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Review

Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects

by
Esperanza Bausela-Herreras
1,
Yurena Alonso-Esteban
2 and
Francisco Alcantud-Marín
3,*
1
Department of Health Sciences, Public University of Navarra, 31008 Pamplona, Spain
2
Faculty of Social and Human Sciences, University of Zaragoza, 44003 Teruel, Spain
3
Department of Developmental and Educational Psychology, University of Valencia, 46010 Valencia, Spain
*
Author to whom correspondence should be addressed.
Children 2024, 11(1), 58; https://doi.org/10.3390/children11010058
Submission received: 8 December 2023 / Revised: 26 December 2023 / Accepted: 28 December 2023 / Published: 30 December 2023
(This article belongs to the Special Issue Reviews on Current Advances in Child Neurology Update)
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Versions Notes

Highlights

What are the main findings?
  1. Deficits in flexibility and inhibition are highlighted as key diagnostic markers for the early detection of autism.
  2. The BRIEF-P tool is validated as an effective instrument for assessing executive functioning in children with ASD, which family members and teachers can administer without requiring specific training.
What is the implication of the main finding?
  1. The findings have significant implications for early autism detection and intervention, as using flexibility and inhibition as markers could improve early diagnosis.
  2. The BRIEF-P tool can be valuable in the diagnostic process and in planning personalized interventions.
  3. Early identification of executive deficits may lead to more individualized therapeutic strategies.

Abstract

:
Background. ADHD is a neurodevelopmental disorder that is accompanied by executive challenges. Objectives. To obtain evidence of the usefulness of the BRIEF-P and to analyze the possible ceiling and floor effect of its scores in the assessment of executive function in preschoolers with signs compatible with a possible diagnosis of ADHD. Method. A search was performed in Science Direct, NCBI (PubMed), and ProQuest Education Journals during the period 2012–2022. We included studies that evaluated samples of individuals with symptomatology compatible with ADHD, with an age range between 2 and 6 years, published in English or Spanish. Of a total of 2538 articles, only seven met the inclusion criteria. The risk of bias was assessed using the QUADAS-2 questionnaire. The main variables were age and executive functioning. Conclusions. Executive deficits in early-age individuals with symptoms compatible with ADHD are more extensive than just deficits in working memory. A floor effect has been found in tests associated with hot executive functions and a ceiling effect in cold executive functions. This makes it necessary to use different tests to assess executive performance in preschoolers with ADHD-compatible symptomatology and to design intervention proposals accordingly. The BRIEF-P is an instrument that facilitates obtaining a sensitive and discriminative executive profile, although it should be used in combination with other neuropsychological performance tests.

