Psychosocial Burden of Undiagnosed Persistent ADHD Symptoms in 12-Year-Old Children: A Population-Based Birth Cohort Study

Abstract

Objective: To describe the psychosocial functioning in children with undiagnosed persistent ADHD symptoms. Method: A prospective, population-based birth cohort study was conducted among 2,945 children and their primary caregivers who lived in Tokyo, Japan, and were followed up at the age of 10 years and 12 years. Parents reported a history of ADHD diagnosis and completed the Strengths and Difficulties Questionnaire. Results: Overall, 91 participants had persistent ADHD symptoms; however, 76 (83.5%) had no history of an ADHD diagnosis. The presence of undiagnosed ADHD symptoms was significantly associated with worse psychosocial functioning for most continuous outcomes when compared with the absence of ADHD symptoms and diagnosis, including lower self-esteem (standardized mean difference [SMD] = −0.31) and higher depression (SMD = 0.36), emotional symptoms (SMD = 0.69), conduct problems (SMD = 1.26), and peer relationship problems (SMD = 0.98). Conclusion: Our findings suggest the importance of paying more attention to the possible underdiagnosis of ADHD in children.

Keywords

overdiagnosis overtreatment underdiagnosis psychosocial impairment

Introduction

ADHD is one of the most common mental disorders in children and adolescents (Perou et al., 2013). The worldwide prevalence of ADHD in children and adolescents is estimated to be between 3.4% and 7.2% (Polanczyk, Salum, Sugaya, Caye, & Rohde, 2015; Thomas, Sanders, Doust, Beller, & Glasziou, 2015). Children and adolescents with ADHD are at risk of a range of poor psychosocial outcomes (Evren, Dalbudak, Evren, Can, & Umut, 2014; Galera, Bouvard, Encrenaz, Messiah, & Fombonne, 2008; Galera, Melchior, Chastang, Bouvard, & Fombonne, 2009; Madsen et al., 2018; Slomkowski, Klein, & Mannuzza, 1995).

Children and adolescents with a diagnosis of ADHD may benefit from initiating optimal treatments for ADHD, including parent-training programs, environmental modifications, behavior therapy, and pharmacotherapy (National Institute for Health and Care Excellence, 2018; Subcommittee on Attention-Deficit/Hyperactivity Disorder & Steering Committee on Quality Improvement and Management, 2011). Experts agree that untreated ADHD can have a negative impact on a child’s life, including failure at school, failed interpersonal relationships, depression, and substance use (National Institute for Health and Care Excellence, 2018; Subcommittee on Attention-Deficit/Hyperactivity Disorder & Steering Committee on Quality Improvement and Management, 2011; UpToDate, 2017). However, 38% to 58% of children and adolescents with ADHD symptoms have no history of receiving an ADHD diagnosis (Cuffe, Moore, & McKeown, 2005; Madsen et al., 2018). In addition, our previous work has indicated that many children and adolescents with ADHD may be undermedicated (Okumura et al., 2019). These findings have raised concerns about the underdiagnosis of ADHD, although the mass media have strong interests on the potential overdiagnosis and overtreatment of ADHD (Sciutto & Eisenberg, 2007).

However, little is known about whether children and adolescents with undiagnosed ADHD symptoms have an elevated risk of impaired psychosocial functioning (Madsen et al., 2018). Understanding the psychosocial burden of undiagnosed ADHD symptoms should help teachers, clinicians, and policy makers pay more attention to the possible underdiagnosis of ADHD. In particular, we consider it important to focus on a subgroup of children with undiagnosed persistent ADHD symptoms, because childhood ADHD symptoms or diagnosis do not persist for a decade in most cases (Caye et al., 2016; Moffitt et al., 2015; Riglin et al., 2016; St. Pourcain et al., 2011). Therefore, using data from a large population–based birth cohort study, we sought to describe differences in the psychosocial functioning among 12-year-old children with an ADHD diagnosis, those with undiagnosed persistent ADHD symptoms, and those without persistent ADHD symptoms or an ADHD diagnosis.

Method

Design

This study was part of the Tokyo TEEN Cohort (TTC) project, an ongoing prospective, population-based birth cohort study of children aged 10 years and their primary caregivers. Details of the TTC are described elsewhere (Kanata et al., 2016; Morimoto et al., 2018; Yamasaki et al., 2016). Briefly, the aims of the TTC were to investigate the health and development of children. A sample of 3,171 households with children aged 10 years (i.e., born between September 2002 and August 2004) was obtained from three municipalities (Chofu, Mitaka, and Setagaya) in Tokyo, Japan, by using random sampling method. When children were aged 12 years, 3,007 households participated in the second wave of the study (Figure 1). Trained interviewers obtained written informed consent from children’s primary caregivers, asked children and their caregivers to complete a set of questionnaires, conducted a semistructured interview, and measured anthropometric data. The study protocol of the TTC was approved by the institutional review boards at the Tokyo Metropolitan Institute of Medical Science, SOKENDAI (Graduate University for Advanced Studies), and the University of Tokyo.

