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Longitudinal associations between ability in arts activities, behavioural difficulties and self-esteem: analyses from the 1970 British Cohort Study

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Abstract

Arts engagement has been shown to have benefits 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 benefits. This study therefore examines the link between arts ability and children’s behavioural difficulties 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 difficulties 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 identified confounders shows that ability in the arts at age 10 was associated with a lower level of behavioural difficulties at age 16 independent of baseline behaviours, identified 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.
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Longitudinal associations between
ability in arts activities, behavioural
diculties and self-esteem:
analyses from the 1970 British
Cohort Study
Hei Wan Mak & Daisy Fancourt
Arts engagement has been shown to have benets 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 benets. This study therefore examines the link between
arts ability and children’s behavioural diculties 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 diculties 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 identied confounders shows that ability in the arts at age 10 was associated with a lower level
of behavioural diculties at age 16 independent of baseline behaviours, identied 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 identied 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-esteem15. However, it remains unclear whether it is frequency of arts engagement or
individual ability in arts activities that is associated with such benets. 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
frequencyof engagement and ability are in fact not causally linked, but could both be aected 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 theteacher’s characteristics11. It is thereforeimportant to understand if there is a
link between ability in the arts and childrens 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 ofsocial 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-Ecacy eory20 that people with high levels of condence 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 benets.
In this study, therefore, we explored the longitudinal association between arts ability at age 10 and both behav-
ioural diculties and self-esteem at age 16: a sensitive developmental period as individuals who experience
behavioural and psychological diculties at this age may be at substantially elevated risk of deviant behaviours
and mental disorders later in life2123. 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 diculties (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 Table1).
Arts ability and behavioural diculties. 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 diculties and self-esteem. Amongst the whole sample, a higher level of arts ability was associated with a
lower level of behavioural diculties in our unadjusted model (Table2) (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 (childrens 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 diculties). However, the relationship was still maintained
even when controlling for all of these identied 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)
(Table3). 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 Table1). 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 Table2). When using the categorical rather than linearscoring 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 diculties by age 16 (coef = 0.22,
SE = 0.08, p = 0.006) (Supplementary Table3). Additionally, when exploring specic sub-componentsof 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 Table4). Finally, when deconstructing the meas-
ure of arts abilityinto 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 diculties, but the association between
painting and drawing at home and behavioural diculties was attenuated aer controlling for parent-child inter-
actions and mental health factors (coef = 0.00, SE = 0.01, p = 0.984) (Supplementary Table5).
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) (Table2). Results
in fully-adjusted models remained non-signicant 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) (Table2).
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 itwas not foundamongst 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) (Table3). When stratifying the sample by gender,
no signicant 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 Table1). 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
Table2). When deconstructing type of arts activity, there was no association between any of the individual arts
activities and children’s self-esteem aer controlling for all covariates (Supplementary Table5).
Discussions
Prior research has oen shown that arts engagement is associated with better psychological and behavioural
outcomes amongstyoung 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 diculties and
self-esteem. We found that arts ability at age 10 is signicantly, inversely associated with behavioural diculties
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 health2426. However, results were main-
tained independent of these factors. In particular, the association between arts ability and behavioural diculties
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 qualication 51.9%
O-level/A-level/Certicate of Education 26.2%
Degree 10.2%
Other qualication(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 denitions 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 scoree0.12 (0.01)
Child’s extroversion scalef0.02 (0.02)
Child’s anxiousness scaleg0.05 (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 “oen. 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). he sum of 19 items with a visual analogue scale (each item ranges from 0 to 100).
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remains signicant amongst children with lower levels of arts engagement frequency. is suggests that arts abil-
ity may have an independent relationship with positivebehavioural 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 benets. 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 identied 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 someaspects of behavioural
diculties and self-esteem may still be inuenced 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 inuence 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 benets of cultivat-
ing ability in arts activities are for child behaviours. We were also only able to examine childrens 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 denition 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 specic ability in music and cras are associated with positivebehav-
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-
ityin ability score, which could have led to a ceiling eect explaining the lack of sustained signicance of the nd-
ing. But it is also possible that there are subtle distinctions between types of activity that inuence behaviours. So
future studies might wish to consider a wider range of arts activities when investigating the relationship between
arts ability and childrens behavioural and psychological adjustment.
