Predicting Initial Specialist Mental Health Care Use in Adolescence Using Self-, Parent-, and Teacher-Reported Problem Behavior: A Prospective Community-Based Record-Linkage Study
A Prospective Community-Based Record-Linkage Study
Objective: The aim of this study was to determine the relative importance of self-, parent-, and teacher-reported problem behavior for initial specialist mental health care use in adolescence and the extent to which the relative importance of each informant changes over time.
Methods: Data from the Dutch community-based cohort study TRacking Adolescents’ Individual Lives Survey (TRAILS) were linked to administrative records of specialist mental health care organizations. Self-, parent-, and teacher-reported internalizing and externalizing problems were assessed at ages 11, 13, and 16 years, with self-reported problems also assessed at age 19 years. The study included 1,478 adolescents, of whom 19.8% had administrative records between January 2000 (age 9 years) and December 2011 (age 21 years).
Results: After effects of internalizing and externalizing problems were adjusted for each other and for sociodemographic correlates, internalizing problems, but not externalizing problems, predicted initial specialist mental health care use. Teacher reports mainly predicted initial specialist care between the ages of 11 and 13 years (hazard ratio [HR] = 1.57; 95% confidence interval [CI], 1.22-2.02; P < .001), parent reports mainly predicted initial specialist care between the ages of 13 and 16 years (HR = 1.47; 95% CI, = 1.13-1.91; P = .004), and self-reports mainly predicted initial specialist care between the ages of 16 and 19 years (HR = 1.61; 95% CI, = 1.25-2.08; P < .001) and between the ages 19 and 21 years (HR = 1.50; 95% CI, 1.10-2.05; P = .011).
Conclusions: Teachers, parents, and adolescents are the driving force behind initial specialist care at consecutive phases in adolescence. Future research should assess whether improving the problem recognition of teachers in secondary education and educating young adults about mental health problems are effective ways of reducing the treatment gap.
J Clin Psychiatry 2018;79(4):17m11484
To cite: Raven D, Jörg F, Visser E, et al. Predicting initial specialist mental health care use in adolescence using self-, parent-, and teacher-reported problem behavior: a prospective community-based record-linkage study. J Clin Psychiatry. 2018;79(4):17m11484.
To share: https://doi.org/10.4088/JCP.17m11484
© Copyright 2018 Physicians Postgraduate Press, Inc.
aDepartment of Psychiatry, University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), Groningen, The Netherlands
bDepartment of Research and Education, Friesland Mental Health Services, Leeuwarden, The Netherlands
cDepartment of Psychiatry, University of Groningen, University Medical Center Groningen, Rob Giel Research center (RGOc), Groningen, The Netherlands
*Corresponding author: Dennis Raven, MSc, University of Groningen, University Medical Center Groningen, Department of Psychiatry, CC72, PO Box 30.001, 9700 RB Groningen, The Netherlands .
Many mental disorders have an onset in childhood or adolescence.1 Their prevalence2,3 and burden4 are very high in adolescence, and their adverse effects last well into adulthood.5-9 Many adolescents with mental disorders do not receive specialist treatment,10,11 however, and for those who do the time to treatment is often many years.12 This lack of or delay in treatment has sparked interest in the factors that may influence help-seeking, as these may be targeted in programs aimed at promoting access to mental health care.13
Help-seeking in adolescence is affected by many actors. Next to the adolescents, parents and teachers play very important roles in the help-seeking process.14,15 Each actor’s influence on help-seeking is likely to differ because the reporting of adolescent mental health problems, often used as a proxy of the central concept of "need for care,"13 is known to differ by informant. Parents play an important role in the help-seeking process,14,15 not only because of parents’ legal responsibilities toward their child, but also because adolescents generally remain dependent on their parents for material support. At a young age, children play a very limited role in the help-seeking process; their ability to recognize mental health problems and a need for care have been found to be unrelated to service use.14 As adolescents strive for more autonomy as part of maturation and increasingly turn to their peers rather than their parents for support,15 adolescents’ own role in the help-seeking process increases. Teachers are likely to play an important role in the help-seeking process in childhood and early adolescence because they generally have close contact with the children in their class in primary education.16 Their role decreases in secondary education because they have to divide their attention over many more adolescents as they teach multiple classes.17
To date, most studies in which adolescent mental health care use was predicted using problem reports from multiple informants included only 2 of the 3 possible informants,18,19 combined measures from multiple informants,20 or both.21,22 Only a few studies have included assessments from all 3 informants simultaneously,17,20,23 thereby leaving unknown the relative importance of each of these informants for mental health care use in adolescence.
