Professional-identity and self-concept appear to have an impact on practice in a research delivery role. Further research should explore these issues further, to enlighten the basis on which such feelings are positioned and to work towards practical solutions.
Nurse-led research and innovation is key to improving health experiences and outcomes and reducing health inequalities. Clinical academic training programmes for nurses to develop research and innovation skills alongside continued development of their clinical practice are becoming increasingly established at national, regional and local levels. Though widely supported, geographical variation in the range and scope of opportunities available remains. It is imperative that clinical academic opportunities for nurses continue to grow to ensure equity of access and opportunity so that the potential of nurse-led clinical academic research to improve quality of care, health experience and health outcomes can be realised. In this paper, we describe and report on clinical academic internship opportunities available to nurses to share internationally, a range of innovative programmes currently in operation across the UK.Examples of some of the tangible benefits for patients, professional development, clinical teams and NHS organisations resulting from these clinical academic internships are illustrated. Information from local evaluations of internship programmes was
INTRODUCTION: Chronic constipation is classified into 2 main syndromes, irritable bowel syndrome with constipation (IBS-C) and functional constipation (FC), on the assumption that they differ along multiple clinical characteristics and are plausibly of distinct pathophysiology. Our aim was to test this assumption by applying machine learning to a large prospective cohort of comprehensively phenotyped patients with constipation. METHODS: Demographics, validated symptom and quality of life questionnaires, clinical examination findings, stool transit, and diagnosis were collected in 768 patients with chronic constipation from a tertiary center. We used machine learning to compare the accuracy of diagnostic models for IBS-C and FC based on single differentiating features such as abdominal pain (a "unisymptomatic" model) vs multiple features encompassing a range of symptoms, examination findings and investigations (a "syndromic" model) to assess the grounds for the syndromic segregation of IBS-C and FC in a statistically formalized way. RESULTS: Unisymptomatic models of abdominal pain distinguished between IBS-C and FC cohorts near perfectly (area under the curve 0.97). Syndromic models did not significantly increase diagnostic accuracy (P > 0.15). Furthermore, syndromic models from which abdominal pain was omitted performed at chancelevel (area under the curve 0.56). Statistical clustering of clinical characteristics showed no structure relatable to diagnosis, but a syndromic segregation of 18 features differentiating patients by impact of constipation on daily life. DISCUSSION: IBS-C and FC differ only about the presence of abdominal pain, arguably a self-fulfilling difference given that abdominal pain inherently distinguishes the 2 in current diagnostic criteria. This suggests that they are not distinct syndromes but a single syndrome varying along one clinical dimension. An alternative syndromic segregation is identified, which needs evaluation in community-based cohorts. These results have implications for patient recruitment into clinical trials, future disease classifications, and management guidelines.
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