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Developmental Relations Between Internalising Problems and ADHD in Childhood: a Symptom Level Perspective

Developmental Relations Between Internalising Problems and ADHD in Childhood: a Symptom Level... ADHD and internalising problems commonly co-occur with up to 50% of children diagnosed with ADHD also suffering from anxiety or depression. However, their developmental relations are currently not well understood. Longitudinal symp- tom level analyses can provide valuable insights into how difficulties in these areas of psychosocial functioning affect each other. Using Gaussian Graphical Models and Graphical Vector Autoregression Models, this study estimated cross-sectional and longitudinal networks of ADHD and internalising symptoms in 1387 children using parent- and teacher-reported Social Behaviour Questionnaires (SBQ) when children were aged 7, 9 and 11. Cross-sectional and longitudinal networks suggested that ADHD shares reciprocal relations with internalising symptoms through a number of potential bridge symptoms that are primarily connected to anxiety symptoms. High scores on child cannot sit still, is restless, or hyperactive were found to be the strongest bridge symptom acting as an antecedent to higher internalising symptoms whereas child is worried was the strongest antecedent for higher ADHD symptoms. Findings of this study highlight several potential bridge symptoms that may serve as key intervention targets and further emphasise the need for clinicians to assess children presenting with ADHD symptoms for internalising problems and vice versa. Keywords ADHD · Internalising problems · Longitudinal network modelling · Z-proso Attention Deficit Hyperactivity Disorder (ADHD) is one of relations (Jarrett & Ollendick, 2008). In addition, most studies the most common mental health issues in children, affecting investigating the co-occurrence of ADHD and internalising around 6.5% of youths worldwide (Polanczyk et al., 2015). problems have focused on clinical samples (Jarrett & ADHD frequently co-occurs with internalising problems, Ollendick, 2008). Since both ADHD and internalising with prevalence estimates in children ranging from 12 to symptoms have been shown to lie on a continuum within the 50% for co-occurring depression and from 15 to 35% for general population (Lubke et al., 2009; Tebeka et al., 2018), co-occurring anxiety (Gnanavel et  al., 2019). However, these studies should be complemented with community- relatively few studies have examined the links between ADHD based samples to provide a comprehensive picture of the links symptoms and internalising problems longitudinally, making between ADHD and internalising problems. it difficult to draw any conclusions on the direction of their Existing evidence on the longitudinal development of internalising problems and ADHD in normative samples suggests that they share reciprocal relations, with, for exam- * Lydia Gabriela Speyer ple, internalising problems leading to higher ADHD symp- lspeyer@ed.ac.uk tomatology and vice versa across mid- to late- adolescence Department of Psychology, Univsersity of Edinburgh, (Murray et al., 2020a, b). Less is known about their relations Edinburgh, UK before this period, which, in the context of the co-occurrence Violence Research Centre, Institute of Criminology, of ADHD and internalising symptoms, may be a particu- University of Cambridge, Cambridge, UK larly vulnerable period given that the median age-of-onset Jacobs Center for Productive Youth Development, University of internalising problems has been found to be at around age of Zurich, Zurich, Switzerland 11 (Kessler et al., 2005). ADHD typically manifests before Autism Research Centre, Department of Psychiatry, the age of 7 but often only gets diagnosed after school entry University of Cambridge, Cambridge, UK Vol.:(0123456789) 1 3 1568 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 as difficulties become more apparent in this setting (Sax serving as a means to describe a specific symptom network. & Kautz, 2003). Hence, to understand the etiology of co- This approach also allows for a more parsimonious under- occurring ADHD and internalising problems, it is of real standing of co-occurring mental health problems given that importance to understand the temporal and concurrent rela- symptoms between mental health disorders show substantial tions of ADHD and internalising symptoms in the period overlap (e.g. concentration difficulties are not only a symp- leading up to adolescence. tom of ADHD but also of depression) (American Psychiat- To date, the mechanisms that underlie the relations ric Association, 2013). Hence, symptom networks between between ADHD and internalising symptoms are still not different disorders are likely to be connected through spe- well understood. This is also partly due to limitations in cific symptoms. These connecting symptoms are commonly the methodology for analysing longitudinal panel data. referred to as ‘bridge symptoms’ and might act as the driv- Most longitudinal studies investigating the links between ing force in the development of a co-occurring disorder by ADHD and internalising problems (e.g. Obsuth et al., 2020) activating another symptom network (Borsboom & Cramer, have used modelling techniques such as cross-lagged panel 2013). This has important implications for clinical inter- models (CLPM), which conflate between- and within-person ventions. Knowing which symptoms might underlie the effects and thus provide ambiguous results regarding the development of another disorder allows for more targeted development of co-occurring mental health issues (Berry and consequently more effective interventions. To further & Willoughby, 2017). An alternative to traditionally used maximise the impact of potential interventions, it is further statistical techniques such as CLPMs are graphical vector crucial to know how these symptom networks change over autoregression (GVAR) models (Epskamp, 2020). GVAR development. In response to the emergence of the network models allow for the separation of within- and between- approach to psychopathology, a number of studies have esti- person effects and are consequently well suited to investigate mated cross-sectional symptom level networks (e.g. Beard dynamic relations between multiple mental health domains. et al., 2016; Rouquette et al., 2018; Silk et al., 2019), some GVAR models further have the advantage that they allow also examining how these symptom networks changed over for an intuitive visualisation and interpretation of complex time (e.g. Martel et al., 2016), and providing insights into results, making it possible to not only investigate the the structure of symptoms underlying mental health. How- relations between multiple mental health domains at the ever, while cross-sectional symptom networks can highlight domain level but also at the symptom level. potential bridge symptoms, they are limited in that they do Another factor that has thus far limited our understand- not give any information on direction of effects. Understand- ing of the links between ADHD symptoms and internalising ing the direction of effects is critical as this could inform problems has been the focus on the disorder level rather the etiology of psychopathology and enables interventions to than the symptom level. There has been some evidence that target the right symptoms at the appropriate time. To date, specific symptoms of internalising problems might be more there have been very few attempts to model the temporal relevant in their association with ADHD than others and relations between symptom networks, with the few stud- vice versa (Michelini et al., 2015). In particular, symptoms ies attempting to model them longitudinally suffering from of anxiety, such as excessive worrying, have been hypoth- similar limitations as domain level analyses. Funkhouser esised to put additional drain on attentional resources, lead- et al. (2020), for instance, used cross‐lagged panel network ing to inattentive behaviour (Zainal & Newman, 2020). On analysis to analyse symptoms of internalising, externalis- the other hand, attention problems might make it more dif- ing and attention symptoms over two time points, which ficult to shift attention away from ruminative thoughts and like CLPMs, conflates within- and between-person effects. thus exacerbate internalising symptoms (Mitchell et  al., Thus, there is a clear need for more appropriate modelling 2013). Thus, some symptoms might be more important in of longitudinal symptom networks. the relations between ADHD and internalising problems, An additional limitation of many studies on the devel- making them priority intervention targets. To identify these opmental relations of different mental health issues stems symptoms, symptom level analyses are needed. Indeed, from the fact that they often rely on a single informant to symptom level analyses have recently gained in popularity measure children’s socio-emotional functioning. Evidence due to a shift in the understanding of mental health disor- from cross-informant studies indicates that different inform- ders that has resulted in the development of the network ants only show small-to-moderate degrees of convergence in approach to psychopathology (Borsboom, 2008). Rather their assessment of children’s mental health, especially when than conceptualising mental health disorders as a collection these informants experience children in different contexts of symptoms caused by a unitary underlying abnormality, (e.g. home or school) (Murray et al., 2007, 2018). Conse- the network approach to psychopathology views mental quently, studies investigating children’s mental health should health disorders as dynamic networks of multiple mutually replicate their findings based on assessments from at least reinforcing symptoms with taxonomic classifications only one other informant. This is particularly relevant in the study 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1569 of ADHD as, according to the DSM-5 diagnostic criteria, ADHD symptoms were available from parents and teachers. a diagnosis is only warranted if individuals show difficul- At the age 7 wave, data was available for 1370 youths, at ties in at least two different settings (American Psychiatric the age 9 wave for 1321 and at the age 11 wave for 1147 Association, 2013). youths. All children who had data on internalising symptoms In the current study, we investigate the developmental and ADHD for at least one time-point from at least one relations of internalising symptoms and ADHD symptoms informant were included in the current study, resulting in a in a large community-based study of N = 1387 children. final sample of 1387 children (51% male). Symptoms of anxiety, depression, inattention and hyper- The z-proso study obtained ethical approval from the activity/impulsivity were measured at median-ages 7, 9 Ethics Committee from the Faculty of Arts and Social Sci- and 11 using parent-reported Social Behaviour Question- ences of the University of Zurich. Parents provided active naires (SBQ). Using Gaussian Graphical Models (GGM) informed consent for children to participate in the study. For and Graphical Vector Autoregression Models, we estimate additional details regarding recruitment, retention, and attri- cross-sectional as well as longitudinal symptom networks tion, see elsewhere (Eisner & Ribeaud, 2007; Eisner et al., of ADHD and internalising problems to gain new insights 2019) and the z-proso website (https:// www. jacob scent er. into concurrent and temporal relations of symptoms bridging uzh. ch/ en/ resea rch/ zproso/ about us. html). ADHD and internalising problems. To evaluate the stabil- ity of our results across informants, we further replicate all cross-sectional models using teacher-reported SBQs. As this Measures is the first study to investigate the symptom-level relations of ADHD symptom and internalising problems longitudinally, Symptoms of ADHD and internalising problems were we took an exploratory approach. measured using parent- and teacher-reported versions of the Social Behaviour Questionnaire (SBQ; Tremblay et al., 1991). The SBQ is an omnibus measure of psychopathol- Methods ogy and measures children’s psychosocial functioning across five areas: ADHD, anxiety/depression, aggression, Participants non-aggressive externalizing problems, and prosocial behav- iour. At ages 7, 9 and 11 in the z-proso study, SBQs were Participants in this study were part of the Zurich Project on completed by parents and teachers and included four items Social Development from Childhood to Adulthood (z-proso), each on