Figure 1.

Flow diagram of participants.

ADHD Symptoms and Diagnosis

ADHD symptoms were assessed using the parent-rated five-item Strengths and Difficulties Questionnaire (SDQ)-hyperactivity/inattention subscale (Goodman, 1997; Matsuishi et al., 2008). The subscale consists of two positively (e.g., “Thinks things out before acting.”) and three negatively (e.g., “Restless, overactive, cannot stay still for long”) worded items assessing ADHD symptoms over the past 6 months on a 3-point Likert-type scale ranging from 0 (not true) to 2 (certainly true). Total scores derived from the questionnaire range from 0 to 10 with higher scores indicating more serious problems. To identify the presence of ADHD symptoms, a cutoff score of ≥ 7 was used as appeared in previous studies (Riglin et al., 2016; St. Pourcain et al., 2011). The SDQ-hyperactivity/inattention subscale has high sensitivity (86%) and specificity (95%) for detecting an ADHD diagnosis when compared with diagnosis made using a structured diagnostic interview (Tanabe, Kashiwagi, Shimakawa, Tamai, & Wakamiya, 2014). Persistent ADHD symptoms were defined as patients with a score of ≥ 7 on the SDQ-hyperactivity/inattention subscale at Waves 1 and 2.

Children with an ADHD diagnosis were identified using two parent-rated items. First, parents were asked whether their child had a history of ADHD diagnosis from medical institutions at Wave 2. Second, parents were asked to report all medications taken by their child in the previous 2 weeks at Waves 1 and 2. Children with a history of an ADHD diagnosis and/or a report of taking any ADHD drugs (atomoxetine and/or methylphenidate) were considered as having received an ADHD diagnosis.

Outcomes

Outcomes of interest were self-harm behavior, school absenteeism, psychological well-being, self-esteem, depression, and positive and negative aspects of behavior. All outcomes were assessed at Wave 2. These outcomes were selected based on the results of earlier investigations regarding ADHD symptoms and negative outcomes (Evren et al., 2014; Galera et al., 2008; Galera et al., 2009; Madsen et al., 2018; Slomkowski et al., 1995).

Self-harm behavior was assessed through an original self-rated item and a parent-rated item from the Child Behavior Checklist (Achenbach, 1991; Itani et al., 2001). Children were asked, “Have you deliberately injured yourself in the past year?” Parents were also asked to rate their child’s self-harm behavior (“Deliberately harms self or attempts suicide”) within the past 6 months on a 3-point scale. Responses were dichotomized into absence (“not true”) versus presence (“somewhat or sometimes true” and “very true or often true”) of self-harm behavior.

School absenteeism was assessed through two parent-rated items: “How often does your child miss school?” and “How often does your child come late or leave early for school?” Parents were asked to rate on a 4-point scale (none, 1-3 days per month, 1-2 days per week, and ≥3 days per week). Children with a response of 1-2 days per week or ≥3 days per week to either of the items were considered as presence of school absenteeism.

Psychological well-being was assessed using the self-rated five-item World Health Organization Well-Being Index (WHO-5; Awata et al., 2007; Bonsignore, Barkow, Jessen, & Heun, 2001). Each item (e.g., “I have felt active and vigorous”) assesses the degree of positive well-being over the past 2 weeks on a 6-point Likert-type scale ranging from 0 (at no time) to 5 (all of the time). Total scores derived from the WHO-5 range from 0 to 25, with higher scores indicating better psychological well-being.

Self-esteem was assessed using the self-rated 10-item Rosenberg Self-Esteem Scale (RSES; Mimura & Griffiths, 2007; Rosenberg, 1965). The RSES consists of five positively (e.g., “On the whole, I am satisfied with myself”) and five negatively (e.g., “At times I think I am no good at all”) worded items measured using a 4-point Likert-type scale ranging from 1 (strongly disagree) to 4 (strongly agree). Total scores derived from the RSES range from 10 to 40, with higher scores indicating higher self-esteem.

Depression was assessed using the self-rated 13-item Short Mood and Feelings Questionnaire (SMFQ; Angold, Costello, Messer, & Pickles, 1995). Each item (e.g., “I felt so tired I just sat around and did nothing”) assesses depression symptoms over the past 2 weeks on a 3-point Likert-type scale ranging from 0 (not true) to 2 (true). Total scores derived from the SMFQ range from 0 to 26, with higher scores indicating severe depression.

Positive and negative aspects of behavior were assessed using the parent-rated SDQ (Goodman, 1997; Matsuishi et al., 2008). The SDQ includes five subscales each with five items assessing emotional symptoms, conduct problems, hyperactivity/inattention, peer relationship problems, and prosocial behavior. Apart from hyperactivity/inattention subscale, the other four subscales were used as outcomes. Emotional symptoms, peer relationship problems, and prosocial behavior subscales assess negative aspects of behavior, whereas prosocial subscale assesses positive aspects of behavior. Total scores derived from the SDQ subscales range from 0 to 10.

