what factors impact our ability to react to a stimulus
Behav Sci (Basel). 2019 January; 9(i): 7.
Which Factors Influence Attentional Functions? Attending Assessed by KiTAP in 105 half dozen-to-10-Twelvemonth-Old Children
Marta Tremolada
1Department of Developmental and Social Psychology, University of Padua; Via Venezia, 8 35131-Padova, Italy; ti.dpinu@inihcinob.s
Livia Taverna
2Faculty of Education, Free University of Bozen-Bolzano, Brixen-Bressanone; Viale Ratisbona, 16 39042-Bressanone, Italy; ti.zbinu@anrevat.aivil
Sabrina Bonichini
1Section of Developmental and Social Psychology, University of Padua; Via Venezia, 8 35131-Padova, Italian republic; ti.dpinu@inihcinob.southward
Received 2018 Nov one; Accustomed 2018 Dec 18.
Abstruse
This research revealed the children with difficulties in attentional functions among healthy children attending master school and aimed to identify the possible sociodemographic factors, such as the child's age, gender, and school grade, that could influence attentive performance. The participants were 105 children aged 6–10 years (M historic period = 8.6; SD = 1.04), attending primary schools. Family economic status was mostly at a medium level (63.v%), and parents virtually often had 13 years of schooling. The computerized test KiTAP was administered to children to appraise their attentional functions. Results showed a higher frequency of omissions and fake alarms and a reduced speed in alertness, go/no-go, and sustained attention tasks compared to Italian norms. Hierarchical regression analyses were run with school grade, gender, and current age equally independent variables and hateful reaction times (and standard deviation), number of omissions, and false alarms as dependent ones. The results showed that male gender and attending a lower grade impacted on lower attentional performance in several subtests. Girls showed the all-time performances in tests of distractibility and impulsive reaction tendencies, while higher school grade positively influenced divided and sustained attention. These results could be useful to identify children with major attentional difficulties, and some recommendations for future studies and the implementation of attention empowerment programmes are proposed.
Keywords: attentional functions, master school, KiTAP, healthy children, gender, delays
one. Introduction
i.1. Definition of Attention and Adopted Theoretical Model
Attention has been identified as a complex construct in psychology which does not express a unitary concept but concerns a psychological miracle that interacts with all other cerebral processes, such as perception, memory, behavioral planning or actions, linguistic product, and spatial orientation [1]. Attentional skills are a prerequisite for responding to daily environmental demands in that, through them, a person tin select and integrate all the relevant information he/she perceives, coming from different sensory channels, and acquaintance them with conceptually superior categories. Also cognitive processes, motivational and emotional processes have been recognized as likewise having an important function: what is perceived as non interesting, without an affective value, does not get a field of study of attention [two]. Attention involves several developmental tasks, including focused attention, sustained attention, attention shifting, and divided attention. Inhibitory control is normally described every bit the power to suppress a dominant or automatic response: response inhibition [3]. It encompasses an attentional component known every bit interference control: the power to selectively nourish to certain stimuli and ignore irrelevant stimuli [iv]. Focused attention refers to being able to actively focus on 1 matter without being distracted by other stimuli; sustained attention can be divers as the ability to maintain concentrated attending over prolonged periods of time [5].
In the present study on attending in main school children, nosotros adopted the aspects of attention model proposed by Van Zomeren and Brouwer [6]. Attention can be categorized into three principal components depending on their different functions: (a) activation (alertness, sustained attention), (b) visual–spatial orientation (overt attention, visual search), and (c) selective executive components (divided attention, inhibitory command, and flexibility). The 2 authors schematized the basic processes of attention by grouping them into two principal reduced components: selectivity and intensity. Inside selectivity, they distinguished focused attention and divided attention, while alertness and sustained attention (or vigilance) were incorporated into intensity (Figure 1).
Supervisory attentional control (SAC), Van Zomeren and Brouwer'south Basic Process Sketch, 1994 [6], (in [seven], p. 184)
The development of these functions is mostly accompanied past the neurological maturation of particular areas in the encephalon and can be clearly distinguished past these areas' evolution pathways. The parietal and dorsum cortex (visual or spatial attending) are involved in the basic attention processes, before the main executive functions, through automatic inhibitory activity, suppress irrelevant data. Executive functions have been associated with the slower maturation of the frontal and prefrontal cortex areas [8,9,10,11,12]. This implies that chronological age has an essential influence on attending performance during development, but also that academic achievement allows pupils to train their attentive skills.
A specific test to assess attentional performance for children (KiTAP) has been developed. The KiTAP is a standardized tool with infrequent psychometric backdrop and has been used in recent neuropsychological inquiry on children with neuropsychiatric disorders such as Attention Deficit and Hyperactivity Disorder (ADHD) [xiii], as well as in children who received a liver transplant [14] and children with motor coordination impairments [fifteen]. The procedure is based on the quantitative and qualitative features of Van Zomeren and Brouwer's neuropsychological model [six].
1.2. Factors Influencing Attention Performance in a School Context
The strong interindividual variability in attention performance depends on a number of factors, both constitutional and environmental, that make up one's mind the different developmental paths that attention could follow. Thus, as with all cerebral skills which are adult, in guild to be understood and evaluated every bit fully equally possible, consideration should exist given to the child's characteristics, taking into business relationship the influence of many factors [sixteen]: the biological characteristics of the child (i.e., temperamental characteristics favouring girls for effortful control and boys for surgency [17], maturation levels of the primal nervous arrangement (activation and visual spatial attention that show earlier evolution than other executive functions [8], general cognitive and emotional capacity of the child [2], and environmental variables, namely his/her personal experiences and the context in which he/she lives (for example, supporting parenting strategies) [18]. As far as environmental variables are concerned, we take into consideration the master school experience because this flow is characterized past rapid changes in attention functions co-ordinate to the literature, and thus the role of attending in bookish learning and accomplishment may be critical [19,twenty]. Scholastic achievement is positively correlated with attending-related skills and the development of attentional processes. However, in well-nigh investigations, attentional performance has been assessed using instructor and parent ratings of children'due south ability to focus and shift attention, thereby introducing a chance of rater bias [21]. While there appears to be an association between attentional processes and scholastic performance, the specific aspects of attentional operation that are associated with scholastic achievement are unknown. School is one of the almost meaning and privileged developmental contexts for the kid. With his or her omnipresence of principal school, the kid faces new developmental challenges compared to early babyhood, which will lead him/her to an important cognitive, emotional, and social evolution [22]. The class that the child attends, people around him/her, and everything defining the child in his/her specificity assume an important part in attention performance.
