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Appendix 1: Data Linkage Specification

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CHILD PROJECT

SPECIFICATION FOR DATA LINKAGE

9 December 2010

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Study team Principal researcher Phil Wilson Senior Lecturer in Infant Mental Health University of Glasgow Centre for Population and Health Sciences Caledonia House RHSC Yorkhill Glasgow G3 8SJ Tel: 0141 202 9239 Email: philip.wilson@glasgow.ac.uk Principal contact Tracy Ibbotson Co-applicants Lucy Reynolds Lucy Thompson Rachael Wood John Butcher Alex McConnachie

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Study proposal Background The ChILD (Childhood Information for Learning and Development) project aims to improve awareness of information available on early child development in Scotland and its use in developing and evaluating services for pre-school children and their families. The first phase of the project explored current data collection systems for pre-school child development throughout Scotland, and planned future improvements. The second phase will explore ways of presenting cross-sectional developmental data at local population level to support activities such as needs assessment and service evaluation. The final phase will explore what data linkage can add by allowing the analysis of developmental trajectories at individual level. It is this final phase that is covered by this proposal. Research Question To what extent can developmental problems evident in toddlers and children starting school be predicted from data that are routinely available by children’s early infancy? Proposed Methods Participants Two cohorts of children will be included in the study. The first cohort comprises approximately 3600 children entering primary school in Glasgow City Council area in 2010. The second cohort comprises approximately 800 children living in West Glasgow Community Health Partnership who were eligible for a 30 month universal contact with their health visitor between July and December 2009. Outcome variables For Cohort 1 the key outcome variable of interest is social, emotional and behavioural problems identified by the Strengths and Difficulties Questionnaire. The SDQ was completed by nursery based Child Development Officers in Glasgow in 2010 as part of the routine transition documentation that accompanies children moving into P1. For Cohort 2 the key outcome variables are delayed language development identified by the Health Visitor using a modified Miniscalco screening tool and Richman Behaviour Checklist score. Predictor variables For both cohorts, predictor variables will comprise factors known or likely to be associated with suboptimal child development about which data are routinely recorded through the Scottish hospital delivery record (SMR02) and/or the Child Health Surveillance Programme – Pre School data system up to the child being 12 weeks old. An SMR02 record is generated every time a baby is born in a Scottish hospital. A CHSP-PS record is generated every time a Health Visitor sees an infant for their universally offered ‘first visit’ (at age 10 days) and 6-8 week review. Further CHSP-PS records can be generated at other times if a HV sees a child for a particular concern. The predictor variables will include factors such as maternal age, baby’s gestation and Apgar scores, smoking in the home, infant feeding, and any developmental concerns identified by the HV. See Appendix 1 for a full list of outcome and predictor variables for the 2 cohorts. Linkage The SDQ data on Cohort 1 children are held by Glasgow City Council Education Department. The relevant data including children’s personal identifiers (first name, second name, gender, date of birth and full home postcode), their Scottish Candidate Number (a unique identifier allocated to all children entering school in Scotland), and their SDQ results will be passed from the Education Department to the ChILD research office. Data from the HV 30 month contacts on Cohort 2 children are held by the Glasgow Parenting Support Framework Evaluation Office in Yorkhill hospital. The relevant data including children’s personal identifiers, their Community Health Index (CHI) number, and language screen results will be passed to the ChILD research office which is co-located with the Parenting Support Framework Evaluation Office. The ChILD research team will generate a unique study number for each child. Each child’s personal identifiers along with their unique study number (but not their developmental data) will then be transferred to NHS National Services Scotland Information Services Division (ISD) which holds the national SMR02 and CHSP-PS data. ISD will use the personal identifiers to link to the children’s SMR02 delivery records and any CHSP-PS records generated when the child was aged up to 12 weeks. ISD will extract the specified predictor variables

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from these records and return these to the ChILD research office along with the children’s unique study number (but not personal identifiers). The predictor and outcome variables for individual children will then be linked by the ChILD research team using the unique study number and this file will be used for analysis. Some analyses will involve calculations of proximity between cases and for these analyses only a separate file will be used holding the child’s postcode of residence. A file holding children’s unique study number and their personal identifiers will be held separately.

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Summary of linkage process

Personal identifiers and language screen data on Cohort 2 from Glasgow Parenting Support

Framework Evaluation Office passed to ChILD research office

ChILD research office generates unique study number for each child

Personal identifiers and USN passed to ISD

Predictor variables extracted from SMR02 and CHSP-PS using

record linkage

Predictor variables and USN passed back to

ChILD research office

Analysis file containing predictor

and outcome variables and USN created

Separate file containing personal identifiers and

USN created

Personal identifiers and SDQ data on Cohort 1 from Glasgow Education Department passed to

ChILD research office

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Analysis Linear and logistic regression will be used to explore which predictor variables are associated (and to what extent) with developmental problems in each of the cohorts. Exploratory analyses will assess the degree of institutional and regional clustering of outcomes. Benefits The project aims to capitalise on the opportunity to explore how existing and novel population based data on early childhood development can be systematically used to support the enhancement and evaluation of services for pre-school children. Duration of study The Childhood Information for Learning and Development (ChILD) project commenced in April 2010. This data linkage project will commence in April 2011 and will be completed in March 2012.

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Governance and security Permission to transfer the outcome data on Cohort 1 children to the ChILD research office and subsequently link it has been sought from the data controller for Glasgow City Council. Permission to transfer the outcome data on Cohort 2 children to the ChILD research office and subsequently link it has been sought from the Director of Public Health in Greater Glasgow and Clyde NHS Board. Permission for the linkage process as outlined above has been sought from the Caldicott Guardian of NHS Greater Glasgow and Clyde. Explicit consent for the use of personal data described in this proposal has not been sought from the children involved or their parents. It is felt that this is proportionate as risks to individuals are very low and the potential bias introduced by seeking explicit consent could reduce the validity of the study considerably. The developmental data collected in the 30 month visit was part of a service evaluation and parents were given an information sheet and the opportunity to opt out of the data collection. The SDQ data are gathered as part of the routine documentation transferred from pre-school establishments and parents are informed about its collection. Research ethics approval for this data will be sought from the University of Glasgow Faculty of Medicine Research Ethics Committee. No individual children or their families will be contacted during, or as a result of, this study. All data relating to this study will be held by the ChILD research office based in Yorkhill hospital, Glasgow or at the Robertson Centre for Biostatistics at the University of Glasgow. Files in the ChILD research office will be held on a secure server within the NHS firewall and accessed through a single password protected computer within the ChILD office. The ChILD office is locked when not in use and there are access controls to the building which is shared with a locked clinical facility. The Data Protection Act registration number for Yorkhill hospital is Z8522787 Data will be physically transferred to the Robertson Centre for Biostatistics (RCB) in encrypted format. Only designated IT and statistical staff will have access to the data, and all analyses will be carried out under the supervision of Dr Alex McConnachie, Senior Statistician. The RCB, part of the UKCRN-accredited Glasgow Clinical Trials Unit (https://www.glasgowctu.org), is a research centre within the University of Glasgow with expertise in the provision of services related to the coordination, data management and statistical analysis of clinical trials and epidemiological studies. The Centre is recognised internationally as a centre of excellence due to its contributions to medical research through its work on major international multi-centre clinical trials, epidemiological studies and other research projects. All studies are managed to the highest standards in accordance with Centre internal standard operating procedures which ensure compliance with all legal guidelines. The Centre has extensive experience of managing data in the context of privacy and data protection legislation, including the Data Protection Act 1998 and EU Data Protection Directive 95/46/EC. The Centre is certified for ISO 9001:2000 for its quality systems, has TickIT certification for its software development and is BS7799 compliant. The Centre is audited every six months by the British Standards in Industry (BSI) and regularly conducts its own internal audits, with these carried out by BSI-trained internal auditors. The Centre has also been subject to numerous external audits, by clients, the Food and Drug Administration (FDA) and the Medicines and Healthcare products Regulatory Agency (MHRA). Only the staff members noted will have access to the files containing any personal identifiers. All staff with access to identifiable data have had training in data protection and confidentiality Files will be retained for up to 10 years following completion of the study then destroyed in line with NHS and Good Clinical Practice guidance. All data transfer required as part of the linkage process will be via email over the NHS net wherever possible. When this is not possible (eg when sending data from education to the NHS) files will be encrypted in line with NHS guidance prior to transfer. Identifiable data gathered through this study will not be shared outwith the study team. Only aggregate, non-disclosive data will be included in published reports and papers.

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Appendix 1 Detail of outcome and predictor variables Outcome variables for Cohort 1 to be obtained from Glasgow City Council Education Department on children entering P1 in Glasgow in 2010

• First name • Second name • Gender • DOB • Postcode • Scottish Candidate Number (may facilitate future linkages) • Strengths and Difficulties Questionnaire results (all questions) • Ethnicity (not routinely available through SMR02 or CHSP-PS data). • Looked after status

Outcome variables for Cohort 2 to be obtained from Glasgow Parenting Support Framework Evaluation Office on children living in West Glasgow who had a 30 month universal contact with their health visitor between July and December 2009.

