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    Developing cancer quality of life assessment tools

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    Using Quality of Life (QoL) as a patient reported outcome relies upon good quality assessment tools. This chapter will consider the basic foundations and principles to guide development. The importance of creating the rationale for development and planning the development process are highlighted. The key stages in the development process are discussed including the generation of QoL items, construction and piloting/pre-testing an assessment tool. Other issues are briefly considered e.g., moving from development into validation, alongside other areas such as translation, electronic applications and modern measurement approaches. The wider context including the importance of collaboration with multidisciplinary experts and patient involvement are highlighted in developing robust QoL assessment tools

    The impact of jejunostomy feeding on nutritional outcomes after oesophagectomy

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    Background: Nutritional status is compromised long-term following oesophagectomy. Controversy surrounds the optimal route for nutrition support post-operatively, and there is wide variation in the use of feeding jejunostomy tubes.Methodology: A retrospective service evaluation was conducted for all consecutive adults who underwent oesophagectomy for a cancer diagnosis within a specialist centre between April 2016 and July 2019 (n=165). Nutritional and clinical outcomes were compared for patients who received jejunostomy feeding (n=24) versus those who did not (n=141).Results: Patients with feeding jejunostomy lost significantly less weight at both 6 and 12 months post-operatively compared to those without jejunostomy (p=Conclusion: Use of short-term supplementary jejunal feeding in addition to oral intake after hospital discharge is beneficial for maintaining weight after oesophagectomy. We suggest a future randomised-controlled trial to confirm these findings.</p

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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