Andrew Booth

BACKGROUND AND OBJECTIVES: The expansion of evidence-based practice across sectors has lead to an increasing variety of review types. However, the diversity of terminology used means that the full potential of these review types may be lost amongst a confusion of indistinct and misapplied terms. The objective of this study is to provide descriptive insight into the most common types of reviews, with illustrative examples from health and health information domains. METHODS: Following scoping searches, an examination was made of the vocabulary associated with the literature of review and synthesis (literary warrant). A simple analytical framework -- Search, AppraisaL, Synthesis and Analysis (SALSA) -- was used to examine the main review types. RESULTS: Fourteen review types and associated methodologies were analysed against the SALSA framework, illustrating the inputs and processes of each review type. A description of the key characteristics is given, together with perceived strengths and weaknesses. A limited number of review types are currently utilized within the health information domain. CONCLUSIONS: Few review types possess prescribed and explicit methodologies and many fall short of being mutually exclusive. Notwithstanding such limitations, this typology provides a valuable reference point for those commissioning, conducting, supporting or interpreting reviews, both within health information and the wider health care domain.

BACKGROUND: Implementation fidelity refers to the degree to which an intervention or programme is delivered as intended. Only by understanding and measuring whether an intervention has been implemented with fidelity can researchers and practitioners gain a better understanding of how and why an intervention works, and the extent to which outcomes can be improved. DISCUSSION: The authors undertook a critical review of existing conceptualisations of implementation fidelity and developed a new conceptual framework for understanding and measuring the process. The resulting theoretical framework requires testing by empirical research. SUMMARY: Implementation fidelity is an important source of variation affecting the credibility and utility of research. The conceptual framework presented here offers a means for measuring this variable and understanding its place in the process of intervention implementation.

Standardized systematic search strategies facilitate rigor in research. Current search tools focus on retrieval of quantitative research. In this article we address issues relating to using existing search strategy tools, most typically the PICO (Population, Intervention, Comparison, Outcome) formulation for defining key elements of a review question, when searching for qualitative and mixed methods research studies. An alternative search strategy tool for qualitative/mixed methods research is outlined: SPIDER (Sample, Phenomenon of Interest, Design, Evaluation, Research type). We used both the SPIDER and PICO search strategy tools with a qualitative research question. We have used the SPIDER tool to advance thinking beyond PICO in its suitable application to qualitative and mixed methods research. However, we have highlighted once more the need for improved indexing of qualitative articles in databases. To constitute a viable alternative to PICO, SPIDER needs to be refined and tested on a wider range of topics.

The GRADE-CERQual ('Confidence in the Evidence from Reviews of Qualitative research') approach provides guidance for assessing how much confidence to place in findings from systematic reviews of qualitative research (or qualitative evidence syntheses). The approach has been developed to support the use of findings from qualitative evidence syntheses in decision-making, including guideline development and policy formulation. Confidence in the evidence from qualitative evidence syntheses is an assessment of the extent to which a review finding is a reasonable representation of the phenomenon of interest. CERQual provides a systematic and transparent framework for assessing confidence in individual review findings, based on consideration of four components: (1) methodological limitations, (2) coherence, (3) adequacy of data, and (4) relevance. A fifth component, dissemination (or publication) bias, may also be important and is being explored. As with the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach for effectiveness evidence, CERQual suggests summarising evidence in succinct, transparent, and informative Summary of Qualitative Findings tables. These tables are designed to communicate the review findings and the CERQual assessment of confidence in each finding. This article is the first of a seven-part series providing guidance on how to apply the CERQual approach. In this paper, we describe the rationale and conceptual basis for CERQual, the aims of the approach, how the approach was developed, and its main components. We also outline the purpose and structure of this series and discuss the growing role for qualitative evidence in decision-making. Papers 3, 4, 5, 6, and 7 in this series discuss each CERQual component, including the rationale for including the component in the approach, how the component is conceptualised, and how it should be assessed. Paper 2 discusses how to make an overall assessment of confidence in a review finding and how to create a Summary of Qualitative Findings table. The series is intended primarily for those undertaking qualitative evidence syntheses or using their findings in decision-making processes but is also relevant to guideline development agencies, primary qualitative researchers, and implementation scientists and practitioners.

Reviewing the literature is an essential part of every research project. This book takes you step-by-step through the process of approaching your literature review systematically, applying systematic principles to a wide range of literature review types. Through numerous examples, case studies and exercises, the book covers often neglected areas of literature review such as concept analysis, scoping and mapping--Jacket.