The Contribution of Atypical Sensory Processing to Executive Dysfunctions, Anxiety and Quality of Life of Children with ADHD

Abstract

The study examined whether atypical sensory processing (ASP) deteriorate executive function (EFs), anxiety and quality of life (QoL) of children with ADHD. Participants were 28 boys with ADHD; 31 with ADHD + ASP; 56 with typical development. Parents completed the Short Sensory Profile (SSP); BRIEF; RCMAS (anxiety) and PedsQoL. Boys with ADHD + ASP had the lowest EFs, highest anxiety and lowest QoL. ASP predicted lower social QoL; Anxiety predicted lower emotional QoL; reduced EFs predicted lower school QoL. ASP in ADHD may increase anxiety, reduce EFs and QoL. ASP should be screened with respect to child’s cognitive/emotional status and daily function.

Keywords:

• Sensory processing
• executive functions
• anxiety
• quality of life
• attention deficit hyperactivity disorder

Introduction

Our daily environments provide us with an ongoing sensory information. The enormous information from all sensory systems is integrated, processed and modulated in the central nervous system (CNS). While most people show normal sensory processing, about 5–15% show atypical sensory processing (ASP) (Engel-Yeger, 2010; Román‐Oyola & Reynolds, 2013), expressed in hyper or hypo sensitivity to sensory input. ASP results from an imbalance between excitation and inhibition of sensory input in the CNS. According to Dunn’s model (Dunn, 1999), the interaction between the neurological threshold to sensory input (that ranges from low to high) and the individual’s behavioral strategy to deal with this threshold (passive or active) yields four sensory processing patterns: (1) sensory seekers – individuals with hyposensitivity who actively seek for activities and environments with intense sensory input (such as extreme sport; spicy food; parties), to cope with their high threshold. (2) low registration – individuals with hyposensitivity who apply a passive strategy (do not actively seek for intense sensations), and thus miss information or seem withdrawn. (3) sensory avoiders – individuals with hypersensitivity who actively limit their exposure to stimuli or activities to avoid the uncomfortable sensations (for example, wear long sleeves in the summer) (4) sensory sensitive individuals who use a passive strategy – although they experience discomfort with sensations, they do not actively eliminate their exposure to the disturbing stimuli.

The inability of individuals found in the extremes of these four patterns to properly perceive and regulate the incoming sensory information, may impair the person’s interaction with the physical and human environments, impair daily function, social interaction, and therefore lead to, a reduced sense of control, frustration, anxiety (Engel-Yeger & Dunn, 2011), to behavioral regulation difficulties (Mimouni-Bloch et al., 2018) and to reduced quality of life (QoL) (Engel-Yeger, 2021).

QoL is defined as the individuals’ subjective perception of their position in life as evidenced by their physical, psychological, and social functioning (World Health organization, World Health Organization, 2001). QoL serves as one of the main outcome measures of intervention efficacy (Lu et al., 2020). Based on the International Classification of Functioning Disability and Health (ICF), health professions should refer to the interaction between health, body functions, ability to perform and participate in daily activities, and QoL (World Health Organization, 2001), in order to improve intervention in terms of improving the person’s daily life context. Hence, elaborating the knowledge about the relations between body functions such as ASP, anxiety, behavioral regulation and daily life, may optimize intervention for populations in which these body functions are frequently impaired (Bruchmüller et al., 2012).

ASP, anxiety and behavioral regulation difficulties are prevalent in children with Attention Deficit Hyperactive Disorder (ADHD)) Koziol & Budding, 2012; Pfeiffer et al., 2015). ADHD is one of the frequently diagnosed neurodevelopmental disorder among school aged children. Its prevalence is 2-7% with an average of around 5% (Mechler et al., 2022). ADHD is characterized by persistent patterns of inattention, distractibility and impulsivity that are not appropriate to the age of development and directly interfere with social, academic, and functional outcomes (American Psychiatric Association, American Psychiatric Association, 2013; Tarakçıoğlu et al., 2019). Insufficient levels of dopamine and norepinephrine, mainly in the prefrontal cortex affect the high cognitive abilities named “Executive Functions” (EFs), which are considered as the main cause of behavioral dysregulation in ADHD (Adams et al., 2015; Kamigaki, 2019). The term ‘EFs’ refers to a set of self-regulatory capacities that enable the performance of goal directed tasks: planning, decision making, working memory, response monitoring, insights, and self-regulation. These components work interactively and support the person’s ability to function in multi-processing tasks and react adaptively to environmental demands (Gioia et al., 2000; Willcutt et al., 2005). Therefore, deficits in EFs may restrict regulatory behavior, and thus affect participation and QoL (Engel-Yeger & Rosenblum, 2021; Schwörer et al., 2020).

