Longitudinal Patterns of Attention-Deficit/Hyperactivity Disorder Children in Shanghai, China

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Methods Using a longitudinal design, school-aged children with ADHD were enrolled and followed, with emotional and behavioral measures repeatedly assessed. Due to varying COVID-19 measures and changing epidemics, and no intervention was admitted, an event-based longitudinal design was adopted, using calendar time from the enrollment of the first participant. Data collection spanned various pandemic control stages, including the Shanghai lockdown (March 28 to May 31, 2022). Emotional and behavioral trends were analyzed using a Generalized Additive Model (GAM) to capture the nonlinear dynamics effectively. Results Overall, 1,102 children with ADHD (mean: 9.2 ± 2.4 years, 83% boys) were enrolled. Emotional and behavioral issues fluctuated over time. Behavioral problems, including inattention, hyperactivity, and conduct issues, peaked around day 260 of isolation and then declined but resurged after the Shanghai lockdown. Emotional issues, such as anxiety and depression, showed a dual-peak pattern, with early pandemic rises and a second peak around day 400. Symptoms rebounded after lockdown and persisted for an extended period. Sub-analyses revealed that boys had higher scores in hyperactivity and oppositional defiance than girls, with no significant gender differences in emotional problems. ADHD-PI children had higher emotional problem scores, while ADHD-HI children exhibited more severe behavioral issues. Conclusion This study highlights the substantial impact of prolonged COVID-19 measures on emotional and behavioral problems in ADHD children, particularly increased adaptive pressures post-lockdown. Phase-specific, individualized interventions are crucial to mitigate these challenges. Biological sciences/Psychology Biological sciences/Psychology/Human behaviour Attention-Deficit/Hyperactivity Disorder COVID Dynamic Change Figures Figure 1 Figure 2 Introduction Attention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neurodevelopmental disorders among children worldwide, with an estimated prevalence of around 5% [ 1 ].Core symptoms include inattention, hyperactivity, and impulsivity, often accompanied by elevated levels of anxiety and depressive symptoms, which are commonly observed in ADHD populations and may reflect co-occurring emotional difficulties rather than being exclusively intrinsic to ADHD itself [ 2 , 38 ]. Studies indicate that children with ADHD are particularly susceptible to the effects of stress, especially when faced with major life events or public health crises. These events and the associated preventive measures can have a pronounced impact on their emotional and behavioral states [ 2 ]. Compared to their peers, children with ADHD encounter greater difficulties in emotional regulation and behavioral control, with such challenges often intensifying in the context of substantial life changes. For example, the COVID-19 pandemic may have a substantial impact on children with ADHD, especially those directly affected by COVID-19 measures (i.e., lockdown) [ 3 ]. These measures may exacerbate mental health issues, leading to increased fluctuations in emotional and behavioral outcomes. However, research examining the dynamic emotional and behavioral changes in children with ADHD under prolonged COVID-19 measures remains limited[ 4 ].This study aims to address this gap by assessing the dynamic changes in emotional and behavioral problems among children with ADHD during the COVID-19 pandemic and exploring differences by gender and ADHD subtype. We hypothesize that emotional and behavioral problems in ADHD children will intensify during the early pandemic and post-lockdown phases, with significant variations across gender and ADHD subtypes. As the COVID-19 pandemic has persisted, extended periods of confinement, heightened social restrictions, and ongoing uncertainties about the future have presented children with ADHD with increasingly intensified challenges in emotional regulation, potentially exacerbating anxiety and other emotional disorders [ 5 ]. Existing research has shown that abrupt environmental changes and prolonged stressors contribute to greater emotional instability and elevated anxiety levels in children with ADHD [ 6 ]. However, there is a marked lack of longitudinal cohort studies that track the temporal dynamics of emotional and behavioral difficulties among this population under prolonged public health restrictions. Longitudinal studies are essential as they can elucidate the progression of emotional and behavioral issues over time under sustained stress, identifying critical high-risk periods and cumulative effects that cross-sectional studies cannot capture. This study provides a unique contribution by conducting a prospective cohort study to systematically evaluate the shifts in emotional and behavioral patterns among children with ADHD across various stages of pandemic control measures. By offering data from this extended period, the study lays a scientific foundation for developing phase-specific, personalized support strategies. Shanghai, China presents a unique case globally, as one of the few cities that experienced over two months of stringent lockdown, during which residents’ outdoor activities were highly restricted. This distinctive context offers significant scientific relevance to our study. Shanghai's extended control measures, broad coverage, and widespread impact on a substantial child and family population likely posed additional challenges to children’s mental health [ 7 ]. Additionally, Shanghai’s well-established pediatric mental health monitoring infrastructure enabled long-term, continuous tracking of children’s emotional and behavioral issues. Against this backdrop, this study provides a valuable opportunity to examine the dynamic changes in emotional and behavioral challenges faced by children with ADHD under high-intensity pandemic control measures, offering crucial insights for supportive strategies in similar scenarios. This study employs a longitudinal design to systematically track emotional and behavioral fluctuations among children with ADHD in Shanghai over 34 months of COVID-19 pandemic controls. By examining gender and ADHD subtype differences in these dynamics, this research also aims to identify high-risk groups and provide a scientific basis for targeted mental health interventions. Methods Study Design and Ethical Approval This study employed a longitudinal design with stratified random sampling, selecting one urban and one suburban district as sampling districts from the 16 administrative districts in Shanghai. The study recruited participants from January 31, 2020, to November 30th, 2020, and continued to follow up with the participants for 24 months, until December 15th, 2022. Ethical approval for the study was obtained from the Ethics Committee of Shanghai Children’s Hospital, Shanghai Jiao Tong University School of Medicine (Ethics Approval Number: 2020R031-E01), all methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from all participants' legal guardians [ 8 ]. Participants recruitment The selection encompassed all registered ADHD children in kindergartens, primary schools, and middle schools of the two chosen districts. To ensure sample representativeness, participants were recruited from multiple schools, covering diverse socioeconomic backgrounds. The inclusion criteria include: 1) ADHD Diagnosis: All children were diagnosed with ADHD by a licensed psychiatrist according to the criteria outlined in the Diagnostic and Statistical Manual of Mental Disorders , Fifth Edition (DSM-5) [ 9 ]; 2) Residency: Participants were required to reside within Shanghai and maintain a stable residence throughout the pandemic to ensure continuity of assessment. 3) Guardian Participation: At least one legal guardian was required to participate in all evaluation phases, providing background information and completing related questionnaires and scales on behalf of the child. If the children have one of the following conditions, they were excluded from this study: 1) Inconsistent Medication Use: Children who had not consistently used ADHD medication for at least three consecutive months prior to assessment were excluded to maintain consistency in treatment response[ 10 ]; 2) Residential Mobility: Children who moved outside of Shanghai or experienced significant residential changes during the study period were excluded to ensure data continuity and reliability. Follow-up and calendar time for analysis Given the varied enrollment times of the study participants, this study employed an event-based longitudinal design to track dynamic changes in individual emotional and behavioral outcomes during the COVID-19 period. Due to the evolving COVID-19 measures and the varying follow-up points for participants, combined with the fact that no interventions were administered to them, we used the calendar time from the enrollment of the first participant (January 31st, 2020) as the evaluation time, rather than the individual follow-up times of the participants. This will allow us to observe directly how the enrolled participants respond to the COVID-19 measures. Given the enrollment lasted for 10 months (January 31 to November 30, 2020), and the participants were followed at 6, 12, and 24 months after enrollment, with assessments conducted within a one-month window of these time points, the total calendar time included in this analysis is 34 months from the first enrollment. Measurements We collected basic demographic information and used the Conners Parent Rating Scale-Revised (CPRS-R) and the Vanderbilt ADHD Diagnostic Parent Rating Scale (VADPRS) to assess behavioral and emotional issues. The CPRS-R evaluated multiple behavioral domains, including conduct, learning issues, psychosomatic symptoms, impulsivity-hyperactivity, and anxiety. The CPRS-R and VADPRS assess symptom severity on continuous scales rather than providing diagnostic classifications for conditions such as anxiety or depression, limiting their ability to confirm clinical comorbidities.Each item on the CPRS-R was rated on a 4-point scale (0 = none to 3 = very severe), with scores above the mean by more than two standard deviations (X + 2SD) classified as abnormal [ 11 ]. The VADPRS assessed core ADHD symptoms—such as inattention, hyperactivity/impulsivity, and oppositional defiance—as well as conduct and emotional issues. Items were rated on a 4-point scale (0 = never to 3 = very often). ADHD symptoms were considered abnormal if inattention or hyperactivity/impulsivity scores were ≥ 13. Oppositional defiant disorder was considered abnormal if ≥ 4 items scored 2 or higher [ 12 ],conduct disorder if ≥ 3 items scored 2 or higher, and anxiety/depression if ≥ 3 items scored 2 or higher [ 12 ]. Both CPRS-R and VADPRS have been validated in Chinese populations. The Chinese version of the CPRS-R was adapted and validated by Su et al. (2001), demonstrating good reliability (Cronbach’s α = 0.85) and concurrent validity with clinical diagnoses in Chinese children with ADHD. Similarly, the VADPRS was translated and validated by Yang et al. (2013), showing high internal consistency (Cronbach’s α = 0.88) and sensitivity for detecting ADHD symptoms in Chinese school-aged children. These validations ensure their applicability in the current study. Both CPRS-R and VADPRS demonstrated high internal consistency (Cronbach’s α > 0.80) in this study, supporting their reliability for longitudinal analysis in ADHD research [ 13 , 14 , 36 , 37 ]. This study’s COVID-19 control periods are specifically defined as follows: Pandemic Control Phase: Encompasses all COVID-19-related home isolation and social distancing measures from January 31, 2020, when Shanghai first implemented COVID-19 prevention protocols, through December 15, 2022 [ 15 ]. During the Pandemic Control Phase, there are two important periods: 1) Lockdown Period: Refers to the strict home confinement measures enforced from March 28 to May 31, 2022, during which residents’ movement was highly restricted. These unique conditions in Shanghai provide a critical lens for understanding ADHD symptom trajectories under prolonged, high-intensity isolation [ 16 ]; 2)Reopening Phase: Begins from June 1 to December 15,2022, where gradual policy relaxation allowed for the return to regular social activities and public life. This phase was critical for observing ADHD children’s adaptation following extended isolation [ 17 ]. Data Analysis This study adopted a longitudinal research design wherein all participants underwent at least three assessments of emotional and behavioral changes between January 31, 2020, and December 15, 2022. Although participants enrolled at different times, the assessment intervals and frequencies were standardized for all participants.To accurately capture the nonlinear trends in emotional and behavioral problems among ADHD children during the pandemic, we employed the Generalized Additive Model (GAM) for analysis. GAM uses nonparametric smoothing functions (e.g., spline functions) to model the relationship between time and symptoms, with time included as a smoothed term and age as a covariate. The smoothing parameters were automatically selected via Generalized Cross-Validation (GCV), and the analysis was conducted using the “mgcv” package in R. GAM effectively captures the complex dynamic changes in emotional and behavioral problems through flexible smoothing functions, providing a more precise reflection of the pandemic's impact on ADHD children across different phases compared to linear models.To minimize bias from data loss, this study applied multiple imputation (MI) to manage missing values [ 18 ]. Additionally, to analyze intergroup differences at each time point, Tukey's Honestly Significant Difference (Tukey HSD) post hoc tests were conducted, with effect sizes reported to quantify the practical impact of observed differences and enhance result interpretation [ 19 ]. Subgroup analyses were conducted based on demographic characteristics (specifically, gender) and ADHD subtypes (predominantly inattentive ADHD-PI vs. hyperactive-impulsive ADHD-HI). The Generalized Additive Model (GAM) was applied to assess temporal dynamics in emotional and behavioral changes within each subgroup. Additionally, a one-way Analysis of Variance (ANOVA) was used to compare ADHD subtypes across various score dimensions at key time points during the Pandemic Control Phase (from January 31, 2020, through December 15, 2022), with F-statistics and p-values reported to determine the significance of observed differences. For statistically significant ANOVA results, post hoc tests (e.g., Tukey’s test) were performed to identify specific subgroup differences. This rigorous analytical approach enabled a detailed understanding of subgroup patterns, supporting evidence-based foundations for targeted intervention strategies. Results Baseline Characteristics Initially, 1,176 children diagnosed with ADHD were recruited for the study. After data screening and processing, 74 participants were excluded due to attrition or incomplete data, leaving a final sample of 1,102 children who completed all evaluations. These 1,102 participants completed the baseline assessment and were included in the final analysis. The ages of the included participants ranged from 4 to 16 years, with a mean age of 9.2 ± 2.4 years. The sample was predominantly male, with boys making up 83.0% of the participants.This gender distribution aligns with the epidemiological characteristics of ADHD, where prevalence is higher among boys than girls [ 5 ]. Regarding birth characteristics, the birth weights primarily fall within the 2500 to 4000-gram range (80.0%). Among the sample, 6.4% were classified as having low birth weight (< 2500 grams), while 13.6% had high birth weight (≥ 4000 grams). The maternal age at childbirth varied, with 69.8% of mothers being under 30 years of age at delivery, 24.1% between 30 and 35 years, and 6.1% aged over 35 years. The monthly household income levels showed that 12.3% earned 30,000 RMB. For ADHD subtype distribution, 49.5% of the children were diagnosed with the combined subtype, 44.1% with the predominantly inattentive subtype, and 6.4% with the hyperactive-impulsive subtype. Detailed demographic characteristics are provided in Table 1 . Changing of Emotional and Behavioral Issues Behavioral Peak in the Early Phase of the Pandemic This study found that during the early phase of COVID-19 pandemic control (around day 260 of isolation), ADHD children experienced significant peaks in behavioral problems, including attention deficits, hyperactivity/impulsivity, learning difficulties, and hyperactivity index scores (see Figs. 1 a, b, g, k). This pattern suggests that early in the pandemic, increased environmental stressors—such as school closures and disrupted social interactions—led to a marked exacerbation of behavioral issues in ADHD children[ 20 ]. However, as time passed, children gradually adapted to the COVID-19 measures, leading to a stabilization in behavioral problems. Unlike behavioral problems, emotional issues in ADHD children—such as anxiety and depression (see Figs. 1 e, h, j)—showed a dual-peak pattern, with two significant fluctuation peaks occurring during the early pandemic stage and around day 400 of isolation. To quantify these dynamics, we applied a Generalized Additive Model (GAM), which revealed a significant nonlinear effect of time on attention deficit symptoms (effective degrees of freedom [edf] = 11, p < 0.05), indicating complex temporal variations. Lockdown Resurgence in Emotional and Behavioral Problems After the full lifting of lockdown restrictions, children with ADHD demonstrated a pronounced resurgence in emotional and behavioral problems, evidenced by significant increases in hyperactivity/impulsivity, oppositional defiance, and anxiety/depression scores. This increase persisted over a prolonged period. The shift from prolonged isolation to normal social interactions appeared to intensify these difficulties, underscoring the urgent need for targeted interventions to support ADHD children through this critical adjustment phase. Gender and ADHD Subtype Differences The impact of gender and ADHD subtype on emotional and behavioral problems was notably significant. This study found that boys scored significantly higher than girls in behavioral dimensions such as hyperactivity/impulsivity, oppositional defiance, and conduct problems(Table 2 ), with this difference being particularly pronounced during the early pandemic control phase and post-lockdown phase (Figs. 1 b, c, d, f, i, k). Children with the predominantly inattentive subtype (ADHD-PI) had higher scores in emotional issues than those with the hyperactive-impulsive subtype (ADHD-HI), especially in areas of anxiety and depression (Table 3 ) (Figs. 2 e, j). In contrast, the ADHD-HI subtype exhibited significantly higher scores in hyperactivity/impulsivity, oppositional defiance, and other behavioral dimensions compared to ADHD-PI children (Table 3 ) (Figs. 2 a, b, c, d, f, g, h, i, k). Discussion Understanding how ADHD children respond to emerging public events is essential. This study employed an event-based longitudinal design to track dynamic changes in individual emotional and behavioral outcomes during COVID-19. It extends the existing literature by using a longitudinal study design, implementing an event-based data analysis strategy, and capturing the responses of different gender and ADHD subtypes. Emotional and behavioral issues in children with ADHD showed significant fluctuations during the pandemic, with emotional problems peaking early and around day 400, and behavioral issues worsening around day 260. After the lockdown, symptoms rebounded and persisted for a period. Boys exhibited higher behavioral scores, while ADHD-PI children had more emotional problems and ADHD-HI children showed more severe behavioral issues. We found that in the early phase of the pandemic, children with ADHD exhibited a significant increase in emotional issues, such as anxiety and depression. This finding aligns with results from Daly and Robinson (2020, 2021) in the U.S. and U.K., where children’s psychological distress peaked early in the pandemic (from mid-March to early April 2020) and gradually subsided as adaptation occurred[ 21 , 22 ]. However, our findings indicate a distinct pattern: while emotional issues peaked early in the pandemic, they resurfaced around day 400 due to the prolonged isolation period. Unlike Daly and