INTRODUCTION
Numerous studies have established a link between attention-deficit/hyperactivity disorder (ADHD) and emotion dysregulation (EDR), yet the precise nature of this association remains elusive (Pylypow et al., 2020; Antony et al., 2022; Bodalski et al., 2023a,b). ADHD is a prevalent psychiatric condition, particularly among children, and is often accompanied by functional difficulties that persist into adolescence and adulthood. Notably, social impairment represents a significant and challenging aspect of ADHD. Prior research has indicated that externalizing behavior problems and social impairment in children with ADHD can largely be attributed to EDR. Some researchers even propose that emotional symptoms constitute a core feature of ADHD rather than a mere comorbidity (Bunford et al., 2018; Hall et al., 2020; Eltyeb, 2023), given their common occurrence and substantial impact on morbidity.
Existing literature on the relationship between EDR and ADHD has led to the classification of three models. The first model, advocated by “lumpers,” posits that EDR is an intrinsic component of ADHD. The second model, supported by “splitters,” suggests that the two constructs together define a unified entity. The third model, endorsed by “diplomats,” asserts that, while the two symptoms are related, they are ultimately distinct dimensions. Currently, there are insufficient data to definitively favor one model over the others, largely due to limited research specifically addressing the question of why EDR is highly prevalent in ADHD (Shaw et al., 2014).
Several studies have explored whether EDR symptoms can be considered a key diagnostic characteristic of ADHD. For instance, Turkia et al. (2021) conducted a cross-sectional study involving 60 children with ADHD, revealing that severe EDR was present in 63% of cases. Children with ADHD often struggle with analyzing their emotions, which poses significant challenges for them and their families. The intersection of social-emotional difficulties and learning differences further compounds these challenges (Barkley and Murphy, 2010).
Although individuals with ADHD commonly experience difficulties with emotion regulation, there is currently no consensus on how to conceptualize this complex domain, highlighting the need for a comprehensive review. In the present study, the authors reviewed the existing literature to elucidate the relationship between EDR and ADHD. They aimed to develop a model that explains the overlapping yet distinct dimensions of both disorders, with EDR serving as a key diagnostic feature of ADHD. The proposed model views the combination of EDR and ADHD as a nosological entity separate from both EDR and ADHD in isolation. The diverse projections of this model offer valuable insights to guide future research in this often overlooked area.
STUDY IMPORTANCE
Studying the correlation between ADHD and EDR among students in Saudi Arabia is crucial due to the high prevalence of ADHD in the Saudi population, estimated at 12.4%, and with specific risk factors like maternal psychological disorders during pregnancy and nutritional deficiencies identified (Aljadani et al., 2023). In Saudi Arabia, EDR in individuals with ADHD is typically addressed from a medical perspective, with clinicians prescribing antipsychotic medications due to a lack of recommended ADHD medications (Alharbi, 2018). Additionally, emotional and behavioral issues have been shown to impact a child’s academic performance, with higher rates observed in students with learning disabilities in Saudi Arabia, especially among younger students (Chutko et al., 2023). Addressing EDR symptoms in students with ADHD in Saudi Arabia is essential for their academic success and overall well-being (Farmer et al., 2023).
EDR is common in individuals with ADHD and can lead to negative consequences, highlighting the importance of early detection and treatment of emotional challenges within this group (Al-Saedi et al., 2023). Furthermore, a study in Riyadh emphasized the significance of teachers’ comprehension of ADHD in identifying students with the disorder, emphasizing the need for training programs to enable early diagnosis and improved outcomes for affected students (Abouammoh et al., 2023). Understanding the interaction between ADHD and EDR can result in improved support systems and interventions for students with ADHD in Saudi Arabia, ultimately enhancing their academic and social well-being. This paper provides valuable insights for educators, healthcare professionals, and policymakers in Saudi Arabia by illuminating the impact of ADHD and EDR.
The present study focused on investigating the relationship between ADHD and EDR among children in elementary schools. Several studies have explored this connection among adolescents, such as the study by Figuracion et al. (2024), which looked into the relationship between EDR and error monitoring in adolescents with ADHD. Additionally, Musella and Weyandt (2023) conducted a study on ADHD and youth’s EDR. Moreover, Farmer et al. (2023) examined well-being and distress in university students with ADHD traits. Shedding light on the impact of ADHD and EDR at a young age presents a valuable opportunity for educators, healthcare professionals, and policymakers in Saudi Arabia to implement suitable interventions earlier.
LITERATURE REVIEW
Attention-deficit/hyperactivity disorder
ADHD is currently recognized as the most prevalent neurobehavioral disorder affecting children worldwide (AlZaben et al., 2018). It is a psychological condition that can persist from childhood into adolescence and adulthood (Bunford et al., 2018). ADHD is associated with various neuropsychiatric disorders, including anxiety, mood disorders, and personality problems. In children, ADHD is primarily characterized by two key behavioral features: poor attention and hyperactivity/impulsivity. To encompass the different presentations of the disorder, the Diagnostic and Statistical Manual of Mental Disorders, fifth edition, introduced three subtypes of ADHD: the inattentive type, requiring at least six symptoms of inattention; the hyperactive/impulsive type, requiring at least six symptoms of hyperactivity or impulsivity; and the combined type, necessitating at least six symptoms from each subtype (Eltyeb, 2023).
ADHD typically manifests in children under the age of 7 years, and the symptoms should persist for at least 6 months. It significantly impacts social, academic, and occupational functioning. Additionally, for an ADHD diagnosis to be established, the symptoms must not be better explained by another disorder, such as autism spectrum disorder, anxiety disorder, or mental illness. Although there may be variations in prevalence across different age groups, the symptomatology and response to treatment are not clearly distinguishable between childhood, adolescence, and adulthood (Hall et al., 2020).
