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Suboptimal decision making
and interpersonal problems
in ADHD: longitudinal evidence
from a laboratory task
L. Sørensen 1*, S. Adolfsdottir
1,2, E. Kvadsheim
3, H. Eichele
4, K. J. Plessen
5 &
E. Sonuga‑Barke
6,7,8
Over half of children with Attention‑Decit/Hyperactivity Disorder (ADHD) display interpersonal and
social problems. Several lines of research suggest that suboptimal decision making, the ability to
adjust choices to dierent risk‑varying options, inuences poorer choices made in social interactions.
We thus measured decision making and its prediction of social problems longitudinally with the
Cambridge Gambling Task in children with ADHD over four years. Children with ADHD had shown
suboptimal decision making driven mainly by delay aversion at baseline and we expected this to
be a stabile trait which would predict greater parent‑reported social problems. From the baseline
assessment (n = 70), 67% participated at the follow‑up assessment, 21 from the ADHD group and
26 from the typically developing group. The mean age at the follow‑up was 14.5 years old. The
results conrmed our expectations that suboptimal decision making was a stabile trait in children
and adolescents with ADHD. Although delay aversion did not dier from controls at follow‑up it still
proved to be the main longitudinal predictor for greater social problems. Our ndings indicate that
impulsivity in social interactions may be due to a motivational decit in youth with ADHD.
Over half of the individuals with attention-decit/hyperactivity disorder (ADHD) have diculties in develop-
ing and maintaining social relationships1–4. ese interpersonal problems seem to be the result of ill-considered
and poorly timed social interventions and responses rather than a lack of knowledge about appropriate social
conduct1,5,6. For instance, people with ADHD might choose to interject a comment into a conversation that has
an inappropriate content, at an inappropriate moment or in an inappropriate way without thinking through the
consequences of the actions7,8. In this sense interpersonal problems can be conceptualized, from one perspec-
tive, as expressions of suboptimal decision making causing poorer and impulsive choices to be made in social
situations9. However, the question of whether the social and interpersonal problems of people with ADHD are
underpinned by more general decits in basic decision-making skills has not yet been addressed. Investigating
the role of decision making in social problems in ADHD could lead to a complementary understanding compared
to simply focusing on that inattentive, impulsive, and hyperactive people cannot focus, wait, or sit still enough
to develop successful interactions. e core ADHD symptoms are in general found to predict social problems10,
at the same time as, treatments that are eective in reducing ADHD symptoms, such as psychostimulant medi-
cation, only have small eects on enhancing social skills11–14. is suggests a dissociation between the core
symptoms of ADHD and other neurocognitive processes linking the diagnosis to social impairment. It is thus
a call for exploring if processes, such as social decision making, might improve the conceptualizations of the
causes for social problems in ADHD and as such, contribute to nding relevant targets for social skill training15.
In the current paper, we examined this question by exploring the prospective predictive relationship between
children’s performance on a widely used and well-validated task measuring risky and impulsive decision making
OPEN
1Department of Biological and Medical Psychology, University of Bergen, Jonas Liesvei 91, 5009 Bergen,
Norway. 2Division of Vision Impairments, Statped – National Service for Special Needs Education, Bergen,
Norway. 3Department of Clinical Medicine, University of Bergen, Bergen, Norway. 4Regional Resource Centre for
Autism, ADHD and Tourette Syndrome Western Norway, Division of Psychiatry, Haukeland University Hospital,
Bergen, Norway. 5Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University
Hospital, University of Lausanne, Lausanne, Switzerland. 6Department of Child and Adolescent Psychiatry,
King’s College London, London, UK. 7Department of Child and Adolescent Psychiatry, Aarhus University, Aarhus,
Denmark. 8Department of Psychology, Hong Kong University, Hong Kong, China. *email: Lin.Sorensen@uib.no
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(Cambridge Gambling Task; CGT)16,17 and parent-reported social and interpersonal problems later in develop-
ment. is task measures the extent to which individuals can adjust their choices to more-or-less-risky options
by integrating external information with internal value systems. e choices are made between response options
with dierent outcome probabilities16,18. Suboptimal decision-making was measured with the CGT scores of:
(1) Risk adjustment (the diculty in adjusting decisions according to level of risk by learning from previous