symptoms of inattention, hyperactivity/impulsivity, a longitudinal study based in Zurich, Switzerland, that has and depression, as well as three items on symptoms of anxi- been tracking the development of an initial target sample of ety. Items were rated on a 5-point Likert scale from Never 1675 children from 2004 when the children entered school at to Very Often. SBQs were administered using a German age 7. Children were recruited based on a stratified sampling translation of the original SBQ which teachers completed design whereby 56 public primary schools in Zurich were in the form of a paper-and-pencil questionnaire while parents selected based on school size and location. Participants were took part in a computer-assisted personal interview that was ethnically diverse with only 39.6% of primary caregivers available in an additional nine languages for non-German being native speakers of the official language of Zurich, that speaking participants. For English phrasings of the items is German, after which the most frequently spoken native used in this study see Table 1. While self-reported SBQs languages were Serbian/Bosnian/Croatian (10%), Albanian were also available, those were not used in the current study (9%), Portuguese (7%) and Tamil (5.3%) (Eisner et  al., as they were collected in the form of an adapted computer- 2019). To maximize engagement of the non-German-native based multimedia version of the SBQ with children answer- speakers, contact letters as well as parent interviews were ing ‘yes’ or ‘no’ to a series of questions relating to their made available in the in the ten most commonly spoken psycho-social development. Psychometric analyses of the languages. Of the children’s male primary caregivers who SBQ have found support for factorial validity, developmental contributed to the first wave of data collection, 76.7% invariance and criterion validity of the SBQ items across were in full-time employment (8.8% unemployed), with various waves of the z-proso study (Murray et al., 2017, 16% having a university-level education, 15.5% a higher 2020a, b). The SBQ has further been shown to be a reliable vocational education 7.8% A-levels, 35.2% apprenticeship measure of moderately low to very high levels of internalis- and 21% mandatory school or less (Murray et al., 2016). To ing and ADHD symptoms in the general population (Murray date, there have been ten waves of data collection at ages 7 et  al., 2019). Descriptive Statistics as well as correlation to 13, 15, 17 and most recently at age 20 with data collection tables of all SBQ items included in the current study are still ongoing. This study uses data from waves at median- available online (Table S1 in the supplementary and excel ages 7, 9 and 11 at which the same items on internalising and files E1 and E2). 1 3 1570 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Table 1 ADHD and Item Domain Item Content Internalising Problems Items 02 (NER) Anxiety < CHILD > is nervous, high-strung or tense 03 (ANX) Anxiety < CHILD > is too fearful or anxious 04 (WOR) Anxiety < CHILD > is worried 05 (DEP) Depression < CHILD > seems to be unhappy, sad, or depressed 06 (NHA) Depression < CHILD > is not as happy as other children 07 (TEN) Depression < CHILD > has trouble enjoying him\herself 08 (DIS) Depression < CHILD > appears miserable, distressed, or unhappy 10 (IMP) Hyperactivity/impulsivity < CHILD > is impulsive, acts without thinking 11 (DWA) Hyperactivity/impulsivity < CHILD > has difficulty a waiting turn in games or groups 12 (RES) Hyperactivity/impulsivity < CHILD > cannot sit still, is restless, or hyperactive 13 (FID) Hyperactivity/impulsivity < CHILD > fidgets 14 (CSE) Inattention < CHILD > cannot settle to anything for more than a few moments 15 (DTB) Inattention < CHILD > is distractible, has trouble sticking to any activity 16 (CON) Inattention < CHILD > cannot concentrate, cannot pay attention for long 17 (INA) Inattention < CHILD > is inattentive using the panelgvar() function of the R package psychon- Statistical Analyses etrics (Epskamp, 2020). GVAR models describe variables that have been measured at several time points as a function To improve our understanding of the concurrent relations of their own past values or as a combined function of their between symptoms of ADHD and internalising prob- own as well as other variables’ past values, allowing insights lems, a series of cross-sectional networks was estimated into temporal as well as concurrent relations between several using Gaussian Graphical Models (GGM). For each time repeatedly measured variables (Wild et al., 2010). These point (ages 7, 9 and 11), separate networks for parent- and temporal and concurrent relations can be visualised using teacher-reported symptoms were built. GGMs use partial GGMs that include directed edges to visualise temporal rela- correlations to intuitively visualise the complex depend- tions and undirected edges to visualise concurrent relations. ence structures of a system of variables. In GGMs, vari- If the data includes a multilevel structure, GVAR models ables are represented by nodes that are connected through also estimate cross-sectional between-person differences directed (temporal network) or undirected (contemporaneous across time, which enables the separation of within- from network) edges which visualise the relations between vari- between-person effects (Epskamp, 2020). This separation ables (Epskamp et al., 2018a, b). Edge weights (w) quan- is critical since between-person effects, which describe tify the strength of the association in the form of partial how someone’s average on a specific symptom compares to correlations. Networks were estimated using the R package someone else’s average on another symptom, act as a con- qgraph (Epskamp et al., 2012) which implements graphi- found when the interest lies on investigating within-person cal LASSO (least absolute shrinkage and selection opera- effects. Within-person effects describe individuals’ devia- tor) regularization in combination with Extended Bayesian tions from their own average symptom levels and can give Information Criterion (EBIC) as model selection criterion insights into whether high- or low-levels on one symptom to estimate a sparse network structure (Epskamp & Fried, influence that same person’s levels on another symptom. 2018). Using the R-package bootnet (Epskamp et al., 2018a, Investigating within-person effects is critical as they can b), 95% Confidence Intervals (CIs) for edge weights were give insights into the mechanisms that might underlie the obtained through bootstrapping routines (N = 1000). Lastly, associations between two symptoms and represent the prime cross-sectional networks at different time points as well as target for interventions (Hamaker et al., 2015). Structurally, parent- and teacher-reported models were compared using GVAR models are closely related to the Random-Intercept permutation based Network Comparison Tests (NCT) which Cross-lagged Panel Model (RI-CLPM) which separates offer information on whether networks differed in global within- from between-person effects by partialling out sta- network strength (S: sum of all edge weights; DiffS: Differ - ble-between person differences through random intercepts ence in S between two networks) and in network structure for each repeatedly measured variable that are allowed to co- (M) (Van Borkulo et al., 2015). vary (Hamaker et al., 2015). In contrast to RI-CLPMs which To analyse the longitudinal relations between ADHD model the within- and between-person covariance structures and internalising symptoms, a Graphical Vector Autore- as marginal variance–covariance matrices, GVAR models, gression (GVAR) model was built for parent-reported data 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1571 however, model these as GGMs. Also, to avoid the need to symptoms from other domains (see Fig. 1). Internalising for estimating a variance–covariance structure for the first domains (i.e., anxiety and depression) and ADHD domains measurement point, GVAR models assume stationary rela- (i.e., hyperactivity/impulsivity and inattention) also formed tions, thus, unlike RI-CLPMs, they treat the first measure- distinct clusters. At every time point, these clusters were ment wave as endogenous (Epskamp, 2020). connected through links between item 13 (FID, Child d fi gets) Before building the GVAR models, data was detrended from the hyperactivity/impulsivity domain and item 2 (NER, for linear age-related effects and standardised across time Child is nervous, high-strung or tense) from the anxiety points to meet the stationarity assumption of GVAR mod- domain. At age 7, item 2 further shared an edge with item 12 els. This was considered appropriate for the current analy- (RES, Child cannot sit still, is restless, or hyperactive) from ses because only the correlational structure and not the the hyperactivity/impulsivity domain. Bridge influence indi- mean structure was of interest. In order to appropriately ces confirmed these visual findings (see Table  2). Pairwise account for missing data, the GVAR model was fitted using NCTs indicated that network structures and global network Full Information Maximum Likelihood (FIML) estimation strength (S = 5.97, S = 6.06, S = 6.25) were invariant over 7 9 11 which provides unbiased estimates under the assumption time with all comparisons yielding p-values larger than 0.05 that data is missing at random (Enders, 2001). To mini- (M = 0.10. M = 0.12, M = 0.10; DiffS = 0.10, 7vs9 7vs11 9vs11 7vs9 mise the chance of finding false positives and to reduce DiffS = 0.28, DiffS = 0.19). Results of bootstrapping 7vs11 9vs11 the model’s complexity, the model was further regularised routines indicated that edges between bridge symptoms were (i.e., constrained to only include the most important edges) moderately stable. Confidence intervals quantifying the using Bayesian Information Criterion (BIC) as model selec- uncertainty associated with all estimated edges are presented tion criterion. Overall model fit was judged using the fol- in the online supplementary Tables S2—S4. lowing relative fit indexes: Comparative Fit Index (CFI), Tucker Lewis Index (TLI) and Root Mean Square Error of Cross‑Sectional Teacher‑Reported Networks Approximation (RMSEA) with CFI > 0.90, TLI > 0.90 and RMSEA < 0.05 used as cut off cr iteria indicating reason- Networks based on teacher-reports showed similar patterns ably good fit (Kline, 2005). Due to computational limitation, to parent-reports with symptoms from the same domains bootstrapping routines could not be employed for the GVAR forming distinct clusters (see Fig. 1). In line with the parent- model. Unfortunately, replicating the parent-reported GVAR reported networks, pairwise NCTs indicated that network model using teacher-reported SBQs was also not possible structures and global network strength were invariant over as GVAR estimations failed due to numerical optimiza- time (M = 0.10. M = 0.15, M = 0.12; S = 0.19, 7vs9 7vs11 9vs11 7vs9 tion issues likely caused by very high correlations (> 0.90) S = 0.24, S = 0.05). With regards to bridge symp- 7vs11 9vs11 between some teacher-reported SBQ items. Given the com- toms, teacher-reported networks also identified anxiety putational complexity involved in t fi ting GVAR models, this item 2 (NER, Child is nervous, high-strung or tense) and is not unexpected. ADHD items 12 (RES, Child cannot sit still, is restless, or All estimated networks were visualised using the hyperactive) and 13 (FID, Child fidgets), as potential bridge Fruchterman-Reingold algorithm in the qgraph package symptoms. However, they further highlighted a number of which places nodes sharing stronger connections closer additional connections bridging the internalising and ADHD together (Epskamp et al., 2012). For cross-sectional net- domains. In particular, item 2 (NER, Child is nervous, high- works, the network layout was kept constant (using average strung or tense) was connected to all symptoms of the hyper- layout of all networks) to facilitate comparisons. To iden- activity/impulsivity domain in the age 7 and age 9 networks, tify the most influential bridge symptoms, bridge influence while only sharing edges with item 10 (IMP, Child is impul- indices were estimated using the R package networktools, sive, acts without thinking) and 12 (RES, Child cannot sit giving insights into the direct and indirect influence of spe- still, is restless, or hyperactive) in the age 11 network. The cific bridge symptoms on symptoms from the other area of age 7 network further highlighted a connection between the psychosocial functioning (Jones et al., 2019). inattention and