Robinson’s observations, symptoms did not normalize post-lockdown but continued to rise. This difference may be attributed to China’s extended lockdown duration, cultural and social differences, and the stringency of control measures. Prolonged and strict restrictions likely reduced children’s adaptability over time, resulting in heightened anxiety and adjustment difficulties upon the sudden resumption of social and daily activities post-lockdown. These findings underscore the critical need for targeted emotional support during the initial phases of a pandemic or other public health emergencies, especially following the lifting of restrictions, to help children transition smoothly back to regular life [ 23 , 24 ]. Although several studies suggest that girls generally score higher on emotional issues while boys exhibit more behavioral problems, our study did not find significant gender differences in emotional issues, particularly in anxiety and depression scores. This outcome might reflect the widespread impact of prolonged pandemic restrictions on all children, which may have minimized gender differences. Consistent with existing literature, boys scored significantly higher on hyperactivity/impulsivity and oppositional defiant behaviors, especially during the initial lockdown and post-restriction periods[ 25 ]. In a public health context, these findings suggest a broad need for emotional support for all children under intense pandemic restrictions. Boys, in particular, may benefit from additional behavioral management strategies and emotional regulation support to help them better adjust to changes in daily life and alleviate the adverse effects of prolonged restrictions[ 26 ]. Significant differences were observed in the emotional and behavioral problems exhibited by children with different ADHD subtypes. These findings underscore the significant differences in how various ADHD subtypes respond to environmental changes, which hold profound implications for the development of clinical interventions and treatment strategies. The results highlight the necessity of tailoring ADHD treatment based on subtype-specific characteristics to more accurately address the unique challenges each subtype faces in emotional and behavioral regulation. This evidence strongly supports the critical role of personalized medicine in ADHD treatment, especially in contexts involving complex environmental changes or prolonged stressors, such as a pandemic. Such individualized approaches not only enhance intervention efficacy but also contribute to the overall improvement of quality of life for both children and their families [ 27 , 28 ]. This study provides critical insights into the care and intervention of children with ADHD during emergency situations. Timely psychological interventions are essential during the early stages of a pandemic or prolonged crises to help ADHD children adapt to environmental changes. These interventions should include emotional support, behavior management, and family education to mitigate emotional fluctuations and reduce behavioral dysregulation[ 29 ]. Tailored strategies based on ADHD subtypes and gender differences can further enhance treatment precision and efficacy. For instance, children with the predominantly inattentive subtype (ADHD-PI) require emotional regulation support, including anxiety management, emotion recognition, emotional expression, and positive psychology training[ 30 ], while those with the hyperactive/impulsive subtype (ADHD-HI) benefit more from intensive behavior management strategies, such as behavior modification and impulse control techniques[ 27 ]. Boys may need a combined approach of behavior management and emotional regulation support, particularly during the post-lockdown period, to adapt to rapid changes in daily routines and social activities. Additionally, the significant increase in emotional and behavioral problems during the post-lockdown transition—particularly in areas such as anxiety and depression—emphasizes the importance of comprehensive psychological support and gradual reintroduction to social activities and academic demands. This should be supplemented with psychological counseling, behavior training, and social skills development. Integrating efforts from families, schools, and broader social systems is crucial for building a robust support network that provides sustained care and helps ADHD children transition smoothly from pandemic-related disruptions to regular social environments, ultimately enhancing their adaptive capacity and quality of life[ 31 , 32 ]. Compared to neurotypical children, ADHD children may exhibit greater vulnerability to the effects of prolonged COVID-19 restrictions. This heightened susceptibility could stem from neurobiological factors, such as deficits in executive functioning and emotional dysregulation, which are core features of ADHD. For instance, impaired prefrontal cortex activity and altered dopamine regulation may limit their ability to adapt to abrupt environmental shifts, such as those imposed by lockdowns, leading to exacerbated behavioral and emotional challenges. Additionally, their reliance on structured routines—disrupted during the pandemic—may further amplify stress responses. Supporting evidence from prior research suggests that children with ADHD experience more pronounced psychological distress under stress compared to their neurotypical peers [ 34 , 35 ]. However, without a control group in this study, we cannot definitively attribute these changes solely to ADHD, highlighting a key limitation that warrants further investigation. Despite revealing dynamic changes in emotional and behavioral problems among ADHD children during prolonged COVID-19 control measures, this study has several limitations. First, the study was conducted solely on ADHD children in the Shanghai region, which may have limited the representative of the study. Caution is needed when generalizing these findings to other regions or countries, as variations in social and cultural backgrounds, pandemic control policies, and healthcare resources may influence child mental health differently[ 33 ]. Second, this study primarily relies on parental self-reports to assess children's emotional and behavioral issues. Although the employed assessment tools exhibit high reliability and validity, there remains a possibility of subjective bias in the data. Moreover, the influence of caregivers during the lockdown period may have affected these reports. The necessity for caregivers to provide constant supervision during Shanghai’s stringent lockdown likely increased their stress levels, potentially skewing their perceptions and overestimating symptom severity in their children. This caregiver burden could introduce additional bias into the study outcomes, suggesting that future research should incorporate assessments of caregiver mental health to better contextualize parental reports.Third,,the lack of detailed subgroup analyses by socioeconomic status (SES) and age restricts our ability to explore differential patterns across these factors. Although SES (proxied by categorical household income) and age were included as fixed effects, the absence of a continuous SES metric and the uneven age distribution (e.g., 69.8% in the 6–10 years group) precluded robust subgroup comparisons. Given evidence that socioeconomic disadvantage and developmental stage may influence ADHD outcomes [ 39 ], future studies with more granular SES data (e.g., composite indices) and balanced age cohorts are needed. Finally, the absence of mediation or moderation analyses limits our understanding of whether ADHD symptom severity directly influences emotional and behavioral fluctuations. Such analyses could elucidate underlying mechanisms and should be considered in subsequent studies." Conclusion Through a long-term longitudinal tracking approach, this study highlights the dynamic changes in emotional and behavioral problems experienced by ADHD children during the COVID-19 pandemic control and post-lockdown phases. The findings indicate that prolonged control measures pose significant challenges to emotional regulation in ADHD children, with adaptive demands increasing post-lockdown. Personalized interventions tailored to the specific pandemic phase, gender, and ADHD subtype can help alleviate adaptive stress. Notably, providing continuous support during the post-lockdown period and the gradual return to social norms may help ADHD children better adapt to environmental changes, ultimately supporting stable mental health development.This study is the first to reveal the dynamic emotional and behavioral changes in ADHD children under prolonged pandemic controls, providing a scientific basis for developing targeted psychological interventions, particularly to safeguard their mental health during public health crises. Declarations Author Contribution XQ, QZ, and WT conceived the research ideas with input from JC; XQ, DZ, XF, YH, XC, SW, and AA collected the data; XQ, WT, and HL performed the data analysis and checked the data analysis; and XQ, DZ, and WT drafted the manuscript, with inputs from XF, YH, XC, SW, AA, JZ, XH, HL, and JC. 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M., Vitiello, B., Plener, P. L. & Clemens, V. The impact of COVID-19 on child and adolescent mental health: A review of the literature. Int. J. Environ. Res. Public Health . 17 (14), 4360. https://doi.org/10.3390/ijerph17144360 (2020). Becker, S. P. et al. Longitudinal effects of COVID-19 on youth mental health: A review of the literature. Psychiatry Research, 291, 113221. https://doi.org/10.1016/j.psychres.2020.113221, & et al. (2020). The psychological impact of quarantine and how to reduce it: A review of the literature. The Lancet, 395(10227), 1124–1132. https://doi.org/10.1016/S0140-6736(20)30460-8 (2020). Zhou, X., Zhang, H. & Li, X. Psychological impact of the COVID-19 pandemic on adolescents in Shanghai. Frontiers in Psychology, 11, 2035. (2020). https://doi.org/10.3389/fpsyg.2020.02035 Ghosh, R., Dubey, M. J., Chatterjee, S. & Dubey, S. Impact of COVID-19 on children: special focus on the psychosocial aspect. Minerva Pediatr. 72 (3), 226–235 (2020). Morelli, M. et al. Parents and Children During the COVID-19 Lockdown: The Influence of Parenting Distress and Parenting Self-Efficacy on Children's Emotional Well-Being. Front. Psychol. 