choices), (2) delay aversion (the choice of the less delayed option rather than the choice with the highest return),
(3) reection time (shorter reection times reect poorer inhibitory control19), and (4) risk proneness (over-
attraction to the risky options). In phase one of the study, we included a cross-sectional baseline analysis of 36
drug-naïve children with ADHD and 34 typically developing peers aged between 8 and 12years old. We observed
that ADHD was associated with fewer optimal decisions (poorer risk adjustment), which was driven primarily
by higher levels of delay aversion20. is nding was consistent with much broader literature highlighting delay
aversion as a core motivational component of ADHD across settings21–25 and further, that poorer risk adjustment
in ADHD seems to be due to other processes than being risk prone per se26. ese dierent decision making
parameters may predict greater social problems as part of an overall suboptimal decision making. For instance,
impulsive choices made in social settings have been suggested to be caused predominantly by poorer inhibitory
control27,28 or delay aversion29,30. However, several studies have shown a weak link between inhibitory control
and social problems in ADHD31–35. As far as we know, no study has investigated the link between delay aversion
and social problems despite the suggestions that it leads to impulsive and disruptive behavior in subjectively
experienced stimulus-poor environments29,30. Furthermore, ADHD has been associated with increased risk prone
behavior (see36). It is not clear to what extent this risky behavior in youth with ADHD is linked to a dierent
social functioning in comparison with typically peers. One recent study indicated that peer inuence compared
to no such inuence increased risk prone choices during the Balloon Analogue Risk Task across the groups of
adolescents with ADHD and their typically developing peers alike37. is may suggest that risk proneness is
similarly related to social inuence in ADHD as in non-ADHD.
We followed up on the sample aer 4years to study the developmental outcomes associated with subopti-
mal decision making in ADHD. Based on the hypothesis that interpersonal problems in ADHD are driven by
core decits in decision making, we predicted that at follow-up individuals with ADHD displaying suboptimal
decision making at baseline (T1) would (i) show more social and interpersonal diculties and (ii) continue to
display poor risk adjustment and delay aversion on the CGT and at the same time continue to not show dier-
ence from typically developing peers in reection time (inhibitory control) or risk proneness. In addition to
parent-reports of social problems from the Child Behavior Checklist (CBCL; Achenbach and Rescorla38), we also
included parent-reports on two other subscales from CBCL of conduct problems and anxiety/depression problem
symptoms due to these problems oen being comorbid with ADHD and recognized in accompanying problems
in social interactions. Children with ADHD oen have social problems due to high frustration levels aecting
their social functioning39. Conduct problems characteristically reect higher levels of irritability, delinquency,
and aggressiveness in the behavior towards peers and others40. Furthermore, problematic symptoms of anxiety
and depression are associated with higher frustration levels and irritability41 as well as with social isolation42.
Results
Sample characteristics
From the original sample (N = 70) at baseline performing the CGT (T1), 67% (N = 47) participated at the follow-
up assessment (T2); 58% (n = 21) from the ADHD group and 77% (n = 26) from the typically developing group
(see Supplemental Fig.1). At T2, the age range was 11–17years old with a mean age of 14.5 (SD = 1.31). e two
groups did not dier signicantly in age or gender distribution (see Table1). e mean T1 and T2 interval was
4.5years (SD = 0.7) with no signicant dierence in interval between the two groups. At T2, all the adolescents
in the ADHD group still met the criteria for an ADHD diagnosis, and 48% of these had a comorbid disorder;
six had anxiety; six had oppositional deant disorder (ODD), two had tics, one had depression, and one obses-
sive–compulsive disorder. In the control group, two had an anxiety disorder. In the ADHD group, 76% (n = 16)
used CNS stimulants to treat their ADHD. Of these, 88% conducted a washout period of at least 24h before test-
ing, whereas two participants had a washout period of at least 12 and 18h, respectively. ese are all acceptable
washout periods due to the two that had a shorter period used methylphenidate, which has a half-life of two to
three hours and the active ingredient eliminated aer 10–15 h43,44. Children with ADHD who remained in the
study at T2 showed no signicant dierences in scores on the CGT, Full-Scale IQ, or ADHD symptoms at T1
compared to their counterparts who dropped out (see Supplemental Table1).