• First name • Second name • Gender • DOB • Postcode • Community Health Index number • Language screen resultsa • Richman Behaviour Checklist score • Parenting Daily Hassles scale score

Predictor variables for both cohorts to be obtained from ISD. SMR02 data

• Maternal age • Maternal ethnicity • Maternal SIMD rank for area of residence • Maternal smoking • Maternal drug use during pregnancy • Parity • Birth order • Gestation at booking • Number of births this pregnancy • Gestation at delivery • Birth weight (combine with gestation to create small for dates indicator) • Mode of delivery • Apgar • OFC • Sex • Neonatal indicator (ie admission to SCBU) • Infant feeding

CHSP-PS data From HV first visit

• Maternal age • Maternal smoking • Child exposed to passive smoking

a Ability to make 2-word utterances (yes/no), vocabulary of 50 words (yes/no)

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• Infant feeding • Concerns raised by carer • Problems noted by HV • HPI

From 6-8 week review

• Infant feeding • Concerns raised by carer • Developmental assessment (gross motor skills, hearing and communication, vision and social

awareness) • Physical examination • Problems noted by HV • HPI

Other CHSP-PS records generated in the first 12 weeks of the child’s life

• Newborn hearing screening results • Concerns raised by carer • Development assessment • Physical examination • Problems noted by HV

Note that the Child Health Surveillance programme offered in Glasgow changed on 1.4.2006 in response to recommendations made in Health for all Children 4. After this time, all children having a HV first visit or 6-8 week review could have a Health Plan Indicator (HPI) category recorded by their HV on the CHSP-PS record of their review. The HPI reflects the child’s overall need for ongoing CHS support (core, additional, or intensive). Cohort 1 children were born before this change hence will not have any HPI data available but Cohort 2 children will have HPI data available. 1 Health for all Children 4: Guidance on Implementation in Scotland 2005

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Appendix 2 Biographies of study team The research will be co-ordinated by Tracy Ibbotson, who has training in data linkage procedures and multiple logistic regression. She is currently involved in an evaluation of a complex multi-agency intervention for early years care in North Lanarkshire. She has a degree in psychology and a PhD in the psychometric assessment of anxiety and depression. Philip Wilson is a general practitioner with a background in paediatrics and neuroscience. He recently completed a Primary Care Research Career Award with a programme of work investigating the role of primary care in improving infant mental health. He has been involved in the development and evaluation of many complex interventions and participated in the MRC-sponsored Primary Care Complex Interventions Methodology group. His most recent work has focussed on early identification and management of emotional, psychological and behavioural problems in preschool children. Rachael Wood is a consultant in public health medicine with a special interest in child public health. She has recently completed a clinical academic training fellowship which incorporated a programme of research on preventive care for preschool children. She also recently achieved the first linkage between national maternity and child health data in Scotland. She is now based in the Information Services Division of NHS National Services Scotland with responsibility for national child health data and using national data for research purposes. Lucy Reynolds is a consultant paediatrician with a special interest in child public health. Her epidemiological training was mostly through a Masters in Community Paediatrics, as part of which she conducted research into the relationships between socioeconomic status and the incidence of autism and speech and language impairment, using the West Sussex child health database. Within the NHS GG&C maternal and child public health team, she now takes the lead on child health surveillance, child health data and population profiling. She chaired the national group which developed the new Personal Child Health Record for Scotland, and is a member of the national “Hall 4” steering group, Maternal and Child Health IT Strategy Group, and the Child Health Surveillance Programme- Preschool National User Group. Lucy Thompson is a Senior Researcher within the Public Health Resource Unit at NHS Greater Glasgow & Clyde and Honorary Research Fellow at the University of Glasgow. Graduating with a PhD in psychology in 2003, she has worked in health service research for over 6 years, facilitating and managing service evaluations and other research projects. In 2009 she completed a Master of Public Health degree, where the research dissertation focused on health visiting, and she currently coordinates the evaluation of the Glasgow City Parenting Support Framework John Butcher is Head of Inclusion at Glasgow City Council Education Services. Originally a teacher, with the majority of his career has been in Education services he has also worked for Social Work and NHS Lanarkshire. He has post Graduate Social work qualifications and is a registered Mental Health Officer. John is a member of the education directorate team in Glasgow and has responsibility for Inclusion and retains a particular interest in meeting the needs of the most disadvantaged children in the city. Alex McConnachie is a senior statistician at the Robertson Centre for Biostatistics. Whilst studying for a PhD in Statistics, he was appointed as Statistician to the MIDSPAN Family Study in 1996, subsequently working in the Department of General Practice and in 2003, he was appointed on a permanent basis as Consultant Statistician at the Robertson Centre for Biostatistics where he completed writing up his PhD. Throughout his career he has collaborated with non-statistical researchers on a wide range of medical (and some non-medical) projects. He has published a large number of papers in the highest quality medical journals

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Appendix 2: Phase 1 full report

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Childhood Information for Learning and Development project Phase one report How do we use information to support Scotland’s children?

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BACKGROUND

The quality of the relationships, stimulation, and services that children receive in their early years are crucial to their long term health and development1-5. We know that children who experience unstimulating environments and fail to receive sensitive and responsive parenting over their early years are likely to be significantly behind their peers in terms of social, emotional, linguistic, and cognitive development by the time of school entry3. We also know that these early inequalities in developmental status often precede widening inequalities in health, educational attainment, and social and economic functioning over the life course1. A European Child Well-being Index created in 2006 used various well-being indicators which placed the UK near the bottom of the index, along with ex-Soviet satellite states6. UNICEF produced an overview of child well-being in which the United Kingdom was ranked at the lowest level of child wellbeing among 21 of the rich OECD countries7. There is therefore a substantial policy focus at national and local level on enhancing services that protect and promote early childhood development8-10.

Scotland is rightly considered to be a world leader in the quantity and quality of its national, whole population based, health data; however it singularly fails to capture data on early childhood development. At national level, good quality data are available on maternal health, births, neonatal health, specific aspects of pre-school children’s health including universal health visitor contacts conducted at 10 days and 6-8 weeks of age, all hospital admissions, and educational attainment of school age children. No whole-population data on the social, emotional, linguistic, and cognitive development of children are however currently collected between eight weeks of age and school entry.

A number of initiatives have generated data relevant to the wellbeing of Scotland’s children, but they either lack detail or a whole-population perspective. The Scottish Public Health Observatory has produced child health profiles for local areas across Scotland but these do not include any information on early childhood developmentb. The Glasgow Centre for Population Health has recently launched a childhood section to their website - ‘Understanding Glasgow’c which focuses on population-level datasets comparable within the city and with other regions. Although this resource covers a range of useful data on children’s lives in Glasgow, it includes only a small proportion of developmental indicators. The Early Years Framework10 data and indicators group has included emotional, behavioural and cognitive readiness for school in their indicators framework11, although these data are derived from the Growing Up in Scotland study which has suffered from differential attrition and the data cannot currently be used at local authority level. A set of Children and Young People’s Mental Health Indicators has been developed by NHS Scotlandd,12, although it acknowledges that limitations of the evidence base and lack of available data means it can only serve as a foundation for much more work. The European Index of Child Well-being has used sample surveys and routine organisational data to generate 51 indicators grouped into eight clusters: material situation, housing, health, subjective well-being, education, children’s relationships, civic participation and risk and safety. The UNICEF report card drew on 40 indicators grouped into six dimensions of child well being: material well-being, health and safety, education, peer and family relationships, behaviour and risks, and young people’s own subjective sense of well-being7.

Survey techniques are used in the Growing Up in Scotland (GUS) study to track the cognitive, emotional and physical development in a cohort of children13 but these data are inevitably subject b see http://scotpho.org.uk/web/FILES/Profiles/2010/CYPP/CYP%20Scotland%20Overview%20final.pdf for examples of ScotPHO’s child health profiles c see http://www.understandingglasgow.com for examples of the Glasgow Centre for Population Health Centre child health indicators d See http://www.healthscotland.com/understanding/population/mental-health-indicators/children.aspx

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to the biases inherent in almost all cohort studies, particularly the tendency to selective attrition of children with behavioural problems14. Finally, it is unclear whether the routinely available (non-developmentally focused) data we do have are being used to inform development and evaluation of services for pre-school children at local level.

A recent environmental scan of early interventions relevant to Scotland provides a comprehensive overview of the field and outlines key gaps in our knowledge of what works15. It is desirable that the establishment of population level data systems describing child development should be available for the evaluation of the effectiveness of future early years policy directions.

The ChILD (Childhood Information for Learning and Development) project was established in part to investigate the types of data currently collected for pre-school child development throughout Scotland, including the consistency in systems, and planned future improvements. The findings will inform further consideration of the best use of data systems by policy makers and planners.

SURVEY OF DATA COLLECTION SYSTEMS IN SCOTLAND

This report presents information based on a mapping survey undertaken across Scotland in 2010. The aim of the survey was to explore how existing population based data on early childhood development are collected and how they are used across Scotland, both in local authorities and health boards.

Methods

Potential participants for the mapping survey were defined as those involved in the commissioning and delivery of services relating to preschool child development in Scotland, e.g., NHS Board child public health leads, education authority information leads and national level data custodians throughout Scotland. A primary list was drawn up by the study steering group with further participants identified using a snowball sampling technique. Potential participants were contacted via email with the following attachments: (i) a cover letter from the Principal Investigator briefly describing the purpose of the study; (ii) a project information sheet describing the study aims, outlining what participation would involve, and featuring contact details for the research team; and (iii) a copy of a consent form. The research fellow followed-up each email with a telephone call to arrange a time and place for the interview at the participant’s convenience. This included the possibility of a telephone interview. Interviews took place once a completed consent form had been returned to the research fellow. Interviews were audio recorded with the permission of the interviewee and each lasted about 30 minutes. The structured interview comprised four sections: socio-demographic information about the respondent, knowledge of current data systems, knowledge of the future development of data systems, and knowledge of other personnel working with data systems for early childhood. The covering letter, information sheet, consent form and interview schedule are available on request.

