Family Fun and School Success
A Wirral-based study commissioned by the Rt Hon. Frank Field MP, funded by the
Westminster Foundation & conducted by the Centre for Family Research &
Psychometrics Centre, University of Cambridge.
Starting school is, for many children, both exciting and enjoyable. However, this transition
brings many challenges, which can make it a difficult period for some children. Negative
experiences at the start of school can adversely affect children’s wellbeing and are likely to
contribute to less positive trajectories in academic and social skills. Given the importance of
children’s success at the start of school it is surprising that there are no simple yet reliable
instruments for evaluating children’s adjustment, skills and experiences. To address this gap we
conducted a study to develop a simple instrument (which we’ve called the Starting School
Survey – SSS or Triple S questionnaire) that should help both to identify in need of in making
the transition to school and to evaluate the effectiveness of preschool interventions.
Professors Claire Hughes, Susan Golombok and John Rust and Dr Irenee Daly) would like to
thank: (i) the teachers at all of the schools in the Wirral who kindly gave their time to take part
in the various stages of the study; (ii) the Wirral local authority for their support and (iii) staff at
Kings Hedges School in Cambridge, for their help in the validation phase of this study.
CONTENTS.
Background……………………………………………………………………………………………………….page 3
Methods for each stage of the study ……………………………………………………..……………page 5
Results:
I: Teachers Views on ‘School Readiness’……………………………………..………………………page 6
II: Scoring, Reliability and Validity of the Triple S…………………………….………………..page 8
III: Do children who struggle starting school show global or specific problems?...page 10
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IV: Is the Triple S sensitive to effects of gender and income status? ……………...…….page 11
V: Using a ‘traffic light’ system to identify children with SEN………………………...…....page 12
VI: Using the traffic light system to investigate effects of social support……………...page 12
VII: Do younger siblings get enough support?..........................................................................page 14
VIII: Item level results for:
Family support……………………………………………………..……………….…………….page 15
Social & Emotional competence……………………………..……………….…….………page 16
Daily Living Skills……………………………..………………………………..….…….……….page 17
Self Regulation…..……………………………..………………………………..….…….……….page 18
Language & Cognition……………………………………………………………………….....page 19
Discussion: Possible Future Directions……………………………………………………………….page 21
Summary: Key ‘take-home’ messages from the study…………………………………………….page 23
Appendix A: Histograms of Subscale Scores on the Triple S…………………………………..page 24
Appendix B: Glossary of Statistical Terms……………………………………………………………page 27
BACKGROUND: SCHOOL READINESS: WHAT EXACTLY IS IT?
Parents often define school readiness in terms of children’s cognitive skills, especially in
relation to literacy and numeracy. In contrast, teachers are more likely to define school
readiness in terms of children’s behaviour and socio-emotional development. In particular,
from a teacher’s perspective, positive relationships with peers provide an index of school
success that is just as important as measures of cognitive ability or achievement. In addition,
much of the debate surrounding the term ‘school readiness’ reflects the fact that it is often
constructed as a static attribute of the child that is devoid of context (Kiernan et al 2008). The
term ‘school readiness’ also causes difficulty when it is seen as value-laden – implying, for
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example, that schools should not have to take children who are not ‘ready’. At an early stage in
the current study we met a few head teachers who expressed quite powerful objections to the
use of this term. In response, we changed the title of our questionnaire from ‘Ready Steady Go’
to the ‘Starting School Survey’. Thus the questionnaire could also be called the Triple-S, a term
chosen to echo the successful Triple P positive parenting programme (Sanders et al 2003).
Despite ongoing debate as to the definition of school readiness, there is a growing
understanding that it is a multi-dimensional concept. Piotrkowski (2004) considers school
readiness to be the joint responsibility of families, schools and communities to provide an
environment that promotes a child’s learning. Reflecting this broader consideration of
readiness, many of the concerns that emerged in our focus group meetings with teachers and
head teachers centred on the children’s family lives, rather than on their performance at school.
Again this resonates the 2011 report by the American committee on early childhood, adoption
and dependent care and council on school health, which stated that “an individual child’s school
readiness is determined in large measure by the environment in which he or she lives and
grows” (High 2011, pg 1009)
The study described in this report was commissioned by Frank Field, as part of a larger focus on
the Foundations Years. Field’s review on Poverty and Life Chances (December, 2010)
recommended a fundamentally different approach to measuring and preventing poverty, going
beyond a narrow focus on incomes and recognising the importance of parenting and family
support, health and education in framing life chances. Graham Allen’s (2012) report pointed out
that using the best evidence available in order to get interventions right not only makes moral
and financial sense but is also key to breaking the intergenerational transmission of dysfunction
and disadvantage.
Our study was also informed by existing research on children making the transition to school.
For example, in a review that pooled data from 60 different longitudinal studies, La Paro and
Pianta (2000) showed that while scores for cognitive ability and academic achievement in
young children are reasonably stable, with preschool scores predicting about 25% of the
variation in scores a few years later, assessments of early social development and behaviour
appear less reliable (preschool scores predict just 10% of later variance). In part, this is because
young children’s behaviour often varies depending on their levels of fatigue, boredom or
hunger. However, the lack of clear stability in young children’s social behaviours also reflects
the wide variety of factors (both within schools and at home) that contribute to individual
differences in children’s behaviour and so also highlights the need for a very broad definition of
school readiness.