ADHD is a highly prevalent and heritable neurodevelopmental disorder, with a global incidence of 5.29% and a local prevalence of 8% in Saudi Arabia, showing a slightly higher prevalence among males (Ministry of Health, 2023). It is characterized by persistent symptoms of inattention, impulsivity, and hyperactivity that are developmentally inappropriate and evident in multiple settings, causing impairments in academic, occupational, and social domains. Consequently, ADHD significantly disrupts an individual’s daily functioning, affecting not only their personal lives but also their families and communities.
The diagnosis of ADHD often relies on clinical examination and the use of rating scales, which are frequently employed in children and adolescents to assess symptom severity and treatment response (Altwaijri et al., 2020). Clinical evaluation primarily involves subjective assessments based on observations of the individual and feedback from parents and teachers. Rating scales serve as valuable tools for collecting data through parent and teacher reports, enhancing consistency and comparability in the evaluation process (Hall et al., 2020; Nigg et al., 2020; Gill et al., 2021).
Assessing ADHD in Saudi Arabia
The management of ADHD varies globally, employing diverse integrated care models that encompass primary and secondary care, depending on each nation’s resources, culture, and practice style. In Saudi Arabia, tertiary care settings primarily handle the diagnosis and treatment of ADHD, lacking consistent clinical guidelines for this condition. As a result, there is considerable variation in the management of ADHD, particularly within the private sector, where resources may be limited, leading to inappropriate or inadequate treatment approaches. Behavioral and psychosocial interventions are frequently included under the umbrella of “treatment” in many Saudi Arabian schools and other settings. These interventions are offered by numerous psychologists working in government and commercial facilities, as well as through special education programs in certain schools. However, the lack of standardization within these interventions contributes to disparities in the quality of treatment provided.
Establishing an accurate diagnosis of ADHD is crucial in addressing these disparities. The use of well-validated rating scales that provide a comprehensive profile of the condition’s pattern and severity in children is a crucial initial step in addressing this imbalance (Saudi Society for Attention Deficit Hyperactivity Disorder, 2020). Additionally, it is common for children diagnosed with attention-deficit disorder to also exhibit learning disabilities (Bashiri et al., 2021). Furthermore, ADHD significantly impacts various aspects of an individual’s life, including social interactions, as others may struggle to manage the symptoms associated with the disorder.
In Saudi Arabia, limited systematic studies have been conducted to examine ADHD in elementary school children, particularly those employing scales or tests with psychometric validity. However, an epidemiological survey conducted in 11 administrative areas of Saudi Arabia revealed that separation anxiety disorder and ADHD were the two most prevalent lifetime disorders, with a prevalence of 11.9% and 8.0%, respectively, in a nationally representative household sample (Altwaijri et al., 2020). In a cross-sectional study conducted in Jeddah, AlZaben et al. (2018) screened a sample of 929 primary school students using the Vanderbilt ADHD scale to assess the prevalence of ADHD, its subtypes, and the associated psychiatric, academic, and behavioral conditions. The overall prevalence of ADHD was 5%, with a slightly higher prevalence in females (5.3%) than in males (4.7%). The most common subtypes were the combination type (2.7% prevalence), the hyperactive type (1.2%), and the inattentive type (1.1%). Grade 3 exhibited the highest overall frequency of ADHD (7.1%), while grade 6 had the lowest prevalence (3.4%).
Since there is no objective test to definitively confirm the diagnosis of ADHD, the use of valid and reliable behavioral rating scales for screening is crucial in accurately diagnosing and treating ADHD in children. However, it should be noted that the rating scales currently utilized in Saudi Arabia are primarily translated versions, and their validity and reliability metrics are still undergoing extensive examination (Almarzouki et al., 2022). Bashiri et al. (2021) emphasized that a Saudi rating instrument cannot be considered valid without comparison to a gold standard, such as an actual clinical diagnosis or another rating scale with established empirical validity. Additionally, Eltyeb (2023) highlighted the insufficient availability of ADHD scales in Saudi schools, particularly for students in the 6- to 12-year age range. Therefore, the development of an ADHD scale specifically designed for the Saudi context, with rigorous evidence of its validity and reliability, is necessary in order to facilitate accurate diagnosis and treatment.
EDR in ADHD children
EDR refers to difficulties in effectively managing and responding to emotions. It is characterized by intense emotional reactions, challenges in calming down, and difficulties in adapting emotional responses to different situations. Recent research has placed significant emphasis on understanding and studying EDR (Shaw et al., 2014; AlZaben et al., 2018; Thorell et al., 2020; Antony et al., 2022). However, this disorder has long been recognized and investigated in the literature through various related concepts, such as neuroticism, fiery temperament, emotional lability, and negative emotionality (Pylypow et al., 2020; Antony et al., 2022; Bodalski et al., 2023a,b).
Poor emotional regulation is a common issue that affects individuals of all ages and is associated with a wide range of psychiatric and physical conditions. It is suggested that EDR may be a key symptom of oppositional defiant disorder (Pylypow et al., 2020; Wycoff et al., 2024). In children, those with anger-irritability symptoms in addition to behavioral symptoms of ADHD often experience more severe anxiety and depressive symptoms (Bodalski et al., 2023a,b). The relationship between EDR and ADHD in children is complex and multifaceted. Although they are distinct constructs, there is evidence to suggest that they can overlap and interact with each other (Bunford et al., 2018). EDR in children with ADHD may intensify the core symptoms of impulsivity and hyperactivity. Conversely, the challenges associated with ADHD may contribute to frustration and EDR (Ginapp et al., 2023; Bodalski et al., 2023a,b).
Interventions that address both ADHD symptoms and EDR have the potential to be more effective (Barkley, 2015). This may involve a combination of behavioral interventions, psychoeducation, and, in some cases, medication. It is important to recognize that the relationship between ADHD and EDR can vary across different developmental stages (Linca et al., 2022). Younger children may exhibit distinct patterns of EDR compared to older adolescents. Understanding and addressing the interplay between ADHD and EDR is crucial for developing comprehensive and individualized interventions for affected children (Turkia et al., 2021).