Ethics

Ethical review and approval was provided by the University of Glasgow Medical Faculty Ethics Committee (ref: FM05809).

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Findings

Final sample

Thirty-one participants were recruited from six NHS Scotland regions, three Local Authorities, NHS Information Services Division (ISD) and the Scottish Government (SG). A range of professions was represented, including medical consultants, service managers, academic staff, IT managers, system managers and administrators.

Types of Developmental Data

Table 1 presents information about the type of developmental data recorded by universal childhood information systems in Scotland. Each row represents the data collected for a specific system. The systems presented in table 1 are:

• The Scottish Morbidity Record (SMR) 01 is a universal episode-based record relating to all inpatients and day cases discharged from non-psychiatric, non-obstetric wards in Scottish hospitals (acute hospital admissions). SMR01 contains clinical and non-clinical data including information on locations and transfers, referral types, diagnostic information and operation and procedure information. The patient diagnosis is the only source of data in SMR 01 potentially relevant to childhood development.

• SMR02 is a maternity record for all women receiving inpatient or day case obstetric care. SMR02 is primarily a record of the mother’s care but does include some information about the baby/babies if the record relates to a delivery (ie not an antenatal/postnatal admission). Developmentally relevant data relating to birth recorded on this system include; weight, Apgar scores, neonatal indicators, and feeding on discharge. Neonatal indicator relates to whether the baby was admitted to Special Care Baby Unit. Main obstetric conditions are also recorded on this system.

• The Scottish Birth Record records data on a baby’s neonatal care including readmissions and transfers. The SBR is used differently across Scotland. The ideal is that Boards use this record for all babies as soon as they are born and it then forms the basis of a lifelong electronic health record but in some areas it is only used to record SCBU admissions (within detailed clinical modules). Most NICUs will tend to have their own systems and the SBR is used more as a repository than a working record. The routine data collected that relate to child development will include birth weight and feeding.

• The Child Health Programme is a universal national health promotion programme which feeds into three information systems: the Child Health Systems Programme Pre School (CHSP-PS), the Child Health Systems Programme School (CHSP-S) and the Scottish Immunisation Recall System (SIRS). The CHSP-PS is a call/recall system, which facilitates the process of Child Health Surveillance and records the results of surveillance examinations from shortly after birth until school entry. The Child Health Surveillance Programme School System (CHSP-S) facilitates the call/recall of both primary and secondary school pupils for examination and immunisation. CHSP records referrals and referral updates. Developmental data recorded at specific time points include attainments in fields of motor skills, speech and language, and social skills and behaviour, along with professional or parent concerns about child development. All children are assigned to a model of continuing contact and support according to the assessed need of the family: core, intensive or additional. This is known as the Health Plan Indicator and is also recorded on the CHSP. The SIRS facilitates call/recall of

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children for the routine pre-school immunisations and includes the result of the neonatal bloodspot screening. These data are also held by the Scottish Newborn Screening Laboratory.

• The Strathclyde Education Electronic Management Information System (SEEMIS) is a universal system used to record data about school children. It is now used beyond the former Strathclyde Region – only four Scottish local authorities use alternative systems. As well as six aspects of developmental data, the system records mental health problems, use of English as an additional language, looked after status, whether the child is a “more able pupil”, and school attendance.

• The Nursery Administration System (NAMS) is a module available on the SEEMIS system used for recording attendance rates at nursery schools and centres.

• The Phoenix e1 is a universal system used to record data about school children in four local authority areas (Aberdeen, Highland, Western Isles and Fife). As well as six aspects of developmental data, the system records mental health problems, use of English as an additional language, looked after status, “more able pupil” status, and school attendance.

• Most general practices in Scotland use either EMIS or InPS-VISION systems for managing patient information. These Windows-based systems have the potential to create full electronic records of children’s contact with primary care and any significant problems/diagnoses. Generally these data are only held within the practice and are not analysable across multiple practices without specific agreement from practices to upload information. Some data are extracted anonymously and aggregated for the purpose of the Quality and Outcomes Framework (QOF), a target-based remuneration system for general practices across the UK. There are no specific QOF targets that apply to child well-being and in a substantial number of practices only immunisation data are recorded in an easily retrievable form. Practice Team Information (PTI), based at ISD, collects information from a sample of Scottish general practices about face-to-face consultations (in a surgery or the patient's home) between patients and a member of the practice team. Read-coded PTI data submissions are received from each general practice's clinical IT system on a monthly basis, which for most practices is a fully automatic process. There are several limitations to the information from PTI: lack of prevalence data, inability to provide information about regions and potential skewing of information by characteristics of practices used in the sample. Some methodological and standardisation inconsistencies are evident.

Uses of Developmental Data

Table 2 presents data on how the above systems are used.

• The Scottish Morbidity Record (SMR) 01 record is formed when a patient is discharged from hospital, changes consultant or is transferred to another hospital or hospital department. SMR01 are long standing administrative returns to ISD. They are completed by medical records/coding staff with reference to the clinical notes after the episode of care is completed. Clinicians generally do not play an active role in completion which may in part be responsible for problems with data completeness.

• SMR02 records are formed when a woman is admitted for day care or inpatient care in a maternity hospital. The record is closed when the episode of care is completed. Information on this system is sent to ISD to prepare reports on obstetric services in Scotland. SMR02 are administrative returns to ISD and are processed in similar manner to SMR01.

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• The SBR is used to create a record of the birth as soon as possible after the child is born. The system data are input by health professionals involved in the birth and care of the newborn. Coding staff have a final input to ensure appropriate codes/data quality. Modern systems such as SBR try to extract data for national returns from real time electronic clinical records. The SBR is linked to the Community Health Index (CHI) number which will create a unique CHI for each SBR. The SBR is currently being modified and will in future include newborn hearing screening data.

• The Health Board Child Health Surveillance departments will use birth information to generate a SIRS record and a CHSP-PS record. In some cases the birth information will be a paper-based birth notification form from the maternity hospital whereas other HB areas have reported the use of daily printouts from the electronic Scottish Birth Record. The CHI number and demographic details of the baby are entered onto the SIRS system which then populates the CHSP. A paper copy of the CHSP-PS first visit form will be sent to the HV for the child which will also include consent form for the routine immunisation schedule. After this the routine vaccinations are managed through SIRS.

• Neonatal hearing screening takes place and is recorded in the maternity unit or soon after discharge. Results of the test are primarily recorded on the Northgate e-Screener Plus (eSP) system with paper copies sent to the Health Board Child Health Surveillance department for recording on CHSP-PS. The hearing test is soon to become part of the SBR (see above).

• The newborn bloodspot screening programme tests for indicators of rare but serious conditions including phenylketonuria (PKU) which will effect brain development and cause serious learning disability if left untreated. Blood samples are sent to the Scottish Newborn Screening Laboratory at the RHSC, Yorkhill which returns results directly to the midwife. Population level data are presented in their annual report and requests can be made for anonymous aggregated data for research / evaluation purposes.

• At 10 days postnatally, the public health nurse / health visitor visits the family at home to initiate assessment and service provision, and will record data on child health and social wellbeing. These and other relevant factors are captured as hard codes on the recording sheet and are subsequently input as Read codes. Health Plan Indicator (HPI) may be allocated by HV at this point (CHSP-PS) or later, depending on local practice. Paper copies of the report for this visit are returned to the Health Board Child Health Surveillance department for data input.

• When the child is 6-8 weeks, the HV and GP will receive a CHSP-PS form to record data about child development following an examination and parent interview. Data include whether or not the infant is exhibiting expected gross motor skills, hearing and communication, vision and social awareness as well as anthropometric (weight and height) data. Paper copies are returned to the Health Board Child Health Surveillance department where the data are input and Read coded.

• In accordance with the UK Childhood Immunisation Schedule, at 2, 3, 4, 12-13 and 40-60 months after birth, parents are sent a letter inviting them to bring children to attend their GP practice for immunisation. Paper records of immunisation are sent back to the Health Board Child Health Surveillance department for input into SIRS. Developmental data are not recorded at these times.

• At 2 years, health visitors are sent a list (from the child health surveillance pre-school system) and are asked to verify the HPI for each child. Parents of children in the Core HPI are sent information by post, with parents of children in the Additional or Intensive HPIs being invited to a face-to-face appointment. Any changes to the HPI and major social concerns are recorded

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on a paper form which is returned to Health Board Child Health Surveillance department for input into the CHSP-PS. This form includes recording of whether or not the child has reached expected milestones in various fields of development.

• Vision screening is undertaken by the orthoptist when the child is 4 years old. Paper copies of results are returned to Health Board Child Health Surveillance departments for data input to CHSP-PS.

• In P1 a school nurse or assistant measures children’s height and weight. These data are recorded on the CHSP-S. In some Health Boards, BMI data are aggregated and returned to Community Health Partnerships (CHPs) in order to recruit children with overweight problems to meet the HEAT targets for tackling obesity. For example, in Grampian the parents of all children above the 91st centile will be invited by their CHPs to participate in the “Eat, Play and Grow Well” programme. All children above the 99.6% centile will be referred to a paediatrician.