Aplenty prove suggests that children's executive functions tin can be improved by interventions [23], schooling [24], and environmental factors [25] during that fourth dimension. For this reason, this study aims to straight assess attentional functions in children within the school environs, taking into consideration not only the chronological age but also the child's bookish achievement. The results of a study by McCrea et al. [24] demonstrate that formal schooling provides small-to-moderately sized furnishings on the development of executive function during the early on schoolhouse grades and that this effect is highly dependent upon the nature of the task. A large schooling upshot on the exact fluency measure at age 8 was detected, suggesting that schooling may directly improve functioning on executive measures. Such schooling effects could conceivably arise from several factors, including an increased knowledge base, learning of full general problem-solving strategies, or the learning of domain-specific strategies [26,27].
1.2.1. Function of Historic period
Several studies on children'southward attentive development have shown that the most rapid improvements in alertness, sustained attention, and spatial orienting (visual search) occur between the ages of half-dozen and x years [28,29]. With respect to the development of executive functions such as inhibition, flexibility, and divided attention, there is growing evidence that these functions actually emerge in the early years of childhood, but that they still develop gradually into belatedly childhood and early adolescence [10,thirty]. Attentional functions, like all the cognitive mechanisms, are primarily affected by the level of cerebral maturation. Throughout childhood and until boyhood, the so-chosen "executive" attending will exist defined to control behaviours, to distribute cerebral resource, and to plan and directly action to achieve specific goals [31]. This could non happen if the primal nervous system and the targeted networks did non mature.
Zimmermann and Fimm [32] studied the general development of attention in good for you children aged 6 to 12 years. Despite the unavoidable interindividual differences, they observed that increasing historic period inevitably increased the quality of operation on attentional tests and that these functioning levels, initially very heterogeneous, tended to stabilize. Reaction times, for example, very different in children aged six–7 years, decreased as their age increased and seemed to stabilize but at the age of 13–14 years. Flexibility, of import to command the focus of attention, as well grew with child maturation. In addition, the results for tests of split attention showed how it was influenced by age. The influence of age was more axiomatic on operation speed than on its quality in v-to 11-yr-old Arab children, with rapid improvement until the age of 9 years, with some attentional functions (alertness and inhibitory control) that seemed to develop earlier than other functions (distractibility and divided attending) [33]. Age was negatively associated with distractibility, lapses of attention, and cognitive speed, indicating that these parameters decrease with age in healthy children [21]. The number of errors (incorrect responses to disquisitional stimuli) and omissions (missed responses to critical stimuli) were found to be critical attention scores for bookish operation in principal school children and seemed to constitute a sensitive measure out of distraction [32].
Inhibitory command shows rapid evolution during the preschool years merely also improves between 5 and 8 years of age [3]. Early attentional control development peaks during the preschool years, although information technology continues to develop during the primary school period alongside the emergence of the core executive functional components [34].
The results of a contempo study [35] indicate significant age-related improvements between viii and 10 years in all the attentional functions, especially regarding the developmental rates for divided attention, sustained attention, and flexibility.
In this cross-sectional study for the start time in the Italian population, it is important to confirm or disconfirm these possible kid age differences in developing attentional functions by inserting this variable into a predictive model that could counterbalance the best predictive variables, including the child'due south age.
1.ii.2. Role of Gender
The literature offers a wide range of studies, for example Biedereman et al. [36] and Siegel and Smythe [37], that accept investigated the most influential factors in attention development according to gender, but only in cases of disorder or pathology. For example, it was noted that Attention Deficit and Hyperactivity Disorder (ADHD) affected boys from three to nine times more girls. Gender-related differences were observed besides in some KiTAP subtests: girls had faster reaction times but were less accurate than boys [33]. A written report [38] revealed that attention problems in boys were related to less well-developed expressive language skills, while in girls in that location was a trend for attention problems to be related to lower performance on academic skills. Other studies have constitute that girls showed a better performance and a higher level of inhibitory control than boys [36]. Gender differences were nowadays too with regard to the speed/arousal dimension, with boys performing faster than girls, both groups aged 6 to thirteen [39]. It can be noted that the gender-based differences in attentional performances are still non clear. Austrian male children (6–x years) were faster in alacrity, divided attention, and inhibition, while girls demonstrated meliorate accuracy in flexibility and inhibition. In dissimilarity, in Mexican children (6–12 years) no gender differences in attending and impulse command were identified [33]. This affair is still field of study to ongoing debate. The literature on gender difference is scarce and mostly related to clinical populations. In this study, nosotros want to see if the situation in healthy children is similar or dissimilar compared with the clinical setting.
