Conclusions
Systematic reviews of complex behaviour change interventions in
healthcare may include a heterogeneous set of studies in terms of
content, context, trial design and setting. The measures of behaviour
change may also vary which leads to difficulty in attempts to synthesise
the data, as well as increased heterogeneity.
In this paper we have presented 4 different methods for combining
behavioural outcome measures from trials, described the strengths and
weaknesses of each method, and the problems inherent with combining
heterogeneous outcome measures with mixed levels of clustering. Each of
the methods presented has advantages and disadvantages, summarised in
table 4, and we recommend that reviewers chose their methods carefully
based on the needs of their review, and plan methods and data conversion
policies in advance to avoid selective reporting. We observed that for
our data, conclusions would remain robust regardless of the methods of
analysis chosen; however the estimated magnitude of the treatment effect
varied quite markedly according to the method chosen. We view the
methods presented as useful when trying to convert all outcome measures
to the same scale and to provide an overall summary, but results should
be interpreted extremely cautiously given the limitations. We would
recommend that results are used as an aid in summarising the evidence
and generating future hypotheses rather than to infer future effects.