11 , 584645 (2020). Mojtahedi, D. et al. The Relationship Between Mental Toughness, Job Loss, and Mental Health Issues During the COVID-19 Pandemic. Front. Psychiatry (2020). Spinelli, M., Lionetti, F., Pastore, M. & Fasolo, M. Parents' Stress and Children's Psychological Problems in Families Facing the COVID-19 Outbreak in Italy. Front. Psychol. 11 , 1713 (2020). Su, L. Y., Yang, Z. W. & Bao, X. L. Reliability and validity of the Chinese version of Conners’Parent Rating Scale-Revised in children with ADHD. Chin. J. Clin. Psychol. 9 (3), 176–179 (2001). Yang, L., Wang, Y. F. & Qian, Q. J. Validation of the Chinese version of the Vanderbilt ADHD Diagnostic Parent Rating Scale in a community sample. Chin. Mental Health J. 27 (5), 345–350 (2013). Biederman, J., Newcorn, J. & Sprich, S. 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Tables Table 1 Summary of Baseline Characteristics of Children with ADHD in Shanghai During COVID-19 Control Measures (N=1102) Variable Category Count Proportion (%) Age 6 to 10 years 769 69.8 10 to 16 years 213 19.3 4 to 6 years 117 10.6 Gender Male 915 83.0 Female 187 17.0 Gestational Age (weeks) 37 to 42 weeks 1020 92.6 <37 weeks 64 5.8 ≥42 weeks 18 1.6 Birth Weight (grams) 2500 to 4000 grams 882 80.0 ≥4000 grams 150 13.6 <2500 grams 70 6.4 Maternal Age at Birth <30 years 769 69.8 30 to 35 years 266 24.1 ≥35 years 67 6.1 ADHD Subtype mixed 545 49.5 attention deficit 486 44.1 hyperactive-impulsive 71 6.4 Wechsler Intelligence 90 to 110 530 48.1 70 to 90 356 32.3 ≥110 179 16.2 30000 106 9.6 Table 2, Differences in Average Scores across Emotional and Behavioral Dimensions among ADHD Children in Shanghai during the Pandemic Control Phase (n=1102) Dimension Male Mean (n=915) (SD) Female Mean (n=187) (SD) P-Value Attention Deficit (Total Score) 14.54 (5.28) 14.30 (4.99) 0.35 Hyperactivity-Impulsivity (Total Score) 11.14 (5.73) 9.21 (5.12) <0.001 Oppositional Defiance (Total Score) 8.04 (4.76) 7.17 (4.50) <0.001 Conduct Disorder (Total Score) 2.19 (2.81) 1.35 (1.52) <0.001 Anxiety-Depression (Total Score) 3.52 (3.35) 3.25 (3.27) 0.10 Conduct Problems (Average Score) 0.73 (0.46) 0.65 (0.41) <0.001 Learning Problems (Average Score) 1.53 (0.62) 1.51 (0.61) 0.62 Psychosomatic Disorders (Average Score) 0.19 (0.29) 0.16 (0.22) 0.04 Impulsivity-Hyperactivity (Average Score) 1.22 (0.68) 1.06 (0.63) <0.001 Anxiety (Average Score) 0.45 (0.43) 0.45 (0.43) 0.68 Hyperactivity Index (Average Score) 1.10 (0.52) 0.99 (0.47) <0.001 Table 3, Differences in Average Scores across Emotional and Behavioral Dimensions among ADHD Subtypes in Shanghai during the Pandemic Control Phase (n=1102) Dimension Attention Deficit Mean (SD) Hyperactivity-Impulsivity Mean (SD) Combined Type Mean (SD) Attention Deficit Sample Size Hyperactivity-Impulsivity Sample Size Combined Type Sample Size P-Value Attention Deficit (Total Score) 15.27 (5.04) 12.06 (4.89) 14.15 (5.32) 486 71 545 <0.001 Hyperactivity-Impulsivity (Total Score) 7.89 (4.05) 17.05 (5.44) 12.73 (5.37) 486 71 545 <0.001 Oppositional Defiance (Total Score) 6.99 (4.40) 9.55 (5.38) 8.55 (4.72) 486 71 545 <0.001 Conduct Disorder (Total Score) 1.58 (1.90) 3.16 (3.47) 2.33 (3.03) 486 71 545 <0.001 Anxiety-Depression (Total Score) 3.75 (3.45) 2.81 (3.05) 3.32 (3.24) 486 71 545 <0.001 Conduct Problems (Average Score) 0.63 (0.42) 0.84 (0.50) 0.79 (0.46) 486 71 545 <0.001 Learning Problems (Average Score) 1.57 (0.62) 1.38 (0.60) 1.51 (0.61) 486 71 545 <0.001 Learning Problems (Average Score) 0.17 (0.26) 0.17 (0.29) 0.19 (0.29) 486 71 545 0.31 Impulsivity-Hyperactivity (Average Score) 0.99 (0.62) 1.56 (0.70) 1.34 (0.65) 486 71 545 <0.001 Anxiety (Average Score) 0.48 (0.44) 0.38 (0.43) 0.44 (0.42) 486 71 545 <0.001 Hyperactivity Index (Average Score) 0.98 (0.48) 1.24 (0.53) 1.16 (0.52) 486 71 545 <0.001 Additional Declarations No competing interests reported. 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Chen","email":"","orcid":"","institution":"Department of Child Health Care, Shanghai Children’s Hospital, School of medicine, Shanghai Jiao Tong University","correspondingAuthor":false,"prefix":"","firstName":"Jinjin","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-12-23 23:08:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5702346/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5702346/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-02254-x","type":"published","date":"2025-06-26T15:57:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80577965,"identity":"a210e742-e9f2-40ea-a55e-71396fcf746d","added_by":"auto","created_at":"2025-04-14 23:00:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":310146,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEmotional and Behavioral Changes across Dimensions among ADHD Children in Shanghai during the Pandemic Control Phase (by Gender) (n=1102),Shaded areas represent 95% confidence intervals derived from GAM analysis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5702346/v1/8e9029bad5286704eb5f981b.png"},{"id":80581930,"identity":"25920679-8765-4907-bd72-d5e363401816","added_by":"auto","created_at":"2025-04-14 23:24:23","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":317995,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEmotional and Behavioral Changes across Dimensions among ADHD Subtypes in Shanghai during the Pandemic Control Phase (n=1102),Shaded areas represent 95% confidence intervals derived from GAM analysis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5702346/v1/f4bf451b41cf9dd58ce45ad3.png"},{"id":85686180,"identity":"2071db80-d03b-41b3-b9c0-efb11289e038","added_by":"auto","created_at":"2025-06-30 16:04:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1719699,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5702346/v1/88fb18d9-5aec-498c-a052-a73036a1fc52.pdf"},{"id":80580747,"identity":"a6c3f1a1-1fa5-4787-96b4-0a8d656e7663","added_by":"auto","created_at":"2025-04-14 23:16:23","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":393896,"visible":true,"origin":"","legend":"","description":"","filename":"Data.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-5702346/v1/92f6198bf31eb2d8533fd310.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Longitudinal Patterns of Attention-Deficit/Hyperactivity Disorder Children in Shanghai, China","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAttention Deficit Hyperactivity Disorder (ADHD) is one of the most prevalent neurodevelopmental disorders among children worldwide, with an estimated prevalence of around 5% [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].Core symptoms include inattention, hyperactivity, and impulsivity, often accompanied by elevated levels of anxiety and depressive symptoms, which are commonly observed in ADHD populations and may reflect co-occurring emotional difficulties rather than being exclusively intrinsic to ADHD itself [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Studies indicate that children with ADHD are particularly susceptible to the effects of stress, especially when faced with major life events or public health crises. These events and the associated preventive measures can have a pronounced impact on their emotional and behavioral states [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Compared to their peers, children with ADHD encounter greater difficulties in emotional regulation and behavioral control, with such challenges often intensifying in the context of substantial life changes. For example, the COVID-19 pandemic may have a substantial impact on children with ADHD, especially those directly affected by COVID-19 measures (i.e., lockdown) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These measures may exacerbate mental health issues, leading to increased fluctuations in emotional and behavioral outcomes. However, research examining the dynamic emotional and behavioral changes in children with ADHD under prolonged COVID-19 measures remains limited[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].This study aims to address this gap by assessing the dynamic changes in emotional and behavioral problems among children with ADHD during the COVID-19 pandemic and exploring differences by gender and ADHD subtype. We hypothesize that emotional and behavioral problems in ADHD children will intensify during the early pandemic and post-lockdown phases, with significant variations across gender and ADHD subtypes.\u003c/p\u003e \u003cp\u003eAs the COVID-19 pandemic has persisted, extended periods of confinement, heightened social restrictions, and ongoing uncertainties about the future have presented children with ADHD with increasingly intensified challenges in emotional regulation, potentially exacerbating anxiety and other emotional disorders [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Existing research has shown that abrupt environmental changes and prolonged stressors contribute to greater emotional instability and elevated anxiety levels in children with ADHD [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, there is a marked lack of longitudinal cohort studies that track the temporal dynamics of emotional and behavioral difficulties among this population under prolonged public health restrictions. Longitudinal studies are essential as they can elucidate the progression of emotional and behavioral issues over time under sustained stress, identifying critical high-risk periods and cumulative effects that cross-sectional studies cannot capture. This study provides a unique contribution by conducting a prospective cohort study to systematically evaluate the shifts in emotional and behavioral patterns among children with ADHD across various stages of pandemic control measures. By offering data from this extended period, the study lays a scientific foundation for developing phase-specific, personalized support strategies.