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The Foundation Years provide a vital grounding for future success in work and life. Too often –
and especially for children from poorer families – disadvantage early in life sets children on a
path that leads to educational failure and frustrated aspirations. By the time children start
school there are already wide variations in ability between children from different backgrounds
– with poorer children doing worse across a wide range of outcomes. In response, the current
coalition government aims to focus on the foundations years. In their report ‘Opening Doors,
Breaking Barriers – A Strategy for Social Mobility’ they say that “children at the age of five living
in poverty are the equivalent of around eight months behind their peers in terms of cognitive
development.” As will be outlined later in this report, our findings confirm this lag indicating
a difference in language and cognitive skills between children who are eligible for Free
School Meals (FSM) and their non-FSM peers that is equivalent to an age gap of about 12months.
The Opening Doors report also highlights the central role played by parents and families and the
need to involve communities and the voluntary and private sectors to an even greater degree, in
delivering early year services. Our goal in the current project was to assist in these community
ventures by developing an instrument – a brief and simple but reliable questionnaire – that
could be used both as a screen to accelerate the identification of children in need of extra
support, and as a means of assessing the benefits of preschool interventions. The results from
this main phase of the study are described in the next section of this report.
METHODS
METHODS I: GETTING TEACHERS’ FEEDBACK ON AN 80-ITEM PILOT QUESTIONNAIRE
In January 2012, we invited Foundation stage teachers from 18 schools in the Birkenhead areas
to rate each of a ‘long list’ of 80 questions as either ‘useful’ or ‘not useful’ in rating a child’s school
readiness. This list included 20 questions in each of the following categories: Language and
Cognition, Daily Living Skills, Social and Emotional Development and Self Regulation. We had a
very good response from teachers, which enabled us to filter out a good number of questions
before seeking further, more detailed, feedback from teachers via focus group discussions. These
were conducted separately with reception class and head teachers and included a broader
discussion of the concept of ‘school readiness’.
Eleven out of the 18 schools sent representatives to these focus groups: 15 reception class
teachers and 9 head teachers. The focus groups gave teachers the opportunities to tell us about
their years of experience in teaching, how it was changing and the main issues currently facing
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them. Their input helped decide which questions to include in the pilot questionnaire. For
example, the teachers felt it necessary to take children’s home environment into account and so
we constructed a fifth scale: Family Support.
METHODS II: PILOT STUDY
In February 2012 we contacted 75 schools from the Wirral (excluding schools in Birkenhead, as these
had been approached already for the first phase of the study). Of these 75 schools, 28 agreed to take
part, and completed a pilot version of the SSS (which had 15 items in each of 5 scales) for 98 boys and
87 girls. Of this pilot sample of 185 children, 97% were White British, 30% were eligible for Free
Schools Meals and 9% had statements of Special Educational Needs (SEN).
Methods III: Validation Study – May to July, 2012.
Having demonstrated the psychometric validity of the scales in the SSS, our next goal was to assess the
agreement between questionnaire ratings and standardized psychometric assessments of children’s
vocabulary and early maths skills. This phase of the study was conducted in a Cambridge School,
selected as being in a Sure Start ward. In total this sample included 30 boys and 29 girls (of whom 68%
were White British, 34% spoke English as a second language, 24% were eligible for Free School Meals
and 2% had a statement of Special Educational Needs).
METHODS IV: STANDARDISATION PHASE: SEPT-DECEMBER 2012.
In July 2012 we approached 97 schools in the Wirral to ask them to take part in the final
standardization phase of the study, which began in earnest in October 2012, to allow the new
intake in Reception a few weeks to settle in. We asked schools to provide details of any reception
class teachers within the school who were willing to take part. To ease the burden, in order to
maximise participation, we told teachers that, if they were unable to complete the Triple S
questionnaire for all of the children in their class, we would be happy to receive responses for a
randomly selected half of the children in the class (picked by choosing every other child in the
register).
We sent teachers from the 46 schools that agreed to participate a questionnaire pack that also
included opt-out forms for parents. These packs were completed by teachers of 51 reception
classes across 36 different schools, giving a final sample of 831 children: 419 girls and 412 boys
(96% White British, 24% eligible for Free School Meals and 53% with older siblings).
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RESULTS I: WHAT ARE THE CONCERNS OF TEACHERS IN THE WIRRAL REGARDING CHILDREN’S READINESS
FOR SCHOOL?
From its inception, we were keenly aware that the project’s success was reliant on getting the
thoughts and opinions of the experts on the ground. With that in mind, in January 2012 (right at
the start of the grant) we conducted separate focus groups with reception class teachers and
head teachers from Birkenhead schools. As expected from past studies, teachers from the
Wirral who participated in our focus group placed a strong emphasis on social success. For
example, when asked what ‘being school ready’ meant, teachers typically responded as
illustrated below:
“For me it is to sit and listen, that they are hungry to learn, good manners and social skills”
“For me it means being ready to accept challenges… to be able to be separated from Mom… and to
get on with other children”
As already mentioned, teachers were also keen to stress the role of the wider family and
community responsibility in preparing a child for school. Teachers made specific reference to
the barriers that they felt were increasingly hindering children from settling into school. One
specific theme to emerge was the increased influence of digital media on young children.
