Abstract
Background
Attention deficit hyperactivity disorder(ADHD) is more prevalent in boys than girls. However, there was a larger proportion of girls displaying inattentive symptoms compared to boys.
Aim
To investigate the gender differences in attentional blink in children with ADHD.
Method
A total of 99 children in the ADHD group and 99 children in the typically developing children group were assessed. All children completed a dual-task rapid continuous visual presentation paradigm.
Results
The onset time of attentional blink in girls in the ADHD group was later than that in the typically developing children group (T1–lag1, P = 0.122 vs. P < 0.001), but it was identical between boys in the ADHD group and typically developing children group (T1–lag1, all P < 0.001). Attentional blink duration in girls in the ADHD group was shorter than that in the typically developing children group (T1–lag6, P = 0.084 vs. P = 0.033), but longer in boys in the ADHD group than in the typically developing children group (T1–lag8, P = 0.022 vs. P = 0.356).
Conclusion
The mechanism of attentional blink may differ between boys and girls with attention deficit hyperactivity disorder.
Supplementary Information
The online version contains supplementary material available at 10.1038/s41598-025-28910-w.
Keywords: Attention deficit hyperactivity disorder, Attentional blink, Rapid serial visual presentation
Subject terms: Psychology, Medical research
Introduction
Attention deficit hyperactivity disorder (ADHD) is among the most common disorders among children and adolescents, with a worldwide prevalence of > 5%1. Despite an overwhelming body of research over the past 10–20 years, the assessment and treatment of ADHD continue to present a challenge for clinicians2.
ADHD is more prevalent in boys than in girls, with male-to-female ratios usually reported as 2:1, or as high as 4 or 5 to 13. However, compared with boys, girls display more inattentive symptoms4,5. Among girls, the risk of reading disability associated with ADHD (vs. non-ADHD) has also been found to be significantly higher than that among boys6. Thus, previous studies have suggested that ADHD exhibits sex differences in clinical features.
In terms of pathophysiology, the prefrontal cortex directly influences attentional processing, and different regions may have distinct functions7. Dirlikov et al.8 reported that compared with typically developing children, girls with ADHD had widespread reductions in surface area in the bilateral dorsolateral prefrontal cortex, the left inferior lateral prefrontal cortex, the right medial prefrontal cortex and the right orbitofrontal cortex; boys with ADHD showed reduced surface area in the right anterior cingulate cortex and the left medial prefrontal cortex. These studies suggest different pathophysiological mechanisms in boys versus girls with ADHD.
Cognitive deficits, particularly impairments in attention and executive function, are commonly observed in children with ADHD9,10. Children with ADHD usually exhibit difficulties in selective attentional processes, such as redirecting attention to new stimuli and sustaining their attention level11. Recent studies have also shown that children with ADHD demonstrate impairments in temporal attention12,13. Therefore, a method to evaluate attentional selectivity and processing in the temporal dimension is needed.
“Attentional blink” is a phenomenon observed in rapid serial visual presentation. Individuals exhibit a reduced ability to accurately recognize the second of two targets (T2) in a stream of distracters if it appears within 200–500 ms of the first (T1)14–16, which reflects the selectivity and processing of attention in the temporal dimension. Broadbent first discovered attentional blink through the dual-task rapid serial visual presentation paradigm in 198714. In the dual-target task, two target stimuli (T1 and T2) were presented at different positions or “lags” within a rapid sequential stream of distractor stimuli17.
The “attentional blink effect” is considered to be the accuracy of detecting a second target stimulus (T2/T1) on the basis of the correct response to the first target stimulus (T1). The lower the accuracy of detection of T2/T1, the more severe the attentional blink effect18. The attentional blink effect varies across populations. Several studies have shown that the attentional blink effect is more severe in patients with social anxiety and schizophrenia19, people who abuse alcohol20, and individuals with autism21. However, the conclusions on the attentional blink effect in children with ADHD are inconsistent. Some studies have shown that compared with control children, those with ADHD exhibit a more pronounced attentional blink effect11,22,23, but some contrary findings have been reported24,25. The differences may be due to varying sample sizes (12–74 children with ADHD) and differences in experimental paradigms.
Attentional blink duration is defined as the time point at which the attentional blink effect disappears. If the interval between T1 and T2 is sufficiently long such that the detection of T2/T1 is not interfered with by T1, then the attentional blink effect disappears, indicating recovery. Li et al. found that recognition of T2 after 500 ms meant that children with ADHD took longer to recover from attentional blink than their healthy counterparts26; however, only 43 children with ADHD and 40 healthy children were included in that study.