It is worth noting that not all children with ADHD will experience significant EDR, and vice versa, as there are individual differences. Therefore, a holistic assessment conducted by mental health professionals is essential for accurate diagnosis and effective intervention planning (Shaw et al., 2014; AlZaben et al., 2018; Thorell et al., 2020; Antony et al., 2022). Common co-occurring issues with ADHD symptoms include internalizing problems such as anxiety and depression. EDR difficulties have been proposed as a potential mediating mechanism through which ADHD symptoms contribute to an increased risk of these problems. Thorell et al. (2020) found that EDR and impulsivity are closely related and prevalent symptoms of ADHD. Individuals with ADHD often demonstrate impulsive behaviors that can intensify emotions and lead to emotional outbursts, without considering the consequences of their actions. Children with combined or hyperactive ADHD are more likely to experience EDR. Their constant movement and restlessness may not allow sufficient time for emotional processing, potentially resulting in impulsive decisions and behaviors (Bunford et al., 2018; Bodalski et al., 2023a,b).
Formulation of conceptual framework and measuring instruments
Conceptual framework
The conceptual framework of this study aims to elucidate the relationship between ADHD and EDR. ADHD is a highly prevalent neurobehavioral disorder, particularly in children, characterized by symptoms of inattention, hyperactivity, and impulsivity (AlZaben et al., 2018; Bunford et al., 2018). EDR, on the other hand, refers to difficulties in managing and responding to emotional experiences (Thorell et al., 2020; Antony et al., 2022). The existing literature has highlighted a significant overlap between ADHD and EDR, suggesting that these conditions often co-occur and may exacerbate each other’s symptoms (Pylypow et al., 2020; Bodalski et al., 2023a,b).
The current study adopted “lumpers’ model” which posits that EDR is an intrinsic component of ADHD. This model has been proved in numerous recent studies (Bunford et al., 2018; Thorell et al., 2020; Antony et al., 2022; Bodalski et al., 2023a,b; Chutko et al., 2023; Martz et al., 2023; Musella and Weyandt, 2023; Esmaeilpour and Mohammadzadeh, 2024; Figuracion et al., 2024). Given the complexity and multifaceted nature of the ADHD–EDR relationship, the present study aims to develop a model that conceptualizes the overlapping yet distinct dimensions of these disorders, with EDR serving as a key diagnostic feature of ADHD. Figure 1 displays the conceptual framework (model of the ADHD–EDR relationship).
Structural equation modeling
The present study employed structural equation modeling (SEM) analysis. This research design is commonly employed to gather data on variables of interest and examine the hypothesized relationships among those variables using SEM. SEM combines confirmatory factor analysis (CFA) and multiple regression analysis to investigate both the measurement and structural properties of the model (AlAli and Al-Barakat, 2022).
SEM is a statistical analysis technique that is widely used in social sciences and other fields to examine complex relationships among variables. It allows researchers to assess both the measurement and structural properties of a conceptual model. In SEM, the researcher specifies a theoretical model that represents the relationships among different constructs or variables of interest. These constructs can be measured using observed indicators or items. CFA is employed to evaluate the measurement properties of the constructs, which involves examining how well the observed indicators align with the underlying latent constructs. Once the measurement model is established, SEM also enables the assessment of the structural relationships between the constructs. This involves estimating the strength and directionality of the relationships, as well as evaluating the overall fit of the model to the data. One advantage of SEM is its ability to handle complex models that involve multiple variables and interrelationships. It allows researchers to test hypotheses, explore causal relationships, and assess the overall model fit to the data. SEM provides valuable insights into the underlying mechanisms and processes that contribute to the observed relationships among variables (Jin et al., 2021; Shi et al., 2021; AlAli and Saleh, 2022).
Regarding sample size, the recommendation of a minimum of 100 participants, as suggested by Hair et al. (2012), is based on the consideration of model complexity and the number of items or indicators for each construct. Adequate sample size is essential to ensure statistical power and reliable estimation of model parameters. However, the specific sample size requirements may vary depending on the complexity of the model and the desired level of statistical precision.
METHODS
The current study adopted a quantitative descriptive survey approach to address its research objectives. Two scales were developed for the purpose of this study. The first scale is the ADHD scale, comprising three dimensions: attention, hyperactivity, and organization. The second scale is the EDR scale, encompassing four dimensions: poor emotional participation, diminished control over conduct, externalization, and neglect. To ensure ethical integrity, the study obtained approval from King Faisal University to conduct the research. Informed consent was obtained from all individual participants included in the study. Participants were provided with a comprehensive explanation regarding the nature and purpose of the scales. Initially, the scales were applied to an exploratory sample, followed by their implementation on the target sample. Subsequently, the gathered data underwent statistical treatments, analyses, and interpretation to derive meaningful findings. These analytical processes allowed for a comprehensive examination of the scales’ psychometric properties and facilitated a deeper understanding of the research outcomes.
Population and sampling
Sampling techniques are critical in establishing the accuracy of study findings, particularly in studies investigating the relationship between ADHD and EDR. Proper sampling methods are required to ensure that the chosen sample is a true reflection of the population, allowing correct inferences to be drawn (Narayan et al., 2023; Saleh and AlAli, 2024). For the purposes of the current study, the researchers used simple randomization to select children with the goal of maximizing statistical representativeness, which is critical to obtaining accurate quantitative research results and making informed decisions about the appropriateness of their sampling strategy in ADHD and EDR studies.
ADHD and EDR scales were utilized by 30 teachers to ensure consistency in understanding and interpreting the items. Various measures were implemented to establish a mutual understanding of the scale items and standardize administration procedures. Teachers conducted evaluations after at least a full semester, allowing them to become familiar with the students. Through workshops, teachers meticulously examined each item, clarifying ambiguities, ensuring a common interpretation of the constructs, and addressing any queries or concerns. Teachers practiced applying the measures using sample student cases to identify and resolve discrepancies in scoring.
