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Longitudinal associations between
ability in arts activities, behavioural
diculties and self-esteem:
analyses from the 1970 British
Cohort Study
Hei Wan Mak & Daisy Fancourt
Arts engagement has been shown to have benets for young people’s psychological and behavioural
adjustment. However, it is unknown whether it is frequency of arts engagement or individual ability in
arts activities that is associated with these benets. This study therefore examines the link between
arts ability and children’s behavioural diculties and self-esteem independent of frequency of
engagement. We analysed data from the 1970 British Cohort Study with an overall sample size of 7700
for the behavioural diculties outcome, and of 4991 for the self-esteem outcome. Baseline measures
were taken when the children were aged 10 and followed up at age 16. OLS regression analysis adjusted
for identied confounders shows that ability in the arts at age 10 was associated with a lower level
of behavioural diculties at age 16 independent of baseline behaviours, identied confounders and
frequency of arts engagement. An association between arts ability and self-esteem was only found
amongst children who have higher educational ability. These result suggest that there may be a value
to encouraging the cultivation of arts skills at the onset of adolescence as a way of helping to foster
children’s positive behavioural development.
A number of studies have identied a relationship between engagement in arts activities and young people’s
psychological and behavioural adjustment, including subjective and psychological well-being, prosocial attitudes
and behaviours, and self-esteem1–5. However, it remains unclear whether it is frequency of arts engagement or
individual ability in arts activities that is associated with such benets. A number of studies have shown that
frequency of engagement in arts activities can lead to enhanced individual ability, referring to a person’s skill in
performing artistic activities, such as painting, drawing, making models, and playing an instrument. For exam-
ple, practice alone or with others is positively associated with acquiring practical skills for musicians6, and vocal
training is associated with increased singing ability7. However, other studies have questioned this, suggesting that
frequencyof engagement and ability are in fact not causally linked, but could both be aected by other factors
including quality of engagement (rather than mere hours spent)8,9, individual genetic variation10, and social fac-
tors such as parental support and theteacher’s characteristics11. It is thereforeimportant to understand if there is a
link between ability in the arts and children’s psychological and behavioural adjustment independent of frequency
of engagement.
In considering how ability could be associated with young people’s behavioural and psychological adjustment,
two theories provide a framework. e General eory of Deviant Behaviour proposed by Kaplan12,13 suggests
that deviant behaviours (e.g. bullying, stealing) are responses to negative self-attitudes. Negative self-attitudes
arise if (a) people’s important others (e.g. family, peers) have negative attitudes towards them, (b) their ability to
cope with self-devaluing experiences is poor, and (c) they do not achieve success in things they value. Individual
ability in the arts may help to counter all three of these. First, ability may draw respect from family and peers as
well as helping more broadly in the development ofsocial connections and social cohesion14,15. Second, arts activ-
ities help enhance self-empowerment and self-worth in people’s own abilities16, which are particularly useful for
Department of Behavioural Science and Health, University College London, London, UK. Correspondence and
requests for materials should be addressed to D.F. (email: d.fancourt@ucl.ac.uk)
Received: 23 May 2019
Accepted: 22 August 2019
Published: xx xx xxxx
OPEN
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developing social resilience and tackling challenges in other aspects of their lives17. ird, in common with almost
all other abilities (e.g. reading and mathematical ability), a high level of arts ability could give rise to a strong sense
of accomplishment. For instance, previous research has found a correlation between positive self-perceived musi-
cal skills, continuation of music participation and a feeling of achievement18,19. Further, it has been suggested by
Bandura’s Self-Ecacy eory20 that people with high levels of condence in their ability (such as in the arts) have
a greater sense of self-esteem. So it is plausible that the development of individual ability in the arts could translate
into psychological and behavioural benets.
In this study, therefore, we explored the longitudinal association between arts ability at age 10 and both behav-
ioural diculties and self-esteem at age 16: a sensitive developmental period as individuals who experience
behavioural and psychological diculties at this age may be at substantially elevated risk of deviant behaviours
and mental disorders later in life21–23. Further, we explored whether this relationship was maintained even when
considering frequency of arts engagement.