Intermediate Outcomes

Harsh discipline was assessed as a potential intermediate outcome associated with worse psychosocial functioning through two parent-rated items: “Do you yell at your child?” and “Do you slap your child as a means of discipline?” Parents were asked to rate on a 4-point scale (rarely, sometimes, often, and always). Responses were dichotomized into absence (rarely and sometimes) versus presence (often and always) of yelling and slapping. These variables were considered as intermediate outcomes of psychosocial burden.

History of Health Service Utilization

Lifetime history of health care service utilization was assessed through a parent-rated item: “Have your child ever received treatments and/or counseling for affective, developmental, and/or conduct problems?” All health care services were included, such as school counseling, educational counseling, medical treatments in pediatrics and psychiatry, and so forth. This variable was used for descriptive purposes only.

Statistical Analyses

Participants who had missing data on ADHD symptoms and/or ADHD diagnosis were excluded from the present analyses. Based on the information about persistent ADHD symptoms and ADHD diagnoses (Table 1), children were categorized into three groups: children with an ADHD diagnosis (ADHD diagnosis group), children with undiagnosed ADHD symptoms (no-ADHD diagnosis group), and children without ADHD symptoms or an ADHD diagnosis (control group). Demographic characteristics were compared across groups using the metric of standardized differences, in which an absolute value greater than 10% indicates an important imbalance in the prevalence of a demographic variable between groups (Austin, 2011). Multiple imputations by chained equations were used to address missing data (van Buuren, 2018). Outcomes with missing data were imputed using variables and imputation techniques listed in Supplemental Table S1. Twenty imputed data sets with 10 iterations were generated using the mice package Version 3.3.0 (van Buuren & Groothuis-Oudshoorn, 2011). Outcomes were compared across groups using risk differences (RDs) for binary outcomes and mean differences (MDs) for continuous variables with their 95% confidence intervals (CIs). Standardized mean differences (SMDs) were also calculated for continuous variables to enhance the interpretability. Significance level was set at 5%. No adjustment for multiplicity was performed given the exploratory nature of this study. All analyses were conducted using R Version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria).

Table 1.

Persistent ADHD Symptoms and Diagnosis.

Persistent ADHD symptoms	ADHD diagnosis
Persistent ADHD symptoms	No	Yes
No	2,819	35
Yes	76	15

Sensitivity Analyses

The main analyses were repeated using the categorization method based on ADHD symptoms at Wave 2, rather than persistent ADHD symptoms. All analyses were repeated using the complete-case method to deal with missing data.

Results

Participants

Of the 3,171 initially enrolled households, 2,945 (92.9%) were included in our final analytic sample (Figure 1). Overall, 91 (3.1%) had persistent ADHD symptoms, 50 (1.7%) had a history of an ADHD diagnosis, and only seven (0.2%) received a prescription of ADHD drugs. A total of 76 (83.5%) out of 91 participants with persistent ADHD symptoms had no history of ADHD diagnosis (Table 1). Of the 76 participants with undiagnosed ADHD symptoms, 43 (56.6%) had never utilized any health care service for conduct problems, and 56 (73.7%) had never utilized medical services including psychiatry, pediatrics, and so forth. Compared to the no-ADHD diagnosis group, the ADHD diagnosis group had a smaller proportion of fathers with an education level of ≥16 years (40.0% vs. 55.3%) and a smaller proportion of families with an income of ≥10 million yen (14.0% vs. 26.3%; Table 2).

Table 2.

Sample Characteristics by Persistent ADHD Symptoms and Diagnosis Groups.