After initial training, teachers independently rated the same students, and intraclass correlation coefficients (ICCs) confirmed high inter-rater agreement (ICC > 0.80 for all scales). Continuous monitoring and feedback were maintained throughout data collection to promptly address any issues with item interpretation or administration.
The study focused on students with learning difficulties in the eastern region of the Kingdom of Saudi Arabia, as per the classification provided by schools. A total of 500 students (44.3% females, 55.7% males) in grades 3-6, aged 9-12 years, were included in the study. The ADHD scale was administered to assess the presence of ADHD, and based on the indicators and criteria, 180 children were diagnosed with the disorder. The average age of the identified children was 10.5 years [standard deviation (SD) = 1.6], with an average grade level of 4.5 (SD = 1.6). Among the diagnosed children, 54.4% were male. Details regarding the characteristics of the sample are provided in Table 1.
Characteristics of the research sample.
| Grade (n) | Third n = 40 (22.22%) | Fourth n = 48 (26.67%) | Fifth n = 42 (23.33%) | Sixth n = 50 (27.78%) |
|---|---|---|---|---|
| Gender | Male (100) | Female (80) | ||
| Mother’s education | Illiterate/primary | 20 (11.11%) | ||
| Intermediate/secondary | 92 (51.11%) | |||
| University | 68 (37.78%) | |||
| Father’s education | Illiterate/primary | 36 (20%) | ||
| Intermediate/secondary | 88 (48.89%) | |||
| University | 56 (31.11%) |
Scales
Individuals with ADHD often encounter challenges in effectively regulating their emotions. However, the absence of comprehensive scales and tests specifically designed to aid in the diagnosis and identification of these emotional difficulties poses significant obstacles for professionals involved in the assessment and treatment process. Consequently, one of the key objectives of the present study is to develop reliable and valid scales targeted at both ADHD and EDR. By addressing this research goal, the study aims to provide valuable tools that can enhance the accuracy and effectiveness of diagnosis and treatment interventions for individuals with ADHD and concurrent emotional difficulties.
ADHD scale
The present study aims to develop and evaluate the psychometric properties and clinical utility of a comprehensive scale designed to measure ADHD, with a specific focus on items pertaining to attention deficit, hyperactivity, and impulsivity. Extensive literature research was conducted to identify relevant studies that have examined the reliability, validity, and diagnostic accuracy of existing ADHD scales. A thorough review of these scales was conducted, with particular emphasis on the Conners’ Adult ADHD Rating Scale (CAARS). The findings from Erhardt et al. (1999) indicate that the CAARS demonstrates strong internal consistency, test–retest reliability, concurrent validity, and diagnostic utility in assessing ADHD symptoms in both adults and young individuals. Similarly, Faries et al. (2001) support the use of the ADHD Rating Scale as a clinician-administered and scored tool, highlighting its acceptable levels of reliability, validity, and responsiveness. Weiler et al. (2000) demonstrate that the Diagnostic Rating Scale, a categorical rating approach, exhibits a high sensitivity to ADHD diagnoses. Additionally, Adler et al. (2008) provide evidence that the CAARS exhibits good internal consistency, inter-rater reliability, and sensitivity to treatment outcomes. Collectively, these findings support the reliability, validity, and diagnostic accuracy of ADHD scales, particularly the CAARS, in effectively assessing ADHD symptoms in both adults and young individuals. The results highlight the utility of these scales in clinical practice and research settings.
The process of developing dimensions and items for an ADHD scale involved several sequential steps, as outlined below.
Literature review: A comprehensive literature review served as the initial step in item generation. The researchers thoroughly examined academic publications, textbooks, and relevant research articles pertaining to ADHD. This neurodevelopmental disorder typically emerges in childhood and persists into adulthood, characterized by persistent patterns of inattention, hyperactivity, and impulsivity that significantly impair daily functioning and overall development.
The symptoms and characteristics of ADHD can vary among individuals, but common signs of inattention include difficulty sustaining focus, easy distractibility, forgetfulness, and disorganization. Hyperactivity symptoms may manifest as excessive talking, fidgeting, restlessness, and an inability to remain still. Impulsivity symptoms can involve interrupting others, impatience, difficulty waiting for turns, and acting without considering consequences. Accurate assessment of ADHD is of utmost importance for several reasons. First, misdiagnosis or delayed diagnosis can have substantial negative impacts on individuals’ educational, occupational, and social well-being. Proper assessment enables appropriate management and support, including medication, therapy, and tailored interventions. Moreover, accurate diagnosis helps reduce stigma and promotes understanding of the condition among individuals, families, and communities (Woods et al., 2002).
The primary symptoms of ADHD encompass hyperactivity and impulsiveness in individuals who also exhibit attention-inattentiveness, overactivity, motor impulsiveness, cognitive impulsiveness, and deficient motor control, as proposed by Johansen et al. (2002). Malloy-Diniz et al. (2007) support the existence of deficits related to three components of impulsivity (motor, cognitive, and attentional) in adults with ADHD. Amador et al. (2001) analyze the presence of inattention and hyperactivity–impulsivity symptoms in children, highlighting the variability of symptoms based on evaluated behaviors and informants.
It is essential to note that the researchers designed the scale based on internationally recognized diagnostic criteria and associated dimensions. The initial set of items for the scale was informed by key concepts, symptoms, and theoretical frameworks established through rigorous research.
Expert opinions: To enhance the content validity and ensure alignment with accepted diagnostic criteria, the researchers sought the opinions of experts in the field of ADHD. These experts, including psychologists, psychiatrists, and researchers with specialized knowledge in ADHD, were consulted to provide valuable insights into the relevance and appropriateness of the scale items. Their expertise played a crucial role in validating and refining the initial items derived from the literature review. By incorporating expert opinions, the researchers ensured that the scale comprehensively captured the diverse manifestations of the disorder and effectively measured the construct of interest.
