Editorial: the power of treatment studies to explore causal processes in childhood disorders.
We all have a tendency to be easily seduced by Occam's razor, or the desire to accept the simplest hypothesis to explain a given phenomenon. If we observe that children with ADHD come from more impoverished backgrounds or have diets that contain more additives than their peers, then a parsimonious theory would be that poverty and/or diet are causal factors in the development of ADHD. Such theories are all the more attractive because they suggest potential targets for intervention: improve family circumstances and child diet and symptoms of ADHD should diminish. Of course in reality untangling causal relationships is much more complicated. We now accept that many common disorders reflect the confluence of genetic and environmental risk factors, but that any given risk factor is likely to account for only a tiny amount of explained variance in symptom profile. What's more, in order to fulfil the promise of intervention, we must begin to unravel the precise mechanisms by which identified risk factors affect the developing system. This issue showcases two key methodologies for understanding causal influences on developmental disorders: longitudinal designs and well-controlled intervention studies. Both may employ statistical techniques that can identify the mediators of observed associations, elucidating potential mechanistic processes.
D001289:Attention Deficit Disorder with Hyperactivity / Q000209:etiology / Q000628:therapy; D015984:Causality; D002648:Child; D002658:Developmental Disabilities / Q000209:etiology / Q000628:therapy*; D006801:Humans
Causal influences; developmental disorders; mechanism of action; mediators of change; response to treatment