depression domains through item 17 (INA, Child is inattentive) and item 6 (NHA, Child is not as happy as other children). At age 11, item 17 was connected to item Results 8 (DIS, Child appears miserable, distressed, or unhappy) instead of item 6. In addition, item 14 (CSE, Child cannot Cross‑sectional Parent‑Reported Networks settle to anything for more than a few moments) shared an edge with item 5 (DEP, Child seems to be unhappy, sad, All parent-reported cross-sectional networks showed clus- or depressed). For bridge influence indices, see Table  2. ters on the domain level with symptoms being more closely The higher connectivity of the teacher-reported networks connected to other symptoms from their own domain than was also reflected in higher values for global network 1 3 1572 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Fig. 1 Cross-sectional partial correlation networks for parent- and ous, ANX: anxious, WOR: worried; DEP: depressed, NHA: not as teacher-reported symptoms at ages 7, 9, and 11. Green edges (solid happy as other children, TEN: trouble enjoying themselves, DIS: dis- lines) indicate positive effects; red edges (dashed) indicate negative tressed, IMP: impulsive, DWA: difficulty awaiting turns, RES: rest - effects. Upper row (a, b, c) represents parent-reported networks, less, FID: fidgets, CSE: cannot settle to anything, DTB: distractible, lower row (d, e, f) represents teacher-reported networks. NER: nerv- CON: cannot concentrate, INA: inattentive strength compared to parent-reported networks (S 7.24, to edges bridging ADHD and internalising domains, hyper- 7= S = 7.43, S = 7.48). NCTs showed that these differences activity/impulsivity items 10 (IMP, Child is impulsive, acts 9 11 were significant at each time point (p < 0.001; DiffS = 1.27, without thinking) and 12 (RES, Child cannot sit still, is DiffS = 1.36, DiffS = 1.22). Network structures were restless, or hyperactive) had positive temporal effects on 9 11 also found to be significantly different for parent- and internalising symptoms from the depression and anxiety teacher-reported networks (p < 0.001; M = 0.30. M = 0.34, domains respectively, while items 15 (DTB, Child is dis- 7 9 M = 0.31). Similar to the parent-reported networks, estimates tractible, has trouble sticking to any activity) and 16 (CON, for edges between bridge symptoms based on teacher-reports Child cannot concentrate, cannot pay attention for long) were moderately stable. For confidence intervals, see Tables from the inattentive domain were associated with increased S2 – S4 in supplementary materials. anxiety symptoms. Regarding the effects of internalising on ADHD symptoms, item 4 (WOR, Child is worried) from the Longitudinal Parent‑Reported Network anxiety domain had positive temporal effects on inattentive ADHD symptoms and items 6 (NHA, Child is not as happy The saturated parent-reported GVAR model showed good fit as other children), and 8 (DIS, Child appears miserable, (CFI = 0.96, TLI = 0.95, RMSEA = 0.028 with 90% CI: 0.026 distressed, or unhappy) from the depression domain were to 0.030). The regularised model performed slightly bet- associated with increased hyperactivity/impulsivity ADHD ter than the saturated model (∆BIC = 1696.74; CFI = 0.94, symptoms. Interestingly, except for one direct link between TLI = 0.93, RMSEA = 0.032 with 90% CI: 0.030 to 0.034). ADHD symptom 10 (IMP, Child is impulsive, acts without Overall, the temporal network indicated that, at the within- thinking) and depression item 8 (DIS, Child appears mis- person level, most symptoms affected other symptoms over erable, distressed, or unhappy), ADHD symptoms mostly time, though symptoms shared more and stronger connec- had positive directional effects on anxiety items. These tions with symptoms from the same domain. With regards in turn shared directional links with depression items, 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1573 Table 2 Bridge Influence Indices for Cross-Sectional Networks Parent-Report: Age 7 Parent-Report: Age 9 Parent-Report: Age 11 Item Direct Influence Indirect Influence Direct Influence Indirect Influence Direct Influence Indirect Influence 02 0.21 0.33 0.09 0.15 0.13 0.20 03 - 0.03 - 0.01 - 0.02 04 - 0.04 - 0.02 - 0.03 05 - - - - - - 06 - - - - - - 07 - - - - - - 08 - - - 0.01 - 0.01 10 - - - 0.01 - 0.02 11 - - - - - - 12 0.11 0.20 - 0.04 - 0.06 13 0.09 0.18 0.09 0.13 0.13 0.18 14 - - - - - - 15 - 0.01 - 0.01 - - 16 - 0.01 - - - - 17 - - - - - - Teacher-Report: Age 7 Teacher-Report: Age 9 Teacher-Report: Age 11 Item Direct Influence Indirect Influence Direct Influence Indirect Influence Direct Influence Indirect Influence 02 0.33 0.59 0.32 0.55 0.23 0.43 03 - 0.05 - 0.05 - 0.04 04 -.04 0.01 - 0.10 - 0.09 05 - 0.03 - - 0.04 0.09 06 0.05 0.08 - - - 0.02 07 - 0.02 - - - 0.01 08 - 0.01 - - 0.05 0.10 10 0.11 0.20 0.10 0.19 0.14 0.22 11 0.06 0.15 0.10 0.20 - 0.09 12 0.09 0.10 0.04 0.15 0.09 0.15 13 0.11 0.17 0.09 0.14 - 0.06 14 - 0.01 - 0.01 0.04 0.10 15 - 0.01 - 0.01 - 0.03 16 - 0.02 - - - 0.03 17 0.05 0.12 - 0.01 0.05 0.10 Bridge influence indices were derived from edge weights (partial correlations) in the respective cross-sectional network model. Direct influence: sum of all edge weights that exist between a node X and all nodes that are not part of the same cluster as node X (i.e. either ADHD or internalis- ing). Indirect influence: direct influence plus indirect effects of Node X through other nodes (e.g. indirect effect on node Z as in X—Y—Z) indicating that anxiety symptoms potentially mediate the indicated that anxiety item 4 (WOR, Child is worried) relations between ADHD and depression symptoms. Out of shared particularly many relations with items from both all symptoms, bridge influence indices (Table  3) indicated ADHD domains, thus, suggesting that at the within-person that ADHD item 12 (RES, Child cannot sit still, is restless, levels, children with higher symptoms of worrying also tend or hyperactive) from the hyperactivity/impulsivity domain to have higher ADHD symptoms at the same time-point. had the strongest direct influence on internalising symptoms, The between-person network (visualised in Figure S2, avail- mainly from the anxiety domain, and internalising item 4 able online) indicated that children who have high scores (WOR, Child is worried) from the anxiety domain had the on anxiety item 2 (NER, Child is nervous, high-strung or strongest direct influence on ADHD symptoms, mainly from tense), tended to also have higher scores on hyperactive/ the inattention domain. The temporal within-person net- impulsive ADHD symptoms compared to children who had work is visualised in Fig. 2. The contemporaneous network, lower scores on item 2 (NER, Child is nervous, high-strung which is visualised in Figure S1 in the online supplementary, or tense). Overall, the between-person network showed 1 3 1574 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Table 3 Bridge Influence Indices for the Parent-Reported Temporal high-strung or tense’ from the anxiety domain. On the GVAR Network temporal level, anxiety item ‘Child is worried’ was the strongest direct antecedent of higher ADHD symptoms Item Out-Strength In-Strength Direct Influence Indirect Influence and item ‘Child cannot sit still, is restless, or hyperactive’ was the strongest direct antecedent of higher internalising 02 - 0.10 - 0.03 symptoms. 03 - 0.06 - 0.02 In line with previous studies using cross-sectional 04 0.13 - 0.13 0.17 symptom networks (Beard et al., 2016; Silk et al., 2019), 05 0.04 - 0.04 0.09 our results indicated that items from the same domain (i.e. 06 0.09 - 0.09 0.12 anxiety, depression, hyperactivity/impulsivity, inattention) 07 - - - 0.01 formed relatively distinct clusters with internalising domains 08 0.06 0.05 0.06 0.07 and ADHD domains clustering more closely together. Nev- 10 0.06 - 0.05 0.07 ertheless, all cross-sectional networks highlighted that these 11 - - - - internalising and ADHD symptom clusters are connected to 12 0.06 0.09 0.06 0.08 each other through items from the anxiety and the hyperac- 13 - 0.06 - 0.02 tivity/impulsivity domain, supporting the conceptualisation 14 - 0.06 - 0.01 of co-occurring psychopathology as connected networks of 15 0.05 - 0.05 0.11 symptoms. In particular, ADHD symptoms formed a bridge 16 0.05 0.07 0.05 0.08 to internalising symptoms through an association with how 17 - 0.04 - 0.01 often a child was nervous. Higher scores on items relating to Bridge influence indices were derived from edge weights (partial cor - restlessness and fidgeting were associated with higher scores relations) in the temporal GVAR model. Out-Strength: Sum of the on the nervousness item. Nervousness often goes hand in absolute values of out-degree edge weights (i.e. edges with a direc- hand with restlessness, making it a plausible bridge symp- tional arrow from node X to another node). In-Strength: Sum of the tom between anxiety and ADHD. Also, the fact that restless- absolute edge weights of in-degree edges (i.e. edges with a direc- tional arrow from another node to node X). Direct influence: sum of ness was part of the bridge to internalising problems is in all edge weights that exist between a node X and all nodes that are line with DSM-5 diagnostic criteria which lists restlessness not part of the same cluster as node X (i.e. either ADHD or inter- as a symptom of both ADHD and anxiety disorders (Ameri- nalising). Indirect influence: direct influence plus indirect effects can Psychiatric Association, 2013). of Node X through other nodes (e.g. indirect effect on node Z as in X—> Y—> Z). Since, these networks are directed, influence meas- Whereas cross-sectional models revealed bridges between ures only include out-degree edges symptom networks of ADHD and internalising problems, longitudinal models allowed insights into directional within- relatively little similarity with the within-person contempo- person relations between these symptoms over time. ‘Child raneous and temporal network, highlighting the necessity cannot sit still, is restless, or hyperactive’ was found to of appropriately disentangling within- from between-person have the strongest direct temporal influence on internalis- effects when within-person effects are of primary interest as ing symptoms overall, with higher scores preceding an in the context of mental health interventions. increase in the anxiety item ‘Child is too fearful or anx- ious’ while some items from the inattentive ADHD domain (‘Child is distractible, has trouble sticking to any activity’ Discussion and ‘Child cannot concentrate, cannot pay attention for long’) preceded higher scores on the anxiety item ‘Child In this study, we used graphical vector autoregression is nervous, high-strung or tense’. This suggests that, at the models to investigate the development of ADHD and inter- within-person level, anxiety symptoms may be exacerbated nalising symptom networks over time. This approach pro- by ADHD symptoms. Previous research has suggested that vides an important advance over cross-sectional symptom the development of co-occurring anxiety could be related to level networks as it allows for the estimation of directional the secondary effects of psychosocial difficulties associated relations that can improve our understanding of the devel- with ADHD such as low educational achievement and social opment of psychopathology and inform interventions. Our functioning deficits (Galéra et al., 2009). Consistent expo- results highlighted a number of potential bridge symptoms sure to such difficulties has wide ranging negative effects and between these areas of psychosocial functioning. On the has also been found to increase the risk of developing anxi- cross-sectional level, ADHD and internalising symptoms were ety problems (Bishop et al., 2019; Mazzone et al., 2007). primarily connected through item ‘Child cannot sit still, is Another contributing factor to the observed association of restless, or hyperactive’ and item ‘Child fidgets’ from the restlessness preceding anxiety could be that restlessness is in hyperactivity/inattention domain and ‘Child is nervous, fact an early sign of anxiety rather than an ADHD symptom 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1575 Fig. 2 Temporal network for parent-reported symptoms standard- enjoying themselves, DIS: distressed, IMP: impulsive, DWA: difficulty ised to directed partial correlations. Green edges (solid lines) indi- awaiting turns, RES: restless, FID: fidgets, CSE: cannot settle to any- cate positive effects. NER: nervous, ANX: anxious, WOR: worried; thing, DTB: distractible, CON: cannot concentrate, INA: inattentive DEP: depressed, NHA: not as happy as other