\u003c/p\u003e \u003cp\u003eShanghai, China presents a unique case globally, as one of the few cities that experienced over two months of stringent lockdown, during which residents\u0026rsquo; outdoor activities were highly restricted. This distinctive context offers significant scientific relevance to our study. Shanghai's extended control measures, broad coverage, and widespread impact on a substantial child and family population likely posed additional challenges to children\u0026rsquo;s mental health [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Additionally, Shanghai\u0026rsquo;s well-established pediatric mental health monitoring infrastructure enabled long-term, continuous tracking of children\u0026rsquo;s emotional and behavioral issues. Against this backdrop, this study provides a valuable opportunity to examine the dynamic changes in emotional and behavioral challenges faced by children with ADHD under high-intensity pandemic control measures, offering crucial insights for supportive strategies in similar scenarios.\u003c/p\u003e \u003cp\u003eThis study employs a longitudinal design to systematically track emotional and behavioral fluctuations among children with ADHD in Shanghai over 34 months of COVID-19 pandemic controls. By examining gender and ADHD subtype differences in these dynamics, this research also aims to identify high-risk groups and provide a scientific basis for targeted mental health interventions.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Ethical Approval\u003c/h2\u003e \u003cp\u003eThis study employed a longitudinal design with stratified random sampling, selecting one urban and one suburban district as sampling districts from the 16 administrative districts in Shanghai. The study recruited participants from January 31, 2020, to November 30th, 2020, and continued to follow up with the participants for 24 months, until December 15th, 2022. Ethical approval for the study was obtained from the Ethics Committee of Shanghai Children\u0026rsquo;s Hospital, Shanghai Jiao Tong University School of Medicine (Ethics Approval Number: 2020R031-E01), all methods were performed in accordance with the relevant guidelines and regulations. Written informed consent was obtained from all participants' legal guardians [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants recruitment\u003c/h3\u003e\n\u003cp\u003eThe selection encompassed all registered ADHD children in kindergartens, primary schools, and middle schools of the two chosen districts. To ensure sample representativeness, participants were recruited from multiple schools, covering diverse socioeconomic backgrounds. The inclusion criteria include: 1) ADHD Diagnosis: All children were diagnosed with ADHD by a licensed psychiatrist according to the criteria outlined in the \u003cem\u003eDiagnostic and Statistical Manual of Mental Disorders\u003c/em\u003e, Fifth Edition (DSM-5) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]; 2) Residency: Participants were required to reside within Shanghai and maintain a stable residence throughout the pandemic to ensure continuity of assessment. 3) Guardian Participation: At least one legal guardian was required to participate in all evaluation phases, providing background information and completing related questionnaires and scales on behalf of the child. If the children have one of the following conditions, they were excluded from this study: 1) Inconsistent Medication Use: Children who had not consistently used ADHD medication for at least three consecutive months prior to assessment were excluded to maintain consistency in treatment response[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]; 2) Residential Mobility: Children who moved outside of Shanghai or experienced significant residential changes during the study period were excluded to ensure data continuity and reliability.\u003c/p\u003e\n\u003ch3\u003eFollow-up and calendar time for analysis\u003c/h3\u003e\n\u003cp\u003eGiven the varied enrollment times of the study participants, this study employed an event-based longitudinal design to track dynamic changes in individual emotional and behavioral outcomes during the COVID-19 period. Due to the evolving COVID-19 measures and the varying follow-up points for participants, combined with the fact that no interventions were administered to them, we used the calendar time from the enrollment of the first participant (January 31st, 2020) as the evaluation time, rather than the individual follow-up times of the participants. This will allow us to observe directly how the enrolled participants respond to the COVID-19 measures. Given the enrollment lasted for 10 months (January 31 to November 30, 2020), and the participants were followed at 6, 12, and 24 months after enrollment, with assessments conducted within a one-month window of these time points, the total calendar time included in this analysis is 34 months from the first enrollment.\u003c/p\u003e\n\u003ch3\u003eMeasurements\u003c/h3\u003e\n\u003cp\u003eWe collected basic demographic information and used the Conners Parent Rating Scale-Revised (CPRS-R) and the Vanderbilt ADHD Diagnostic Parent Rating Scale (VADPRS) to assess behavioral and emotional issues. The CPRS-R evaluated multiple behavioral domains, including conduct, learning issues, psychosomatic symptoms, impulsivity-hyperactivity, and anxiety. The CPRS-R and VADPRS assess symptom severity on continuous scales rather than providing diagnostic classifications for conditions such as anxiety or depression, limiting their ability to confirm clinical comorbidities.Each item on the CPRS-R was rated on a 4-point scale (0\u0026thinsp;=\u0026thinsp;none to 3\u0026thinsp;=\u0026thinsp;very severe), with scores above the mean by more than two standard deviations (X\u0026thinsp;+\u0026thinsp;2SD) classified as abnormal [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The VADPRS assessed core ADHD symptoms\u0026mdash;such as inattention, hyperactivity/impulsivity, and oppositional defiance\u0026mdash;as well as conduct and emotional issues. Items were rated on a 4-point scale (0\u0026thinsp;=\u0026thinsp;never to 3\u0026thinsp;=\u0026thinsp;very often). ADHD symptoms were considered abnormal if inattention or hyperactivity/impulsivity scores were \u0026ge;\u0026thinsp;13. Oppositional defiant disorder was considered abnormal if\u0026thinsp;\u0026ge;\u0026thinsp;4 items scored 2 or higher [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e],conduct disorder if\u0026thinsp;\u0026ge;\u0026thinsp;3 items scored 2 or higher, and anxiety/depression if\u0026thinsp;\u0026ge;\u0026thinsp;3 items scored 2 or higher [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Both CPRS-R and VADPRS have been validated in Chinese populations. The Chinese version of the CPRS-R was adapted and validated by Su et al. (2001), demonstrating good reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.85) and concurrent validity with clinical diagnoses in Chinese children with ADHD. Similarly, the VADPRS was translated and validated by Yang et al. (2013), showing high internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.88) and sensitivity for detecting ADHD symptoms in Chinese school-aged children. These validations ensure their applicability in the current study. Both CPRS-R and VADPRS demonstrated high internal consistency (Cronbach\u0026rsquo;s α\u0026thinsp;\u0026gt;\u0026thinsp;0.80) in this study, supporting their reliability for longitudinal analysis in ADHD research [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study\u0026rsquo;s COVID-19 control periods are specifically defined as follows: Pandemic Control Phase: Encompasses all COVID-19-related home isolation and social distancing measures from January 31, 2020, when Shanghai first implemented COVID-19 prevention protocols, through December 15, 2022 [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. During the Pandemic Control Phase, there are two important periods: 1) Lockdown Period: Refers to the strict home confinement measures enforced from March 28 to May 31, 2022, during which residents\u0026rsquo; movement was highly restricted. These unique conditions in Shanghai provide a critical lens for understanding ADHD symptom trajectories under prolonged, high-intensity isolation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]; 2)Reopening Phase: Begins from June 1 to December 15,2022, where gradual policy relaxation allowed for the return to regular social activities and public life. This phase was critical for observing ADHD children\u0026rsquo;s adaptation following extended isolation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThis study adopted a longitudinal research design wherein all participants underwent at least three assessments of emotional and behavioral changes between January 31, 2020, and December 15, 2022. Although participants enrolled at different times, the assessment intervals and frequencies were standardized for all participants.To accurately capture the nonlinear trends in emotional and behavioral problems among ADHD children during the pandemic, we employed the Generalized Additive Model (GAM) for analysis. GAM uses nonparametric smoothing functions (e.g., spline functions) to model the relationship between time and symptoms, with time included as a smoothed term and age as a covariate. The smoothing parameters were automatically selected via Generalized Cross-Validation (GCV), and the analysis was conducted using the \u0026ldquo;mgcv\u0026rdquo; package in R.\u003c/p\u003e \u003cp\u003eGAM effectively captures the complex dynamic changes in emotional and behavioral problems through flexible smoothing functions, providing a more precise reflection of the pandemic's impact on ADHD children across different phases compared to linear models.To minimize bias from data loss, this study applied multiple imputation (MI) to manage missing values [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Additionally, to analyze intergroup differences at each time point, Tukey's Honestly Significant Difference (Tukey HSD) post hoc tests were conducted, with effect sizes reported to quantify the practical impact of observed differences and enhance result interpretation [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSubgroup analyses were conducted based on demographic characteristics (specifically, gender) and ADHD subtypes (predominantly inattentive ADHD-PI vs. hyperactive-impulsive ADHD-HI). The Generalized Additive Model (GAM) was applied to assess temporal dynamics in emotional and behavioral changes within each subgroup. Additionally, a one-way Analysis of Variance (ANOVA) was used to compare ADHD subtypes across various score dimensions at key time points during the Pandemic Control Phase (from January 31, 2020, through December 15, 2022), with F-statistics and p-values reported to determine the significance of observed differences. For statistically significant ANOVA results, post hoc tests (e.g., Tukey\u0026rsquo;s test) were performed to identify specific subgroup differences. This rigorous analytical approach enabled a detailed understanding of subgroup patterns, supporting evidence-based foundations for targeted intervention strategies.