Results
Demographics. We used data from the 1970 British Cohort Study (BCS70), a prospective longitudinal sur-
vey. is study used Waves 3 (1980) and 4 (1986) interviews when the children were aged 10 and 16 respectively.
A total of 10,651 participants and their parents provided data in both waves, of whom 7,700 provided data for the
outcome measure of behavioural diculties (measured using the Rutter Behaviour Scale) and 4,991 provided data
for the outcome measure of self-esteem (measured using the Lawrence’s Self-Esteem Questionnaire). Multiple
imputation was used to account for missing data on covariates to maintain this sample size. Of these participants,
49% were females and 96% of them were White. On average, 60% of the cohort had both parents who were work-
ing (see Table1).
Arts ability and behavioural diculties. We used OLS regression models to investigate the association
between arts ability (measured as a standardised average of mothers’ ratings of their children’s ability in painting
and drawing at home, making models, playing a musical instrument and reading music) and adolescents’ behav-
ioural diculties and self-esteem. Amongst the whole sample, a higher level of arts ability was associated with a
lower level of behavioural diculties in our unadjusted model (Table2) (coef = −0.14, SE = 0.01, p < 0.001). is
association was reduced by the inclusion of demographic factors (gender, ethnicity, parental employment status,
household income, SES, parents’ education, family composition, and the number of children in the household),
educational factors (children’s academic ability in maths, spelling, creative writing, reading, verbal ability and
non-verbal ability as well as their physical activity), parent-child interactions (maternal interest in child’s edu-
cation and the time spent on talking to the parents each day),and psychological factors (mothers’ malaise, child
extroversion, child anxiety, and baseline behavioural diculties). However, the relationship was still maintained
even when controlling for all of these identied confounders (coef = −0.06, SE = 0.01, p < 0.001). is nding
was consistent amongst children who had both lower (coef = −0.06, SE = 0.02, p = 0.001) and higher levels of arts
engagement (coef = −0.05, SE = 0.02, p = 0.015).
Results were consistent when stratifying the sample by level of SES (lower SES: coef = −0.05, SE = 0.02,
p = 0.010; higher SES: coef = −0.06, SE = 0.02, p < 0.001) and by level of educational ability (lower educa-
tional ability: coef = −0.05, SE = 0.02, p = 0.001; higher educational ability: coef = −0.05, SE = 0.02, p = 0.006)
(Table3). Further, ndings were consistent in both boys and girls (boys: coef = −0.07, SE = 0.02, p < 0.001; girls:
coef = −0.05, SE = 0.02, p = 0.003) (Supplementary Table1). When excluding those with behavioural problems at
baseline (the worst 20% of behavioural scores), results were also maintained (coef = −0.05, SE = 0.01, p < 0.001)
(Supplementary Table2). When using the categorical rather than linearscoring system for the Rutter scale which
categorises children as having ‘normal’, ‘moderate’ or ‘severe’ behavioural problems, higher levels of arts ability
at age 10 were associated with lower odds of developing severe behavioural diculties by age 16 (coef = −0.22,
SE = 0.08, p = 0.006) (Supplementary Table3). Additionally, when exploring specic sub-componentsof behav-
ioural problems,arts ability was associated with a lower probability of developing aggressiveness and hyper-
activity, but the association with anxiety/fearfulness was attenuated when including baseline mental health
(aggressiveness: coef = −0.03, SE = 0.01, p = 0.039; anxiety-fearfulness: coef = −0.02, SE = 0.01, p = 0.215; hyper-
activity: coef = −0.06, SE = 0.01, p < 0.001) (Supplementary Table4). Finally, when deconstructing the meas-
ure of arts abilityinto individual activities we found that the ability in making models (coef = −0.05, SE = 0.01,
p < 0.001), playing a musical instrument (coef = −0.03, SE = 0.01, p = 0.016) and reading music (coef = −0.05,
SE = 0.01, p < 0.001) were associated with a lower level of behavioural diculties, but the association between
painting and drawing at home and behavioural diculties was attenuated aer controlling for parent-child inter-
actions and mental health factors (coef = 0.00, SE = 0.01, p = 0.984) (Supplementary Table5).
Arts ability and self-esteem. ere was a less consistent association between arts ability and self-esteem.