Did decision making decits seen at baseline persist to follow up?
Cross-sectionally, the ADHD group showed poorer risk adjustment compared with the control group at both T1
and T2, higher delay aversion only at T1, and higher risk proneness only at T2 (see Table1). No cross-sectional
group dierences appeared in relation to reection times (inhibitory control). Longitudinally (alpha levels (α)
were Bonferroni corrected for conducting four ANOVAs; p < 0.013), including both ADHD and the two time
points as factors, there was a main eect (F(1,90) = 8.91, p = 0.004, ηp2 = 0.09) of group on decision making quality
with the ADHD sample showing poorer risk adjustment at both baseline and follow-up (see Fig.1 and Supple-
mental Table2). ere was no signicant eect of time and no interaction between time and group. Furthermore,
the risk adjustment scores at baseline and follow-up were signicantly correlated in the whole sample (r = 0.36,
p = 0.014) and in the ADHD group (r = 0.51, p = 0.018) but not in the control group alone (r = 0.20). However,
stability was less clear for the other decision elements with the ADHD group showing more delay aversion than
controls at baseline than follow-up (main eect of time points: F(1,90) = 18.16, p = 0.001, ηp2 = 0.20). Still, in the
whole sample (r = 0.34, p = 0.02) and in the ADHD group (r = 0.45, p = 0.041), greater delay aversion at both time
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points correlated signicantly, except in the control group (r = 0.29). No signicant eect of ADHD appeared on
risk proneness or in reection times (inhibitory control) neither at baseline nor follow-up when the two time
points were included as a factor in addition to ADHD. Risk proneness as measured at the two time points did
not correlate, whereas reection times correlated highly between the two timepoints in the whole sample and in
both subgroups. See Supplemental Table4 for all the intercorrelations of the CGT parameters cross-sectionally
and longitudinally.
Did adolescents with ADHD show more social problems?
Parents reported that children with ADHD showed greater social problems and greater problems of conduct
behavior and anxiety/depression at both time points compared with control children (see Table1). At follow
up all three problem areas of social problems, conduct behavior, and anxiety/depression correlated highly with
each other (see Table2).
Table 1. Demographic information, CGT parameter scores, and social problem scores in the groups of
adolescents with ADHD and healthy controls. DM decision making, anx. anxiety, dep. Depression, sympt.
symptoms, ^inhibitory control. e CGT parameters are in z scores and the social problem scores are in
percentile scores. **p < 0.01; *p < 0.05.
Variables
ADHD (n = 21) Controls (n = 26) Group analysis
T1 T2 T1 T2 T1 T2
Mean SD Mean SD Mean SD Mean SD t t
Age 9.88 1.25 14.33 1.50 10.08 1.00 14.58 1.15 0.20 0.64
T1–T2 interval 4.46 0.91 4.5 0.56 0.21
Full-scale IQ 94 7.03 109 10.42 5.70**
Risk adjustment −0.54 0.73 −0.10 0.77 −0.00 0.92 0.50 1.13 2.19* 2.06*
Delay aversion 0.80 0.99 −0.36 0.81 0.04 0.91 −0.39 0.88 −2.74** −0.10
Reection time^0.61 1.14 −0.47 0.59 0.58 0.68 −0.75 0.39 −0.08 −1.97
Risk proneness −0.00 0.99 0.29 0.82 0.26 1.17 −0.26 0.95 0.09 −2.11*
Social problems 80.10 16.24 81.48 13.34 53.92 7.97 53.88 9.72 −7.23** −8.20**
Anx./dep. sympt 69.00 18.90 77.38 18.89 57.58 14.34 58.35 13.91 −2.36* −3.98**
Conduct problems 65.43 8.91 63.33 11.33 50.85 1.74 51.85 5.27 −8.18** −4.60**
Sex n males n females n males n females X2
15 6 15 11 9.49
Figure1. Group eects shown at baseline and follow-up on the CGT parameters of (a) risk adjustment, (b)
delay aversion, (c) reection time (inhibitory control), and (d) risk proneness.
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Were social problems correlated with decision making on the CGT cross sectionally and
longitudinally?
