Literature DB >> 28645979

The 2015 Middle Childhood Survey (MCS) of mental health and well-being at age 11 years in an Australian population cohort.

Kristin R Laurens1,2,3, Stacy Tzoumakis4, Kimberlie Dean1,2,5, Sally A Brinkman6,7, Miles Bore8, Rhoshel K Lenroot1,2, Maxwell Smith9, Allyson Holbrook9, Kim M Robinson9, Robert Stevens10, Felicity Harris1,2, Vaughan J Carr1,2,11, Melissa J Green1,2.   

Abstract

PURPOSE: The Middle Childhood Survey (MCS) was designed as a computerised self-report assessment of children's mental health and well-being at approximately 11 years of age, conducted with a population cohort of 87 026 children being studied longitudinally within the New South Wales (NSW) Child Development Study. PARTICIPANTS: School Principals provided written consent for teachers to administer the MCS in class to year 6 students at 829 NSW schools (35.0% of eligible schools). Parent or child opt-outs from participation were received for 4.3% of children, and MCS data obtained from 27 808 children (mean age 11.5 years, SD 0.5; 49.5% female), representing 85.9% of students at participating schools. FINDINGS TO DATE: Demographic characteristics of participating schools and children are representative of the NSW population. Children completed items measuring Social Integration, Prosocial Behaviour, Peer Relationship Problems, Supportive Relationships (at Home, School and in the Community), Empathy, Emotional Symptoms, Conduct Problems, Aggression, Attention, Inhibitory Control, Hyperactivity-Inattention, Total Difficulties (internalising and externalising psychopathology), Perceptual Sensitivity, Psychotic-Like Experiences, Personality, Self-esteem, Daytime Sleepiness and Connection to Nature. Distributions of responses on each item and construct demarcate competencies and vulnerabilities within the population: most children report mental health and well-being, but the population distribution spanned the full range of possible scores on every construct. FUTURE PLANS: Multiagency, intergenerational linkage of the MCS data with health, education, child protection, justice and early childhood development records took place late in 2016. Linked data were used to elucidate patterns of risk and protection across early and middle child development, and these data will provide a foundation for future record linkages in the cohort that will track mental and physical health, social and educational/occupational outcomes into adolescence and early adulthood. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  behaviour; child development; data linkage; epidemiology; personality; psychopathology; record linkage; social-emotional function

Mesh:

Year:  2017        PMID: 28645979      PMCID: PMC5726143          DOI: 10.1136/bmjopen-2017-016244

Source DB:  PubMed          Journal:  BMJ Open        ISSN: 2044-6055            Impact factor:   2.692


The Middle Childhood Survey (MCS) assessed psychosocial and behavioural constructs reflecting mental health and well-being by self-report in a large sample of 27 808 children aged approximately 11 years (31.4% of eligible children), which is representative of the New South Wales population. Constructs were assessed using items selected from measures with established reliability and validity for assessment of children aged 11 years, but item reduction and modifications made to item wording, response options and scale scoring limits direct comparison with published data on some measures. The depth of information obtained was constrained by the time available within schools for survey administration, lack of accompanying parent and/or teacher reports and sensitivities associated with assessing psychosocial and behavioural constructs in children by self-report. The MCS measured the full spectrum of personal competencies and vulnerabilities in the population, providing capacity to guide the development and implementation of universal mental health promotion programmes alongside targeted approaches for vulnerable children. The MCS is embedded within an intergenerational, multiagency record linkage study, the New South Wales Child Development Study, which permits MCS data to be interpreted in the context of longitudinal data that is subject to minimal selection and participation bias.

Introduction

Middle childhood (age 6–12 years) is a critical period in which to establish social, emotional-behavioural, cognitive and physical competencies that support successful transition to adolescence.1 2 Children are increasingly exposed to influences beyond the home, and encounter various new challenges, particularly at school. During this time, mental health problems emerge for some children, causing impairments in functioning and increasing risk for future adverse health, social and educational outcomes.3 4 Thus, middle childhood represents an important period for establishing strong psychosocial foundations to support future mental health and well-being. Here, we introduce the 2015 Middle Childhood Survey (MCS), designed as a self-report measure of children’s psychosocial experiences in middle childhood (at approximately 11 years of age) administered online during the final year of primary (elementary) school for a population cohort of children being studied longitudinally within the New South Wales Child Development Study5 (NSW-CDS; http://nsw-cds.com.au/). The NSW-CDS is a multigenerational record linkage study that combines administrative health, education, child protection and justice records for an Australian state-based population cohort of children (n=87 026) and their parents. The cohort was defined as those children who entered their first year of full-time schooling (Kindergarten) in NSW in 2009 at approximately 5 years of age and for whom class teachers completed the Australian Early Development Census6 (AEDC) on each child (99.7% coverage). The AEDC data on early childhood social, emotional-behavioural, cognitive, communication and physical development were linked with child and parent administrative records in a first record linkage conducted in 20135; a second record linkage that included MCS data and updated administrative records to the age of 12 years was undertaken in late 2016. Reflecting the primary interest of the NSW-CDS in identifying childhood predictors of later mental health and related outcomes,5 the MCS items focused on the assessment of social and emotional-behavioural competencies that are typically attained during middle childhood1 2 and which have been demonstrated as predictive of various adolescent and adulthood health and social outcomes.3 4 7 These competencies include establishing and maintaining positive social relationships, understanding and appreciating the perspectives of others, recognising and managing emotions and behaviours and the development of personality and self-esteem. Other aspects of childhood mental health and well-being that are associated with health, social and educational outcomes, such as psychotic-like experiences,7 8 daytime sleepiness9 and engagement with the natural environment10 were also included. Like the AEDC, the MCS was designed as a population measurement tool rather than a diagnostic instrument for the identification of children presenting needs that require specialist support services or therapeutic intervention.11Thus, the MCS measured both successful attainment of these competencies as well as vulnerabilities or immaturity of these skills relative to age peers. This paper describes the content and administration of the MCS, and presents the mental health and well-being profiles of children in the MCS sample.

Cohort description

Eligible sample

The target sample for the study included all year 6 students enrolled at government (public) and non-government (private) schools in the Australian state of New South Wales (NSW) during 2015 (88 572 children enrolled in 2371 schools), in order to capture the same cohort of children assessed within the AEDC in 2009. A two-stage recruitment procedure was used (figure 1) to ensure that students remained anonymous to researchers for future record linkage purposes: Principals (Head Teachers) provided active consent for their school to participate; subsequent child recruitment within participating schools was managed by school personnel using an opt-out consent procedure for parents and/or children.
Figure 1

Flow diagram illustrating derivation of the final sample of 829 schools, and 27 808 children, who participated in the Middle Childhood Survey 2015 (MCS). [NSW, New South Wales.]

Flow diagram illustrating derivation of the final sample of 829 schools, and 27 808 children, who participated in the Middle Childhood Survey 2015 (MCS). [NSW, New South Wales.]

Procedures

Pilot testing

Commencing in October 2012, school sector representatives and stakeholders representing various education and parent and communities groups (see Acknowledgements) were consulted regarding the method of MCS administration in schools. During 2014, the feasibility of administration procedures (and acceptability of the MCS items) was tested with year 6 students (n=645) enrolled at 11 schools spanning the government and non-government sectors, and metropolitan and rural regions of NSW. Minor adaptations to administration procedures and MCS items were made on the basis of feedback received from participating schools, and on psychometric analysis of the pilot data (including factor and item response theory analyses).