Two additional factors that may contribute to the dysregulated behavior are ASP and emotional difficulties, mainly anxiety. Both ASP and anxiety are prevalent in ADHD. Anxiety in children with ADHD is manifested in objective physiologic measures, such as high salivary cortisol level and enhanced electro dermal activity-EDA and in subjective measures, as parents’ reports (Lane et al., 2010; Lane & Reynolds, 2019). Anxiety in children with ADHD is known to negatively affect their daily function and their participation in various life settings (Wu et al., 2022). These impacts may be enhanced in the presence of ASP as a result from atypical neural networks that connect sensory and limbic areas. The impaired sensory and emotional modulation may be manifested in hyper arousability, “fight or flight” behavior and in exaggerated emotional responses when facing the unpleasant sensory input (Pryweller et al., 2014). This emotional load may also cause cognitive load (the mental resources and efforts required for performing tasks) and affect EFs. Studies highlight that among individuals with ASP, the hyper vigilance and stress that result from the inconvenient interaction with the environment via the sensory systems, may lead to attention problems, to distractibility, to disorganization (Shields et al., 2016; Soler et al., 2019). These difficulties characterize children with ADHD (Diagnostic and Statistical Manual of Mental Disorders [DSM-5th] American Psychiatric Association, 2013). Not only that ASP, anxiety and difficulties in EFs are related (Gürkan et al., 2010; Mimouni-Bloch et al., 2018; Tsujii et al., 2020), they also worsen ADHD symptoms (Shimizu et al., 2014) and reduce daily function and QoL in children with ADHD (Crow, 2019; Jarrett & Ollendick, 2008; Schwörer et al., 2020; Shirkhani et al., 2020).

Yet, studies mainly refer to the prevalence and characteristics of ASP in ADHD (Engel-Yeger & Ziv-On, 2011; Mimouni-Bloch et al., 2021; Reynolds & Lane, 2009) and to differences between ASP and ADHD (Van Hulle et al., 2012, Yochman et al., 2013). A lacuna exists regarding the relations between the triad body functions – ASP, anxiety and EFs and their implications for QOL in children with ADHD. Moreover, the knowledge about the contribution of modulation comorbidities of ASP to inherent characteristics as EFs difficulties, to anxiety and to QoL should be elaborated. Moreover, as mentioned above, QoL is a main outcome measure of intervention efficacy (Lu et al., 2020). Therefore, this study (1) compared EFs, anxiety and QoL between children with ADHD, ADHD + ASP and controls with typical development; (2) examined the correlations between EFs, anxiety and QoL in each group; (3) examined the contribution of group (ADHD, ADHD+ ASP, controls), EFs and anxiety to the prediction of QoL domains; (4) examined whether ASP mediates between EFs, anxiety and QoL in children with ADHD+ ASP, meaning that with the mediation of ASP, the relation between EFs, anxiety and QoL would be stronger.

It was hypothesized that ASP would enhance EFs difficulties, anxiety and reduce QoL. This would be derived from examining the following hypotheses: (1) children with ADHD+ ASP would have significantly greater EFs difficulties, anxiety and lower QoL than children with ADHD, and controls with typical development; (2) In each group, greater difficulties in sensory processing would significantly correlate with greater difficulties in EFs, enhanced anxiety and reduced QoL; (3) Being included in the ADHD+ ASP group would be the main predictor of reduced QoL; (4) In children with ADHD+ ASP, ASP would be a significant mediator between EFs, anxiety and QoL.

In order to better understand the implications of dysregulation in ADHD and how it affects daily life, this study used ecologically valid measures, which reflected ASP and EFs in children’s real-life situations, based on their parents’ reports.