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eInitially, 1,176 children diagnosed with ADHD were recruited for the study. After data screening and processing, 74 participants were excluded due to attrition or incomplete data, leaving a final sample of 1,102 children who completed all evaluations. These 1,102 participants completed the baseline assessment and were included in the final analysis. The ages of the included participants ranged from 4 to 16 years, with a mean age of 9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 years. The sample was predominantly male, with boys making up 83.0% of the participants.This gender distribution aligns with the epidemiological characteristics of ADHD, where prevalence is higher among boys than girls [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Regarding birth characteristics, the birth weights primarily fall within the 2500 to 4000-gram range (80.0%). Among the sample, 6.4% were classified as having low birth weight (\u0026lt;\u0026thinsp;2500 grams), while 13.6% had high birth weight (\u0026ge;\u0026thinsp;4000 grams). The maternal age at childbirth varied, with 69.8% of mothers being under 30 years of age at delivery, 24.1% between 30 and 35 years, and 6.1% aged over 35 years. The monthly household income levels showed that 12.3% earned\u0026thinsp;\u0026lt;\u0026thinsp;5000 RMB, 39.1% earned 5000\u0026ndash;10,000 RMB, 39.0% earned 10,000\u0026ndash;30,000 RMB, and 9.6% earned\u0026thinsp;\u0026gt;\u0026thinsp;30,000 RMB.\u003c/p\u003e \u003cp\u003eFor ADHD subtype distribution, 49.5% of the children were diagnosed with the combined subtype, 44.1% with the predominantly inattentive subtype, and 6.4% with the hyperactive-impulsive subtype. Detailed demographic characteristics are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eChanging of Emotional and Behavioral Issues\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBehavioral Peak in the Early Phase of the Pandemic\u003c/h2\u003e \u003cp\u003eThis study found that during the early phase of COVID-19 pandemic control (around day 260 of isolation), ADHD children experienced significant peaks in behavioral problems, including attention deficits, hyperactivity/impulsivity, learning difficulties, and hyperactivity index scores (see Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, b, g, k). This pattern suggests that early in the pandemic, increased environmental stressors\u0026mdash;such as school closures and disrupted social interactions\u0026mdash;led to a marked exacerbation of behavioral issues in ADHD children[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, as time passed, children gradually adapted to the COVID-19 measures, leading to a stabilization in behavioral problems. Unlike behavioral problems, emotional issues in ADHD children\u0026mdash;such as anxiety and depression (see Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ee, h, j)\u0026mdash;showed a dual-peak pattern, with two significant fluctuation peaks occurring during the early pandemic stage and around day 400 of isolation. To quantify these dynamics, we applied a Generalized Additive Model (GAM), which revealed a significant nonlinear effect of time on attention deficit symptoms (effective degrees of freedom [edf]\u0026thinsp;=\u0026thinsp;11, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), indicating complex temporal variations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLockdown Resurgence in Emotional and Behavioral Problems\u003c/h2\u003e \u003cp\u003eAfter the full lifting of lockdown restrictions, children with ADHD demonstrated a pronounced resurgence in emotional and behavioral problems, evidenced by significant increases in hyperactivity/impulsivity, oppositional defiance, and anxiety/depression scores. This increase persisted over a prolonged period. The shift from prolonged isolation to normal social interactions appeared to intensify these difficulties, underscoring the urgent need for targeted interventions to support ADHD children through this critical adjustment phase.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eGender and ADHD Subtype Differences\u003c/h2\u003e \u003cp\u003eThe impact of gender and ADHD subtype on emotional and behavioral problems was notably significant. This study found that boys scored significantly higher than girls in behavioral dimensions such as hyperactivity/impulsivity, oppositional defiance, and conduct problems(Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with this difference being particularly pronounced during the early pandemic control phase and post-lockdown phase (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, c, d, f, i, k). Children with the predominantly inattentive subtype (ADHD-PI) had higher scores in emotional issues than those with the hyperactive-impulsive subtype (ADHD-HI), especially in areas of anxiety and depression (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee, j). In contrast, the ADHD-HI subtype exhibited significantly higher scores in hyperactivity/impulsivity, oppositional defiance, and other behavioral dimensions compared to ADHD-PI children (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, b, c, d, f, g, h, i, k).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUnderstanding how ADHD children respond to emerging public events is essential. This study employed an event-based longitudinal design to track dynamic changes in individual emotional and behavioral outcomes during COVID-19. It extends the existing literature by using a longitudinal study design, implementing an event-based data analysis strategy, and capturing the responses of different gender and ADHD subtypes. Emotional and behavioral issues in children with ADHD showed significant fluctuations during the pandemic, with emotional problems peaking early and around day 400, and behavioral issues worsening around day 260. After the lockdown, symptoms rebounded and persisted for a period. Boys exhibited higher behavioral scores, while ADHD-PI children had more emotional problems and ADHD-HI children showed more severe behavioral issues.\u003c/p\u003e \u003cp\u003eWe found that in the early phase of the pandemic, children with ADHD exhibited a significant increase in emotional issues, such as anxiety and depression. This finding aligns with results from Daly and Robinson (2020, 2021) in the U.S. and U.K., where children\u0026rsquo;s psychological distress peaked early in the pandemic (from mid-March to early April 2020) and gradually subsided as adaptation occurred[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, our findings indicate a distinct pattern: while emotional issues peaked early in the pandemic, they resurfaced around day 400 due to the prolonged isolation period. Unlike Daly and Robinson\u0026rsquo;s observations, symptoms did not normalize post-lockdown but continued to rise. This difference may be attributed to China\u0026rsquo;s extended lockdown duration, cultural and social differences, and the stringency of control measures. Prolonged and strict restrictions likely reduced children\u0026rsquo;s adaptability over time, resulting in heightened anxiety and adjustment difficulties upon the sudden resumption of social and daily activities post-lockdown. These findings underscore the critical need for targeted emotional support during the initial phases of a pandemic or other public health emergencies, especially following the lifting of restrictions, to help children transition smoothly back to regular life [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough several studies suggest that girls generally score higher on emotional issues while boys exhibit more behavioral problems, our study did not find significant gender differences in emotional issues, particularly in anxiety and depression scores. This outcome might reflect the widespread impact of prolonged pandemic restrictions on all children, which may have minimized gender differences. Consistent with existing literature, boys scored significantly higher on hyperactivity/impulsivity and oppositional defiant behaviors, especially during the initial lockdown and post-restriction periods[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In a public health context, these findings suggest a broad need for emotional support for all children under intense pandemic restrictions. Boys, in particular, may benefit from additional behavioral management strategies and emotional regulation support to help them better adjust to changes in daily life and alleviate the adverse effects of prolonged restrictions[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSignificant differences were observed in the emotional and behavioral problems exhibited by children with different ADHD subtypes. These findings underscore the significant differences in how various ADHD subtypes respond to environmental changes, which hold profound implications for the development of clinical interventions and treatment strategies. The results highlight the necessity of tailoring ADHD treatment based on subtype-specific characteristics to more accurately address the unique challenges each subtype faces in emotional and behavioral regulation. This evidence strongly supports the critical role of personalized medicine in ADHD treatment, especially in contexts involving complex environmental changes or prolonged stressors, such as a pandemic. Such individualized approaches not only enhance intervention efficacy but also contribute to the overall improvement of quality of life for both children and their families [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study provides critical insights into the care and intervention of children with ADHD during emergency situations. Timely psychological interventions are essential during the early stages of a pandemic or prolonged crises to