Characteristics	Persistent ADHD symptoms and diagnosis			Standardized difference, %
Characteristics	ADHD diagnosis group (n = 50)	No-ADHD diagnosis group (n = 76)	Control group (n = 2,819)	ADHD diagnosis vs. No-ADHD diagnosis	ADHD diagnosis vs. Control	No-ADHD diagnosis vs. Control
Sex, number (%)
Boys	39 (78.0)	57 (75.0)	1,454 (51.6)	7.1	57.6	50.1
Girls	11 (22.0)	19 (25.0)	1,365 (48.4)	−7.1	−57.6	−50.1
Age at second wave, M (SD), months	146.1 (4.6)	146 (3.6)	146 (3.6)	4.7	4.6	0.0
Mothers’ age at second wave, number (%), years
≤ 39	13 (26.0)	13 (17.1)	338 (12.0)	21.8	36.3	14.5
40-49	32 (64.0)	49 (64.5)	2,010 (71.3)	−1.0	−15.7	−14.7
≥ 50	2 (4.0)	7 (9.2)	248 (8.8)	−21.1	−19.7	1.4
Missing	3 (6.0)	7 (9.2)	223 (7.9)	−12.1	−7.5	4.6
Fathers’ age at second wave, number (%), years
≤ 39	8 (16.0)	12 (15.8)	177 (6.3)	0.6	31.3	30.7
40-49	24 (48.0)	39 (51.3)	1,644 (58.3)	−6.6	−20.8	−14.1
≥ 50	10 (20.0)	15 (19.7)	602 (21.4)	0.7	−3.3	−4.0
Missing	8 (16.0)	10 (13.2)	396 (14.0)	8.1	5.5	−2.6
Mothers’ education level, number (%), years
≤ 12	13 (26.0)	17 (22.4)	456 (16.2)	8.5	24.3	15.7
13-15	26 (52.0)	37 (48.7)	1,226 (43.5)	6.6	17.1	10.4
≥ 16	11 (22.0)	20 (26.3)	1,116 (39.6)	−10.1	−38.8	−28.5
Missing	0 (0.0)	2 (2.6)	21 (0.7)	−23.3	−12.3	14.7
Fathers’ education level, number (%), year
≤ 12	14 (28.0)	18 (23.7)	472 (16.7)	9.9	27.3	17.3
13-15	10 (20.0)	13 (17.1)	356 (12.6)	7.5	20.0	12.6
≥ 16	20 (40.0)	42 (55.3)	1,865 (66.2)	−30.9	−54.3	−22.4
Missing	6 (12.0)	3 (3.9)	126 (4.5)	30.1	27.7	−2.6
Annual family income, number (%), million yen
0.00-3.99	9 (18.0)	6 (7.9)	233 (8.3)	30.4	29.1	−1.4
4.00-5.99	9 (18.0)	16 (21.1)	432 (15.3)	−7.7	7.2	14.9
6.00-7.99	16 (32.0)	21 (27.6)	468 (16.6)	9.6	36.5	26.8
8.00-9.99	6 (12.0)	6 (7.9)	495 (17.6)	13.7	−15.7	−29.3
≥ 10	7 (14.0)	20 (26.3)	924 (32.8)	−31.1	−45.5	−14.2
Missing	3 (6.0)	7 (9.2)	267 (9.5)	−12.1	−13.0	−0.9

Note. A larger absolute value of the standardized difference indicates a greater imbalance in the prevalence of a demographic variable between the two groups.

ADHD Diagnosis Group Versus No-ADHD Diagnosis Group

There were no between-group differences in most outcomes between the ADHD diagnosis group and the no-ADHD diagnosis group, although the risk of self-rated self-harm was greater in the ADHD diagnosis group than in the no-ADHD diagnosis group (21.8% vs. 13.9%; RD = 7.9%, 95%CI = [−7.7, 23.4]; Figure 2; Supplemental Table S2). Mean prosocial behavior scores were significantly higher in the ADHD diagnosis group than in the no-ADHD diagnosis group (6.4 vs. 5.4; MD = 1.0, 95%CI = [0.3, 1.8]; SMD = 0.42). Children with an ADHD diagnosis were less likely to be yelled than those with undiagnosed ADHD symptoms (43.6% vs. 68.8%; RD = −25.2, 95%CI = [−43.2, −7.2]).

Figure 2.

Differences in the binary and intermediate outcomes (Panel A) and continuous outcomes (Panel B) between the ADHD diagnosis and no-ADHD diagnosis groups.

No-ADHD Diagnosis Group Versus Control Group

There were no between-group differences in the binary outcomes between the no-ADHD diagnosis group and the control group (Figure 3; Supplemental Table S2). Compared with the control group, the no-ADHD diagnosis group had significantly lower scores on self-esteem (MD = −1.4, 95%CI = [−2.6, −0.3]; SMD = −0.31) and prosocial behavior (MD = −1.2, 95%CI = [−1.7, −0.7]; SMD = −0.56), whereas the no-ADHD diagnosis group had higher scores on depression (MD = 1.6, 95%CI = [0.5, 2.7]; SMD = 0.36), emotional symptoms (MD = 1.1, 95%CI = [0.7, 1.5]; SMD = 0.69), conduct problems (MD = 1.8, 95%CI = [1.5, 2.2]; SMD = 1.26), and peer relationship problems (MD = 1.5, 95%CI = [1.2, 1.9]; SMD = 0.98). Children with persistent ADHD symptoms were more likely to be yelled at (68.8% vs. 31.6%; RD = 37.2, 95%CI = [26.0, 48.4]) and slapped (15.2% vs. 4.1%; RD = 11.1, 95%CI = [2.9, 19.3]) than those without ADHD symptoms or an ADHD diagnosis.

Figure 3.

Differences in the binary and intermediate outcomes (Panel A) and continuous outcomes (Panel B) between the no-ADHD diagnosis and control groups.

Sensitivity Analyses

The number of no-ADHD diagnosis groups was twofold higher among participants with ADHD symptoms at Wave 2 (n = 155) than among those with persistent ADHD symptoms from Waves 1 to 2 (n = 76; Supplemental Table S3). When examining the participants with ADHD symptoms at Wave 2, compared with those in the no-ADHD diagnosis group, participants in the ADHD diagnosis group had a smaller proportion of fathers with an education level of ≥ 16 years (40.0% vs. 57.4%) and a smaller proportion of families with an income of ≥ 10 million yen (14.0% vs. 27.3%; Supplemental Table S4). Sensitivity analyses using this categorization method produced similar results to those of main analyses (Supplemental Table S5). In addition, the use of the complete-case method generated consistent results with that of the multiple imputation method (Supplemental Tables S6 and S7).