Data management

The MCS data collection was managed by a third party information technology (IT) contractor that delivered the online student survey and the automated email correspondence with schools on behalf of the researchers. The IT contractor was provided with all Principal/school email addresses by the school sector representatives, and received all NSW year 6 students’ identifying information (eg, name, date of birth), based on 2014 (year 5) enrolment records, directly from the NSW Board of Studies, Teaching and Educational Standards, under a confidential data usage agreement. Identifying information for these eligible students was prepopulated into an online administration portal that was accessible only to school teachers assisting with MCS administration. To account for new enrolments in 2015, teachers were able to update the personal identifiers to include new students. A unique access code was generated by the IT contractor for each child to ensure that the survey responses were associated with the correct personal identifiers for later linkage processes.

School recruitment

From March 2015, the school sector representatives and study stakeholders used their established avenues for communicating with school personnel and/or parents to seek their support and participation in the study. In April 2015, Principals of NSW schools with an enrolment of year 6 students were sent an electronic study information leaflet by email, inviting the school to participate in the study. Principals (or an authorised representative) provided written informed consent for their school to participate, or declined participation, using a unique web-link for each school. Where no responses were received from schools during a 4-month school recruitment period, telephone contact was made by researchers and supplemented by automated reminder emails. Principals of participating schools were able to nominate a preferred 2-week window during July–September 2015 to administer the MCS, and a dedicated coordinator (ie, teacher or support person) to supervise MCS administration at their school.

Child recruitment

Both printed and electronic copies of study information leaflets were sent to participating schools for distribution to parents/carers of year 6 students at least a fortnight prior to the scheduled MCS administration. Electronic copies of these leaflets were also available on the study website in English and the 10 most common languages spoken by families of children enrolled in NSW schools; an audio version in English was also available at this site. Parents/carers could opt-out their child from participation using online forms, or by written or verbal instruction to class teachers. Children could opt-out either online or by verbal instruction to class teachers. Teachers recorded online any written or verbal opt-outs received from parents or children prior to administration of the MCS. Opting out of the study was also possible after MCS administration; capacity to withdraw MCS data remained available until the closure of the survey portal to data collection on 16 October 2015. MCS data were then deidentified by the IT contractor for provision to the researchers, at which point removal of a specific child’s responses was no longer possible.

Survey administration

The MCS was administered within participating schools during class time over a 3-month period commencing July 2015. Classroom teachers supervised the survey administration according to instructions provided in an online administration guide. Schools determined the setting of survey administration depending on availability of computing resources, while maintaining confidentiality for participants. Children could complete the survey over multiple sessions, using the unique access code provided to the child by their teacher. Children with special needs could complete the survey with the assistance of their normal classroom support (eg, adult helper) and/or an audio-recording of the survey. Researchers monitored the administration of MCS in schools via an online portal (which held school-level information only), and arranged alternative administration times for any school that had not administered the survey within their nominated 2-week window.

Data provision

During the administration process, participating students’ personal identifiers were stored by the IT contractor separately from MCS responses. Only deidentified survey data (coded by unique identification number) was provided to the researchers in December 2015. A separate dataset containing only the minimum identifying information for the cohort of participating students (ie, without the survey response data) was provided to a third party linkage provider—the Centre for Health and Record Linkage (http://www.cherel.org.au/)—to be retained under a confidential data usage agreement that enables linkage of MCS data with administrative data collections in the NSW-CDS; at no time during the study execution were personal identifiers available to researchers.

Measures

The content of the MCS was established via consensus among a working group comprising NSW-CDS Scientific Committee members who are coauthors on this manuscript. Members represented expertise in child development, developmental psychopathology, education, psychology, psychiatry and population health. The group reviewed measures with established reliability and validity for assessment of children aged 11 years, and incorporated measures both of competencies and vulnerabilities in social and emotional-behavioural development. Each construct of interest was assessed by multiple items; in some instances, only a subset of the items from the original scales was included due to constraints on the number of items that could be administered to children during class time. In such cases, the subset of items demonstrated in previous studies as providing the most coherent but comprehensive assessment of the construct was selected. Minor wording changes were made to several MCS items to increase their acceptability to Australian children (modified items are indicated by * in table 1 and online supplementary table 1-X). Furthermore, to avoid children having to adapt their responses to the different response formats used in the original scales, a standardised response format was adopted for all items, modelled on the three-choice format of the Strengths and Difficulties Questionnaire (SDQ),12 13 namely: not true (scored 0); somewhat true (1) and certainly true (2). A standard approach of summing items on all scales (after reverse scoring of some items, as indicated in table 1 and online supplementary table 1-X) to compute total scale scores was also adopted.
Table 1

Summary of items measuring each mental health and well-being domain assessed within the Middle Childhood Survey (MCS) and, for each item, the number of children providing data (of the 27 808 who commenced the survey) and the distributions of the three response options