• At school registration, children are allocated a Scottish Candidate Number (SCN) and their details are entered onto the SEEMIS system in 28 out of 32 Local Authorities. Aggregate data are used by Local Authorities for planning and monitoring. Statistical returns are transmitted to the Scottish Government (ScotXed Unit) via SEEMIS and others transmitted to the Scottish Government using ProcXed.

• The ScotXEd Unit is part of the Education Analytical division within the Scottish Government which utilises the ProcXEd database to produce reports such as the annual Scottish Schools Census. The main benefit for the primary school is the download of information for school handbooks. Secondary schools benefit more from ScotXEd than primary schools because of the availability to secondary schools of Standard Tables and Charts (STACs) which relate to educational attainment.

• In other areas, children are allocated a unique identifier and details are entered onto the Phoenix e1 system. This system is web based and designed to meet the requirements of electronic data-sharing in relation to Getting it Right for Every Child. This system is used in Highland, Western Isles, Fife and Aberdeen City. School clerical and administrative staff, senior management and teachers input information into the secondary school systems. Primary school clerical workers have been trained in the system but not all primary head teachers or primary teachers as yet. Development of the system has been slower in primary schools than in secondary schools. Aggregate data are used by Local Authorities for planning and monitoring but in most cases for workforce statistics. Some data are recorded and reported to the Scottish Government using the ProcXEd database for the purposes of the school census data. The use for primary schools is limited as discussed above.

• Clinical systems have the means to allow rapid data entry e.g. via EMIS Templates, and IN Practice Systems (INPS Vision) Guidelines. These allow data entry in clinical situations, by prompting the clinician to ask questions or examine patients and enter data which are automatically Read Coded, and therefore eliminates the need to remember precise Read Codes. The guidelines operate as an ‘opt-in’ system and many GPs will use alternative ways of accessing the system such as the basic route offered in most training.

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Limitations of the mapping survey

Survey coverage

This report aimed to describe the nature and uses of universal developmental data systems in the early years in Scotland. Whilst we have endeavoured to include all relevant universal systems and any current development plans for these, it is possible that our mapping has not been entirely comprehensive. The findings presented here represent the level of information we were able to obtain in the six months during which the survey was conducted (June – November 2010). It proved difficult in some organisations to identify a key individual to describe accurately their childhood information systems. We also found that different respondents provided different descriptions of the same systems. As far as possible, we tried to validate the findings by cross referencing responses from IT specialists, senior managers and project officers. Any potential loss of information due to the time lag between the original survey and this report has been mitigated where possible by update meetings with key respondents.

Quality of data

Whilst we have endeavoured to describe the systems, the data held within and their application, the quality of the data has not been systematically examined. Where possible we have commented on known issues of data quality and the implications for its use within the relevant sections of the report.

Other data systems

This report focuses on two aspects of large scale national systems: types of developmental data that are recorded and how developmental data are currently being used. There are many more data systems in routine use which are not used nationally, or are not used for the whole population. For example, the systems used within specialist children’s services (e.g., speech and language therapy, audiology, community paediatrics), whilst available to all children should they come into a position of need, only contain data on the minority who are known to these services. Clinicians within such services will need to access data on the children in their care held within other systems, but the extent to which this is possible or happens in practice is variable.

National surveys

There is also a range of national surveys which provide useful data on the wellbeing of the population based on representative sampling. The Growing Up in Scotland cohort study is an obvious example. This study has gathered data on two cohorts of children (one birth cohort and one child cohort) since 2005, and a new birth cohort was instigated in 2010. A range of data is gathered in each sweep, including some developmental data (i.e., the Strengths and Difficulties Questionnaire). The fact that these surveys are not necessarily conducted regularly, do not ask the same questions every sweep, do not include the whole population, and suffer from recruitment / retention bias, means they do not fit within the scope of this report. But they are worthy of mention as they provide an invaluable adjunct to routine data sets, providing detailed information useful in making policy decisions.

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Conclusions and recommendations

The findings of survey demonstrate that:

− There is a range of universal data systems used in health and education sectors where varying levels of developmental data could potentially be recorded. However:

o Most do not routinely record data about developmental measures for children aged 5 and younger. At the CHSP-PS 6-8 week visit a range of developmental measures is recorded, including social awareness / communication. These outcome measures are not monitored until the child reaches primary school. Delays in language development are one of the key predictors of long term development and should be monitored throughout pre-school years to facilitate the provision of effective early interventions (although see ‘Future developments’ below).

o Although systems are universally available, these don’t always achieve universal coverage. There is reasonable evidence to suggest that it is the more vulnerable children who are being missed from these datasets as they are less likely to come into contact with services16. This must be taken into account in interpreting data and subsequent service and policy design.

− Many of the data collected from health and education services are recorded in an electronic format which should allow greater use among service planners and practitioners. However, many of those interviewed reported lack of access as a barrier to using the system in their practice. Improvement in accessible electronic systems, similar to the changes taking place in NHSGGC CHSP-PS systems, should be considered where possible.

− GPs have regular contact with children and good access to information systems. There is however no expectation placed upon GPs to routinely record developmental outcomes for children. Nor is there currently the capacity to mine primary care data in a practical way on a regional or national level. Optimising the utility of primary care data systems must be a priority.

22

Future developments

Child Health Surveillance: 24-30 month contact

The Scottish Government mandated in January 201117 that regional health boards should re-introduce a universal child health review at 24-30 months by April 2013. The policy specified that the new visit should address the key issues of: speech, language and communication skills; personal, social and emotional development (including behavioural issues); nutrition, growth and weight; immunisations; parental concerns and issues; vision, hearing and oral health; and physical activity and play. Detailed guidance on the content and delivery of the review, including specification for a national minimum dataset within the CHSP-PS, has been prepared by a short life working group set up in October 2011 and due to report in Autumn 2012. This is expected to include the recommendation that social, emotional, behavioural and language development is assessed through a combination of structured discussion with the child’s carers and elicitation of any concerns parents have, observation of the child, and the use of validated developmental assessment tools.

Child Health Surveillance: modernisation of systems

NHS Greater Glasgow and Clyde is currently in the process of modernising its local child health surveillance – preschool system, both to reflect the new child health surveillance contact detailed above, and to reflect the recent change to the Health Plan Indicator to only include ‘Core’ and ‘Additional’ de. The latter change has been made with Getting It Right For Every Child (GIRFEC) principles in mind. Due to be fully implemented by the end of 2013, this modernisation will mean that every child health surveillance assessment in the NHSGGC area will be made within the 8 GIRFEC domains, noting both strengths and risk factors, using a linked electronic system.

School Readiness

East Lothian Council, with the Scottish Collaboration for Public Health Research and Policy, has recently undertaken a pilot project testing the feasibility of using the teacher-completed Early Development Instrument (EDI) as a measure of school readiness in school entrants. The EDI was completed for all children in Primary 1 in East Lothian four months after starting school in January 2012. The measure is designed to be used to indicate the school readiness of whole populations of children – data are not analysed or reported at individual child level. The project is currently entering its third phase where qualitative methods will be used to examine the utilisation of the results within the policy-making context. The final phase is planned for 2016 when the data will be collected again in East Lothian, allowing comparisons with the 2012 cohort. Following the development work of this pilot project, the EDI could reasonably be implemented as a comprehensive assessment of children’s wellbeing on a national scale.

Since 2010 Glasgow City Council has used the Strengths and Difficulties Questionnaire (SDQ)18 to assess children’s school readiness. The SDQ was originally designed as a psychiatric screening tool but has subsequently proven to be valid and reliable as a population measure. It is shorter and less comprehensive in scope than the EDI, but nevertheless serves as a useful brief measure of children’s social and emotional wellbeing. A benefit of the SDQ is that it was designed with measurement of the individual child in mind. It can therefore be used to assess the wellbeing of children at both the population and the individual level, although the latter only for the purpose of informing primary one teachers of the profile of their new intake of pupils. Staff in early years establishments in Glasgow City complete the SDQ for their preschool year in the context of the routine transfer documentation in the spring / summer term of the academic year. The use of the

e http://www.scotland.gov.uk/Publications/2011/01/11133654/7

23

SDQ in this context has been largely welcomed by early years establishment staff and qualitative work has helped optimise the system. The SDQ now exists as a module on SEEMIS so is available for any of the 28 local authorities to use in the same way.

Primary Care data

Scottish Clinical Information Management in Practice (SCIMP) are aiming to introduce new Read codes to primary care data systems that will allow GPs to indicate where they have concern for a child as well as when that concern is no longer present. Further, a request is currently being processed for Read codes indicating HPI to be added in order to support interoperability of data with other community-based healthcare workers and social work teams. Finally, a core aim of the Scottish Health Informatics Programme (SHIP) is to set up a data repository for research purposes taking in data from across systems, including primary care. The Highland Research Alliance (UHI, NHS Highland, Albasoft) have been working over the past 18 months to develop an accepted model for a Scottish primary care research repository which is now complete and ready to be piloted. The combination of these developments would improve the routine recording of data on children’s development within primary care systems and capitalise on these data for use in research.

Early Years Collaborative The Scottish Government has recently launched the Early Years Collaborative to ensure that evidence is applied to practice consistently and comprehensively. One of the key aims is to ensure that ‘clear measurement and real-time data is available and acted upon’. To this end an Improvement Advisor has been recruited to support the community planning partnerships in the regular reporting of data, understanding of findings, and the application of these findings to subsequent practice.