1.two.3. Role of Family Factors
The function of family influences on preschool and schoolhouse-age cognitive development has received considerable empirical attention from cerebral developmental psychology researchers in the terminal few decades [40]. The literature shows that a family unit's socioeconomic status (SES) could influence the child'south attention performance in early on infancy, with low-SES infants showing higher inattention than their loftier-SES peers already at six, 9, and 12 months and being less likely to modulate their cognitive skills with respect to stimulus complexity [40]. The link between family socioeconomic status and development trajectories has gained diverse explanations, with bear witness suggesting that higher family incomes are related to more stimulating learning environments. Parents who take fiscal resources invest in obtaining equipment (toys and books) and in undertaking activities (reading books and teaching abilities) that foster cognitive skills, language evolution, behavioural performance, and socioemotional competence skills of their children [41]. It has been speculated that the underlying physiological mechanism leading to reduced attending in low-SES infants could be due to maternal nutrition choices for children [42], which have been establish to be associated with long-term alterations in brain evolution. Moreover, furnishings of socioeconomic disadvantage on neural structures were observed in 10-year-sometime children showing widespread modifications in various brain regions and smaller volumes of grey affair. Though the link between parental SES and children'south brain structures could exist mediated by other factors (i.e., genetic inheritance), there is considerable evidence for direct ecology furnishings in other species [43].
Recently, a meta-analysis [44] showed how SES disparities played a relevant role on the executive function performance of children. Families with a low cultural level and income compared to average/loftier ones showed a considerably college presence of ADHD. The importance of maternal didactics for children's academic outcomes was widely recognized [45]. The number of siblings did not appear to limit children'south cognitive evolution during early on childhood [46]. The literature has emphasized that a good growth environment, with acceptable stimulation, facilitates the development non but of attention just of all the near important cerebral abilities [47]. Confirming this, there were data from studies that constitute a strong correlation between children with ADHD and a depression sociocultural and economic family condition [48].
1.iii. Gap in the Literature: Attention in Salubrious Children
A review of the literature on attending in children revealed few studies that specifically investigated the development and characteristics of the attentional mechanisms of good for you children during the primary schoolhouse menses. Furthermore, developmental studies on children's attentional skills have been express to clinical targets, such equally children with difficulty or disturbance of attention [49,50,51]. Enquiry on salubrious schoolhouse-age populations which examines the bear on of various functions and components of attention on bookish achievement is a relatively new inquiry surface area [16,52]. Inside this framework, the present study aimed to provide empirical evidence for the contribution of distinct attention functions in main school children adopting a friendly computerized arrangement, KiTAP. Research with KiTAP in typically developing school populations is limited to only 2 developmental cross-cultural studies [36] and i on attentional performance and scholastic achievement [53]. KiTAP has been proved to be an age-sensitive musical instrument in chief school children (6–11 years). Previous findings suggest that less-complex functions similar alertness and sustained and selective attending show early on emergence (at kindergarten age) in the course of development and stabilize around the historic period of 10, while components of executive functions (flexibility, divided attention, inhibitory command) show improvements beyond childhood that continue until early adolescence.
1.iv. Research Goals
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The main objective of this written report was to identify children with attentional deficit attending primary schoolhouse, comparing their scores with the Italian relative norms. The neuropsychological model will guide this research strand, and nosotros expected that fourth dimension variability in a go ⁄ no-go task, followed by number of errors in a divided attending chore and response fourth dimension variability in an alertness chore, could be identified every bit possible good measures to discriminate between children with and without attention difficulties [x].
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Nosotros expected that attentional functions could amend with growing age, when the child is attention the quaternary and fifth class levels [54,55]. Influence of age on attentional functions could depend on the types of examined functions, with superior executive tasks (i.eastward., flexibility, divided attending, inhibitory control) improving by increasing age, while other lower tasks (i.e., alertness, sustained and selective attention) remain stable [35].
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Nosotros expected to observe gender differences in attentional functions [36,37]. In fact, some studies have revealed that boys, for constitutional reasons, were less likely than girls to stay focused, house, and alarm, while they had faster reaction times [33]. Nosotros supposed that boys were faster than girls in the majority of attentive tasks, but that girls were more accurate and precise in their attentional performance.
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We wanted to verify whether children's family SES could influence attentional functions, specifically if SES disparities could influence attentive performance among children [44]. We expected that children with lower SES and parental schooling could accept difficulties in their attentional operation.
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We aimed to understand if the presence of siblings or parents' level of education could influence the quality of the children'due south attentional performance [45,46]. Nosotros supposed that children with siblings could take a meliorate attentional performance than children without siblings.
2. Materials and Methods
ii.1. Participants
The participants were 105 children aged 6–ten years old with a hateful age of viii.half-dozen (SD = ane.04), 57 of whom were female, attending iii main schools in a northeast region of Italy, from the 2d year of school to the fifth/last year. We received a valid consent grade from 115 families amidst 132 contacted (response rate 87.12%). 10 children were not reached in the assessments because of logistical issues (teachers' other priorities, ill children in the data drove menstruation, no tranquility room bachelor for assessments). Table 1 shows sociodemographic information for the participants, and Table 2 shows family sociodemographic characteristics.
Table ane
Participants' sociodemographic characteristics.
| Form | North | Males | Females |
|---|---|---|---|
| 2nd | xix (18.1%) | v | 14 |
| 3rd | 42 (40%) | 21 | 21 |
| 4th | 27 (25.seven%) | 13 | xiv |
| 5th | 17 (16.two%) | nine | 8 |
| Full | 105 (100%) | 48 | 57 |
Table ii
Family's sociodemographic characteristics.