Table2 shows the correlations between social problems at follow-up and CGT parameters at baseline and follow-
up. Cross-sectional associations at follow-up were signicant between the CGT parameters of poorer risk adjust-
ment and longer reection times (inhibitory control), and further, between poor risk adjustment and greater
social problems, and greater anxiety/depression problems. Furthermore, the CGT parameters did not correlate
with conduct problems nor did risk proneness correlate with social problems or problems of conduct behavior
and anxiety/depression at follow-up. Longitudinally, signicant correlations were seen for both the baseline
CGT parameters of poorer risk adjustment and greater delay aversion with greater social problems at follow-
up. Baseline reection times (inhibitory control) and risk proneness did not correlate with social problems at
follow-up. Further, only the baseline CGT parameter of greater delay aversion correlated with higher anxiety/
depression problems at follow-up, and only longer reection times (inhibitory control) at baseline correlated
with greater conduct problems at follow up. To test for the specicity of the eect baseline CGT parameters had
on social problems and problems of conduct behavior and anxiety/depression at follow up, we included the three
baseline CGT parameters that correlated longitudinally with these problems as predictors (risk adjustment,
delay aversion, and reection times) in three multiple linear regression analyses with the three CBCL scores as
outcome variables [alpha level (α) was Bonferroni corrected for conducting three regression analyses; p < 0.017].
e results showed that only greater delay aversion at baseline, and not poorer risk adjustment or reection
times (inhibitory control), predicted greater social problems at follow up (see Table3 and Fig.2). None of the
CGT parameters specically predicted level of conduct problems or anxiety/depression problems at follow-up.
Table 2. Bivariate correlations between the CGT parameters at both time points and parent-reported social
problems and conduct and anxiety/depression problems at follow up. **p < 0.01; *p < 0.05. DM decision
making, ^Inhibitory control.
T2 social T2 anxiety/ T2 conduct
problems depression problems
T2 anxiety/depression 0.60**
T2 conduct problems 0.67** 0.56**
T1 CGT risk adjustment −0.32* −0.23 −0.14
T1 CGT delay aversion 0.43** 0.40 0.22
T1 CGT reection time^−0.11 −0.03 0.31*
T1 CGT risk proneness −0.20 −0.28 0.01
T2 CGT risk adjustment −0.40** −0.37* −0.22
T2 CGT delay aversion 0.02 0.17 −0.29
T2 CGT reection time^0.33* 0.27 0.20
T2 CGT risk proneness 0.16 0.006 −0.05
Table 3. e longitudinal prediction of baseline CGT parameters of poorer risk adjustment, delay aversion,
and reection time (inhibitory control) on parent-reported social problems and conduct and anxiety/
depression problems at follow-up. *Bonferroni corrected p-level (0.05/3) = 0.017. DM decision making;
^Inhibitory control.
Predictors Adj. R2df F p B β t p 95% CI for B
T2 parent-reported social/interpersonal problems from CBCL
T1 risk adjustment 0.17 3/43 4.14 0.012* −2.52 −0.12 −0.80 0.430 −8.89 to 3.86
T1 delay aversion 6.99 0.40 2.59 0.013* 1.54 to 12.43
T1 reection time^2.78 0.14 1.00 0.325 −2.85 to 8.40
T2 parent-reported anxiety/depression problems from CBCL
T1 risk adjustment 0.11 3/43 2.84 0.049 −1.56 −0.07 −0.45 0.653 −8.47 to 5.36
T1 delay aversion 6.87 0.37 2.34 0.024 0.96 to 12.79
T1 reection time^0.17 0.01 0.06 0.957 −5.93 to 6.27
T2 parent-reported conduct problems from CBCL
T1 risk adjustment 0.10 3/43 2.73 0.055 0.44 0.04 0.23 0.817 −3.34 to 4.22
T1 delay aversion 2.78 0.28 1.73 0.09 −0.45 to 6.01
T1 reection time^3.93 0.35 2.38 0.022 0.60 to 7.26
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Discussion
In the current study, children with ADHD were followed up longitudinally to study the development of subop-
timal decision making over time and its prediction of social problems between childhood and adolescence. We
originally found that the children with ADHD displayed suboptimal choices as measured with risk adjustment at
baseline, driven primarily by delay aversion on the CGT compared with typically developing peers. At follow-up
four years later, we expected that individuals with ADHD would still show poorer risk adjustment and greater
delay aversion than their typically developing peers, and that baseline suboptimal decision making would predict
greater parent-reports of social problems and conduct and anxiety/depression problems. As expected, the results
showed that poorer risk adjustment was a stable trait over 4years in children and adolescents with ADHD. Delay
aversion, on the other hand, was no longer signicantly dierent at follow-up in the ADHD group compared
with the control group. Still, greater delay aversion along with poorer risk adjustment correlated from baseline to
follow-up only in the ADHD group and not in the control group. e CGT parameters of poorer risk adjustment,
greater delay aversion, and longer reection times (inhibitory control) were correlated both cross-sectionally
and longitudinally with greater interpersonal problems and conduct and anxiety/depression problems. However,
when including these CGT parameters in the same statistical model, greater delay aversion at baseline (T1) was
the only CGT parameter that four years later (T2) predicted greater social problems (see Fig.3). Furthermore,
none of these CGT parameters at baseline predicted conduct or anxiety/depression problems four years later.
