The ‘double-edged sword’ of a sessional academic career

There have been widespread changes to working arrangements and employment relationships, including significant decreases in continuing/full-time employment contracts. This trend is particularly notable in academia, with more universities relying on the expertise of sessional, teaching-focused academics. This qualitative study extends understanding of this important group of professionals, identifying sessional work as a ‘double-edged sword’ and suggesting a typology of sessional academic careers to be tested in future research. It reports on the diversity among sessional academics, some enjoying the autonomy and flexibility of this working arrangement, others seeking more job security and greater alignment with continuing employment. It also identifies synergies and contradictions between sessional academic careers and key themes in the contemporary careers literature

Patient and clinician factors associated with prehospital pain treatment and outcomes: cross sectional study

Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.Objective: We aimed to identify how patient (age, sex, condition) and paramedic factors (sex, role) affected prehospital analgesic administration and pain alleviation. Methods: We used a cross-sectional design with a 7-day retrospective sample of adults aged 18 years or over requiring primary emergency transport to hospital, excluding patients with Glasgow Coma Scale below 13, in two UK ambulance services. Multivariate multilevel regression using Stata 14 analysed factors independently associated with analgesic administration and a clinically meaningful reduction in pain (≥2 points on 0–10 numerical verbal pain score [NVPS]). Results: We included data on 9574 patients. At least two pain scores were recorded in 4773 (49.9%) patients. For all models fitted there was no significant relationship between analgesic administration or pain reduction and sex of the patient or ambulance staff. Reduction in pain (NVPS ≥2) was associated with ambulance crews including at least one paramedic (odds ratio [OR] 1.52, 95% confidence interval [CI] 1.14 to 2.04, p < 0.01), with any recorded pain score and suspected cardiac pain (OR 2.2, 95% CI 1.02 to 4.75). Intravenous morphine administration was also more likely where crews included a paramedic (OR 2.82, 95% CI 1.93 to 4.13, P < 0.01), attending patients aged 51 to 64 years (OR 2.04, 95% CI 1.21 to 3.45, p = 0.01), in moderate to severe (NVPS 4–10) compared with lower levels of pain for any clinical condition group compared with the reference condition. Conclusion: There was no association between patient sex or ambulance staff sex or grade and analgesic administration or pain reduction.Peer reviewedFinal Accepted Versio

A Rising Tide: Oyster Aquaculture Survey Instrument

This document provides the survey instrument for the oyster aquaculture survey that was conducted throughout August and October of 2021. The purpose of the survey was to gain a food system-wide perspective on gender dynamics in the region’s aquaculture industry, inclusive of different genders and identify potential gender-based barriers and opportunities to participation for men, women, and non-binary/third gender oyster aquaculturists

A Rising Tide: Oyster Aquaculture Survey Results

This document provides the results from a survey conducted August-October 2021 on the Maine and New Hampshire oyster aquaculture industry. The purpose of the survey was to gain a food system-wide perspective on gender dynamics in the region’s aquaculture industry, inclusive of different genders and identify potential gender-based barriers and opportunities to participation for men, women, and non-binary/third gender oyster aquaculturists. The published survey results include qualitative responses and demographic data for a subset of farmers in the oyster aquaculture industry of Maine and New Hampshire

A Rising Tide Photovoice Photobook

This document provides the results of the photographic documentation and written narrative portion of the photovoice case study conducted from November, 2021 to March, 2022 by (n=4) research participants. The goal of the Photobook is to share the data collected by the research participants on their experiences as women owning and operating an oyster farm in Maine and New Hampshire

Advance care planning in older hospitalised patients following an emergency admission: A mixed methods study.