Future work (this project)

This report represents the first of three phases of the Childhood Information for Learning and Development (ChILD) project funded by the Scottish Collaboration for Public Health Research and Policy as part of their Early Life Working Group. The research questions for each phase of ChILD are as follows:

1 What is the current status of population-based data collection systems for pre-school child development throughout Scotland at health or education authority and at national level?

What future developments are planned for these systems? 2 Can service development in the interests of pre-school children be influenced by novel

methods of collation of population level data for key stakeholders? 3 Is it possible to develop systems for linking population level data, specifically maternity, child

health surveillance and education data? Are the data sufficiently complete to allow epidemiological investigation?

Phase 2 will involve surveying key stakeholders (those responsible for designing and commissioning children’s services) regarding the findings of Phase 1 and improvements that might be advantageous in their decision making.

Phase 3 will involve the linkage of two research data sets with two of the routinely collected data sets (specifically the SBR and CHSP-PS systems) to assess feasibility and utility.

Phases 2 and 3 will be complete by the end of December 2012 with reports available in Jan 2013.

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References

1. Mensah FK, Kiernan KE. Maternal general health and children's cognitive development and behaviour in the early years: findings from the Millennium Cohort Study. Child: Care, Health and Development 2011; 37(1):44-54.

2. Murray J, Irving B, Farrington DP, Colman I, Bloxsom CA. Very early predictors of conduct problems and crime: results from a national cohort study. Journal of Child Psychology and Psychiatry 2010; 51(11):1198-1207.

3. Geoffroy MC, Côté SM, Giguère C-É, Dionne G, Zelazo PD, Tremblay RE et al. Closing the gap in academic readiness and achievement: the role of early childcare. Journal of Child Psychology and Psychiatry 2010; 51(12):1359-1367.

4. Hertzman C, Siddiqi A, Hertzman E, Irwin LG, Vaghri Z, Houweling TAJ et al. Bucking the inequality gradient through early child development. BMJ 2010; 340:c468.

5. Sinclair A. 0-5: How Small Children Make a Big Difference. Volume 3 number 1. 2007. The Work Foundation. Provocation Series.

6. Bradshaw J, Hoelscher P, Richardson D. An Index of Child Well-being in the European Union. Social Indicators Research 2007; 80(1):133-177.

7. Adamson P, Bradshaw J, Hoelscher P, Richardson D. Child Poverty in Perspective: An overview of child well-being in rich countries, Innocenti Report Card, vol. 7. 2007. Florence, Italy, Unicef Innocenti Research Centre.

8. The Scottish Government. Towards a Mentally Flourishing Scotland: Policy & Action Plan 2009-2011. 2009. 9. The Scottish Government. Better Health, Better Care: Action Plan. 2007. 10. The Scottish Government. The Early Years Framework. 2008. 11. The Scottish Government. Early Years Outcomes and Indicators Framework. 15-3-2011. 10-7-2012. 12. Parkinson J. Establishing a core set of national, sustainable mental health indicators for children and young people

in Scotland: Final Report. 2012. Glasgow, NHS Health Scotland. 13. Centre for Research on Families and Relationships. Using the findings from the Growing Up in Scotland Study to

Inform Policy Development and Service Planning at the Local Level - A Guide for Local Authorities and Health Boards. 2010. Edinburgh, The University of Edinburgh.

14. Wolke D, Waylen A, Samara M, Steer C, Goodman R, Ford T et al. Selective drop-out in longitudinal studies and non-biased prediction of behaviour disorders. British Journal of Psychiatry 2009; 195(3):249-256.

15. Geddes R, Haw S, Frank J. Interventions for Promoting Early Child Development for Health: An environmental scan with special reference to Scotland. Edinburgh : Scottish Collaboration for Public Health Research and Policy; 2010.

16. Wood R, Stirling A, Nolan C, Chalmers J, Blair M. Trends in the coverage of 'universal' child health reviews: observational study using routinely available data. BMJ Open 2012 Mar 28;2(2):e000759.

17. Scottish Government. A New Look at Hall 4 - the Early Years - Good Health for Every Child. 2011. Edinburgh, Scottish Government.

18. Goodman R. The Strengths and Difficulties Questionnaire: a research note. Journal of Child Psychology and Psychiatry 1997; 38(5):581-586.

Acknowledgements: This work would not have been possible without the survey respondents generously giving their time to be interviewed. The ChILD project steering group have provided input both as key respondents in the survey and in guiding the content and style of this report. Thanks also to the Scottish Collaboration for Public Health Research and Policy for providing funding for the work.

25

TABLE 1. TYPES OF DEVELOPMENTAL DATA RECORDED

SYSTEM

DEVELOPMENTAL MEASURES CONCERNS or DIAGNOSES

Hearing Vision Motor skills

Social and emotional

development Language /

communication Health Plan

Indicator Other relevant measures (e.g. feeding, learning

disability)

Professional concerns and/or

diagnosis Parental concerns

SMR01

N N N N N N Reason for admission Main condition, 5 other conditions

coded

N

SMR02

N N N N N N Estimated gestation, birthweight, Apgars, admitted to SCBU, feeding on discharge

Obstetric conditions coded.

N

Scottish Birth Record

N N N N N N Feeding, birthweight, reason for admission to NICU (if relevant)

N N

CHSP P-S: Hearing

Y N N N N N N N N

PHN 1st visit N N N N N Y Feeding Y Y

6-8 week review

Y Y Y Y Y Y Feeding Y Y

Vision N Y N N N N N N N

CHSP-S: P1 screen

N N N N N Y Vision screening not routinely checked now if pre-school screening done.

Y N

P1 assessment

N N Y Y Y Y Vision screening only done for children for whom there are concerns

Y Y

SIRS

N N N N N N Immunisation record, bloodspot screening N N

SEEMIS / NAMS N N N N N N Attendance N N SEEMIS Primary School

Y Y Y Y Y N Mental health problems, learning disability / difficulty / dyslexia, English as additional language,

looked after, more able pupil, attendance

N N

Phoenix e1

Y Y Y Y Y As above N N

EMIS/InPS VISION

N N N N N N Immunisation records. Details of children vary according to system used.

Y Y

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TABLE 2. HOW DEVELOPMENTAL DATA ARE USED

SYSTEM WHERE / WHEN RECORD

GENERATED WHO ENTERS DATA TO

SYSTEMS ACCESS TO INDIVIDUAL

RETURNS ACCESS TO AGREGATE

DATA FUNCTION SMR01

At time of hospital discharge from inpatient care

Medical records/ administrative staff

Medical records/coding staff, ISD DQA staff, NHS board information services teams

ISD specialist intelligence services, NHS board information services teams

Coding staff ensure completion of data and data quality. DQA information is used to report accuracy and coverage of systems. Information from hospitals is submitted to ISD for annual reports such as hospital activity and morbidity monitoring

SMR02

At discharge after admission for an episode of obstetric care

Medical records/ administrative staff

Medical records/coding staff, ISD DQA staff, NHS board information services teams

ISD specialist intelligence services, NHS board information services teams

Coding staff ensure completion of data and data quality. DQA information is used to report accuracy and coverage of systems. Information from Maternity hospitals is submitted to ISD for annual reports such as hospital activity and morbidity monitoring

SCOTTISH BIRTH RECORD

At time of birth in the Maternity Hospital

Clinical staff, (midwives, neonatal, paediatric), administrative staff, and coding staff

Clinical staff, coding staff, administrative staff

ISD specialist intelligence services, Administrative staff, SBR Team

As a clinical system to encourage data collection in real time by clinical staff. Coding staff will code the data entered on the clinical system. Administration staff will act as contact between SBR and site. They can access information from SBR about hospital activity, e.g., generate monthly reports.

CHSP P-S HEARING

In the maternity unit or at home or outpatient clinic soon after discharge

Clinical staff (Audiologist, ENT specialist, screener), administrative staff

Clinical staff, coding staff. ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plan for children with hearing problems. Coding staff at HB Child Health Surveillance use paper record to ensure completion of data and data quality. ISD CHSP collate aggregate data nationally.

CHSP P-S FIRST VISIT

In the child’s home around 10 days after birth

Clinical staff (PHN), administrative staff

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plans. Coding staff at HB Child Health Surveillance use paper record to ensure completion of data and data quality.

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SYSTEM WHERE / WHEN RECORD

GENERATED WHO ENTERS DATA TO

SYSTEMS ACCESS TO INDIVIDUAL

RETURNS ACCESS TO AGREGATE

DATA FUNCTION Data used by HB administrative staff to generate call/recall lists for 2 year checklists or vision screening. ISD CHSP collate aggregate data nationally to produce routine breast feeding reports.

CHSP P-S 6-8 WEEK ASSESS

At PHN clinic and GP practice within 6-8 week of birth.

Clinical staff (PHN/GP). Administrative staff.

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plans. Coding staff at HB Child Health Surveillance use paper record to ensure completion of data and data quality. Data used by HB administration staff to generate call/recall lists for 2 year checklists or vision screening. ISD CHSP collate aggregate data nationally to produce routine breast feeding reports.

CHSP P-S VISION

Early years education establishment

Clinical staff (orthoptist/ school nurse). Administrative staff.

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plans. Coding staff at HB Child Health Surveillance use paper record to ensure completion of data and data quality. ISD CHSP collate aggregate data nationally..

CHSP-S P1 SCREEN.

Primary schools Clinical staff (school nurse). Administrative staff.

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plans. Coding staff at HB Child Health Surveillance use paper record to ensure completion of data and data quality. ISD CHSP collate aggregate data nationally.

CHSP-S P1 ASSESS.