Specifically, teachers felt that increasingly DVDs were replacing bedtime stories; large screen
TVs, iPads and computers replaced more traditional skills-based activities such as painting,
drawing and craft making and imaginative play. Thus the teachers expressed concern that
children were coming to school with less experience of sharing toys, turn taking, manual
dexterity, hand-eye coordination, as well as reduced concentration. As one teacher said:
“ They spend so much time playing computer games. They are solitary. They don’t know how to
share”.
Teachers in Birkenhead also expressed concern that children whose own parents had a negative
school experience were additionally disadvantaged as these parents did not see the value and
importance of education and so, were less likely to engage in supporting their child’s success at
school. The role of teachers as educators as opposed to proxy-parents was a particular bone of
contention. One teacher said, rather bleakly: “Education is not valued – we are mere child
minders”.
Teachers were also frustrated that children increasingly started school without basic daily
living skills. For example, teachers reported that every year there were a few children who
were coming to school not fully toilet trained, still using a pacifier and still being transported in
6
a buggy. Teachers were concerned that pacifiers adversely affect children’s speech and language
and that travelling by pushchair affects children’s posture and motor skills.
Teachers expressed the view that children arrive at school unable to do basic self-help tasks
such as taking off their coats in the morning. Many teachers thought that preschool and
breakfast clubs were a good way of tackling these issues. Likewise some head teachers spoke
about visiting children’s home before they started school, so that they were already building a
relationship with the parents and child. In this way, parents who did not have a positive
educational experience could learn what was expected of them to prepare their child for school.
It is worth noting that in the literature there is debate about the types of interactions that are
most beneficial to children’s development in low-income families (Brody et al 1995; Lamborn et
al 1996). However, the extent to which parents engage in constructive activities that provide
their child with learning opportunities, both within and away from the home, have been found
to contribute to school readiness. In particular, providing children with shared reading
experience books and other print material contributes to children’s language and literacy
competence (e.g., Payne et al 1994, Raz and Bryant 1990).
RESULTS II: SCORING, RELIABILITY AND VALIDITY OF THE STARTING SCHOOL SURVEY
The Triple S includes five subscales (Family support, Social and Emotional Adjustment, Daily Living
Skills, Self-regulation and Language and Cognitive skills), each with 5-6 items (presented in mixed
order and rated on a simple 4-point scale (strongly agree, agree, disagree or strongly disagree). Items
in the pilot version of the Triple S were removed or retained depending on the extent to which
teachers’ responses to the item showed variation that cohered with variation on other items from the
same subscale. In order to ensure that a good proportion of items were positively worded, 10 items
were phrased in a way that required reverse coding before creating the subscale scores. For these
items ( 3, 5 ,6, 13, 16, 19, 20, 23, 26 and 29) the instructions for scoring are: strongly agree = 1,
somewhat agree = 2, somewhat disagree = 3 and strongly disagree = 4. For all other items (1, 2, 4, 7,
11, 14, 15, 17, 21, 24, and 25) the instructions for scoring are: strongly agree = 4, somewhat agree = 3,
somewhat disagree = 2 and strongly disagree = 1. The subscale scores are computed as follows:
mean social emotional skills score (av for 9, 20, 22, 27, 3rev and 13rev)
mean self regulation score (av for 1, 8, 5rev, 19rev, 23rev and 29rev)
mean language cognition score (av for 2, 15, 17, 21, 25, 30)
mean daily living skills score (av for 10, 12, 18, 28, 16 rev and 26 rev)
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mean family support score (av for 4 ,7, 11, 14, 24, and 6rev)
An Item Analysis was used to confirm the six items structure of each factor (see Table 1), and provided a
good model fit, as indicated by a non-significant chi-square, a comparative fit index (CFI) of 0.94, a TuckerLewis index (TLI) of 0.93 and a RMSEA of 0.04. All the factor loadings were significant – demonstrating
good internal reliability for each scale. Cronbach’s alpha values for each subscale ranged from .78 to .85,
indicating excellent internal reliability. In addition, all the R2-values were also significant, indicating that
responses to these items varied significantly across participants. Histograms showing the distributions of
subscale scores are given in the appendix and exhibit good variation for each subscale, with no hint of
floor or ceiling effects - thus each scale is developmentally appropriate for this age group. Finally, the
results from the validation phase of this study were also positive. In particular, Triple S scores for
language and cognition showed significant correlations with scores on standardized
psychometric tests of vocabulary (British Picture Vocabulary Test, r57 = .31, p < .01) and early
mathematical skills (Wechsler Intelligence Arithmetic Test, r57 = .35, p < .01).
