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The Treatment of Child Anxiety in Primary Care (T-CAP) via Guided CBT Self-Help: a randomised controlled trial

Dates: 2012-2015
Funding: National Institute for Health Research (NIHR)
 Collaborators: Dr Cathy Creswell, School of Psychology, University of Reading
 Information: Mara Violato

Anxiety disorders are common in childhood and they lead to emotional and social disturbances later on. Cognitive Behavioural Treatments (CBT) for anxious children are generally successful, but only a minority of children in need have access to this treatment. It is thus logical to look for alternative and less costly ways of dealing with child anxiety. One potential route to cost-effective care is a stepped care approach, which involves offering a simple first level CBT treatment, followed by referring non-responders to specialist care.

There is evidence that CBT treatment delivered through parents is effective in reducing child anxiety. Similarly, there is evidence that CBT-based self-help manuals for parents of children with other psychological difficulties are an effective way of delivering treatment. Thus, self-help treatment via parents is a promising first line approach for the treatment of childhood anxiety problems. There is only limited research, however, into the effectiveness of self help manuals for parents of anxious children.

The proposed study is a Randomised Controlled Trial to evaluate the efficacy and cost-effectiveness of guided CBT self-help for child anxiety within Primary Child and Adolescent Mental Health Services (PCAMHS) across Oxfordshire. Participants, parents of clinically anxious children aged 5-12 years, will be randomly allocated to either the guided CBT self-help condition or PCAMHS standard care (i.e. Solution Focused Brief Therapy, SFBT) in order to establish whether the guided CBT self-help approach offers benefits in comparison to the intervention families usually receive within PCAMHS. The study will assess whether guided CBT self-help delivers improved outcomes (i.e., reduction of symptoms) in comparison to standard care; whether these differences are maintained six months post-treatment, and whether self-help significantly lowers the costs associated with child anxiety.

Health Economic Assessment

The economic analysis will estimate the incremental cost and effectiveness of guided CBT self-help in relation to standard care. Patient level resource use data, including all health and social care costs (staff costs, GP costs, referrals, and other relevant services identified) as well as leisure and productivity estimates for parents, will be collected within trial forms (such as Client Service Receipt Inventory (CSRI) – Children’s version’ - Knapp et al. 1999) and valued using appropriate unit costs. Staff training costs and the costs of staff supervision will be identified and allocated pro-rata. The outcome measures for the cost-effectiveness analyses will be the improvement status (CGI-I; much/very much improved or not), a measure of ‘days off school avoided’; a generic quality of life assessed using the child friendly EuroQol EQ-5D (Hennessy and Kind, 2002); the Child Health Utility 9D (CHU9D), the new paediatric, preference-based measure of health related quality of life (Stevens 2009, 2010, 2011); a proxy version of the CHU9D which is intended for self complete by the parent/guardian. These instruments will be administered at baseline, following treatment, and at 6 month follow up.

Consideration of the distribution of the cost and effect data will be given in the economical analysis. In order to explore the variation around the costs and effects generated by the trial data stochastic variance around the cost-effect pairs will be estimated using non-parametric bootstrapping methods. Allowance for differential timing of costs and benefits will be made using recommended discount rates. The incremental cost and the incremental benefits (effectiveness and utility) will be reported within an incremental cost-effectiveness ratio (ICER) format where appropriate. The results for the cost-effectiveness analyses will be expressed in terms of positioning on the cost-effectiveness plane as well as translated into cost-effectiveness acceptability curves, indicating the likelihood that the results fall below any given cost-effectiveness ceiling ratio (Rc).