INTRODUCTION: Although advance care planning may be beneficial for older adults in the last year of life, its relevance following an emergency hospitalisation requires further investigation. This study quantifies the one-year mortality outcomes of all emergency admissions for patients aged 70+ years and explores patient views on the value of advance care planning following acute hospitalisation. METHOD: This mixed methods study used a two-stage approach: firstly, a quantitative longitudinal cohort study exploring the one-year mortality of patients aged 70+ admitted as an emergency to a large multi-centre hospital cohort; secondly, a qualitative semi-structured interview study gathering information on patient views of advance care planning. RESULTS: There were 14,260 emergency admissions for 70+-year olds over a 12-month period. One-year mortality for admissions across all conditions was 22.6%. The majority of these deaths (59.3%) were within 3 months of admission. Binary logistic regression analysis indicated higher one-year mortality with increasing age and male sex. Interviews with 20 patients resulted in one superordinate theme, "Planning for health and wellbeing in the spectrum of illness". Sub-themes entitled (1) Advance care planning benefitting healthcare for physical and psycho-social health, (2) Contemplation of physical deterioration death and dying and 3) Collaborating with healthcare professionals to undertake advance care planning, suggest that views of advance care planning are shaped by experiences of acute hospitalisation. CONCLUSION: Since approximately 1 in 5 patients aged 70+ admitted to hospital as an emergency are in the last year of life, acute hospitalisation can act as a trigger for tailored ACP. Older hospitalised patients believe that advance care planning can benefit physical and psychosocial health and that discussions should consider a spectrum of possibilities, from future health to the potential of chronic illness, disability and death. In this context, patients may look for expertise from healthcare professionals for planning their future care

Predicting 10-year breast cancer mortality risk in the general female population in England: a model development and validation study

Background Identifying female individuals at highest risk of developing life-threatening breast cancers could inform novel stratified early detection and prevention strategies to reduce breast cancer mortality, rather than only considering cancer incidence. We aimed to develop a prognostic model that accurately predicts the 10-year risk of breast cancer mortality in female individuals without breast cancer at baseline. Methods In this model development and validation study, we used an open cohort study from the QResearch primary care database, which was linked to secondary care and national cancer and mortality registers in England, UK. The data extracted were from female individuals aged 20–90 years without previous breast cancer or ductal carcinoma in situ who entered the cohort between Jan 1, 2000, and Dec 31, 2020. The primary outcome was breast cancer-related death, which was assessed in the full dataset. Cox proportional hazards, competing risks regression, XGBoost, and neural network modelling approaches were used to predict the risk of breast cancer death within 10 years using routinely collected health-care data. Death due to causes other than breast cancer was the competing risk. Internal–external validation was used to evaluate prognostic model performance (using Harrell's C, calibration slope, and calibration in the large), performance heterogeneity, and transportability. Internal–external validation involved dataset partitioning by time period and geographical region. Decision curve analysis was used to assess clinical utility. Findings We identified data for 11 626 969 female individuals, with 70 095 574 person-years of follow-up. There were 142 712 (1·2%) diagnoses of breast cancer, 24 043 (0·2%) breast cancer-related deaths, and 696 106 (6·0%) deaths from other causes. Meta-analysis pooled estimates of Harrell's C were highest for the competing risks model (0·932, 95% CI 0·917–0·946). The competing risks model was well calibrated overall (slope 1·011, 95% CI 0·978–1·044), and across different ethnic groups. Decision curve analysis suggested favourable clinical utility across all age groups. The XGBoost and neural network models had variable performance across age and ethnic groups. Interpretation A model that predicts the combined risk of developing and then dying from breast cancer at the population level could inform stratified screening or chemoprevention strategies. Further evaluation of the competing risks model should comprise effect and health economic assessment of model-informed strategies. Funding Cancer Research UK

Development and internal-external validation of statistical and machine learning models for breast cancer prognostication: cohort study

