Objective The aim of the present review was to examine epidemiological evidence to determine if there is strong evidence of a positive gradient of increasing physical activity across the socio-economic strata, and how relationships are affected by socio-economic measurement. Design Systematic review. Method A search of major databases was conducted to identify published studies that reported physical activity in relation to socio-economic position (SEP) in adults. Results Twenty-eight cross-sectional and five longitudinal studies met the inclusion criteria. Approximately half of these were American. Consequently education and income were most commonly used to represent SEP. The majority of studies were secondary analyses of existing health survey data, which could explain the generally large sample sizes and methodological weaknesses in physical activity and SEP measurement. There was consistent evidence of a higher prevalence or higher levels of leisure-time or moderate-vigorous intensity physical activity in those at the top of the socio-economic strata compared with those at the bottom. Evidence for positive gradients across the socio-economic strata was less consistent. Education produced the most stable relationships, less susceptible to confounding effects of ethnicity and the environment. Conclusion Those at the top of the socio-economic scale appear to perform more leisure-time activity than those at the bottom. Diverse and often crude physical activity and socio-economic measurement made it difficult to distinguish between artefact and true effect in a relationship with so many potential confounding influences. Further studies using up-to-date methods of socio-economic and physical activity measurement are necessary to further explore this relationship and its confounders.

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This paper discusses the challenges of how to provide a transparent account of the use of the software programme QSR*NVIVO (QSR 2000) within a Grounded Theory framework (Glaser and Strauss 1967;Strauss and Corbin 1998). Psychology students are increasingly pursuing qualitative research projects such to the extent that the UK Economic and Social Research Council (ESRC) advise that students should have skill in the use of computer assisted qualitative data analysis software (CAQDAS) (Economic and Social Research Council 2001). Unlike quantitative studies, rigid formulae do not exist for writing-up qualitative projects for doctoral theses. Most authors, however, agree that transparency is essential when communicating the findings of qualitative research. Sparkes (2001) recommends that evaluative criteria for qualitative research should be commensurable with the aims, objectives, and epistemological assumptions of the research project. Likewise, the use of CAQDAS should vary according to the research methodology followed, and thus researchers should include a discussion of how CAQDAS was used. This paper describes how the evolving process of coding data, writing memos, categorising, and theorising were integrated into the written thesis. The structure of the written document is described including considerations about restructuring and the difficulties of writing about an iterative process within a linear document.Keywords: Grounded Theory, CAQDAS, QSR NVIVO, computer, structure, writing, Qualitative Research Solutions, International (QSR) has developed two product lines for qualitative data analysis. The original programme, NUD*IST, which stands for Nonnumerical Unstructured Data, Indexing, Searching, and Theorising, was first created by Professors Lyn and Tom Richards in the early 1980s when the former was looking for more efficient ways to manage her data than the chaotic task of photocopying, cutting, highlighting, and filing interviews and coding by hand. It is also difficult to conduct complex searches of the data without the assistance of a computer. Tom Richards, a computer scientist, created the answer to her problem by creating NUD*IST, a programme that was easy to use, organised data, allowed for links between the data, allowed for detailed memos to be added to the documents or coding, and enabled complex searching of the text and coding. QSR NUD*IST VIVO (NVIVO's less commonly used full name) was first produced in 1999 and was designed to provide the same services as NUD*IST but in a much more refined way. It was named for 'in vivo' coding, that is, naming a category directly from a participant's own words. The programme facilitates naming in this way but does not require it.With the development of CAQDAS has come debate about the appropriateness of using computers to analyse qualitative data (see for example, Catterall and Maclaran 1997; Use of NVIVO in GT Study 4

This study used grounded theory to describe the emotional responses of athletes following injury and their situational and temporal contexts. Sixteen seriously injured athletes were interviewed. The NUD*IST (Nonnumerical Unstructured Data Indexing Searching and Theorizing) computer program was used to search, store, explore, and organize the qualitative material. The main emotional responses, appraisals, events, and behaviors that emerged from the analysis were represented diagrammatically. Frustration and depression were the prevalent emotional responses throughout rehabilitation, although the situational corollaries differed as recovery progressed. In the early phase of rehabilitation, frustration and depression resulted from disruption to normal function, in the middle phase they were provoked by a negative appraisal of rehabilitation progress, and. at the end of rehabilitation the main instigator was impatience to return to sport. Whether to risk returning prematurely to sport emerged as a key theme, as did the confounding effects of exercise withdrawal. symptoms in extremely committed athletes. The results were considered in terms of both cognitive appraisal and risk models.

This review critically examines Transtheoretical Model (TTM)-based interventions for physical activity (PA) behavior change. It has been suggested that the TTM may not be the most appropriate theoretical model for applications to PA behavior change. However, previous reviews have paid little or no attention to how accurately each intervention represents the TTM. Findings comprise two sections: sample characteristics of each intervention reviewed and a summary outlining the use of the TTM to develop the interventions. Results reveal numerous inconsistencies regarding the development and implementation/application of TTM-based interventions. Specifically, the majority of interventions reported to be based on the TTM fail to accurately represent all dimensions of the model. Therefore, until interventions are developed to accurately represent the TTM, the efficacy of these approaches and the appropriateness of the underpinning theoretical model cannot be determined.