Although arts ability and self-esteem were related in unadjusted models (coef = 0.10, SE = 0.02, p < 0.001),
and even when controlling for demographic factors (coef = 0.07, SE = 0.02, p < 0.001) and educational factors
(coef = 0.03, SE = 0.02, p = 0.047), when considering parent-child interactions, maternal and child mental health,
and baseline behaviours, this association was attenuated (coef = 0.02, SE = 0.02, p = 0.235) (Table2). Results
in fully-adjusted models remained non-signicant when splitting the sample by lower (coef = 0.02, SE = 0.02,
p = 0.499) and higher arts engagement (coef = −0.00, SE = 0.03, p = 0.915) (Table2).
When considering sub-group analyses, the relationship was found amongst those of higher educational ability
(coef = 0.06, SE = 0.03, p = 0.035)and there were suggestions it was present in those of higher SES (coef = 0.05,
SE = 0.02, p = 0.055), but itwas not foundamongst those of lower SES (coef = −0.01, SE = 0.02, p = 0.819) or
lower educational ability (coef = −0.01, SE = 0.02, p = 0.725) (Table3). When stratifying the sample by gender,
no signicant association was found between arts ability and self-esteem (boys: coef = 0.01, SE = 0.03, p = 0.827;
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girls: coef = 0.03, SE = 0.02, p = 0.206) (Supplementary Table1). ere was also no evidence for the association
when excluding those with baseline behavioural problems (coef = −0.01, SE = 0.02, p = 0.958) (Supplementary
Table2). When deconstructing type of arts activity, there was no association between any of the individual arts
activities and children’s self-esteem aer controlling for all covariates (Supplementary Table5).
Discussions
Prior research has oen shown that arts engagement is associated with better psychological and behavioural
outcomes amongstyoung people, but most research has focused on frequency of engagement. is study went
beyond this and investigated the relationship between arts ability and adolescents’ behavioural diculties and
self-esteem. We found that arts ability at age 10 is signicantly, inversely associated with behavioural diculties
at age 16. It is of note that factors such as demographics, SES, child academic abilities, child mental health and
maternal mental health explained a large proportion of this association. is is as expected, given that such
factors are linked both with access to the arts and also with child mental health24–26. However, results were main-
tained independent of these factors. In particular, the association between arts ability and behavioural diculties
Variables Mean (SE)/%
Outcome (age 16): Child behaviours Rutter behaviour scale (unstandardized; ranges from 20 to 60) 23.4 (4.12)
Self-esteem (unstandardized; ranges from 0 to 20) 6.14 (8.38)
Exposure (age 10): Arts ability Arts ability (unstandardized; ranges from 0 to 100) 58.2 (20.6)
Covariates (age 10): Gender Female 49%
Ethnicity White 96%
Parents’ employment status
No parents work 8.3%
One parent works 32.3%
Both parents work 59.5%
Household income
<£35–£49 per week 6.7%
£50–£99 per week 30.1%
£100–£149 per week 34.4%
£150–£199 per week 16.5%
£200–£250+ per week 12.4%
Parents’ socio-economic status
Professional 5.7%
Intermediate 23.0%
Skilled non-manual 10.7%
Unskilled manual 41.7%
Partly skilled 14.3%
Unskilled 4.7%
Parents’ education
No qualication 51.9%
O-level/A-level/Certicate of Education 26.2%
Degree 10.2%
Other qualication(s) 11.7%
Family composition Intact family 21.1%
Number of children in the household 2.47 (0.02)
Child’s educational ability
Higher education abilitya41.5%
British Ability Scale: (Verbal) Word denitions −0.17 (0.02)
British Ability Scale: (Verbal) Word similarities −0.12 (0.02)
British Ability Scale: (Non- verbal) Recall of digits −0.06 (0.02)
British Ability Scale: (Non-verbal) Matrices −0.23 (0.02)
Reading ability 0.17 (0.01)
Physical activity Freq. of physical activityb2.42 (0.01)
Parent-child interactions Mother’s interest in children’s educationc3.40 (0.01)
Time spent on talking to the parents each dayd2.59 (0.00)
Mother’s mental health
Child’s personalities and behaviour
Mother’s malaise scoree−0.12 (0.01)
Child’s extroversion scalef−0.02 (0.02)
Child’s anxiousness scaleg−0.05 (0.02)
Rutter behaviour scaleh420.01 (3.76)
Table 1. Descriptive statistics. Note: aAn additive score of various subjects, including maths, spelling, and
creative writing. bA three-point scale, “never/hardly ever”, “sometimes”, and “oen”. cA four-point scale,
“uninterested”, “very little interested”, “moderate interested”, and “very interested”. dA three-point scale, “none at
all”, “not very much”, and “quite a lot”. eDervied from 22 items with a 1–100 scale (standardised). fAn introvert-
extrovert scale rated from the teacher (standardised). gAn unworried-anxious scale rated from the teacher
(standardised). he sum of 19 items with a visual analogue scale (each item ranges from 0 to 100).