| Parents' Characteristics | Categories | Mothers | Fathers |
| Frequency | Frequency | ||
| Education (years of schooling) | five years | 1% | 1.1% |
| viii years | 26.eight% | 35.1% | |
| xiii years | 60.eight% | 53.2% | |
| 16 years | 5.2% | 2.1% | |
| xviii years | five.2% | 7.4% | |
| >18 years | 1% | one.ane% | |
| Employment | Looking for a job | 19.vii% | three.1% |
| Function-time | 50% | 3.1% | |
| Full-time | xxx.three% | 93.8% | |
| Weekly job hours | fifty or more | 1.6% | 17.half-dozen% |
| xl–49 | 16.1% | 61.5% | |
| xxx–39 | 37.1% | 18.7% | |
| 20–29 | 38.7% | 2.2% | |
| 10–19 | three.2% | 0% | |
| 0–ix | 3.2% | 0% | |
| Mean (SD) | Mean (SD) | ||
| Current age | forty.11 (4.36) | 43.01 (4.56) | |
| Family's Characteristics | Categories | Family | |
| Frequency | |||
| Relationship status | Married | 89.1% | |
| Divorced/Separated | 5.5% | ||
| Cohabitant | 5.4% | ||
| Single | 0% | ||
| Economic situation perceived | Depression | 21.9% | |
| Medium | 63.five% | ||
| High | 14.6% | ||
| Abode state of affairs | Rent | 6.one% | |
| In-progress mortgage | 45.9% | ||
| Finished mortgage | 37.8% | ||
| Other | ten.2% | ||
| Range | Hateful (SD) | ||
| N familiars | ii–6 | 3.9 (0.75) | |
| N siblings | 1–3 | i.2 (0.49) |
two.2. Procedure
The project was successfully proposed to the manager of the school, who showed information technology to the institute councils. A letter explaining the inquiry project was sent to families of students attending the second to the fifth grade, requesting the students' participation in the study through an attached informed consent grade. The inclusion criteria were no history of chronic affliction or injury and absence of sensory deficiencies and other pathological aspects. Fantabulous children were non involved as the trial might be too tiring for them, specially for the data collection period that was simply at the beginning of the schoolhouse year (from Oct to December).
Out of more than 500 letters sent, 132 responses were received with permission to participate, merely 17 children were excluded considering the informed consent had been signed by just one parent. From these families, 74 filled in the sociodemographic survey and 105 children completed the attention assessment test.
Students were met individually in a silent and empty room where the laptop with KiTAP for the assessment was located. Each student was assessed in half-dozen of the full battery of 8 tests. Administering the entire battery would have meant asking the child to exist engaged for well-nigh an 60 minutes and a one-half. This was deemed an excessive length as well as having a negative effect on the quality of the kid's classroom performance; additionally, scheduling within the regular school day would accept been difficult. Thus, vigilance and visual scanning subtests were removed from the examination.
At the end of the exam, the psychologist e'er thanked the participant, stressing the importance of his or her contribution. Overall, the assistants lasted 30 min for the oldest and fastest students, and 45 min for the younger ones.
Scores obtained from each subject area in each test were stored automatically. They were placed in a tabular array that provided information most the subject, the examiner, and reaction times (RTs) for each trial. In add-on, in that location was a listing of results with information about the individual parameters: mean, median, and standard divergence of RT; number of right and incorrect reactions; and number of omissions. Scores were expressed in percentiles or in T points. The program besides offered graphs.
two.3. Instruments
two.three.1. KiTAP
This exam has been created to ensure optimal motivation for children during attention testing past providing a design suitable specially for younger children. Past increasing motivation and compliance, the validity of the test should be maximised.
Great importance has been attributed to the attentional functions of school-age children. Assessing attention in schoolchildren is crucial for several different diagnostic questions. All the same there is a current lack of test instruments specifically designed to provide a differential mensurate of young schoolchildren's attentional abilities.
The battery Test of Attentional Functioning for Children KiTAP [32,49,54,56,57] has been constructed with particular attention to the same consideration that was applied in the adult version of the exam (TAP). The selection of KiTAP's tests has been based on the analysis of information from 148 children between the ages of 6 and 10 years tested with TAP. A factor assay of the data has revealed a cistron structure with v independent aspects or factors, which take been represented by a TAP subtest. Table iii shows KiTAP'due south parameters [49].
Table 3
Parameters in each KiTAP subtest.
| Test | Execution Time | Parameters |
|---|---|---|
| Alacrity | 1.five min | Reaction times (RT): mean, median, standard divergence |
| Distractibility | iii min | RT median, omissions, false alarms |
| Divided attention | 4.5 min | RT median, omissions, false alarms |
| Flexibility | one.v–two min | RT median and RT median in percentiles, fake alarms and fake alarms in percentiles |
| Go/no-go | two.five min | RT median, omissions, fake alarms |
| Sustained attention | ten min | RT median, omissions, false alarms |
Alertness ("the witch") is a central attribute of attentional intensity. Intrinsic alertness is measured with a uncomplicated reaction chore. In this test, a witch appears at a window and should be driven away every bit fast equally possible by pressing the key. The median provides data on processing speed, while standard divergence indicates the level of stable, maintained alertness. In improver, comparing the operation of tested children with the KiTAP normative operation values, the percentile median and the standard departure (percentile) were calculated.
Distractibility ("the sad and the happy ghost"): 1 of the central aspects of focused attention is the ability to intentionally maintain control over the focus of attention in complex situations and under distracting conditions. Younger children stand out because of their high level of distractibility, through which they frequently lose sight of their goals from one moment to the next when something else captures their attention. A depression caste of distractibility is therefore an important prerequisite for concentrated piece of work and is of detail importance for school-aged children. The purpose of this exam is to perform a centrally presented decision task, while in half the trials a distracting stimulus appears in the periphery of the visual field. The central stimulus, a cheerful or sorry ghost, is designed and so that the distinction between cheerful and sad is just possible past focusing visually. The assessed parameters are number of omissions and false alarms: the beginning indicates the degree of distractibility of the subject, and the second indicates when he or she reacted according to a "suspicion" and not for having really recognized the stimulus. In improver, the ii parameters were considered as percentiles, so that we could compare our sample with norms. Scores were considered both in a distractor country and a no-distractor land.