Materials and methods

Study design

A cross-sectional study design was performed after receiving the approval by the ethics committee (038/15) (approval number: 038/15).

Participants

According to G-GPOWER program an effect size of 0.25, p = .05 and power of 0.80, each group should include 40 participants (a total of 120 participants). However, due to the study time limit and the difficulties in recruiting children with ADHD or ASP alone, the number of participants in each group was lower than expected.

This cross-sectional study included 115 boys aged 8–11.9 years and their parents (based on the higher prevalence of ADHD among boys) (Rucklidge, 2010). Participants were divided into three groups: 28 children with ADHD; 31 children with ADHD and ASP (based on the cut off scores of “probable difference” of the Short Sensory Profile) (Dunn, 1999); 56 children with typical development, with no ASP, who were recruited to provide a baseline for the QoL scores (since norms exist for the other used measures). ADHD diagnosis was performed by neuro-pediatricians and based on the criteria of the DSM-5th (American Psychiatric Association, 2013). All children studied in regular education schools. Exclusion criteria included: chronic or severe diseases/psychiatric disorders; medication treatment that impact the central nervous system (except for medication for ADHD). Children who use medications for reducing ADHD symptoms (such as methylphenidate) were asked not to use the medications on the day of the study. Table 1 summarizes participants’ sociodemographic data.

Table 1. Participants’ Sociodemographic Data.

		ADHD (n = 28)	ADHD + ASP (n = 31)	Healthy controls (n = 56)
		Mean (SD)	Mean (SD)	Mean (SD)
Age (years)		9.5 (1.42)	9.67 (1.27)		F3=.36, NS
		%	%	%	Χ6^2
Parents’ income	Low	17.9	9.7	8.9	7.18 NS
	Average	28.6	29	32.1
	High	53.6	61.3	58.9
Mothers’ education	Elementary school	7.1	3.2	0	15.04 NS
	High school	39.3	25.8	19.6
	Professional	3.6	12.9	21.4
	Academic	50	58.1	58.9
Secular		93.5	100	100
Religious		6.5	0

ADHD: attention deficit hyperactivity disorder; SD: standard deviation; NS: not significant.

As presented in Table 1, no significant differences were found between the groups in the sociodemographic variables.

Measures

Health Status/Socio-Demographic Questionnaire – gathered information about child’s health to assure child’s inclusion criteria as well as information about factors known to influence child’s development and quality of life, as child’s age; parents’ education level; familial socio-economic level (Didsbury et al., 2016; Ha et al., 2022).

The Short Sensory Profile (SSP, McIntosh et al., 1999) - this parents’ report aims to measure the child’s sensory processing patterns as expressed in daily life. The SSP comprises the 38 items and includes seven sections of sensory processing: Tactile Sensitivity; Taste/Smell Sensitivity; Movement Sensitivity; Visual/Auditory Sensitivity; Auditory Filtering; Low Energy/Weak; and under responsive/Seeks Sensation. Scoring: for each item, parent estimates the child’s behavioral reaction to daily sensory stimuli on a Likert scale from one (always) to five (never). Answers are then summarized to indicate whether the child has ‘typical performance’, ‘probable difficulties’ or ‘definite difficulties’ in each section separately and altogether, according to the SSP norms. SSP demonstrated discriminate validity of >95% in identifying children with or without SPD in various clinical populations including ADHD (McIntosh et al., 1999). In this study we chose to use the SSP rather than the long version of the Sensory Profile. The SSP is more commonly used in research since it enables data collection and analysis in a shorter time. Yet, the SSP provides information about patterns of sensory processing that are essential for answering the research questions and aims. The innumerous studies that used the SSP reflect its high feasibility (e.g. Engel-Yeger, 2010; Williams et al., 2018).

