Power

As numbers within a study increase so does the precision of results, enabling important but subtle differences to be detected, if they do indeed exist. Should a new treatment be considerably better than its predecessors few people would have to be randomized in order to demonstrate clearly the advantage of the innovative approach. As the advantage expected of new treatments is usually modest, reasonably large studies are often needed.

The power calculation is an important prerequisite for any randomized trial. For example, if clinical observation suggests that a new treatment can help 20 per cent more people avoid admission than the standard care, this can form the basis for a power calculation for a trial. Using a simple formula (3) the trialist can work out how many people would have to be randomized in order to have a known probability of highlighting such a difference, should one really exist. In this case, about 150 people would have to be allocated to each arm of the trial to be reasonably confident of detecting a true 20 per cent difference (a = 0.05, b = 0.8). Most mental health trials are far too small to show up anything but very gross differences between treatments. For example, the average number of participants in schizophrenia trials is 65 and this has not changed over time.(4)

A single small trial should not greatly influence the clinician, but the combined results of several small studies may begin to have the power to inform practice. Biases

Randomization attempts to control for the biases that would influence treatment allocation (selection biases). Blinding at outcome attempts to control for biases that would result from participants or raters knowing which treatment had been allocated to whom (observer bias). Inadequate randomization leads to an overestimate of effect in the region of 31 to 40 per cent, and poor blinding at outcome to that of about 17 per cent. (5) Further overestimate results from the use of unpublished or modified scales, commonly seen in mental health studies, and a financial or academic investment in the therapy by the trialists. (6)

There are many threats to the validity of a single trial. Viewing all relevant studies, each of which was subject to different degrees of bias, should give a more balanced picture. Of course, the reader of a review should be vigilant for the systematic bias, across all trials, that may consistently sway results one particular direction.

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