Critical Overview Of The Study Issues Of Trial Quality

While this work concluded that CBT is an effective treatment, improvement to the design and conduct of treatment trials can be made. For example, we concluded that most trials were statistically underpowered and that some trials were overcomplex with multiple treatment and control groups. The content and differentiation of control groups from treatment requires more consideration. Patients assigned to a waiting list in one trial may continue to receive existing treatments that may be equivalent to the treatment control in another trial. The distinction between the content of an active treatment and a control condition can be a fine one. Allocation to a control condition will have different psychological consequences from allocation to an active treatment, even if that treatment is based on predominantly non-psychological principles, e.g. physical therapy. There was variation in quality and quantity of treatment given. Some authors gave explicit accounts of the treatment procedures with reference to manualized interventions which were appropriately monitored, but this was not universally so. We also noted a paucity of information about the impact of CBT on economically important outcomes.

We have sought to quantify the quality of trials by developing a quality scale (QS) designed specifically for complex psychological treatments. Most published quality scales evaluate important biases (e.g. compromised randomization), but some of these are not applicable to psychological treatments. The extant quality scales pay scant attention to important aspects of treatment administration. Yates et al.49 obtained consensus agreement on the desirable content of a QS from a set of experts. The final scale contained items measuring both methodological quality and the quality of treatment implementation. Studies were carried out to assess the scale's reliability and validate its use and these provided formal evidence of our conclusions about trial quality. Yates et al. also examined six more recently published trials and the analysis indicated that the quality of trials appears to be improving. Future meta-analysis of trials will be able to examine the influence of overall trial quality and of specific features, for example duration of treatment, on outcome. Furthermore, more advanced statistical analysis that can incorporate the complexities of trial design (multiple trial arms and multiple outcomes) will circumvent some of the compromises made in the original meta-analysis.

Finally, trialists are beginning to report outcomes as the proportion of patients showing clinical improvement on a given variable, rather than a mean difference score. The main method for this is the application of the reliable change index and clinically significant change criteria50,5152 to dichotomize continuous measures using the statistical and normative properties of the outcome measure. Although this approach is not free of problems, it enables researchers to express outcomes in terms that might be more widely understood.25

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