The Behavior Rating Inventory of Executive Functions (Brief)-Parents’ Version: (Gioia et al., 2000) – this measure aims to elicit everyday EF of children of 5–18 years old, as observed by their parents. The BRIEF composes two major index scales: behavioral regulation index (BRI) and metacognition index (MC), in addition to a global executive composite (GEC). Each index is further divided into executive component scales: BRI is composed of inhibition, shift and emotional control scales, whereas MC is composed of initiation, working memory, planning, organization of materials, and monitoring scales. A total of 86 items describes various behaviors in which the parent rates the behavior frequency on a Likert Scale ranging from one(rare) to three (often). Total scores are revised into standardized scores; above 65 points reflect executive impairments. This BRIEF version has good psychometric properties (test re-test reliability: r = 0.86 for GEC, r = 0.88 for BRI, r = 0.84 for MC; Alpha Cronbach = 0.84) (Affrunti & Woodruff-Borden, 2015; Gioia et al., 2000). THE REVISED CHILDREN’S MANIFEST ANXIETY SCALE (RCMAS; Reynolds & Richmond, 2000)– this 37-item report measures the level and nature of anxiety in children and youth aged 6–19 years. The respondent is required to circle either Yes or No, depending on which response is most true for him or her. High scores indicate high levels of anxiety. Using 28 of the 37 items, the RCMAS produces a Total Anxiety score. Because anxiety is thought to be a multidimensional construct, three subscale scores are also frequently computed. The Physiological scale is composed of ten items that assess biological correlates of anxiety including sleep problems, stomach upset, and trouble breathing. The Worry & Oversensitivity scale includes eleven items designed to measure excessive, untargeted worrying, and concern of external pressures. The Social Concern and Concentration scale contains seven items that assess fears of social isolation and difficulty paying attention. The remaining nine items form the Lie scale and are designed to measure social desirability and “faking good.” Good psychometric properties of the RCMAS were reported. Based on the data from the total standardization sample, a T score of 60 corresponds to a cutoff score of 19 (M = 11.70, SD = 6.21). Reports demonstrate the good psychometric properties of the RCMAS: Alpha Cronbach=.82; test-retest reliabilities r = 0.60–0.88; Concurrent Validity: r = 0.78, p < .001) with the Trait Anxiety scale of the State-Trait Anxiety Inventory for Children (STAIC) (Spielberger et al., 1983).

Reynolds (1980) administered the RCMAS to 97 kindergarten children and demonstrated reliability with (a = 0.79 with males, a = 0.85 with females, and a = 0.82 for the total sample). These correlations are high and similarly indicate internal consistency when the RCMAS is used with younger children. THE PEDIATRIC QUALITY OF LIFE INVENTORY (PedsQL) (Varni et al., 2001) is a questionnaire that assesses HRQOL of children and adolescents between the ages of 2 and 18 years. The PedsQL evaluates four domains physical functioning, emotional functioning, social functioning, and school functioning. The three domains of emotional, social, and school functioning comprise a total score for Psychosocial Health Summary Score. In addition, a total scale score is calculated from all items taken together. The PedsQL includes versions to be completed by parents or children. It refers to four age-groups (2–4 years, 5–7 years, 8–12 years, and 13–18 years). All questionnaires use a five-point scale from zero (never a problem) to four (almost always) that describe specific items related to HRQoL over the previous one month period. Scores are reversed and converted into a zero to 100 scale (100 indicates the best HRQOL). In this study, we used the parents’ report. The PedsQL was found to distinguish between healthy children and children with chronic health conditions and showed high internal reliability (Alpha Cronbach of the =0.92) (Varni et al., 2006).

Procedure

After receiving approval from the ethics committee of the (BLINDED), an email with explanation of the study aims and details was sent to occupational therapists and neurologists in private clinics in the north of Israel to recruit children with ADHD. Following the clinicians’ consent to perform the study in their clinic, they were further asked to advertise the study to parents by sending forms calling parents to participate in a study about ADHD and ASP among school aged children. Parents of children with ADHD who responded to the advertisement were invited to the clinic, signed a consent form and completed the socio-demographic questionnaire. Parents whose children answered inclusion criteria were further asked to complete the SSP and the BRIEF in the presence of the study evaluator. Typically developing participants were recruited via advertisement calling for participatants in this study and published in the same geographic area of the study groups. Their parents completed the questionnaires in their homes.

