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      Explaining local variation in referrals from health services to children’s social care in England 2013–16: a study using ‘children in need’ administrative data

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          Abstract

          Background

          Referral rates from Health service to Children’s Social Care (CSC) services vary across England. In 2019, the National Audit Office (re)iterated the urgent need to understand the drivers of such variation.

          Methods

          Using administrative data (Children in Need Census, 2013–16), we calculated annual referral rates from Health to CSC services (Health referral rate) by Local Authority (LA) areas. We used multilevel linear regression to investigate the relationship between age-adjusted Health referral rates and local need (demand factors) and local practice/systems (supply factors). We present a tool to compare unadjusted and adjusted LA rates.

          Results

          There was high LA variation in Health referral rates, particularly for infants (mean = 29.0/1000 children < 1 y; range = 6.5–101.8; sd = 12.4). LA variation persisted after age-adjustment. Child poverty (local need) and overall referral rate (local practice/systems) explained 60% of variation in age-adjusted Health referral rates. Overall referral rate was the strongest predictor. Adjusted referral rates were substantially different from unadjusted rates. After adjustment, 57.7% of LAs had higher/lower Health referral rates than expected.

          Conclusions

          While higher levels of local need are associated with higher Health referrals, some areas have high Health referrals irrespective of local need. Our tool demonstrates the benefits of using adjusted rates to compare LAs.

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          Most cited references26

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

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              Burden and consequences of child maltreatment in high-income countries.

              Child maltreatment remains a major public-health and social-welfare problem in high-income countries. Every year, about 4-16% of children are physically abused and one in ten is neglected or psychologically abused. During childhood, between 5% and 10% of girls and up to 5% of boys are exposed to penetrative sexual abuse, and up to three times this number are exposed to any type of sexual abuse. However, official rates for substantiated child maltreatment indicate less than a tenth of this burden. Exposure to multiple types and repeated episodes of maltreatment is associated with increased risks of severe maltreatment and psychological consequences. Child maltreatment substantially contributes to child mortality and morbidity and has longlasting effects on mental health, drug and alcohol misuse (especially in girls), risky sexual behaviour, obesity, and criminal behaviour, which persist into adulthood. Neglect is at least as damaging as physical or sexual abuse in the long term but has received the least scientific and public attention. The high burden and serious and long-term consequences of child maltreatment warrant increased investment in preventive and therapeutic strategies from early childhood.
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                Author and article information

                Contributors
                Role: Teaching Fellow in Biological Anthropology, UCL Anthropology
                Role: Research Officer, Rees Centre, University of Oxford
                Role: Senior Lecturer, UCL Great Ormond Street Institute of Child Health
                Role: Lecturer in Child and Family Policy, Thomas Coram Research Unit, UCL Institute of Education
                Journal
                J Public Health (Oxf)
                J Public Health (Oxf)
                pubmed
                Journal of Public Health (Oxford, England)
                Oxford University Press
                1741-3842
                1741-3850
                March 2021
                18 June 2019
                18 June 2019
                : 43
                : 1
                : 180-188
                Affiliations
                [1 ] UCL Anthropology , University College London, 14 Taviton Street, London, UK
                [2 ] Rees Centre for Research in Fostering and Education , Department of Education, University of Oxford, 15 Norham Gardens, Oxford, UK
                [3 ] UCL Great Ormond Street Institute of Child Health , University College London, 30 Guildford Street, London, UK
                [4 ] Thomas Coram Research Unit , UCL Institute of Education, University College London, 27–28 Woburn Square, London, UK
                Author notes
                Corresponding author: emily.emmott@ 123456ucl.ac.uk
                Author information
                http://orcid.org/0000-0003-4862-179X
                http://orcid.org/0000-0002-3418-2856
                http://orcid.org/0000-0002-9403-4177
                Article
                fdz050
                10.1093/pubmed/fdz050
                8042370
                31211394
                a220a451-a38e-418a-ab8b-351b500fc551
                © The Author(s) 2019. Published by Oxford University Press on behalf of Faculty of Public Health.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 27 June 2018
                : 13 March 2019
                : 24 April 2019
                Page count
                Pages: 9
                Funding
                Funded by: Academy of Medical Sciences, DOI 10.13039/501100000691;
                Award ID: HOP001/1021
                Funded by: Wellcome Trust, DOI 10.13039/100010269;
                Award ID: HOP001/1021
                Award ID: 103975/Z/14/Z
                Funded by: NIHR, DOI 10.13039/501100000272;
                Award ID: ES/L007517/1
                Funded by: Economic and Social Research Council, DOI 10.13039/501100000269;
                Award ID: ES/L007517/1
                Funded by: Administrative Data Research Centre for England;
                Categories
                AcademicSubjects/MED00860
                Original Article

                Public health
                Public health

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