Publications by authors named "C G Semple"

Introduction: After treatment for head and neck cancer (HNC), up to 90% of patients have difficulties eating and drinking. Despite the enormity of challenges explicitly relating to the social dimension of eating, there are limited extant interventions to specifically support social eating, nor any replicable for use in contemporary clinical practice. This study aims to plan, develop and optimise a self-management intervention to promote social eating for patients living with and beyond HNC.

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Background: Families are often unsure how best to prepare dependent children for the death of a significant caregiver with a poor cancer prognosis and seek guidance and support from health care teams. Health and social care professionals (hereafter referred to as professionals) often lack educational opportunities to gain the desired knowledge, skills, and confidence to provide family-centered supportive cancer care. e-Learning has positively impacted access and reach, improving educational opportunities in health care.

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Purpose: Health and social care professionals (professionals) often lack knowledge, skills and confidence to support adults at end of life with significant caregiving responsibilities for children, < 18. A recent systematic review highlighted a dearth of educational interventions (n = 2) to equip professionals to provide supportive care to families when a parent has cancer. Addressing an evident gap in education, this paper details the adaption and optimisation of a face-to-face educational intervention to an accessible eLearning resource.

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Background: Children and young people living with severe obesity experience a range of complications of excess weight (CEW); however the prevalence of complications is not well defined. We have evaluated baseline characteristics and CEW of patients from two UK tier 3 paediatric weight management services.

Methods: All new patients aged 2-17 years seen from March 2022 to February 2023 were included.

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Advances in protein structure determination and modeling allow us to study the structural context of human genetic variants on an unprecedented scale. Here, we analyze millions of cancer-associated missense mutations based on their structural locations and predicted perturbative effects. By considering the collective properties of mutations at the level of individual proteins, we identify distinct patterns associated with tumor suppressors and oncogenes.

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