Statistical analysis

All the statistical analyses were conducted using SPSS-25 program. Descriptive statistics was conducted regarding all measures. After approving normal distribution of the variables, by Skewness values, Multivariant Analysis of Variance (MANOVA) examined the differences between the groups in the BRIEF and RCMAS sub-scales while One-Way ANOVA examined the differences between groups in the measures’ total scores. Post hoc analysis followed the MANOVA/ANOVA to examine the differences between the three groups: children with ADHD+ ASP; ADHD only and typically developing children. After performing Pearson correlations, a stepwise Linear Regression examined the contribution of group (ADHD or ADHD+ ASP)/EFs/anxiety to the prediction of each QoL domain. Hayes’ (Hayes & Rockwood, 2020) PROCESS Model 4 was used to examine whether ASP mediated between EFs, anxiety and QoL in children with ADHD+ ASP. The level of significance was set at p ≤ 0.05.

Results

Hypothesis 1:

Comparing differences between groups in executive functions (BRIEF).

When comparing the three groups, children with both ADHD+ ASP had lower EFs than children with ADHD in all BRIEF scales, however these differences were significant only in the GEC total score (p = .012) and in the emotional control scale (p = .005). Table 2 describes the comparison between the ADHD groups and the typically developing participants (as a verification for their normal EFs). The typically developing participants had significantly better performance than both ADHD groups in all BRIEF scores (p < .001).

Table 2. Comparing BRIEF Standard (T) Scores Between the Groups.

		ADHD (n = 28)		ADHD + ASP (n = 31)		Healthy controls (n = 56)
		Mean	SD	Mean	SD	Mean	SD	F
	GEC	56.64	10.65	64.45	10.17	54.59	11.51	25.41***
	MC	60.07	2.30	62.52	12.86	53.39	13.81	28.26***
	BRI	63.11	11.38	67.52	12.91	57.04	14.34	38.38***
MC subscales	Initiation	56.64	10.65	61.71	11.99	53.41	11.84	20.95***
	Working memory	55.46	17.22	59.71	15.78	53.02	12.64	14.85***
	Plan	55.43	3.17	56.65	9.98	50.26	10.27	20.72***
	Organization	49.03	7.30	51.19	9.27	47.21	9.31	3.76***
	Self monitoring	53.39	12.67	57.97	9.19	49.76	12.47	19.65***
BRI subscales	Inhibition	49.14	7.66	54.87	9.80	48.85	10.15	8.17***
	Shift	73.36	18.87	77.77	14.20	65.04	18.15	47.17***
	Emotion control	61.39	10.61	71.29	13.84	56.44	16.72	60.87***

*p ≤ .05; **p ≤ .01; ***p ≤ .001.

ASP: atypical sensory processing; ADHD: attention deficit hyperactivity disorder; BRIEF: Behavior Rating Inventory of Executive Functions; GEC: global executive composite; BRI: Behavioral Regulation Index; MC: Metacognition Index; SD: standard deviation; NS: not significant.

F and t test analysis were performed only for the ADHD groups.

Higher BRIEF score represent lower EF; Italic indicates executive dysfunctions (scores above 65).

Comparing differences between groups in anxiety as measured by RCMAS

Children with ADHD+ ASP had higher anxiety as reflected in most RCMAS scales. Yet, the only significant difference was found in Physical Anxiety (F_57,1 = 6.28, p = .01).

Comparing differences between groups in QoL as measured by PedsQL

Significant differences were found between the groups in all PedsQL scores. Post hoc analysis revealed that in the physical QoL, no significant difference was found between both ADHD groups. However, children with ADHD+ ASP had significantly lower emotional QoL, as compared to the typically developing participants (p < .001) and to children with ADHD (p = .001); lower social QoL, as compared to the typically developing participants (p < .001) and to children with ADHD (p < .001). In the school QoL – no significant difference was found between both ADHD groups. However, children with ADHD+ ASP had significantly lower school related QoL than the typically developing participants (p < .001).

Figure 1 summarizes the gaps between children with/without ASP in EFs, anxiety levels and QoL.

Figure 1. Comparing executive functions, anxiety and quality of life between children with ADHD and children with ADHD + ASP.

Hypothesis 2:

Examining the relationships between EF, anxiety and QoL in the ADHD groups

In both groups, lower EFs and greater anxiety correlated with lower QoL. These correlations were more prevalent in children with ADHD+ ASP (Table 3).