Overall, our results suggest there is an independent longitudinal relationship between arts ability and behav-
ioural diculties 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 buer
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 diculties at Wave 4 (N = 7700) and 3706 participants provided full data across
all othermeasures 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 othermeasuresincluded in the analyses. e reduction in sample size across both
measureswaslargelydue 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 childrens behaviours (i.e. “does not apply”; “applies somewhat”; “denitely 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 diculties.
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 motherson 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 identied 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 qualication, O-level/A-level/Certicate of Education, degree,
or other qualication(s)), family composition (intact or non-intact family), number of children in the house-
hold, mothers’ malaise score, andchildrens frequency of physical activity. For child academic ability, we included
both subjective and objective measures including children’s self-reportedacademicabilities (binary scores assess-
ingwhether children felt they did well vs did not do well inmaths, spelling, and creative writing;summed and
then binarised into the top 40% of responses vs other responses), parent-reported childreading 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 objectiveacademic ability using the British
Ability Scales (BAS) at age 1033. is scale has four academic ability subscales: word denitions 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 reportedspending talking to their
parents each day. Additionally, we controlled for children’s mental healthand behaviours at baseline: the degree
of extroversion (rated by teachers; standardised), the level of anxiety (rated by teachers; standardised), and behav-
ioural diculties measured using the Rutter behaviour scale (rated by mothers; a visual analogue scale with a
meanscore of 420).
Whole sample Lower arts engagement frequency at age 10 Higher arts engagement frequency at age 10
Behavioural diculties Self-esteem Behavioural diculties Self-esteem Behavioural diculties 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 diculties and self-esteem (age 16): the
whole sample and stratied sample by arts engagement frequency. Note: Statistical signicance 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 diculties).
Lower SES Higher SES Lower education Higher education
Behavioural
diculties Self-esteem Behavioural
diculties Self-esteem Behavioural
diculties Self-esteem Behavioural
diculties 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 signicance 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 diculties).
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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 Tables6 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 diculties 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 diculties). e risk of multicollinearity was very low with a mean value of the Variance
Ination 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 signicance of results aer 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 stratied the sample into two sub-groups using a median split: lower arts engage-
ment frequency and higher arts engagement frequency. Frequency ofarts engagement was measured by reports
from mothers as to the frequency with which their childengaged invarious arts activities, including going to a
museum and playing a musical instrument.
As supplementary analyses, we repeated the analyses stratied by (1) parents’ SES, (2) children’s educational
performance, and (3) childrens gender to assess whether there were any sub-group dierences. Additionally,
to assess whether results were skewed by inclusion of those with behavioural diculties 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 diculties). We also tested whether using the alternative scoring system for
the Rutter scale aected 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 (Cronbachs α = 0.68), and hyperactivity (Cronbach’s α = 0.62). e three-factor structure of
Rutter Behaviour Scale was conrmed 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 specic
ability in a particular arts activity, we split our ability index into an individual ability score foreach 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 draed 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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... Due to these shortcomings, it is relevant to examine whether broader arts engagement could reduce the risk of externalising behaviours occurring in the first instance 21 . There is some evidence to suggest creativity and artistic ability are helpful in reducing the risk of externalising behaviors [22][23][24][25] , but the literature is limited. Therefore, more work is needed to identify whether arts engagement could be a positive strategy in preventing or reducing externalising behaviours during adolescence. ...
... There has been little research into the use of arts as a risk-reduction strategy for externalising behaviours (as opposed to as an intervention). Our findings that extracurricular arts activities are associated with reduced externalising behaviours align with the little longitudinal evidence available in this area and further supports the theory that arts may be an effective risk reduction strategy 22,23 . There are numerous well known benefits of arts engagement that may aid in the reduction of externalising behaviours, which can occur on the individual, group, and/or societal level 34 . ...