Table 1: Results from Item Analysis for the Starting School Survey
ITEM
Social/Emotional Skills
Self Regulation
Family Support
Factor Loading
R2
Can play with lots of different children of his or her own age
.524
.274
Is respectful towards adults
.772
.597
Had trouble sitting still when required
.796
.633
Respond poorly to reprimands
.872
.760
Is usually happy to share with peers
.866
.751
Has temper tantrums
.819
.672
Is good at waiting patiently when required (e.g. turn taking)
.887
.787
Is easily distracted
.859
.738
Is good at calming down when asked to do so
.829
.687
Gets easily frustrated if a task is too difficult
.789
.623
Grabs others children’s belongings
.930
.864
Often interrupts conversations inappropriately
.833
.694
Often receives praise or encouragement from caregivers
.728
.530
Is always punctual
.723
.523
Rarely misses a day at school
.691
.478
Talks about fun, shared activities
.740
.547
Regularly reads at home (e.g. book-bag diary up to date)
.724
.525
8
Daily Living Skills
Language & Cognition
Often appears sleep or tired
.894
.799
Is able to work independently on most tasks
.837
.701
Is careful using scissors or other sharp objects
.810
.656
Often appears aimless when asked to choose an activity
.746
.556
Is able to use a fork or spoon correctly
.580
.336
Is fully independent in his or her use of the toilet
.410
.168
Often needs help looking after his or her belongings
.760
.578
Speaks clearly and is easily understood by adults
.558
.311
Enjoys identifying letters of the alphabet
.920
.846
Understands wh questions (what where when and why)
.754
.569
Can recognise his or her name in print
.881
.776
Uses one-to-one correspondence to count up to 5 objects
.718
.515
Enjoys songs and rhymes
.655
.430
RESULTS III: DO CHILDREN WHO STRUGGLE STARTING SCHOOL SHOW GLOBAL OR SPECIFIC PROBLEMS?
Prior to conducting any further statistical analyses (e.g., to assess whether mean scores on the
Triple S sub-scales, differed for boys and girls, or for children eligible for Free School Meals and
their non FSM peers), we examined the relations between individual subscale scores by
calculating correlation coefficients. Table 2 shows these correlations separately for children
eligible for FSM (above diagonal) and for non-FSM peers (below diagonal). Note that these two
groups of children showed the same mean age (4 years 9 months, SD = 4 months). Table 2 also
includes age, which was a significant correlate of scores on the language/cognition and the daily
living skills subscales (but not of scores for family support, self-regulation and social/emotional
skills were unrelated to age).
Table 2: Correlations between Triple S subscale scores for children eligible for FSM
(above diagonal, N = 193) and for non-FSM peers (below diagonal, N = 597)
Age
Family
Social /
Daily Living
Self
Language /
support
Emotional
Skills
Regulation
Cognition
Age
-
.08
.04
.13**
.03
.16**
Family support
.08
-
.37**
.11
.32**
.38**
Social / Emotional
.07
.52**
-
.23**
.71**
.44**
9
Daily Living Skills
.26**
.15**
.14*
-
.04
.24**
Self Regulation
.12
.45**
.71**
.09
-
.37**
.65**
.52**
.21**
.46**
-
Language/Cognition .19**
** correlation is significant at p < .01 level; * correlation is significant at p < .05 level.
As shown in Table 2, relations between child outcomes were similar for children who were
eligible for FSM and their non-FSM peers: in both groups, self-regulation and socio-emotional
skills were strongly inter-related, while daily living skills were relatively independent from the
other subscales. However, there was a group difference in the relationship between family
support and both social /emotional competence (z = 2.40) and language / cognitive skills (z =
4.53). Specifically, for children who were eligible for FSM (but not their non-FSM peers),
both academic and social skills appear to be relatively independent of family support.
RESULTS IV: DO TRIPLE S SCORES DIFFER BY GENDER OR SOCIO-ECONOMIC STATUS?
Difficulties in starting school are known to be more common in boys and in children from
disadvantaged backgrounds and so our next goal was to examine whether mean subscale scores
were sensitive to the expected effects of these factors. For reasons of simplicity and
confidentiality we used eligibility for Free School Meals (FSM) to index of children’s socioeconomic status. We conducted a single multivariate analysis because the child subscales were
significantly inter-related. This analysis showed that girls received higher scores than boys for
all scales, although this difference was very modest for family support, accounting for just 1% of
the variance, as compared with 3-5% of the variance on the child scales. Effects of gender and
income showed no interaction effects. That is, the contrast between girls and boys was similar
for all children, regardless of family background.
Children who were eligible for Free School Meals received lower ratings than their non-FSM
peers on all five subscales of the Triple S. This contrast was particularly striking for family
support and accounted for 15% of the variance in this scale, as compared with just 2-5% of the
variance in the child scales. To illustrate the magnitude of these effects, Figure 1 shows the
mean scores for Language and Cognition for children who were eligible for FSM (green bars)
and non-FSM peers (blue bars), with results presented separately for three age groups (4;0-4;7;
4;8-4;11 and 5;0-5;6). As Figure 1 shows, the oldest group of children eligible for FSM scored no
higher than the youngest group of non-FSM peers – indicating that by the age of 5, the average
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cognitive performance of children from low-income families is almost a year lower than
that of their peers.
RESULTS V: CAN THE TRIPLE S PROVIDE A ‘TRAFFIC LIGHT’ SYSTEM FOR IDENTIFYING CHILDREN WITH
SPECIAL EDUCATIONAL NEEDS?