“Attentional blink magnitude” is defined as the difference between the maximum level (usually at one of the longer lags) of the accuracy of detection for T2/T1 and the minimum level (usually at one of the shorter lags) of the accuracy of detection for T2/T1. A greater difference indicates a more pronounced attentional blink magnitude27. However, “traditional” attentional blink magnitude seems to evaluate only the overall magnitude of attentional blink rather than the changes at each T2 lag. In the present study, attentional blink magnitude is defined as the difference in detection accuracy between T1 and each T2 lag. A greater difference indicates a higher attentional blink magnitude. The value of the attentional blink magnitude reflects the degree of interference of T1 upon the recognition accuracy of T2.
Previous research has shown that children with ADHD exhibit more significant attentional blink deficits in rapid serial visual presentation tasks than TD children25. Zhang D et al.28 first measured the attentional blink of healthy adults using a dual-target rapid serial visual presentation paradigm during functional magnetic resonance imaging (fMRI) scanning to construct an attentional blink-associated neural network (connectome) and attempted to identify a distributed brain network for attentional blink in children with ADHD. They reported that this individual attentional blink network could serve as an applicable neuroimaging-based biomarker of attentional blink deficits and predict symptoms of ADHD in children. Therefore, the neural mechanisms underlying attentional blink may also contribute to ADHD. However, studies comparing differences in attentional blink between boys and girls with ADHD are currently lacking.
The primary aim of this study was to explore whether sex differences exist in attentional blink between children with ADHD and typically developing children. The results may contribute to better understanding the differences in clinical features and pathophysiology mechanisms between boys and girls with ADHD.
Materials and methods
Ethics statement
This study was approved by the Ethics Committee of the Children’s Hospital of Fudan University (Shanghai, China; Approval No. 2018 − 289) and was conducted in accordance with the Declaration of Helsinki and relevant national and institutional guidelines. Written informed consent was obtained from the legal guardians of all participants. In addition, assent was obtained from the children when appropriate. Participants were informed that they could withdraw from the study at any time without consequences. The flowchart of the methodological details is shown in Fig. 1.
Fig. 1.
The methodology flowchart. ADHD: Attention deficit hyperactivity disorder; RSVP: Rapid serial visual presentation paradigm.
Participants
The study was divided into two groups: the ADHD group and the typically developing children group. Their respective inclusion and exclusion criteria were as follows:
The ADHD group comprised 99 children diagnosed with ADHD who were recruited from the Children’s Hospital of Fudan University and Shanghai Mental Health Center (Shanghai, China). Diagnoses and subtype classifications (combined type, inattentive type, or hyperactive-impulsive type) were made by a consultant psychiatrist with expertise in ADHD. We confirmed this ADHD diagnosis according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR, American Psychiatric Association, 2000), incorporating information from the MINI-International Neuropsychiatric Interview (MINI) interview as well as parent/teacher rating scales. Inclusion criteria for this group were: (1) A confirmed diagnosis of ADHD; (2) Age range of 7–14 years; (3) An intelligence quotient (IQ) ≥ 85 based on the Wechsler Intelligence Scale. Exclusion criteria included: (1) Any psychiatric comorbidity or other mental disorders; (2) Any history of medication use prior to study initiation.
The typically developing group consisted of 99 children recruited from primary schools in Nanjing and Shanghai, China. Inclusion criteria for this group were: (1) Age range of 7–14 years; (2) An intelligence quotient (IQ) ≥ 85 based on the Wechsler Intelligence Scale; (3) Absence of acute physical illness within one week prior to enrollment. Exclusion criteria included: (1) History of significant chronic physical disease, neurological disorder, or serious mental disorder; (2) Any history of medication use prior to study initiation.
Testing
The dual-task rapid serial visual presentation paradigm was employed to observe attentional blink in the ADHD group and typically developing children group. The rapid serial visual presentation test program used was developed by Houcan Zhang and Yongrui Li from Beijing Normal University (Beijing, China)29. All children completed this test on a computer.
The dual-target rapid serial visual presentation task included 160 trials. Each trial consisted of a rapid serial stream of capital letters presented centrally on the screen. Each letter appeared for 10 ms, with an interstimulus interval of 125 ms. The distractor stimuli were black capital letters, randomly selected, while the first target stimulus (T1) was a white capital letter randomly positioned within the stream. Between 7 and 15 distractors preceded T1. The second target stimulus (T2) was a black letter “X”, appearing at a lag of 1 to 8 positions following T1. Target and distractor positions were fully randomized across trials. After the stimulus had been presented, participants were required to report T1 and T2 accurately. After each stream, participants were asked to report both T1 and T2 using the keyboard. Trials in which participants failed to correctly identify T1 were excluded from the T2 accuracy calculation. Participants whose T1 accuracy was less than 50% across the entire session were excluded from further analysis. Before the formal task, participants completed 10 practice trials to familiarize themselves with the procedure.