Primary schools Clinical staff (school nurse). Administrative staff.

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Clinical staff use the system to facilitate health plans. Coding staff use paper record to ensure completion of data and data quality. Data used by administrations staff at some HBs to childhood obesity reports. ISD CHSP collate aggregate data nationally to produce routine childhood obesity reports.

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SYSTEM WHERE / WHEN RECORD

GENERATED WHO ENTERS DATA TO

SYSTEMS ACCESS TO INDIVIDUAL

RETURNS ACCESS TO AGREGATE

DATA FUNCTION SIRS

Immunisation clinics Clinical staff (PHN/PN/GP). Administrative staff.

Clinical staff, coding staff, HB administration

ISD Child Health Surveillance programme

Coding staff use paper record to ensure completion of data and data quality. Data used by HB administration staff to generate call/recall lists. ISD CHSP collate aggregate data nationally to produce routine child immunisation reports

SEEMIS/ NAMS Nursery

Nursery Schools Administration staff. Administration staff LA administration staff Nursery administration staff send an electronic copy of the applications NAMS database is sent LA. Used by LA administration staff to monitor demand for nursery places.

SEEMIS Primary School

Primary, and ASL schools. Administration staff. Administration staff LA administration staff, ScotXEd Unit

School administration staff use data for management information purposes and send in electronic format to the LA. LA administration use the data plan and monitor services. Data is used by the ScotXEd to produce the annual Schools census report Pupils in Scotland.

Phoenix e1

Primary schools Primary clerical workers Administration staff LA administration staff, ScotXEd Unit

School administration staff use data for management information purposes and send in electronic format to the LA. LA administration use the data plan and monitor services. Data is used by the ScotXEd to produce the annual Schools census report Pupils in Scotland.

InPS VISION /EMIS

General Practice/Health Centres

Clinical staff (GPs), administration staff.

GPs, administration staff HB administration staff Data used by GPs for clinical purposes to monitor child development and health. Aggregated data on immunisations is returned to SIRS for immunisation payments.

29

Appendix 3: Full univariate analyses from Phase 3

30

ChILD – univariate analyses SMR02 data THM dataset Language delay (n=244) PDHS-I (n=205) RBSQ (n=252)

SIMD (birth) Y

n (%) N

n (%) Mean (SD) Mean (SD)

SIMD1 (most dep) 14 (13.3) 91 (86.7) 41.3 (14.9) 11.76 (5.2) SIMD2 4 (10) 36 (90) 35.4 (8.6) 8.96 (4.2) SIMD3 5 (14.7) 29 (85.3) 32.8 (9.4) 8.61 (4.3) SIMD4 3 (10.7) 25 (89.3) 34.0 (14.7) 8.97 (3.2) SIMD5 (least dep) 1 (2.7) 36 (97.3) χ2=3.69 p=.45 36.9 (12.8) F=4.68 p=.001 9.07 (4.3) F=6.04 P<.001 SDQ dataset (n=3189) Emotional problems Conduct Problems Hyperactivity

SIMD (birth) Mean (SD) Mean (SD) Mean (SD)

SIMD1 (most dep) 1.26 (1.8) 0.81 (1.4) 2.76 (2.6) SIMD2 1.01 (1.6) 0.63 (1.2) 2.66 (2.7) SIMD3 1.20 (1.9) 0.69 (1.3) 2.42 (2.5) SIMD4 0.88 (1.5) 0.57 (1.2) 1.86 (2.3) SIMD5 (least dep) 0.78 (1.5) F=6.16 p=<.001 0.47 (1.0) F=5.19 p=<.001 1.64 (2.3) F=13.43 p=<.001 Peer problems Total Difficulties Prosocial behaviour

SIMD (birth) Mean (SD) Mean (SD) Mean (SD)

SIMD1 (most dep) 1.48 (1.8) 6.31 (5.5) 7.48 (2.5) SIMD2 1.29 (1.8) 5.59 (5.4) 7.60 (2.5) SIMD3 1.37 (1.8) 5.69 (5.4) 7.56 (2.5) SIMD4 1.18 (1.7) 4.49 (4.8) 8.14 (2.5) SIMD5 (least dep) 0.78 (1.3) F=7.99 p=<.001 3.67 (5.4) F=14.83 p=<.001 8.34 (2.2) F=8.1 p=<.001

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THM dataset Language delay PDHS-I RBSQ

SMR02 variables Yes n (%)

No n (%)

N Mean (SD) N Mean (SD)

Smoked in pregnancy? Yes 8 (12.7) 55 (87.3) 50 40.12 (15.2) 65 11.11 (4.95) No 12 (7.8) 142 (92.2) χ2=1.29 p=.28 137 35.56 (11.1) F=4.99 p=.027 160 9.54 (4.6) F=5.05 p=.026 Parity First born 11 (10.1) 98 (89.9) 89 33.4 (9.6) 111 9.96 (4.1)

Subseq birth 16 (11.9) 119 (88.1) χ2=.19 p=.66 116 39.52 (14.3) F=12.2 p=.001 141 10.32 (5.3) F=3.5 p=.56

Mode of delivery NVD 14 (9.7) 130 (90.3) 121 37.7 (13.9) 149 10.1 (4.9) ElCS 6 (21.4) 22 (78.6) 26 37.7 (14.1) 28 10.7 (5.9) EmCS 5 (11.1) 40 (88.9) 34 34.9 (9.3) 47 10.1 (4.5) OthAs 2 (7.4) 25 (92.6) χ2=3.69 p=.29 24 34.4 (9.5) F=.77 p=.51 28 10.0 (3.7) F=.13 p=.94 Neonatal indicator No admit 25 (10.8) 207 (89.2) 194 36.8 (12.9) 237 10.2 (4.7) Admit<48 0 4 (100) 3 44.3 (24.2) 6 11.2 (7.6) Admit>48 2 (25) 6 (75) χ2=2.1 p=.35 8 36.6 (6.4) F=.52 p=.59 9 9.8 (5.2) F=.15 p=.86 Gestation at birth <28wk 0 1 (100) 0 1 4.7 28-36 wk 3 (25) 9 (75) 10 36.4 (11.8) 13 9.7 (5.2) >37 wk 24 (10.4) 207 (89.6) χ2 for trend=1.4 p=.24 195 36.9 (12.9) F=.02 p=.89 238 10.2 (4.8) F=.71 p=.49 Birthweight <1500g 1 (50) 1 (50) 2 29.5 (3.5) 3 4.5 (2.3) 1500-2499g 4 (28.6) 10 (71.4) 10 42.9 (17.6) 15 11.5 (4.1) >2500g 21 (9.3) 204 (90.7) χ2 for trend=8.25 p=.004 190 36.5 (12.5) F=1.5 p=.22 231 10.1 (4.8) F=2.75 p=.066 Mode of feeding on Breast 7 (6.9) 95 (93.1) 87 36.7 (12.5) 103 9.4 (4.2) discharge Formula 12 (10.9) 98 (89.1) 95 37.1 (13.3) 117 10.6 (5.4) Mixed 1 (50) 1 (50) 1 20 2 10.5 (4.5) Other 2 (28.6) 5 (71.4) χ2=7.48 p=.058 7 39.6 (12.9) F=.69 p=.56 7 11.9 (3.9) F=1.39 p=.25

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SDQ dataset Emotional difficulties Conduct problems Hyperactivity

SMR02 variables N Mean (SD) Mean (SD) Mean (SD) Smoked in pregnancy? Yes 603 1.36 (1.95) .95 (1.5) 3.05 (2.7) No 1413 1.07 (1.70) F=14.13 p<.001 .60 (1.1) F=34.07 p<.001 2.33 (2.5) F=33.55 p<.001 Parity First born 1458 1.09 (1.7) .76 (1.3) 2.62 (2.6) Subseq birth 1713 1.21 (1.8) F=3.51 p=.05 .70 (1.2) F=1.83 p=.18 2.54 (2.6) F=.80 p=.37 Mode of delivery NVD 2030 1.18 (1.8) .77 (1.6) 2.69 (2.7) ElCS 314 1.14 (1.8) .68 (1.2) 2.15 (2.4) EmCS 501 1.18 (1.7) .66 (1.2) 2.57 (2.4) OthAs 349 0.97 (1.7) F=1.47 p=.22 .62 (1.2) F=2.14 p=.09 2.32 (2.3) F=5.18 p=.001 Neonatal indicator No admit 2965 1.15 (1.8) .73 (1.3) 2.57 (2.6) Admit<48 57 0.96 (1.5) .56 (1.3) 2.21 (2.1) Admit>48 168 1.24 (1.8) F=.52 p=.59 .77 (1.2) F=.58 p=.56 2.88 (2.5) F=1.69 p=.19 Gestation at birth <28wk 10 1.30 (1.6) 0.80 (1.5) 3.80 (3.5) 28-36 wk 221 1.05 (1.6) 0.64 (1.2) 2.71 (2.5) >37 wk 2963 1.16 (1.8) F=.49 p=.61 0.74 (1.3) F=.60 p=.55 2.56 (2.6) F=1.43 p=.24 Birthweight <1500g 27 1.04 (1.5) 0.56 (1.2) 3.52 (2.9) 1500-2499g 218 1.22 (1.7) 0.83 (1.4) 2.87 (2.6) >2500g 2942 1.15 (1.8) F=.21 p=.81 0.72 (1.3) F=.87 p=.42 2.55 (2.6) F=3.37 p=.03 Mode of feeding on Breast 770 0.98 (1.6) 0.64 (1.2) 2.33 (2.5) discharge Formula 943 1.25 (1.8) 0.74 (1.3) 2.72 (2.6) Not applicable 5 2.20 (3.5) 0 0.80 (0.8) Mixed 34 1.18 (1.9) 0.38 (0.5) 2.91 (2.6) Other 28 0.93 (1.4) F=3.14 p=.014 0.50 (1.0) F=1.79 p=.13 2.04 (2.2) F=3.59 p=.006