Our sample of 843 children included 50 children identified by teachers as having special
educational needs (SEN). Our next goal was therefore to examine whether scores on the Triple
S could be used to predict the presence of SEN. To this end, we adopted a simple ‘traffic light’
approach; assigning ‘red’ status to children with scores that were at least 2 standard deviations
below the sample mean (i.e., the bottom 5%) and an ‘amber’ status to children with scores that
fell between 1 and 2 standard deviations below the sample mean (i.e., bottom 6-15%). Across all
four child scales (socio-emotional competence, daily living skills, self regulation and
language/cognition), 16% of the sample received at least one red rating and 55% received at
least one amber or red rating. Table 3 shows the range of scores for each zone:
Amber zone
Red Zone
Social / Emotional
2.1-2.5
0-2
Self Regulation
1.8-2.2
0-1.7
Daily Living Skills
2.1-2.6
0-2
Language / Cognition
2.1-2.5
0-2
Family support
2.1-2.6
0-2.1
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Support for the validity of our traffic light approach came from the finding that 84% of the study
children with identified SEN received at least one amber rating. To investigate this further we
conducted a binary logistic regression, using the presence / absence of an amber or red child
score to predict SEN status. This analysis showed a significant odds ratio of 3.99 (95%
confidence interval = 1.84 to 8.67). In other words, children who received at least one amber
rating on the Triple S were four times as likely as their peers to be identified as having
special educational needs.
RESULTS VI: ARE TRAFFIC LIGHT SCORES ON THE TRIPLE S SENSITIVE TO EFFECTS OF SOCIAL SUPPORT?
Our traffic light coding was sensitive to the effects of family support: for family support ratings
of green, amber or red, the percentage of children with >1 amber or red Triple S child subscale
score was 53%, 71% and 80%, respectively. In other words, 4 out of 5 children receiving low
family support (but just 1 out of 2 children receiving adequate or high family support)
were given an amber/red rating on at least one child scale.
We also used the traffic light coding to construct an index of children’s social environments
outside the home. Specifically, we pooled data from all children in each class (typically 15 to 30)
in order to calculate the percentage of children with low (amber or red) scores for family
support. We then conducted two separate hierarchical regression analyses with Language and
Cognition sub-scale scores as the dependent variable.
In the first analysis we entered gender, age-triad, FSM status, and family support scores at the
first step and the percentage of classmates with low family support scores at the second step.
Key results were:
1) Family support accounted for 37% of the variance.
2) Gender and age group each accounted for an additional 2-3% of the variance.
3) Considered alongside family support, gender, and age group, the percentage of
classmates with low family support accounted for an additional 1% of variance.
4) Despite being a robust individual predictor (see Figure 1), FSM status did not predict
any additional variance when considered alongside age, gender, family support and
social support for classmates.
In the second analysis we swapped the order of entry for our measures of family support and of
support for classmates, in order to assess the unique variance explained by family support.
Here, key results were:
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1) When entered at the first step, FSM status showed a significant predictive effect, similar
in magnitude to gender.
2) Together, gender, FSM-status, age group and support for classmates explained 12% of
the variance in Language and Cognition sub-scale scores.
3) Family support (entered at the second step) explained an impressive additional 30% of
the variance.
Together, these findings highlight that it is not poverty but family support that matters.
Note that although there is widespread concern about gender differences in ‘school readiness’,
effects of gender were modest in comparison with effects of family support. In addition, our
results suggest that children whose own home environments are unsupportive may
benefit from interacting with children who do have supportive families.
RESULTS VII: DO YOUNGER SIBLINGS HAVE PARTICULAR DIFFICULTY IN MAKING THE TRANSITION TO SCHOOL?
As well as indicating each child’s gender and FSM status, teachers also provided information on
children’s ethnic background (reflecting the local population, 96% of the sample was White
British, precluding any further analysis) and whether or not the child had any older siblings.
Providing young children with all the attention they need is undoubtedly more difficult for
parents who are caring for more than one child. To test whether the Triple S questionnaire was
sensitive to this challenge (and whether children with older siblings differ from firstborns in the
child scales), we repeated the multivariate analysis of variance conducted above, including birth
order as an additional variable. Since all the information was provided by teachers (rather than
parents) we only asked whether the child had one or more older sibling, as this question can be
answered by teachers more easily than more detailed question about siblings. Our analysis
showed that children with older siblings received marginally lower scores on two child scales
(Social and Emotional Competence and Language and Cognitive Skills) and significantly lower
scores for Family Support. Figures 1a and 1b show this effect graphically for children eligible for
Free School Meals and for their non-FSM peers (the effect appears stronger among the lowincome families, but this interaction is not statistically significant). From a policy-maker’s
perspective, the reduced family support observed among children with older siblings is an
important finding, as it suggests that assistance for low-income families is especially important
among families with more than one child.
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RESULTS VIII: INDIVIDUAL ITEMS IN THE TRIPLE S, PRESENTED BY SUBSCALE
Having established the general reliability, validity and utility of the Triple S scores, we then
adopted a more detailed approach, reporting the percentages of children for whom teachers
agreed (or strongly agreed) with individual items within each subscale.
Family Support.
Focus group discussions with teachers were particularly valuable in highlighting the importance
of assessing family support, as well as potential difficulties in constructing items that could
readily be completed by teachers. As shown in Table 2, the Triple S includes items relating to
attendance, punctuality and fatigue (which are easily rated by teachers) as well as items relating
to parent child interactions (praise, support for reading, engagement in positive activities) that
we think can be inferred from children’s talk within the classroom about life at home. Asterisks
indicate statistically significant contrasts between boys and girls, or with regard to FSM status
(and double asterisks indicate particularly strong effects).