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remains signicant amongst children with lower levels of arts engagement frequency. is suggests that arts abil-
ity may have an independent relationship with positivebehavioural development in childhood.
On the contrary, we found less evidence of a relationship between arts ability and self-esteem. is echoes
ndings from previous research that showed no association between music, art or reading ability and self-esteem
at age 1127. However, it is of note that we did nd a relationship in our sub-group analyses for children with
stronger educational ability at age 10. Previous research has shown a relationship between positive self-worth
and school grades, with a further relationship with lower delinquency28. So it is possible that, although arts abil-
ity may not be related to self-esteem amongst all children, amongst those who are already showing strong aca-
demic achievement (and related self-esteem), arts ability may have additive benets. However, this remains to be
explored further.
is study has several limitations. First, causality cannot be assumed from these observational ndings.
However, we did use a large and nationally-representative dataset, longitudinal tracking over 6 years, and we
controlled for all identied confounding factors at baseline. Second, while we aimed to disentangle frequency
of engagement from ability by stratifying the sample, it is reasonable to believe that someaspects of behavioural
diculties and self-esteem may still be inuenced by frequency of engagement, rather than the arts ability alone.
Future studies could build on these ndings by using advanced techniques (e.g. propensity score matching) to
disentangle the relationship between arts ability and frequency of arts engagement. We also believe there is scope
for a better understanding of the Rutter Behaviour Scale’s underlying dimensions; our supplementary analysis
suggest that arts ability may exert greater inuence on children’s aggressiveness and hyperactivity than their
anxiety-fearfulness, but these three latent variables extracted from a factor analysis only accounted for 40% of
the variance. Whilst this was in line with previous factor analyses of the scale, further work exploring these
separate constructs in more detail using other data could help to elucidate what the potential benets of cultivat-
ing ability in arts activities are for child behaviours. We were also only able to examine children’s Rutter scores
based on mothers’ reports, as teachers’ reports on the Rutter questions were not available in the data. It would be
worthwhile to repeat the analyses using teacher’s reports, given these have been shown to produce more reliable
estimates29.
Finally, our denition of arts ability was limited by what questions were available within BCS70. We were
unable to explore children’s ability in other popular arts activities such as drama and dance. Our results suggest
that average ability in arts activities and also specic ability in music and cras are associated with positivebehav-
ioural development, but for painting and drawing results are attenuated when considering maternal mental health
and child behaviours. Notably, there was an overall higher mean ability for painting and drawing and less variabil-
ityin ability score, which could have led to a ceiling eect explaining the lack of sustained signicance of the nd-
ing. But it is also possible that there are subtle distinctions between types of activity that inuence behaviours. So
future studies might wish to consider a wider range of arts activities when investigating the relationship between
arts ability and children’s behavioural and psychological adjustment.
Overall, our results suggest there is an independent longitudinal relationship between arts ability and behav-
ioural diculties around the onset of adolescence, but not with self-esteem. ese ndings imply there could be a
value to encouraging the cultivation of creative skills around the onset of adolescence as a way of helping to buer
against of aggression and hyperactivity and promoting positive behavioural development.Future intervention
studies are therefore encouraged.