The primary objective of this study was to examine participants’ ability to detect T2 based on their correct response to T1 (T2/T1). Specifically, we recorded the accuracy of detection of T2/T1 at different lags. If T2 occurred immediately after T1 without any intervening stimuli, the accuracy of detection was noted as “lag1,” which had an interval of 135 ms. If there was a distraction stimulus between T1 and T2, then the accuracy of detection was recorded as “lag2” with an interval time of 270 ms. The accuracy of detection of T2/T1 at “lag3” had two distraction stimuli between T1 and T2 and a response time of 405 ms. We followed this method of recording data until “lag8,” which indicated seven distracting stimuli between T1 and T2 and an interval of 1080 ms.
Statistical analyses
An “a priori” sample size calculation was performed using the program G*Power (version 3.1.9.7)30. The following statistical criteria were established: (1) an effect size of 0.5, (2) an alpha error of 0.05, (3) a statistical power of 95% and (4) an allocation ratio of 1:1. Using G*Power’s “Means - difference between two independent means (two groups)” function with these parameters produces a result indicating that at least 89 participants per group are required to achieve sufficient power and significance—resulting in a minimum total of 178 participants. An expected drop-out rate of 10% was considered, leading to a target final sample size of 196 participants. In the end, a total of 198 participants were included, with 99 participants in each group. Statistical analyses were performed using R 4.1.3 (R Institute for Statistical Computing, Vienna, Austria). Continuous variables are expressed as means ± standard deviations. Categorical variables are presented as numbers (%). For comparisons between two groups, Student’s t test was used for continuous variables with a normal distribution, the Wilcoxon rank-sum test was employed for non-normally distributed continuous variables, and the chi-square test was used for categorical variables. Paired data were analyzed using the paired-sample Student’s t tests. “Difference” values represent the mean difference in detection accuracy between each T2 lag (lag1–lag8) and T1 within the same participant group. Corresponding t-values represent test statistics from paired-sample t tests, which were used to compare the detection accuracy of T1 and each T2 lag. For the linear mixed-effects model, we used the “lme” function in the nlme package31. The dependent variable was attentional blink magnitude. The fixed effects included group (ADHD vs. typically developing children), lag (lag1–lag8), interaction (group × lag), and age (as a continuous covariate). A random intercept for each participant was included to account for within-subject variability.
Results
Baseline characteristics of all children
For the ADHD group (N = 99, mean age: 10.22 ± 1.51 years), the distribution of ADHD subtypes was as follows:46 had combined type (ADHD-C), 43 had predominantly inattentive type (ADHD-I), and 10 had predominantly hyperactive-impulsive type (ADHD-HI). A gender breakdown showed that among the 64 boys, 31 had ADHD-C, 26 had ADHD-I, and 7 had ADHD-HI. For the 35 girls, 15 had ADHD-C, 17 had ADHD-I, and 3 had ADHD-HI.
The typically developing group (N = 99, mean age: 10.28 ± 1.47 years) consisted of 67 boys and 32 girls. There were no significant differences in age (P = 0.775) or sex (P = 0.764) between the two groups. Baseline characteristics of all children are summarized in Table 1.
Table 1.
Baseline characteristics of all children.
| ADHD | Typically developing children | t/χ2 | P-value | |
|---|---|---|---|---|
| N | 99 | 99 | ||
| Age (mean ± SD)) | 10.22 ± 1.51 | 10.28 ± 1.47 | 0.286 | 0.775 |
| Gender (%) | 0.203 | 0.764 | ||
| Male | 64 (64.6) | 67 (67.7) | ||
| Female | 35 (35.4) | 32 (32.3) |
ADHD: Attention deficit hyperactivity disorder; SD: Standard deviation.
Differences in the accuracy of detection between the two groups of all children
Comparison of detection accuracy between the two groups (Table 2) revealed significant differences in the accuracy of detection at T1 at lag3–lag8 (all P < 0.05) but not at lag1–lag2 (all P > 0.05). Cohen’s d values for significant differences at T1 and lag3–lag8 ranged from − 0.31 to -0.46, indicating small to moderate effects. Effect sizes at lag1 and lag2 were close to zero, suggesting negligible group differences.
Table 2.
Differences in the accuracy of detection between the two groups of all children.