33

Peer problems Total difficulties Prosocial behaviour

SMR02 variables N Mean (SD) Mean (SD) Mean (SD) Smoked in pregnancy? Yes 603 1.57 (1.9) 6.95 (6.0) 7.33 (2.5) No 1413 1.31 (1.7) F=8.81 p=.003 5.3 (5.0) F=40.99 p<.001 7.74 (2.4) F=11.75 p=.001 Parity First born 1458 1.33 (1.7) 5.80 (5.4) 7.58 (2.5) Subseq birth 1713 1.42 (1.8) F=2.32 p=.13 5.87 (5.5) F=.14 p=.71 7.61 (2.5) F=.13 p=.72 Mode of delivery NVD 2030 1.46 (1.8) 6.10 (5.6) 7.51 (2.6) ElCS 314 1.19 (1.6) 5.17 (5.2) 7.86 (2.4) EmCS 501 1.33 (1.7) 5.75 (5.1) 7.60 (2.3) OthAs 349 1.08 (1.6) F=6.16 p<.001 5.83 (5.4) F=6.06 p<.001 7.92 (2.3) F=3.85 p=.009 Neonatal indicator No admit 2965 1.37 (1.8) 5.82 (5.5) 7.61 (2.5) Admit<48 57 1.26 (1.8) 5.00 (4.3) 8.28 (1.9) Admit>48 168 1.51 (1.9) F=.61 p=.55 6.39 (5.5) F=1.56 p=.21 7.32 (2.4) F=3.21 p=.04 Gestation at birth <28wk 10 2.80 (2.7) 8.70 (6.9) 7.20 (1.9) 28-36 wk 221 1.27 (1.6) 5.66 (4.7) 7.58 (2.4) >37 wk 2963 1.38 (1.8) F=3.67 p=.026 5.84 (5.5) F=1.50 p=.22 7.61 (2.5) F=.15 p=.86 Birthweight <1500g 27 2.37 (2.3) 7.48 (6.3) 6.89 (2.6) 1500-2499g 218 1.36 (1.7) 6.28 (5.6) 7.48 (2.5) >2500g 2942 1.37 (1.8) F=4.36 p=.01 5.79 (5.4) F=2.04 p=.13 7.62 (2.5) F=1.44 p=.24 Mode of feeding on Breast 770 1.30 (1.7) 5.24 (5.0) 7.73 (2.5) discharge Formula 943 1.40 (1.8) 6.11 (5.4) 7.59 (2.4)

Not applicable 5 1.80 (1.3) 4.80 (4.1) 8.00 (2.3)

Mixed 34 1.47 (1.6) 5.94 (4.9) 6.65 (2.5)

Other 28 1.54 (1.6) F=.56 p=.69 5.00 (4.3) F=3.15 p=.014 7.82 (2.6) F=1.78 p=.13

34

THM dataset

Language delay PDHS-I RBSQ

SMR02 variables Y

Mean (SD) N

Mean (SD) F p

Mother’s age 26.41 (5.4) 28.7 (6.4) 2.67 .10 r=-.047 p=.51

r=-.24 p<.001

Gestation at delivery 38.96 (2.8) 39.2 (1.8) 1.76 .19 r=-.042 p=.55

r=-.055 p=.39

Birthweight 3097.12 (813.6) 3365.60 (562.1) 2.74 .10 r=.044 p=.53

r=-.015 p=.81

APGAR score 9.19 (.56) 9.06 (.83) .11 .74 r=-.026 p=.72

r=.018 p=.78

Occipital frontal circumference 34.34 (1.68) 34.65 (1.92) .22 .64 r=-.014 p=.85

r=-.11 p=.12

35

SDQ dataset

SMR02 variables

Emotional problems

Conduct problems

Hyperactivity Peer problems

Total difficulties

Prosocial behaviour

Mother’s age r=-.048 p=.007

r=-.078 p<.001

r=-.091 p<.001

r=-.047 p=.007

r=-.093 p<.001

r=.064 p<.001

Gestation at delivery r=.005 p=.79

r=.004 p=.83

r=-.041 p=.02

r=-.029 p=.12

r=-.026 p=.14

r=.033 p=.06

Birthweight r=-.001 p=.95

r=.007 p=.71

r=-.046 p=.009

r=-.03 p=.09

r=-.03 p=.09

r=.014 p=.43

APGAR score r=-.024 p=.18

r=-.019 p=.30

r=-.004 p=.82

r=-.004 p=.81

r=-.015 p=.39

r=.025 p=.17

Occipital frontal circumference r=-.002 p=.92

r=-.008 p=.71

r=-.014 p=.51

r=-.022 p=2.9

r=-.016 p=.44

r=-.017 p=.42

36

FV data THM dataset Language delay PDHS-I RBSQ

First visit variables Yes n (%)

No n (%)

n Mean (SD) n Mean (SD)

Mother currently smoking? Yes 6 (9.7) 56 (90.3) 50 40.01 (15.7) 64 11.45 (5.1) No 22 (10.5) 187 (89.5) χ2=.037 p=.85 175 35.21 (11.3) F=5.82 p=.017 215 9.65 (4.6) F=7.21 p=.008 Any parental concerns? Yes 7 (11.9) 52 (88.1) 49 36.39 (12.1) 61 10.21 (4.7) No 21 (9.6) 197 (90.4) χ2=.25 p=.61 180 36.49 (12.8) F=.002 p=.96 224 10.04 (4.9) F=.06 p=.80 Current mode of feeding Breast 7 (6.7) 98 (93.3) 88 35.21 (11.6) 105 9.33 (4.2) Bottle 16 (11.1) 128 (88.9) 118 37.05 (13.3) 152 10.50 (5.2) Mixed 4 (16.0) 21 (84.0) χ2=2.52 p=.28 21 38.54 (13.6) F=.84 p=.43 25 10.91 (4.6) F=2.27 p=.11 HPI at first visit Core 2 (6.7) 28 (93.3) 25 43.22 (14.7) 32 9.57 (3.5) Additional 22 (9.7) 204 (90.3) 189 35.22 (11.7) 232 10.10 (4.9) Intensive 4 (23.5) 13 (76.5) 13 43.48 (16.5) 18 10.88 (5.8) Unknown 0 4 (100) χ2=4.25 p=.24 2 24.00 (1.41) F=5.26 p=.002 3 8.53 (2.8) F=.39 p=.76 SDQ dataset Emotional difficulties Conduct problems Hyperactivity

First visit variables N Mean (SD) Mean (SD) Mean (SD)

Mother currently smoking? Yes 905 1.37 (1.9) .90 (1.4) 3.07 (2.8) No 2414 1.07 (1.7) F=20.08 p<.001 .67 (1.2) F=20.99 p<.001 2.39 (2.5) F=45.13 p<.001 Any parental concerns? Yes 771 1.24 (1.9) .74 (1.3) 2.68 (2.6) No 2633 1.13 (1.7) F=2.50 p=.11 .72 (1.3) F=.05 p=.83 2.55 (2.6) F=1.57 p=.21 Current mode of feeding Breast 965 .91 (1.6) .65 (1.2) 2.14 (2.5) Bottle 2185 1.26 (1.8) .78 (1.3) 2.78 (2.6) Mixed 227 1.1 (1.6) F=12.92 p<.001 .54 (1.0) F=5.77 p=.003 2.52 (2.6) F=20.55 p<.001 HPI at first visit Core 1260 1.04 (1.6) .68 (1.2) 2.32 (2.5) Additional 1791 1.16 (1.8) .70 (1.3) 2.59 (2.6) Intensive 171 1.47 (1.9) 1.08 (1.4) 3.77 (2.9) Unknown 13 1.85 (1.82) 1.54 (1.9) 3.15 (3.2) Pre-Hall 4 166 1.52 (2.2) F=5.06 p<.001 .96 (1.6) F=6.49 p<.001 3.08 (3.1) F=13.84 p<.001

37

Peer problems Total difficulties Prosocial behaviour

First visit variables N Mean (SD) Mean (SD) Mean (SD)

Mother currently smoking? Yes 905 1.54 (1.8) 6.89 (5.8) 7.38 (2.5) No 2414 1.33 (1.7) F=9.07 p=.003 5.47 (5.2) F=45.54 p<.001 7.66 (2.5) F=8.25 p=.004 Any parental concerns? Yes 1.37 (1.8) 6.03 (5.7) 7.56 (2.5) No 1.39 (1.8) F=.13 p=.72 5.79 (5.4) F=1.09 p=.30 7.60 (2.5) F=.14 p=.71 Current mode of feeding Breast 965 1.33 (1.7) 5.03 (5.2) 7.82 (2.5) Bottle 2185 1.40 (1.8) 6.21 (5.6) 7.51 (2.5) Mixed 227 1.47 (1.8) F=.74 p=.48 5.63 (5.2) F=15.83 p<.001 7.50 (2.7) F=5.47 p=.004 HPI at first visit Core 1260 1.28 (1.7) 5.32 (5.1) 7.78 (2.4) Additional 1791 1.38 (1.7) 5.84 (5.4) 7.56 (2.5) Intensive 171 1.77 (2.0) 8.09 (6.5) 6.79 (2.8) Unknown 13 1.85 (1.8) 8.38 (6.9) 7.08 (2.5) Pre-Hall 4 166 1.86 (2.1) F=6.50 p<.001 7.42 (6.8) F=14.56 p<.001 7.27 (2.8) F=7.17 p<.001

