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Using intervention trials in developmental psychiatry to illuminate basic science

  • Jonathan Green (a1) and Graham Dunn (a2)

Summary

We discuss the nature of intervention in developmental psychiatry and the implication of this for clinical trials. New ideas in the design of randomised trials for complex interventions, along with recent statistical advances in causal analysis, give such trials additional potential as a means by which to study the basic science of complex developmental disorders. The challenge for designers of trials is to model designs effectively to make best use of these new opportunities. We give examples of how this might be done and discuss implications for future trials designs in the area.

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Copyright

Corresponding author

Jonathan Green, Room 4.319, 4th Floor (East), University Place, University of Manchester, Oxford Road, Manchester M13 9PL, UK. Email: jonathan.green@manchester.ac.uk

Footnotes

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Declaration of interest

None.

Funding detailed in Acknowledgements.

Footnotes

References

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1 Green, J. The evolving randomised controlled trial in mental health: studying complexity and treatment process. Adv Psychiatr Treat 2006; 12: 268–79.
2 Medical Research Council. A Framework for Development and Evaluation of RCTs for Complex Interventions to Improve Health. MRC, 2000 (http://www.mrc.ac.uk/Utilities/Documentrecord/index.htm?d=MRC003372).
3 Howe, GW, Reiss, D, Yuh, J. Can prevention trials test theories of etiology? Dev Psychopathol 2002; 14: 673–94.
4 Bloom, HS. Learning More from Social Experiments. Russell Sage Foundation, 2005.
5 Angrist, JD, Imbens, GW, Rubin, DB. Identification of causal effects using instrumental variables (with discussion). J Am Stat Assoc 1996; 91: 444–72.
6 Dunn, G & Bentall, R. Modelling treatment-effect heterogeneity in randomised controlled trials of complex interventions (psychological treatments). Stat Med 2007; 26: 4719–45.
7 Kraemer, HC, Fairburn, CG, Agras, WS. Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry 2002; 59: 877–83.
8 Baron, RM & Kenny, DA. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986; 51: 1173–82.
9 Kazdin, AE, Whitley, M. (2006) Pre-treatment social relations, therapeutic alliance and improvements in parenting practices in parent management training. J Consult Clin Psychol 2006; 74: 345–55.
10 Green, JM. The therapeutic alliance – a significant but neglected variable in child mental health treatment studies. J Child Psychol Psychiatry 2006; 47: 425–35.

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Using intervention trials in developmental psychiatry to illuminate basic science

  • Jonathan Green (a1) and Graham Dunn (a2)
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eLetters

Re: "SEM in developmental psychiatry"

Jonathan Green, Professor of Child and Adolescent Psychiatry
23 September 2008



Sir

We thank Dr MacFarlane for his favourable comments on our views. The development of research designs that can rigorously test the complexities of mental health intervention and also have face validity to clinicians is at the centre of our concern. In a brief editorial we could do no more than whet the readers' appetites. There was no mention of structural equation modelling because of lack of space, and not because we do not have sympathies with the technique. In fact, one of us (GD) has taught structural equation modelling (SEM) for nearly twenty years (see Dunn, Everitt & Pickles, 1993). When used wisely and with correctly specified models, SEM approaches can be very powerful - but they do not obviate the need for good design (including the randomisation in an RCT). In particular, the correspondent is mistaken when he suggests that the use of SEM (MIMIC) models can successfully address issues of hidden confounding in the absence of appropriate design. Although enthusiasts in the social and behavioural scientists have used 'structural equations models' and 'causal models' interchangeably for many years, their naïvety has frequently brought SEM into disrepute. Pearl's book covers the structural modelling in the appropriate way, but many readers of this journal will find it a bit heavy going. We do indeed plan to publish on these issues in much greater detail in the near future.



Prof Jonathan GreenProf Graham DunnUniversity of Manchester

REFERENCEDunn, G., Everitt, B & Pickles, A. (1993). Modelling Covariances and Latent Variables Using EQS. London: Chapman and Hall.

DECLARATION OF INTERESTG.D. is a member of the UK Mental Health Research Network (MHRN) Methodology Research Group. Methodological research funding for both GD and JG is provided by the UK Medical Research Council (grant numbers G0600555/ G0401546). No other interest to declare.
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"SEM in developmental psychiatry"

Don MacFarlane, Consultant in CAMHS
03 September 2008

The paper, 'Using intervention trials in developmental psychiatry to illuminate basic science', by Green,J. and Dunn,G. (BJP, Vol.192,5, May2008) may prove to be of merit in the interpretation of causal relationships between interventions and outcomes. In particular, the recommendation that RCT methodology should be embedded within statistical methods from observation studies is long overdue. Such an approach would greatly assist in the interpretation of results which seem completely counterintuitive to those in everyday clinical practice. One such result is the finding of S.Byford, B.Barret et.al.(BJP,Dec 2007, 191, 521 - 527) that CBT provides no added or separate advantage to SSRIs in the treatmentof adolescent depression.

I have a quibble with the length of time it has taken for basic concepts on causality introduced by Green and Dunn to appear in psychiatric research. These concepts have been commonplace in social science research for more than twenty years and their section on Causal Inference in Analysis is little more than a primer. For a more complete coverage of principles of causality, I can recommend Judea Pearl's book,'Causality: Models, Reasoning and Inference'.

Is there any particular reason why Green and Dunn, having put their toes in the water by introducing basic concepts on causality, have not taken their paper further or are we to await a follow-up? In particular, why is there no mention of SEM (structural equation modelling), otherwise known as covariance structure analysis? SEM has been extensively used in social science research for the past 20 years and adaptations of the method such as MIMIC seem to address the issues on confounding variables adequately without the need to revert to RCT methodology. It would be interesting to hear from Green and Dunn their thoughts as to how necessarywould RCT methods be in developmental psychitry research whenever an SEM model is being employed.
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Conflict of interest: None Declared

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