| Children with ADHD (N = 99) | Typically developing children (N = 99) | t | P-value | Cohen’s d | |
|---|---|---|---|---|---|
| T1 | 65.8 ± 20.81 | 72.4 ± 21.24 | 2.192 | 0.030* | -0.31 |
| lag1 | 47.0 ± 26.27 | 44.4 ± 28.48 | -0.662 | 0.509 | 0.10 |
| lag2 | 28.9 ± 21.36 | 27.2 ± 20.85 | -0.554 | 0.580 | 0.08 |
| lag3 | 32.1 ± 23.15 | 40.8 ± 23.98 | 2.593 | 0.010* | -0.37 |
| lag4 | 39.0 ± 24.10 | 51.3 ± 28.77 | 3.250 | 0.001** | -0.46 |
| lag5 | 40.2 ± 23.49 | 51.3 ± 27.15 | 3.068 | 0.002** | -0.44 |
| lag6 | 51.2 ± 25.40 | 63.3 ± 28.84 | 3.136 | 0.002** | -0.45 |
| lag7 | 52.2 ± 26.37 | 61.4 ± 28.28 | 2.369 | 0.019* | -0.34 |
| lag8 | 61.5 ± 28.92 | 70.9 ± 30.12 | 2.229 | 0.027* | -0.32 |
ADHD: Attention deficit hyperactivity disorder; T1 was the accuracy of detection for first target stimulus; T2/T1 was the accuracy of detection for second target stimulus; lag1 was the accuracy of detection for T2/T1 at the position of 135ms; lag2 was the accuracy of detection for T2/T1 at the position of 270ms; lag3∼lag8 were recorded in the same manner. *P < 0.05; **P < 0.01.
Differences in the accuracy of detection between the two groups stratified by gender
Comparison of detection accuracy for boys in the two groups (Table 3) revealed a significant difference at lag4 (P < 0.05) but not at T1, lag1–lag3, or lag5–lag8 (all P > 0.05). The effect size at lag4 was moderate (Cohen’s d = -0.42).
Table 3.
Difference in the accuracy of detection between the two groups stratified by gender.
| Boys (N = 131) | Girls (N = 67) | |||||||
|---|---|---|---|---|---|---|---|---|
| Children with ADHD (N = 64) | Typically developing children (N = 67) | Cohen’s d | P-value | Children with ADHD (N = 35) | Typically developing children (N = 32) | Cohen’s d | P-value | |
| T1 | 70.3 ± 16.5 | 70.3 ± 22.7 | 0.00 | 0.999 | 57.6 ± 25.2 | 76.7 ± 17.3 | -0.87 | < 0.001*** |
| lag1 | 46.9 ± 26.6 | 48.4 ± 30.0 | -0.05 | 0.754 | 47.2 ± 26.1 | 36.0 ± 23.2 | 0.45 | 0.069 |
| lag2 | 28.5 ± 21.3 | 29.5 ± 20.4 | -0.05 | 0.781 | 29.7 ± 21.8 | 22.5 ± 21.3 | 0.33 | 0.179 |
| lag3 | 32.8 ± 23.9 | 40.9 ± 25.2 | -0.33 | 0.061 | 31.0 ± 22.0 | 40.7 ± 21.6 | -0.44 | 0.073 |
| lag4 | 39.9 ± 25.8 | 51.6 ± 29.6 | -0.42 | 0.018* | 37.3 ± 20.8 | 50.6 ± 27.5 | -0.55 | 0.028* |
| lag5 | 43.0 ± 25.3 | 50.3 ± 29.2 | -0.27 | 0.131 | 35.1 ± 19.1 | 53.3 ± 22.6 | -0.87 | < 0.001*** |
| lag6 | 51.7 ± 27.6 | 60.2 ± 30.9 | -0.29 | 0.103 | 50.3 ± 21.2 | 70.0 ± 22.9 | -0.89 | < 0.001*** |
| lag7 | 52.8 ± 27.7 | 57.0 ± 29.8 | -0.15 | 0.401 | 51.0 ± 24.0 | 70.5 ± 22.8 | -0.83 | 0.001** |
| lag8 | 63.4 ± 29.8 | 67.8 ± 32.6 | -0.14 | 0.422 | 58.1 ± 27.3 | 77.3 ± 23.4 | -0.75 | 0.003** |
ADHD: Attention deficit hyperactivity disorder; T1 was the accuracy of detection for first target stimulus; T2/T1 was the accuracy of detection for second target stimulus; lag1 was the accuracy of detection for T2/T1 at the position of 135ms; lag2 was the accuracy of detection for T2/T1 at the position of 270ms; lag3∼lag8 were recorded in the same manner. *P < 0.05; **P < 0.01; ***P < 0.001.
Comparisons of detection accuracy for girls in the two groups (Table 3) revealed significant differences at T1 and lag4–lag8 (all P < 0.05) but not at lag1–lag3 (all P > 0.05). Effect sizes at T1 and lag4–lag8 ranged from − 0.44 to -0.89, indicating moderate to large group differences.
Attentional Blink duration in all children in the two groups
Among all children (Table 4), significant differences in detection accuracy between T1 and T2 (lag1–lag7) (all P < 0.001) were found, but not at lag8 (P > 0.05). Cohen’s d values for T1–T2 (lag1–lag7) ranged from 0.506 to 1.383 in the ADHD group and from 0.424 to 1.631 in the typically developing group, indicating moderate to large effects. These results suggest that attentional blink duration in both groups lasted between 945 ms and 1080 ms.