MCS domain (and source measure)ItemSampleNot TrueSomewhat TrueCertainly True
(n)%(n)%(n)%(n)
Social Integration (QSL) My school is a place where…
… I learn to get along with other people26 8593.0(806)26.8(7189)70.2(18 864)
… Other students accept me as I am26 8566.6(1769)32.6(8760)60.8(16 327)
… People trust me26 8564.1(1100)34.0(9136)61.9(16 620)
… I am popular with other students26 85617.0(4574)45.1(12 123)37.8(10 159)
… I know people think a lot of me26 85620.1(5393)50.5(13 566)29.4(7897)
… I get on well with the other students in my class26 8553.4(920)33.3(8933)63.3(17 002)
… People can depend on me26 8545.1(1380)35.5(9542)59.3(15 932)
… Other students are very friendly26 8544.8(1281)37.5(10 075)57.7(15 498)
Prosocial Behaviours (SDQ)I try to be nice to other people. I care about their feelings27 4941.3(359)22.6(6224)76.1(20 911)
I usually share with others (eg, CDs, games, food)27 4867.9(2180)45.9(12 609)46.2(12 697)
I am helpful if someone is hurt, upset or feeling ill27 4822.6(728)29.7(8174)67.6(18 580)
I am kind to younger children27 4782.1(583)15.2(4177)82.7(22 718)
I often volunteer to help others (parents, teachers, children)27 4746.0(1653)44.0(12 096)50.0(13 725)
Peer Relationship Problems (SDQ)I would rather be alone than with people of my age27 48471.6(19 667)20.6(5650)7.9(2167)
I have one good friend or more (R)27 4802.0(544)7.6(2077)90.5(24 859)
Other people my age generally like me (R)27 4806.4(1745)42.1(11 576)51.5(14 159)
Other children or young people pick on me or bully me27 47766.9(18 387)23.7(6517)9.4(2573)
I get along better with adults than with people my own age27 47452.8(14 518)36.7(10 075)10.5(2 881)
Supportive Home Relationships (HKS/MDI) In my home, there is a parent or another adult …
… who listens to me when I have something to say26 9244.4(1181)30.3(8147)65.4(17 596)
… who I can talk to about my problems26 9228.2(2212)24.3(6553)67.4(18 157)
… who wants me to do my best26 9281.6(435)12.0(3220)86.4(23 273)
… who believes that I will be a success26 9223.4(906)20.0(5382)76.6(20 634)
Supportive School Relationships (HKS/MDI) At my school, there is a teacher or another adult…
… who really cares about me26 9187.1(1920)34.4(9265)58.4(15 733)
… who listens to me when I have something to say26 9165.7(1528)31.5(8466)62.9(16 922)
… who believes that I will be a success26 9175.7(1536)32.8(8831)61.5(16 550)
… who tells me when I've done a good job26 9153.8(1017)23.0(6177)73.3(19 721)
Supportive Community Relationships (HKS/MDI) In my neighbourhood/community (NOT from your school or family), there is an adult…
… who really cares about me26 91019.0(5101)35.5(9540)45.6(12 269)
… who listens to me when I have something to say26 91020.5(5522)37.2(10 005)42.3(11 383)
… who believes that I will be a success26 90920.4(5477)35.9(9673)43.7(11 759)
… who tells me when I've done a good job26 90919.3(5186)30.9(8308)49.9(13 415)
Empathy (FTI)I want to help people who get treated badly27 1173.5(957)27.7(7500)68.8(18 660)
I often feel worried about people that are not as lucky as me, and feel sorry for them27 1135.3(1425)34.4(9337)60.3(16 351)
I sometimes try to understand my friends better by pretending I am them†27 11140.6(11 003)39.1(10 591)20.3(5517)
I think people can have different opinions about the same thing27 1082.1(567)21.8(5919)76.1(20 622)
Emotional Symptoms (SDQ)I get a lot of headaches, stomach-aches or sickness27 48956.6(15 552)33.0(9075)10.4(2862)
I worry a lot27 48440.4(11 097)41.1(11 304)18.5(5083)
I am often unhappy, depressed or tearful27 48072.8(20 017)21.2(5817)6.0(1646)
I am nervous in new situations. I easily lose confidence27 47936.9(10 128)44.4(12 191)18.8(5160)
I have many fears, I am easily scared27 47356.5(15 517)32.0(8803)11.5(3153)
Conduct Problems (SDQ)I get very angry and often lose my temper27 48562.1(17 079)26.7(7350)11.1(3056)
I usually do as I am told (R)27 4843.1(863)43.7(12 011)53.2(14 610)
I fight a lot. I can make other people do what I want27 48083.3(22 896)14.0(3846)2.7(738)
I am often accused of lying or cheating27 47862.6(17 207)26.5(7278)10.9(2993)
I take things that are not mine from home, school or elsewhere27 47488.3(24 267)9.6(2636)2.1(571)
Aggression (EATQ-R)If I get mad at someone, I might hit them*27 48465.6(18 020)25.4(6975)9.1(2489)
When I am angry, I throw or break things27 47279.8(21 916)14.6(4022)5.6(1534)
Attention (EATQ-R)I pay close attention when someone asks me to do something*27 1654.2(1133)46.3(12 588)49.5(13 444)
It is easy for me to really concentrate on homework problems27 14418.3(4969)47.4(12 854)34.3(9321)
When trying to study, I have difficulty tuning out background noise and concentrating (R)27 12026.3(7146)45.2(12 260)28.4(7714)
Inhibitory Control (EATQ-R)When I am excited, it’s hard for me to wait my turn to speak* (R)27 16225.7(6970)44.2(11 993)30.2(8199)
When someone tells me to stop doing something, it is easy for me to stop‡27 1579.4(2540)47.6(12 926)43.0(11 691)
I often say the first thing that comes to mind* (R)27 15524.3(6586)52.0(14 118)23.8(6451)
It’s hard for me not to open presents before I’m supposed to (R)27 14943.6(11 827)30.6(8302)25.9(7020)
When I am having a good time I find it hard to go home* (R)27 14414.6(3955)33.5(9086)52.0(14 103)
I often call out answers before the teacher calls my name* (R)27 13354.8(14 873)33.4(9059)11.8(3201)
The more I try to stop myself from doing something I shouldn’t, the more likely I am to do it (R)27 12751.4(13 938)36.8(9994)11.8(3195)
Hyperactivity/Inattention (SDQ)I am restless, I cannot stay still for long27 49032.8(9024)41.2(11 317)26.0(7149)
I am constantly fidgeting or squirming27 48152.7(14 478)34.0(9335)13.3(3668)
I am easily distracted, I find it difficult to concentrate27 47939.5(10 846)42.5(11 676)18.0(4957)
I think before I do things (R)27 4747.6(2087)52.7(14 466)39.8(10 921)
I finish the work I'm doing. My attention is good (R)27 4725.9(1610)48.2(13 232)46.0(12 630)
Perceptual Sensitivity (EATQ-R)I am very aware of noises27 15711.0(2988)40.8(11 071)48.2(13 098)
I notice even little changes taking place around me, like lights getting brighter in a room27 15314.2(3853)39.4(10 696)46.4(12 604)
I tend to notice little changes that other people do not notice27 14013.0(3533)49.2(13 360)37.8(10 247)
I can tell if another person is angry by their expression27 1382.9(774)28.2(7644)69.0(18 720)
Psychotic-Like Experiences (PLEQ-C) Have you ever…
… believed that other people could read your thoughts?*27 00054.2(14 642)33.5(9048)12.3(3310)
… believed that you were being sent special messages through the television?26 99369.5(18 773)22.0(5947)8.4(2273)
… thought that you were being followed or spied on?26 99243.0(11 601)34.2(9229)22.8(6162)
… heard voices that other people could not hear?26 99042.9(11 567)30.5(8227)26.7(7196)
… felt that you were under the control of some special power?26 99070.4(19 012)19.3(5221)10.2(2757)
… known what another person was thinking even though that person wasn't speaking?26 98342.0(11 345)38.3(10 330)19.7(5308)
… felt as though your body had been changed in some way that you could not understand?26 97655.2(14 879)30.7(8290)14.1(3807)
… felt that you had special powers that other people don't have?*26 97662.0(16 732)23.4(6314)14.6(3930)
… seen something or someone that other people could not see?26 97648.0(12 949)27.8(7489)24.2(6538)
Agreeableness (BFQ-C)I am friendly to others in my school*27 7350.7(185)22.5(6238)76.8(21 312)
I forgive others when they do something wrong*27 7343.2(898)38.3(10 619)58.5(16 217)
I am kind even to people I don’t like*27 42210.4(2853)49.6(13 615)39.9(10 954)
I think other people are good and honest27 4164.9(1354)55.7(15 269)39.4(10 793)
I like to let other people use my things*27 4157.7(2121)49.7(13 614)42.6(11 680)
Conscientiousness (BFQ-C)I check my work to make sure it is right*27 7347.6(2118)48.3(13 395)44.1(12 221)
I like to be on time*27 7334.7(1301)29.0(8051)66.3(18 381)
I keep my room neat and tidy*27 42716.8(4596)49.1(13 476)34.1(9355)
I like to keep my things in order*27 42611.5(3153)40.7(11 151)47.8(13 122)
I am messy* (R)27 42149.6(13 591)39.0(10 687)11.5(3143)
Neuroticism (BFQ-C)I get nervous about many things*27 73424.0(6649)53.7(14 895)22.3(6190)
I have bad moods*27 73424.0(6662)51.1(14 177)24.9(6895)
I get angry easily*27 73451.6(14 314)34.1(9446)14.3(3974)
I get upset easily*27 73354.6(15 134)34.2(9473)11.3(3126)
I cry a lot*27 73375.4(20 901)19.7(5469)4.9(1363)
Extraversion (BFQ-C)I am happy and active*27 7351.0(289)25.2(6999)73.7(20 447)
I like to be with other people*27 7342.0(556)20.8(5772)77.2(21 406)
I like to talk with others27 4281.6(443)19.5(5358)78.9(21 627)
I make friends easily*27 4198.5(2325)38.0(10 426)53.5(14 668)
I am a shy person* (R)27 41947.1(12 928)39.0(10 696)13.8(3795)
Intellect/Openness (BFQ-C)I easily learn my school work*27 7354.2(1171)51.1(14 177)44.7(12 387)
I know many things27 7353.3(919)46.2(12 812)50.5(14 004)
I know the answers to questions my teacher asks*27 7343.3(907)71.4(19 808)25.3(7019)
I understand my school work*27 7332.7(762)45.4(12 588)51.9(14 383)
I like learning new things27 4153.2(865)26.3(7223)70.5(19 327)
Self-esteem (MSLSS)There are lots of things I can do well27 1742.3(629)32.1(8726)65.6(17 819)
I like myself27 1716.0(1622)28.5(7745)65.5(17 804)
I am a nice person27 1691.4(369)29.6(8033)69.1(18 767)
Daytime Sleepiness (PDSS)I fall asleep or get drowsy during class*27 10659.5(16 120)30.4(8248)10.1(2738)
I am tired and grumpy during the day*27 10565.8(17 833)28.6(7754)5.6(1518)
I am usually alert most of the day* (R)27 1049.1(2475)45.3(12 282)45.6(12 347)
Connection to Nature (CTNI/CTNS)When I feel sad, I like to go outside and enjoy nature27 10319.8(5361)41.9(11 345)38.4(10 397)
Being in nature makes me feel peaceful*27 10210.1(2729)38.1(10 335)51.8(14 038)
I feel strongly connected with nature*27 10121.5(5825)45.0(12 207)33.5(9069)