1. Introduction

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders, and its prevalence in children is estimated at 2–7% [1]. Although there are very old precedents for its description in the literature (see [2]), its current concept dates back to the publication of the DSM-IV-TR [3]. The most characteristic symptoms are inattention (daydreaming), forgetting or losing things, motor restlessness, excessive talking (without control or respecting the turn of the conversation), making careless mistakes or committing recklessness, problems in relationships with others, etc. In the context of ADHD, daydreaming is often associated with inattention. It is a symptom not to be confused with “cognitive disengagement syndrome” (CDS), which has been replaced by “sluggish cognitive tempo” (SCT). SCT involves a constellation of behaviors involving excessive daydreaming, confusion and mental fogginess, and slowness of behavior and thinking. SCT is a distinct syndrome [4], although much work and research remain to clarify various aspects, such as its nature.
The DSM 5 [5] establishes as a criterion the presence of a persistent behavioral pattern of inattention and/or hyperactivity/impulsivity that interferes with functioning or development. In DSM 5 TR [6], up to three diagnostic subcategories are established depending on the combined presence of inattention and hyperactivity. The diagnostic criteria for ADHD in the DSM-5-TR remained identical to those in the previous edition. Koutsoklenis and Honkasilta [7] make a critique of these criteria, concluding that they are ambiguous, redundant, and arbitrary, reinforcing normality and inadequate attention to context.
Because of the nature of ADHD (multicausal etiology and heterogeneous symptoms [8,9]), different psychometric tools useful in the diagnostic process are cited in the scientific literature, according to DSM-5 criteria (e.g., Conners 3rd Edition [10]; ADHD Rating Scale-5 for Children and Adolescents [11], among others).
Many of the symptoms of ADHD are linked to different impairments of executive function (EF): inhibition, self-regulation, working memory, and flexibility, among others [12,13,14]. However, given the heterogeneity of ADHD, its high co-morbidity with other disorders and difficulties [15,16,17], and the different conceptions of the EF, there is no consensus on the existence of a characteristic profile [18,19,20]. Thus, the assessment of EF is taken as complementary information aimed both at excluding another disorder and at planning interventions.
Most studies on EFs consider the Miyake et al. [21] model as a reference, emphasizing cold EFs: inhibitory control [22], cognitive flexibility (or set shifting) [23], and working memory [24], among others. There is also a more-or-less-general consensus that the development of EFs starts during the first years of life and accelerates with schooling [25,26]. Evidence suggests that it is during the school period (6 to 12) that the development of hot and cold EFs is most evident [27]. Hot EFs, which require the intervention of affective regulation processes, include inhibitory control, decision making, and emotional regulation. Among the cold EFs, they are linked to reasoning, MT, attention, cognitive flexibility, and planning [28].
Some studies reveal the possibility of a slower development of hot EFs compared to cold EFs [29,30]. Rastikerdar et al. [31] compare the development of cold and hot executive functions in people with and without ADHD, pointing out differences in their development throughout the life cycle. Thus, cold EFs reach adult levels by the age of twelve, while hot EFs progress more slowly at school age and improve throughout adolescence. Shakehnia et al. [32], after controlling for age, parental education, and number of children, report significant differences between group means (hyperactivity disorder versus ADHD) in EF assessed with BRIEF (Behavior Rating Inventory of Executive Function): hot executive function (Behavioral Regulation Index), cold executive function (Metacognitive Index), total executive function, and other subscales. These researchers consider that hot executive functions and cold executive functions are related and interact, but that in people with ADHD, they are dissociated. Several studies have found a delay in the development of EF in people with ADHD [33,34]. This delay is not homogeneous or equal in all dimensions. Delays have been found in: (i) inhibitory control [33], (ii) working memory [35]; (iii) cognitive flexibility [36]; and (iv) delayed gratification and risky decision-making [37]. In conclusion [35], people who develop ADHD present a wide range of cognitive deficits, but they are only manifested in some EFs (fundamentally, cold EFs; see model by Zelazo and Carlson [28]). Several prospective studies have shown in individuals with ADHD the association of executive function deficits with poorer academic performance [38], the occurrence of substance use disorders [39], and other psychiatric comorbidities [40].
In general terms, it is accepted that the main impairment in people who develop ADHD is a deficit in inhibitory control (cold executive function) [33,41,42,43,44], to such an extent that Barkley [45] proposes the self-regulation model, understanding that the basic problem of people with ADHD is a deficit in behavioral inhibition which, in turn, has repercussions on other parallel cognitive and psychological processes: non-verbal working memory, verbal working memory, planning and reconstruction, and the self-regulation of emotions, motivation and arousal. Barkley’s model has been studied and compared with others that also consider self-regulation as the core deficit of ADHD [46]. However, symptom variability poses irresolvable problems for a model based predominantly on a single factor of EF. Evidence suggests that deficits in working memory [27,47,48,49,50] and deficits in cognitive flexibility (cold executive function) are also present in individuals who develop ADHD. A lack of adaptive capacity (cognitive flexibility) allows individuals to adapt their cognitive processing strategies to cope with unforeseen events [51], and its deficit correlates with mental health problems [52]. From a more organismic point of view, the results of studies based on brain imaging using functional magnetic resonance imaging (fMRI) show that the anterior cingulate, as well as the superior and inferior frontal gyri, which are involved in cognitive flexibility, are less active in people with ADHD [53], confirming the previous point.
Although the scientific literature shows a high level of interest in EF, its assessment remains complex and there is no consensus on the type of measure to use. The complexity of measuring EF lies in the different conceptual models [54] and in the need to perform a task where EF performance is evidenced. Some of the measures used, such as the Stroop Test, the Tower of Hanoi, or the Wisconsin Card Sorting Test, have low ecological validity and are not representative of the individual’s functioning in real-life contexts [55,56,57,58,59,60,61]. Based on these measures and sometimes benefiting from technological resources, digitized test batteries such as CANTAB (Cambridge Neuropsychological Test Automated Battery, [62]) have been developed. These include the NIH EXAMINER (Executive Abilities: Measures and Instruments for Neurobehavioral Evaluation and Research [63]), the CAS (Cognitive Assessment System [64] and CAS2 [65]), the D-KEFS (Delis–Kaplan Executive Function System [66]), and the CEFI (Comprehensive Executive Function Inventory [67]), among others.
However, these systems are complex to implement at school age due, among other reasons, to the high number of evaluation requests. An alternative is questionnaires based on rating scales such as the BRIEF (Behavior Rating Inventory of Executive Function; [68]). BRIEF is one of the most widely used scales in ADHD diagnosis and intervention. It is a family of questionnaires that attempt to capture the behavioral manifestations of executive dysfunction across the lifespan (2 to 90 years). The original BRIEF [68] has a range of application from 5 to 18 years of age, with separate forms for parents and teachers. There are self-report versions for adolescents (11–18 years) (BRIEF-SR [69]) and for adults (BRIEF-A [70]) from 18 to 90 years with separate self-report or third-person forms. As mentioned above, ADHD presents the first symptoms at early ages and has a need for valid and reliable tools at early stages in order to plan early intervention [71], so it is worth highlighting the preschool version of the BRIEF.
BRIEF-P (Behavior Rating Inventory of Executive Function-Preschool Version [72]) is an assessment tool adapted to Preschool Age (designed for children aged 2 to 5 years). The questions and scenarios are tailored to the understanding and experience of young children. BRIEF-P uses reports of observed behavior in everyday situations, providing a more complete and contextualized picture of the child’s executive skills in real-life environments. BRIEF-P results can be useful for planning specific interventions that address the identified areas of difficulty.
The assessment and diagnosis of ADHD are clinical and should be conducted by trained mental health professionals, and BRIEF-P is a tool that can complement the comprehensive assessment of the child. Additionally, the information gathered through BRIEF-P should be interpreted in the context of a broader evaluation that includes clinical observation, history collection, and other assessment methods.
Although there is evidence for the psychometric goodness of the BRIEF [73] and in particular of the BRIEF-P [74], at the clinical level the differentiation between typically developing children and ADHD is made dependent on the combination of the cut-off points of the test [75]. Examining the floor and ceiling effects of the BRIEF-P in clinical use is crucial for several reasons. Firstly, understanding these effects allows for assessing the instrument’s sensitivity to detect both deficiencies and exceptional abilities in executive function within the target population. Additionally, it helps to identify potential limitations of the instrument in its ability to discriminate adequately between extreme levels of performance. This information is essential for an accurate interpretation of results and informed decision-making in the clinical setting. By addressing floor and ceiling effects, we can enhance the utility and validity of the BRIEF-P as an assessment tool for preschool-aged children with neurodevelopmental disorders.
The aim of this paper is to determine, through an analysis of the scientific literature, the floor and ceiling scores of the EF components measured by the BRIEF-P in a population with symptoms compatible with ADHD.

2. Method

This systematic search and meta-analysis was registered in the Prospero platform under the registration number CRD42023465855. Articles in Spanish and English published in the databases Science Direct, NCBI (PubMed), and ProQuest Education Journals were reviewed. The articles had to be published between 2013 and 2023. In the databases, the search was restricted to “all article” and “journal article” in psychology, health, and education journals. The keywords were Attention Deficit Hyperactivity Disorder or ADHD or ADHD; Behavior Rating Instrument of Executive Function—School or BRIEF-P.
The research question was formulated following PICOS (Population, Intervention, Comparison, Outcome, Study Design) in an attempt to delve into the floor effect and ceiling effect of the BRIEF-P as an instrument to be considered in the early identification of symptoms compatible with ADHD:
Regarding the floor effect (minimum score), are there statistically significant differences in the executive profile of preschool children with ADHD versus typically developing children?
In terms of the ceiling effect (maximum score), are there significant differences in the executive profile of preschool children with ADHD versus typically developing children?

Search Strategy

In order for studies to be included in the review, they had to meet the inclusion/exclusion criteria set out in Table 1. The methodological structure of the search and screening methods followed the guidelines of the PRISMA guide (Preferred Reporting Items for Systematic Reviews and Meta-Analyses [76,77]). The expressions of the searches were different for each database according to the database conditions, as shown below:
(i)
Science Direct ◊
-
(Attention deficit hyperactivity disorder or ADHD) and (Behavior Rating Instrument of Executive Function-Preschool).
-
(Attention deficit hyperactivity disorder or ADHD) and (BRIEF-P).
(ii)
NCBI ◊ PubMed Central ◊ 247 results
-
(Attention deficit hyperactivity disorder + or + ADHD) and (BRIEF-P).
(iii)
ProQuest Education Journals
-
((Attention deficit hyperactivity disorder or ADHD) AND (BRIEF-P)).
AND stype.exact(“Scholarly Journals”) Education Database.
-
(Attention deficit hyperactivity disorder or ADHD) and (Behavior Rating Instrument of Executive Function-Preschool) Education Database.
After analyzing the 2538 papers, only 7 papers were selected that met the inclusion-exclusion criteria (see Table 1). The resulting flow can be visualized in Figure 1.