Divided attention ("the owls"): A common feel in daily life is that of paying attending to a number of things or events at once. This requires the ability to divide attending between simultaneously occurring events. In this test, a sequence of audio-visual and visual stimuli has to be observed simultaneously and responses to stimuli are made by pressing a fundamental. 1 sees an owl sitting in a window, which closes its optics from time to time. This modify should exist reacted to. Simultaneously, 2 owls calling to each other tin be heard in the background. The number of omissions and median reaction times and simulated alarms, both for acoustic stimuli and visual stimuli, were measured. The number of omissions is the most important parameter, equally information technology indicates the ability to divert attention from dissimilar tasks.
Flexibility ("the dragons' firm"): Selective attention refers not only to the ability to direct attending toward single events and stimuli, simply also to redirect attentional focus according to electric current demands of a situation. The term "flexibility" is used to refer to the ability to intentionally regulate and redirect attention focus. In this exam, two dragons of dissimilar colour (green and blue) appear to the left and right of the center of the monitor (a gate) simultaneously. The target stimuli alternate: to begin with, a primal has to exist pressed on the side at which the green dragon appears. At the next presentation, a key has to be pressed on the side at which the blue dragon appears. The number of false alarms committed and the median of reaction times are the parameters considered, and respective percentiles are calculated for a comparison with the KiTAP normative performance scores.
Go/no-go ("the bat"): Attending comprises not simply the control processes through which we take in information from the environment, merely equally the control of our reactions and of our behaviour and inhibitory control. This includes the determination every bit to whether and how we should react every bit well equally the continual, e.yard., visuo-motor, control of actions. One of the key processes in this connection is control of impulsive behaviour, that is, power to suppress an inappropriate reaction. The simplest way to measure out impulsive reaction tendencies is by means of the so-called "become/no-get" chore. In this test, one sees either a vampire bat or a cat, whereas just the bat should be reacted to. The number of false alarms indicates the ability to inhibit the reaction and the mean of reaction times, which indicates the speed of controlling ability. In addition, to compare the number of alerts made by our sample with those fabricated past the normative sample, the number of percentile errors was considered.
Sustained attention ("the ghost's brawl"): In this task, the effortful maintenance of selective attention over a longer bridge of fourth dimension is tested. In dissimilarity to vigilance, where operation requires the detection of infrequent stimuli that are difficult to discriminate and are presented under experimental conditions of extreme monotony, demands with sustained attention are more than complex. Conditions of sustained attending or concentration are more characteristic of daily life demands. This chore requires comparing a stimulus with a subsequent stimulus to determine whether these two stimuli have a predetermined stimulus feature in mutual. Stimuli to exist compared are ghosts of different color that appear consecutively at different windows of a castle ruin. This procedure places demands on working memory and flexibility, and in a more than circuitous variant, on the ability to divide attending, since two of the stimulus aspects have to be observed. Parameters are the number of omissions, which indicates the performance stability, and false alarms fabricated, specifically for the starting time 5 min of the examination, for the second five min, and for the total exam. For the latter condition, the number of omissions and percentile errors take also been considered, so that a comparison with the normative sample of KiTAP could be made.
2.3.2. Sociodemographic Data
Parental didactics and occupational status were measured, past collecting information on didactics (number of years of school achievement), type and average hours of job, and economic status.
two.4. Statistical Analyses Plan
Information were preliminarily checked for normality, adopting the Kolmagorov–Smirnov and Shapiro–Wilks tests. Data distribution was normal, so we decided to use parametric statistics. To reply the enquiry questions, nosotros ran preliminary Pearson's correlations and ANOVAs to place the possible pregnant associations between our variables, adopting post hoc Bonferroni correction if necessary. Perceived economical condition, number of siblings, and parental educational activity level were non inserted in the model considering they did not obtain significant associations. Then a series of hierarchical regression analyses were run with schoolhouse grade (grades two, three, 4, and 5), gender (i = male, 2 = female), and child's current age every bit contained variables. The scores obtained at the half dozen individual KiTAP tests (mean reaction times and SD, number of missions, and false alarms) were entered as dependent variables, one by one, choosing the parameters considered as the about significant in the exam manual. We will show merely the significant obtained results. The interaction factors, if significant, will be indicated.
3. Results
For each KiTAP test, the Italian normative scores for the individual parameters were shown in the transmission. These norms were given as percentiles. We assessed the distribution of children forth these percentiles, comparing the scores obtained in each subtest with those from Italian standardized norms (Table 4), except for divided attention, where there are no normative values.
Table 4
Distribution of children'due south performance in standardized tests past percentile categories.
| Test | <25° | 25°–49° | 50°–75° | >75° | |
|---|---|---|---|---|---|
| Alacrity | RT median RT SD | 21 32 | 16 19 | 31 27 | 37 27 |
| Distractibility | RT median omissions False alarms | iii 66 3 | iv 23 10 | fourteen 13 22 | 84 three 70 |
| Flexibility | RT median Faux alarms | 6 28 | 14 41 | 27 14 | 59 34 |
| Become/no-Go | RT median Omissions Simulated alarms | nine thirteen 33 | 20 77 38 | 31 5 xviii | 45 10 xv |
| Sustained attention | RT median omissions False alarms | 14 31 46 | 21 26 30 | 26 28 nineteen | 44 20 10 |
Observing Table four, nosotros run across how a great proportion of children fell in the lower level of percentile categories in their scoring of simulated alarms and omissions in almost all the attentional tasks. Only medians for distractibility and rapidity assessed by reaction times attested to normal or superior scores, even if exclusively in distractibility and flexibility subtests.
Nosotros also ran ANOVAs with perceived economic status as an contained variable and the several attentive scores every bit dependent variables inserted i by one. We obtained no meaning means differences.
We also ran Pearson'south correlations to identify the significant associations of our contained variables with the several attentional subtests' parameters. Table 5 shows these correlations.
