The Arabian Gulf countries have undergone rapid industrialisation and a significant elevation in standard of living in the past decade due to hydrocarbon exploration and their location as a transhipment hub. Socioeconomic changes have also caused transformations in their demographic landscape. In other words, this region is currently in its second phase as demography in transition, characterized by high birth rates, the plasticity of life and the resulting “youth bulge” [11].
Newer studies that have examined the well-being of children and adolescents have indicated that the region is rife with neurodevelopmental disorders, including ADHD [11]. Although a large number of studies have focused on the description and phenomenology of ADHD, there is a dearth of studies that have examined the neuropsychological status of children with this condition [32]. Conceptually, the core symptoms of ADHD, namely inattention and executive hyperactivity, appear to be accompanied by impairment in the processing of information which, in turn, could be due to inattention or domains such as temporal organisation of behaviour, namely executive functioning [33].
To date, the neuropsychological profile of ADHD that has been widely documented elsewhere has received little attention from the Arabian Gulf population. As such, this study has embarked on a comparison of the neuropsychological profiles of children with ADHD and neurotypical children, focussing on differences in clinical risk factors and sociodemographic background, and examining whether the integrity of sleep, screen time, and comorbidity have associations with performance in cognitive indices. This comparison with healthy children is justified due to the lack of normative data for neuropsychological measures among these age groups.
The current study from two tertiary centres located in northern Oman identified 70 children with ADHD who met the criteria of DSM-5 for the condition. Most of the children were of mixed type: they had both inattention and hyperactivity. Many of the participants were drug-nave with some others on nonpharmacological treatment or complementation with supplements.
Demographic, Socioeconomic, and Clinical Characteristics of the Study Cohort
The first objective was to compare the two cohorts of children based on clinical risk factors and sociodemographic background. It appeared that the two cohorts did not differ in terms of age, sex, place of residence, occupations of the mother, and whether they reported low birth weight or having parents with consanguineous marriages.
The Oman fertility rate per woman until the end of 2020 was recorded as 2.67 and the average household in Oman consists of 7.2 people per household [34]. Therefore, it may be worthwhile to examine the role of the number of siblings and its relation to the development of ADHD. The present data suggest that with an increase in the number of siblings, there was an increase in the prevalence of ADHD, suggesting that those with ADHD are more likely to come from multi-child families (77.1% having more than 3 siblings compared to 52% of the neurotypical controls). Although this trend deserves further scrutiny, it intuitively indicates that the number of children in the household can create environments that encourage the development of ADHD.
Another significant variable was the occupation of the father, which showed that all fathers of children with ADHD were employed compared to 63% of fathers of neurotypical children. This may suggest that stay-at-home fathers may be a protective factor, however, further studies in this area are required.
Although it is difficult to operationalise what constitutes sociodemographic status in emerging economies such as Oman, this study attempted to shed light on the relationship between socioeconomic status (SES) and ADHD. For the present study, socioeconomic status was quantified by monthly income. In terms of families receiving income support (those not likely to have jobs or those experiencing financial dependence), neurotypical children were surprisingly more in number in this category of SES. However, ADHD appeared to be more prevalent in the high-income group (monthly income of more than 2500 USD according to the APA’s classification of SES). It should be noted that in the literature, there is no consensus on whether SES is related to the development of ADHD [35-38].
Previous studies in Oman have suggested that sleep-wake cycles and sleep apnea problems are likely to be common among children with ADHD [39]. The current study showed that the two cohorts appeared to differ, with 56% of the control group sleeping well and awake refreshed compared to 10% reported by those in the ADHD group. Furthermore, 30% of those in the ADHD group reported snoring compared to 13% in the neurotypical group. Both previous research and the present study support the view that sleep problems could be a consequence or a contributing factor to ADHD.
Previous research has extensively suggested that high-risk pregnancies, such as exposure to gestational diabetes mellitus [40], hypertensive disorders of pregnancy [41], maternal obesity, autoimmune disorders, and asthma [42], can increase the risk of the development of ADHD in their offspring. The results of the current study also explored the type of pregnancy experienced by mothers of the children in the sample, showing that 16% of the children with ADHD were delivered through high-risk pregnancies compared to neurotypical children.
A hypothesis emerging in the literature and this study is that ADHD has various comorbidities such as conduct disorder (7.1%), scholastic skill problems (73%), and externalisation behavioural problems (20%). Previous studies have also suggested that screen time use is common among children with ADHD [18]. A meta-analysis conducted in 2022 suggests that indulgence in screen time usage may be associated with attention problems [43]. This study suggests that while children with ADHD spent more time playing video games (27% versus 10%), neurotypical children spent more time watching television (90% versus 73%).
Differences in Intellectual Capacity and Cognitive Function
The second objective of the current study was to compare intellectual capacity in various cognitive domains, including working memory, visual perception, vigilance, learning and remembering, and verbal fluency. Interestingly, the cohort sample did not differ on the indices of intellectual capacity. Previous studies have suggested that there is a relationship between intellectual capacities and cognitive domains [44].
From the present study, in terms of the neurocognitive measures implemented, the cohort appears to differ significantly on all indices examined except for the forward digit span. Existing literature suggests that forward digit span, at times thought to be underlined by complex information processing, appears to be more dysfunctional in children with ADHD. Furthermore, when considering the dichotomy of digit span forward versus backward, research has suggested that only digit span forward is a predictor of attention problems [45]. However, the appearance of digit span as one of the strongest indicators of impairment in children with ADHD does not appear to hold in Oman, although the comparison here was not to establish impairment, but to compare performance with those that are neurotypical.
Examination of whether intellectual capacity and cognition are affected by factors such as sleep, screentime, and comorbidity.
The third hypothesis is to investigate factors associated with intellectual and cognitive status. For the present study, the role of sleep patterns was explored. Overall, when comparing those who slept well and those who did not, there were no significant differences in sleep indices except for verbal fluency and verbal working memory (Digit span backwards).
Similarly, another factor that was examined to explore the association between cognition and intellectual capacity was screen time. This study suggests that screen time, whether watching television or playing video games, was not of notable significance.
In terms of comorbidities, significant differences were found in verbal working memory (digit span backwards), indices of visual perception and vigilance (dot cancellation test), short- and long-term verbal memory and verbal fluency.
Limitations
Studies of this sort are likely to come with their own set of limitations. First, this is a convenient sample among consecutive patients who were referred to a tertiary care centre. It is possible that this was a self-selected group and not a global representation of the spectrum of ADHD in terms of severity or other demographics. Second, due to the lack of normative data for neuropsychological measures, most studies of this nature tend to employ a control group. Although the controls did not have a history of ADHD, some were found to have conduct issues. Since the boundary between conduct disorder and ADHD is often blurred, future studies should be more precise in delineating what constitutes a clinical population within a control group. Third, some of the outcome variables such as sleep, screen time, and comorbidity were elicited through yes/no questions. Since there are many instruments to measure these indices, future studies could employ more well-established measures, including semi-structured interviews for comorbidity and screen time. Furthermore, the gold standard for sleep detection is through sleep laboratories, and this was not carried out in the present study for logistical reasons.
Lastly, although the sample size may appear noticeably low compared to other case-control studies. However, neuropsychological tests are typically time consuming and sample sizes such as the present have been frequently featured in the literature [46].