3. Results

A meta-analysis was conducted, continuing with the raw data available in each of the publications. A random-effects model was chosen for a meta-analysis. The random-effects model operates on the premise that the true effect may vary from one study to another due to differences (heterogeneity) among studies [77].
Table S1 (see Supplementary Materials) summarizes the characteristics of the seven studies included in the review with participants under 6 years of age with ADHD-compatible symptoms compared to typically developing participants, with executive functioning being assessed using BRIEF-P and with data on mean scores obtained by the ADHD group versus the typically developing control group. Table 2 shows the data relating to the number of participants in each study according to diagnosis.

3.1. Risk of Bias

We followed the PRISMA 2020 checklist for structured abstracts: Title, Background, Methods, Results, Discussion, and Other. To assess the methodological quality of the studies, we used the criteria outlined in Quality in Prognosis Studies (QUIPS), which consider six specific domains: sample selection, representativeness of the sample, measurement of variables, measurement bias, follow-up bias, and statistical analysis.

3.2. Floor Effect and Ceiling Effect

In the case of ADHD, variability in executive functioning can be significant among individuals. The main reasons to take into account the floor or ceiling effect in this sample are (i) limitations in measurement sensitivity: the floor effect occurs when most participants score very low, indicating that the measure used may not be sensitive enough to capture variations in performance; (ii) limitations in variance: the ceiling effect occurs when most participants score very high, suggesting that the measure may not be able to distinguish adequately between higher levels of ability or performance; (iii) impact on test validity: if a test is not able to accurately measure both lower and higher levels of the variable it is assessing, it can impact the overall validity of the test; and (iv) reflection of sample diversity: the presence of floor or ceiling effects may indicate the need for a more appropriate measurement tool, especially if the sample includes individuals with a wide range of abilities or levels of functioning.
Considering these effects is essential to ensure that the measure used is valid and sensitive to variations in performance within the studied sample.
A comparison was made between the group with symptoms compatible with ADHD and the typically developing group, considering the lower and upper scores, to find out the floor effect and the ceiling effect. Effect size estimates were calculated, taking Cohen’s d, the random effects model, as the effect size measure.
The results are presented in a forest plot or effects graph in which the results obtained in each study, as well as the overall effect and its 95% confidence interval, are presented in vertical order according to a certain criterion (the study number). The studies with lower precision are those that have greater visual impact (longer horizontal lines due to the greater confidence interval), and the mean value of each study is usually represented by a symbol (square or diamond) whose area is proportional to the weight with which the study intervenes in the overall calculation (inversely proportional to the variance), highlighting the most precise studies.

3.2.1. Floor Effect

The studies with the lowest mean score obtained after the application of the BRIEF-P were selected. As a clinical instrument, higher scores indicate greater executive dysfunction.
The 10th percentile was chosen, placing the mean score between the following values: ADHD group (15–26) and typically developing group (13–20) Five studies obtained mean scores on the Flexibility clinical scale and on the Emotional Control index. The studies included in the meta-analysis were the mean score in the ADHD-compatible symptoms group [14,26] and the mean score of the typically developing group [12,32]. Significant differences were observed between the ADHD group and the typically developing control group (d = 0.615; Z = 4.335; p ≤ 0.001; 95% CI 0.337–0.893) (Table 3). With d = 0.615, we are in the moderate range. This suggests that the observed difference has practical significance but is not substantial enough to be considered a large effect. It may indicate that, although there is a significant difference, it might not be substantial enough to have a dramatic or practical impact.
The studies included in the meta-analysis are represented in a forest plot (Figure 2). The study with the highest impact is study 4 and the study with the lowest impact is study 2.

3.2.2. Ceiling Effect

The studies with the lowest scores were selected. Thus, studies with scores above the 90th percentile were selected, placing the mean score between the following values: ADHD group (100–108) and typically developing group (54–84). Four studies obtained mean scores on the Flexibility clinical scale and on the Emotional Control index. The studies were included in the meta-analysis with the mean score of the ADHD group (84,103) and the score of the typically developing group (67,89).
Significant differences were observed between the group with symptoms compatible with ADHD and the typically developing control group (d = 2.962; Z = 3.249; p ≤ 0.001; CI 95% 1.175–4.749) (Table 4). Such a large effect size suggests a noteworthy and practically significant difference between the compared groups.
The study with the highest impact is study 3 and the study with the lowest impact is study 7. The studies included in the meta-analysis are represented in a forest plot (Figure 3).