R denotes an item that was subsequently reversed in the computation of domain scores.

*Denotes item with minor wording change from original scale.

†Denotes item removed from the modified Empathy scale (three items).

‡Denotes item reassigned from the modified Inhibitory Control (items) to the modified Attention scale (items).

QSL, Quality of School Life; BFQ-C, short form of the Big Five Questionnaire for Children; CTNI/CTNS, Connection to Nature Index/Connectedness to Nature Scale; EATQ-R, Early Adolescent Temperament Questionnaire—Revised; FTI, Feeling and Thinking Index; HKS/MDI, Healthy Kids Scale/Middle Years Development Index; MSLSS, Multidimensional Students’ Life Satisfaction Scale; PDSS, Pediatric Daytime Sleepiness Scale; PLEQ-C, Psychotic-Like Experiences Questionnaire for Children; SDQ, Strengths and Difficulties Questionnaire.

Summary of items measuring each mental health and well-being domain assessed within the Middle Childhood Survey (MCS) and, for each item, the number of children providing data (of the 27 808 who commenced the survey) and the distributions of the three response options R denotes an item that was subsequently reversed in the computation of domain scores. *Denotes item with minor wording change from original scale. †Denotes item removed from the modified Empathy scale (three items). ‡Denotes item reassigned from the modified Inhibitory Control (items) to the modified Attention scale (items). QSL, Quality of School Life; BFQ-C, short form of the Big Five Questionnaire for Children; CTNI/CTNS, Connection to Nature Index/Connectedness to Nature Scale; EATQ-R, Early Adolescent Temperament Questionnaire—Revised; FTI, Feeling and Thinking Index; HKS/MDI, Healthy Kids Scale/Middle Years Development Index; MSLSS, Multidimensional Students’ Life Satisfaction Scale; PDSS, Pediatric Daytime Sleepiness Scale; PLEQ-C, Psychotic-Like Experiences Questionnaire for Children; SDQ, Strengths and Difficulties Questionnaire. In total, the MCS comprised 116 items with specific forced-choice response options. The first eight items assessed demographic information: age, sex, month of birth, residential postcode, number of people living in the child’s usual residence, main language spoken at home and whether the child used the audio-recording or received assistance from an adult to complete the survey (table 2). The remaining 108 items assessed a range of child mental health and well-being constructs, including: Social Integration, Prosocial Behaviour, Peer Relationship Problems, Supportive Relationships (at home, school and in the community), Empathy, Emotional Symptoms, Conduct Problems, Aggression, Attention, Inhibitory Control, Hyperactivity-Inattention, Total Difficulties (internalising and externalising psychopathology), Perceptual Sensitivity, Psychotic-Like Experiences, Personality, Self-esteem, Daytime Sleepiness and Connection to Nature (engagement with natural environment). The source measure for each of these constructs is described below; for brevity, these are presented according to their questionnaire of derivation:
Table 2

Summary of selected demographic characteristics self-reported by the 27 808 children completing the Middle Childhood Survey (MCS)

Demographic itemSamplePrevalence
(n)%(n)
Age of child27 808
  10 years or younger0.5(135)
  11 years54.7(15 198)
  12 years44.1(12 259)
  13 years or older0.8(216)
Sex of child27 808
  Female49.5(13 754)
  Male50.5(14 054)
Number of people living in child’s home (main residence)27 803
  3 or less15.1(4187)
  435.8(9948)
  527.8(7718)
  6 or more21.4(5950)
Main language spoken at home27 803
  English87.3(24 272)
  Arabic1.9(525)
  Vietnamese1.3(365)
  Cantonese1.1(296)
  Mandarin1.0(278)
  Hindi0.8(211)
  Tagalog0.5(141)
  Spanish0.4(99)
  Greek0.2(49)
  Italian0.1(35)
  Other5.5(1532)
Child made use of MCS audio recording27 8032.5(695)
Child received assistance from an adult to complete survey27 8025.0(1398)
Social Integration at school was assessed using the full, unmodified 8-item Social Integration subscale of the Quality of School Life questionnaire.14 Response options were reduced from the original 4-choice to the standard 3-choice response format, and the total sum of items derived in place of an average of items used in previous research. Prosocial Behaviour and Psychopathology were assessed using the 25-item SDQ,12 13 which comprises four psychopathology subscales (Emotional Symptoms, Peer Relationship Problems, Conduct Problems, Hyperactivity-Inattention), and a Prosocial Behaviour subscale. Items and response options were unmodified from the original scale, and the standard scoring metric applied: five items assessed each of the subscales, and Total Difficulties was computed by summing the 20 items from the four psychopathology subscales. Supportive Relationships at , at were assessed using 12 items (four per subscale) selected from the Healthy Kids Survey.15 These items included those (three per subscale) used in the Middle Years Development Index 16 (MDI) plus an additional item for each subscale. Item wordings were unmodified from the MDI, but the 4-choice rating scale and averaged total score were replaced. Sixteen items from four subscales in the Early Adolescent Temperament Questionnaire—Revised (EATQ-R) 17 assessed Attention (four items; selected from seven), Inhibitory Control (seven items; selected from 11), Perceptual Sensitivity (four items; selected from six) and Aggression (two items; selected from 11). The first three of these subscales comprise part of a measure of Effortful Control within the EATQ-R. Minor modifications to the wording of several items were made, and the original 5-point rating response scale and averaged total score replaced. Empathy was assessed using four items from the 12-item Feeling and Thinking Instrument 18; item wording was unmodified, but the original 5-point rating response scale replaced. Psychotic-like experiences were assessed with nine items from the Psychotic-Like Experiences Questionnaire for Children 8 19 (two with minor rewording from the original), with the original 3-choice response format retained. Dimensions of personality (Extraversion, Neuroticism, Conscientiousness, Agreeableness and Intellect/Openness) were assessed using 25 items (5 per dimension) modified from an unpublished 30-item short-form of the 65-item Big Five Questionnaire for Children (BFQ-C)20 supplied by the author (Barbaranelli, personal communication). Items were reworded to simplify the translation from Italian to English. Following pilot testing in 2014, 5 of the 25 items were replaced with other candidates, adapted from the full BFQ-C, to improve psychometric properties. The original 5-point rating response scale was replaced. Self-esteem was measured with three unmodified items from the 7-item Self-Satisfaction subscale of the Multidimensional Students’ Life Satisfaction Scale.21 The original 4-choice response scale and averaged total score were replaced. Daytime sleepiness was assessed with three items selected from the 8-item Pediatric Daytime Sleepiness Scale,9 with minor rewording of items and replacement of the original 5-point response scale. Connection to Nature (or, children’s engagement with the natural environment) was measured with three items; two were modified from the 7-item Enjoyment of Nature subscale of the Connection to Nature Index 22 and one modified from the 14-item Connectedness to Nature Scale.23 The original 5-point rating scales of both measures were replaced. Summary of selected demographic characteristics self-reported by the 27 808 children completing the Middle Childhood Survey (MCS)