Risk proneness was not dierent in the ADHD group at T1 but showed a tendency to be higher in this group at
T2. It did, however, not correlate with social problems or conduct or anxiety/depression problems. Reection
time (inhibitory control) was not dierent between the groups at either time point.
Parents and teachers consistently report that children with ADHD struggle with interpersonal interactions
and relationships1,4,6,35, as is the case in the current study. ese reports typically coincide with the perception
Figure2. Scatterplots of the longitudinal relationship between the baseline CGT parameters of risk adjustment,
delay aversion, and reection time (inhibitory control) and parent-reported social problems at follow-up. Delay
aversion was the only predictor of these CGT parameters that predicted signicantly greater social problems at
follow-up.
Figure3. Hypothesized models illustrating (a) the expected prediction of baseline suboptimal decision making
on longitudinal interpersonal problems, and the eect of delay aversion on interpersonal problems via poorer
risk adjustment, and (b) the role of baseline delay aversion both as contributing to suboptimal decision making
and directly predicting interpersonal problems four years later.
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reported by peers that children with ADHD are more oen rejected and neglected by peers, having fewer friends
and fewer and less diverse social activities13,31,45,46. Our results indicate that these problems are predicted by
diculties in adapting dynamically to changing contextual conditions. On the CGT this can be observed by dif-
culties in adapting choices to the changing patterns of outcome probabilities (poorer risk adjustment). In the
current study, the motivational style of escaping delays was the main driver for these problems. Delay aversion
has previously been suggested to cause social problems by leading to impulsive and disruptive behavior29,30.
Importantly, our study appears, as far as we know, to be the rst to experimentally investigate and link delay
aversion with greater interpersonal problems. is is in line with the dominant causal hypothesis of ADHD in
children in that they tend to choose immediate rewards more consistently when this choice gives escape from
delay compared to when the same choice does not escape delay23. is drive for escape when children with ADHD
perceive situations as tedious (stimulus-poor) is suggested to be associated with a negative aective state (high
frustration), which is supported by fMRI studies of adolescents25,47 and adults48 with ADHD.
In line with ndings from several previous studies31–35, the children with ADHD did not show suboptimal
decision making or social problems due to poorer inhibitory control as reected in shorter reection times.
Rather, it was a general nding that longer reection times correlated with greater social problems, which prob-
ably are linked to challenges of processing information fast enough in social situations49. Important to note,
though, is that a previous study has shown that the delay aversion score from the CGT can be challenging to
distinguish from poor inhibitory control in ADHD22. In our original study20, we therefore tested for this and
found that (a) the delay aversion score was linked to shorter test duration time—showing the CGT delay aver-
sion score to be linked to escape of delay and not just an impulsive drive for immediate reward (see23,50), and
(b) the prediction of delay aversion in explaining suboptimal decision making in ADHD was not explained by
poorer inhibitory control (as measured with the Cambridge Stop Signal Test) or by level of intelligence and
working memory capacity. Inhibitory control, intelligence and working memory capacity did not either covary
in our original study with suboptimal decision making when testing the group dierences between ADHD and
control children20.