The influence of adolescents, parents, and teachers in the help-seeking process may vary over time, but studies that examined help-seeking longitudinally are scarce.19,23,24 Laitinen-Krispijn et al24 showed that parent-reported mental health problems at ages 10-12 years consistently predicted initial specialist care up to the age of 16. They assessed mental health problems only at baseline, however. Similarly, Zwaanswijk et al found that teacher-reported mental health problems were related to a need for care in childhood,16 but not in adolescence.17 However, since these conclusions were based on 2 cross-sectional studies, each with a wide age range, precisely how the role of teachers develops through adolescence remains uncertain. In conclusion, the currently available studies leave obscure the relative importance of adolescents, parents, and teachers in the help-seeking process and how this relative importance changes over time.
The aim of this study was to assess the relative importance of adolescents, parents, and teachers for help-seeking in adolescence and the extent to which the relative importance of each informant changes over time. Our study covered initial specialist mental health care use, hereafter referred to as specialist care, from preadolescence (age 9 years) to early adulthood (age 21 years). Specialist mental health care includes any kind of child, adolescent, and adult mental health care for which a referral is required. In The Netherlands, the general practitioner, preventive child health care, and the Office for Youth Care are primary care providers who can refer adolescents to specialist care.19 Register-based specialist care was predicted using up to 4 assessments of adolescents’ mental health. We differentiated between internalizing and externalizing problems25 because of their distinct differences with regard to development26 and recognition.27
- Adolescents are dependent on others for access to specialist mental health care, but it is unclear which individuals are most influential at different stages of adolescence.
- Teachers, parents, and adolescents themselves are the driving force behind initial specialist care at consecutive phases in adolescence.
- In addition to addressing the problems that drive help-seeking, clinicians should be aware of other problems that may arise in other settings.
The data used in this study were from the TRacking Adolescents’ Individual Lives Survey (TRAILS),28 a prospective population-based cohort study aimed at explaining the development of mental health from early adolescence into adulthood. The TRAILS sample, response rates, and study contents have been described in detail elsewhere.28-31 In short, after exclusion of children whose schools refused participation (n = 338) and children with serious mental or physical health problems or language difficulties (n = 210), informed consent to participate in the study was obtained for 2,230 children (76.0%; 51% girls). Nonresponse was related to being male, poor school performance, and low socioeconomic background, but not to teacher-reported levels of psychopathology.31
We used data from 4 consecutive assessment waves, which ran from March 2001 to July 2002 (T1; N = 2,230; 10-12 years), from September 2003 to December 2004 (T2; n = 2,149; 12-15 years), from September 2005 to August 2007 (T3; n = 1,816; 15-17 years), and from October 2008 to September 2010 (T4; n = 1,881; 18-20 years), respectively. Dropout was related to having a parent born in a nondeveloped country, low parental socioeconomic position, and parent-reported externalizing problems.29
The TRAILS data were linked to the Psychiatric Case Register North Netherlands (PCRNN; hereafter referred to as the register),32 which covered use of specialist child, adolescent, and adult mental health care organizations from January 2000 through December 2011. The catchment area of the register overlaps with the geographic area from which TRAILS participants were recruited. The register did not include primary (youth) mental health care, private practices, and commercial mental health care organizations. A comparison of register data with data from Statistics Netherlands33 showed that the register included 75% of all of child and adolescent mental health treatment trajectories in the north of The Netherlands.10 Consent to link the TRAILS database to the register was obtained from 1,698 adolescents and their parents (76.1%). A 95% likelihood matching procedure uniquely identified 447 adolescents with 1 record or more in the register (26.3%). One twin pair was excluded because data from the register could not be uniquely matched. Furthermore, the register contained only empty records from 48 matches.