4. Discussion and Conclusions

The executive deficits presented by individuals in the early stages of the life cycle with symptoms compatible with ADHD are broader than deficits in working memory. There is a need for comprehensive assessment protocols for all dimensions that make up EF in line with the model of Miyake et al. [21] and adapted for children by Wiebe et al. [83] and the model developed by Zelazo and Carlson [28]. The results of the assessment will be the key to developing a personalized intervention [84]. With this review, we aimed to obtain evidence of the usefulness of the BRIEF-P by analyzing its floor and ceiling effects in the assessment of executive function in preschoolers with signs compatible with a possible diagnosis of ADHD.
The floor effect was associated with the Flexibility clinical scale and the Emotional Control index, both hot executive functions according to the model proposed by Zelazo and Carlson [28]. The study with the highest impact was the study by Skogan et al. [80] and the one with the lowest impact was the study by Ezpeleta and Granero [79]. Like other researchers [85], they suggested that emotional dysregulation contributes to ADHD symptomatology and is prevalent in ADHD across the lifespan.
The ceiling effect was associated with two of the BRIEF-P indices: Global Executive Functioning and the Emergent Metacognition index, configured by the clinical scales Working Memory and Planning/Organization. These indices are associated with the cold dimensions of executive functioning proposed in the model of Zelazo and Carlson [28]. The study with the highest impact is the study by Zhang et al. [22], and the one with the lowest impact is the study by Çak et al. [71]. Preschoolers with early symptoms consistent with ADHD presented significant difficulties in BRIEF-P. These results are in line with previous studies in which the core domains of EF (response inhibition [86,87], working memory [88,89], and flexibility [36,53]) were closely associated with ADHD symptoms.
In the mentioned results, three studies have been identified as reporting the floor effect in the BRIEF-P [22,79,80]. This implies that in these studies, participant scores were predominantly concentrated at lower levels of ability, suggesting that the instrument may not be sufficiently sensitive to detect differences in lower-level executive function skills in preschool children.
On the other hand, two of these studies identified reported the ceiling effect in the BRIEF-P [22,79]. This indicates that in these studies, participant scores were mainly concentrated at higher levels of ability, suggesting that the instrument may not be sensitive enough to differentiate between higher-level executive function skills in these preschool children.
Both floor and ceiling effects can be indicative of limitations in the test’s sensitivity to accurately measure the full range of abilities in the evaluated population. This may impact the test’s ability to detect real changes in performance over time or between different groups.
In summary, these results highlight potential limitations in the sensitivity of the BRIEF-P to accurately measure and differentiate between different levels of executive function skills in preschool children, both at lower and higher levels. This may necessitate adjustments to the instrument to enhance its assessment capability across the full spectrum of skills.
The findings obtained suggest potential limitations in the sensitivity of the BRIEF-P, prompting the consideration of several improvement actions for its strengthening: (i) Conduct a thorough review of the BRIEF-P design to identify possible areas for improvement. This may involve evaluating and adjusting items that could be contributing to the floor and ceiling effects. (ii) Consider the inclusion of new items that more effectively address the diversity of executive function skills in preschool children. This could help broaden the measurement range and enhance the test’s sensitivity. (iii) Carry out additional validation studies to confirm the effectiveness of the proposed modifications. This may include pilot testing with representative samples of the target population to ensure that the revisions have the desired impact. (iv) Consider adjustments to the scoring scale or interpretation of results to mitigate floor and ceiling effects. This could involve revising skill classification criteria to more accurately reflect the performance of preschool children. (v) Establish a continuous monitoring system to assess the effectiveness of the implemented modifications. This will allow for additional adjustments as needed and ensure the ongoing improvement of the BRIEF-P.
By implementing these recommendations, the goal is to strengthen the BRIEF-P’s ability to accurately measure executive functions in preschool children and overcome the identified limitations.
Studies suggest that children with ADHD exhibit statistically significant and large working memory deficits relative to their typically developing peers; however, executive deficits, which are broader, affect several executive dimensions including, for example, emotional dysregulation, and need to be further explored. This requires a comprehensive assessment and subsequent intervention, accordingly.
The results obtained point to the need to work on cold executive functions in preschoolers with symptoms compatible with ADHD. These include working memory, attentional control, problem solving, cognitive flexibility, phonological fluency, semantic fluency, error detection, and the inhibition of automatic responses [90].
The review has some limitations, as it is based on studies with small sample sizes. The average age of the participants (before ADHD diagnosis) precludes considering the influence of factors related to developmental stage and maturity in the study of people with ADHD.
The study of EF in preschoolers involves greater difficulties. The structure of EF in preschoolers requires further study. Some studies suggest a single general factor of executive functioning, with these functions being more differentiated with age, and others propose two (inhibition, working memory), three (inhibitory self-control, flexibility, emergent metacognition) or four (hyperactive behaviors, attention problems, disinhibition behaviors, emotional regulation behaviors) factors.
Subtypes of ADHD also need to be considered in future studies. Follow-up with children assessed for the first time at preschool age, in additional diagnostic groups and in larger samples, together with multiple performance-based EF tests, would be necessary. For future studies, we plan to analyze the concordance between standardized and performance measures in the identification of executive difficulties in preschoolers with early symptoms compatible with ADHD.
Finally, temporal variability may be a limitation of the study. The studies were focused on the last decade. Study results may vary over time due to changes in clinical practice, technological advances, or changes in the population studied. A meta-analysis may not fully capture these temporal variabilities.
These results provide us with information on the executive dimensions to be strengthened in preschoolers with early symptoms compatible with ADHD and the tests to be included to complement the information obtained after the application of BRIEF-P. This review supports the clinical utility of the BRIEF-P as a measure of EF in preschoolers with ADHD-compatible symptoms in combination with performance-based neuropsychological tests, integrating two models: (i) the three domains proposed by Miyake et al. [21] and (ii) the hot versus cold executive functions model developed by Zelazo and Carlson [28].

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/children11010058/s1, Table S1: Characteristics of the studies included in the review and meta-analysis with their respective bibliographic references.