children, TEN: trouble per se. Further research is needed to illuminate the reasons b). These findings are also consistent with the hypothesis for these associations. that one reason why some individuals only develop ADHD Examining the within-person longitudinal ee ff cts of inter - symptoms later in life is that these individuals have not been nalising symptoms on ADHD symptoms, results suggested exposed to the same environmental risk load as those who that the anxiety item ‘Child is worried, high-strung or tense’ develop symptoms early in life (Lunsford‐Avery & Kollins,  showed directional relations with inattentive symptoms. This 2018). These individuals showing increased ADHD symp- indicates that internalising symptoms potentially aggravate tom following anxiety symptoms may already be at risk of ADHD symptoms in middle childhood, adding to emerg- ADHD symptoms with anxiety acting as a triggering fac- ing evidence that ADHD and internalising problems share tor. Another potential mechanism underlying the observed reciprocal within-person relations (Murray et al., 2020a, temporal association of anxiety symptoms with inattentive 1 3 1576 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 symptoms is that anxiety inhibits the appropriate allocation Findings of the current study support current clinical best of working memory resources, negatively impacting execu- practice. In particular, results highlight the need for screen- tive functioning, and in turn leading to increased inattentive ing children who show high ADHD symptomatology also behaviour (Eysenck et al., 2007; Zainal & Newman, 2020). for internalising problems and vice versa, especially if they Similarly, the observed directional association may capture show symptoms of anxiety and for paying particular atten- the fact that worrying interferes with an individual’s concen- tion to the presence of bridge symptoms that may put a child tration, manifesting as inattention symptoms. at risk of the development or escalation of co-occurring Temporal within-person networks also highlighted rela- issues. Interventions such as Cognitive Behavioural Therapy tions between symptoms of depression and hyperactivity/ (CBT) may be particularly beneficial for children suffering impulsivity. In particular, over time, ‘Child is not as happy from both ADHD and internalising symptoms as symptoms as other children’ or ‘Child appears miserable, distressed, such as worrying, which was found to bridge these two men- or unhappy’ was associated with increases in symptoms tal health domains, have been found to respond very well to relating to restlessness and fidgeting. This finding is con- CBT (Barrett et al., 2001). Intervention studies have further sistent with the exacerbation hypothesis which proposes shown that targeting anxiety symptoms with CBT also leads that children high on ADHD and internalising symptoms, to a reduction in ADHD symptoms (Gould et al., 2018), thus usually anxiety, display more severe behavioural symptoms showing promise for reducing the co-occurrence of ADHD due to the combined effect of impairments in inhibitory con- and internalising problems. trol associated with both difficulties (Becker et al., 2012). Alternatively, the observed associations could also simply reflect the fact that depression is sometimes accompanied Limitations and Future Directions by a state of agitation which manifests in symptoms such as restlessness (Winstanley et al., 2006). Our results fur- The main limitation of this study is that our measure of ther suggest that within-person links between depression ADHD and internalising problems relied on relatively few items and ADHD are mostly mediated through difficulties items, allowing only limited inference on bridge symptoms in the anxiety domain as, apart from impulsivity showing an between these areas of psychosocial functioning. Future stud- association with increased distress, ADHD symptoms only ies should use a broader range of symptoms and ideally the had indirect temporal effects on depression through anxiety full set of DSM-5 symptoms for ADHD and internalising symptoms. This is in line with previous research on the rela- disorders to investigate the development of their symptom tions between depression and ADHD which has found that networks over time. Also, results of the current study are their relation is often mediated through anxiety and disrup- based on a community sample and consequently might not tive behaviour disorders (Roy et al., 2014). generalise to clinical populations. While using community Finally, the longitudinal within-person network also high- samples has some important advantages, such as minimis- lighted some potentially revealing relations between differ - ing the risk for Berkson’s bias (i.e. the overestimation of ent ADHD symptoms. In particular, the two impulsivity symptom co-occurrence; Berkson, 1946), future studies have items, ‘Child is impulsive, acts without thinking’ and ‘Child to be conducted to investigate whether the observed rela- has difficulty awaiting turn in games or groups’, were only tions would unfold differently for children at the clinical indirectly connected through the item ‘Child is distractible, end of the spectrum. Further, the current study relied on has trouble sticking to any activity’. Considering that the estimating associations between individual symptoms meas- GVAR model is based on partial correlations, this indicates ured by single-items, which means that measurement error that any relation between the two impulsivity items may be was likely greater than when using a composite of multiple better explained by their shared relation with distractibility. items. Future research should investigate the reliability of Specifically, the directional effects suggest that increased these single-item measurements and ideally use a multi-item impulsivity may lead to higher distractibility symptoms measure of individual symptoms. In addition, some meth- which might subsequently increase difficulties with awaiting odological considerations need to be addressed in future turns. Another reason why the impulsivity items were not research. While we were able to show that cross-sectional directly connected could be that impulsivity is multi-faceted networks were fairly similar between parent- and teacher- and these two items may capture different forms of impul- reports, we were not able to replicate the longitudinal symp- sivity that are based on distinct underlying deficits. Difficul- tom network using the teacher-reported data as the high col- ties awaiting turns is likely closely related to delay aversion linearity between some of the SBQ items led to estimation which has been associated with temporal processing deficits difficulties. Further, the GVAR model was exploratory in in ADHD whereas the more general ‘Child is impulsive, acts nature and will need to be replicated in independent data. without thinking’ item might capture more fundamental dif- The development of confirmatory longitudinal network mod- ficulties with inhibitory control (Winstanley et al., 2006). els will be important to enable testing of the replicability of 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1577 Acknowledgements The authors are grateful to the children, parents longitudinal networks because concerns have been raised and teachers who provided data for the z-proso study and the research regarding their stability (Jordan et al., 2020). assistants involved in its collection. In terms of other future directions, it will be valuable to extend the symptom networks to range from childhood to Authors’ Contributions LGS conceptualized and designed the study, adolescence and into adulthood in order to provide a compre- conducted analyses, drafted the initial manuscript, and reviewed and revised the manuscript. ME and DR made substantial contributions hensive picture of ADHD and internalising symptom rela- to the conception and design of the study and to the acquisition of tions over the lifespan. In addition, future studies should also data and critically reviewed the manuscript for important intellectual include features associated with a broader ADHD phenotype content. ALM, ML, and BA made substantial contributions to the in their analyses. In particular, emotional dysregulation and conception and design of the study and critically reviewed the manu- script for important intellectual content. All authors approved the final sluggish cognitive tempo have been identified as potential manuscript as submitted and agree to be accountable for all aspects mediators between symptoms of ADHD and internalising of the work. problems (Anastopoulos et al., 2011; Sevincok et al., 2020). Due to sample size constraints, the current study did not Funding The Zurich Project on Social Development from Childhood investigate whether factors such as child gender, ADHD to Adulthood is supported by the Jacobs Foundation and the Swiss National Science Foundation. This work was further supported by subtype or symptom severity might lead to symptom net- the University of Edinburgh (LGS, Principal’s Careers Development works unfolding differently concurrently and temporally. Scholarship); the European Union’s Horizon 2020 research and inno- This would be valuable to explore in future research using vation programme (BA, Marie Skłodowska-Curie grant agreement methods such as moderated network analyses (Haslbeck No.813546); the Baily Thomas Charitable Fund (BA, TRUST/VC/AC/ SG/469207686); and the UK Economic and Social Research Council et  al., 2019). Finally, future research should also investi- (BA, ES/N018877/1). gate whether psychological or pharmacological treatments for ADHD or internalising symptoms have an effect on the Availability of Data and Material Data available upon request. overall network structure and especially on edges between ADHD and internalising symptoms. Some evidence from Code Availability Code available upon request. intervention studies suggests that treatment of anxiety and ADHD leads to a greater reduction in symptoms for concur- Declarations rent anxiety and hyperactive/impulsive symptoms than for concurrent anxiety and inattentive symptoms (Jarrett, 2013). Ethical Approval The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national This is in line with results from our cross-sectional networks and institutional committees on human experimentation and with the which suggest that anxiety shares closer links with hyper- Helsinki Declaration of 1975, as revised in 2008. activity/impulsivity symptoms than inattentive symptoms. Thus, these preliminary results highlight that investigating Conflicts of Interest The authors have no conflicts of interest relevant the effects of treatments on symptom networks could pave to this article to disclose. the way for developing interventions that reduce the chances Informed Consent Parents provided active informed consent for chil- of developing co-occurring symptoms of ADHD or inter- dren to participate in the study. nalising problems by targeting specific bridge symptoms. Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- Conclusion tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes This study offered unique insights into the developmental were made. The images or other third party material in this article are relations of internalising and ADHD symptoms. Results included in the article’s Creative Commons licence, unless indicated of cross-sectional and within-person longitudinal analy- otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not ses highlight that ADHD shares reciprocal relations with permitted by statutory regulation or exceeds the permitted use, you will internalising symptoms through a number of potential need to obtain permission directly from the copyright holder. To view a bridge symptoms that are primarily connected to symp- copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . toms from the anxiety domain. 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Journal of Child and Adolescent Psychophar- macology, 17(5), 605–619. https://d oi.o rg/1 0.1 089/c ap.2 007.0 060 Publisher’s Note Springer Nature remains neutral with regard to Obsuth, I., Murray, A. L., Di Folco, S., Ribeaud, D., & Eisner, M. jurisdictional claims in published maps and institutional affiliations. (2020). Patterns of Homotypic and Heterotypic Continuity Between ADHD Symptoms, Externalising and Internalising 1 3 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Abnormal Child Psychology Springer Journals

Developmental Relations Between Internalising Problems and ADHD in Childhood: a Symptom Level Perspective

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10.1007/s10802-021-00856-3