help ADHD children adapt to environmental changes. These interventions should include emotional support, behavior management, and family education to mitigate emotional fluctuations and reduce behavioral dysregulation[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Tailored strategies based on ADHD subtypes and gender differences can further enhance treatment precision and efficacy. For instance, children with the predominantly inattentive subtype (ADHD-PI) require emotional regulation support, including anxiety management, emotion recognition, emotional expression, and positive psychology training[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], while those with the hyperactive/impulsive subtype (ADHD-HI) benefit more from intensive behavior management strategies, such as behavior modification and impulse control techniques[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Boys may need a combined approach of behavior management and emotional regulation support, particularly during the post-lockdown period, to adapt to rapid changes in daily routines and social activities. Additionally, the significant increase in emotional and behavioral problems during the post-lockdown transition\u0026mdash;particularly in areas such as anxiety and depression\u0026mdash;emphasizes the importance of comprehensive psychological support and gradual reintroduction to social activities and academic demands. This should be supplemented with psychological counseling, behavior training, and social skills development. Integrating efforts from families, schools, and broader social systems is crucial for building a robust support network that provides sustained care and helps ADHD children transition smoothly from pandemic-related disruptions to regular social environments, ultimately enhancing their adaptive capacity and quality of life[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCompared to neurotypical children, ADHD children may exhibit greater vulnerability to the effects of prolonged COVID-19 restrictions. This heightened susceptibility could stem from neurobiological factors, such as deficits in executive functioning and emotional dysregulation, which are core features of ADHD. For instance, impaired prefrontal cortex activity and altered dopamine regulation may limit their ability to adapt to abrupt environmental shifts, such as those imposed by lockdowns, leading to exacerbated behavioral and emotional challenges. Additionally, their reliance on structured routines\u0026mdash;disrupted during the pandemic\u0026mdash;may further amplify stress responses. Supporting evidence from prior research suggests that children with ADHD experience more pronounced psychological distress under stress compared to their neurotypical peers [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. However, without a control group in this study, we cannot definitively attribute these changes solely to ADHD, highlighting a key limitation that warrants further investigation.\u003c/p\u003e \u003cp\u003eDespite revealing dynamic changes in emotional and behavioral problems among ADHD children during prolonged COVID-19 control measures, this study has several limitations. First, the study was conducted solely on ADHD children in the Shanghai region, which may have limited the representative of the study. Caution is needed when generalizing these findings to other regions or countries, as variations in social and cultural backgrounds, pandemic control policies, and healthcare resources may influence child mental health differently[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Second, this study primarily relies on parental self-reports to assess children's emotional and behavioral issues. Although the employed assessment tools exhibit high reliability and validity, there remains a possibility of subjective bias in the data. Moreover, the influence of caregivers during the lockdown period may have affected these reports. The necessity for caregivers to provide constant supervision during Shanghai\u0026rsquo;s stringent lockdown likely increased their stress levels, potentially skewing their perceptions and overestimating symptom severity in their children. This caregiver burden could introduce additional bias into the study outcomes, suggesting that future research should incorporate assessments of caregiver mental health to better contextualize parental reports.Third,,the lack of detailed subgroup analyses by socioeconomic status (SES) and age restricts our ability to explore differential patterns across these factors. Although SES (proxied by categorical household income) and age were included as fixed effects, the absence of a continuous SES metric and the uneven age distribution (e.g., 69.8% in the 6\u0026ndash;10 years group) precluded robust subgroup comparisons. Given evidence that socioeconomic disadvantage and developmental stage may influence ADHD outcomes [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], future studies with more granular SES data (e.g., composite indices) and balanced age cohorts are needed. Finally, the absence of mediation or moderation analyses limits our understanding of whether ADHD symptom severity directly influences emotional and behavioral fluctuations. Such analyses could elucidate underlying mechanisms and should be considered in subsequent studies.\"\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThrough a long-term longitudinal tracking approach, this study highlights the dynamic changes in emotional and behavioral problems experienced by ADHD children during the COVID-19 pandemic control and post-lockdown phases. The findings indicate that prolonged control measures pose significant challenges to emotional regulation in ADHD children, with adaptive demands increasing post-lockdown. Personalized interventions tailored to the specific pandemic phase, gender, and ADHD subtype can help alleviate adaptive stress. Notably, providing continuous support during the post-lockdown period and the gradual return to social norms may help ADHD children better adapt to environmental changes, ultimately supporting stable mental health development.This study is the first to reveal the dynamic emotional and behavioral changes in ADHD children under prolonged pandemic controls, providing a scientific basis for developing targeted psychological interventions, particularly to safeguard their mental health during public health crises.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXQ, QZ, and WT conceived the research ideas with input from JC; XQ, DZ, XF, YH, XC, SW, and AA collected the data; XQ, WT, and HL performed the data analysis and checked the data analysis; and XQ, DZ, and WT drafted the manuscript, with inputs from XF, YH, XC, SW, AA, JZ, XH, HL, and JC. All the co-authors have reviewed and approved the final manuscript for submission.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors acknowledge all the participants.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data generated or analysed during this study are available by emailing the request to the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePolanczyk, G. V., de Lima, M. S., Horta, B. L., Biederman, J. \u0026amp; Rohde, L. A. The worldwide prevalence of ADHD: A systematic review and metaregression analysis. \u003cem\u003eAm. J. 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Socioeconomic associations with ADHD: Findings from a mediation analysis. \u003cem\u003ePLoS ONE\u003c/em\u003e. \u003cb\u003e10\u003c/b\u003e (6), e0128248. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0128248\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0128248\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2015).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Summary of Baseline Characteristics of Children with ADHD in Shanghai During COVID-19 Control Measures (N=1102)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"482\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 173px;\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eCount\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 77px;\"\u003e\n \u003cp\u003eProportion (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6 to 10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10 to 16 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4 to 6 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e83.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGestational Age (weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37 to 42 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e92.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;37 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;42 weeks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBirth Weight (grams)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2500 to 4000 grams\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e882\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e80.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;4000 grams\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;2500 grams\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMaternal Age at Birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 to 35 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;35 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eADHD Subtype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003emixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eattention deficit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e44.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ehyperactive-impulsive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWechsler Intelligence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90 to 110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e48.