Objective To develop a clinically useful model that estimates the 10 year risk of breast cancer related mortality in women (self-reported female sex) with breast cancer of any stage, comparing results from regression and machine learning approaches. Design Population based cohort study. Setting QResearch primary care database in England, with individual level linkage to the national cancer registry, Hospital Episodes Statistics, and national mortality registers. Participants 141 765 women aged 20 years and older with a diagnosis of invasive breast cancer between 1 January 2000 and 31 December 2020. Main outcome measures Four model building strategies comprising two regression (Cox proportional hazards and competing risks regression) and two machine learning (XGBoost and an artificial neural network) approaches. Internal-external cross validation was used for model evaluation. Random effects meta-analysis that pooled estimates of discrimination and calibration metrics, calibration plots, and decision curve analysis were used to assess model performance, transportability, and clinical utility. Results During a median 4.16 years (interquartile range 1.76-8.26) of follow-up, 21 688 breast cancer related deaths and 11 454 deaths from other causes occurred. Restricting to 10 years maximum follow-up from breast cancer diagnosis, 20 367 breast cancer related deaths occurred during a total of 688 564.81 person years. The crude breast cancer mortality rate was 295.79 per 10 000 person years (95% confidence interval 291.75 to 299.88). Predictors varied for each regression model, but both Cox and competing risks models included age at diagnosis, body mass index, smoking status, route to diagnosis, hormone receptor status, cancer stage, and grade of breast cancer. The Cox model’s random effects meta-analysis pooled estimate for Harrell’s C index was the highest of any model at 0.858 (95% confidence interval 0.853 to 0.864, and 95% prediction interval 0.843 to 0.873). It appeared acceptably calibrated on calibration plots. The competing risks regression model had good discrimination: pooled Harrell’s C index 0.849 (0.839 to 0.859, and 0.821 to 0.876, and evidence of systematic miscalibration on summary metrics was lacking. The machine learning models had acceptable discrimination overall (Harrell’s C index: XGBoost 0.821 (0.813 to 0.828, and 0.805 to 0.837); neural network 0.847 (0.835 to 0.858, and 0.816 to 0.878)), but had more complex patterns of miscalibration and more variable regional and stage specific performance. Decision curve analysis suggested that the Cox and competing risks regression models tested may have higher clinical utility than the two machine learning approaches. Conclusion In women with breast cancer of any stage, using the predictors available in this dataset, regression based methods had better and more consistent performance compared with machine learning approaches and may be worthy of further evaluation for potential clinical use, such as for stratified follow-up

Up-regulation of anti-apoptotic genes confers resistance to the novel anti-leukaemic compound PEP005 in primary AML cells

We showed previously that PEP005 induced apoptosis in leukaemic cell lines and blasts from patients with acute myeloid leukaemia (AML). Here we assess the anti-leukeamic effects of PEP005 in vivo and determine the mechanism of resistance of PEP005 non-responsive cells. We used 2 human xenograft mouse models of AML to assess the anti-leukaemic effects of PEP005 in vivo. Expression microarray analysis of primary AML blasts following treatment with PEP005 was used to determine patterns of gene expression that conferred resistance. PEP005 significantly reduced tumour burden in two human leukaemia mouse xenograft models. We also assessed responsiveness of 33 AML samples to PEP005, with 78% of the samples entering apoptosis at 100nM. Resistance to PEP005 was not restricted to a particular AML subtype. Expression microarray analysis of resistant samples following treatment with PEP005 revealed a significant up regulation of the anti-apoptotic genes Bcl-2A1, Mcl-1, and PHLDA1 which was verified using RT-PCR. We conclude that PEP005 shows broad efficacy against AML subtypes and that up regulation of anti-apoptotic genes underlies resistance to this agent and could be used to screen for patients unlikely to benefit from a therapeutic regime involving PEP005

Singing teaching as a therapy for chronic respiratory disease - a randomised controlled trial and qualitative evaluation

<p>Abstract</p> <p>Background</p> <p>Despite optimal pharmacological therapy and pulmonary rehabilitation, patients with COPD continue to be breathless. There is a need to develop additional strategies to alleviate symptoms. Learning to sing requires control of breathing and posture and might have benefits that translate into daily life.</p> <p>Methods</p> <p>To test this hypothesis we performed a randomised controlled trial, comparing a six week course of twice weekly singing classes to usual care, in 28 COPD patients. The experience of singing was assessed in a qualitative fashion, through interviews with a psychologist. In addition, we surveyed patients with chronic respiratory conditions who participated in a series of open singing workshops.</p> <p>Results</p> <p>In the RCT, the physical component score of the SF36 improved in the singers (n = 15) compared to the controls (n = 13); +7.5(14.6) vs. -3.8(8.4) p = 0.02. Singers also had a significant fall in HAD anxiety score; -1.1(2.7) vs. +0.8(1.7) p = 0.03. Singing did not improve single breath counting, breath hold time or shuttle walk distance. In the qualitative element, 8 patients from the singing group were interviewed. Positive effects on physical sensation, general well-being, community/social support and achievement/efficacy emerged as common themes. 150 participants in open workshops completed a questionnaire. 96% rated the workshops as "very enjoyable" and 98% thought the workshop had taught them something about breathing in a different way. 81% of attendees felt a "marked physical difference" after the workshop.</p> <p>Conclusion</p> <p>Singing classes can improve quality of life measures and anxiety and are viewed as a very positive experience by patients with respiratory disease; no adverse consequences of participation were observed.</p> <p>Trial Registration</p> <p>Current Controlled Trials - ISRCTN17544114.</p