Table 5
Pearson's correlations between the examined variables and each attentional functioning calibration.
| No/Yes Presence of Sibling | Child's Current Age | Mother's Schooling Years | Begetter's Schooling Years | Child's Gender (1 = Male, ii = Female person) | |
|---|---|---|---|---|---|
| RT Median Alertness | r = −0.12; p = 0.28 | r = −0.41 **; p = 0.001 | r = 0.05; p = 0.63 | r = −0.06; p = 0.52 | r = 0.21 * p = 0.02 |
| SD Alertness | r = −0.13; p = 0.25 | r = −0.29 **; p = 0.003 | r = 0.02; p = 0.82 | r = −0.11; p = 0.27 | r = −0.03; p = 0.76 |
| Omissions Distractibility_Total | r = 0.01; p = 0.89 | r = −0.17; p = 0.08 | r = 0.fourteen; p = 0.sixteen | r = 0.20; p = 0.05 | r = −0.11; p = 0.27 |
| Imitation Alarms Distractibility_Total | r = −0.05; p = 0.65 | r = −0.24 *; p = 0.01 | r = −0.fourteen; p = 0.16 | r = −0.09; p = 0.93 | r = −0.23 *; p = 0.01 |
| RT Median Distractibility_Total | r = 0.12; p = 0.30 | r = −0.18; p = 0.05 | r = 0.05; p = 0.58 | r = −0.08 p = 0.43 | r = 0.35 **; p = 0.0001 |
| Imitation Alarms Flexibility | r = −0.09; p = 0.42 | r = −0.xv; p = 0.11 | r = −0.xix; p = 0.05 | r = 0.07; p = 0.49 | r = −0.thirteen; p = 0.xvi |
| RT Median Flexibility | r = −0.15; p = 0.19 | r = −0.37 **; p = 0.0001 | r = −0.07; p = 0.49 | r = −0.08; p = 0.twoscore | r = 0.16; p = 0.08 |
| Omissions Go/No-Go | r = 0.05; p = 0.lx | r = −0.12; p = 0.xx | r = −0.06; p = 0.57 | r = 0.03; p = 0.77 | r = −0.22 *; p = 0.02 |
| False alarms Get/No-Get | r = −0.13; p = 0.24 | r = −0.1; p = 0.32 | r = −0.09; p = 0.38 | r = −0.09; p = 0.36 | r = −0.31 **; p = 0.001 |
| RT Median Get/ No-Go | r = 0.xx; p = 0.07 | r = −0.42 **; p = 0.0001 | r = 0.xix; p = 0.07 | r = −0.12; p = 0.25 | r = 0.18; p = 0.06 |
| Omissions Sustained_attention_Total | r = −0.08; p = 0.44 | r = −0.41 **; p = 0.0001 | r = −0.xviii; p = 0.06 | r = 0.05; p = 0.65 | r = −0.i; p = 0.31 |
| Faux Alarms Sustained attention_Total | r = −0.04; p = 0.68 | r = −0.09; p = 0.34 | r = −0.03; p = 0.79 | r = −0.01; p = 0.91 | r = −0.20 *; p = 0.04 |
| RT Median Sustained attention_Total | r = −0.13; p = 0.25 | r = −0.47 **; p = 0.0001 | r = −0.03; p = 0.79 | r = 0.01; p = 0.87 | r = 0.12; p = 0.20 |
| Omissions Divided_attention_acoustic | r = −0.08; p = 0.48 | r = −0.22 *; p = 0.02 | r = −0.xix; p = 0.05 | r = −0.12; p = 0.25 | r = −0.03; p = 0.73 |
| False Alarms Divided attention_acoustic | r = −0.ten; p = 0.36 | r = 0.04; p = 0.67 | r = −0.23 *; p = 0.02 | r = −0.16; p = 0.10 | r = −0.11; p = 0.25 |
| RT Median Divided attention_acoustic | r = −0.19; p = 0.08 | r = −0.18; p = 0.07 | r = −0.04; p = 0.65 | r = −0.05; p = 0.59 | r = −0.006; p = 0.95 |
| Omissions Divided_attention_visual | r = 0.08; p = 0.43 | r = 0.02; p = 0.80 | r = 0.09; p = 0.37 | r = 0.09; p = 0.37 | r = −0.55; p = 0.57 |
| False Alarms Divided attention_visual | r = 0.02; p = 0.fourscore | r = −0.12; p = 0.23 | r = −0.15; p = 0.14 | r = −0.15; p = 0.13 | r = −0.79; p = 0.42 |
| RT Median Divided attention_visual | r = −0.01; p = 0.99 | r = −0.38 **; p = 0.0001 | r = 0.07; p = 0.49 | r = 0.18; p = 0.08 | r = −0.10; p = 0.28 |
From this analysis, we identified the variables to insert in the next regression models: gender, schoolhouse grade, and child's current historic period every bit independent variables. Table half-dozen shows summary hierarchical regression results.
Table half-dozen
Summary of hierarchical regression results.
| RESULTS | Alertness | Distractibility | Divided Attention | Go/no-get | Flexibility | Sustained Attention |
|---|---|---|---|---|---|---|
| Schoolhouse grade (3 levels: 2, three, four–5) | NS | NS | p < 0.05 omissions visual stimuli conditions p < 0.05 RT median visual stimuli conditions p < 0.05 RT median acoustic stimuli conditions | NS | NS | p < 0.05 for number of omissions and RT median (get-go 5 min) omissions (second 5 min) |
| Gender (male person/female) | NS | p < 0.05 RT median and false alarms (with and without distractor conditions) | p < 0.05 RT median visual stimuli condition | p < 0.05 fake alarms and omissions | NS | p < 0.05 for number of simulated alarms (second v min) (second 5 min and total time) |
three.1. Alertness
We obtained no significant predictors of alacrity median, reaction times, and standard difference.