Table 3. Correlations Between EFs, Anxiety and QoL in Each ADHD Group (Based on Pearson Correlation Test).

		Physical QoL	Emotional QoL	Social QoL	School related QoL	Total QoL
EFs	GEC	−0.48**	−0.12	−0.44*	−0.27	−0.06
					−0.56***	−0.36*
	BRI	0.04	−0.21	−0.37	−0.13	−0.21
			−0.39*		−0.47**	−0.37*
	MC	−0.37	−0.18	0.09	−0.29	−0.32
Anxiety	Total	−0.13	−0.38*	−0.25	0.24	−0.19
	Physical anxiety	−0.23	−0.08	−0.14	0.32	−0.05
	Worriedness	−0.01	−0.49**	−0.41*	0.19	−0.26
	Social anxiety	−0.06	−0.54**	−0.26	−0.24	−0.36
	Lie/desirability	−0.14	0.15	0.17	0.22	0.13

*p ≤ .05; **p ≤ .01; ***p ≤ .001.

ADHD: attention deficit hyperactivity disorder; EFs: executive functions; QoL: quality of life; GEC: global executive composite; BRI: behavioral regulation index; MC: metacognition index.

Bold – significant correlations in children with ADHD.

Not bolded – significant correlations in children with ADHD + ASP.

NS: not significant.

Based on the significant correlations presented above, the next step was predicting each QoL domain with group, EFs and anxiety scores.

Hypothesis 3:

The prediction of quality of life by group, EFs and anxiety

Physical QoL was not significantly predicted by these variables. As presented in Table 4, the prediction of the emotional QoL yielded two models: the first included anxiety total score as a significant predictor accounting for 19% of the variance; “group” (ADHD only or ADHD+ ASP) accounted for additional 10% of the variance. Social QoL was significantly predicted by “group”, accounting for 23% of the variance. School related QoL was predicted by BRIEF total score (GEC) accounting for 21% of the variance. The prediction of the total QoL score yielded two models: the first included anxiety as a significant predictor accounting for 22% of the variance; the second included the “group” which added 8% to the variance.

Table 4. Predicting QoL Domains by Group, EFs and Anxiety.

		Model 1			Model 2
	Predictors	B	SE B	β	B	SE B	β
Emotional QoL	Total anxiety	−1.79	0.48	−0.44
	Group (ADHD or ADHD + ASP)	−1.47	0.47	−0.36	−14.73	5.32	−0.32
	R^2	19%			29%
	F1,57 for change in R^2	13.58***			7.68**
Social QoL	Group (ADHD or ADHD + ASP)	−19.64	4.78	−0.48
	R^2	23%
	F1,57 for change in R^2	16.89***
School related QoL	General executive composite (GEC)	−0.87	0.22	−0.46
	R^2	21%
	F1,57 for change in R^2	15.51***
Total QoL	Total anxiety	−0.71	0.31	−0.27
	Group (ADHD or ADHD + ASP)	−14.18	3.415	−0.48	−12.26	3.39	−0.42
	R^2	22%			30%
	F1,57 for change in R^2	17.26***			5.36*

*p ≤ .05; **p ≤ .01; ***p ≤ .001.

EFs: executive functions; QoL: quality of life; ADHD: attention deficit hyperactivity disorder; ASP: atypical sensory processing.

Hypothesis 4:

Examining whether ASP mediated between EFs-QoL and anxiety-QoL in children with ADHD+ ASP

EFs – An indirect effect of EFs on QoL via the ASP was found based on Hayes and Rockwood’s (2020)³⁹ PROCESS Model 4 (95% CI [−0.64, −0.09]), F(2, 28) = 9.15, p < .001, R² = 0.63. The coefficient was 0.53, SE = 0.15, p = .001. Therefore, ASP significantly mediated between EFs and QoL.

Anxiety – An indirect effect of anxiety on QoL via the ASP was found (95% CI [−0.97, −0.03]), F(2, 28) = 10.01, p < .001, R² = 0.65. The coefficient was 0.51, SE = 0.13, p = .001. Therefore, ASP mediated between anxiety and QoL (Figure 2).