We excluded a further 170 adolescents, of whom 62.4% had records in the register, because of parent-reported contact with specialist care before January 2000. The final sample hence contained 1,478 adolescents, of whom 293 (19.8%) had records in the register.
Adolescents who could not be included due to any cause of missing register data (n = 582) differed from included adolescents on variables that are traditionally associated with attrition (see Supplementary Table 1); they were more often male, of an ethnic minority, and attending special education; had a lower socioeconomic background; and had higher levels of parent- and teacher-reported problem behavior. By definition, adolescents with parent-reported specialist care before 2000 differed distinctly from those without it (see Supplementary Table 1); they were more often male, attending special education, and suffering from disadvantageous family characteristics and had higher levels of reported problem behavior. Furthermore, when only adolescents with records in the register were compared, adolescents with parent-reported specialist care before 2000 had their first record in the register much earlier than adolescents without it.
The study was approved by the Dutch Central Committee on Research Involving Human Subjects (CCMO) and was conducted according to the principles of the Declaration of Helsinki.
The outcome variable was initial contact with specialist care, indicated by the date of first entry in the register.
The predictor variables were internalizing and externalizing problems. At T1, T2, and T3, these problems were measured using the Youth Self-Report (YSR),34 Child Behavior Checklist (CBCL),34 and Teacher Checklist of Psychopathology (TCP).31 At T4, only the Adult Self-Report (ASR)35 was available. The YSR, CBCL, and ASR broadband scales of internalizing and externalizing problems included the withdrawn/depressed, anxious/depressed, and somatic complaints subscales and the aggressive behavior and delinquent behavior subscales, respectively. The TCP, which places a lower burden on teachers compared to the Teacher’s Report Form (TRF),34 consists of vignettes with descriptions of the problem behaviors of the subscales covered by the TRF.
We included a number of covariates that have been related to help-seeking in prior TRAILS studies and that either could be assumed constant throughout adolescence or were measured consistently over time: sex, age at parental separation, lifetime parental internalizing and externalizing problems at T1, and parental socioeconomic position at T1.12,19,36-38 Parental internalizing (depression and anxiety) and externalizing (substance abuse and antisocial behavior) problems were assessed using the Brief TRAILS Family History Interview, administered as part of the parent interview at baseline.37,39 Each syndrome was assessed using a vignette describing its main DSM-IV characteristics, followed by questions regarding occurrence, treatment, and medication (or, in case of antisocial behavior, police arrest and criminal record). For each syndrome, each parent was assigned to 1 of the following categories: "No" (0); "Yes" (1); or "Yes, and treatment and/or medication or police arrest and/or criminal record" (2). Syndromes were combined into measures of familial vulnerability for internalizing and externalizing problems separately using a weighted sum score. Weights were based on path coefficients for genetic risk factors found by Kendler et al.40 Following Veenstra et al,37 we calculated familial vulnerability for internalizing problems as 0.54 ×— (depression mother + depression father) + 0.43 ×— (anxiety mother + anxiety father) and familial vulnerability for externalizing problems as 0.61 ×— (substance abuse mother + substance abuse father) + 0.47 ×— (antisocial behavior mother + antisocial behavior father). We also included a dummy variable for being 18 to 21 years old as a proxy for the transition from child and adolescent to adult mental health care.41 Parental separation and being 18 to 21 years old were included as time-dependent covariates. We limited the number of covariates in our study because the evidence for many possible predictors of help-seeking is very inconsistent.42-44
Complete data were available from 25.7% of the included adolescents. The proportion of missing values ranged from 0% to 59% per variable, with variables from later waves typically having higher proportions of missing values (see Supplementary Table 2). Overall, 10.7% of all data points were missing. We used multiple imputation45 to generate 50 complete datasets using predictive mean matching. The imputation model contained the exposures and covariates from the analyses in addition to various auxiliary variables assessed at T1 (see Supplementary Table 1).