The results shown in Table 3 suggest a mixed picture of family support: while ratings of school
attendance and punctuality were reassuringly high, 1 in 5 children were rated by teachers as
‘often sleepy at school’. Given that most classes include 30 children, this figure suggests that
teachers regularly encounter child fatigue. The results in Table 3 also help explain why gender
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accounted for just 1% of the variance in overall family support: girls appeared more likely than
boys to receive praise at home, and to talk about fun activities at home but there were no
gender differences for the other three family support items. In contrast, children who were
eligible for free school meals received lower ratings than their non-FSM peers for all 5
family support items (explaining why FSM status accounted for 15% of the variance in family
support). This contrast was particularly striking for two key markers of family support: just
over 50% of children eligible for free school meals (as compared with 80-88% of non-FSM
peers) were reported to talk about fun at home or to read regularly at home. To investigate
whether these two markers predicted children’s social, behavioural and cognitive competencies
we examined the distribution of scores on each of the child scales of the Triple S by reading /
fun at home status, as well as by gender and FSM eligibility (see Tables 4-7).
Table 3: Family Support (% for whom teachers agree with item)
Gender
Eligible for FSM?
Boys
Girls
No
Yes
Gets praise at home
90
95**
96
83**
Rarely misses school
91
91
95
81**
Is often sleepy at school
21
18
83
73**
Is punctual
87
89
93
73**
Talks about fun at home
68
79**
80
54**
Regularly reads at home
79
81
88
56**
** correlation is significant at p < .01 level;
Social and Emotional Competence.
As shown in Table 4, ratings for all 5 items on the social and emotional competence subscale
were higher for girls than for boys but showed few differences between children who were
eligible for free school meals and their non-FSM peers, with temper tantrums being the only
item to show a significant difference. Fun at home and reading at home were both significant
predictors of children’s social and emotional competence and showed contrasts that were
comparable in strength to effects of gender.
15
Table 4: Social and Emotional Adjustment (% for whom teachers agree with item)
Gender
Eligible for
Talks about
Regularly reads at
Free School
fun at home?
home?
Meals?
Boys
Girls
No
Yes
Yes
No
Yes
No
92
96*
95
92
96
89**
96
89**
Shares with peers
92
80**
87
82
90
75**
88
78**
Plays with lots of
77
85**
82
77
88
38**
82
73*
35
25**
28
32
26
40**
25
46**
22
16*
17
25*
14
31**
16
33**
Is respectful towards
adults
different children
Interrupts
conversations
Has temper tantrums
** correlation is significant at p < .01 level; * correlation is significant at p < .05 level.
Specifically, children who talked about fun activities at home were more than twice as likely as
their peers to be rated by teachers as being able to play with lots of other children (odds ratio =
2.71; 95% CI = 2.07 to 3.55); this effect was stronger than the effect of gender and FSM status
did not predict peer play. Conversely, while neither gender nor FSM status predicted temper
tantrums, children who did NOT talk about fun activities at home were significantly more likely
than their peers to have temper tantrums (odds ratio = 1.49; 95% CI = 1.16 to 1.91).
Daily Living Skills.
During our focus group discussions, teachers also highlighted the importance of assessing
children’s daily living skills. Table 5 presents the results for each of the items on this subscale.
Here, contrasts related to income (i.e., FSM status) were significant for three items (ability to
use fork and spoon, care with sharp objects and ability to work independently), but nonsignificant for the other two items (toilet training and ability to look after own belongings).
Girls were rated as showing significantly better daily living skills than boys on all items except
toilet training. In particular, boys were almost twice as likely as girls to be rated as needing help
16
in looking after belongings - a finding that will ring true for any parent or teacher who has had
occasion to inspect a school lost-property box! Fun at home and reading at home were, once
again, each at least as predictive as gender in predicting children’s daily living skills. Indeed, for
one key item (ability to work independently), fun at home and reading at home were each
stronger predictors than gender.
Table 5: Daily Living Skills (% for whom teachers agree with item)
Gender
Eligible for
Talks about fun
Regularly reads
Free School
at home?
at home?
Meals?
Boys
Girls
No
Yes
Yes
No
Yes
No
Is toilet trained
97
95
96
94
97
92**
96
92*
Can use a fork and
84
93**
91
84*
94
76**
91
78**
81
94**
89
82*
92
73**
90
76**
63
83**
76
67*
83
46**
79
47**
38
21**
28
33
23
47**
25
48**
spoon
Is careful with
sharp objects
Can work
independently
Needs help
looking after
belongings
** correlation is significant at p < .01 level; * correlation is significant at p < .05 level.
Self regulation.
Although teachers did not often mention self-regulatory skills during the focus groups, there is
good evidence (both from our own research and from research conducted in the USA) that early
self-regulatory skills are important predictors of children’s later academic and social success.