Our ndings showed that delay aversion at baseline tended to specically predict greater interpersonal prob-
lems in general and not conduct or anxiety/depression problems. Both conduct and anxiety/depression problem
scores were signicantly higher in the ADHD group and highly correlated with social problems. In relation to
the CGT scores, greater delay aversion correlated with higher anxiety/depression problem symptoms, and longer
reection times with greater conduct problems. is supports delay aversion being described as expressing nega-
tive aectivity48—typically associated with higher levels of anxiety and/or depression51. Longer reection times
have also been found to be associated with lower motivation to do tasks as instructed52, which higher conduct
problems can reect via non-compliance with external expectations. However, including the CGT parameters
that correlated with social problems and the problem scores of conduct behavior and anxiety/depression in the
same regression models, showed that none of them specically predicted higher conduct or anxiety/depression
problems.
To our knowledge, this is the rst study that has investigated the link between suboptimal decision making
and interpersonal problems in ADHD. However, in adults with schizophrenia53 and in young healthy adults54,
both studies using a dierent test method than CGT, found that suboptimal decision making was associated with
poorer social skills and interpersonal relationships. In children with ADHD, one study investigated the ability of
teacher-reported ADHD symptoms to predict parent-reports on the social problem subscale from the CBCL and
performance on a decision making task using aective cues two years later55. e ADHD symptoms predicted
both greater social problems and poorer decision making. However, the cross-sectional correlation coecient
between social problems and the aective cuing decision making task scores was low (r = 0.21). Future studies are
encouraged to further test the prediction of suboptimal decision making on social problems in ADHD. e low
sample size in the current study may rise issues of low statistical power when testing longitudinal associations
despite the a priori power analysis showed the sample size to be sucient for avoiding a type II error.
In the current study, the children with ADHD were drug naïve at baseline and the majority on medication
at follow-up. is may have aected the longitudinal ndings in that medication according to its objectives is
supposed to have long-term eects on cognition and motivational style56. ese eects may be present even
though we asked the participants to refrain from taking the medicine before the testing. We found, however,
that suboptimal decision making was a stable trait in the ADHD group suggesting that CNS medication did not
have a long-term eect on improving the ability to choose optimal options in ambiguous and risky situations (on
the gambling task)—besides the short-term eects shown previously on the CGT
57. is is in line with a recent
study on the eects of methylphenidate in adolescents with ADHD, in which no long-term eects were found on
any of the outcome measures including on cognitive functioning14. It is possible that medication may have led
to a higher tolerance for delay at the follow-up assessment, or it may be due to the children with ADHD being
older and more mature in their decision making abilities. In relation to social competence and the eect of CNS
medication, one systematic review found that children treated with medication and/or non-pharmacological
interventions for their ADHD had better social functioning compared to untreated children with ADHD58. Other
studies, however, have found that methylphenidate alone, or in combination with cognitive behavioral therapy,
had only a limited eect on social behavior in children with ADHD11–14. In boys with ADHD, the positive eect
of methylphenidate was specically observed in higher compliance with expected behavior and a decrease in
aggressive behavior tendencies12.
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Conclusion
Interpersonal problems are recognized as one of the important impairments negatively aecting quality of life
in children with ADHD58,59. Early predictors and mechanisms of interpersonal problems are thus essential to
identify15. e current study showed that suboptimal decision making driven by delay aversion can be an impor-
tant predictor to address in future studies of interpersonal competence in ADHD. A deeper understanding of
this relationship may initiate specic programs of psychoeducation about living with ADHD for caregivers and
the children. is relationship may also be important to address in training programs to improve quality of life
for children with ADHD.
