The application of complex interventions in the area of public health, clinical research and education is becoming increasingly widespread. The effectiveness of complex interventions may be affected by numerous factors due to the complexity of interventions, intervention pathways or the context of implementation. Therefore, it is significantly important to evaluate the process of complex interventions, which will provide information to understand the implementation of interventions. The British Medical Research Council’s process evaluation guidelines provide a framework for implementing and reporting on process evaluation research. This paper aims to interpret the guide in detail on complex intervention and process evaluation for the references of domestic researchers.
As a tool for building consensus among groups, Delphi technique has been widely used in healthcare research which is appropriate for clinical questions where quantitative methods are unlikely to yield results that can be successfully implemented in practice. Researchers in palliative care developed standards for conducting and reporting Delphi studies (CREDES). This paper introduces and interprets the specific content of CREDES standards, with a view to providing reference for the evaluation of Delphi research design quality and report transparency.
The level of evidence in randomized controlled studies is high. However, it cannot be widely applied due to its high cost, external authenticity, ethics and other reasons. The traditional observational studies reduce the internal authenticity due to various confounding factors, and the level of evidence is low. Regression discontinuity design (RDD) is a design that observes and compares outcome of object around the threshold under practical clinical conditions. Its capability to adjust confounding factors is second only to that of randomized control studies. It can be used in cases where the intervention (or exposure) is directly related to the value of a continuous variable. For instance, whether an HIV patient needs antiretroviral treatment mainly depends on whether the CD4 cell count is lower than 200/μL. Because the measurement of continuous variables has random error, whether intervention is given near the threshold or is close to random, the baseline of patients in the intervention group and non-intervention group near the threshold should be balanced and comparable. Based on this assumption, the causal effect of intervention (or exposure) and outcome can be estimated by comparing the outcomes of populations near the threshold. RDD is mainly applicable to the study of classification outcomes in medicine, among which two-stage least square method, likelihood ratio based estimation method and Bayesian method are more commonly used model estimation methods. However, the application conditions of RDD and the requirement of sample size limit its extensive application in medicine. With the improvement of data accessibility and the development of real world research, RDD will be more widely used in clinical research.
Mixed methods research (MMR) is the third research paradigm that combines quantitative and qualitative research. MMR can overcome limitations of qualitative and quantitative methods by integrating the advantages of these two. The environment of real world research is complicated. When using real world data to assess the health status of patients, process of treatment, outcomes of prevention and treatment, prognosis and prediction, and support for medical policy development, MMR can be applied to tackle research questions more comprehensively for the quality of research.