Discussion

In our population-based birth cohort study, we found that most children with persistent ADHD symptoms had no history of an ADHD diagnosis and most of them had never utilized medical services for conduct problems. We confirmed that the presence of undiagnosed ADHD symptoms was significantly associated with worse psychosocial functioning for most continuous outcomes when compared with the absence of ADHD symptoms and diagnosis, whereas it was not the case when compared with the presence of an ADHD diagnosis. In addition, we observed that there were no significant differences in binary outcomes among the three groups. Results were robust to a variety of sensitivity analyses.

To the best of our knowledge, this is the second study to evaluate the increased psychosocial burden of undiagnosed ADHD symptoms. In several aspects, we extend a recent cohort study that estimated the number of 7-year-old children with ADHD symptoms in the absence of an ADHD diagnosis from the age of 5 years until the age of 10 years to 17 years and that investigated whether the SDQ characteristics of this group differed from the children diagnosed with ADHD during the follow-up period (Madsen et al., 2018). First, our exposure definition comprised persistent ADHD symptoms rather than ADHD symptoms at a single point. Second, the end of the observational period for an ADHD diagnosis in our study was the same as the last assessment of ADHD symptoms. Third, our outcomes were comprehensive to understand the various negative outcomes of undiagnosed ADHD.

We observed that children with undiagnosed persistent ADHD symptoms were impaired in various aspects of psychosocial functioning including self-esteem, depression, emotional symptoms, conduct problems, and peer relationship problems. Similar findings were observed in children with undiagnosed ADHD symptoms at a single time point; however, it seems more important to focus on persistent ADHD symptoms rather than transient ADHD symptoms. This is because children with persistent ADHD symptoms may be more likely to continue to have ADHD symptoms at least until the age of 17 years, whereas some children with transient ADHD symptoms may show a decline in ADHD symptoms as they age (Riglin et al., 2016; St. Pourcain et al., 2011). Our data suggest that teachers, clinicians, and policy makers should pay more attention to the possible underdiagnosis of ADHD in children, although clinicians should also have concerns about overdiagnosis of ADHD in daily practice (Merten, Cwik, Margraf, & Schneider, 2017).

Of note, our findings on the key parameters had both consistencies and inconsistencies with previous studies. The prevalence of persistent ADHD symptoms in our study (3.1%) is very similar to that reported in previous studies (3.9%; Riglin et al., 2016; St. Pourcain et al., 2011). However, the prevalence of parent-reported ADHD diagnosis is much lower in our study (1.7%) than that in the United States (9.4% in children aged 2-17 years; Danielson et al., 2018) and in Germany (4.9% in children aged ≤ 17 years; Knopf, Holling, Huss, & Schlack, 2012). In addition, the prevalence of undiagnosed ADHD among children with ADHD symptoms is much higher in our study (83.5%) than that reported in the United States (61.9% in boys and 52.7% in girls; Cuffe et al., 2005) and in Denmark (57.7%; Madsen et al., 2018).

These key parameters would be the mutually related factors for the lack of statistical differences in most outcomes between the ADHD diagnosis group and the no-ADHD diagnosis group. Under the abovementioned parameter estimates, over 15,000 participants would be needed to detect an RD of 7.9% (21.8% vs. 13.9%) with a power of 80% and a Type I error of 5%. Future studies should incorporate more participants to evaluate the differences between the ADHD diagnosis group and the no-ADHD diagnosis group.

Interestingly, we found that children with undiagnosed ADHD symptoms had the lowest levels of prosocial behavior among the three groups. Similar findings were reported in the previous study of children with ADHD symptoms (Madsen et al., 2018). One possible explanation for this is that harsh discipline may be an intermediate variable in the causal pathway between undiagnosed ADHD symptoms and prosocial behavior. Many theories of child development assume that parenting style has a key role for the socialization of children (Putnick et al., 2018). In fact, previous cohort studies showed that negative parenting style, including harsh discipline, contributed to a reduction of children’s prosocial behavior (Bhide, Sciberras, Anderson, Hazell, & Nicholson, 2017; Putnick et al., 2018). In our study, children with undiagnosed ADHD symptoms often received harsh discipline, which may negatively influence children’s prosocial behavior.