Figure 2. Mediation models:

ASP mediated between EFs and QoL in children with ADHD+ ASP

ASP mediated between anxiety and QoL in children with ADHD+ ASP

Discussion

This study aimed to illuminate the contribution of ASP to EFs difficulties, anxiety and QoL in children with ADHD. Based on the higher prevalence of ADHD in boys as compared to girls, this study included only boys. The current study compared EFs difficulties, anxiety and QoL between three groups: boys with ADHD+ ASP, boys with ADHD only and controls with typical development. The main result was that the involvement of ASP in ADHD, impaired EFs, elevated anxiety and reduced the boys’ QOL.

When referring to hypothesis 1: children with ADHD+ ASP had the lowest EFs, the highest anxiety and the lowest QoL. Their lower EFs were expressed in all BRIEF subscales, with an emphasis on inhibition and emotional control. Difficulties in inhibition and in emotional control are prevalent in boys with ADHD, probably due to the dysregulated function of the pre-frontal cortex and the limbic system (Nikolaidis et al., 2022).

Children with ADHD+ ASP had the highest anxiety. Indeed, when sensory stimuli from daily environment are not properly perceived or are too intense and linger long after the stimuli ended, the environment is experienced as intimidating, leading to emotional arousability and even to anxiety (Lane & Reynolds, 2019). Boys with ADHD+ ASP had greater anxiety as found in all RCMAS scales, compared to children with ADHD. Yet, the only significant RCMAS scale that differed between both groups was physical anxiety. The items included in this scale refer to hyper arousability/sympathetic manifestations of anxiety (for example: “It is hard for me to get to sleep at night”; “My hands feel sweaty”), and to exhaustion (“I am tired a lot”). Previous reports based on subjective and objective measures, such as EDA (Morris et al., 2020) and vagal tone (Schaaf et al., 2003), support this result and emphasize the un-modulated autonomic activity in children with ADHD in response to sensory input.

Interestingly, in the presence of executive function difficulties, as found in children with ADHD, the impact of ASP on emotional liability is greater. Difficulties in executive control, as in altering and orienting attentional networks, as well as poor problem-solving skills may limit the individual’s ability to reappraise or flexibly respond to stressful situations such as when facing unpleasant sensory input in daily environments (Pacheco-Unguetti et al., 2010; Sanz-Cervera et al., 2019; Teper & Inzlicht, 2013).

The reduced QoL of children with ADHD in this study supports previous reports on children with ADHD in school years (Galloway & Newman, 2017). Indeed, the complexity and the chronicity of ADHD, especially during school age, may significantly impact QoL (Gallego-Méndez et al., 2020). However, the present study emphasizes that in the presence of ASP the impact on QoL is greater. The gap in QoL between children with ADHD+ ASP and typical controls was larger than the gap between children with ADHD and typical controls. Both ADHD groups did not differ in most QoL domains, except for the emotional domain, in which children with ADHD+ ASP had significant lower emotional QOL than children with ADHD (and typical controls). Lee et al. (2016) noted that based on children and parents’ reports, ADHD may reduce various QoL domains, with a moderate effect in physical and a severe effect in emotional, social, and school domains. Not only that children with ADHD experience emotional burden that reduces their QoL, this emotional burden may persist into adulthood and lead to severe consequences as un-social behavior, addiction and crimes (Quintero et al., 2019). Thus, it is important to screen for emotional difficulties in children with ADHD as early as possible, treat them and understand if and how they are related to possible accelerators as EFs difficulties and ASP. Support for that may be found when referring to hypotheses two and three.

Hypothesis two and three were proved as well: in the present study, lower EFs and greater anxiety correlated with lower QoL, in both ADHD groups. Anxiety was the main predictor of emotional QoL. The emotional domain of the PEDS-QL includes statements such as: “Feeling afraid or scared”; “Feeling angry “; “Worrying about what will happen to him or her". Anxiety (as well as other prevalent emotional problems in ADHD, including poor self-regulation of emotion, anger and aggression, difficulties to cope with frustration), leads to severe functional and social difficulties and thus may explain the reduced emotional QoL (Wehmeier et al., 2010). As mentioned above, clinicians should pay greater attention on the implications of ADHD on emotional status in order to minimize the risk of developing antisocial behavior and adjustment problems. Clinicians should assess, monitor and treat emotional difficulties alongside ADHD symptoms (Stern et al., 2020). As emphasized in this study, clinicians should consider the interaction between emotional status, cognitive status and ASP.

