated using Cronbach’s α) of the SCT-CBCL scores obtained in our study was .71, which is within the same range as in previous studies (Cronbach’s α ranging from .65 to .86; Hartman et al., 2004; Langberg et al., 2014; Watabe, Owens, Evans, & Brandt, 2014). Recent studies (del Mar Bernad, Servera, Grases, Collado, & Burns, 2014; Burns et al., 2013; Lee et al., 2014) have validated a scale of eight items for the evaluation of symptoms of SCT in the Spanish population. This eight-item scale showed adequate reliability and validity.

Another limitation of the present study is the age range of the participants. Although our sample is representative for ages between 7 and 10 years, our results can only be generalized to this age group. Finally, to elucidate the differences between SCT and ADHD with more precision, it would be necessary to analyze the data using additional groupings, as follows: SCT + ADHD, SCT + no ADHD, no SCT + ADHD, no SCT + no ADHD. It was not possible to conduct such analysis in our study because the number of participants in each group was too low (n = 4, n = 16, n = 15, n = 147, respectively).

In summary, in a sample of children aged between 7 and 10 years from schools in Barcelona, Spain, with a prevalence of SCT of some 11%, we show that those children with more SCT symptoms show the following characteristics: They live in an area with a high socioeconomic vulnerability index; they exhibit more symptoms of inattention, emotional problems, and problems in relating with peers; and they have more symptoms of dyslexia.

Footnotes

Acknowledgements

We thank all the families who participated in the study for their altruism and particularly the schools Antoni Brusi, Baloo, Betània–Patmos, Centre d’Estudis Montseny, Col·legi Shalom, Costa i Llobera, Escola El Sagrer, Els Llorers, Escola Pia de Sarrià, Escola Pia Balmes, Escola Concertada Ramon Llull, Escola Lourdes, Escola Tècnica Professional del Clot, Ferran i Clua, Francesc Macià, Frederic Mistral, Infant Jesús, Joan Maragall, Jovellanos, La Llacuna del Poblenou, Lloret, Menéndez Pidal, Nuestra Señora del Rosario, Miralletes, Ramon Llull, Rius i Taulet, Pau Vila, Pere Vila, Pi d’en Xandri, Projecte, Prosperitat, Sant Ramon Nonat–Sagrat Cor, Santa Anna, Sant Gregori, Sagrat Cor Diputació, Tres Pins, Tomàs Moro, Torrent d’en Melis, and Virolai. We also thank the ESCAPE project for the design and supervision of the modeling of air pollution. Furthermore, we thank Xavier Mayoral for technical development of the n-back test, and Cecilia Persavento, Judit Gonzalez, Laura Bouso, and Pere Figueras for contributing to the fieldwork. We are grateful to James Grellier and Christopher Evans for language revision.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The research leading to these results has received funding from the European Research Council under the ERC Grant Agreement (ERC-AdG 2010 GA#268479).

Author Biographies

E. Camprodon-Rosanas, MS, is a psychologist of Sant Martí-La Mina Child and Adolescent Mental Health Service (CAMHS) from Barcelona, Spain. Professor of the Master of Child and Adolescent Psychiatry from the Universidad Autonoma de Barcelona. Her research interest include the study of the features and neuropsychological profile associated with SCT symptoms.

N. Ribas-Fitó, MD, PHD, is a child and adolescent psychiatrist and coordinator of Child and Adolescent Mental Health (CAMHS). She formerly trained and worked as an Epidemiologist. Her curent research areas of interest include adolescent borderline personality and trauma.

S. Batlle Vila, MS, is a psychologist and coordinator of Sant Martí-La Mina Child and Adolescent Mental Health Service (CAMHS) from Barcelona, Spain. Professor of the Master of Child and Adolescent Psychiatry from the Universidad Autonoma de Barcelona. His research interest include the attention neuropsychology. He has designed a paper-pencil cancellation test to the selective and sustained attention (TASS) assessment.

C. Persavento works as a research technician at the Center for Research in Environmental Epidemiology (CREAL) responsible for data collection and field work, her main interest is child health and neurodevelopmental

M. Alvarez-Pedrerol, PhD, works as a project manager at the Center for Research in Environmental Epidemiology (CREAL). She is interested in environmental and neurodevelopmental epidemiology,

J. Sunyer, MD, PhD, is an epidemiologist who works on research on the health effects of environmental exposures in order to inform prevention and abatement initiatives. He is currently Joint Scientific Director and coordinator of the Child Health Research Program at CREAL (Center for Research of Environmental Epidemiology) in Barcelona and Professor of Preventive Medicine at Pompeu Fabra University (UPF, Barcelona).

J. Forns, MPH, PhD, is a research epidemiologist at Research Center of Environmental Epidemiology (CREAL). His research interests are the study of social and environmental determinants of neuropsychological development.

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