Our study has several limitations. First, parents’ report on an ADHD diagnosis and ADHD drugs have not been validated against health record data, which may be subject to recall and reporting bias. Second, the diagnostic information was limited to an ADHD diagnosis; hence, we could not identify whether other physical and mental health conditions could account for ADHD symptoms. Third, the assessment of ADHD symptoms was solely based on parents’ report rather than multiple informants. Fourth, ADHD symptoms were measured 2 times at an interval of 2 years; therefore, we could not confirm whether children had clinically elevated ADHD symptoms throughout the interval. Fifth, our study population was limited to three municipalities, where the proportion of families with an income of ≥ 10 million yen was much higher in our sample (32%) than in Japan as a whole (14%) (Ministry of Health, Labour and Welfare 2018); consequently, the generalizability of our findings, especially to low-income municipalities, remains unknown. Sixth, the prevalence of undiagnosed ADHD in our study was indirect evidence for the underdiagnosis of ADHD due to the inability to make ADHD diagnoses using standardized-multimodal assessments for ADHD (Sciutto & Eisenberg, 2007). Finally, the follow-up period in our study was limited to 2 years. Thus, long-term studies are needed to investigate whether children with undiagnosed ADHD symptoms show impairment in various aspects of psychosocial functioning over the long term and whether the ADHD symptoms will continue into adulthood.

In conclusion, we observed that most children with persistent ADHD symptoms had no history of an ADHD diagnosis; however, they showed impairment in several aspects of psychosocial functioning. Our findings suggest the importance of paying more attention to the possible underdiagnosis of ADHD in children.

Supplemental Material

Supplemental_material – Supplemental material for Psychosocial Burden of Undiagnosed Persistent ADHD Symptoms in 12-Year-Old Children: A Population-Based Birth Cohort Study

Supplemental material, Supplemental_material for Psychosocial Burden of Undiagnosed Persistent ADHD Symptoms in 12-Year-Old Children: A Population-Based Birth Cohort Study by Yasuyuki Okumura, Syudo Yamasaki, Shuntaro Ando, Masahide Usami, Kaori Endo, Mariko Hiraiwa-Hasegawa, Kiyoto Kasai and Atsushi Nishida in Journal of Attention Disorders

Footnotes

Acknowledgements

The authors thank Editage () for English-language editing.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: For the past 3 years, Y.O. received personal fees from Merck & Co., Inc.; Janssen Pharmaceuticals, Inc.; the Medical Technology Association; Cando Inc.; the Japan Medical Data Center; and the Japan Medical Research Institute Co., Ltd. M.U. received personal fees from Janssen Pharmaceutical Inc. and Eli Lilly Japan. Authors not mentioned here have disclosed no conflicts of interest.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was funded by a grant from a Japan Scientific Research Grant on an Innovative Area from the Ministry of Education, Culture, Sports, Science and Technology (MEXT KAKENHI 23118002); a Japan Scientific Research Grant on an Innovative Area from the Japan Society for the Promotion of Science (JSPS KAKENHI 16H06395, 16H06398, 16K21720, JP16H06395); a Grant-in-Aid for Scientific Research (B) from the Japan Society for the Promotion of Science (JSPS KAKENHI 16H03745); and a Tokyo Metropolitan Institute of Medical Science Project Grant (Kokoronokenko H27-H31). This work was also supported in part by UTokyo Center for Integrative Science of Human Behavior (CiSHuB) and by the International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS). The funding bodies had no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

Supplemental material

Supplementary material for this article is available online.

ORCID iD

Yasuyuki Okumura

Author Biographies

Yasuyuki Okumura, PhD, is a chief researcher at the Tokyo Metropolitan Institute of Medical Science.

Syudo Yamasaki, PhD, is a chief researcher at the Tokyo Metropolitan Institute of Medical Science.

Shuntaro Ando, MD, PhD, is a visiting scientist at the Tokyo Metropolitan Institute of Medical Science and a Lecture at the University of Tokyo.

Masahide Usami, MD, PhD, is a Department Director at the Kohnodai Hospital, National Center for Global Health and Medicine.

Kaori Endo, PhD, is a research scientist at the Tokyo Metropolitan Institute of Medical Science.

Mariko Hiraiwa-Hasegawa, PhD, is the president at the SOKENDAI (The Graduate University for Advanced Studies).

Kiyoto Kasai, MD, PhD, is a professor at the Tokyo University.

Atsushi Nishida, PhD, is a project leader at the Tokyo Metropolitan Institute of Medical Science.

References

Achenbach

T. M.

(1991). Integrative guide for the 1991 CBCL/4-18, YSR, and TRF profiles. Burlington: The University of Vermont.

Angold

Costello

E. J.

Messer

S. C.

Pickles

(1995). Development of a short questionnaire for use in epidemiological studies of depression in children and adolescents. International Journal of Methods in Psychiatric Research, 5, 237-249.

