Combining adjusted and unadjusted findings in mixed research synthesis

Abstract

Finding ways to incorporate disparate types of evidence into research syntheses has the potential to build a better evidence base for clinical practice and policy. Yet conducting such mixed research synthesis studies is challenging. Researchers have to determine whether and how to use adjusted and unadjusted quantitative findings in combination with each other and with qualitative findings. Among quantitative findings, adjustment for confounding, either via study design or statistical analysis, can be a considerable source of heterogeneity. Yet there is no consensus about the best way to synthesize findings resulting from different methods for addressing confounding. When synthesizing qualitative and quantitative findings, additional considerations include determining whether findings are amenable to synthesis by aggregation or configuration, which, in turn, depends on the degree of interpretive transformation of findings. Qualitative survey findings appear similar in form to unadjusted or minimally adjusted quantitative findings and, when addressing the same relationship, can be summed. More interpreted qualitative findings appear similar in form to adjusted findings found in, for example, structural equation models specifying the relationship among a host of latent variables. An option for synthesis of conceptually similar models is reciprocal translation. These decisions will ultimately be judged on the meaningfulness of their results to practice or policy.