Methods
Participants
e current study was a follow-up of children 8 to 12years old with ADHD and age-matched typically developing
peers performing the CGT
20. e children were originally included at baseline (T1) with a Full-Scale Intelligent
Quotient (FSIQ) > 8060 and diagnostically evaluated with the Schedule for Aective Disorders and Schizophrenia
for School-Age Children—Present and Lifetime Version (K-SADS)61. e K-SADS was re-administered at the
follow-up assessment (T2). e test administrators of the neuropsychological test battery including the CGT
were blinded to group status both at T1 and T2. e parents reported on the children’s’ mental health and social
functioning at both time points (described below). At T2, children were rst interviewed with the K-SADS
while parents lled out questionnaires, and subsequently the children performed a neuropsychological test bat-
tery and lled out questionnaires while the parents were interviewed with the K-SADS. e study protocol was
approved by the Regional committee for medical research ethics of western Norway (study number: 2014/1304)
and research was conducted according to relevant regulations and guidelines. Informed consent was given both
orally and in written form from all the parents and the adolescents. Both the adolescents’ (at T2) and their parents
(at T1 and T2) signed written consent in accordance with the Declaration of Helsinki. e participants received
a reimbursement of $115.
Cambridge gambling task (CGT)
e CGT from the Cambridge Neuropsychological Test Automated Battery, CANTAB; www. camcog. com 16,17,
was administered at T1 and T2 (see Fig.4). e children were rst instructed that a yellow token was hidden
behind either a blue or red box, presented in an array of 10 boxes at the top of the computer screen. Secondly,
they were instructed to make a bet on the likelihood of their decision being correct or not. Points were presented
in a box on the right-hand side in 5-s increments/decrements sequences. e children touched the box to place
a bet. In four of the test blocks, the bets were presented in an ascending order of 5, 25, 50, 75, and 95% por-
tion of the points that the children would “earn” on each trial (displayed on the le-hand side of the computer
screen), and in the other four blocks they were presented in a descending order (95, 75, 50, 25, and 5% portion
of the points). e order of presentation (ascending or descending) was counterbalanced across individuals
within the groups at both time points. e task was administered on a desktop PC and responses recorded via a
touch-sensitive screen (see Sørensen etal.20 for further details). As measures of suboptimal decision making, we
included the CGT generated scores of (a) risk adjustment measuring the ability in adjusting decisions according
to level of risk by learning from previous choices, (b) delay aversion measured the proportion of choices made
for the option available most immediately irrespective of the outcome, (c) reection time (inhibitory control)
measured the time taken to think about the options during the decision phase and was calculated based on the
deliberation time between stimulus presentation and choice outcome, and (d) risk proneness was dened by the
total number of points that were gambled on the most improbable outcome—reecting the overall tendency to
take risks. ese scores were centralized as z-scores.
Social problems and conduct and anxiety/depression problems
Parents completed the Child Behavior Checklist 6–18 (CBCL)38 at T1 and T2. e CBCL is a 113-item rating
scale with a 3-point response scale, from 0 for not true to 2 for very true/oen true. e CBCL is a widely used
Figure4. A screen shot of the Cambridge Gambling Task (CGT). e red and blue boxes at the top of the
screen are hiding a yellow token and the red and blue squares at the bottom of the screen are pushed to guess
which colored box the token is hidden behind. e numbers presented represent percentages of the points
displayed at the le-hand side that are presented either in ascending or descending sequences. Note. e image
is printed with permission from © Copyright 2023 Cambridge Cognition Limited. All rights reserved.
Content courtesy of Springer Nature, terms of use apply. Rights reserved
8
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instrument with excellent test–retest reliability, internal consistency, and interrater reliability38. e total score
from the subscale of social problems was used as a measure of interpersonal problems. e items of this subscale
relate to dierent areas of social functioning including peer rejection, interaction style, impact of peer rejection
(feeling lonely), and behaviors that are observed with peer rejection such as clumsiness and speech problems.
e subscales of social problems, anxiety/depression problems, and conduct problems have all been shown to
have high test–retest reliability38 and acceptable internal consistency (≥ 0.70) with the Norwegian translation62.
e standardized percentile scores were included in the statistical analyses.
Statistical analyses
All analyses were performed with SPSS, version 28. e longitudinal sample was rst described by testing group
dierences on sample characteristics with independent sample t-tests. To test for longitudinal eects of ADHD
on decision making, four analyses of variances (ANOVAs) were conducted with a 2 (ADHD vs. no ADHD) × 2
(eects of timepoint vs. no eects of timepoints) factorial design to test for between-group dierences on the
CGT scores of risk adjustment, delay aversion, reection time (inhibitory control), and risk proneness. An
interaction eect between ADHD and time points would suggest that the eect of ADHD on one of the CGT
scores would be specic to one of the time points. Age and gender were not included as covariates in the nal
ANOVA models due to not changing the signicant eects of ADHD on the CGT scores. See Supplemental
Table3 for the age-adjusted ANOVA results in which age only covaried with delay aversion and gender only
with risk proneness (see also Supplemental Tables4 and 5). Further, the eect of ADHD on social problems and
problems of conduct behavior and anxiety/depression was investigated with independent sample t-test analyses.