3.2. Distractibility
For the beginning condition, with presence of the distractor on the screen, the significant model (R2 = 0.13; Fthree = 5.33; p = 0.002) identified female gender (ß = 0.213; p = 0.014) as the factor influencing the increase of distractibility RT median. On the other hand, female person gender (R2 = 0.15; F3 = half-dozen.23; p = 0.001) impacted as a protective gene in making false alarms (ß = −0.33; p = 0.001).
For the 2d condition, without distractor, the significant model (R2 = 0.xix; F3 = seven.88; p = 0.0001) showed that the distractibility RT median increased by female gender (ß = 0.38; p = 0.0001). Some other hierarchical model (R2 = 0.15; Fthree = half dozen.23; p = 0.001) identified gender (ß = −0.33; p = 0.0001) every bit the variable influencing the false alarms frequency, more often made in boys than girls.
3.3. Divided Attention
Considering the condition of acoustic stimuli, the significant model (R2 = 0.07; F3 = 2.64; p = 0.05) identified the school grade (ß = −0.43; p = 0.03) equally the factor influencing median RT in the divided attention test. By increasing the child's schoolhouse grade, median RT was lower, with meliorate rapidity.
Considering the condition of visual stimuli, the pregnant model (Rtwo = 0.21; F3 = 9.24; p = 0.0001) identified female gender (ß = −0.17; p = 0.05) and higher child's school form (ß = −0.47; p = 0.01) equally predictors of lower median RT in the divided attention test. A dissimilar number of omissions (R2 = 0.x; F3 = 3.97; p = 0.01) resulted from the kid'due south schoolhouse grade (ß = −0.55; p = 0.008).
3.iv. Go/No-Go
Gender (ß = −0.33; p = 0.001) influenced significantly the number of false alarms (R2 = 0.12; F3 = 4.51; p = 0.005). The aforementioned consequence was shown for omissions (R2 = 0.07; F3 = 2.vi; p = 0.05), with gender impacting significantly (ß = −0.24; p = 0.015). Girls had the all-time performance.
iii.5. Flexibility
A series of hierarchical regression analyses was performed, with kid's gender, current age, and school course as independent variables and RT median, RT median in percentiles, false alarms, and faux alarms in percentiles equally dependent ones, inserted 1 by one. Results showed that the number of false alarms and RT median, both in raw score and in percentiles, showed no meaning change along these demographic factors.
3.6. Sustained Attention
In the first five min of testing, the child's school grade (ß = −0.49; p = 0.001) significantly impacted the number of omissions (Rtwo = 0.eighteen; Fthree = vii.34; p = 0.01). Another regression model (R2 = 0.26; F3 = xi.83; p = 0.0001) identified the child's school grade (ß = −5; p = 0.009) as a meaning factor influencing the RT median. The children in higher grades showed lower RT medians and made fewer omissions.
For the second part of the test, i.e., the last v min, the regression model (Rii = 0.07; F3 = 2.84; p = 0.04) identified female person gender (ß = −0.23; p = 0.01) every bit a significant cistron impacting a reduced number of simulated alarms. Omissions were influenced significantly by the kid's school age (ß = −0.59; p = 0.003) in some other regression model (Rtwo = 0.24; Fthree = 10.61; p = 0.0001), where children with higher school accomplishment that obtain a ameliorate performance.
4. Discussion
To reply the first enquiry question, we showed the distribution of children's operation in standardized tests for the Italian population by percentile categories. A great proportion of children enter the lower level of percentiles of faux alarms and omissions in almost all the attentional tasks, compared with Italian norms. On the other manus, reaction time medians that correspond to process rapidity are quite constant, except for alacrity and sustained attention tasks, where at least a tertiary or more do not achieve the 50th percentile, under the normative cutting-off. In the distractibility test, children obtain good scores in rapidity, merely at the expense of accuracy, with a college frequency of omissions of the target stimuli. We know that response inhibition tasks load mainly on key executive measures, predicting reading power [21], then loftier frequencies of faux alarms and omissions in the go/no-go test could be precursors of reading difficulties in children.
Dealing with the 2nd inquiry question, the results testify that for all 6 KiTAP tests school course appears to be a key factor, indicating that it significantly influences the performance of students throughout the bombardment. Their operation along the three school class groups varies and differs, peculiarly for children in grade 2. Probably from the age of 8 years, in that location is a transition from an immature stage to a more competent i, as indicated in previous studies [21,35]. An important increase in attentional functions operation is obtained from students in grade 3, and it continues to get better in the last two years of master school (ix–10 years of age). These results identify the school form as a primal factor, too controlling for chronological historic period, showing how the bookish experience and learning through several school cycles are even more important than the chronological age, confirming the important function of schooling achievement in improving superior attending functions [38]. In the alertness examination, no significant difference results are found forth school grade, chronological age, or gender. The performance is stable throughout the several sociodemographic factors, as found in other studies adopting KiTAP [35,56]. Summarizing, nosotros tin country that the division of the sample into the three school form groups is interesting, considering it allows the states to detect the worse performances in pupils attending grade 2 compared to the college classes. Chronological age is not significant in itself, simply but associated with academic level. This is an innovative consequence, obtained with this design, that weights the several possible predictors identifying the best. Probably chronological historic period is important, just only if accompanied past the schooling experience and activities. Unfortunately, a limit of this report is given past the fact that we did not appraise children attention grade 1. Further studies should take into consideration performance amid first-graders, enabling researchers to accomplish a more complete description of the development of attentional functions in childhood.
Possible gender differences [36,37] were also investigated in the 3rd research question. In the distractibility test, rapidity in reaction times is mostly obtained by boys, even if they commit more fake alarms. This suggests that boys are faster but less accurate and more focused on their task than are girls, both in the condition with and without the distractor on the screen.