Table 6 shows the items in this scale and indicates that girls outperformed boys on all items. In
particular, boys were approximately twice as likely as girls to receive ratings high ratings for
distractibility, restlessness and difficulties in frustration control. Note, however, that once again
fun at home was as effective as gender in predicting teacher ratings of children’s self-regulatory
17
skills: in addition to the near halving in regulatory problems of distractibility, restlessness and
poor frustration control associated with boys, children who talked about fun activities at home
were also only half as likely as their peers to show aimless behaviour at school. Note also that
with regards to self-regulatory skills, the effects of reading at home were similar, but smaller in
magnitude.
Table 6: Self regulation (% for whom teachers agree with item)
Gender
Eligible for
Talks about fun
Regularly reads
Free School
at home?
at home?
Meals?
Boys
Girls
No
Yes
Yes
No
Yes
No
81
89**
86
83
89
75**
88
72**
Can wait patiently
67
83**
70
76
79
63**
79
63**
Gets easily distracted
59
32**
42
57**
38
68**
40
68**
Has trouble sitting still
48
25**
33
47
29
57**
30
62**
Gets easily frustrated
36
19**
25
66*
22
42**
25
41**
Appears aimless
27
20*
22
26
18
38**
27
20*
Is good at calming
down
** correlation is significant at p < .01 level; * correlation is significant at p < .05 level.
Language and Cognitive Skills.
Last, but by no means least, the Triple S includes a subscale that indexes children’s cognitive
skills, from simple items such as enjoyment of songs and rhymes, to more complex items such as
enjoyment of alphabet games and understanding of ‘wh’ questions (i.e., what / where / when /
why?). Once again, girls outperformed boys on all of the items in this scale, which also appeared
sensitive to effects of family income. And, as before, fun at home and reading at home were as
strong as gender in predicting each of these cognitive items. Interestingly, literacy skills were
as strongly predicted by fun at home as by reading at home. This is, we believe, a genuinely
valuable finding, which may help to engage parents in supporting their children’s academic
progress. That is, parents who do not themselves enjoy reading can be encouraged to foster
18
their child’s learning simply by taking the time to have fun with them – indeed, this may prove
to be a virtuous circle in that by providing the foundations for positive interactions between
parents and children, fun at home may well increase the frequency with which parents support
their children’s reading.
Table 7: Cognitive Skills (% for whom teachers agree with item)
Gender
Eligible for
Talks about fun
Regularly reads
Free School
at home?
at home?
Meals?
Enjoys songs and
Boys
Girls
No
Yes
Yes
No
Yes
No
90
99**
95
93
98
85**
96
89**
87
96**
93
83**
95
80**
95
75**
83
92**
90
80**
92
74**
89
78**
74
87**
85
71**
90
55**
86
58**
76
85**
85
68**
89
58**
84
63**
rhymes
Can recognise her
/his name in print
Can use 1 to 1
counting for 5
objects
Enjoys alphabet
games
Understands ‘wh’
questions
** correlation is significant at p < .01 level; * correlation is significant at p < .05 level.
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DISCUSSION: POSSIBLE FUTURE DIRECTIONS.
We hope the findings summarized in this report demonstrate that the Triple S is promising both
as a screening instrument and as a tool for exploring variation in children’s success in making
the transition to school. Based on this success, the University of Cambridge has provided
financial support for a PhD student (Nik Darshane) who will conduct a more detailed study with
an ‘at-risk’ sample who have been participating in an MRC-funded study conducted by a team of
researchers at the University of Liverpool (led Dr Helen Sharp and Professor Jonathan Hill). The
majority of children in this MRC study will start school in September 2013, and the rich data
that has already been gathered in this study (at multiple time points from birth) will enable
Darshane to examine a variety of early family measures as predictors of children’s success in the
transition to primary school. However, several other important questions arise from this
research and can only be addressed with further funding (from the Westminster Foundation or
other charitable organization). For example:
1) Is the Triple S useful for measuring developmental improvements across the Foundation
Years?
The distribution of Triple S scores suggests that this questionnaire should be sensitive to
variation among younger children and so could be useful in tracking progress across the
nursery year. The longitudinal design needed to address this question would also be useful for
exploring the developmental links between subscales. In particular, assessing whether early
success on one subscale predicts improvements in related scales (or end-of-year measures of
academic performance) is important in order to develop effective preschool interventions to
maximise children's success as they begin school.
2) Is the Triple S useful for measuring stable individual differences between children?
Assessing whether Triple S ratings provide an index of stable individual differences would be a
valuable test of the questionnaire's utility in identifying children who need extra support as
early as pre-school. Our goal in the current study was to develop a brief and teacher-friendly
instrument that has real potential as a tool for accelerating support to children in need. Here,
we were particularly impressed by the finding that children who received at least one amber
rating on the Triple S were four times as likely as their peers to be identified as having special
educational needs. However, more work is needed to test whether individual differences in
children’s scores on this questionnaire are stable – across time and across informants.
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3) How does school readiness in the Wirral compare with other regions of the UK?
Reflecting the local population, this Wirral sample was ethnically quite homogeneous. Before
the Triple S can be used nationally it is important to establish whether children from ethnic
minorities show a different profile of performance on this questionnaire. For example, is the
relationship between income and family support similar in strength for children from different
ethnic groups, or do low income ethnic minority families provide greater support for their
children’s educational success? Likewise, the FSM eligibility rate of 25% in this sample matches
that for the Wirral as a whole, but is distinctly higher than the national average of 15% - raising
questions about whether the profile of low family support associated with FSM status in this
study also applies to other regions in the UK.