Bivariate correlations were estimated rst on the relationship between the parent-reported problem scores and
thereaer on the cross-sectional and longitudinal relationship between the CGT scores and the parent-reported
scores of social problems, conduct problems, and anxiety/depression problems. e baseline CGT scores (T1)
that correlated with the social and conduct and anxiety/depression problems at follow-up (T2) were further
included (simultaneous) as predictors in three multiple linear regression analyses with the follow-up parent
reported scores on social problems, conduct problems, and anxiety/depression problems as the outcome vari-
ables, respectively. Age was not included as a covariate in the nal linear regression models due to not covarying
with the parent-reported outcome scores of social problems, conduct problems, or anxiety/depression problems
(see Supplemental Table6 for the bivariate correlations between age and the CBCL scores of social problems,
anxiety/depression problems, and conduct problems).
We adjusted for multiple analyses by using Bonferroni correction of alpha level (α) in the between-group
analyses (ANOVAs); p = 0.05/4, (four CGT outcome scores) which gives an α corrected p level of 0.013, and in
the multiple linear regression analysis with parent-reported problem scores as the outcome variables; p = 0.05/3
(three CBCL outcome scores), which gives an α corrected p level of 0.017. Outliers were dened using a ± 3
standard deviations threshold from the sample mean and replaced and included in the statistical analyses with
a score of ± 3 standard deviations from the sample mean. On the CGT: One child with ADHD showed very long
reection time (z = 4.24) and two typically developing children showed very high scores on risk adjustment
(z = 3.18 and z = 3.52). No outlier scores were detected on the CBCL.
A priori estimation of statistical power was performed to determine the sample size needed to estimate longi-
tudinal statistical eects of ADHD on suboptimal decision making. Using g*power, we included the mean scores
of risk adjustment of the ADHD group (0.61) and the controls (1.20), respectively, from T120, and adjusted for
the statistical variance (SD = 0.65) of the ADHD group. We specied the conventional level of sucient power
to be 1−ß = 0.80 and a signicance of α = 0.05. e analysis revealed that a total number of n = 42 young people
would at least be required to avoid a type II error in our study, which is below our sample size of n = 47.
Data availability
e datasets used and analyzed during the current study are available from the corresponding author on reason-
able request.
Received: 24 May 2023; Accepted: 13 March 2024
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Acknowledgements
We would like to thank the children and parents who participated in the study and Dr. Hayley MacDonald for
language editing the manuscript. is work was supported by grants from the Research Council of Norway
(190544/H110), the Western Norway Health Authority (MoodNet and the Network for Anxiety Disorders;
911435, 911607, 911827) to KP and by grants from the Western Norway Health Authority (911460) and the
National Norwegian ADHD network to LS. is paper represents independent research part funded by the NIHR
Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College
London. e views expressed are those of the authors and not necessarily those of the NIHR or the Department
of Health and Social Care. Figure4 was printed with permission from Cambridge Cognition.
Author contributions
LS: Study design, experimental design, data collection, data analysis, interpretation, writing of the manuscript.
SA: Data collection, interpretation, writing of the manuscript. EK: Data collection, revision of the manuscript.
HE: Data collection, revision of the manuscript. KP: Study design, experimental design, data collection, revision
of the manuscript. ESB: Guiding data analysis, interpretation, writing of the manuscript.
Funding
Open access funding provided by University of Bergen.
Competing interests
Lin Sørensen has received small research funding for speaking and conference support from Medice in 2023.
Edmund Sonuga-Barke declares competing interest during the 3years prior to July 2023: Speaker fees, consul-
tancy or research funding from Medice, Takeda, Neurotech Solutions and QBTech. All other authors declare
no competing interests.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 024- 57041-x.
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