Also, in the divided attention test children attending the last grades show the best performance, while the worst is still for seven-year-erstwhile boys attending grade ii: they globally commit more omissions, specially when the target stimulus is visual. Girls in the lower grades prove higher reaction times. Perhaps a visual target elicits more than attention than an acoustic one on the screen. So, 7-year-one-time boys show the worst ability to stay concentrated and focused on multiple tasks. When the stimulus is audio-visual, the median RT is higher in children belonging to lower grades.
In the become/no-become test, boys show more false alarms and omissions than do girls; probably they press the button less often and then brand fewer mistakes.
In the flexibility test, there are no significant run a risk factors influencing the children's operation, merely in general it is possible to note that children are really fast, but not authentic.
With regard to the last examination, sustained attention, in the first 5 min pupils in the higher grades take the best operation, doing the fewest number of omissions and having more rapid reactions (median RT), while the worst performances are by those in the lower grades. Boys committed more false alarms in the last 5 min. This can be explained by the nature of the test: elementary and specially monotonous, the worst performances of pupils can be acquired by fatigue, especially in younger children (vii years), and boredom, especially in boys, who accept more difficulty in staying focused on the examination.
Summarizing, the analyses conducted on the scores obtained from our sample, consisting of 48 boys and 57 girls, bear witness that, overall, the worst performances are obtained from boys for accuracy. Comparing the performance of boys and girls through the three schoolhouse grade groups, it is to be noted that the number of omissions or faux alarms were generally college for boys, specifically in the go/no-get and distractibility tests, while median reaction times are reduced. In KiTAP trials, therefore, girls by and large have improve results than boys, showing that their performances are consistently better in accuracy, even if less rapid. Boys are faster but less accurate. Girls in the lower grades have more median RT in the divided attention examination with the visual target on the screen.
The tertiary inquiry question aimed to investigate whether the socioeconomic context of the pupil's family could influence his or her attentional performance [44]. The economic condition is non a gene that appears equally a pregnant variable for attentional performance.
The fourth question involved siblings: Could being a single kid or having siblings touch on the quality of the attentional performance? The assumption is that the presence of siblings is an of import resource of rich social, emotional, and cognitive stimuli [45,46]. Results from this study show that this factor does not touch on performance in favour of having siblings, merely it is necessary to consider that in our sample of 105 pupils, 78 had siblings and just 27 were unmarried children, so information technology is hard to exclude this factor.
Strengths and Limitations
A force of this study is the opportunity to investigate attention in an exclusive and accurate way, directly on children in their school setting. The choice of KiTAP equally the assessment instrument is valuable from different points of view: it is structured through very simple and firsthand tests; it is a computer-based exam bombardment comprising various subtests that encompass a broad range of neuropsychological functions of attention; and it allows a good investigation of attention and its mechanisms, fifty-fifty with young or inexperienced children, considering that the different subtests are contained from language. In addition, because it is a computer test presented as a form of play and with fantastic stories and fun, colourful graphics, information technology is jump to motivate children.
The ample number of participants involved in the project, all from the same geographical expanse, is a betoken of strength fifty-fifty if similar residence can also be considered as a limitation; future research should aim to involve other primary schools in other areas to have a sample more than representative of the unabridged state. Another limitation is represented past the inhomogeneity of the sample along age groups, with younger children (6–7 years sometime) less numerous than older ones (eight–10 years erstwhile). Information technology will be important to increase the number of participants in the offset age grouping to have a more homogeneous distribution according to age. We too could non take a blended SES to answer our research question considering our variable was assessed forth different parameters: perceived socioeconomic condition, parental educational level, parental workload in a week. Nosotros could non composite these different scales and variables in a unique dimension. Some other limitation is that this report could not present the entire KiTAP.
Future research could also focus on improve agreement how family socioeconomic condition affects children's abilities, and even more than, to empathise whether parents' minor presence in the lives of children affects the quality of their attentional functioning. The presence of siblings does non seem to help the child to reach amend attentional operation. It would be interesting to better understand this phenomenon, also assessing siblings' attentional functions or observing the sibling human relationship during daily family unit life. Longitudinal studies could exist more informative on the development of attentional functioning in children throughout the different schoolhouse grades, and hereafter studies have to focus on this type of design. Other factors such as the student–teacher relationship and temperament should be taken into consideration in futurity studies as possible factors that may also play a part in children'southward attentional performance.
5. Conclusions
Higher school class matches better performance, peculiarly in advanced attentional tasks, such as divided and sustained attention, with pupils attention the lower grades showing the worst functioning independently from their chronological age. Observing these results, we tin imagine how school activities and omnipresence touch on upon avant-garde circumspect tasks. Schooling accomplishment implements and empowers children'south attentive tasks more than the normal advancement of historic period, providing a sort of preparation in attentional functions. In this written report, we ostend the distinction between basic and nonbasic skills: for the bones tests (i.eastward., alertness, distractibility, go/no-go), the performance of lower-class pupils is at least similar to those of their higher-form companions, while in the nonbasic skills (divided and sustained attention) the child'southward scholastic achievement becomes a primal cistron in ameliorating the child'due south performance.
The results testify that girls obtained a consistently higher operation throughout the iii age groups, especially in the go/no-go and distractibility tests. On the other manus, boys reported best performance with regard to rapidity, even if they are less accurate. Possible educative programmes should focus on amelioration of boys' inhibitory activeness and empowerment of girls' fast reaction times.
Family factors such as presence of siblings, parental schooling years, and socioeconomic condition practise not emerge as possible significant variables on attentional functioning. Further studies with a more homogeneous sample of these variables might better investigate these aspects, for instance, if the presence of siblings helps in attentive functions.
Author Contributions
Conceptualization, L.T.; Data curation, Grand.T.; Formal analysis, One thousand.T.; Methodology, S.B.; Supervision, L.T. and South.B.; Writing—original draft, M.T.; Writing—review & editing, L.T. and S.B.
Funding
This research received no external funding.
Conflicts of Interest
The authors declare no conflict of interest.
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