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Abstract

ADHD and internalising problems commonly co-occur with up to 50% of children diagnosed with ADHD also suffering from anxiety or depression. However, their developmental relations are currently not well understood. Longitudinal symp- tom level analyses can provide valuable insights into how difficulties in these areas of psychosocial functioning affect each other. Using Gaussian Graphical Models and Graphical Vector Autoregression Models, this study estimated cross-sectional and longitudinal networks of ADHD and internalising symptoms in 1387 children using parent- and teacher-reported Social Behaviour Questionnaires (SBQ) when children were aged 7, 9 and 11. Cross-sectional and longitudinal networks suggested that ADHD shares reciprocal relations with internalising symptoms through a number of potential bridge symptoms that are primarily connected to anxiety symptoms. High scores on child cannot sit still, is restless, or hyperactive were found to be the strongest bridge symptom acting as an antecedent to higher internalising symptoms whereas child is worried was the strongest antecedent for higher ADHD symptoms. Findings of this study highlight several potential bridge symptoms that may serve as key intervention targets and further emphasise the need for clinicians to assess children presenting with ADHD symptoms for internalising problems and vice versa. Keywords ADHD · Internalising problems · Longitudinal network modelling · Z-proso Attention Deficit Hyperactivity Disorder (ADHD) is one of relations (Jarrett & Ollendick, 2008). In addition, most studies the most common mental health issues in children, affecting investigating the co-occurrence of ADHD and internalising around 6.5% of youths worldwide (Polanczyk et al., 2015). problems have focused on clinical samples (Jarrett & ADHD frequently co-occurs with internalising problems, Ollendick, 2008). Since both ADHD and internalising with prevalence estimates in children ranging from 12 to symptoms have been shown to lie on a continuum within the 50% for co-occurring depression and from 15 to 35% for general population (Lubke et al., 2009; Tebeka et al., 2018), co-occurring anxiety (Gnanavel et  al., 2019). However, these studies should be complemented with community- relatively few studies have examined the links between ADHD based samples to provide a comprehensive picture of the links symptoms and internalising problems longitudinally, making between ADHD and internalising problems. it difficult to draw any conclusions on the direction of their Existing evidence on the longitudinal development of internalising problems and ADHD in normative samples suggests that they share reciprocal relations, with, for exam- * Lydia Gabriela Speyer ple, internalising problems leading to higher ADHD symp- lspeyer@ed.ac.uk tomatology and vice versa across mid- to late- adolescence Department of Psychology, Univsersity of Edinburgh, (Murray et al., 2020a, b). Less is known about their relations Edinburgh, UK before this period, which, in the context of the co-occurrence Violence Research Centre, Institute of Criminology, of ADHD and internalising symptoms, may be a particu- University of Cambridge, Cambridge, UK larly vulnerable period given that the median age-of-onset Jacobs Center for Productive Youth Development, University of internalising problems has been found to be at around age of Zurich, Zurich, Switzerland 11 (Kessler et al., 2005). ADHD typically manifests before Autism Research Centre, Department of Psychiatry, the age of 7 but often only gets diagnosed after school entry University of Cambridge, Cambridge, UK Vol.:(0123456789) 1 3 1568 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 as difficulties become more apparent in this setting (Sax serving as a means to describe a specific symptom network. & Kautz, 2003). Hence, to understand the etiology of co- This approach also allows for a more parsimonious under- occurring ADHD and internalising problems, it is of real standing of co-occurring mental health problems given that importance to understand the temporal and concurrent rela- symptoms between mental health disorders show substantial tions of ADHD and internalising symptoms in the period overlap (e.g. concentration difficulties are not only a symp- leading up to adolescence. tom of ADHD but also of depression) (American Psychiat- To date, the mechanisms that underlie the relations ric Association, 2013). Hence, symptom networks between between ADHD and internalising symptoms are still not different disorders are likely to be connected through spe- well understood. This is also partly due to limitations in cific symptoms. These connecting symptoms are commonly the methodology for analysing longitudinal panel data. referred to as ‘bridge symptoms’ and might act as the driv- Most longitudinal studies investigating the links between ing force in the development of a co-occurring disorder by ADHD and internalising problems (e.g. Obsuth et al., 2020) activating another symptom network (Borsboom & Cramer, have used modelling techniques such as cross-lagged panel 2013). This has important implications for clinical inter- models (CLPM), which conflate between- and within-person ventions. Knowing which symptoms might underlie the effects and thus provide ambiguous results regarding the development of another disorder allows for more targeted development of co-occurring mental health issues (Berry and consequently more effective interventions. To further & Willoughby, 2017). An alternative to traditionally used maximise the impact of potential interventions, it is further statistical techniques such as CLPMs are graphical vector crucial to know how these symptom networks change over autoregression (GVAR) models (Epskamp, 2020). GVAR development. In response to the emergence of the network models allow for the separation of within- and between- approach to psychopathology, a number of studies have esti- person effects and are consequently well suited to investigate mated cross-sectional symptom level networks (e.g. Beard dynamic relations between multiple mental health domains. et al., 2016; Rouquette et al., 2018; Silk et al., 2019), some GVAR models further have the advantage that they allow also examining how these symptom networks changed over for an intuitive visualisation and interpretation of complex time (e.g. Martel et al., 2016), and providing insights into results, making it possible to not only investigate the the structure of symptoms underlying mental health. How- relations between multiple mental health domains at the ever, while cross-sectional symptom networks can highlight domain level but also at the symptom level. potential bridge symptoms, they are limited in that they do Another factor that has thus far limited our understand- not give any information on direction of effects. Understand- ing of the links between ADHD symptoms and internalising ing the direction of effects is critical as this could inform problems has been the focus on the disorder level rather the etiology of psychopathology and enables interventions to than the symptom level. There has been some evidence that target the right symptoms at the appropriate time. To date, specific symptoms of internalising problems might be more there have been very few attempts to model the temporal relevant in their association with ADHD than others and relations between symptom networks, with the few stud- vice versa (Michelini et al., 2015). In particular, symptoms ies attempting to model them longitudinally suffering from of anxiety, such as excessive worrying, have been hypoth- similar limitations as domain level analyses. Funkhouser esised to put additional drain on attentional resources, lead- et al. (2020), for instance, used cross‐lagged panel network ing to inattentive behaviour (Zainal & Newman, 2020). On analysis to analyse symptoms of internalising, externalis- the other hand, attention problems might make it more dif- ing and attention symptoms over two time points, which ficult to shift attention away from ruminative thoughts and like CLPMs, conflates within- and between-person effects. thus exacerbate internalising symptoms (Mitchell et  al., Thus, there is a clear need for more appropriate modelling 2013). Thus, some symptoms might be more important in of longitudinal symptom networks. the relations between ADHD and internalising problems, An additional limitation of many studies on the devel- making them priority intervention targets. To identify these opmental relations of different mental health issues stems symptoms, symptom level analyses are needed. Indeed, from the fact that they often rely on a single informant to symptom level analyses have recently gained in popularity measure children’s socio-emotional functioning. Evidence due to a shift in the understanding of mental health disor- from cross-informant studies indicates that different inform- ders that has resulted in the development of the network ants only show small-to-moderate degrees of convergence in approach to psychopathology (Borsboom, 2008). Rather their assessment of children’s mental health, especially when than conceptualising mental health disorders as a collection these informants experience children in different contexts of symptoms caused by a unitary underlying abnormality, (e.g. home or school) (Murray et al., 2007, 2018). Conse- the network approach to psychopathology views mental quently, studies investigating children’s mental health should health disorders as dynamic networks of multiple mutually replicate their findings based on assessments from at least reinforcing symptoms with taxonomic classifications only one other informant. This is particularly relevant in the study 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1569 of ADHD as, according to the DSM-5 diagnostic criteria, ADHD symptoms were available from parents and teachers. a diagnosis is only warranted if individuals show difficul- At the age 7 wave, data was available for 1370 youths, at ties in at least two different settings (American Psychiatric the age 9 wave for 1321 and at the age 11 wave for 1147 Association, 2013). youths. All children who had data on internalising symptoms In the current study, we investigate the developmental and ADHD for at least one time-point from at least one relations of internalising symptoms and ADHD symptoms informant were included in the current study, resulting in a in a large community-based study of N = 1387 children. final sample of 1387 children (51% male). Symptoms of anxiety, depression, inattention and hyper- The z-proso study obtained ethical approval from the activity/impulsivity were measured at median-ages 7, 9 Ethics Committee from the Faculty of Arts and Social Sci- and 11 using parent-reported Social Behaviour Question- ences of the University of Zurich. Parents provided active naires (SBQ). Using Gaussian Graphical Models (GGM) informed consent for children to participate in the study. For and Graphical Vector Autoregression Models, we estimate additional details regarding recruitment, retention, and attri- cross-sectional as well as longitudinal symptom networks tion, see elsewhere (Eisner & Ribeaud, 2007; Eisner et al., of ADHD and internalising problems to gain new insights 2019) and the z-proso website (https:// www. jacob scent er. into concurrent and temporal relations of symptoms bridging uzh. ch/ en/ resea rch/ zproso/ about us. html). ADHD and internalising problems. To evaluate the stabil- ity of our results across informants, we further replicate all cross-sectional models using teacher-reported SBQs. As this Measures is the first study to investigate the symptom-level relations of ADHD symptom and internalising problems longitudinally, Symptoms of ADHD and internalising problems were we took an exploratory approach. measured using parent- and teacher-reported versions of the Social Behaviour Questionnaire (SBQ; Tremblay et al., 1991). The SBQ is an omnibus measure of psychopathol- Methods ogy and measures children’s psychosocial functioning across five areas: ADHD, anxiety/depression, aggression, Participants non-aggressive externalizing problems, and prosocial behav- iour. At ages 7, 9 and 11 in the z-proso study, SBQs were Participants in this study were part of the Zurich Project on completed by parents and teachers and included four items Social Development from Childhood to Adulthood (z-proso), each on symptoms of inattention, hyperactivity/impulsivity, a longitudinal study based in Zurich, Switzerland, that has and depression, as well as three items on symptoms