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70 to 90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIncome level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0-5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e135\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5000-10000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e431\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10000-30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e430\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;30000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e106\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch4\u003e\u003cstrong\u003eTable 2, Differences in Average Scores across Emotional and Behavioral Dimensions among ADHD Children in Shanghai during the Pandemic Control Phase (n=1102)\u003c/strong\u003e\u003c/h4\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"451\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 237px;\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eMale Mean (n=915) (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eFemale Mean (n=187) (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAttention Deficit (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.54 (5.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.30 (4.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHyperactivity-Impulsivity (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.14 (5.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.21 (5.12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eOppositional Defiance (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.04 (4.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.17 (4.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eConduct Disorder (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.19 (2.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.35 (1.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnxiety-Depression (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.52 (3.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.25 (3.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eConduct Problems (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.73 (0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.65 (0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLearning Problems (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.53 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.51 (0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePsychosomatic Disorders (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.19 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.16 (0.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eImpulsivity-Hyperactivity (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.22 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.06 (0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAnxiety (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHyperactivity Index (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.10 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.99 (0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3, Differences in Average Scores across Emotional and Behavioral Dimensions among ADHD Subtypes in Shanghai during the Pandemic Control Phase \u0026nbsp;(n=1102)\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"678\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eDimension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003eAttention Deficit Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eHyperactivity-Impulsivity Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eCombined Type Mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003eAttention Deficit Sample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003eHyperactivity-Impulsivity Sample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003eCombined Type Sample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAttention Deficit (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e15.27 (5.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e12.06 (4.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e14.15 (5.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eHyperactivity-Impulsivity (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e7.89 (4.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e17.05 (5.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e12.73 (5.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eOppositional Defiance (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e6.99 (4.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e9.55 (5.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e8.55 (4.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eConduct Disorder (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.58 (1.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e3.16 (3.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e2.33 (3.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAnxiety-Depression (Total Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e3.75 (3.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e2.81 (3.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e3.32 (3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eConduct Problems (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.63 (0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.84 (0.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.79 (0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eLearning Problems (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e1.57 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.38 (0.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.51 (0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eLearning Problems (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.17 (0.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.17 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.19 (0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eImpulsivity-Hyperactivity (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.99 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.56 (0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.34 (0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eAnxiety (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.48 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e0.38 (0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e0.44 (0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 164px;\"\u003e\n \u003cp\u003eHyperactivity Index (Average Score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e0.98 (0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e1.24 (0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e1.16 (0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e486\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e545\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Attention-Deficit/Hyperactivity Disorder, COVID, Dynamic Change","lastPublishedDoi":"10.21203/rs.3.rs-5702346/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5702346/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to assess dynamic changes in emotional and behavioral problems among children with Attention-Deficit/Hyperactivity Disorder (ADHD) in Shanghai, China.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing a longitudinal design, school-aged children with ADHD were enrolled and followed, with emotional and behavioral measures repeatedly assessed. Due to varying COVID-19 measures and changing epidemics, and no intervention was admitted, an event-based longitudinal design was adopted, using calendar time from the enrollment of the first participant. Data collection spanned various pandemic control stages, including the Shanghai lockdown (March 28 to May 31, 2022). Emotional and behavioral trends were analyzed using a Generalized Additive Model (GAM) to capture the nonlinear dynamics effectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 1,102 children with ADHD (mean: 9.2 ± 2.4 years, 83% boys) were enrolled. Emotional and behavioral issues fluctuated over time. Behavioral problems, including inattention, hyperactivity, and conduct issues, peaked around day 260 of isolation and then declined but resurged after the Shanghai lockdown. Emotional issues, such as anxiety and depression, showed a dual-peak pattern, with early pandemic rises and a second peak around day 400. Symptoms rebounded after lockdown and persisted for an extended period. Sub-analyses revealed that boys had higher scores in hyperactivity and oppositional defiance than girls, with no significant gender differences in emotional problems. ADHD-PI children had higher emotional problem scores, while ADHD-HI children exhibited more severe behavioral issues.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study highlights the substantial impact of prolonged COVID-19 measures on emotional and behavioral problems in ADHD children, particularly increased adaptive pressures post-lockdown. Phase-specific, individualized interventions are crucial to mitigate these challenges.\u003c/p\u003e","manuscriptTitle":"Longitudinal Patterns of Attention-Deficit/Hyperactivity Disorder Children in Shanghai, China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-14 23:00:18","doi":"10.21203/rs.3.rs-5702346/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-28T07:11:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-26T12:29:45+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-18T02:01:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"307178976166328987126155330260812540464","date":"2025-04-10T08:05:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"129165533223263806082324610651945101599","date":"2025-04-10T06:02:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-09T06:55:17+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-09T05:54:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-03-29T14:56:36+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e185c317-337b-4bf5-969e-6d2250a002fe","owner":[],"postedDate":"April 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46890469,"name":"Biological sciences/Psychology"},{"id":46890470,"name":"Biological sciences/Psychology/Human behaviour"}],"tags":[],"updatedAt":"2025-06-30T16:01:25+00:00","versionOfRecord":{"articleIdentity":"rs-5702346","link":"https://doi.org/10.1038/s41598-025-02254-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-06-26 15:57:06","publishedOnDateReadable":"June 26th, 2025"},"versionCreatedAt":"2025-04-14 23:00:18","video":"","vorDoi":"10.1038/s41598-025-02254-x","vorDoiUrl":"https://doi.org/10.1038/s41598-025-02254-x","workflowStages":[]},"version":"v1","identity":"rs-5702346","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5702346","identity":"rs-5702346","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}