{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T11:13:14Z","timestamp":1780657994154,"version":"3.54.1"},"reference-count":43,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T00:00:00Z","timestamp":1776729600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["804752"],"award-info":[{"award-number":["804752"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["J intellect Disabil Res"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Children with developmental disabilities show a high prevalence of behaviours that challenge (BtC). Thus, harnessing known risk markers to target early intervention to children at the greatest risk of BtC is essential. In this study, machine learning techniques were used to develop prediction models of risk (no, low and high severity behaviour) for different BtC (self\u2010injurious behaviour, aggression, property destruction, \u2018any BtC\u2019). A secondary aim was to assess the external validation of these models to predict future behaviour.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Method<\/jats:title>\n                    <jats:p>\n                      Caregivers of individuals with developmental disabilities completed the Self\u2010injury, Aggression and Destruction Screening Questionnaire. One dataset (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009778) was used to train and test models to establish internal validation. Algorithms were created using random forest classifiers, K\u2010nearest neighbours, multiple logistic regressions and Gaussian mixture models (GMM) for each type of behaviour. External validation utilising a second dataset of caregivers (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009121) completing the SAD\u2010SQ at baseline and 12\u2009months later was then conducted.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Outcomes<\/jats:title>\n                    <jats:p>\n                      Across internal and external validation, the random forest classifiers and GMM algorithms for\n                      <jats:italic>any BtC<\/jats:italic>\n                      showed the highest number of correct classifications with fair to good recall and precision, with 83.5% of people at risk of BtC correctly predicted. Predictions of persistence and incidence of behaviour over 12\u2009months was also good (83.5% and 83.3%, respectively).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Interpretation<\/jats:title>\n                    <jats:p>The novel prediction models showed the ability to predict BtC for children with developmental disabilities. Such models have applicability to clinical practice to inform provision of early preventative interventions for BtC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jir.70105","type":"journal-article","created":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T11:30:27Z","timestamp":1776771027000},"page":"700-708","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Development and Validation of Models of Risk for Behaviours That Challenge in Children With Developmental Disabilities: A Novel Machine Learning Approach"],"prefix":"10.1111","volume":"70","author":[{"given":"Laura","family":"Groves","sequence":"first","affiliation":[{"name":"School of Psychology University of Birmingham  Birmingham UK"},{"name":"Birmingham and Solihull Mental Health NHS Foundation Trust  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guy","family":"Davies","sequence":"additional","affiliation":[{"name":"School of Physics and Astronomy University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chris","family":"Oliver","sequence":"additional","affiliation":[{"name":"School of Psychology University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Debbie","family":"Allen","sequence":"additional","affiliation":[{"name":"School of Education &amp; Psychology in the Faculty of Education, Health, &amp; Wellbeing University of Wolverhampton  Wolverhampton UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlie","family":"Bamford","sequence":"additional","affiliation":[{"name":"Wolverhampton and Sandwell CAMHS Black Country Healthcare NHS Foundation Trust  Wolverhampton UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Louise","family":"Bell","sequence":"additional","affiliation":[{"name":"Sefton Community Learning Disabilities Team Mersey Care NHS Foundation Trust  Southport UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chloe","family":"Brown","sequence":"additional","affiliation":[{"name":"Adult Learning Disabilities Community Health Team South West Yorkshire Partnership NHS Foundation Trust  Wakefield UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vivian","family":"Cooper","sequence":"additional","affiliation":[{"name":"The Challenging Behaviour Foundation  Chatham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Louise","family":"Daniel","sequence":"additional","affiliation":[{"name":"Specialist Assessment Service, University Hospitals Birmingham NHS Foundation Trust Chelmsley Wood Primary Care Centre  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9268-0581","authenticated-orcid":false,"given":"Jo","family":"Garstang","sequence":"additional","affiliation":[{"name":"Birmingham Community Healthcare NHS Foundation Trust; Birmingham School of Nursing University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chris","family":"Jones","sequence":"additional","affiliation":[{"name":"School of Psychology University of Birmingham  Birmingham UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4950-0768","authenticated-orcid":false,"given":"Joseph\u00a0P.","family":"McCleery","sequence":"additional","affiliation":[{"name":"Department of Psychology &amp; Kinney Center for Autism Education and Support Saint Joseph's University  Philadelphia Pennsylvania USA"},{"name":"Center for Autism Research Children's Hospital of Philadelphia  Philadelphia Pennsylvania USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3825-225X","authenticated-orcid":false,"given":"Ashley","family":"Liew","sequence":"additional","affiliation":[{"name":"National &amp; Specialist CAMHS South London &amp; 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