Methods
Participants. is study analysed data from the 1970 British Cohort Study (BCS70); a prospective longitu-
dinal survey that follows a group of people (N = 17,000) from infancy into adulthood (age 50). Data were drawn
from Waves 3 (1980) and 4 (1986) interviews when the children were aged 10 and 16 respectively. A total of
10,651 participants and their parents provided data in both waves. Of these, around 72% of the parents were given
the questionnaire for behavioural diculties at Wave 4 (N = 7700) and 3706 participants provided full data across
all othermeasures that were included in analyses. With respect to the self-esteem items, only 50% of the cohort
members were given the questionnaire for self-esteem (N = 4991) in the Wave 4 interview and, of these, 1922
provided full data across all othermeasuresincluded in the analyses. e reduction in sample size across both
measureswaslargelydue to cohort members having le school, and industrial action by the teachers, resulting
in a delay of the survey and incomplete data collection30. So multiple imputation was used to account for missing
data, providing an overall sample size of 7700 for the Rutter Behaviour scale outcome and 4991 for the self-esteem
outcome.
BCS70 has received ethical approval from the NHS Multi-Centre Research Ethics Committee (MREC) and
all participants gave informed consent. All methods were performed in accordance with the relevant guidelines
and regulations.
Measures. We used the Rutter Behaviour Scale reported by mothers to measure children’s behaviour at home
and at school: a well-validated instrument that was originally developed for use with British children/adolescents
and has been used in epidemiological and psychological studies to detect behavioural problems in young peo-
ple31. Our main model was based on an additive scale derived from 20 items, in which parents were asked to give
descriptions of children’s behaviours (i.e. “does not apply”; “applies somewhat”; “denitely applies”). e scale was
then standardised to have a mean of zero and a standard deviation of 1, with higher scores indicating a greater
incidence of behavioural diculties.
For self-esteem, we used the Lawrence’s Self-Esteem Questionnaire (LAWSEQ) to measure children’s
self-reported sense of self-worth and self-esteem32. e scale was derived from 10 items, ranging from 0 (the
lowest self-esteem score) to 20 (the highest self-esteem score), and standardised.
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Children’s abilities in arts at age 10 were rated by their motherson a scale from 0 to 100. We created an index
of average ability derived from 4 ability scales - painting and drawing at home, making models, playing a musical
instrument, and reading music. e scale was averaged and then standardised.
We identied a number of potentially confounding factors that we controlled for at baseline (age 10). For
demographic and socio-economic factors, we included parent-reported gender, ethnicity (white or non-white),
parental employment status (no parents work, one parent works, or both parents work), household income
(£ per week), socio-economic status (SES; professional, intermediate, skilled non-manual, unskilled manual,
partly skilled, or unskilled), parents’ education (no qualication, O-level/A-level/Certicate of Education, degree,
or other qualication(s)), family composition (intact or non-intact family), number of children in the house-
hold, mothers’ malaise score, andchildren’s frequency of physical activity. For child academic ability, we included
both subjective and objective measures including children’s self-reportedacademicabilities (binary scores assess-
ingwhether children felt they did well vs did not do well inmaths, spelling, and creative writing;summed and
then binarised into the top 40% of responses vs other responses), parent-reported childreading ability (a stand-
ardised scale of an average of three reading-related abilities rated by the mother: recalling the content of a book,
making use of public library, and reading comics and magazines), and objectiveacademic ability using the British
Ability Scales (BAS) at age 1033. is scale has four academic ability subscales: word denitions and word similar-
ities (to measure verbal ability), and recall of digits and matrices (to measure non-verbal ability).
We also adjusted for several variables that captured the interactions between children and their parents: mother’s
interest in child’s education (reported by teachers) and the time that children reportedspending talking to their
parents each day. Additionally, we controlled for children’s mental healthand behaviours at baseline: the degree
of extroversion (rated by teachers; standardised), the level of anxiety (rated by teachers; standardised), and behav-
ioural diculties measured using the Rutter behaviour scale (rated by mothers; a visual analogue scale with a
meanscore of 420).