Table 4.
Attentional Blink duration in all children in the two groups.
| T1-T2/T1 | Children with ADHD | Typically developing children | ||||
|---|---|---|---|---|---|---|
| Difference | Cohen’s d | P-value | Difference | Cohen’s d | P-value | |
| T1-lag1 | 18.838 | 0.586 | < 0.001*** | 27.967 | 0.985 | < 0.001*** |
| T1-lag2 | 36.926 | 1.383 | < 0.001*** | 45.139 | 1.631 | < 0.001*** |
| T1-lag3 | 33.660 | 1.191 | < 0.001*** | 31.525 | 1.377 | < 0.001*** |
| T1-lag4 | 26.806 | 1.013 | < 0.001*** | 21.099 | 0.912 | < 0.001*** |
| T1-lag5 | 25.583 | 1.021 | < 0.001*** | 21.062 | 0.890 | < 0.001*** |
| T1-lag6 | 14.582 | 0.582 | < 0.001*** | 9.022 | 0.424 | < 0.001*** |
| T1-lag7 | 13.632 | 0.506 | < 0.001*** | 10.979 | 0.583 | < 0.001*** |
| T1-lag8 | 4.260 | 0.171 | 0.093 | 1.458 | 0.068 | 0.501 |
ADHD: Attention deficit hyperactivity disorder; T1 was the accuracy of detection for first target stimulus; T2/T1 was the accuracy of detection for second target stimulus; lag1 was the accuracy of detection for T2/T1 at the position of 135ms; lag2 was the accuracy of detection for T2/T1 at the position of 270ms; lag3∼lag8 were recorded in the same manner; the “Difference” represents the mean difference in accuracy of detection between each T2 lag (lag1–lag8) and T1 within the same participant group. ***P < 0.001.
Attentional Blink duration stratified by gender in the two groups
Among boys in the ADHD group (Table 5), significant differences in detection accuracy were found between T1 and T2 at lag1–lag8 (all P < 0.05). Cohen’s d (lag1–lag8) ranged from 0.293 to 1.618, indicating small to large effect sizes. These results suggest that attentional blink duration of boys in the ADHD group was ≥ 1080 ms.
Table 5.
Attentional Blink duration time in boys in the two groups.
| T1-T2/T1 | Children with ADHD | Typically developing children | ||||
|---|---|---|---|---|---|---|
| Difference | Cohen’s d | P-value | Difference | Cohen’s d | P-value | |
| T1-lag1 | 23.425 | 0.867 | < 0.001*** | 21.862 | 0.818 | < 0.001*** |
| T1-lag2 | 41.823 | 1.618 | < 0.001*** | 40.803 | 1.534 | < 0.001*** |
| T1-lag3 | 37.510 | 1.385 | < 0.001*** | 29.393 | 1.192 | < 0.001*** |
| T1-lag4 | 30.359 | 1.217 | < 0.001*** | 18.713 | 0.859 | < 0.001*** |
| T1-lag5 | 27.231 | 1.158 | < 0.001*** | 19.953 | 0.782 | < 0.001*** |
| T1-lag6 | 18.545 | 0.749 | < 0.001*** | 10.113 | 0.439 | < 0.001*** |
| T1-lag7 | 17.472 | 0.727 | < 0.001*** | 13.229 | 0.721 | < 0.001*** |
| T1-lag8 | 6.849 | 0.293 | 0.022* | 2.445 | 0.114 | 0.356 |
ADHD: Attention deficit hyperactivity disorder; T1 was the accuracy of detection for first target stimulus; T2/T1 was the accuracy of detection for second target stimulus; lag1 was the accuracy of detection for T2/T1 at the position of 135ms; lag2 was the accuracy of detection for T2/T1 at the position of 270ms; lag3∼lag8 were recorded in the same manner; the “Difference” represents the mean difference in accuracy of detection between each T2 lag (lag1–lag8) and T1 within the same participant group. *P < 0.05; ***P < 0.001.
For boys in the typically developing children group (Table 5), significant differences were found between T1 and T2 at lag1–lag7 (P < 0.001) but not at lag8 (P > 0.05). Cohen’s d values for T1–T2 (lag1–lag7) ranged from 0.439 to 1.534, indicating moderate to large effects. These results indicate that attentional blink duration in boys in the typically developing children group lasted between 945 ms and 1080 ms.
Among girls in the ADHD group (Table 6), significant differences were observed between T1 and T2 at lag2–lag5 (all P < 0.001) but not at lag1 or lag6–lag8 (all P > 0.05). Cohen’s d values for T1–T2 (lag2–lag5) ranged from 0.720 to 1.065, indicating moderate to large effects. These results suggest that for girls in the ADHD group, the onset time of attentional blink was 135–270 ms and the attentional blink duration lasted between 675 ms and 810 ms.