Iterative item refinement: Upon receiving feedback from experts and individuals with ADHD experience, a process of iterative refinement was initiated to enhance the quality of the scale items. This involved carefully reviewing and revising the wording, structure, and phrasing of the items to improve their clarity, specificity, and relevance to the dimensions of ADHD. The objective was to ensure that the items accurately represented the constructs being measured and encompassed a broad range of ADHD symptoms and behaviors. By incorporating inputs from multiple sources, such as literature review, expert opinions, and individuals with personal experience of ADHD, the resulting scale achieved a comprehensive representation of the disorder’s dimensions. Acknowledging the contributions of experts and referencing the consulted literature appropriately in the academic report are crucial to honoring their valuable input.
Response format, instructions, and cultural sensitivity: The ADHD scale was designed to assess symptoms of ADHD. It aims to provide an objective measurement of ADHD symptoms, enabling reliable and valid evaluations across diverse populations. In order to facilitate accurate assessment, several considerations were given to the response format, instructions for participants, and cultural sensitivity.
Response format selection: The Likert scale was selected as the response format for the ADHD scale due to its effectiveness in capturing the degree and frequency of symptoms. Participants were asked to rate the severity of symptoms on a continuum, ranging from “not at all” to “very frequently.” By offering a range of response options, Likert scales enhance sensitivity and enable precise grading of symptoms.
Instructions for participants: Clear instructions were provided to participants to ensure their understanding and minimize potential misinterpretations. General instructions included an overview of the scale’s purpose and a guarantee of confidentiality. Participants were informed that their responses would be used solely for research purposes and were encouraged to respond honestly and thoughtfully. Item-specific instructions were also provided to guide participants in responding based on their observations of the student’s behavior within the given timeframe. Examples of appropriate responses were given to illustrate the intended use of the scale.
Considerations for cultural sensitivity and applicability: The ADHD scale was developed in modernized Arabic to ensure accessibility to the target population. The researchers paid careful attention to cultural context, idiomatic expressions, and potential sensitivity to certain concepts to maintain accuracy across diverse linguistic and cultural groups. This approach ensured that the scale was culturally and linguistically adapted, allowing for effective use by individuals from different backgrounds, taking into account their cultural norms and variations in symptom expression. The ADHD scale consists of three dimensions: attention (seven items), hyperactivity (seven items), and organization (eight items) (See Appendix A).
EDR scale
An essential first step in comprehending the part EDR plays in the emergence, maintenance, and management of psychological disorders (like ADHD) is screening for the disorder. To measure the four aspects of EDR, we constructed the Brief Emotion Dysregulation Scale: the first dimension is poor emotional participation (five items), followed by diminished control over conduct (four items), emotional response style externalization (four items), and feeling neglected (five five items) as the fourth dimension (See Appendix B). On a scale of 1-4, we defined things as follows: 1 = strongly disagree, 2 = disagree, 3 = agree, and 4 = highly agree. Emotional participation is defined as a student’s involvement in and enthusiasm for school. When students are emotionally engaged, they want to participate in school, and they enjoy that participation more. Reactivity was defined as an intense, fast, and negative emotional reaction to stress or other external or internal stimuli. Reactivity may be a useful understanding of emotional response strength that may be applied to both clinical and nonclinical populations, even if it is not specifically mentioned in Wycoff et al.’s (2024) definition of EDR. Please note that our emotionality scales emphasize negative emotionality more than positive emotionality. We provided our working definitions of the four domains to evaluate the content validity of our initial pool of 18 items. Four researchers who specialize in EDR were asked to classify each of the 18 items according to the categories to which they belong.
DATA ANALYSIS
To address the research question and establish the construct validity of the study, various indicators were employed, including McDonald’s omega and composite reliability (CR) for assessing internal consistency, as well as measures of convergent validity and discriminant validity. Furthermore, exploratory factor analysis (EFA) and CFA were conducted using SPSS (version 26) and Amos statistical software (version 25) to evaluate factor validity. CFA, a type of SEM, is a valuable statistical technique for identifying patterns in data and examining relationships among latent constructs. It serves as an analytical tool for developing measurement instruments, assessing construct validity, and distinguishing methodological influences. Throughout the instrument’s development process, CFA is employed to examine the latent structure of the assessment tool, validate its primary dimensions, and assess factor loadings (FLs). In the broader context of psychometric evaluation, CFA plays a significant role as an essential analytical tool.
Ensuring validity and reliability for both scales
Indicators and coefficients of construct validity
The reliability and validity of a questionnaire are crucial aspects of its psychometric properties. Reliability refers to the consistency and stability of measurement, while validity pertains to the extent to which the questionnaire measures what it is intended to measure. In the context of reliability, two commonly used measures are McDonald’s omega and CR. McDonald’s omega assesses the internal consistency of a scale by considering the intercorrelations among items and the overall variability in the scores. Similarly, CR examines the extent to which the items in a scale contribute to measuring the underlying construct (AlAli and Saleh, 2022). Both scales provide an indication of the scale’s reliability, with higher values suggesting greater consistency among the items. The results presented in Table 2 demonstrate that the values of McDonald’s omega and CR for the ADHD scale constructs fall within the recommended ranges of 0.875-0.889 and 0.891-0.908, respectively, while the values of McDonald’s omega and CR for the EDR scale constructs fall within the recommended ranges of 0.795-0.868 and 0.814-0.923, respectively. These values indicate a high level of internal consistency, suggesting that the items within each dimension of the scale are strongly correlated and contribute consistently to measuring their respective constructs.
Some indicators and coefficients of construct validity.
| Scale | Constructs | Items | FL | McDonald’s omega | CR |
|---|---|---|---|---|---|
| ADHD | Attention | 7 | 0.56-0.78 | 0.875 | 0.891 |
| Hyperactivity | 7 | 0.66-0.81 | 0.880 | 0.903 | |
| Organization | 8 | 0.58-0.79 | 0.889 | 0.908 | |
| Poor emotional participation | 5 | 0.54-0.76 | 0.795 | 0.814 | |
| EDR | Diminished control over conduct | 4 | 0.65-0.87 | 0.853 | 0.872 |
| Externalization | 4 | 0.83-0.86 | 0.868 | 0.923 | |
| Neglect | 5 | 0.68-0.87 | 0.841 | 0.894 |
Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CR, composite reliability; EDR, emotion dysregulation; FL, factor loading.