Findings to date

Sample characteristics

A flow diagram summarising the stages of school and child recruitment is provided in figure 1; this also details the reasons for non-participation of schools and/or children in the MCS. Of the 2371 NSW schools with an eligible year 6 student enrolment, 829 (35.0%) administered the MCS. These schools provided a total enrolment of 32 389 children who were invited to complete the MCS (representing 36.6% of year 6 enrolments in NSW schools). Among these, 27 808 participated in the MCS (85.9% of invited children). Parent and child opt-outs totalled 4.3% of eligible children (the remaining 9.9% did not participate for other reasons detailed in figure 1). The mean age of participating children was 11.5 years (SD 0.5); other demographic information on participants is summarised in table 2. Average survey completion time was 16.5 min, with 90% of children completing within 7–50 min. The representativeness of participating schools and children relative to the respective state population was estimated using publicly accessible national school-level data on enrolment and sociodemographic indices. Table 3 compares the demographic characteristics of all NSW schools and MCS participating schools, first as distributions of unweighted data, and second as distributions after weighting by year 6 enrolment and number of MCS participants per school. The 829 schools that participated in the MCS were comparable on a range of demographic indices to the total population of NSW schools with a year 6 enrolment; all figures reported for the MCS participating schools (both unweighted data and weighted estimates) lie within ~2% of NSW rates.
Table 3

Demographic characteristics of MCS participating schools relative to all NSW schools with a year 6 student enrolment (unweighted and weighted by enrolment)

Demographic measureUnweighted averagesWeighted averages*
NSW schools (n=2371)MCS schools (n=829)NSW schools (weighted)MCS schools (weighted)
% (n)% (n)% (n)% (n)
School sector:
  Government67.9 (1609)67.1 (556)67.466.6
  Non-government32.1 (762)32.9 (273)32.633.4
Geographical location:
  Metropolitan59.9 (1421)62.4 (517)76.376.2
  Rural37.7 (894)35.8 (297)23.123.3
  Remote1.8 (43)1.4 (12)0.40.5
  Very remote0.5 (13)0.4 (3)0.10.1
Mean (SD)Mean (SD)Mean (SD)Mean (SD)
ICSEA score1007.7 (93.5)1002.8 (92.4)1033.2 (87.1)1026.5 (84.1)
Socioeducational quartiles based on ICSEA (%):
  Lowest28.8 (22.3)29.6 (22.3)23.5 (20.3)24.6 (20.5)
  Lower-Middle24.3 (9.3)24.6 (8.4)22.9 (9.3)23.6 (8.7)
  Higher-Middle23.4 (8.8)23.5 (8.7)24.7 (7.8)24.9 (7.8)
  Highest23.5 (21.7)22.4 (20.5)29.0 (23.4)26.9 (21.7)
Proportion LBOTE (%)23.3 (27.3)23.7 (27.4)31.1 (30.3)30.2 (30.1)
Proportion Indigenous (%)9.1 (13.7)9.5 (13.4)6.0 (9.2)6.3 (9.1)
Proportion female (%)48.6 (9.3)48.8 (7.1)48.5 (10.3)48.7 (7.0)

*To estimate the proportions of children in NSW and MCS schools described by each demographic measure, weighting was applied based on the number of year 6 students (NSW schools) and MCS participants in each school (MCS schools); see Australian Curriculum, Assessment and Reporting Authority [2015], ICSEA 2014: Technical Report. http//www.acara.edu.au/_resources/ICSEA_2014_technical_report.pdf).

ICSEA, Index of Community Socio-Educational Advantage 2014 (this score is derived from a number of variables, including parental school and non-school education and occupation, the school’s geographical location and proportion of Indigenous students); LBOTE, Language Background Other Than English; MCS, Middle Childhood Survey; NSW, New South Wales.

Demographic characteristics of MCS participating schools relative to all NSW schools with a year 6 student enrolment (unweighted and weighted by enrolment) *To estimate the proportions of children in NSW and MCS schools described by each demographic measure, weighting was applied based on the number of year 6 students (NSW schools) and MCS participants in each school (MCS schools); see Australian Curriculum, Assessment and Reporting Authority [2015], ICSEA 2014: Technical Report. http//www.acara.edu.au/_resources/ICSEA_2014_technical_report.pdf). ICSEA, Index of Community Socio-Educational Advantage 2014 (this score is derived from a number of variables, including parental school and non-school education and occupation, the school’s geographical location and proportion of Indigenous students); LBOTE, Language Background Other Than English; MCS, Middle Childhood Survey; NSW, New South Wales.

Item responses and scale distributions

Table 1 summarises the distribution of children’s responses on all MCS items, grouped according to the constructs they measured. Similar data, reported separately for girls and boys, are provided in online supplementary table 1-X. The total number of children reporting each item ranged from a minimum of 26 853 (3.4% missing) to 27 735 (0.3% missing). An unknown portion of these missing responses related to data server capacity issues encountered early in the MCS administration period and resolved promptly by the IT contractor. For each MCS construct, table 4 (and online supplementary table 2-X) provides descriptive statistics (including number of children providing complete data on the scale, means, SD, minima and maxima), internal consistency coefficients (ordinal α-coefficients24) and scores corresponding to a range of percentiles in the sample distribution (ie, 10th, 25th, 50th, 75th, 90th). These percentiles were adapted from those reported for the AEDC6 (where scores in the lowest 10th percentile were described as ‘developmentally vulnerable’, between the 10th and 25th percentiles as ‘developmentally at risk' and between the 25th–50th and >50th percentiles as two bands of ‘developmentally on track’ scores), with the 75th and 90th percentiles added to accommodate the bidirectional orientation of MCS scales.
Table 4

Descriptive statistics (number of children providing complete data on the subscale, means, SD, minima and maxima), internal consistency coefficients (ordinal α) and scores corresponding to a range of percentiles in the sample distribution for each mental health and well-being domain assessed within the Middle Childhood Survey (MCS)