We used Cox regression analyses46 to test the relations between self-, parent-, and teacher-reported internalizing and externalizing problems and initial specialist care. First, we estimated the unadjusted effects for each predictor with a Cox regression analysis. All reports of problem behavior from the same type were entered into the Cox regression analysis simultaneously for each informant separately (eg, self-reported internalizing problems at ages 11, 13, 16, and 19 years), as reports from different waves never predicted specialist care at the same time point. Thereafter, we estimated fully adjusted effects by including the sociodemographic covariates and all reports of internalizing and externalizing problems in one Cox regression analysis. In general, problems reported at wave T were modeled as predictors of initial specialist care between waves T and T + 1. Initial specialist care between T4 and December 31, 2011, was predicted only by self-reported problems at T4. Data were censored if participants had moved out of the area covered by the register or if they had had no contact with specialist care by December 31, 2011. Continuous measures were standardized to mean = 0 and SD = 1. We used Kaplan-Meier plots47 to illustrate the relationship between internalizing and externalizing problems and initial specialist care for each informant. The analyses were conducted using SPSS version 23.0.48
The annual incidence of specialist care fluctuated around 1.5% from ages 10 to 14 years, increased to around 2.3% from ages 14 to 17 years, and varied between 1.3% and 2.2% from ages 17 to 21 years.
Results from the Cox regression analyses are shown in Table 1. Unadjusted, all but 2 measures of self-, parent-, and teacher-reported problems were associated with initial specialist care. These unadjusted associations are illustrated in Figure 1 (internalizing problems) and Figure 2 (externalizing problems). Hazard ratios for internalizing problems were typically larger than for externalizing problems. In the fully adjusted model, all effects for externalizing problems lost significance. Regarding internalizing problems, the informant who best predicted initial specialist care shifted over time. Teacher reports predicted initial specialist care mainly from ages 11 to 13 years and to a lesser extent from ages 13 to 16 years. Parent reports predicted initial specialist care mainly from ages 13 to 16 years. Self-reports predicted initial specialist care mainly from ages 16 to 19 years and from ages 19 to 21 years.
Boys were more likely than girls to enter into specialist care around the age of 10 years, but this relation reversed over time. Experiencing a parental separation and coming from a low or middle socioeconomic background increased the risk of entering into specialist care, as did internalizing problems of the parents. Finally, the hazard of entering into specialist care between the ages of 18 to 21 years was halved compared to between the ages of 9 to 17 years.
Post hoc Analyses
To better understand our findings, we re-estimated the effects for each informant separately while simultaneously including internalizing and externalizing problems as well as the effects for internalizing and externalizing problems separately while simultaneously including all 3 informants (see Supplementary Table 3). All effects were adjusted for sociodemographic covariates. The analyses for each informant separately showed that although the effects of externalizing problems often remained statistically significant, these were considerably weaker than the effects of internalizing problems. The analyses for internalizing and externalizing problems separately both showed the same temporal pattern as was found in the full model.
In a second post hoc analysis, we included the 170 children with parent-reported specialist care before 2000 (see Supplementary Table 4). Differences were negligible compared to the effects reported in Table 1. Most notably, externalizing problems remained unassociated with initial specialist care in the fully adjusted model.
To account for the possibility that specialist care was initiated for attention problems rather than externalizing problems, we added self-, parent-, and teacher-reported attention problems in a third post hoc analysis (see Supplementary Table 5). Attention problems did not predict initial specialist care, and the hazard rates of internalizing and externalizing problems were only fractionally lower compared to those reported in Table 1.
Overall, the post hoc analyses support the substantive conclusions.
This study contributes to the literature on determinants of help-seeking in adolescence because of 2 unique features: (1) it combined assessments of mental health from the perspectives of adolescents themselves, their parents, and their teachers, and (2) it used successive measurements of mental health at ages 11, 13, 16, and 19 years. The data were linked to administrative records of specialist care. Initial specialist care at ages 11 to 13, 13 to 16, and 16 to 19 years was predicted best by teacher-reported internalizing problems at age 11 years, parent-reported internalizing problems at age 13 years, and self-reported internalizing problems at age 16 years, respectively. Furthermore, externalizing problems no longer predicted initial specialist care at any age once we adjusted for internalizing problems.
