Health professionals, their medical interventions and uncertainty : a study focusing on women at midlife

Health professionals face a tension between focusing on the individual and attending to health issues for the population as a whole. This tension is intrinsic to medicine and gives rise to medical uncertainty, which here is explored through accounts of three medical interventions focused on women at midlife: breast screening, hormone replacement therapy and bone densitometry. The accounts come from interviews with UK health professionals using these medical interventions in their daily work. Drawing on the analysis of Fox [(2002). Health and Healing: The public/private divide (pp. 236–253). London: Routledge] we distinguish three aspects of medical uncertainty and explore each one of them in relation to one of the interventions. First is uncertainty about the balance between the individual and distributive ethic of medicine, explored in relation to breast screening. Second is the dilemma faced by health professionals when using medicial evidence generated through studies of populations and applying this to individuals. We explore this dilemma for hormone replacement therapy. Thirdly there is uncertainty because of the lack of a conceptual framework for understanding how new micro knowledge, such as human genetic information, can be combined with knowledge of other biological and social dimensions of health. The accounts from the bone denistometry clinic indicate the beginnings of an understanding of the need for such a framework, which would acknowledge complexity, recognising that factors from many different levels of analysis, from heredity through to social factors, interact with each other and influence the individual and their health. However, our analysis suggests biomedicine continues to be dominated by an individualised, context free, concept of health and health risk with individuals alone responsible for their own health and for the health of the population. This may continue to dominate how we perceive responsibilities for health until we establish a conceptual framework that recognises the complex interaction of many factors at macro and micro level affecting health

Online Health Recommendation System: A Social Support Perspective

Online Health Communities (OHC) aim to support patients through offer them the opportunities to exchange support with others. However, patients have difficulties and problems locating expertise within the online health communities. In this regard, this study aims to create a patient recommender system to help users locate those with relevant experience and similar health status. Specifically, we aim to leverage the type of online social support users seek to determine the patient health status to build a patient status prediction model. Building the model will help create a peer recommendation system for online support group members to easily locate peers and build a sustainable online health community. Building this type of recommendation system will help patients to effectively interact with other patients who have same health status. Moreover, it will help online health communities in improving the services provided, which in turn will be reflected positively on patient’s health status

Factors influencing ICU referral at the end of life in the elderly

Referral to the intensive care unit (ICU) and frequency of do-not-resuscitate (DNR) decisions at the end of life (EOL) in adult hospitalized patients a parts per thousand yen75 years and those < 75 years were examined and influencing factors in the elderly were determined. Data were prospectively collected in all adult patients who deceased during a 12-week period in 2007 and a 16-week period in 2008 at a university hospital in Belgium. Overall, 330 adult patients died of whom 33% were a parts per thousand yen75 years old. Patients a parts per thousand yen75 years old were less often referred to ICU at the EOL (42% vs. 58%, p=0.008) and less frequently died in the ICU (31% vs. 46%, p=0.012) as compared to patients < 75 years old. However, there was no difference in frequency of DNR decisions (87% vs. 88%, p=0.937) for patients dying on non-ICU wards. After adjusting for age, gender, and the Charlson comorbidity index, being admitted on a geriatric ward (OR 0.30, 95% CI 0.10-0.85, p=0.024) and having an active malignant disease (OR 0.39, 95% CI 0.19-0.78, p=0.008) were the only factors associated with a lower risk of dying in the ICU. Patients a parts per thousand yen75 years are less often referred to the ICU at the EOL as compared to patients < 75 years old. However, the risk of dying in the ICU was only lower for elderly with cancer and for those admitted to the geriatric ward

Unsolicited written narratives as a methodological genre in terminal illness: challenges and limitations

Stories about illness have proven invaluable in helping health professionals understand illness experiences. Such narratives have traditionally been solicited by researchers through interviews and the collection of personal writings, including diaries. These approaches are, however, researcher driven; the impetus for the creation of the story comes from the researcher and not the narrator. In recent years there has been exponential growth in illness narratives created by individuals, of their own volition, and made available for others to read in print or as Internet accounts. We sought to determine whether it was possible to identify such material for use as research data to explore the subject of living with the terminal illness amyotrophic lateral sclerosis/motor neuron disease—the contention being that these accounts are narrator driven and therefore focus on issues of greatest importance to the affected person. We encountered and sought to overcome a number of methodological and ethical challenges, which is our focus here

A corpus based, lexical analysis of patient information for radiography

Despite the importance and the ubiquity of medical patient information in many healthcare systems in the world, we know very little about the lexical characteristics of the register. We do not know how patients perceive the information in the leaflets or whether the messages are transmitted effectively and fully understood. How a medical authority instructs and obliges patients in written information is also unclear. While the number of radiographic examinations performed globally increases year on year, studies consistently show that patients lack basic knowledge regarding the commonly-performed exams and show very poor understanding of the concomitant risks associated with radiation. There is, then, a pressing need to investigate radiography patient information in order to better understand why, and where, it is less effective. This thesis applies three approaches common to the field of corpus linguistics to uncover some of the lexical characteristics of patient information for radiography. The approaches used in this thesis are a keyword extraction, a lexical bundles analysis and an investigation of modal verbs used to express obligation. The findings suggest that patient information for radiography possesses characteristics more common to academic prose than conversation, although the high informational content of the register goes some way to explaining this and suggests that the reliance on these structures may, to a certain extent, be unavoidable. Results also suggest that the reliance on should to oblige and instruct is problematic as it may cause interpretation problems for certain patients, including those for whom English is not a primary language. Certain other characteristics of patient information revealed by the analyses may also cause comprehension, and while further research is needed, none of these characteristics would be evaluated as problematic by standard readability measures, furthering doubts about the suitability of such measures for the evaluation of medical information