MCS domain (number of items in subscale)Source MeasureSample (n)MeanSDMinimaMaximaOrdinal αScores corresponding to percentiles:
10th25th50th75th90th
Social Integration (8 items)QSL26 85311.763.380160.9179121416
Prosocial Behaviour (5 items)SDQ27 4748.031.730100.7867#8910
Peer Relationship Problems (5 items)SDQ27 4742.031.780100.690123#4
Supportive Home Relationships (4 items)HKS/MDI26 9226.781.640 80.8846888
Supportive School Relationships (4 items)HKS/MDI26 9156.341.920 80.9145788
Supportive Community Relationships (4 items)HKS/MDI26 9095.022.760 80.9604588
Empathy (4 items)FTI27 1085.741.480 80.6045678
Empathy (3 items)*FTI27 1084.941.200 60.7034566
Emotional Symptoms (5 items)SDQ27 4733.022.310100.790134#6
Conduct Problems (5 items)SDQ27 4741.801.800100.800013#4
Aggression (2 items)EATQ-R27 4720.691.040 40.8100012
Attention (3 items)EATQ-R27 1203.591.420 60.5723456
Attention (4 items)*EATQ-R27 1204.931.780 80.6734567
Inhibitory Control (7 items)EATQ-R27 1277.932.940140.764681012
Inhibitory Control (6 items)*EATQ-R27 1276.592.680120.75357910
Hyperactivity-Inattention (5 items)SDQ27 4723.602.370100.770235#7
Total Difficulties (Psychopathology) (20 items)SDQ27 47210.456.070400.88361014#19
Perceptual Sensitivity (4 items)EATQ-R27 1385.601.770 80.7134678
Psychotic-like experiences (9 items)PLEQ-C26 9765.664.460180.90025912
Extraversion (5 items)BFQ-C27 4198.031.760100.76678910
Neuroticism (5 items)BFQ-C27 7333.482.280100.8012357
Conscientiousness (5 items)BFQ-C27 4216.902.200100.78457910
Agreeableness (5 items)BFQ-C27 4157.301.860100.77567910
Intellect/Openness (5 items)BFQ-C27 4157.271.910100.85567910
Self-esteem (3 items)MSLSS27 1694.911.190 60.7034566
Daytime Sleepiness (3 items)PDSS27 1041.541.370 60.6400123
Connection to Nature (3 items)CTNI/CTNS27 1013.721.810 60.8813456

#For the Strengths and Difficulties Questionnaire subscales, scores corresponding to the 80th percentile (ie, equating to the cut-off describing a ‘Borderline’ rating) were: Emotional Symptoms=5, Peer Relationship Problems=3, Conduct Problems=3, Hyperactivity-Inattention=6, Prosocial Behaviour (20th percentile)=7 and Total Difficulties=16. The Total Difficulties scale represents the sum of items on the four psychopathology scales (Emotional Symptoms, Peer Relationship Problems, Conduct Problems, Hyperactivity-Inattention); BFQ-C, short form of the Big Five Questionnaire for Children; CTNI/CTNS, Connection to Nature Index/Connectedness to Nature Scale. * Indicates the revised version of the scale with modified number of items (see Footnote ii); EATQ-R, Early Adolescent Temperament Questionnaire—Revised; FTI, Feeling and Thinking Index; HKS/MDI, Healthy Kids Scale/Middle Years Development Index; MSLSS, Multidimensional Students’ Life Satisfaction Scale; QSL, Quality of School Life; PDSS, Pediatric Daytime Sleepiness Scale; PLEQ-C, Psychotic-Like Experiences Questionnaire for Children; SDQ, Strengths and Difficulties Questionnaire.

Descriptive statistics (number of children providing complete data on the subscale, means, SD, minima and maxima), internal consistency coefficients (ordinal α) and scores corresponding to a range of percentiles in the sample distribution for each mental health and well-being domain assessed within the Middle Childhood Survey (MCS) #For the Strengths and Difficulties Questionnaire subscales, scores corresponding to the 80th percentile (ie, equating to the cut-off describing a ‘Borderline’ rating) were: Emotional Symptoms=5, Peer Relationship Problems=3, Conduct Problems=3, Hyperactivity-Inattention=6, Prosocial Behaviour (20th percentile)=7 and Total Difficulties=16. The Total Difficulties scale represents the sum of items on the four psychopathology scales (Emotional Symptoms, Peer Relationship Problems, Conduct Problems, Hyperactivity-Inattention); BFQ-C, short form of the Big Five Questionnaire for Children; CTNI/CTNS, Connection to Nature Index/Connectedness to Nature Scale. * Indicates the revised version of the scale with modified number of items (see Footnote ii); EATQ-R, Early Adolescent Temperament Questionnaire—Revised; FTI, Feeling and Thinking Index; HKS/MDI, Healthy Kids Scale/Middle Years Development Index; MSLSS, Multidimensional Students’ Life Satisfaction Scale; QSL, Quality of School Life; PDSS, Pediatric Daytime Sleepiness Scale; PLEQ-C, Psychotic-Like Experiences Questionnaire for Children; SDQ, Strengths and Difficulties Questionnaire. The total number of children providing complete scale data ranged from a minimum of 26 853 (3.4% missing) to a maximum of 27 733 (0.3% missing). On average, children in the sample scored in the range reflecting healthier or more developmentally mature functioning on each construct, but the population distribution spanned the full range of possible scores on every scale. For most scales, each of the specified percentiles was associated with a unique score on the scale even at the extremes (10th and 90th percentiles), indicating a lack of ceiling/floor effects in measurement. The ordinal α-coefficients indicated adequate reliability for all MCS domains; for the two scales with the lowest α-coefficients (Attention and Empathy), minor modifications to these scales improved the coefficients and these revised scales are also summarised in the Tables.

Profile of mental health and well-being in the MCS cohort

High mean total scores on Social Integration, Prosocial Behaviour, Empathy, Attention, Inhibitory Control and Self-esteem were indicative of healthier functioning or developmentally more mature capacities for the majority of children in the sample. High mean scores also indicated most children’s access to Supportive Relationships at Home, School and in the Community, and engagement with the natural environment (Connection to Nature). Low mean total scores on Peer Relationship Problems, Emotional Symptoms, Conduct Problems, Aggression, Hyperactivity-Inattention, Total Difficulties (psychopathology) and Daytime Sleepiness were further indicative of healthy functioning among the majority of children in the MCS cohort. Nonetheless, on all scales, there were children who displayed less healthy or developed functioning or lacked access to supports (eg, 13.2% of children reported a lack of any supportive relationship with an adult in their community or neighbourhood). Other scales in the MCS measured unusual thoughts or perceptual experiences that, although more prevalent in children with neurodevelopmental disorders and those who later develop adult psychiatric illness, are nonetheless common in child populations25: a majority of children (52.2%) responded ‘Certainly True’ to at least one of the nine PLE items, and the high mean total scores on Perceptual Sensitivity indicated that most children also reported sensitivity to slight, low-intensity stimulation in the environment. With respect to personality dimensions, on average, children produced higher scores on Extraversion, Conscientiousness, Agreeableness and Openness/Intellect scales (reflecting a tendency to avoid endorsement of the ‘Not True’ response), and lower scores on Neuroticism, relative to the scale range of each construct. Pearson’s correlation coefficients indicating the pattern, direction and strength of associations (small 0.1; medium 0.3; large 0.5)26 between the MCS scales are provided in online supplementary table 3-X (with associations for girls and boys provided in online supplementary table 4-X). Almost all constructs related significantly in this large sample, with almost half (45%) of the associations of medium or large magnitude.