Table 6.
Attentional Blink duration time in girls in the two groups.
| T1-T2/T1 | Children with ADHD | Typically developing children | ||||
|---|---|---|---|---|---|---|
| Difference | Cohen’s d | P-value | Difference | Cohen’s d | P-value | |
| T1-lag1 | 10.449 | 0.268 | 0.122 | 40.747 | 1.462 | < 0.001*** |
| T1-lag2 | 27.972 | 1.065 | < 0.001*** | 54.219 | 1.929 | < 0.001*** |
| T1-lag3 | 26.621 | 0.904 | < 0.001*** | 35.990 | 1.970 | < 0.001*** |
| T1-lag4 | 20.308 | 0.720 | < 0.001*** | 26.094 | 1.029 | < 0.001*** |
| T1-lag5 | 22.569 | 0.813 | < 0.001*** | 23.385 | 1.208 | < 0.001*** |
| T1-lag6 | 7.336 | 0.302 | 0.084 | 6.739 | 0.394 | 0.033* |
| T1-lag7 | 6.611 | 0.215 | 0.212 | 6.267 | 0.325 | 0.076 |
| T1-lag8 | -0.474 | -0.017 | 0.919 | -0.608 | -0.028 | 0.875 |
ADHD: Attention deficit hyperactivity disorder; T1 was the accuracy of detection for first target stimulus; T2/T1 was the accuracy of detection for second target stimulus; lag1 was the accuracy of detection for T2/T1 at the position of 135ms; lag2 was the accuracy of detection for T2/T1 at the position of 270ms; lag3∼lag8 were recorded in the same manner; the “Difference” represents the mean difference in accuracy of detection between each T2 lag (lag1–lag8) and T1 within the same participant group. *P < 0.05; ***P < 0.001.
For girls in the typically developing children group (Table 6), significant differences were found between T1 and T2 at lag1–lag6 (all P < 0.05) but not at lag7–lag8 (all P > 0.05). Cohen’s d for T1–T2 (lag1–lag6) ranged from 0.325 to 1.970, also suggesting moderate to large effects. These results indicate that the attentional blink duration for girls in the typically developing children group lasted between 810 ms and 945 ms.
Linear mixed effects in attentional Blink magnitude
The results for the linear mixed effects for the attentional blink magnitude are shown in Table 7.
Table 7.
Linear mixed effects in attentional Blink magnitude of all subjects.
| All children | Boys | Girls | |
|---|---|---|---|
| Group | 1.87 (3.47) | 0.00 (4.03) | 1.70 (6.36) |
| lag1 | 27.97 (2.46) *** | 21.86 (2.93) *** | 40.75 (4.32) *** |
| lag2 | 45.14 (2.46) *** | 40.80 (2.93) *** | 54.22 (4.32) *** |
| lag3 | 31.53 (2.46) *** | 29.39 (2.93) *** | 35.99 (4.32) *** |
| lag4 | 21.10 (2.46) *** | 18.71 (2.93) *** | 26.09 (4.32) *** |
| lag5 | 21.06 (2.46) *** | 19.95 (2.93) *** | 23.39 (4.32) *** |
| lag6 | 9.02 (2.46) *** | 10.11 (2.93) *** | 6.74 (4.32) |
| lag7 | 10.98 (2.46) *** | 13.23 (2.93) *** | 6.27 (4.32) |
| lag8 | 1.46 (2.46) | 2.44 (2.93) | -0.61 (4.32) |
| age | -2.06 (0.87) * | -0.30 (1.05) | -1.39 (1.51) |
| Group×lag1 | -9.12 (3.47) ** | 1.56 (4.19) | -30.30 (5.97) *** |
| Group×lag2 | -8.21 (3.47) * | 1.02 (4.19) | -26.25 (5.97) *** |
| Group×lag3 | 2.13 (3.47) | 8.12 (4.19) | -9.37 (5.97) |
| Group×lag4 | 5.71 (3.47) | 11.65 (4.19) ** | -5.79 (5.97) |
| Group×lag5 | 4.52 (3.47) | 7.28 (4.19) | -0.82 (5.97) |
| Group×lag6 | 5.56 (3.47) | 8.43 (4.19) * | 0.60 (5.97) |
| Group×lag7 | 2.65 (3.47) | 4.24 (4.19) | 0.34 (5.97) |
| Group×lag8 | 2.80 (3.47) | 4.40 (4.19) | 0.13 (5.97) |
| Constant | 20.17 (8.89) * | 3.07 (11.08) | 0.00 (4.39) |
| Observations | 198 | 131 | 67 |
| Log Likelihood | -7785.21 | -5108.89 | -2603.69 |
| Akaike Inf. Crit. | 15612.41 | 10259.79 | 5249.39 |
| Bayesian Inf. Crit. | 15727.38 | 10365.97 | 5341.15 |
Values indicate the estimated effect (β) and corresponding standard error (SE). Group was the ADHD group and the typically developing children group; lag1 was the attentional blink magnitude at the position of 135ms; lag2 was the attentional blink magnitude at the position of 270ms; lag3∼lag8 were recorded in the same manner. *P < 0.05; **P < 0.01; ***P < 0.001.
