Objective: To outline the importance of the clarity of data analysis in the doing and reporting of interview-based qualitative research. Approach:We explore the clear links between data analysis and evidence.We argue that transparency in the data analysis process is integral to determining the evidence that is generated. Data analysis must occur concurrently with data collection and comprises an ongoing process of 'testing the fit' between the data collected and analysis. We discuss four steps in the process of thematic data analysis: immersion, coding, categorising and generation of themes. Conclusion: Rigorous and systematicanalysis of qualitative data is integral to the production of high-quality research.Studies that give an explicit account of the data analysis process provide insights into how conclusions are reached while studies that explain themes anchored to data and theory produce the strongest evidence.

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Reassurance of the "worried well"-anxious patients with symptoms or patients concerned by a health query resulting from a routine medical examination or from screening-constitutes a large part of medical practice. It seems to be widely assumed that explaining that tests have shown no abnormality is enough to reassure. The results of this study refute this and emphasise the importance of personal and social factors as obstacles to reassurance.

Objective: To highlight the importance of sampling and data collection processes in qualitative interview studies, and to discuss the contribution of these processes to determining the strength of the evidence generated and thereby to decisions for public health practice and policy.Approach: This discussion is informed by a hierarchy-of-evidence-for-practice model. Pu bl i c h e a l t h r e s e a r c h u s i n g qualitative methods produces studies that can range from an exploratory study with modest implications for practice to well-developed, generalisable studies. The contribution that a study can make to public health practice and policy rests on several core features of sound qualitative research. In common with other empirical studies, qualitative research starts by justifying the research problem by reference to the literature. Qualitative research then defines a theoretical framework for the study, identifying the theoretical concepts that are relevant and will be employed in the study.1 The next step is to collect data according to a sampling plan, following which there is the analysis of data and reporting of research findings.2 In this paper, our focus is on sampling and data collection.There are inconsistencies and gaps in the literature regarding appropriate appraisal of qualitative research. 3 We propose that sampling and data collection are critical to determining the quality of a study. We use the underlying model of a hierarchy of evidencefor-practice 3 to discuss the role of sampling and data collection in determining the strength of the evidence for decisions made in practice or policy settings. This has particular relevance as a guide for researchers seeking publication and reviewers of submitted articles, given recent concerns about the quality of qualitative papers being submitted for publication. 4 One of the biggest problems noted was the lack of information provided about sampling, providing little opportunity Methods Article

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