Comparison with published data

Direct comparison of MCS responses with published data on the SDQ and PLE scales from general population samples was afforded by use of the original items, response options and scoring methods for these scales. Mean scores on Prosocial Behaviour and Conduct Problems aligned closely with Australian self-report SDQ norms published in 2005 by age and sex (based on a Victorian community sample of 553 children aged 11–17 years, including 292 children aged 11–13 years)27, and were slightly greater in our sample for Total Difficulties, Emotional Symptoms, Peer Relationship Problems and Hyperactivity-Inattention. This pattern of change in means over the decade between the 2005 study and ours appears consistent with the small, but significant, increases observed between 2007 and 2012 in the self-report subscale means for Total Difficulties, Emotional Symptoms, Peer Relationship Problems and Hyperactivity-Inattention (but a decrease in Conduct Problems) in nationally representative New Zealand samples of children aged 12–15 years,28 and with a similar increase in Emotional Symptoms and decrease in Conduct Problems between 2009 and 2014 in English community samples of children aged 11–13 years.29 The mean PLE score in the MCS sample aligned closely with that reported previously for a relatively deprived inner-city London, UK, community sample aged 9–12 years19 using these same nine items, although the overall prevalence of a ‘Certainly True’ to at least one of the nine items in the MCS (52.2%) was lower than that obtained in the London sample (66.0%).8 For the SDQ psychopathology scales, table 5 (and online supplementary table 5-X) indicates the proportions of children falling within the normal (defined as ~80%), borderline (~10%) and abnormal (~10%) categories defined for the SDQ based on the UK population norms, as well as the proportions of children scoring in each category of the more recent four-level solution (close to average ~80%, slightly raised ~10%, high ~5%, very high ~5%). Several departures from these figures are notable (eg, 91% of children scored in the normal range of the Prosocial Behaviour scale, and only 67% of children scored ‘close to average’ on the Peer Relationship Problems scale); the application of the established scoring metrics derived on the UK population samples may overestimate the prevalence of problems with peers and underestimate vulnerability on Prosocial Behaviour among Australian children aged approximately 11 years.
Table 5

Distribution of the Strengths and Difficulties Questionnaire (SDQ) categories on each subscale as defined by the traditional three-level and more recent four-level solutions

SDQ subscaleSampleNormalBorderlineAbnormal
(n)%(n)%(n)%(n)
 Emotional Symptoms27 47384.6(23 233)6.5(1778)9.0(2462)
 Peer Relationship Problems27 47481.2(22 318)13.8(3789)5.0(1367)
 Conduct Problems27 47483.2(22 870)7.7(2125)9.0(2479)
 Hyperactivity-Inattention27 47278.0(21 416)9.5(2613)12.5(3443)
 Prosocial Behaviour27 47490.7(24 908)5.6(1543)3.7(1023)
 Total Difficulties27 47279.9(21 943)11.6(3180)8.6(2349)

*For the Prosocial Behaviour subscale, the four-level classification labels are instead ‘close to average’, ‘slightly lowered’, ‘low’ and ‘very low’.

Distribution of the Strengths and Difficulties Questionnaire (SDQ) categories on each subscale as defined by the traditional three-level and more recent four-level solutions *For the Prosocial Behaviour subscale, the four-level classification labels are instead ‘close to average’, ‘slightly lowered’, ‘low’ and ‘very low’. Capacity for direct comparison of MCS data with published data from similar large, general population samples was limited for the other scales owing to modification from the original response formats to a standard three-choice format, adoption of a standard method of summed total scores for all scales and by minor alterations to the wording of some items. Despite these modifications, consistencies with data from other developed nations were apparent: children’s reports of Social Integration at school were similar to those reported previously in primary school samples in Australia14 and Hong Kong30 31; response patterns on the EATQ-R scales (Attention, Inhibitory Control, Perceptual Sensitivity and Aggression) aligned with data from a community sample of 1055 Dutch32 school students of similar age and access to Supportive Relationships at Home, School and in the Community was similar to that reported for a community sample of Canadian fourth-grade school children (~2 years younger than our sample).16 The pattern of responses on the Big Five personality constructs was also consistent with that reported for an Australian sample of 268 children aged 10–12 years33 using the full 65-item version of the BFQ-C.20

Sex differences

Supplementary table 2-X provides the item responses and scale distributions separately for girls and boys, and the eta squared (η2) estimate of the effect size of sex differences for each scale. Statistically significant differences between the scores of girls and boys were apparent on all scales, although the magnitude of these differences was small (sex effects on all scales accounted for ≤2% of total variance, except for the small-to-medium effects, explaining 4% of total variance, on Prosocial Behaviour and Aggression). Across the domains, girls’ mean scores were greater than those of boys’ on Social Integration, Prosocial Behaviour, Supportive Relationships at Home, School and in the Community, Empathy, Emotional Symptoms, Attention and Inhibitory Control, Perceptual Sensitivity and Psychotic-Like Experiences, Neuroticism, Conscientiousness, Agreeableness, Self-esteem and Connection to Nature. Conversely, boys’ mean scores were greater on Peer Relationship Problems, Conduct Problems and Aggression, Hyperactivity-Inattention, Total Difficulties (psychopathology), Extraversion, Openness/Intellect and Daytime Sleepiness.

Strengths and limitations

The major strengths of the MCS are twofold. First, the MCS provides a comprehensive assessment of psychosocial and behavioural constructs reflecting mental health and well-being in a large sample of 27 808 children aged approximately 11 years (representing 31.4% of eligible NSW students), which is representative of the NSW population on a range of demographic variables (table 3). Second, the MCS incorporated measures of both personal competencies and vulnerabilities, and the scores on every scale spanned the entire range of possible scores, providing capacity to examine patterns of both strength and vulnerability in the population. This also facilitates the identification of determinants of average mental health in the population (rather than focusing on the extreme ends of the distribution), which will provide important information to guide the development and implementation of universal mental health promotion programmes alongside targeted approaches for vulnerable children.34 Data were collected by self-report, providing access to the child’s own perspective on their experiences, which may be particularly important for phenomena that are less readily judged by other informants. Finally, an important strength of the MCS lies in being embedded within planned record linkages of the NSW-CDS,5 incorporating intergenerational records on health, education, child protection and justice contacts, and with the AEDC6 assessment of early childhood development at age 5 years. This will allow responses on the MCS to be interpreted in the context of longitudinal data that is subject to minimal selection bias and will permit investigation of multiple factors associated with outcomes of low prevalence, and/or of relevance to cultural, geographic, socioeconomic or other subgroups within the population. A number of limitations of the MCS must be acknowledged. Despite the large sample obtained being representative of the population from which it was drawn, failure to obtain data from all individuals will have the consequence of limiting data available to the current and future record linkages conducted within the NSW-CDS framework. The MCS is further limited by a lack of parent and/or teacher reports to supplement children’s self-report. Only moderate agreement is typical between child, parent and teacher ratings of children’s mental health and well-being, indicating that the ratings of informants are not interchangeable.35 Furthermore, the MCS was limited in coverage both in terms of domains assessed and the number of items assessing each domain; these were constrained by the limited time available within schools for survey administration, lack of parent and/or teacher reports on additional aspects of children’s experiences and by the sensitivities associated with assessing domains perceived as potentially distressing for the child. For example, information on potentially important constructs such as bullying/victimisation experiences or physical health (including participation in health/leisure activities and nutrition) was not obtained. Similarly, our assessment of Aggression was limited to only two items, which do not capture the full complexity and multidimensional nature of this construct. And, while aspects of the cognitive control of emotions and behaviours were measured, no assessment of cognitive capacities was obtained; linkage of the MCS with education records on academic progress within the NSW-CDS will provide some index of these capacities. The lack of capacity to compare MCS data directly with published data from similar large, general population samples was limited for most scales owing to modification from the original response formats to a standard three-choice format, adoption of a standard method of summed total scores for all scales and by minor alterations to the wording of some items. On several scales, including the personality dimensions, the restriction of responses to three categories may have artificially reduced variability among participants, with <10% of children electing one of the three options on several items. Prior to MCS administration, psychometric testing of our English translation of the short-form Italian BFQ-C20 measure of personality dimensions was conducted using the data obtained from 645 children during pilot testing of the survey in 2014, with subsequent revision of 5 of the 25 items assessing these dimensions in the MCS. A manuscript reporting the validity and reliability of this revised measure is currently being drafted for publication.