Author Contributions

Conceptualization, E.B-H. and Y.A.-E.; methodology, F.A.-M.; software, E.B.-H.; validation, E.B.-H., Y.A.-E. and F.A.-M.; formal analysis, E.B.-H.; investigation, E.B.-H.; resources, E.B.-H.; data curation, E.B.-H.; writing—original draft preparation, E.B.-H.; writing—review and editing, Y.A.-E. and F.A.-M.; supervision, F.A.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Sayal, K.; Prasad, V.; Daley, D.; Ford, T.; Coghill, D. ADHD in children and young people: Prevalence, care pathways, and service provision. Lancet Psychiatry 2018, 5, 175–186. [Google Scholar] [CrossRef] [PubMed]
  2. Lange, K.; Reichl, S.; Lange, K.; Tucha, L.; Tucha, O. The history of attention deficit hyperactivity disorder. ASHD Atten. Deficit Hyperact. Disord. 2010, 2, 241–255. [Google Scholar] [CrossRef]
  3. American Psychiatric Association (APA). Diagnóstic and Statistical Manual of Mental Disorders; Text Revision (DSM-IV-TR); American Psychiatric Association: Washington, DC, USA, 2000. [Google Scholar]
  4. Becker, S.P.; Willcutt, E.G.; Leopold, D.R.; Fredrick, J.W.; Smith, Z.R.; Jacobson, L.A.; Burns, G.L.; Mayes, S.D.; Waschbusch, D.A.; Froehlich, T.E.; et al. Report of a Work Group on Sluggish Cognitive Tempo: Key Research Directions and a Consensus Change in Terminology to Cognitive Disengagement Syndrome. J. Am. Acad. Child Adolesc. Psychiatry 2023, 62, 629–645. [Google Scholar] [CrossRef]
  5. American Psychiatric Association (APA). Diagnostic and Statistical Manual of Mental Disorders: DSM-5, 5th ed.; American Psychiatric Publishing: Arlington, MA, USA, 2013. [Google Scholar]
  6. American Psychiatric Association (APA). Diagnóstic and Statistical Manual of Mental Disorders: DSM-5-TR, 5th ed.; American Psychiatric Association: Arlington, MA, USA, 2022. [Google Scholar]
  7. Koutsoklenis, A.; Honkasilta, J. ADHD in the DSM-5-TR: What has changed and what has not. Front. Psychiatry 2023, 13, 1064141. [Google Scholar] [CrossRef] [PubMed]
  8. Faraone, S.; Perlis, R.H.; Doyle, A.E.; Smoller, J.W.; Goralnick, J.; Holmgren, M.A.; Sklar, P. Molecular Genetics of Attention-Deficit/Hyperactivity Disorder. Biol. Psychiatry 2005, 57, 1313–1323. [Google Scholar] [CrossRef] [PubMed]
  9. Millichap, J. Etiologic Classification of Attention-Deficit/Hyperactivity Disorder. Pediatrics 2008, 121, e358–e365. [Google Scholar] [CrossRef]
  10. Conners, C.K.; Pitkanen, J.; Rzepa, S.R. Conners 3rd Edition (Conners 3; Conners 2008). In Encyclopedia of Clinical Neuropsychology; Springer: New York, NY, USA, 2011; pp. 675–678. [Google Scholar] [CrossRef]
  11. DuPaul, G.J.; Power, T.J.; Anastopoulos, A.D.; Reid, R. ADHD Rating Scale—5 for Children and Adolescents: Checklists, Norms, and Clinical Interpretation; Guilford Press: New York, NY, USA, 2016. [Google Scholar]
  12. Antshel, K.; Hier, B.O.; Barkley, R. Executive Functioning Theory and ADHD. In Handbook of Executive Funtioning; Springer: New York, NY, USA, 2014; pp. 107–120. [Google Scholar] [CrossRef]
  13. Barkley, R.A. Attention-Deficit Hyperactivity Disorder: A Handbook for Diagnosis and Treatment; The Guilford Press: New York, NY, USA, 2006. [Google Scholar]
  14. Doyle, A.E. Executive functions in attention-deficit/hyperactivity disorde. J. Clin. Psychiatry 2006, 67 (Suppl. S8), 21–26. [Google Scholar]
  15. Bauermeister, J.; Shrout, P.; Ramírez, R.; Bravo, M.; Alegría, M.; Martínez-Taboas, A.; Chávez, L.; Rubio-Stipec, M.; García, P.R.J. ADHD correlates, comorbidity, and impairment in community and treated samples of children and adolescents. J. Abnorm. Child Psychol. 2007, 35, 883–898. [Google Scholar] [CrossRef]
  16. Gnanavel, S.; Sharma, P.; Kaushal, P.; Hussain, S. Attention deficit hyperactivity disorder and comorbidity: A review of literature. World J. Clin. Cases 2019, 7, 2420–2426. [Google Scholar] [CrossRef]
  17. Marqués-Cabezas, P.; Segura-Rodríguez, A.; García-Barriuso, P.; Gallardo-Borge, L.; Mateos-Sexmero, M.; Blanco, J.; Viuda, M.Q.D.L.D.L.; Perez-Carranza, M.; Aparicio-Parras, A.; Espina-Barrio, J.; et al. Comorbility symptoms in AHDH adult patients. Eur. Psychiatry 2022, 65, S466. [Google Scholar] [CrossRef]
  18. Brown, T.E. Executive Functions and Attention Deficit Hyperactivity Disorder: Implications of two conflicting views. Int. J. Disabil. Dev. Educ. 2006, 53, 35–46. [Google Scholar] [CrossRef]
  19. Castellanos, X.F.; Sonuga-Barke, E.J.S.; Milham, M.P.; Tannock, R. Characterizing cognition in ADHD: Beyond executive dysfunction. Trends Cogn. Sci. 2006, 10, 117–123. [Google Scholar] [CrossRef] [PubMed]
  20. Lambek, R.; Tannock, R.; Dalsgaard, S.; Trillingsgaard, A.; Damm, D.; Thomsen, P. Validating neuropsychological subtypes of ADHD: How do children with and without an executive function deficit differ? J. Child Psychol. Psychiatry 2010, 51, 895–904. [Google Scholar] [CrossRef] [PubMed]
  21. Miyake, A.; Friedman, N.P.; Emerson, M.J.; Witzki, A.H.; Howerter, A.; Wager, T.D. The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis. Cogn. Psychol. 2000, 41, 49–100. [Google Scholar] [CrossRef] [PubMed]
  22. Zhang, H.; Shuai, L.; Zhang, J.; Wang, Y.; Lu, T.; Tan, X.; Pan, J.; Shen, L. Neuropsychological Profile Related with Executive Function of Chinese Preschoolers with Attention-Deficit/Hyperactivity Disorder: Neuropsychological Measures and Behavior Rating Scale of Executive Function-Preschool Version. Chin. Med. J. 2018, 131, 648–656. [Google Scholar] [CrossRef] [PubMed]
  23. Babb, K.A.; Levine, L.J.; Arseneault, J.M. Shifting gears: Coping flexibility in children with and without ADHD. Int. J. Behav. Dev. 2010, 34, 10–23. [Google Scholar] [CrossRef]
  24. Petersen, I.; Hoyniak, C.; McQuillan, M.; Bates, J.; Staples, A. Measuring the development of inhibitory control: The challenge of heterotypic continuity. Dev. Rev. 2016, 40, 25–71. [Google Scholar] [CrossRef]
  25. Bausela-Herreras, E. Development of Executive Function at the Preschool Age. In Handbook of Research on Neurocognitive Development of Excecutive Funtions and Implications for Intervention; IGI Glogal: Hershey, PA, USA, 2022; pp. 1–22. [Google Scholar]