Based on the findings of the present study, as expected, EFs were the main predictors of school-related QoL. EFs are critical for academic performance and achievements (Sibley et al., 2019). The school domain in PEDS-QL includes items such as: “Paying attention in class”; “Forgetting things”; “Keeping up with school activities” which lean on EFs. It should be noticed that EFs impact additional factors that are important for school performance, such as peer relations (Chiang & Gau, 2014). Indeed, a large part of the literature refers to the interaction between EFs, emotional/social difficulties and QoL of children with ADHD (Tamm et al., 2021). The current study adds another player to this interaction – ASP. The results showed that the presence of ASP may further deteriorate the reduced QoL of children with ADHD, with an emphasis on the social domain. Therefore, intervention for children with ADHD should use an elaborated perspective in which the interaction between ADHD, ASP, emotional and cognitive aspects should be considered as well as their implications on all QoL.

Clinicians should refer to the involvement of ASP in ADHD pathogenesis and comorbidities and to the implications on child’s daily function. The evaluation process should screen for deficits in EFs, anxiety and ASP in children with ADHD. When found, the relations between these factors and their implications on child’s daily life should be considered. Occupational therapists that aim to enhance participation and QoL, should elevate the awareness of children with ADHD, their parents and teachers to the fact that difficulties to properly perceive and modulate sensory input may create a vicious cycle in which cognitive and emotional load are elevated, self-confidence is reduced, and daily function and QoL are further impaired. Clinicians should create together with the child, the parents, and the teachers, strategies and environmental adaptation that would enable better coping with the sensory, emotional, cognitive and behavioral challenges, in various life settings (Fox et al., 2020; Morris et al., 2020), with an emphasis on participation in social and school-based activities.

Intervention should include a multidisciplinary team. It is important that the multidisciplinary team includes occupational therapists who are the central factor in bridging between the individual’s health conditions, comorbidities and participation in meaningful activities in real life settings (Machingura et al., 2022) and by that provide intervention aims and strategies that go beyond clinical settings. Intervention should be created based on evaluations that include ecologically valid assessments (such as the BRIEF), that gather information about child’s function in actual life, from people who are closest to the child (parents, teachers). QoL, which is a significant factor in measuring intervention efficiency (World Health Organization, 2001), should be routinely evaluated in children with ADHD for understanding how the disorder, its comorbidities and the intervention affect child’s function, development, QoL and wellbeing (Rentz et al., 2005).

Limitations

The study has several limitations. First, it included only boys. Information about the measured outcomes in girls is missing. Second, the study referred to boys in a specific age range, with un-equal distribution in the number, socio-economic status, and parents’ education level, of the three groups. The sample size of each group was relatively low. These facts limit the generalization of the results. In addition, this study included only parents’ self-reports. Information from the children is important to validate the information gathered from the parents and include the child’s experience and perspective.

Studies of larger sample sizes should explore the unique relations between ADHD, comorbidities such as ASP, anxiety, participation, and QoL in boys and girls to illuminate gender effects. Studies should gather data from various sources – parents, teachers, and children with ADHD, to create an elaborated perspective about ADHD’s implications on various life settings and contexts. Cohort studies should explore developmental impacts on the sensory-emotional-cognitive interactions in ADHD as well as on intervention efficacy. It is also recommended to increase the use of ecologically valid measures to better understand how body dysfunctions limit activity performance and participation in daily life of children with ADHD. By doing that, we may tailor better interventions to enhance child’s daily function and QoL (Giovannetti et al., 2020).

Conclusions

ASP may worsen EFs and anxiety in children with ADHD and predict their reduced quality of life. Therefore, ASP should receive attention in evaluation and intervention for children with ADHD. Intervention should include a multi-disciplinary team with occupational therapists that may significantly contribute to the understanding of ASP’s effects on child’s cognitive abilities, emotional status and quality of life. This elaborated perspective, based on the ICF, which emphasize functional aspects, may assist in tailoring optimal interventions to enhance child’s development, function, and wellbeing.

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.