4) Can supported play interventions compensate for low family support?
One of the most intriguing findings from this study concerns the apparent widespread benefits
for children of having fun at home. Further work is needed to establish whether the results
obtained in this study are a genuine reflection of variation in playful interactions at home. This
is because the item in the questionnaire is worded ‘Does this child talk about fun at home’ – such
that it could be that the predictive power comes from children’s willingness and ability to talk,
rather than about their actual experiences at home. However, if we assume that this item does
actually index family support (rather than children’s conversational skills), another important
question to address is ‘what can be done to help children who receive little support at home’?
On this point it is worth noting that the validation phase of this project was conducted in
tandem with other work being conducted by Prof. Hughes and her team, who are developing a
‘Think Art!’ intervention that involves 6 weeks of regular group sessions in which art-based
activities are led by researchers trained in methods of scaffolding the social and cognitive
development of young children. Results from this pilot work are very encouraging (with
improvements being seen in girls’ maths skills and boys’ language skills). If funding was
available, this team would be interested assessing the extent to which the adverse effects of low
family support could be reversed by this Think Art! intervention. Alternatively, we would be
willing to consider working in partnership with existing support programmes already in place
in the Wirral.
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SUMMARY OF TAKE HOME MESSAGES.

The Triple S is a 30 item teacher questionnaire, with 6 items in each of 5 scales: Family
support, Social and Emotional Adjustment, Daily Living Skills, Self-regulation and
Language and Cognitive skills

The Triple S scales are developmentally appropriate for Reception aged children and
also likely to be suitable for Nursery aged children).

Scores on the language and cognitive skills scale shows good agreement with formal
psychometric tests of vocabulary and early mathematical ability.

The scales are inter-related but distinct. The traffic light system should provide teachers
with a rough profile of each child’s strengths and difficulties.

Children who receive at least one amber score are 4 times as likely as their peers to
receive a statement of Special Educational Needs

Dividing the children into 3 age bands (with approximately 1 year between oldest and
youngest band) showed that effects of gender and family background (eligibility for free
school meals - FSM) were both similar in size to effects of age band.

Family support was the strongest predictor for each subscale – explaining about 30% of
unique variance in language and cognition scores, for example. When family support
was included as a predictor, FSM was no longer significant. So it is family support rather
than family income that matters for these early child outcomes.

Item level analysis showed that the two most significant markers of family support were
regular reading at home and the child talking about having fun at home. Interestingly,
fun at home was as strong a predictor of language / cognition scores as reading at home.

Children whose own home environments are unsupportive may benefit from interacting
with children who do have supportive families.
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APPENDIX A: HISTOGRAMS SHOWING DISTRIBUTIONS FOR EACH SUB-SCALE OF THE TRIPLE S.
23
24
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APPENDIX B. GLOSSARY OF STATISTICAL TERMS
In writing this report we have tried to keep statistical terms to a minimum, but the use of some
statistical language was necessary to ensure that the information presented was accurate.
Below we provide a lay person’s definition of some of the terms used. Feedback on whether
there were other words or phrases that could be clarified would be appreciated, as we plan to
send a version of this report to all the schools who participated in the study.
1. Correlation – This term refers to the extent to which two measures are related to each
other. Correlation coefficients range from +1 to -1. These extreme values are very rare
and indicate a perfect positive or negative correlation. A value of zero indicates no
relationship at all. In terms of effect size (see below), correlations of .1 to .2 indicate
small effects, correlations of .3 to .4 indicate moderate effects and correlations of .5 or
higher indicate large effects.
2.
Effect size: This is exactly what it says on the tin - a measure of the magnitude of an
effect. In correlation and regression analyses, this is often expressed as the percentage
of variance (see below) in one measure that can be explained by variance in another
measure. Another form of expressing an effect size is as an odds ratio (see below).
3. Odds ratio: This is the ratio of the odds of an event occurring in one group to the odds of
it occurring in another group. So in relation to poor child outcomes on the Triple S, an
odds ratio of 4 associated with low family support means that children with low levels of
family support are 4 times as likely as their peers to receive at least one poor score on
the Triple S child subscales.
4. P <.01: This is a mathematical way of expressing the likelihood of a result happening by
chance. P< .01 level suggests that there is less than a 1% probability of the result being a
chance finding; p <.05 indicates that less than a 5% probability of the result being a
chance finding.
5. Regression analyses are used to look at several correlations at the same time, in order
to explore the independence of associations. Logistic regressions are used for measures
that are scored as yes/no and hierarchical regression is a way of controlling for one set
of predictors before looking at the effects of another predictor.
26
6. Standard Deviation. This term is used to refer to the spread of values in a given
measure. It is calculated such that 70% of values fall within one standard deviation of
the mean (with 15% lying 1 SD above the mean and 15% lying 1 SD below the mean).
Likewise a value that is 2 SD above the mean will, by definition, fall in the top 5%.
7. Variance. This term refers to how much variation there is in a particular measure. The
histograms shown in Appendix A provide a visual indication of variance. From a
statistical perspective, variance is an index of variation that takes into account all the
possible values and their probabilities (and so is not the same as ‘range’ which simply
indicates the difference between minimum and maximum values).
27