  26. Zelazo, P.; Müller, U.; Frye, D.; Marcovitch, S.; Argitis, G.; Boseovski, J.; Chiang, J.; Hongwanishkul, D.; Schuster, B.; Sutherland, A. The development of executive function in early childhood. Monogr. Soc. Res. Child Dev. 2003, 68, vii-137. [Google Scholar] [CrossRef]
  27. Lensing, N.; Elsner, B. Development of hot and cool executive functions in middle childhood: Three-year growth curves of decision making and working memory updating. J. Exp. Child Psychol. 2018, 173, 187–204. [Google Scholar] [CrossRef]
  28. Zelazo, P.; Carlson, S. Hot and Cool Executive Function in Childhood and Adolescence: Development and Plasticity. Child Dev. Perspect. 2012, 6, 354–360. [Google Scholar] [CrossRef]
  29. Homer, B.D.; Plass, J.L.; Rose, M.C.; MacNamara, A.P.; Pawar, S.; Ober, T.M. Activating adolescents’ “hot” executive functions in a digital game to train cognitive skills: The effects of age and prior abilities. Cogn. Dev. 2019, 49, 20–32. [Google Scholar] [CrossRef]
  30. Prencipe, A.; Kesek, A.; Cohen, J.; Lamm, C.; Lewis, M.; Zelazo, P. Development of hot and cool executive function during the transition to adolescence. J. Exp. Child Psychol. 2011, 108, 621–631. [Google Scholar] [CrossRef] [PubMed]
  31. Rastikerdar, N.; Nejati, V.; Sammaknejad, N.; Fathabadi, J. Developmental trajectory of hot and cold executive functions in children with and without attention deficit-hyperactivity disorder (ADHD). Res. Dev. Disabil. 2023, 137, 104514. [Google Scholar] [CrossRef] [PubMed]
  32. Shakehnia, F.; Amiri, S.; Ghamarani, A. The comparison of cool and hot executive functions profiles in children with ADHD symptoms and normal children. Asian J. Psychiatry 2021, 55, 102483. [Google Scholar] [CrossRef] [PubMed]
  33. Berger, I.; Slobodin, O.; Aboud, M.; Melamed, J.; Cassuto, H. Maturational delay in ADHD: Evidence from CPT. Front. Hum. Neurosci. 2013, 7, 691. [Google Scholar] [CrossRef]
  34. Schoemaker, K.; Bunte, T.; Wiebe, S.; Espy, K.; Deković, M.; Matthys, W. Executive function deficits in preschool children with ADHD and DBD. J. Child Psychol. Psychiatry 2012, 53, 111–119. [Google Scholar] [CrossRef]
  35. Yáñez-Téllez, G.; Romero-Romero, H.; Rivera-García, L.; Prieto-Corona, B.; Bernal-Hernández, J.; Marosi-Holczberger, E.; Guerrero-Juárez, V.; Rodríguez-Camacho, M.; Silva-Pereyra, J.F. Cognitive and executive functions in ADHD. Actas Españolas Psiquiatr. 2012, 40, 293–298. [Google Scholar]
  36. Roshani, F.; Piri, R.; Malek, A.; Michel, T.M.; Vafaee, M.S. Comparison of cognitive flexibility, appropriate risk-taking and reaction time in individuals with and without adult ADHD. Psychiatry Res. 2020, 284, 112494. [Google Scholar] [CrossRef]
  37. Karalunas, S.L.; Huang-Pollock, C.L. Examining relationships between executive functioning and delay aversion in attention deficit hyperactivity disorder. J. Clin. Child Adolesc. Psychol. 2011, 40, 837–847. [Google Scholar] [CrossRef]
  38. Varrasi, S.; Boccaccio, F.M.; Guerrera, C.S.; Platania, G.A.; Pirrone, C.; Castellano, S. Schooling and Occupational Outcomes in Adults with ADHD: Predictors of Success and Support Strategies for Effective Learning. Educ. Sci. 2023, 13, 37. [Google Scholar] [CrossRef]
  39. Vergara-Maragues, E.; González-Saiz, F.; Lozano-Rojas, Ó.; Billbao-Acedos, I.; Fernández-Calderón, F.; Betanzos-Espinosa, P.; Verdejo García, A.; Pérez-García, M. Diagnosing adult attention-deficit/hyperactivity disorder in patients with cocaine dependence: Usefulness of new Barkley executive function symptoms. Trastor. Adict. 2010, 12, 72–78. [Google Scholar] [CrossRef]
  40. Zhang, S.-Y.; Qiu, S.-W.; Pan, M.-R.; Zhao, M.-J.; Zhao, R.-J.; Liu, L.; Li, H.-M.; Wang, Y.-F.; Qian, Q.-J. Adult ADHD, executive function, depressive/anxiety symptoms, and quality of life: A serial two-mediator model. J. Affect. Disord. 2021, 293, 97–108. [Google Scholar] [CrossRef] [PubMed]
  41. Barkley, R. Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychol. Bull. 1997, 121, 65–94. [Google Scholar] [CrossRef] [PubMed]
  42. Hobson, C.; Scott, S.; Rubia, K. Investigation of cool and hot executive function in ODD/CD independently of ADHD. J. Child Psychol. Psychiatry 2011, 52, 1035–1043. [Google Scholar] [CrossRef] [PubMed]
  43. Nejati, V. Reading mind from the eyes in individuals with attention deficit-hyperactivity disorder (ADHD): A meta-analysis. Expert Rev. Neurother. 2022, 22, 889–896. [Google Scholar] [CrossRef] [PubMed]
  44. Nigg, J. Is ADHD a disinhibitory disorder? Psychol. Bull. 2001, 127, 571–598. [Google Scholar] [CrossRef]
  45. Barkley, R. Advances in the diagnosis and subtyping of attention deficit hyperactivity disorder: What may lie ahead for DSM-V. Rev. Neurol. 2009, 48 (Suppl. S2), S101–S106. [Google Scholar]
  46. Servera, M. Modelo de autorregulación de Barkley aplicado al trastorno por déficit de atención con hiperactividad: Una revisión. Rev. Neurol. 2005, 40, 358–368. [Google Scholar] [CrossRef]
  47. Kofler, M.; Singh, L.; Soto, E.; Chan, E.; Miller, C.; Harmon, S.; Spiegel, J. Working memory and short-term memory deficits in ADHD: A bifactor modeling approach. Neuropsychology 2020, 34, 686–698. [Google Scholar] [CrossRef]
  48. Kasper, L.; Alderson, R.; Hudec, K. Moderators of working memory deficits in children with attention-deficit/hyperactivity disorder (ADHD): A meta-analytic review. Clin. Psychol. Rev. 2012, 32, 605–617. [Google Scholar] [CrossRef]
  49. Nejati, V.; Derakhshan, Z.; Mohtasham, A. The effect of comprehensive working memory training on executive functions and behavioral symptoms in children with attention deficit-hyperactivity disorder (ADHD). Asian J. Psychiatry 2023, 81, 103469. [Google Scholar] [CrossRef] [PubMed]
  50. Yang, B.; Chan, R.; Gracia, N.; Cao, X.; Zou, X.; Jing, J.; Mai, J.; Li, J.; Shum, D. Cool and hot executive functions in medication-naive attention deficit hyperactivity disorder children. Psychol. Med. 2011, 41, 2593–2602. [Google Scholar] [CrossRef] [PubMed]
  51. Cañas, J.; Quesada, J.; Antolí, A.; Fajardo, I. Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks. Ergonomics 2003, 46, 482–501. [Google Scholar] [CrossRef] [PubMed]