of anxi- been tracking the development of an initial target sample of ety. Items were rated on a 5-point Likert scale from Never 1675 children from 2004 when the children entered school at to Very Often. SBQs were administered using a German age 7. Children were recruited based on a stratified sampling translation of the original SBQ which teachers completed design whereby 56 public primary schools in Zurich were in the form of a paper-and-pencil questionnaire while parents selected based on school size and location. Participants were took part in a computer-assisted personal interview that was ethnically diverse with only 39.6% of primary caregivers available in an additional nine languages for non-German being native speakers of the official language of Zurich, that speaking participants. For English phrasings of the items is German, after which the most frequently spoken native used in this study see Table 1. While self-reported SBQs languages were Serbian/Bosnian/Croatian (10%), Albanian were also available, those were not used in the current study (9%), Portuguese (7%) and Tamil (5.3%) (Eisner et  al., as they were collected in the form of an adapted computer- 2019). To maximize engagement of the non-German-native based multimedia version of the SBQ with children answer- speakers, contact letters as well as parent interviews were ing ‘yes’ or ‘no’ to a series of questions relating to their made available in the in the ten most commonly spoken psycho-social development. Psychometric analyses of the languages. Of the children’s male primary caregivers who SBQ have found support for factorial validity, developmental contributed to the first wave of data collection, 76.7% invariance and criterion validity of the SBQ items across were in full-time employment (8.8% unemployed), with various waves of the z-proso study (Murray et al., 2017, 16% having a university-level education, 15.5% a higher 2020a, b). The SBQ has further been shown to be a reliable vocational education 7.8% A-levels, 35.2% apprenticeship measure of moderately low to very high levels of internalis- and 21% mandatory school or less (Murray et al., 2016). To ing and ADHD symptoms in the general population (Murray date, there have been ten waves of data collection at ages 7 et  al., 2019). Descriptive Statistics as well as correlation to 13, 15, 17 and most recently at age 20 with data collection tables of all SBQ items included in the current study are still ongoing. This study uses data from waves at median- available online (Table S1 in the supplementary and excel ages 7, 9 and 11 at which the same items on internalising and files E1 and E2). 1 3 1570 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Table 1 ADHD and Item Domain Item Content Internalising Problems Items 02 (NER) Anxiety < CHILD > is nervous, high-strung or tense 03 (ANX) Anxiety < CHILD > is too fearful or anxious 04 (WOR) Anxiety < CHILD > is worried 05 (DEP) Depression < CHILD > seems to be unhappy, sad, or depressed 06 (NHA) Depression < CHILD > is not as happy as other children 07 (TEN) Depression < CHILD > has trouble enjoying him\herself 08 (DIS) Depression < CHILD > appears miserable, distressed, or unhappy 10 (IMP) Hyperactivity/impulsivity < CHILD > is impulsive, acts without thinking 11 (DWA) Hyperactivity/impulsivity < CHILD > has difficulty a waiting turn in games or groups 12 (RES) Hyperactivity/impulsivity < CHILD > cannot sit still, is restless, or hyperactive 13 (FID) Hyperactivity/impulsivity < CHILD > fidgets 14 (CSE) Inattention < CHILD > cannot settle to anything for more than a few moments 15 (DTB) Inattention < CHILD > is distractible, has trouble sticking to any activity 16 (CON) Inattention < CHILD > cannot concentrate, cannot pay attention for long 17 (INA) Inattention < CHILD > is inattentive using the panelgvar() function of the R package psychon- Statistical Analyses etrics (Epskamp, 2020). GVAR models describe variables that have been measured at several time points as a function To improve our understanding of the concurrent relations of their own past values or as a combined function of their between symptoms of ADHD and internalising prob- own as well as other variables’ past values, allowing insights lems, a series of cross-sectional networks was estimated into temporal as well as concurrent relations between several using Gaussian Graphical Models (GGM). For each time repeatedly measured variables (Wild et al., 2010). These point (ages 7, 9 and 11), separate networks for parent- and temporal and concurrent relations can be visualised using teacher-reported symptoms were built. GGMs use partial GGMs that include directed edges to visualise temporal rela- correlations to intuitively visualise the complex depend- tions and undirected edges to visualise concurrent relations. ence structures of a system of variables. In GGMs, vari- If the data includes a multilevel structure, GVAR models ables are represented by nodes that are connected through also estimate cross-sectional between-person differences directed (temporal network) or undirected (contemporaneous across time, which enables the separation of within- from network) edges which visualise the relations between vari- between-person effects (Epskamp, 2020). This separation ables (Epskamp et al., 2018a, b). Edge weights (w) quan- is critical since between-person effects, which describe tify the strength of the association in the form of partial how someone’s average on a specific symptom compares to correlations. Networks were estimated using the R package someone else’s average on another symptom, act as a con- qgraph (Epskamp et al., 2012) which implements graphi- found when the interest lies on investigating within-person cal LASSO (least absolute shrinkage and selection opera- effects. Within-person effects describe individuals’ devia- tor) regularization in combination with Extended Bayesian tions from their own average symptom levels and can give Information Criterion (EBIC) as model selection criterion insights into whether high- or low-levels on one symptom to estimate a sparse network structure (Epskamp & Fried, influence that same person’s levels on another symptom. 2018). Using the R-package bootnet (Epskamp et al., 2018a, Investigating within-person effects is critical as they can b), 95% Confidence Intervals (CIs) for edge weights were give insights into the mechanisms that might underlie the obtained through bootstrapping routines (N = 1000). Lastly, associations between two symptoms and represent the prime cross-sectional networks at different time points as well as target for interventions (Hamaker et al., 2015). Structurally, parent- and teacher-reported models were compared using GVAR models are closely related to the Random-Intercept permutation based Network Comparison Tests (NCT) which Cross-lagged Panel Model (RI-CLPM) which separates offer information on whether networks differed in global within- from between-person effects by partialling out sta- network strength (S: sum of all edge weights; DiffS: Differ - ble-between person differences through random intercepts ence in S between two networks) and in network structure for each repeatedly measured variable that are allowed to co- (M) (Van Borkulo et al., 2015). vary (Hamaker et al., 2015). In contrast to RI-CLPMs which To analyse the longitudinal relations between ADHD model the within- and between-person covariance structures and internalising symptoms, a Graphical Vector Autore- as marginal variance–covariance matrices, GVAR models, gression (GVAR) model was built for parent-reported data 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1571 however, model these as GGMs. Also, to avoid the need to symptoms from other domains (see Fig. 1). Internalising for estimating a variance–covariance structure for the first domains (i.e., anxiety and depression) and ADHD domains measurement point, GVAR models assume stationary rela- (i.e., hyperactivity/impulsivity and inattention) also formed tions, thus, unlike RI-CLPMs, they treat the first measure- distinct clusters. At every time point, these clusters were ment wave as endogenous (Epskamp, 2020). connected through links between item 13 (FID, Child d fi gets) Before building the GVAR models, data was detrended from the hyperactivity/impulsivity domain and item 2 (NER, for linear age-related effects and standardised across time Child is nervous, high-strung or tense) from the anxiety points to meet the stationarity assumption of GVAR mod- domain. At age 7, item 2 further shared an edge with item 12 els. This was considered appropriate for the current analy- (RES, Child cannot sit still, is restless, or hyperactive) from ses because only the correlational structure and not the the hyperactivity/impulsivity domain. Bridge influence indi- mean structure was of interest. In order to appropriately ces confirmed these visual findings (see Table  2). Pairwise account for missing data, the GVAR model was fitted using NCTs indicated that network structures and global network Full Information Maximum Likelihood (FIML) estimation strength (S = 5.97, S = 6.06, S = 6.25) were invariant over 7 9 11 which provides unbiased estimates under the assumption time with all comparisons yielding p-values larger than 0.05 that data is missing at random (Enders, 2001). To mini- (M = 0.10. M = 0.12, M = 0.10; DiffS = 0.10, 7vs9 7vs11 9vs11 7vs9 mise the chance of finding false positives and to reduce DiffS = 0.28, DiffS = 0.19). Results of bootstrapping 7vs11 9vs11 the model’s complexity, the model was further regularised routines indicated that edges between bridge symptoms were (i.e., constrained to only include the most important edges) moderately stable. Confidence intervals quantifying the using Bayesian Information Criterion (BIC) as model selec- uncertainty associated with all estimated edges are presented tion criterion. Overall model fit was judged using the fol- in the online supplementary Tables S2—S4. lowing relative fit indexes: Comparative Fit Index (CFI), Tucker Lewis Index (TLI) and Root Mean Square Error of Cross‑Sectional Teacher‑Reported Networks Approximation (RMSEA) with CFI > 0.90, TLI > 0.90 and RMSEA < 0.05 used as cut off cr iteria indicating reason- Networks based on teacher-reports showed similar patterns ably good fit (Kline, 2005). Due to computational limitation, to parent-reports with symptoms from the same domains bootstrapping routines could not be employed for the GVAR forming distinct clusters (see Fig. 1). In line with the parent- model. Unfortunately, replicating the parent-reported GVAR reported networks, pairwise NCTs indicated that network model using teacher-reported SBQs was also not possible structures and global network strength were invariant over as GVAR estimations failed due to numerical optimiza- time (M = 0.10. M = 0.15, M = 0.12; S = 0.19, 7vs9 7vs11 9vs11 7vs9 tion issues likely caused by very high correlations (> 0.90) S = 0.24, S = 0.05). With regards to bridge symp- 7vs11 9vs11 between some teacher-reported SBQ items. Given the com- toms, teacher-reported networks also identified anxiety putational complexity involved in t fi ting GVAR models, this item 2 (NER, Child is nervous, high-strung or tense) and is not unexpected. ADHD items 12 (RES, Child cannot sit still, is restless, or All estimated networks were visualised using the hyperactive) and 13 (FID, Child fidgets), as potential bridge Fruchterman-Reingold algorithm in the qgraph package symptoms. However, they further highlighted a number of which places nodes sharing stronger connections closer additional connections bridging the internalising and ADHD together (Epskamp et al., 2012). For cross-sectional net- domains. In particular, item 2 (NER, Child is nervous, high- works, the network layout was kept constant (using average strung or tense) was connected to all symptoms of the hyper- layout of all networks) to facilitate comparisons. To iden- activity/impulsivity domain in the age 7 and age 9 networks, tify the most influential bridge symptoms, bridge influence while only sharing edges with item 10 (IMP, Child is impul- indices were estimated using the R package networktools, sive, acts without thinking) and 12 (RES, Child cannot sit giving insights into the direct and indirect influence of spe- still, is restless, or hyperactive) in the age 11 network. The cific bridge symptoms on symptoms from the other area of age 7 network further highlighted a connection between the psychosocial functioning (Jones et al., 2019). inattention and depression domains through item 17 (INA, Child is inattentive) and item 6 (NHA, Child is not as happy as other children). At age 11, item 17 was connected