When interpreting these findings, one must take 3 important limitations into consideration. First, parent and teacher ratings of problem behavior were not available at age 19. The effects of self-reported problem behavior at age 19 on initial specialist care at ages 19-21 may therefore have been overestimated. Second, almost a quarter of TRAILS participants did not consent to link their data to the case register, partially due to attrition. Although attrition is typically higher in vulnerable participants, TRAILS has been successful in retaining many vulnerable participants.29 Furthermore, the absence of consent was not related to the presence of DSM-IV disorders.10 Nevertheless, the predictive value of problem behavior on initial specialist care may have been underestimated. Third, not all providers of specialist care were covered by the PCRNN. While covered services probably provided all the care that noncovered services provided, we expect that covered services additionally provided care for more severe and rare conditions. As adolescents may have used a noncovered service prior to being referred to a covered service, the recorded date of initial contact may have been too late. This would have led to conservative effect estimates overall, but not to systematic biases in the effect estimates of any informant or problem type in particular. With regard to care that is provided by both covered and noncovered services, we expect that the choice for a particular provider is mostly affected by factors that are unlikely to be associated with coverage by the PCRNN, such as proximity.49 Specific information regarding these factors was not available in our data.
Internalizing and externalizing problem behavior reported by adolescents, parents, and teachers independently predicted initial specialist care from preadolescence through late adolescence. Once the effects of internalizing and externalizing problems were adjusted for each other and for sociodemographic correlates, 2 important patterns emerged.
First, externalizing problems no longer predicted initial specialist care for any of the informants at any age. In childhood, help-seeking is more often initiated for externalizing than for internalizing problems because the most incident externalizing problems, such as oppositional defiant disorder and conduct disorder, are more disturbing to and therefore easier to recognize by the social environment50 than the most incident internalizing problems, such as separation anxiety disorder and phobias. In adolescence, conversely, help-seeking is probably more often initiated for internalizing than for externalizing problems. The type of externalizing problems that may develop changes over time, from disruptive behavior in childhood to delinquency and substance use in adolescence.51 Behavior problems in childhood are often a precursor for externalizing problems in adolescence,3 and thus many adolescents with externalizing problems may have entered into specialist care already in childhood. If not, they are unlikely to enter into specialist care in adolescence, because delinquency may lead to police contact rather than specialist care. This is illustrated by a study by Farmer et al,52 who showed that, after school-based services, specialist mental health care was the second most common entry into mental health care for youth up to age 13, whereas juvenile justice was the second most common entry into mental health care for youth between the ages of 14 and 16. In a Finnish register-based study,53 youth crime was found to be predominantly associated with antisocial personality disorder (for which evidence of conduct disorder before the age of 15 is a prerequisite according to the DSM-IV54) and substance use disorders. Help-seeking for substance use is uncommon in adolescence.11,12,41,55 More generally, denial of externalizing problems has been shown to be a major barrier to care among young adults.56
Internalizing problems that are highly incident in adolescence include depression and generalized anxiety disorder, for which the proportions treated are higher and the time to treatment is shorter than for other common anxiety and behavior disorders.12 In adolescence, incident specialist care is therefore most likely due to internalizing problems. Externalizing problems very likely predicted initial specialist care when adjustment was not made for internalizing problems because both are moderately correlated25 and because behavior disorders often precede mood and anxiety disorders.3
An alternative explanation for our findings could be that adolescents enter into specialist care for attention problems. However, post hoc analyses showed that when attention problems were added, the patterns we found for internalizing and externalizing problems did not change. This result confirms the robustness of our findings. Furthermore, attention problems did not predict specialist care when adjustment was made for internalizing and externalizing problems. A likely explanation for these findings is that in The Netherlands, adolescents with attention problems are often treated by the general practitioner instead of being referred to specialist care.57