  52. Schoemaker, M.; Hijlkema, M.; Kalverboer, A. Physiotherapy for clumsy children: An evaluation study. Dev. Med. Child Neurol. 1994, 36, 143–155. [Google Scholar] [CrossRef] [PubMed]
  53. Wixted, E.; Sue, I.; Dube, S.; Potter, A. Cognitive Flexibility and Academic Performance in College Students with ADHD: An fMRI Study. Bachelor’s Thesis, University of Vermont, Burlington, VT, USA, 2016. Available online: https://scholarworks.uvm.edu/cgi/viewcontent.cgi?article=1144&context=hcoltheses (accessed on 19 October 2023).
  54. Chan, R.C.; Shum, D.; Toulopoulou, T.; Chen, E.Y. Assessment of executive functions: Review of instruments and identification of critical issues. Arch. Clin. Neuropsychol. 2008, 23, 201–216. [Google Scholar] [CrossRef] [PubMed]
  55. Donders, J. The Behavior Rating Inventory of Executive Function: Introduction. Child Neuropsychol. 2002, 8, 229–230. [Google Scholar] [CrossRef]
  56. Gioia, G.; Kenworthy, L.; Isquith, P. Executive Function in the Real World: BRIEF lessons from Mark Ylvisaker. J. Head Trauma Rehabil. 2010, 25, 433–439. [Google Scholar] [CrossRef]
  57. Henry, L.A.; Bettenay, C. The assessment of executive functioning in children. Child Adolesc. Ment. Health 2010, 15, 110–119. [Google Scholar] [CrossRef]
  58. Lezak, M.; Howieson, D.; Bigler, E.; Tranel, D. Neuropsychological Assessment; Oxford University Press: New York, NY, USA, 2012. [Google Scholar]
  59. Miyake, A.; Emerson, M.J.; Friedman, N.P. Assessment of executive functions in clinical settings: Problemas and recomendations. Semin. Speech Lang. 2000, 21, 169–183. [Google Scholar] [CrossRef]
  60. Toplak, M.; Bucciarelli, S.; Jain, U.; Tannock, R. Executive functions: Performance-based measures and the behavior rating inventory of executive function (BRIEF) in adolescents with attention deficit/hyperactivity disorder (ADHD). Child Neuropsychol. 2009, 15, 53–72. [Google Scholar] [CrossRef]
  61. Verdejo-García, A.; Bechara, A. Neuropsychology of the executive Funtions. Psicothema 2010, 22, 227–235. [Google Scholar] [PubMed]
  62. Wild, K.; Musser, E.D. The Cambridge Neuropsychological Test Automated Battery in the Assessment of Executive Functioning. In Handbook of Executive Funtioning; Springer: New York, NY, USA, 2014; pp. 171–190. [Google Scholar] [CrossRef]
  63. Kramer, J.; Mungas, D.; Possin, K.; Rankin, K.; Boxer, A.; Rosen, H.; Bostrom, A.; Sinha, L.; Berhel, A.; Widmeyer, M. NIH EXAMINER: Conceptualization and development of an executive function battery. J. Int. Neuropsychol. Soc. 2014, 20, 11–19. [Google Scholar] [CrossRef] [PubMed]
  64. Naglieri, J.; Das, J. Cognitive Assessment System; Riverside Publishing Company: Itasca, IL, USA, 1997. [Google Scholar]
  65. Naglieri, J.; Das, J.; Goldstein, S. Cognitive Assessment System2; ProEd: Austin, TX, USA, 2013. [Google Scholar]
  66. Delis, D.; Kaplan, E.; Kramer, J. Delis Kaplan (D-KEFS) Technical Manual; NCS Pearson Inc.: San Antonio, TX, USA, 2001. [Google Scholar]
  67. Naglieri, J.A.; Goldstein, S. Comprenhensive Executive Functioning Index; Multi Health Systems: Toronto, ON, Canada, 2013. [Google Scholar]
  68. Gioia, G.; Isquith, P.; Guy, S.; Kenworthy, L. BRIEF: Behavior Rating Inventory of Executive Function Professional Manual; Psychological Assessment Resources: Lutz, FL, USA, 2000. [Google Scholar]
  69. Guy, S.C.; Isquith, P.K.; Gioia, G.A. Behavior Rating Inventory of Executive Function—Self Report Version; Psychological Assessment Resources: Lutz, FL, USA, 2004. [Google Scholar]
  70. Roth, R.M.; Isquith, P.K.; Gioia, G.A. Behavior Rating Inventory of Executive Function. Adult Version (BRIEF-A); Psychological Assessment Resources: Lutz, FL, USA, 2005. [Google Scholar]
  71. Çak, H.T.; Çengel, S.E.; Gökler, B.; Öktem, F.; Taşkıran, C. The Behavior Rating Inventory of Executive Function and Continuous Performance Test in Preschoolers with Attention Deficit Hyperactivity Disorder. Psychiatry Investig. 2017, 14, 260–270. [Google Scholar] [CrossRef] [PubMed]
  72. Gioia, G.A.; Espy, K.A.; Isquith, P.K. Behavior Rating Inventory of Executive Function Preschool Version (BRIEF-P); Psychological Assessment Resources: Lutz, FL, USA, 2003. [Google Scholar]
  73. García-Fernández, T.; González-Pienda, J.A.; Rodríguez-Pérez, C.; Álvarez-García, D. Psychometric characteristics of the BRIEF scale for the assessment of executive functions in Spanish clinical population. Psicothema 2014, 26, 47–54. [Google Scholar] [CrossRef] [PubMed]
  74. Skogan, A.H.; Egeland, J.; Zeiner, P.; Øvergaard, K.R.; Oerbeck, B.; Reichborn-Kjennerud, T.; Aase, H. Factor structure of the Behavior Rating Inventory of Executive Functions (BRIEF-P) at age three years. Child Neuropsychol. 2016, 22, 472–492. [Google Scholar] [CrossRef]
  75. Mahone, E.M.; Hoffman, J. Behavior Ratings of Executive Function among Preschoolers with ADHD. Clin. Neuropsychol. 2007, 21, 569–586. [Google Scholar] [CrossRef]
  76. Page, M.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Rev. Española Cardiol. 2021, 74, 790–799. [Google Scholar] [CrossRef]
  77. Dettori, J.; Norvell, D.; Chapman, J. Fixed-Effect vs. Random-Effects Models for Meta-Analysis: 3 Points to Consider. Glob. Spine J. 2022, 12, 1624–1626. [Google Scholar] [CrossRef]
  78. Lacerda, B.; Martínez, S.; Franz, A.; Moreira-Maia, C.; Silveira, R.; Procianoy, R.; Wagner, F. Does ADHD worsen inhibitory control in preschool children born very premature and/or with very low birth weight? Trends Psychiatry Psychother. 2020, 42, 340–347. [Google Scholar] [CrossRef]
  79. Ezpeleta, L.; Granero, R. Executive functions in preschoolers with ADHD, ODD, and comorbid ADHD-ODD: Evidence from ecological and performance-based measures. J. Neuropsychol. 2015, 9, 258–270. [Google Scholar] [CrossRef]
  80. Skogan, A.H.; Zeiner, P.; Egeland, J.; Urnes, A.-G.; Reichborn-Kjennerud, T.; Aase, H. Parent ratings of executive function in young preschool children with symptoms of attention-deficit/-hyperactivity disorder. Behav. Brain Funct. 2015, 11, 16. [Google Scholar] [CrossRef] [PubMed]
  81. Schneider, H.; Ryan, M.; Mahone, E. Parent versus teacher ratings on the BRIEF-preschool version in children with and without ADHD. Child Neuropsychol. 2020, 26, 113–128. [Google Scholar] [CrossRef] [PubMed]