38

SIX data THM dataset Language delay PDHS-I RBSQ

Six – eight week check variables Yes n (%)

No n (%) n Mean (SD) n Mean (SD)

Any parental concerns? Yes 6 (13.6) 38 (86.4) 33 33.08 (11.3) 51 9.86 (4.4) No 20 (9.3) 195 (90.7) χ2=.76 p=.41 177 36.73 (12.4) F=2.48 p=.12 216 9.97 (4.9) F=.02 p=.89

Any physical problems? Yes 1 (12.5) 7 (87.5) 3 33.30 (10.7) 8 9.39 (5.9)

No 14 (12.8) 95 (87.2) χ2=.001 p=.98 85 37.92 (12.2) F=.42 p=.52 112 10.69 (4.4) F=.63 p=.43

Current mode of feeding Breast 2 (2.7) 73 (97.3) 60 35.83 (12.3) 75 8.94 (4.3)

Bottle 20 (12.9) 135 (87.1) 126 36.30 (12.7) 163 10.31 (5.0)

Mixed 4 (13.8) 25 (86.2) χ2=6.37 p=.04 24 36.19 (10.5) F=.03 p=.97 29 10.53 (4.1) F=2.41 p=.09

Observed problem: gross motor Normal 22 (8.9) 224 (91.1) 201 36.34 (12.3) 254 9.97 (4.7)

Doubtful / uncertain 2 (50) 2 (50) 3 24.33 (4.0) 4 6.47 (5.0)

Abnormal 0 0 0 - 0 -

Not done / incomplete 2 (22.2) 7 (77.8) χ2=8.88 p=.01 6 35.98 (11.1) F=1.42 p=.25 9 10.77 (5.3) F=1.2 p=.30

Observed problem: hearing Normal 23 (9.3) 223 (90.7) 202 36.21 (12.4) 254 9.92 (4.8)

Doubtful / uncertain 0 0 0 - 1 17.78

Abnormal 0 0 0 - 0 -

Not done / incomplete 2 (16.7) 10 (83.3) χ2=9.68 p=.008 8 34.76 (10.2) F=.11 p=.75 12 9.95 (4.8) F=1.36 p=.26

Observed problem: vision Normal 22 (8.9) 224 (91.1) 200 36.10 (12.3) 253 9.84 (4.7)

Doubtful / uncertain 1 (50) 1 (50) 1 25.00 2 19.29 (12.3)

Abnormal 0 0 0 - 0 -

Not done / incomplete 3 (27.3) 8 (72.7) χ2=7.5 p=.02 9 38.65 (13.2) F=.60 p=.55 12 10.74 (4.4) F=4.19 p=.02

HPI at 6-8 week check Core 3 (6.5) 43 (93.5) 43 35.53 (10.3) 50 8.71 (4.5)

Additional 20 (10.2) 176 (89.8) 155 35.77 (12.4) 200 10.01 (4.7)

Intensive 3 (18.8) 13 (81.3) 11 45.56 (14.95) 16 13.10 (5.4)

Unknown 0 1 (100) 1 20.00 1 8.42

Pre-Hall 4 0 0 χ2=2.09 p=.55 0 - F=2.89 p=.04 F=3.61 p=.01

39

SDQ dataset Emotional problems Conduct problems Hyperactivity

Six – eight week check variables N Mean (SD) Mean (SD) Mean (SD)

Any parental concerns? Yes 659 1.23 (1.9) .66 (1.2) 2.50 (2.6) No 2445 1.11 (1.7) F=2.36 p=.12 .71 (1.3) F=.94 p=.33 2.54 (2.6) F=.14 p=.71 Any physical problems? Yes 142 0.99 (1.7) 0.85 (1.4) 2.92 (2.9) No 1183 1.15 (1.7) F=1.16 p=.28 0.87 (1.4) F=.04 p=.85 3.13 (2.7) F=.73 p=.39 Current mode of feeding Breast 633 0.84 (1.5) .56 (1.1) 2.05 (2.5) Bottle 2199 1.22 (1.8) .75 (1.3) 2.70 (2.6) Mixed 258 1.16 (1.7) F=12.08 p<.001 .64 (1.2) F=5.85 p=.003 2.33 (2.6) F=16.77 p<.001 Observed problem: gross motor Normal 2958 1.12 (1.7) 0.68 (1.2) 2.51 (2.6) Doubtful / uncertain 44 0.80 (1.6) 1.09 (1.4) 2.98 (2.7) Abnormal 4 2.00 (2.5) 2.50 (3.1) 4.25 (3.7) Not done / incomplete 93 1.73 (2.4) F=4.55 p=.003 1.04 (1.5) F=6.76 p<.001 3.16 (2.8) F=2.93 p=.03 Observed problem: hearing Normal 2997 1.12 (1.7) 0.69 (1.2) 2.51 (2.6) Doubtful / uncertain 10 0.20 (0.4) 0.30 (0.7) 3.00 (2.1) Abnormal 0 - - - Not done / incomplete 92 1.68 (2.4) F=6.07 p=.002 1.10 (1.5) F=5.27 p=.005 3.32 (2.9) F=4.46 p=.01 Observed problem: vision Normal 2965 1.12 (1.7) 0.69 (1.2) 2.50 (2.6) Doubtful / uncertain 31 1.26 (1.8) 1.10 (1.4) 3.42 (2.8) Abnormal 2 0 0 0 Not done / incomplete 101 1.50 (2.2) F=1.80 p=.15 1.01 (1.5) F=3.43 p=.02 3.21 (2.9) F=4.24 p=.005 HPI at 6-8 week check Core 1054 0.99 (1.6) 0.62 (1.2) 2.25 (2.4) Additional 1784 1.18 (1.8) 0.70 (1.3) 2.57 (2.6) Intensive 169 1.44 (1.9) 1.12 (1.5) 3.69 (3.0) Unknown 8 2.75 (2.4) 1.00 (1.4) 3.25 (2.9) Pre-Hall 4 82 1.40 (2.1) F=5.61 p<.001 0.82 (1.3) F=6.08 p<.001 3.05 (2.9) F=12.77 p<.001

40

Peer problems Total difficulties Prosocial behaviour

Six – eight week check variables N Mean (SD) Mean (SD) Mean (SD)

Any parental concerns? Yes 659 1.34 (1.7) 5.73 (5.3) 7.64 (2.4) No 2445 1.38 (1.8) F=.25 p=.62 5.74 (5.5) F=.01 p=.95 7.62 (2.5) F=.03 p=.87 Any physical problems? Yes 142 1.13 (1.6) 5.88 (5.7) 7.44 (2.5) No 1183 1.45 (1.9) F=3.8 p=.05 6.60 (5.8) F=1.96 p=.16 7.10 (2.6) F=2.21 p=.14 Current mode of feeding Breast 633 1.31 (1.7) 4.76 (5.1) 7.95 (2.5) Bottle 2199 1.38 (1.8) 6.06 (5.5) 7.53 (2.5) Mixed 258 1.45 (1.8) F=0.60 p=.55 5.57 (5.5) F=14.26 p<.001 7.55 (2.5) F=6.95 p=.001 Observed problem: gross motor Normal 2958 1.36 (1.8) 5.67 (5.4) 7.65 (2.5) Doubtful / uncertain 44 1.07 (1.8) 5.93 (5.6) 6.95 (2.6) Abnormal 4 3.75 (3.3) 12.5 (12.1) 3.50 (4.0) Not done / incomplete 93 1.70 (2.0) F=3.98 p=.008 7.63 (6.8) F=6.04 p<.001 7.31 (2.6) F=5.35 p=.001 Observed problem: hearing Normal 2997 1.36 (1.8) 5.69 (5.4) 7.64 (2.5) Doubtful / uncertain 10 1.20 (1.5) 4.70 (2.9) 7.70 (2.1) Abnormal 0 - - - Not done / incomplete 92 1.60 (1.8) F=.83 p=.44 7.70 (6.7) F=6.31 p=.002 7.14 (2.8) F=1.78 p=.17 Observed problem: vision Normal 2965 1.36 (1.8) 5.68 (5.4) 7.64 (2.5) Doubtful / uncertain 31 2.10 (2.2) 7.87 (5.9) 6.84 (2.8) Abnormal 2 0 0 9.50 (0.7) Not done / incomplete 101 1.44 (1.8) F=2.23 p=.08 7.15 (6.3) F=4.75 p=.003 7.24 (2.8) F=2.29 p=.08 HPI at 6-8 week check Core 1054 1.28 (1.7) 5.14 (5.1) 7.87 (2.4) Additional 1784 1.34 (1.7) 5.79 (5.3) 7.57 (2.5) Intensive 169 1.97 (2.2) 8.22 (6.7) 6.98 (2.7) Unknown 8 3.75 (2.2) 10.75 (5.9) 6.75 (2.6) Pre-Hall 4 82 1.74 (2.0) F=10.42 p<.001 7.01 (6.3) F=15.18 p<.001 7.01 (2.9) F=7.26 p<.001