Accounting for changing temperature patterns increases historical estimates of climate sensitivity

Eight atmospheric general circulation models (AGCMs) are forced with observed historical (1871–2010) monthly sea surface temperature and sea ice variations using the Atmospheric Model Intercomparison Project II data set. The AGCMs therefore have a similar temperature pattern and trend to that of observed historical climate change. The AGCMs simulate a spread in climate feedback similar to that seen in coupled simulations of the response to CO2 quadrupling. However, the feedbacks are robustly more stabilizing and the effective climate sensitivity (EffCS) smaller. This is due to a pattern effect, whereby the pattern of observed historical sea surface temperature change gives rise to more negative cloud and longwave clear‐sky feedbacks. Assuming the patterns of long‐term temperature change simulated by models, and the radiative response to them, are credible; this implies that existing constraints on EffCS from historical energy budget variations give values that are too low and overly constrained, particularly at the upper end. For example, the pattern effect increases the long‐term Otto et al. (2013, https://doi.org/10.1038/ngeo1836) EffCS median and 5–95% confidence interval from 1.9 K (0.9–5.0 K) to 3.2 K (1.5–8.1 K

Researching Chinese Students in the UK - the Use of Ethnography in Social Media Studies

The growing prevalence of digital media has led to an increasing number of studies investigating its role in people’s lives. Traditionally, ethnographers go to the fieldsite physically to understand people and their culture. Now, with a large amount of social interaction taking place online, ethnographers have also began attempting to use digital methods to understand people’s online practices, interactions, and cultural production. This paper documents both online and offline ethnographic methods employed in a pilot study that set out to understand the ways that Chinese students portray their lives on social media when studying at UK universities. With a focus on in-depth reflections on methodologies and data collection processes, this paper aims to provide a point of reference for researchers who are interested in doing ethnography in the digital field

Incidence, attributable mortality, and healthcare and out-of-pocket costs of Clostridioides difficile infection in US Medicare Advantage Enrollees

BACKGROUND: US attributable Clostridioides difficile infection (CDI) mortality and cost data are primarily from Medicare fee-for-service populations, and little is known about Medicare Advantage Enrollees (MAEs). This study evaluated CDI incidence among MAEs from 2012 to 2019 and determined attributable mortality and costs by comparing MAEs with and without CDI occurring in 2018. METHODS: This retrospective cohort study assessed CDI incidence and associated mortality and costs for eligible MAEs ≥65 years of age using the de-identified Optum Clinformatics Data Mart database (Optum; Eden Prairie, Minnesota, USA). Outcomes included mortality, healthcare utilization, and costs, which were assessed via a propensity score-matched cohort using 2018 as the index year. Outcome analyses were stratified by infection acquisition and hospitalization status. RESULTS: From 2012 to 2019, overall annual CDI incidence declined from 609 to 442 per 100 000 person-years. Although the incidence of healthcare-associated CDI declined overall (2012, 53.2%; 2019, 47.2%), community-associated CDI increased (2012, 46.8%; 2019, 52.8%). The 1-year attributable mortality was 7.9% (CDI cases, 26.3%; non-CDI controls, 18.4%). At the 2-month follow-up, CDI-associated excess mean total healthcare and out-of-pocket costs were $13 476 and$396, respectively. Total excess mean healthcare costs were greater among hospitalized (healthcare-associated, $28 762; community-associated,$28 330) than nonhospitalized CDI patients ($5704 and$2320, respectively), whereas total excess mean out-of-pocket cost was highest among community-associated hospitalized CDI patients ($970). CONCLUSIONS: CDI represents an important public health burden in the MAE population. Preventive strategies and treatments are needed to improve outcomes and reduce costs for healthcare systems and this growing population of older US adults

Can Teaching Enthusiasm Partially Predict the Reading Attainment of Low-income Students in Secondary Schools in England?

The poverty achievement gap in early reading is a persistent issue in England and around the world, potentially disadvantaging poor students and their further study. This new study employs student-perceived teaching enthusiasm and reading attitudes to help explain the poverty attainment gap. The sample was 5,242 15-year-old participants in PISA 2018 from 175 secondary schools in England. Path analysis is used to investigate the potential effect of teaching enthusiasm on the reading attainment of low-income students. The findings indicate that family socioeconomic status remains an important predictor of students' reading achievement. Students from economically privileged families tend to rate teaching enthusiasm more highly and express a positive reading attitude, which can partially explain the poverty attainment gap in reading. Therefore, teachers might be able to enhance low-income students’ reading outcomes and close the poverty attainment gap a little through enhanced teaching enthusiasm to cultivate students’ positive reading attitudes

School-Based Physical Activity Intervention: A Qualitative Process Evaluation of a Feasibility Trial in Yangzhou, China

Background: There is an urgent need for children in China to increase their physical activity levels. We first developed a 16-week school-based behavior change intervention based on the Behavior Change Wheel and Theoretical Domains Framework. We then conducted a cluster feasibility non-randomized controlled trial (RCT) among children in Yangzhou, China. Aim: This qualitative process evaluation was embedded within the cluster feasibility non-RCT and aimed to: (1) explore the experiences and perceptions of participants and providers in the intervention and trial; and (2) generate recommendations to inform a future intervention and full-scale cluster RCT. Methods: A qualitative study, using semi-structured interviews with trial participants (n = 20 children: 10 intervention, 10 control), parents (n = 20), and health education providers (n = 2), was conducted in two public schools in Yangzhou, China. Interviews were audio-recorded, transcribed, and translated verbatim from Mandarin to English. Data were analyzed using thematic analysis. Results: Findings believed to reflect experiences and perceptions of participants in the intervention and the trial are presented as eight major themes: (1) perceived high efficacy of the intervention components to help children become more active, (2) appreciation of the intervention features, (3) factors that facilitated or impeded intervention attendance and delivery, (4) positive experiences and feelings gained through the data collection process, (5) satisfaction regarding the organization and implementation of the trial, (6) influences of personal beliefs and emotional responses to the trial, (7) social influences on participatory decision-making, and (8) key barriers to consider regarding the recruitment of participants. Conclusions: The intervention and trial methods were acceptable to children, parents, and health education providers. School-based behavior change intervention was perceived to be a useful approach to increase physical activity in children aged 10–12 years in China. However, there were barriers to intervention delivery and engagement that should be considered when designing a future cluster RCT to assess the intervention efficacy

Windowed Eigen-Decomposition Algorithm for Motion Artifact Reduction in Optical Coherence Tomography-Based Angiography

Optical coherence tomography-based angiography (OCTA) has attracted attention in clinical applications as a non-invasive and high-resolution imaging modality. Motion artifacts are the most seen artifact in OCTA. Eigen-decomposition (ED) algorithms are popular choices for OCTA reconstruction, but have limitations in the reduction of motion artifacts. The OCTA data do not meet one of the requirements of ED, which is that the data should be normally distributed. To overcome this drawback, we propose an easy-to-deploy development of ED, windowed-ED (wED). wED applies a moving window to the input data, which can contrast the blood-flow signals with significantly reduced motion artifacts. To evaluate our wED algorithm, pre-acquired dorsal wound healing data in a murine model were used. The ideal window size was optimized by fitting the data distribution with the normal distribution. Lastly, the cross-sectional and en face results were compared among several OCTA reconstruction algorithms, Speckle Variance, A-scan ED (aED), B-scan ED, and wED. wED could reduce the background noise intensity by 18% and improve PSNR by 4.6%, compared to the second best-performed algorithm, aED. This study can serve as a guide for utilizing wED to reconstruct OCTA images with an optimized window size