For all children, significant main effects were observed at lag1–lag7. Significant group × lag interaction effects were found at lag1–lag2. The number of model observations was 198. The Akaike Inf. Crit (AIC), Bayesian Inf. Crit (BIC), and log likelihood of the model were 15612.41, 15727.38, and − 7785.21, respectively.
For boys, there were significant main effects at lag1–lag7 (Table 2), with significant group × lag interaction effects at lag4 and lag6. There were 131 observations of the model. The AIC, BIC, and log likelihood of the model were 10259.79, 10365.97, and − 5108.89, respectively.
For girls, significant main effects were observed at lag1–lag5, with significant group × lag interaction effects at lag1–lag2. There were 67 observations of the model. The AIC, BIC, and log likelihood of the model were 5249.39, 5341.15, and − 2603.69, respectively.
Discussion
For humans, information processing is based on attention, and attentional blink appears to be a physiological phenomenon. Raymond et al. reported that if individuals detect the first target stimulus correctly, their accuracy in detecting a second target stimulus forms a U-shaped distribution diagram15. In this study, both groups encountered attentional blink, and a U-shaped distribution diagram was constructed. Compared with T1, the accuracy of lag1–lag2 detection rapidly decreased. Lag2 registered the lowest point in detection accuracy, beyond which the detection accuracy began to increase.
We evaluated a larger study cohort than in previous studies and documented five main findings. First, the accuracy of detection at T1 was significantly lower in the ADHD group than in the typically developing children group, which is consistent with the results of Carr and colleagues25. This phenomenon was found in girls but not in boys. Second, the detection accuracy in the ADHD group was significantly lower than that in the typically developing children group (greater attentional blink effect) at all T2 lags except lag1 and lag2, which is consistent with the results of Amador-Campos and colleagues11. Additionally, the accuracy of detection for boys in the ADHD group was lower than that for boys in the typically developing children group only at lag4. However, the accuracy of detection for girls in the ADHD group was lower than that for girls in the typically developing children group at lag4–lag8. Third, significant group × lag interaction effects in attentional blink magnitude were found at lag1–lag2, and the β value was negative, which indicated that the rate of decline in detection accuracy in the ADHD group was slower than that in the typically developing children group. This phenomenon occurred in girls but not in boys. Fourth, at lag1, both groups experienced the onset of attentional blink, but this phenomenon was observed in girls, not boys. Fifth, all children in both groups recovered from attentional blink at lag8 (1080 ms). Compared with boys in the typically developing children group, boys in the ADHD group needed a longer time to recover from attentional blink. In contrast, an opposite effect was noted for girls in the ADHD group. Li CS and colleagues reported that children with ADHD require a longer time to recover from attentional blink than typically developing children26, which is consistent with the results for boys in the ADHD group in our study.
Among boys, significant group × lag interaction effects on attentional blink magnitude were observed at lag2 and lag4. These findings suggest that the rate of recovery of the detection accuracy was irregular for boys in both the ADHD group and the typically developing children group. This result has been due to random attention distractions during testing. Attention instability may contribute to poor performance in children with ADHD who have attentional blink32.
Paired Student’s t test revealed that the onset time of attentional blink for boys in the ADHD group was identical to that for boys in the typically developing children group. However, the duration of attentional blink was longer in boys with ADHD than in boys in the typically developing children group. These findings may be explained by the limited attentional resources theory. According to the interference model proposed by Shapiro et al.33, the two-stage model proposed by Raymond and colleagues15, and the central interference model proposed by Jolicoeur and collaborators34, attentional blink is caused by limited attentional resources. That is, when the interval between T1 and T2 is relatively short, then T1 processing uses a significant amount of attentional resources, resulting in insufficient attention to process the blink, thereby preventing it from being processed fully. Therefore, the prolonged duration of attentional blink for boys in the ADHD group might be attributed to the heavy use of attentional resources at T1.
Among girls, there were significant group × time interaction effects on attentional blink magnitude at lag1–lag2, and the β value was positive, indicating that the rate of decline in detection accuracy for girls in the ADHD group was slower than that for girls in the typically developing children group. Paired Student’s t test revealed that the onset time of attentional blink for girls in the ADHD group was later than that for girls in the typically developing children group. Additionally, the attentional blink duration for the girls in the ADHD group was shorter than that for girls in the typically developing children group.