Assessment of construct validity through factor analysis
To evaluate the construct validity of the scale, EFA and CFA were performed using SPSS (version 26) and Amos statistical software (version 25). These analytical techniques allowed for a thorough examination of the underlying factors and the confirmation of the proposed factor structure. EFA facilitated the identification of latent factors and their interrelationships, while CFA provided a rigorous assessment of how well the hypothesized factor structure fits the data. By employing these statistical methods, the study aimed to establish the validity and robustness of the scale’s measurement model.
Principal component analysis was utilized to conduct EFA on the responses obtained from the final scales. An oblique rotation, specifically the promax method, was performed on the extracted factors that had eigenvalues >1 as illustrated in Table 3.
The results of the EFA using the promax method.
| Scale | Component | Initial eigenvalues | ||
|---|---|---|---|---|
| Total | % of variance | Cumulative % | ||
| ADHD | Attention | 2.738 | 91.270 | 91.270 |
| Hyperactivity | 1.197 | 6.553 | 97.823 | |
| Organization | 1.065 | 2.177 | 100.000 | |
| Poor emotional participation | 3.062 | 76.555 | 76.555 | |
| EDR | Diminished control over conduct | 1.470 | 11.746 | 88.301 |
| Externalization | 1.339 | 8.473 | 96.773 | |
| Neglect | 1.129 | 3.227 | 100.000 | |
Abbreviations: ADHD, attention-deficit/hyperactivity disorder; EDR, emotion dysregulation; EFA, exploratory factor analysis.
Table 3 illustrates the presence of three factors for the ADHD scale with eigenvalues >1, accounting for an explanatory variance ratio of 100.00%. The eigenvalue of the first dimension was 2.738, with an explanatory variance ratio of 91.270. There were four factors for the EDR scale with eigenvalues >1, accounting for an explanatory variance ratio of 100.00%. The eigenvalue of the first dimension was 3.062, with an explanatory variance ratio of 76.555.
CFA was utilized to establish the factorial construct validity of both scales. The final versions of both scales were administered to the study sample, and CFA was conducted to examine the relationship between the scale items and their respective dimensions. The adopted model for the ADHD scale depicted the distribution of its 22 items across three dimensions, as illustrated in Figure 2. Similarly, the adopted model for the EDR scale depicted the relationship of its 18 items distributed over four dimensions, as depicted in Figure 3. CFA served as a statistical technique to assess the fit between the hypothesized models and the observed data, confirming the validity of the factorial structures for both scales.
Results of the CFA for the relationship of the ADHD scale items to its dimensions. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CFA, confirmatory factor analysis.
Results of the CFA for the relationship of the EDR scale items to their dimensions. Abbreviations: CFA, confirmatory factor analysis; EDR, emotion dysregulation.
Figure 2 displays the item loadings on their respective dimensions of the ADHD scale. The findings indicate that each item obtained a high loading score within its dimension, with all values surpassing 0.40. This suggests a robust association between the items and their intended dimensions, affirming the construct validity of the scale. Additionally, the results reveal a strong correlation among the different dimensions of the scale, further supporting the interrelated nature of the constructs being measured.
Figure 3 displays the item loadings on their respective dimensions of the EDR scale. The findings indicate that each item obtained a high loading score within its dimension, with all values surpassing 0.40. This suggests a robust association between the items and their intended dimensions, affirming the construct validity of the scale. Additionally, the results reveal a strong correlation among the different dimensions of the scale, further supporting the interrelated nature of the constructs being measured.
STUDY PROCEDURES
The researchers requested that the primary teacher in each class complete the ADHD scale for each student between September 1 and November 1, 2023. Thirty of the 30 teachers (100%) who were requested to participate consented. Teachers used the ADHD scale to assess 500 students in the participating classes, of which 55% were boys and 45% were girls. The evaluation conducted by their school revealed that each child assessed on the scale had a distinct set of learning difficulties. Afterward, in the second stage, the scales from the first application were sorted. And the 180 students who had the highest ratings on the ADHD scale were chosen as their pupils. Before working with children to complete the scale, written informed consent was sought from each teacher. The Saudi Ministry of Education gave the permission to contact teachers. The Helsinki Declaration’s guiding principles were followed while conducting the study. To screen students for ADHD, the primary teacher in each class was asked to complete the ADHD Diagnostic Teacher Rating Scale. The second step of the assessment process involved choosing students who had previously been classified as having one or more forms of ADHD using the EDR scale.
RESULTS
Q1. What is the impact of ADHD on EDR?
In this study, the structural model was employed to examine the impact of ADHD on EDR, as depicted in Figure 4. Within the structural model, the causal effect of the independent variable X on its dependent variable Y must be statistically significant. This significance indicates a meaningful relationship between the variables and provides evidence for the influence of ADHD on EDR.
The proposed measurement model of influence of ADHD on EDR. Abbreviations: ADHD, attention-deficit/hyperactivity disorder; CFI, comparative fit index; EDR, emotion dysregulation; NFI, normed fit index; RMSEA, root mean square error of approximation; TLI, Tucker–Lewis index.
The analysis demonstrated that the model exhibited a good fit with the data. Figure 4 depicts FLs ranging from 0.73 to 0.99 for all sub-instruments, indicating values above the recommended threshold of 0.5. Additionally, the squared multiple correlations (SMCs) for the sub-instruments ranged from 0.57 to 0.96, surpassing the minimum threshold of 0.30. Furthermore, the root mean square error of approximation (RMSEA) value was 0.074, which is below the recommended cutoff of 0.08. Moreover, the comparative fit index (CFI), Tucker–Lewis index (TLI), and normed fit index (NFI) had values of 0.972, 0.956, and 0.944, respectively, all exceeding the desired threshold of 0.90. Consequently, the model fit analysis indicated a strong fit, demonstrating a favorable level of goodness of fit for the model.