Future plans

Further structural analysis of the MCS data is underway to derive the most psychometrically robust measures of each mental health and well-being domain. The multiagency, intergenerational linkage of the MCS data with other health, education, child protection, justice and AEDC records took place late in 2016. This will be used to elucidate patterns of risk and protection across early and middle child development, and also provide a foundation for future record linkages in the cohort that will track mental and physical health, social and educational/occupational outcomes into adolescence and early adulthood. The record linkage will also incorporate data on the quality and extent of implementation of mental health promotion and early intervention programmes in NSW schools, affording an opportunity to examine how delivery of such programmes may modify individual pathways of social, emotional and behavioural function between early and middle childhood. This work will assist in determining appropriate universal mental health promotion and targeted early intervention programmes that can bolster strengths and mitigate risks in order to maximise healthy development. The reasons for principal opt-outs were not assessed systematically, but among those who volunteered this information, these were predominantly that the school was too busy to participate or already committed to other research participation. For the Empathy construct, the ‘alpha if item removed’ value indicated improvement of the α-coefficient following removal of one of the four items. For the Attention construct, alpha was improved by relocating an item from the Inhibitory Control scale that has been previously demonstrated to load with the Attention items in published factor analysis of the full scale.32 These modifications are indicated by ‡ in table 1 (and online supplementary table 1-X), and detail on the revised scales included in table 4 (and online supplementary table 2-X).
  17 in total

1.  Population mean scores predict child mental disorder rates: validating SDQ prevalence estimators in Britain.

Authors:  Anna Goodman; Robert Goodman
Journal:  J Child Psychol Psychiatry       Date:  2010-08-13       Impact factor: 8.982

2.  Community screening for psychotic-like experiences and other putative antecedents of schizophrenia in children aged 9-12 years.

Authors:  Kristin R Laurens; Sheilagh Hodgins; Barbara Maughan; Robin M Murray; Michael L Rutter; Eric A Taylor
Journal:  Schizophr Res       Date:  2007-01-05       Impact factor: 4.939

3.  A power primer.

Authors:  J Cohen
Journal:  Psychol Bull       Date:  1992-07       Impact factor: 17.737

4.  The Strengths and Difficulties Questionnaire: a research note.

Authors:  R Goodman
Journal:  J Child Psychol Psychiatry       Date:  1997-07       Impact factor: 8.982

Review 5.  The Great Smoky Mountains Study: developmental epidemiology in the southeastern United States.

Authors:  E Jane Costello; William Copeland; Adrian Angold
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2016-03-24       Impact factor: 4.328

Review 6.  Prevalence of psychotic symptoms in childhood and adolescence: a systematic review and meta-analysis of population-based studies.

Authors:  I Kelleher; D Connor; M C Clarke; N Devlin; M Harley; M Cannon
Journal:  Psychol Med       Date:  2012-01-09       Impact factor: 7.723

7.  Data resource profile: the Australian early development index (AEDI).

Authors:  Sally A Brinkman; Tess A Gregory; Sharon Goldfeld; John W Lynch; Matthew Hardy
Journal:  Int J Epidemiol       Date:  2014-04-24       Impact factor: 7.196

8.  The pediatric daytime sleepiness scale (PDSS): sleep habits and school outcomes in middle-school children.

Authors:  Christopher Drake; Chelsea Nickel; Eleni Burduvali; Thomas Roth; Catherine Jefferson; Badia Pietro
Journal:  Sleep       Date:  2003-06-15       Impact factor: 5.849

9.  The Dunedin Multidisciplinary Health and Development Study: overview of the first 40 years, with an eye to the future.

Authors:  Richie Poulton; Terrie E Moffitt; Phil A Silva
Journal:  Soc Psychiatry Psychiatr Epidemiol       Date:  2015-04-03       Impact factor: 4.328

Review 10.  Common or distinct pathways to psychosis? A systematic review of evidence from prospective studies for developmental risk factors and antecedents of the schizophrenia spectrum disorders and affective psychoses.

Authors:  Kristin R Laurens; Luming Luo; Sandra L Matheson; Vaughan J Carr; Alessandra Raudino; Felicity Harris; Melissa J Green
Journal:  BMC Psychiatry       Date:  2015-08-25       Impact factor: 3.630

View more
  5 in total

1.  An event- and network-level analysis of college students' maximum drinking day.

Authors:  Matthew K Meisel; Angelo M DiBello; Sara G Balestrieri; Miles Q Ott; Graham T DiGuiseppi; Melissa A Clark; Nancy P Barnett
Journal:  Addict Behav       Date:  2017-12-27       Impact factor: 3.913

2.  Self-reported mental health of children known to child protection services: an Australian population-based record linkage study.

Authors:  Kirstie O'Hare; Aniqa Hussain; Kristin R Laurens; Gabrielle Hindmarsh; Vaughan J Carr; Stacy Tzoumakis; Felicity Harris; Melissa J Green
Journal:  Eur Child Adolesc Psychiatry       Date:  2021-07-10       Impact factor: 4.785

3.  Making Nature Explicit in Children's Drawings of Wellbeing and Happy Spaces.

Authors:  Zoe Moula; Nicola Walshe; Elsa Lee
Journal:  Child Indic Res       Date:  2021-03-24

4.  Children's mental and behavioral health, schooling, and socioeconomic characteristics during school closure in France due to COVID-19: the SAPRIS project.

Authors:  Maëva Monnier; Flore Moulin; Xavier Thierry; Stéphanie Vandentorren; Sylvana Côté; Susana Barbosa; Bruno Falissard; Sabine Plancoulaine; Marie-Aline Charles; Thierry Simeon; Bertrand Geay; Laetitia Marchand; Pierre-Yves Ancel; Maria Melchior; Alexandra Rouquette; Cédric Galera
Journal:  Sci Rep       Date:  2021-11-17       Impact factor: 4.379

5.  Developmental profiles of schizotypy in the general population: A record linkage study of Australian children aged 11-12 years.

Authors:  Melissa J Green; Kirstie O'Hare; Kristin R Laurens; Stacy Tzoumakis; Kimberlie Dean; Johanna C Badcock; Felicity Harris; Richard J Linscott; Vaughan J Carr
Journal:  Br J Clin Psychol       Date:  2022-03-01
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.