Austin

P. C.

(2011). An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research, 46, 399-424. doi:10.1080/00273171.2011.568786

Awata

Bech

Koizumi

Seki

Kuriyama

Hozawa

. . . Tsuji

(2007). Validity and utility of the Japanese version of the WHO-Five Well-Being Index in the context of detecting suicidal ideation in elderly community residents. International Psychogeriatrics, 19, 77-88. doi:10.1017/S1041610206004212

Bhide

Sciberras

Anderson

Hazell

Nicholson

J. M.

(2017). Association between parenting style and social outcomes in children with and without attention-deficit/hyperactivity disorder: An 18-month longitudinal study. Journal of Developmental and Behavioral Pediatrics, 38, 369-377. doi:10.1097/DBP.0000000000000453

Bonsignore

Barkow

Jessen

Heun

(2001). Validity of the five-item WHO Well-Being Index (WHO-5) in an elderly population. European Archives of Psychiatry and Clinical Neuroscience, 251(Suppl. 2), II27-I131.

Caye

Rocha

T. B.

Anselmi

Murray

Menezes

A. M.

Barros

F. C.

. . . Rohde

L. A.

(2016). Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood: Evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry, 73, 705-712. doi:10.1001/jamapsychiatry.2016.0383

Cuffe

S. P.

Moore

C. G.

McKeown

R. E.

(2005). Prevalence and correlates of ADHD symptoms in the national health interview survey. Journal of Attention Disorders, 9, 392-401. doi:10.1177/1087054705280413

Danielson

M. L.

Bitsko

R. H.

Ghandour

R. M.

Holbrook

J. R.

Kogan

M. D.

Blumberg

S. J.

(2018). Prevalence of parent-reported ADHD diagnosis and associated treatment among U.S. children and adolescents, 2016. Journal of Clinical Child & Adolescent Psychology, 47, 199-212. doi:10.1080/15374416.2017.1417860

10.

Evren

Dalbudak

Evren

Can

Umut

(2014). The severity of attention deficit hyperactivity symptoms and its relationship with lifetime substance use and psychological variables among 10th grade students in Istanbul. Comprehensive Psychiatry, 55, 1665-1670. doi:10.1016/j.comppsych.2014.06.002

11.

Galera

Bouvard

M. P.

Encrenaz

Messiah

Fombonne

(2008). Hyperactivity-inattention symptoms in childhood and suicidal behaviors in adolescence: The Youth Gazel Cohort. Acta Psychiatrica Scandinavica, 118, 480-489. doi:10.1111/j.1600-0447.2008.01262.x

12.

Galera

Melchior

Chastang

J. F.

Bouvard

M. P.

Fombonne

(2009). Childhood and adolescent hyperactivity-inattention symptoms and academic achievement 8 years later: The GAZEL Youth study. Psychological Medicine, 39, 1895-1906. doi:10.1017/S0033291709005510

13.

Goodman

(1997). The strengths and difficulties questionnaire: A research note. Journal of Child Psychology and Psychiatry, 38, 581-586.

14.

Itani

Kanbayashi

Nakata

Kita

Fujii

Kuramoto

. . . Natori

(2001). Standardization of the Japanese version of the child behavior checklist/4-18 (in Japanese). Psychiatria et Neurologia Paediatrica Japonica, 41, 243-252.

15.

Kanata

Koike

Ando

Nishida

Usami

Yamasaki

. . . Kasai

(2016). Enuresis and hyperactivity-inattention in early adolescence: Findings from a population-based survey in Tokyo (Tokyo Early Adolescence Survey). PLoS ONE, 11(7), e0158786. doi:10.1371/journal.pone.0158786

16.

Knopf

Holling

Huss

Schlack

(2012). Prevalence, determinants and spectrum of Attention-Deficit Hyperactivity Disorder (ADHD) medication of children and adolescents in Germany: Results of the German Health Interview and Examination Survey (KiGGS). BMJ Open, 2(6), e000477. doi:10.1136/bmjopen-2011-000477

17.

Madsen

K. B.

Ravn

M. H.

Arnfred

Olsen

Rask

C. U.

Obel

(2018). Characteristics of undiagnosed children with parent-reported ADHD behaviour. European Child & Adolescent Psychiatry, 27, 149-158. doi:10.1007/s00787-017-1029-4

18.

Matsuishi

Nagano

Araki

Tanaka

Iwasaki

Yamashita

. . . Kakuma

(2008). Scale properties of the Japanese version of the strengths and difficulties questionnaire (SDQ): A study of infant and school children in community samples. Brain & Development, 30, 410-415. doi:10.1016/j.braindev.2007.12.003

19.

Merten

E. C.

Cwik

J. C.

Margraf

Schneider

(2017). Overdiagnosis of mental disorders in children and adolescents (in developed countries). Child and Adolescent Psychiatry and Mental Health, 11, Article 5. doi:10.1186/s13034-016-0140-5

20.

Mimura

Griffiths

(2007). A Japanese version of the Rosenberg Self-Esteem Scale: Translation and equivalence assessment. Journal of Psychosomatic Research, 62, 589-594. doi:10.1016/j.jpsychores.2006.11.004

21.

Ministry of Health, Labour and Welfare. (2018). Comprehensive survey of living conditions in 2017. Retrieved from http://www.mhlw.go.jp/toukei/list/20-21.html

22.