After establishing the validity and reliability of the scales used, we proceeded with SEM to explore the relationship between ADHD and EDR. The findings of the study exhibited a strong alignment with the collected data, as presented in Table 2. The chi-square to its degree of freedom ratio (χ2/df) was 1.87, indicating a satisfactory fit as it is below the threshold of 5. Furthermore, the RMSEA index was 0.074, which is lower than the recommended cutoff of 0.08, suggesting a favorable model fit. Additionally, the NFI (0.944), TLI (0.956), and CFI (0.972) indices demonstrated a robust agreement with established benchmarks in the literature, indicating an excellent fit for the model.
All of the hypotheses put forth in the study were confirmed. Specifically, ADHD exhibited a significant and positive influence on EDR.
Table 4 provides an overview of the indicators of the internal construct validity, thus substantiating the internal construction validity of the scale items. This assessment was undertaken to validate the outcomes of the CFA that was conducted on the selected model, assessing the relationship between the scale items and their respective dimensions. The table further demonstrates the alignment of the model with the observed data, affirming that all indicators meet the predetermined criteria established for the study. These findings lend support to the stability of the model about the relationships among the scale items.
CFA outcomes regarding the adopted model’s fit to the relationship between scale items and their respective dimensions.
| Name of category | Indicators of the internal construct validity | Level of acceptance | Indices in the proposed model |
|---|---|---|---|
| Absolute fit | χ2 | P > 0.05 | Significant |
| RMSE | RMSE < 0.08 | 0.074 | |
| Incremental fit | CFI | CFI > 0.90 | 0.972 |
| TLI | TLI > 0.90 | 0.956 | |
| NFI | NFI > 0.90 | 0.944 | |
| Parsimonious fit | χ2/df | χ2/df < 5.0 | χ2/df = 1.87 < 5.0 |
Abbreviations: CFA, confirmatory factor analysis; CFI, comparative fit index; NFI, normed fit index; RMSE, root mean square error; TLI, Tucker–Lewis index.
Q2. Do the father’s education, mother’s education, and gender factors predict ADHD?
To answer the question, independent variables (father’s education, mother’s education, and gender) predicted ADHD. The only one of the variables that affect ADHD is the mother’s education level; in other words, only the mother’s education level affects ADHD (t = 5.848, sig = 0.000); the other two factors did not. The findings indicate that gender and father’s education level are not factors in ADHD risk as shown in Table 5, which demonstrates the summary of regression analysis for variables predicting ADHD. Figure 5 shows the estimated marginal means of ADHD by mother’s education level.
Estimated marginal means of ADHD by mother’s education level. Abbreviation: ADHD, attention-deficit/hyperactivity disorder.
Summary of regression analysis for variables predicting ADHD.
| Model | Unstandardized coefficients | Standardized coefficients | t | Significance | ||
|---|---|---|---|---|---|---|
| B | Standard error | Beta | ||||
| 1 | Constant | 98.145 | 3.571 | 27.485 | 0.000 | |
| Gender | 2.840 | 1.744 | 0.088 | 1.629 | 0.109 | |
| Mother’s education | 12.995 | 2.222 | 0.795 | 5.848 | 0.000 | |
| Father’s education | 1.938 | 2.121 | 0.124 | 0.914 | 0.364 | |
Abbreviation: ADHD, attention-deficit/hyperactivity disorder.
According to the results shown in Figure 5, children of mothers with high levels of education scored highly on the ADHD scale, and vice versa for mothers with low or no education.
DISCUSSION
The findings of this research offer strong evidence for the significant influence of ADHD on EDR. The structural model utilized exhibited a good fit with the data, indicating a meaningful connection between ADHD and EDR. Specifically, the FLs varied from 0.73 to 0.99, exceeding the recommended threshold of 0.5, and the SMCs ranged from 0.57 to 0.96, well surpassing the minimum threshold of 0.30. Furthermore, the RMSEA value of 0.074, alongside the CFI, TLI, and NFI values surpassing 0.90, collectively suggest a favorable model fit.
These results are in line with previous studies that have frequently emphasized the co-occurrence of ADHD and EDR. For instance, Esmaeilpour and Mohammadzadeh (2024) proposed that EDR is often inherent in ADHD, while Pylypow et al. (2020) and Bodalski et al. (2023a,b) highlighted the overlapping nature of these conditions. This study supports the “lumpers” model, suggesting that EDR is a fundamental aspect of ADHD rather than a separate comorbidity. Moreover, the significant and positive impact of ADHD on EDR validated in this study echoes the claims of Antony et al. (2022) and Bunford et al. (2018), who pointed out that EDR exacerbates the primary symptoms of ADHD, like impulsivity and hyperactivity.
Prior research has presented differing conclusions regarding the relationship between ADHD and EDR, a gap that this study contributes to filling. For example, Eltyeb (2023) and Hall et al. (2020) suggested that emotional symptoms are pivotal to ADHD, a viewpoint supported by the present findings. In contrast, some researchers, such as Turkia et al. (2021), Faraone et al. (2019), and Chutko et al. (2023), emphasized the distinct yet interconnected nature of EDR and ADHD, proposing that these should be viewed as separate disorders that interact. However, this study leans toward the integrated perspective where ADHD and EDR are inherently connected, enhancing the overall comprehension of ADHD.
The regression analysis uncovered that among the independent variables (father’s education, mother’s education, and gender), only the mother’s level of education has an influence on ADHD; the mother’s educational achievement is a reliable predictor of their children’s ADHD, while the other two factors do not show such impact. The results indicate that gender does not predict ADHD. These findings are consistent with AlZaben et al.’s (2018) study. Nonetheless, this study contrasts with the American Psychiatric Association’s (2013) findings, which suggested that gender played a role in ADHD and that males outnumbered females by nearly 6:1.