The second pattern that emerged from the analyses was that the relative importance of informants for best predicting initial specialist care shifted over time, from the teacher at the ages 11 to 13 years, to the parents at the ages 13 to 16 years, and to the adolescents at the ages 16 to 19 years. One should not conclude, however, that these informants do not influence the help-seeking process during the other stages in adolescence, but rather that each of these informants is the driving force behind initial specialist care at a particular stage. In early adolescence, teachers usually have close contact with the adolescents and their parents in primary education.17 Whereas parents may view certain symptoms of problem behavior as being part of their child’s nature and develop coping strategies that mitigate the need for treatment, teachers may recognize such symptoms as being deviant and requiring professional help. The school network is an important support system for preadolescents,14 which, apart from providing care itself, has also been shown to play an important role in the pathway to specialist care.16 Between the ages 13 to 16 years, the incidence of specialist care was best predicted by the parents. During this stage, the teachers’ influence may have declined because in secondary education adolescents typically have multiple teachers versus one main teacher in primary education.14,17 Concurrently, adolescents increasingly strive for autonomy, which is a major barrier to help-seeking.58 Even if adolescents are willing to seek treatment, they still need their parents’ compliance.14 Therefore, the parents remain as the most important actors for help-seeking. As the process of maturation continues, responsibilities continue to shift from parents to adolescents, thereby effectively leaving adolescents as the driving force behind entry into specialist care from the age of 16 years to the age of 21 years.
Regarding the sociodemographic covariates, one finding worth mentioning is that from the age of 18 years to the age of 21 years, the risk of entering into specialist care is halved compared to that from the age of 9 years to the age of 17 years . Although we cannot rule out the possibility that this decrease is partially caused by the availability of only self-reported problems at age 19, this finding may point to a lower overall inclination to seek help in early adulthood compared to adolescence.41
Our study contributes to the growing body of literature that addresses the wide treatment gap in mental health care.10-12,59 Internalizing problems are of particular interest due to their steep increase in incidence in adolescence.1,3 Teachers and parents are important for recognizing and seeking help for internalizing problems in early and middle adolescence despite the fact that internalizing problems are typically more difficult to recognize than externalizing problems.27 Given the importance of school-based services for entry into specialist care,14,16,60 the decreasing influence of teachers in middle adolescence is worrying. Strengthening the ties between teachers, parents, and adolescents may improve recognition in secondary education, thereby reducing the treatment gap in middle adolescence. The treatment gap is largest after the transition from late adolescence into early adulthood,41 most likely because during this transition young adults are switching between supportive networks by finishing education and leaving the parental home, but have not yet settled with a partner. A cost-effective means of enhancing problem recognition and help-seeking in youths, and thus reducing the treatment gap, could be provided by E-mental health.61,62 E-mental health refers to the use of information and communication technology for, among other activities, screening, health promotion, prevention, early intervention, and treatment in mental health care63 and is particularly suited for reaching young people, as the internet has become an integral part of their daily lives.64
Submitted: January 24, 2017; accepted November 28, 2017.
Published online: July 10, 2018.
Potential conflicts of interest: The authors report no biomedical financial interests or potential conflicts of interest.
Funding/support: TRAILS has been financially supported by various grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grant 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 452-04-314 and GB-MaGW 452-06-004; NWO large-sized investment grant 175.010.2003.005; NWO Longitudinal Survey and Panel Funding 481-08-013 and 481-11-001), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006), Biobanking and Biomolecular Resources Research Infrastructure BBMRI-NL (CP 32), and the participating universities (University Medical Center and University of Groningen, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in The Netherlands).
Role of the sponsor: The supporters had no role in the design, analysis, interpretation, or publication of this study.
Previous presentation: This research was presented orally at the 25th European Congress of Psychiatry (EPA 2017); April 1-4, 2017; Florence, Italy and at the 12th Congress of the European Network for Mental Health Service Evaluation (ENMESH 2017); October 5-7, 2017; Groningen, The Netherlands.
Acknowledgments: The authors are grateful to everyone who participated in this research or worked on this project to make it possible.
Supplementary material: Available at PSYCHIATRIST.COM.
