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      A randomized controlled trial comparing parent child interaction therapy - toddler, circle of security– parenting™ and waitlist controls in the treatment of disruptive behaviors for children aged 14–24 months: study protocol

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          It is common for toddlers to display disruptive behaviors (e.g., tantrums, aggression, irritability) but when these become severe and persistent they can be the start of a trajectory towards poor outcomes in childhood and adolescence. Parent Child Interaction Therapy - Toddler is an intervention model designed to meet the specific developmental needs of toddlers aged 12–24 months presenting with disruptive behaviors.


          This study will use a randomized controlled design to evaluate the efficacy of the Parent Child Interaction Therapy - Toddler intervention for children aged 14–24 months with disruptive behaviors. Ninety toddlers with parent-reported disruptive behavior will be randomly allocated to either Parent Child Interaction Therapy - Toddler, Circle of Security– Parenting™ or a waitlist control group. Key parenting capacity outcome variables will include positive and negative parenting, parenting sensitivity, parental sense of competence in managing negative toddler emotions, parent sense of caregiving helplessness, parent mentalizing about the child, parent emotion regulation, child abuse potential and parental stress. Key outcome variables for children will include child social-emotional functioning (initiative, relationship functioning, self-regulation), child emotion regulation, child attachment security, and child behavior.


          Delivered in the early intervention period of toddlerhood, Parent Child Interaction Therapy - Toddler has the potential to bring about significant and lasting changes for children presenting with early onset behavioral issues.

          Trial registration

          Australian New Zealand Clinical Trials Registry (ANZCTR), 12618001554257. Registered 24 September 2018 – retrospectively registered.

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          Most cited references 40

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          Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort.

          If most adults with mental disorders are found to have a juvenile psychiatric history, this would shift etiologic research and prevention policy to focus more on childhood mental disorders. Our prospective longitudinal study followed up a representative birth cohort (N = 1037). We made psychiatric diagnoses according to DSM criteria at 11, 13, 15, 18, 21, and 26 years of age. Adult disorders were defined in the following 3 ways: (1) cases diagnosed using a standardized diagnostic interview, (2) the subset using treatment, and (3) the subset receiving intensive mental health services. Follow-back analyses ascertained the proportion of adult cases who had juvenile diagnoses and the types of juvenile diagnoses they had. Among adult cases defined via the Diagnostic Interview Schedule, 73.9% had received a diagnosis before 18 years of age and 50.0% before 15 years of age. Among treatment-using cases, 76.5% received a diagnosis before 18 years of age and 57.5% before 15 years of age. Among cases receiving intensive mental health services, 77.9% received a diagnosis before 18 years of age and 60.3% before 15 years of age. Adult disorders were generally preceded by their juvenile counterparts (eg, adult anxiety was preceded by juvenile anxiety), but also by different disorders. Specifically, adult anxiety and schizophreniform disorders were preceded by a broad array of juvenile disorders. For all adult disorders, 25% to 60% of cases had a history of conduct and/or oppositional defiant disorder. Most adult disorders should be reframed as extensions of juvenile disorders. In particular, juvenile conduct disorder is a priority prevention target for reducing psychiatric disorder in the adult population.
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            Sensitivity and Attachment: A Meta-Analysis on Parental Antecedents of Infant Attachment

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              Financial cost of social exclusion: follow up study of antisocial children into adulthood.

              To compare the cumulative costs of public services used through to adulthood by individuals with three levels of antisocial behaviour in childhood. Costs applied to data of 10 year old children from the inner London longitudinal study selectively followed up to adulthood. Inner London borough. 142 individuals divided into three groups in childhood: no problems, conduct problems, and conduct disorder. Costs in 1998 prices for public services (excluding private, voluntary agency, indirect, and personal costs) used over and above basic universal provision. By age 28, costs for individuals with conduct disorder were 10.0 times higher than for those with no problems (95% confidence interval of bootstrap ratio 3.6 to 20.9) and 3.5 times higher than for those with conduct problems (1.7 to 6.2). Mean individual total costs were 70 019 pounds sterling for the conduct disorder group (bootstrap mean difference from no problem group 62 pound sterling; 898 pound sterling 22 692 pound sterling to 117 pound sterling) and 24 324 pound sterling (16 707 pound sterling; 6594 pound sterling to 28 149 pound sterling) for the conduct problem group, compared with 7423 pound sterling for the no problem group. In all groups crime incurred the greatest cost, followed by extra educational provision, foster and residential care, and state benefits; health costs were smaller. Parental social class had a relatively small effect on antisocial behaviour, and although substantial independent contributions came from being male, having a low reading age, and attending more than two primary schools, conduct disorder still predicted the greatest cost. Antisocial behaviour in childhood is a major predictor of how much an individual will cost society. The cost is large and falls on many agencies, yet few agencies contribute to prevention, which could be cost effective.

                Author and article information

                BMC Psychol
                BMC Psychol
                BMC Psychology
                BioMed Central (London )
                31 August 2020
                31 August 2020
                : 8
                [1 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, School of Psychiatry, , University of New South Wales, ; P.O. Box 241, Villawood, NSW 2163 Australia
                [2 ]Karitane, Carramar, NSW Australia
                [3 ]GRID grid.429098.e, Ingham Institute for Medical Research, ; Liverpool, NSW Australia
                [4 ]GRID grid.1004.5, ISNI 0000 0001 2158 5405, Macquarie University, ; Ryde, NSW Australia
                [5 ]GRID grid.1022.1, ISNI 0000 0004 0437 5432, Griffith University, ; Gold Coast, QLD Australia
                [6 ]GRID grid.410692.8, ISNI 0000 0001 2105 7653, South Western Sydney Local Health District, ; Liverpool, Australia
                [7 ]GRID grid.1005.4, ISNI 0000 0004 4902 0432, Mark Wainwright Analytical Centre, , University of New South Wales, ; Kensington, NSW Australia
                [8 ]Families In Mind Psychology, Canberra, Australia
                [9 ]GRID grid.268154.c, ISNI 0000 0001 2156 6140, West Virginia University, ; Morgantown, WV USA
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funded by: UNSW-Karitane Academic Partnership
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                © The Author(s) 2020


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