Research has explored the association between a mother’s education and various facets of her child’s development, such as behavior and hyperactivity. Torvik et al. (2020), for instance, noted in their research that a mother’s educational level is often used as a proxy for socioeconomic status. A higher socioeconomic status is linked to greater maternal education. Mothers with higher education tend to have better access to resources, provide a stimulating home environment, and offer enhanced educational opportunities for their children.
More educated mothers tend to have more mentally stimulating situations at home. Mothers who have completed higher education may know more about excellent parenting strategies and how children develop (Al-Mohsin et al., 2020). Given that Saudi women enroll in colleges at a higher rate than Saudi males, the high level of education among moms in this study could be indicative of this. According to Setyanisa et al.’s (2022) study, the likelihood of ADHD is higher among young mothers and mothers with lower levels of education. Good parenting approaches have been related to improved behavioral outcomes in children, such as reduced hyperactivity. Better access to healthcare services is typically linked to better maternal education levels (AlZaben et al., 2018).
CONCLUSIONS
This study has provided significant insights into the relationship between ADHD and EDR, as well as the influence of parental education and gender on ADHD. The structural model demonstrated a strong and statistically significant impact of ADHD on EDR. This confirms that EDR is a core component of ADHD, supporting the integrated view proposed by the “lumpers” model. The study’s findings are consistent with previous research suggesting that EDR intensifies ADHD symptoms, such as impulsivity and hyperactivity, and should be considered a key diagnostic feature of ADHD. The model exhibited excellent fit indices (e.g. FL, SMC, RMSEA, CFI, TLI, NFI), indicating that the proposed scales for ADHD and EDR are reliable and valid. The significant FLs and high SMCs further validate the robustness of the model, reinforcing the study’s conclusions. Among the predictors examined (father’s education, mother’s education, and gender), only the mother’s education level significantly influenced ADHD. Children of mothers with higher education levels showed higher ADHD scores. The lack of significant influence from father’s education and gender aligns with some previous studies, emphasizing the unique role maternal education plays in ADHD prevalence and reporting.
The strong association between ADHD and EDR suggests that treatment and intervention strategies for ADHD should also address EDR to improve overall outcomes. The influence of maternal education on ADHD highlights the need for educational support and awareness programs targeted at parents, particularly mothers, to better manage and report ADHD symptoms.
LIMITATIONS AND FUTURE DIRECTIONS
This research study is subject to several limitations that warrant consideration. First, the inclusion of primary school pupils in our sample raises concerns about the generalizability of the findings to other age groups or clinical populations. Therefore, the applicability of the current findings to a broader range of individuals necessitates further research. Additionally, it is important to note that all data were collected exclusively from the eastern region during the fall of 2023. Consequently, the extent to which the current findings can be extrapolated to the entire Saudi environment remains uncertain. To ensure the appropriate utilization of the findings pertaining to EDR and ADHD across diverse groups, additional research efforts are warranted.
Future research should focus on several important directions to enhance the understanding and applicability of the EDR scale and the ADHD scale. First, it is crucial to replicate the existing factor structure of these scales in diverse samples to validate their robustness and generalizability. Replication studies will contribute to establishing a solid foundation for the interpretation and use of these scales in various contexts. Furthermore, conducting assessments of EDR and ADHD in both clinical and community samples would be valuable in generating normative data and establishing cutoff scores that indicate clinically significant levels of EDR or ADHD symptoms. Such research endeavors will enhance the clinical utility of these measures and facilitate treatment decision-making processes. It is important to acknowledge that the selected constructs for the validation of the EDR and ADHD scales may not encompass all relevant behavioral or clinical aspects. Therefore, future investigations could explore additional indicators, such as the specific diagnosis status of individuals or a comprehensive assessment of counseling utilization. This comprehensive approach will provide a more comprehensive understanding of the scales and their implications. Lastly, it is essential to recognize that the brevity of the EDR scale may limit its ability to capture all dimensions of EDR compared to longer and more precise scales. Consequently, the EDR scale may have limitations in its capacity to thoroughly assess EDR. Future research may consider incorporating scales with more extensive and refined dimensions to provide a more comprehensive assessment of EDR.
The study opens up new research pathways by suggesting the need for longitudinal studies and deeper exploration of the mechanisms by which maternal education influences ADHD. This sets the stage for future investigations that can further refine ADHD models and interventions, ultimately improving outcomes for affected individuals. These innovative contributions not only enhance the current understanding of ADHD and its relationship with EDR but also provide practical tools and frameworks that can be adopted in both research and clinical settings.
CONTRIBUTIONS
The integration of ADHD and EDR in a robust structural model in this study advances the field, showing their intrinsic connection unlike previous models. Instead of treating them as separate constructs, this model positions EDR as a fundamental aspect of ADHD, offering a comprehensive framework that can improve diagnostic accuracy and treatment approaches. A significant methodological contribution lies in the development and validation of new scales for ADHD and EDR with high reliability and validity. These scales, displaying FLs above recommended thresholds and strong fit indices, equip researchers and clinicians with reliable tools for assessing ADHD and EDR across diverse populations. The rigorous validation of translated ADHD scales in the Saudi context by this study addresses a crucial gap in the literature, ensuring linguistic and cultural appropriateness of the tools for more precise assessments and effective treatments.
A novel finding in ADHD research is the significant prediction of ADHD in children by maternal education level, while paternal education and gender do not play a significant role. This underscores the importance of maternal educational background in comprehending and handling ADHD, suggesting targeted support for parents and educational programs as potential interventions. Contributing to the limited research on ADHD in non-Western contexts, this study sheds light on the Saudi Arabian context. The examination of ADHD prevalence and predictors in Saudi Arabia enhances the global understanding of ADHD, emphasizing the necessity for culturally sensitive diagnostic tools and interventions.