Whole sample Lower arts engagement frequency at age 10 Higher arts engagement frequency at age 10
Behavioural diculties Self-esteem Behavioural diculties Self-esteem Behavioural diculties Self-esteem
B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P
Model 1 −0.14 ± 0.01 <0.001 0.10 ± 0.02 <0.001 −0.14 ± 0.02 <0.001 0.07 ± 0.02 =0.001 −0.12 ± 0.02 <0.001 0.06 ± 0.03 =0.028
Model 2 −0.13 ± 0.01 <0.001 0.07 ± 0.02 <0.001 −0.13 ± 0.02 <0.001 0.05 ± 0.02 =0.025 −0.10 ± 0.02 <0.001 0.03 ± 0.03 =0.193
Model 3 −0.09 ± 0.01 <0.001 0.03 ± 0.02 =0.047 −0.09 ± 0.02 <0.001 0.03 ± 0.02 =0.182 −0.09 ± 0.02 < 0.001 0.01 ± 0.03 =0.816
Model 4 −0.06 ± 0.01 <0.001 0.02 ± 0.02 =0.235 −0.06 ± 0.02 =0.001 0.02 ± 0.02 =0.499 −0.05 ± 0.02 =0.015 −0.00 ± 0.03 =0.915
N 7700 4991 4622 2827 3020 2113
Table 2. Relationship between arts ability (age 10) and behavioural diculties and self-esteem (age 16): the
whole sample and stratied sample by arts engagement frequency. Note: Statistical signicance is denoted by
asterisks: *sig at 5%, **sig at 1%, ***sig at 0.1%. Model 1 was unadjusted, model 2 adjusted for demographic
factors (gender, ethnicity, parental employment status, household income, SES, parents’ education, family
composition, and number of children in the household), model 3 additionally adjusted for child academic
ability (maths, spelling, creative writing, reading, verbal ability and non-verbal ability) as well as physical
activity, while model 4 additionally controlled for parent-child interactions (mother’s interest in child’s
education and the time spent on talking to the parents each day) and mental health (mothers’ malaise, child
extroversion, child anxiety, and baseline behavioural diculties).
Lower SES Higher SES Lower education Higher education
Behavioural
diculties Self-esteem Behavioural
diculties Self-esteem Behavioural
diculties Self-esteem Behavioural
diculties Self-esteem
B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P B ± SE P
Model 1 −0.11 ± 0.02 <0.001 0.04 ± 0.02 =0.046 −0.15 ± 0.02 <0.001 0.11 ± 0.02 <0.001 −0.14 ± 0.02 <0.001 0.06 ± 0.02 =0.002 −0.14 ± 0.02 <0.001 0.10 ± 0.02 <0.001
Model 2 −0.10 ± 0.02 <0.001 0.04 ± 0.02 =0.122 −0.15 ± 0.02 <0.001 0.10 ± 0.02 <0.001 −0.13 ± 0.02 <0.001 0.04 ± 0.02 =0.115 −0.12 ± 0.02 <0.001 0.09 ± 0.03 =0.001
Model 3 −0.08 ± 0.02 <0.001 0.01 ± 0.02 =0.758 −0.10 ± 0.02 <0.001 0.06 ± 0.02 =0.013 −0.09 ± 0.02 <0.001 0.01 ± 0.02 =0.645 −0.08 ± 0.02 <0.001 0.06 ± 0.03 =0.015
Model 4 −0.05 ± 0.02 =0.010 −0.01 ± 0.02 =0.819 −0.06 ± 0.02 <0.001 0.05 ± 0.02 =0.055 −0.05 ± 0.02 =0.001 −0.01 ± 0.02 =0.725 −0.05 ± 0.02 =0.006 0.06 ± 0.03 =0.035
N 3277 2254 4356 2679 4334 2784 3289 2136
Table 3. By parents’ SES and children’s education performance. Note: Statistical signicance is denoted by
asterisks: *sig at 5%, **sig at 1%, ***sig at 0.1%. Model 1 was unadjusted, model 2 adjusted for demographic
factors (gender, ethnicity, parental employment status, household income, SES, parents’ education, family
composition, and number of children in the household), model 3 additionally adjusted for child academic
ability (maths, spelling, creative writing, reading, verbal ability and non-verbal ability) as well as physical
activity, while model 4 additionally controlled for parent-child interactions (mother’s interest in child’s
education and the time spent on talking to the parents each day) and mental health (mothers’ malaise, child
extroversion, child anxiety, and baseline behavioural diculties).