2. Merikangas KR, He J-P, Burstein M, et al. Lifetime prevalence of mental disorders in US adolescents: results from the National Comorbidity Survey Replication-Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry. 2010;49(10):980-989. PubMed CrossRef
3. Ormel J, Raven D, van Oort F, et al. Mental health in Dutch adolescents: a TRAILS report on prevalence, severity, age of onset, continuity and co-morbidity of DSM disorders. Psychol Med. 2015;45(2):345-360. PubMed CrossRef
4. Whiteford HA, Degenhardt L, Rehm J, et al. Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010. Lancet. 2013;382(9904):1575-1586. PubMed CrossRef
6. Hofstra MB, van der Ende J, Verhulst FC. Child and adolescent problems predict DSM-IV disorders in adulthood: a 14-year follow-up of a Dutch epidemiological sample. J Am Acad Child Adolesc Psychiatry. 2002;41(2):182-189. PubMed CrossRef
7. Reef J, van Meurs I, Verhulst FC, et al. Children’s problems predict adults’ DSM-IV disorders across 24 years. J Am Acad Child Adolesc Psychiatry. 2010;49(11):1117-1124. PubMed
9. Ormel J, Oerlemans AM, Raven D, et al. Functional outcomes of child and adolescent mental disorders: current disorder most important but psychiatric history matters as well. Psychol Med. 2017;47(7):1271-1282. PubMed CrossRef
11. Merikangas KR, He J-P, Burstein M, et al. Service utilization for lifetime mental disorders in US adolescents: results of the National Comorbidity Survey-Adolescent Supplement (NCS-A). J Am Acad Child Adolesc Psychiatry. 2011;50(1):32-45. PubMed CrossRef
15. Logan DE, King CA. Parental facilitation of adolescent mental health services utilization: a conceptual and empirical review. Clin Psychol Sci Pract. 2001;8(3):319-333. CrossRef
16. Zwaanswijk M, van der Ende J, Verhaak PFM, et al. Help-seeking for child psychopathology: pathways to informal and professional services in the Netherlands. J Am Acad Child Adolesc Psychiatry. 2005;44(12):1292-1300. PubMed CrossRef
17. Zwaanswijk M, Van der Ende J, Verhaak PFM, et al. The different stages and actors involved in the process leading to the use of adolescent mental health services. Clin Child Psychol Psychiatry. 2007;12(4):567-582. PubMed CrossRef
18. Stanger C, Achenbach TM, McConaughy SH. Three-year course of behavioral/emotional problems in a national sample of 4- to 16-year-olds, 3: predictors of signs of disturbance. J Consult Clin Psychol. 1993;61(5):839-848. PubMed CrossRef
20. Achenbach TM, Howell CT, McConaughy SH, et al. Six-year predictors of problems in a national sample of children and youth, II: signs of disturbance. J Am Acad Child Adolesc Psychiatry. 1995;34(4):488-498. PubMed CrossRef
21. Verhulst FC, Koot HM, Van der Ende J. Differential predictive value of parents’ and teachers’ reports of children’s problem behaviors: a longitudinal study. J Abnorm Child Psychol. 1994;22(5):531-546. PubMed CrossRef
22. Achenbach TM, Howell CT, McConaughy SH, et al. Six-year predictors of problems in a national sample, IV: young adult signs of disturbance. J Am Acad Child Adolesc Psychiatry. 1998;37(7):718-727. PubMed CrossRef
24. Laitinen-Krispijn S, Van der Ende J, Wierdsma AI, et al. Predicting adolescent mental health service use in a prospective record-linkage study. J Am Acad Child Adolesc Psychiatry. 1999;38(9):1073-1080. PubMed CrossRef
25. Achenbach TM, Ivanova MY, Rescorla LA, et al. Internalizing/externalizing problems: review and recommendations for clinical and research applications. J Am Acad Child Adolesc Psychiatry. 2016;55(8):647-656. PubMed CrossRef
26. Rutter M, Caspi A, Moffitt TE. Using sex differences in psychopathology to study causal mechanisms: unifying issues and research strategies. J Child Psychol Psychiatry. 2003;44(8):1092-1115. PubMed CrossRef