  82. Perrin, H.; Heller, N.; Loe, I. School Readiness in Preschoolers With Symptoms of Attention-Deficit/Hyperactivity Disorder. Am. Acad. Pediatr. 2019, 144, e20190038. [Google Scholar] [CrossRef] [PubMed]
  83. Wiebe, S.; Sheffield, T.; Nelson, J.; Clark, C.; Chevalier, N.; Espy, K. The structure of executive function in 3-year-olds. J. Exp. Child Psychol. 2011, 108, 436–452. [Google Scholar] [CrossRef] [PubMed]
  84. Takacs, Z.; Kassai, R. The efficacy of different interventions to foster children’s executive function skills: A series of meta-analyses. Psychol. Bull. 2019, 145, 653–697. [Google Scholar] [CrossRef] [PubMed]
  85. Shaw, P.; Stringaris, A.; Nigg, J.; Leibenluft, E. Emotion dysregulation in attention deficit hyperactivity disorder. Am. J. Psychiatry 2014, 171, 276–293. [Google Scholar] [CrossRef] [PubMed]
  86. Slaats-Willemse, D.; Swaab-Barneveld, H.; de Sonneville, L.; van der Meulen, E.; Buitelaar, J. Deficient response inhibition as a cognitive endophenotype of ADHD. J. Am. Acad. Child Adolesc. Psychiatry 2003, 42, 1242–1248. [Google Scholar] [CrossRef] [PubMed]
  87. Barkley, R.A. Response inhibition in attention-deficit hyperactivity disorder. Ment. Retard. Dev. Disabil. Res. Rev. 1999, 5, 177–187. [Google Scholar] [CrossRef]
  88. Mukherjee, P.; Hartanto, T.; Iosif, A.M.; Dixon, J.F.; Hinshaw, S.P.; Pakyurek, M.; van den Bos, W.; Guyer, A.E.; McClure, S.M.; Schweitzer, J.B.; et al. Neural basis of working memory in ADHD: Load versus complexity. NeuroImage Clin. 2021, 30, 102662. [Google Scholar] [CrossRef]
  89. Van De Voorde, S.; Roeyers, H.; Verté, S.W.J. Working memory, response inhibition, and within-subject variability in children with attention-deficit/hyperactivity disorder or reading disorder. J. Clin. Exp. Neuropsychol. 2010, 32, 366–379. [Google Scholar] [CrossRef]
  90. Salehinejad, M.; Ghanavati, E.; Rashid, M.; Nitsche, M.A. Hot and cold executive functions in the brain: A prefrontal-cingular network. Brain Neurosci. Adv. 2021, 23, 5. [Google Scholar] [CrossRef] [PubMed]
Children 11 00058 g001
Figure 1. PRISMA flow diagram (based on the work of [76]).
Figure 1. PRISMA flow diagram (based on the work of [76]).
Children 11 00058 g001
Children 11 00058 g002
Figure 2. Forest plot (soil effect).
Figure 2. Forest plot (soil effect).
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Children 11 00058 g003
Figure 3. Forestry graph (soil effect).
Figure 3. Forestry graph (soil effect).
Children 11 00058 g003
Table 1. Inclusion/exclusion criteria.
Table 1. Inclusion/exclusion criteria.
Inclusion CriteriaExclusion Criteria
(a) Participants: persons with symptoms compatible with ADHD obtained from the application of standardized tests;(a) Participants: not diagnosed with ADHD;
(b) Cognitive age that allows the application of BRIEF-P;(b) Cognitive age: does not allow application of BRIEF-P;
(c) Cognitive competence (obtained through the application of standardized tests);(c) Cognitive competence: not available;
(d) Executive dimensions: single construct or basic dimensions (flexibility, inhibition and working memory);(d) Assessment instruments: non-standardized;
(e) Assessment instruments: standardized for assessing executive functions: hetero- and/or self-report; (e) Type of studies: case study and review;
(f) Type of studies: empirical; (f) Type of design: non-comparative-causal;
(g) Type of design: non-experimental, comparative-causal (group with ADHD-compatible symptoms versus group with typical development);(g) Type of design: non-comparative-causal;
(h) Language: English and Spanish; (h) Language: other;
(i) Other characteristics: full text. (i) Other characteristics: abstract, full text not available.
Table 2. Number of participants according to diagnosis in each of the seven studies selected for the meta-analysisi (references in Table S1 Supplementary Material).
Table 2. Number of participants according to diagnosis in each of the seven studies selected for the meta-analysisi (references in Table S1 Supplementary Material).
StudyAuthor/Year/CountryADHDCONTROLODDODD + ADHD
1(Lacerda et al. 2020) Brazil [78];2455
2(Ezpeleta and Granero, 2015) Sapin [79];235385110
3(Zhang et al. 2018) China [22];16363
4(Skogan et al. 2015) Norway [80];1134
5(Schneider, Ryan & Mahone, 2020) USA [81];4935
6(Perrin, Heller & Loe, 2019) USA [82];4548
7(Çak, Çengel, Gökler, Öktem & Taşkıran, 2017) Turkey [71].2152
SUBTOTAL14597915110
TOTAL2311
Table 3. Effect size estimates for the studies (floor effect).
Table 3. Effect size estimates for the studies (floor effect).
Effect SizeStandard ErrorZSig. (Bilateral)Confidence Interval 95%Prediction Interval 95% a
LowerUpperLowerUpper
Global0.6150.14194.335<0.0010.3370.893−0.3431.574
a. Based on t-distribution.
Table 4. Effect size estimates for the studies (ceiling effect).
Table 4. Effect size estimates for the studies (ceiling effect).
Effect SizeStandard ErrorZSig. (Bilateral)Confidence Interval 95%Prediction Interval 95% a
LowerUpperLowerUpper
Global2.9620.91173.2490.0011.1754.749−5.67911.603
a. Based on t-distribution.
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Bausela-Herreras, E.; Alonso-Esteban, Y.; Alcantud-Marín, F. Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects. Children 2024, 11, 58. https://doi.org/10.3390/children11010058

AMA Style

Bausela-Herreras E, Alonso-Esteban Y, Alcantud-Marín F. Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects. Children. 2024; 11(1):58. https://doi.org/10.3390/children11010058

Chicago/Turabian Style

Bausela-Herreras, Esperanza, Yurena Alonso-Esteban, and Francisco Alcantud-Marín. 2024. "Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects" Children 11, no. 1: 58. https://doi.org/10.3390/children11010058

APA Style

Bausela-Herreras, E., Alonso-Esteban, Y., & Alcantud-Marín, F. (2024). Behavior Rating Inventory of Executive Function in Preschool (BRIEF-P) and Attention-Deficit and Hyperactivity Disorders (ADHD): A Systematic Review and Meta-Analysis of Floor and Ceiling Effects. Children, 11(1), 58. https://doi.org/10.3390/children11010058

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