Moffitt

T. E.

Houts

Asherson

Belsky

D. W.

Corcoran

D. L.

Hammerle

. . . Caspi

(2015). Is adult ADHD a childhood-onset neurodevelopmental disorder? Evidence from a four-decade longitudinal cohort study. Am J Psychiatry, 172, 967-977. doi:10.1176/appi.ajp.2015.14101266

23.

Morimoto

Yamasaki

Ando

Koike

Fujikawa

Kanata

. . . Nishida

(2018). Purpose in life and tobacco use among community-dwelling mothers of early adolescents. BMJ Open, 8(4), e020586. doi:10.1136/bmjopen-2017-020586

24.

National Institute for Health and Care Excellence. (2018). Attention deficit hyperactivity disorder: Diagnosis and management. Retrieved from https://www.nice.org.uk/guidance/ng87/resources/attention-deficit-hyperactivity-disorder-diagnosis-and-management-pdf-1837699732933

25.

Okumura

Usami

Okada

Saito

Negoro

Tsujii

. . . Iida

. (2019). Prevalence, incidence and persistence of ADHD drug use in Japan. Epidemiology and Psychiatric Sciences, 28, 692-696. doi:10.1017/S2045796018000252

26.

Perou

Bitsko

R. H.

Blumberg

S. J.

Pastor

Ghandour

R. M.

Gfroerer

J. C.

, . . . Centers for Disease Control and Prevention. (2013). Mental health surveillance among children: United States, 2005-2011. Morbidity and Mortality Weekly Report: Supplement, 62(2), 1-35.

27.

Polanczyk

G. V.

Salum

G. A.

Sugaya

L. S.

Caye

Rohde

L. A.

(2015). Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. Journal of Child Psychology and Psychiatry, 56, 345-365. doi:10.1111/jcpp.12381

28.

Putnick

D. L.

Bornstein

M. H.

Lansford

J. E.

Chang

Deater-Deckard

Di Giunta

. . . Bombi

A. S.

(2018). Parental acceptance-rejection and child prosocial behavior: Developmental transactions across the transition to adolescence in nine countries, mothers and fathers, and girls and boys. Developmental Psychology, 54, 1881-1890. doi:10.1037/dev0000565

29.

Riglin

Collishaw

Thapar

A. K.

Dalsgaard

Langley

Smith

G. D.

. . . Thapar

(2016). Association of genetic risk variants with attention-deficit/hyperactivity disorder trajectories in the general population. JAMA Psychiatry, 73, 1285-1292. doi:10.1001/jamapsychiatry.2016.2817

30.

Rosenberg

(1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press.

31.

Sciutto

M. J.

Eisenberg

(2007). Evaluating the evidence for and against the overdiagnosis of ADHD. Journal of Attention Disorders, 11, 106-113. doi:10.1177/1087054707300094

32.

Slomkowski

Klein

R. G.

Mannuzza

(1995). Is self-esteem an important outcome in hyperactive children? Journal of Abnormal Child Psychology, 23, 303-315.

33.

St. Pourcain

Mandy

W. P.

Heron

Golding

Davey Smith

Skuse

D. H

. (2011). Links between co-occurring social-communication and hyperactive-inattentive trait trajectories. Journal of the American Academy of Child & Adolescent Psychiatry, 50, 892-902.e5. doi:10.1016/j.jaac.2011.05.015

34.

Subcommittee on Attention-Deficit/Hyperactivity Disorder & Steering Committee on Quality Improvement and Management. (2011). ADHD: Clinical practice guideline for the diagnosis, evaluation, and treatment of attention-deficit/hyperactivity disorder in children and adolescents. Pediatrics, 128, 1007-1022. doi:10.1542/peds.2011-2654

35.

Tanabe

Kashiwagi

Shimakawa

Tamai

Wakamiya

(2014). Outpatient screening of Japanese children with epilepsy for Attention-Deficit/Hyperactivity Disorder (AD/HD). Brain & Development, 36, 301-305. doi:10.1016/j.braindev.2013.05.005

36.

Thomas

Sanders

Doust

Beller

Glasziou

(2015). Prevalence of attention-deficit/hyperactivity disorder: A systematic review and meta-analysis. Pediatrics, 135(4), e994-e1001. doi:10.1542/peds.2014-3482

37.

UpToDate. (2017). Patient education: Treatment of attention deficit hyperactivity disorder in children (beyond the basics). Retrieved from https://www.uptodate.com/contents/treatment-of-attention-deficit-hyperactivity-disorder-in-children-beyond-the-basics

38.

van Buuren

. (2018). Flexible imputation of missing data (2nd ed.). Boca Raton, FL: CRC Press.

39.

van Buuren

Groothuis-Oudshoorn

. (2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45(3), 1-67. doi:10.18637/jss.v045.i03

40.

Yamasaki

Ando

Koike

Usami

Endo

French

. . . Nishida

(2016). Dissociation mediates the relationship between peer victimization and hallucinatory experiences among early adolescents. Schizophrenia Research: Cognition, 4, 18-23. doi:10.1016/j.scog.2016.04.001

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