to item Results 8 (DIS, Child appears miserable, distressed, or unhappy) instead of item 6. In addition, item 14 (CSE, Child cannot Cross‑sectional Parent‑Reported Networks settle to anything for more than a few moments) shared an edge with item 5 (DEP, Child seems to be unhappy, sad, All parent-reported cross-sectional networks showed clus- or depressed). For bridge influence indices, see Table  2. ters on the domain level with symptoms being more closely The higher connectivity of the teacher-reported networks connected to other symptoms from their own domain than was also reflected in higher values for global network 1 3 1572 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Fig. 1 Cross-sectional partial correlation networks for parent- and ous, ANX: anxious, WOR: worried; DEP: depressed, NHA: not as teacher-reported symptoms at ages 7, 9, and 11. Green edges (solid happy as other children, TEN: trouble enjoying themselves, DIS: dis- lines) indicate positive effects; red edges (dashed) indicate negative tressed, IMP: impulsive, DWA: difficulty awaiting turns, RES: rest - effects. Upper row (a, b, c) represents parent-reported networks, less, FID: fidgets, CSE: cannot settle to anything, DTB: distractible, lower row (d, e, f) represents teacher-reported networks. NER: nerv- CON: cannot concentrate, INA: inattentive strength compared to parent-reported networks (S 7.24, to edges bridging ADHD and internalising domains, hyper- 7= S = 7.43, S = 7.48). NCTs showed that these differences activity/impulsivity items 10 (IMP, Child is impulsive, acts 9 11 were significant at each time point (p < 0.001; DiffS = 1.27, without thinking) and 12 (RES, Child cannot sit still, is DiffS = 1.36, DiffS = 1.22). Network structures were restless, or hyperactive) had positive temporal effects on 9 11 also found to be significantly different for parent- and internalising symptoms from the depression and anxiety teacher-reported networks (p < 0.001; M = 0.30. M = 0.34, domains respectively, while items 15 (DTB, Child is dis- 7 9 M = 0.31). Similar to the parent-reported networks, estimates tractible, has trouble sticking to any activity) and 16 (CON, for edges between bridge symptoms based on teacher-reports Child cannot concentrate, cannot pay attention for long) were moderately stable. For confidence intervals, see Tables from the inattentive domain were associated with increased S2 – S4 in supplementary materials. anxiety symptoms. Regarding the effects of internalising on ADHD symptoms, item 4 (WOR, Child is worried) from the Longitudinal Parent‑Reported Network anxiety domain had positive temporal effects on inattentive ADHD symptoms and items 6 (NHA, Child is not as happy The saturated parent-reported GVAR model showed good fit as other children), and 8 (DIS, Child appears miserable, (CFI = 0.96, TLI = 0.95, RMSEA = 0.028 with 90% CI: 0.026 distressed, or unhappy) from the depression domain were to 0.030). The regularised model performed slightly bet- associated with increased hyperactivity/impulsivity ADHD ter than the saturated model (∆BIC = 1696.74; CFI = 0.94, symptoms. Interestingly, except for one direct link between TLI = 0.93, RMSEA = 0.032 with 90% CI: 0.030 to 0.034). ADHD symptom 10 (IMP, Child is impulsive, acts without Overall, the temporal network indicated that, at the within- thinking) and depression item 8 (DIS, Child appears mis- person level, most symptoms affected other symptoms over erable, distressed, or unhappy), ADHD symptoms mostly time, though symptoms shared more and stronger connec- had positive directional effects on anxiety items. These tions with symptoms from the same domain. With regards in turn shared directional links with depression items, 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1573 Table 2 Bridge Influence Indices for Cross-Sectional Networks Parent-Report: Age 7 Parent-Report: Age 9 Parent-Report: Age 11 Item Direct Influence Indirect Influence Direct Influence Indirect Influence Direct Influence Indirect Influence 02 0.21 0.33 0.09 0.15 0.13 0.20 03 - 0.03 - 0.01 - 0.02 04 - 0.04 - 0.02 - 0.03 05 - - - - - - 06 - - - - - - 07 - - - - - - 08 - - - 0.01 - 0.01 10 - - - 0.01 - 0.02 11 - - - - - - 12 0.11 0.20 - 0.04 - 0.06 13 0.09 0.18 0.09 0.13 0.13 0.18 14 - - - - - - 15 - 0.01 - 0.01 - - 16 - 0.01 - - - - 17 - - - - - - Teacher-Report: Age 7 Teacher-Report: Age 9 Teacher-Report: Age 11 Item Direct Influence Indirect Influence Direct Influence Indirect Influence Direct Influence Indirect Influence 02 0.33 0.59 0.32 0.55 0.23 0.43 03 - 0.05 - 0.05 - 0.04 04 -.04 0.01 - 0.10 - 0.09 05 - 0.03 - - 0.04 0.09 06 0.05 0.08 - - - 0.02 07 - 0.02 - - - 0.01 08 - 0.01 - - 0.05 0.10 10 0.11 0.20 0.10 0.19 0.14 0.22 11 0.06 0.15 0.10 0.20 - 0.09 12 0.09 0.10 0.04 0.15 0.09 0.15 13 0.11 0.17 0.09 0.14 - 0.06 14 - 0.01 - 0.01 0.04 0.10 15 - 0.01 - 0.01 - 0.03 16 - 0.02 - - - 0.03 17 0.05 0.12 - 0.01 0.05 0.10 Bridge influence indices were derived from edge weights (partial correlations) in the respective cross-sectional network model. Direct influence: sum of all edge weights that exist between a node X and all nodes that are not part of the same cluster as node X (i.e. either ADHD or internalis- ing). Indirect influence: direct influence plus indirect effects of Node X through other nodes (e.g. indirect effect on node Z as in X—Y—Z) indicating that anxiety symptoms potentially mediate the indicated that anxiety item 4 (WOR, Child is worried) relations between ADHD and depression symptoms. Out of shared particularly many relations with items from both all symptoms, bridge influence indices (Table  3) indicated ADHD domains, thus, suggesting that at the within-person that ADHD item 12 (RES, Child cannot sit still, is restless, levels, children with higher symptoms of worrying also tend or hyperactive) from the hyperactivity/impulsivity domain to have higher ADHD symptoms at the same time-point. had the strongest direct influence on internalising symptoms, The between-person network (visualised in Figure S2, avail- mainly from the anxiety domain, and internalising item 4 able online) indicated that children who have high scores (WOR, Child is worried) from the anxiety domain had the on anxiety item 2 (NER, Child is nervous, high-strung or strongest direct influence on ADHD symptoms, mainly from tense), tended to also have higher scores on hyperactive/ the inattention domain. The temporal within-person net- impulsive ADHD symptoms compared to children who had work is visualised in Fig. 2. The contemporaneous network, lower scores on item 2 (NER, Child is nervous, high-strung which is visualised in Figure S1 in the online supplementary, or tense). Overall, the between-person network showed 1 3 1574 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 Table 3 Bridge Influence Indices for the Parent-Reported Temporal high-strung or tense’ from the anxiety domain. On the GVAR Network temporal level, anxiety item ‘Child is worried’ was the strongest direct antecedent of higher ADHD symptoms Item Out-Strength In-Strength Direct Influence Indirect Influence and item ‘Child cannot sit still, is restless, or hyperactive’ was the strongest direct antecedent of higher internalising 02 - 0.10 - 0.03 symptoms. 03 - 0.06 - 0.02 In line with previous studies using cross-sectional 04 0.13 - 0.13 0.17 symptom networks (Beard et al., 2016; Silk et al., 2019), 05 0.04 - 0.04 0.09 our results indicated that items from the same domain (i.e. 06 0.09 - 0.09 0.12 anxiety, depression, hyperactivity/impulsivity, inattention) 07 - - - 0.01 formed relatively distinct clusters with internalising domains 08 0.06 0.05 0.06 0.07 and ADHD domains clustering more closely together. Nev- 10 0.06 - 0.05 0.07 ertheless, all cross-sectional networks highlighted that these 11 - - - - internalising and ADHD symptom clusters are connected to 12 0.06 0.09 0.06 0.08 each other through items from the anxiety and the hyperac- 13 - 0.06 - 0.02 tivity/impulsivity domain, supporting the conceptualisation 14 - 0.06 - 0.01 of co-occurring psychopathology as connected networks of 15 0.05 - 0.05 0.11 symptoms. In particular, ADHD symptoms formed a bridge 16 0.05 0.07 0.05 0.08 to internalising symptoms through an association with how 17 - 0.04 - 0.01 often a child was nervous. Higher scores on items relating to Bridge influence indices were derived from edge weights (partial cor - restlessness and fidgeting were associated with higher scores relations) in the temporal GVAR model. Out-Strength: Sum of the on the nervousness item. Nervousness often goes hand in absolute values of out-degree edge weights (i.e. edges with a direc- hand with restlessness, making it a plausible bridge symp- tional arrow from node X to another node). In-Strength: Sum of the tom between anxiety and ADHD. Also, the fact that restless- absolute edge weights of in-degree edges (i.e. edges with a direc- tional arrow from another node to node X). Direct influence: sum of ness was part of the bridge to internalising problems is in all edge weights that exist between a node X and all nodes that are line with DSM-5 diagnostic criteria which lists restlessness not part of the same cluster as node X (i.e. either ADHD or inter- as a symptom of both ADHD and anxiety disorders (Ameri- nalising). Indirect influence: direct influence plus indirect effects can Psychiatric Association, 2013). of Node X through other nodes (e.g. indirect effect on node Z as in X—> Y—> Z). Since, these networks are directed, influence meas- Whereas cross-sectional models revealed bridges between ures only include out-degree edges symptom networks of ADHD and internalising problems, longitudinal models allowed insights into directional within- relatively little similarity with the within-person contempo- person relations between these symptoms over time. ‘Child raneous and temporal network, highlighting the necessity cannot sit still, is restless, or hyperactive’ was found to of appropriately disentangling within- from between-person have the strongest direct temporal influence on internalis- effects when within-person effects are of primary interest as ing symptoms overall, with higher scores preceding an in the context of mental health interventions. increase in the anxiety item ‘Child is too fearful or anx- ious’ while some items from the inattentive ADHD domain (‘Child is distractible, has trouble sticking to any activity’ Discussion and ‘Child cannot concentrate, cannot pay attention for long’) preceded higher scores on the anxiety item ‘Child In this study, we used graphical vector autoregression is nervous, high-strung or tense’. This suggests that, at the models to investigate the development of ADHD and inter- within-person level, anxiety symptoms may be exacerbated nalising symptom networks over time. This approach pro- by ADHD symptoms. Previous research has suggested that vides an important advance over cross-sectional symptom the development of co-occurring anxiety could be related to level networks as it allows for the estimation of directional the secondary effects of psychosocial difficulties associated relations that can improve our understanding of the devel- with ADHD such as low educational achievement and social opment of psychopathology and inform interventions. Our functioning deficits (Galéra et al., 2009). Consistent expo- results highlighted a number of potential bridge symptoms sure to such difficulties has wide ranging negative effects and between these areas of psychosocial functioning. On the has also been found to increase the risk of developing anxi- cross-sectional level, ADHD and internalising symptoms were ety problems (Bishop et al., 2019; Mazzone et al., 2007). primarily connected through item ‘Child cannot sit still, is Another contributing factor to the observed association of restless, or hyperactive’ and item ‘Child fidgets’ from the restlessness preceding anxiety could be that restlessness is in hyperactivity/inattention domain and ‘Child is nervous, fact an early sign of anxiety rather than an ADHD symptom 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1575 Fig. 2 Temporal network for parent-reported symptoms standard- enjoying themselves, DIS: distressed, IMP: impulsive, DWA: difficulty ised to directed partial correlations. Green edges (solid lines) indi- awaiting turns, RES: restless, FID: fidgets, CSE: cannot settle to any- cate positive effects. NER: nervous, ANX: anxious, WOR: worried; thing, DTB: distractible, CON: cannot concentrate, INA: inattentive DEP: depressed, NHA: not as happy as other children, TEN: trouble per se. Further research is needed to illuminate the reasons b). These findings are also consistent with the hypothesis for these