Automatically detecting open academic review praise and criticism

This is an accepted manuscript of an article published by Emerald in Online Information Review on 15 June 2020. The accepted version of the publication may differ from the final published version, accessible at https://doi.org/10.1108/OIR-11-2019-0347.Purpose: Peer reviewer evaluations of academic papers are known to be variable in content and overall judgements but are important academic publishing safeguards. This article introduces a sentiment analysis program, PeerJudge, to detect praise and criticism in peer evaluations. It is designed to support editorial management decisions and reviewers in the scholarly publishing process and for grant funding decision workflows. The initial version of PeerJudge is tailored for reviews from F1000Research’s open peer review publishing platform. Design/methodology/approach: PeerJudge uses a lexical sentiment analysis approach with a human-coded initial sentiment lexicon and machine learning adjustments and additions. It was built with an F1000Research development corpus and evaluated on a different F1000Research test corpus using reviewer ratings. Findings: PeerJudge can predict F1000Research judgements from negative evaluations in reviewers’ comments more accurately than baseline approaches, although not from positive reviewer comments, which seem to be largely unrelated to reviewer decisions. Within the F1000Research mode of post-publication peer review, the absence of any detected negative comments is a reliable indicator that an article will be ‘approved’, but the presence of moderately negative comments could lead to either an approved or approved with reservations decision. Originality/value: PeerJudge is the first transparent AI approach to peer review sentiment detection. It may be used to identify anomalous reviews with text potentially not matching judgements for individual checks or systematic bias assessments

SPARC 2019 Fake news & home truths : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2019 SPARC conference. This year we not only celebrate the work of our PGRs but also our first ever Doctoral School Best Supervisor awards, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 90 presenters, the conference truly showcases a vibrant, innovative and collaborative PGR community at Salford. These abstracts provide a taster of the inspiring, relevant and impactful research in progress, and provide delegates with a reference point for networking and initiating critical debate. Find an abstract that interests you, and say “Hello” to the author. Who knows what might result from your conversation? With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research needs interdisciplinary collaboration. This is recognised and rewarded by all major research funders. Engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers. Even better, our free ice cream van means that you can have those conversations while enjoying a refreshing ice lolly

Transperineal template saturation and conventional biopsy for stage prediction in prostate cancer

OBJECTIVE To evaluate the performance of risk calculators (RCs) predicting lymph node invasion (LNI) and extraprostatic extension (EPE) in men undergoing transperineal magnetic resonance imaging/transrectal ultrasound (TRUS)-fusion template saturation biopsy (TTSB) and conventional systematic TRUS-guided biopsy (SB). PATIENTS AND METHODS The RCs were tested in a consecutive cohort of 645 men undergoing radical prostatectomy with extended pelvic LN dissection between 2005 and 2019. TTSB was performed in 230 (35.7%) and SB in 415 (64.3%) men. Risk of LNI and EPE was calculated using the available RCs. Discrimination, calibration, and clinical usefulness stratified by different biopsy techniques were assessed. RESULTS Lymph node invasion was observed in 23 (10%) and EPE in 73 (31.8%) of cases with TTSB and 53 (12.8%) and 158 (38%) with SB, respectively. RCs showed an excellent discrimination and acceptable calibration for prediction of LNI based on TTSB (area under the curve [AUC]/risk estimation: Memorial Sloan Kettering Cancer Center [MSKCC]-RC 0.79/-4%, Briganti (2012)-RC 0.82/-4%, Gandaglia-RC 0.81/+6%). These were comparable in SB (MSKCC-RC 0.78/+2%; Briganti (2012)-RC 0.77/-3%). Decision curve analysis (DCA) revealed a net benefit at threshold probabilities between 3% and 6% when TTSB was used. For prediction of EPE based on TTSB an inferior discrimination and variable calibration were observed (AUC/risk estimation: MSKCC-RC 0.71/+8% and Martini (2018)-RC 0.69/+2%) achieving a net benefit on DCA only at risk thresholds of >17%. Performance of RCs for prediction of LNI and EPE based on SB showed comparable results with a better performance in the DCA for LNI (risk thresholds 1-2%) and poorer performance for EPE (risk threshold >20%). This study is limited by its retrospective single-institution design. CONCLUSIONS The potentially more accurate grading ability of TTSB did not result in improved performance of preoperative RCs. Prediction tools for LNI proved clinical usefulness while RCs for EPE did not