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Introduction: Externalising behaviours during adolescence are associated with numerous long-term negative outcomes, although the majority of research is intervention-based as opposed to focused on risk reduction. Arts engagement has been associated with numerous beneficial factors linked to externalising behaviours, yet direct evidence linking them in longitudinal studies is lacking. / Methods: Data from the Early Childhood Longitudinal Study were used, with baseline taken at 5th grade (aged 10-11 years) and outcomes measured at 8th grade (13-14 years). Ordinary least squares regression was used to examine individual-level associations between extracurricular and school-based arts engagement (number arts classes and adequacy of arts facilities) with externalising behaviours measured using the Strengths and Difficulties Questionnaire. Poisson regression was used to examine associations between school-level arts classes and facilities with an administrator-reported index of externalising behaviours in the school. All models were adjusted for sociodemographic factors. Individual-level analyses were clustered by school. / Results: At the individual level, engaging in a greater number of extracurricular arts activities in 5th grade was associated with fewer externalising behaviours in 8th grade, although there was no association for school-based arts engagement. There were no school-level associations between arts classes or adequate arts facilities and externalising behaviours. / Conclusions: Our results suggest extracurricular arts activities may be beneficial in reducing the risk for externalising behaviours, but the relationship is seen at an individual-level of engagement rather than based on school-level provision or facilities. Ensuring extracurricular access to the arts should be considered as a cost-effective way of preventing externalising behaviours while simultaneously promoting healthy emotional, coping, and social behaviours.
... It seems to be required to consider socioeconomic and demographic elements for these situations. The reason is that arts or music engagement would be often associated with each self-esteem who has developed to the professional education level [24]. For latest report, partnerships among academic researchers and research-oriented organizations or private music industries can contribute the cooperative development and data integrity, leading to of higher quality in this category [25]. ...
... Research shows that taking into account confounding factors such as age, socioeconomic status and gender, consuming art has a tangible impact on self-reported wellbeing (Fancourt & Steptoe, 2019;Mak & Fancourt, 2019;Wang et al., 2020). Whilst the neuroscientific underpinnings of such effects have yet to be explored, plausible mechanisms function via DMN engagement and connectivity (Luo et al., 2016;Shi et al., 2018;Williams et al., 2018) and reduction in stress related hormones and associated physiological changes (Kaimal et al., 2016;Mastandrea et al., 2019). ...
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... Of course, these correlational effects may not necessarily reflect causal associations, but could be due to bidirectional influences, as suggested by claims that musicians may be at higher risk for internalizing problems [54][55][56]. It is also necessary to consider demographic and socioeconomic factors in these associations [57], for example, because arts engagement may be more strongly associated with self-esteem in those with higher education [58]. ...
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... Of course, these correlational effects may not necessarily reflect causal associations, but could be due to bidirectional influences, as suggested by claims that musicians may be at higher risk for internalizing problems 54-56 . It is also necessary to consider demographic and socioeconomic MUSIC ENGAGEMENT AND MENTAL HEALTH 11 factors in these associations 57 , for example, because arts engagement may be more strongly associated with self-esteem in those with higher education 58 . ...
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Is engaging with music good for your mental health? This question has long been the topic of empirical clinical and nonclinical investigations, with studies indicating positive associations between music engagement and quality of life, reduced depression or anxiety symptoms, and less frequent substance use. However, many earlier investigations were limited by small populations and methodological limitations, and it has also been suggested that aspects of music engagement may even be associated with worse mental health outcomes. The purpose of this scoping review is first to summarize the existing state of music engagement and mental health studies, identifying their strengths and weaknesses. We focus on broad domains of mental health diagnoses including internalizing psychopathology (e.g., depression and anxiety symptoms and diagnoses), externalizing psychopathology (e.g., substance use), and thought disorders (e.g., schizophrenia). Second, we propose a theoretical model to inform future work that describes the importance of simultaneously considering music-mental health associations at the levels of (1) correlated genetic and/or environmental influences versus (bi)directional associations, (2) interactions with genetic risk factors, (3) treatment efficacy, and (4) mediation through brain structure and function. Finally, we describe how recent advances in large-scale data collection, including genetic, neuroimaging, and electronic health record studies, allow for a more rigorous examination of these associations that can also elucidate their neurobiological substrates.
... Third, self-esteem was measured using a reduced version of the LAWSEQ containing 10 of the 16 original items. However, this version was used with adolescents previously (Mak and Fancourt, 2019;Viner and Cole, 2006), and is based on evidence that the scale is unidimensional (Rae et al., 2011). Finally, it is possible that unmeasured confounders, such as psychological or mental health issues, might have influenced the results. ...
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