Limited attentional resources theory cannot explain the findings in girls stated above. Therefore, some researchers have posited that attentional blink may not be based solely on limited resources but could involve resource allocation35,36. Olivers et al. reported that detection accuracy did not diminish but instead improved under positively charged emotions37. Vermeulen et al. found that individuals in a negative emotional state automatically increase their attention to distracting stimuli, thereby increasing the attentional blink effect38. In our study, detection accuracy for girls in the ADHD group was significantly lower than that for girls in the typically developing children group at T1, suggesting that the total processing capacity for attention was impaired. However, it is precisely this deficit that requires children with ADHD to exert greater effort in maintaining attention, which could explain why girls in the ADHD group had a later onset time for attentional blink and earlier recovery time from attentional blink than girls in the typically developing children group.
In summary, the results for boys with ADHD aligned with the limited attentional resources theory; the boys exhibited attentional blink when attentional demands exceeded total available capacity, and they had an earlier onset and later offset of the blink period. In contrast, the results for girls with ADHD were consistent with both the limited attentional resources theory and resource-allocation theory. Additionally, their overall attention-processing ability was more severely impaired than that of boys with ADHD. However, girls with ADHD compensated through subjectively increased attention, resulting in a later onset and earlier offset of the attentional blink. These sex differences may be linked to underlying neurobiological and neurodevelopmental mechanisms. Studies have shown that girls with ADHD demonstrate increased functional connectivity in brain networks such as the visual network and default-mode network, which supports more effective resource allocation and attentional control, contributing to compensatory effects such as delayed onset and earlier offset of attentional blink39. Neuropsychological studies have also shown that differences in arousal levels between girls with ADHD and typically developing girls are greater than those observed between boys with ADHD and typically developing boys40. This may help explain why overall attention-processing impairment is more severe in girls with ADHD than in boys with ADHD.
In clinical practice, we found that girls with ADHD are older than boys with ADHD at the time of medical intervention, yet they exhibit more significant attention deficits. Ahmad SI et al.41 also reported that ADHD-related symptoms may intensify or become more apparent later in adolescence, especially in females, during transitions to middle or high school. In exploring sex differences in attentional blink in the ADHD group, we found that the total attention-processing ability of girls with ADHD was more impaired than that of boys with ADHD. At lower levels of attention demand (earlier grades), this can be compensated by subjectively improved attention. Still, as the demand for attention increases (in upper grades), the difference between boys and girls with ADHD in total attention-processing ability has a significant effect on their academic performance. This may explain why girls with ADHD were older than boys at the time of medical intervention yet presented more significant attention deficits.
This study has several limitations. First, although age was included as a covariate in the statistical model, we did not conduct stratified analyses by age due to limited sample size in each subgroup, which may have reduced the statistical power. Future research should expand the overall sample size to allow age-specific subgroup analyses. Second, we did not incorporate neurophysiological or neuroimaging methods (e.g., event-related potentials or magnetic resonance imaging) to investigate the neural mechanisms underlying sex differences in attentional blink in ADHD. Exploring these neural correlates will be important for future research.
Conclusion
Compared with the typically developing children, boys and girls with ADHD exhibit significant differences in the onset time of attentional blink, rate of decline of the accuracy of detection, time taken to recover from attentional blink, and attentional blink duration. These findings suggest that the underlying mechanisms of attentional blink may vary by sex among children with ADHD. Future studies should further investigate the developmental trajectories and neurobiological correlates associated with these differences using longitudinal designs or advanced neuroimaging techniques. Additionally, examining how these sex-specific patterns relate to real-world cognitive or behavioral outcomes may provide deeper insight into optimizing clinical assessment tools and developing individualized treatment approaches for children with ADHD.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors are thankful for all the participants in this study.
Author contributions
**JS: ** Writing – original draft, Conceptualization, Methodology. **YT: ** Writing – original draft, Conceptualization, Methodology. **JZ: ** Data curation, Software. **WX: ** Data curation, Software. **SS: ** Data curation, Software. **YZ: ** Data curation, Software. **JHS: ** Supervision, Writing – review & editing.
Funding
This work was supported by grants from the Important and Weak Key Discipline Construction Projects of Health System in Shanghai in 2019: Psychosomatic Medicine (2019ZB0203); Natural Science Foundation of Shanghai (19ZR1406500); Three-year action plan from 2020 to 2022 for the construction of Shanghai public health system (GWV-10.2-XD31); Clinical Science and Technology Innovation Projects of Shanghai Shenkang hospital development center (SHDC12020126); Medical Discipline Construction Project of Pudong Health Committee of Shanghai (PWYgy2021-02).
Data availability
All data generated or analyzed during this study are included in this published article (and its Supplementary Information files).
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Data Availability Statement
All data generated or analyzed during this study are included in this published article (and its Supplementary Information files).