27. De Los Reyes A, Kazdin AE. Informant discrepancies in the assessment of childhood psychopathology: a critical review, theoretical framework, and recommendations for further study. Psychol Bull. 2005;131(4):483-509. PubMed CrossRef
29. Nederhof E, Jörg F, Raven D, et al. Benefits of extensive recruitment effort persist during follow-ups and are consistent across age group and survey method: the TRAILS study. BMC Med Res Methodol. 2012;12(1):93. PubMed CrossRef
30. Ormel J, Oldehinkel AJ, Sijtsema J, et al. The TRacking Adolescents’ Individual Lives Survey (TRAILS): design, current status, and selected findings. J Am Acad Child Adolesc Psychiatry. 2012;51(10):1020-1036. PubMed CrossRef
31. de Winter AF, Oldehinkel AJ, Veenstra R, et al. Evaluation of non-response bias in mental health determinants and outcomes in a large sample of pre-adolescents. Eur J Epidemiol. 2005;20(2):173-181. PubMed CrossRef
36. Amone-P’ Olak K, Ormel J, Oldehinkel AJ, et al. Socioeconomic position predicts specialty mental health service use independent of clinical severity: the TRAILS study. J Am Acad Child Adolesc Psychiatry. 2010;49(7):647-655. PubMed CrossRef
37. Veenstra R, Lindenberg S, Oldehinkel AJ, et al. Bullying and victimization in elementary schools: a comparison of bullies, victims, bully/victims, and uninvolved preadolescents. Dev Psychol. 2005;41(4):672-682. PubMed CrossRef
39. Ormel J, Oldehinkel AJ, Ferdinand RF, et al. Internalizing and externalizing problems in adolescence: general and dimension-specific effects of familial loadings and preadolescent temperament traits. Psychol Med. 2005;35(12):1825-1835. PubMed CrossRef
40. Kendler KS, Prescott CA, Myers J, et al. The structure of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry. 2003;60(9):929-937. PubMed CrossRef
43. Ryan SM, Jorm AF, Toumbourou JW, et al. Parent and family factors associated with service use by young people with mental health problems: a systematic review. Early Interv Psychiatry. 2015;9(6):433-446. PubMed CrossRef
44. Zwaanswijk M, Verhaak PFM, Bensing JM, et al. Help seeking for emotional and behavioural problems in children and adolescents: a review of recent literature. Eur Child Adolesc Psychiatry. 2003;12(4):153-161. PubMed CrossRef
47. Kaplan E, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53(282):457-481. CrossRef
49. Zulian G, Donisi V, Secco G, et al. How are caseload and service utilisation of psychiatric services influenced by distance? a geographical approach to the study of community-based mental health services. Soc Psychiatry Psychiatr Epidemiol. 2011;46(9):881-891. PubMed CrossRef
50. Wu P, Hoven CW, Bird HR, et al. Depressive and disruptive disorders and mental health service utilization in children and adolescents. J Am Acad Child Adolesc Psychiatry. 1999;38(9):1081-1090, discussion 1090-1092. PubMed CrossRef
51. Loeber R. Development and risk factors of juvenile antisocial behavior and delinquency. Clin Psychol Rev. 1990;10(1):1-41. CrossRef
53. Elonheimo H, Niemel×¤ S, Parkkola K, et al. Police-registered offenses and psychiatric disorders among young males : the Finnish "From a boy to a man" birth cohort study. Soc Psychiatry Psychiatr Epidemiol. 2007;42(6):477-484. PubMed CrossRef
55. Garland AF, Aarons GA, Brown SA, et al. Diagnostic profiles associated with use of mental health and substance abuse services among high-risk youths. Psychiatr Serv. 2003;54(4):562-564. PubMed CrossRef
58. Wilson CJ, Deane FP. Brief report: need for autonomy and other perceived barriers relating to adolescents’ intentions to seek professional mental health care. J Adolesc. 2012;35(1):233-237. PubMed CrossRef
59. Kohn R, Saxena S, Levav I, et al. The treatment gap in mental health care. Bull World Health Organ. 2004;82(11):858-866. PubMed
Buy this Article as a PDF