associations. that one reason why some individuals only develop ADHD Examining the within-person longitudinal ee ff cts of inter - symptoms later in life is that these individuals have not been nalising symptoms on ADHD symptoms, results suggested exposed to the same environmental risk load as those who that the anxiety item ‘Child is worried, high-strung or tense’ develop symptoms early in life (Lunsford‐Avery & Kollins,  showed directional relations with inattentive symptoms. This 2018). These individuals showing increased ADHD symp- indicates that internalising symptoms potentially aggravate tom following anxiety symptoms may already be at risk of ADHD symptoms in middle childhood, adding to emerg- ADHD symptoms with anxiety acting as a triggering fac- ing evidence that ADHD and internalising problems share tor. Another potential mechanism underlying the observed reciprocal within-person relations (Murray et al., 2020a, temporal association of anxiety symptoms with inattentive 1 3 1576 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 symptoms is that anxiety inhibits the appropriate allocation Findings of the current study support current clinical best of working memory resources, negatively impacting execu- practice. In particular, results highlight the need for screen- tive functioning, and in turn leading to increased inattentive ing children who show high ADHD symptomatology also behaviour (Eysenck et al., 2007; Zainal & Newman, 2020). for internalising problems and vice versa, especially if they Similarly, the observed directional association may capture show symptoms of anxiety and for paying particular atten- the fact that worrying interferes with an individual’s concen- tion to the presence of bridge symptoms that may put a child tration, manifesting as inattention symptoms. at risk of the development or escalation of co-occurring Temporal within-person networks also highlighted rela- issues. Interventions such as Cognitive Behavioural Therapy tions between symptoms of depression and hyperactivity/ (CBT) may be particularly beneficial for children suffering impulsivity. In particular, over time, ‘Child is not as happy from both ADHD and internalising symptoms as symptoms as other children’ or ‘Child appears miserable, distressed, such as worrying, which was found to bridge these two men- or unhappy’ was associated with increases in symptoms tal health domains, have been found to respond very well to relating to restlessness and fidgeting. This finding is con- CBT (Barrett et al., 2001). Intervention studies have further sistent with the exacerbation hypothesis which proposes shown that targeting anxiety symptoms with CBT also leads that children high on ADHD and internalising symptoms, to a reduction in ADHD symptoms (Gould et al., 2018), thus usually anxiety, display more severe behavioural symptoms showing promise for reducing the co-occurrence of ADHD due to the combined effect of impairments in inhibitory con- and internalising problems. trol associated with both difficulties (Becker et al., 2012). Alternatively, the observed associations could also simply reflect the fact that depression is sometimes accompanied Limitations and Future Directions by a state of agitation which manifests in symptoms such as restlessness (Winstanley et al., 2006). Our results fur- The main limitation of this study is that our measure of ther suggest that within-person links between depression ADHD and internalising problems relied on relatively few items and ADHD are mostly mediated through difficulties items, allowing only limited inference on bridge symptoms in the anxiety domain as, apart from impulsivity showing an between these areas of psychosocial functioning. Future stud- association with increased distress, ADHD symptoms only ies should use a broader range of symptoms and ideally the had indirect temporal effects on depression through anxiety full set of DSM-5 symptoms for ADHD and internalising symptoms. This is in line with previous research on the rela- disorders to investigate the development of their symptom tions between depression and ADHD which has found that networks over time. Also, results of the current study are their relation is often mediated through anxiety and disrup- based on a community sample and consequently might not tive behaviour disorders (Roy et al., 2014). generalise to clinical populations. While using community Finally, the longitudinal within-person network also high- samples has some important advantages, such as minimis- lighted some potentially revealing relations between differ - ing the risk for Berkson’s bias (i.e. the overestimation of ent ADHD symptoms. In particular, the two impulsivity symptom co-occurrence; Berkson, 1946), future studies have items, ‘Child is impulsive, acts without thinking’ and ‘Child to be conducted to investigate whether the observed rela- has difficulty awaiting turn in games or groups’, were only tions would unfold differently for children at the clinical indirectly connected through the item ‘Child is distractible, end of the spectrum. Further, the current study relied on has trouble sticking to any activity’. Considering that the estimating associations between individual symptoms meas- GVAR model is based on partial correlations, this indicates ured by single-items, which means that measurement error that any relation between the two impulsivity items may be was likely greater than when using a composite of multiple better explained by their shared relation with distractibility. items. Future research should investigate the reliability of Specifically, the directional effects suggest that increased these single-item measurements and ideally use a multi-item impulsivity may lead to higher distractibility symptoms measure of individual symptoms. In addition, some meth- which might subsequently increase difficulties with awaiting odological considerations need to be addressed in future turns. Another reason why the impulsivity items were not research. While we were able to show that cross-sectional directly connected could be that impulsivity is multi-faceted networks were fairly similar between parent- and teacher- and these two items may capture different forms of impul- reports, we were not able to replicate the longitudinal symp- sivity that are based on distinct underlying deficits. Difficul- tom network using the teacher-reported data as the high col- ties awaiting turns is likely closely related to delay aversion linearity between some of the SBQ items led to estimation which has been associated with temporal processing deficits difficulties. Further, the GVAR model was exploratory in in ADHD whereas the more general ‘Child is impulsive, acts nature and will need to be replicated in independent data. without thinking’ item might capture more fundamental dif- The development of confirmatory longitudinal network mod- ficulties with inhibitory control (Winstanley et al., 2006). els will be important to enable testing of the replicability of 1 3 Research on Child and Adolescent Psychopathology (2021) 49:1567–1579 1577 Acknowledgements The authors are grateful to the children, parents longitudinal networks because concerns have been raised and teachers who provided data for the z-proso study and the research regarding their stability (Jordan et al., 2020). assistants involved in its collection. In terms of other future directions, it will be valuable to extend the symptom networks to range from childhood to Authors’ Contributions LGS conceptualized and designed the study, adolescence and into adulthood in order to provide a compre- conducted analyses, drafted the initial manuscript, and reviewed and revised the manuscript. ME and DR made substantial contributions hensive picture of ADHD and internalising symptom rela- to the conception and design of the study and to the acquisition of tions over the lifespan. In addition, future studies should also data and critically reviewed the manuscript for important intellectual include features associated with a broader ADHD phenotype content. ALM, ML, and BA made substantial contributions to the in their analyses. In particular, emotional dysregulation and conception and design of the study and critically reviewed the manu- script for important intellectual content. All authors approved the final sluggish cognitive tempo have been identified as potential manuscript as submitted and agree to be accountable for all aspects mediators between symptoms of ADHD and internalising of the work. problems (Anastopoulos et al., 2011; Sevincok et al., 2020). Due to sample size constraints, the current study did not Funding The Zurich Project on Social Development from Childhood investigate whether factors such as child gender, ADHD to Adulthood is supported by the Jacobs Foundation and the Swiss National Science Foundation. This work was further supported by subtype or symptom severity might lead to symptom net- the University of Edinburgh (LGS, Principal’s Careers Development works unfolding differently concurrently and temporally. Scholarship); the European Union’s Horizon 2020 research and inno- This would be valuable to explore in future research using vation programme (BA, Marie Skłodowska-Curie grant agreement methods such as moderated network analyses (Haslbeck No.813546); the Baily Thomas Charitable Fund (BA, TRUST/VC/AC/ SG/469207686); and the UK Economic and Social Research Council et  al., 2019). Finally, future research should also investi- (BA, ES/N018877/1). gate whether psychological or pharmacological treatments for ADHD or internalising symptoms have an effect on the Availability of Data and Material Data available upon request. overall network structure and especially on edges between ADHD and internalising symptoms. Some evidence from Code Availability Code available upon request. intervention studies suggests that treatment of anxiety and ADHD leads to a greater reduction in symptoms for concur- Declarations rent anxiety and hyperactive/impulsive symptoms than for concurrent anxiety and inattentive symptoms (Jarrett, 2013). Ethical Approval The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national This is in line with results from our cross-sectional networks and institutional committees on human experimentation and with the which suggest that anxiety shares closer links with hyper- Helsinki Declaration of 1975, as revised in 2008. activity/impulsivity symptoms than inattentive symptoms. Thus, these preliminary results highlight that investigating Conflicts of Interest The authors have no conflicts of interest relevant the effects of treatments on symptom networks could pave to this article to disclose. the way for developing interventions that reduce the chances Informed Consent Parents provided active informed consent for chil- of developing co-occurring symptoms of ADHD or inter- dren to participate in the study. nalising problems by targeting specific bridge symptoms. Open Access This article is licensed under a Creative Commons Attri- bution 4.0 International License, which permits use, sharing, adapta- Conclusion tion, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes This study offered unique insights into the developmental were made. The images or other third party material in this article are relations of internalising and ADHD symptoms. Results included in the article’s Creative Commons licence, unless indicated of cross-sectional and within-person longitudinal analy- otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not ses highlight that ADHD shares reciprocal relations with permitted by statutory regulation or exceeds the permitted use, you will internalising symptoms through a number of potential need to obtain permission directly from the copyright holder. To view a bridge symptoms that are primarily connected to symp- copy of this licence, visit http://cr eativ ecommons. or g/licen ses/ b y/4.0/ . toms from the anxiety domain. 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Journal of Child and Adolescent Psychophar- macology, 17(5), 605–619. https://d oi.o rg/1 0.1 089/c ap.2 007.0 060 Publisher’s Note Springer Nature remains neutral with regard to Obsuth, I., Murray, A. L., Di Folco, S., Ribeaud, D., & Eisner, M. jurisdictional claims in published maps and institutional affiliations. (2020). Patterns of Homotypic and Heterotypic Continuity Between ADHD Symptoms, Externalising and Internalising 1 3

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Journal of Abnormal Child Psychology – Springer Journals

Published: Dec 1, 2021

Keywords: ADHD; Internalising problems; Longitudinal network modelling; Z-proso

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