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Statistics. To account for missing values and attrition between waves, multiple imputation by chained equations
using all variables included in our statistical models was carried out to create 50 imputed data sets. We used regress,
logit and mlogit commands within the mi command to impute linear, binary and categorical variables respectively.
Missingness across variables is shown in Supplementary Tables6 and 7. Sensitivity analyses using the available data
produced very similar results, so we present results from the imputed data sets for greater statistical power.
OLS regression models were used to investigate the association between arts ability and adolescents’ behav-
ioural diculties and self-esteem. In order to identity possible underlying mechanisms that may explain the
association, we built our models sequentially. Model 1 was unadjusted, model 2 adjusted for demographic factors
(gender, ethnicity, parental employment status, household income, SES, parents’ education, family composition,
number of children in the household), model 3 additionally adjusted for child academic ability (maths, spell-
ing, creative writing, reading, verbal ability and non-verbal ability) as well as physical activity, while model 4
additionally controlled for parent-child interactions (mother’s interest in child’s education and the time spent
on talking to the parents each day) and mental health (mothers’ malaise, child extroversion, child anxiety, and
baseline behavioural diculties). e risk of multicollinearity was very low with a mean value of the Variance
Ination Factor (VIF) of 1.22, suggesting that our analyses did not violate the OLS assumptions. All other model
assumptions were also met. Given we had two outcome variables, a Bonferroni correction with an alpha of 0.05/2
(outcomes) = 0.025 can be applied to assess the signicance of results aer adjustment for multiple comparisons.
Given that arts ability and frequency of arts engagement was highly correlated (r = 0.51), in addition to ana-
lysing the whole sample, we also stratied the sample into two sub-groups using a median split: lower arts engage-
ment frequency and higher arts engagement frequency. Frequency ofarts engagement was measured by reports
from mothers as to the frequency with which their childengaged invarious arts activities, including going to a
museum and playing a musical instrument.
As supplementary analyses, we repeated the analyses stratied by (1) parents’ SES, (2) children’s educational
performance, and (3) children’s gender to assess whether there were any sub-group dierences. Additionally,
to assess whether results were skewed by inclusion of those with behavioural diculties at baseline, we car-
ried out the analyses by excluding the respondents who were at the top 20% on the Rutter Behaviour Scale (i.e.
those with the highest behavioural diculties). We also tested whether using the alternative scoring system for
the Rutter scale aected results by additionally presenting models using the categorical indicator of behaviours
which divides children into three subgroups- (a) “normal”, scores below the 80th percentile; (b) “moderate”,
scores between the 80th and 95th percentile; and (c) “severe”, scores above the 95th percentile34). In order to iden-
tify any potential underlying sub-categories of the Rutter Behaviour Scale, we also performed a factor analysis
and extracted three factors (as also were found in McGee et al.‘s study35): aggressiveness (Cronbach’s α = 0.80),
anxiety-fearfulness (Cronbach’s α = 0.68), and hyperactivity (Cronbach’s α = 0.62). e three-factor structure of
Rutter Behaviour Scale was conrmed by eigenvalues >1 and visual inspection of a screeplot according to Kaiser’s
elbow criterion36 accounted for 40% of the variance (Kaiser-Meyer-Olkin = 0.88), in line with previous factor
analyses of this scale35. Finally to test whether results were driven by average ability in any arts activity or a specic
ability in a particular arts activity, we split our ability index into an individual ability score foreach activity and
re-ran analyses.
Data Availability
e 1970 British Cohort Study data set is available via the UK Data Service.
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Acknowledgements
DF is supported by the Wellcome Trust [205407/Z/16/Z]. HWM is funded through the AHRC project HEARTS
(AH/P005888/1). e anonymous 1970 British Cohort Study data are publicly-available through the UK Data
Service.
Author Contributions
D.F. and H.W.M. designed the study. H.W.M. carried out the analyses and draed the manuscript. Both authors
critically reviewed the manuscript and approved it for submission.
Additional Information
Supplementary information accompanies this paper at https://doi.org/10.1038/s41598-019-49847-x.
Competing Interests: e authors declare no competing interests.
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