Examining GRI Sustainability Reports through the Lens of the Stakeholder Theory

Publishing a successful sustainability report is a rising concern among organizations seeking to meet the expectations of their stakeholders. The purpose of this research is to examine how stakeholder engagement influences Global Reporting Initiative’s (GRI) reporting processes. We use stakeholder theory to assert that an organization’s sustainability practices are prompted by the demands of a variety of stakeholders. Cisco GRI reports were chosen for analysis because in 2020 Cisco was ranked 4th amongst the global 100 most sustainable corporations in the world. We conducted a longitudinal analysis of Cisco\u27s corporate social responsibility reports from 2005 to 2020. Using text mining techniques and text statistical analysis we identified the primary stakeholders in each year’s sustainability report and document stakeholder-related sustainability practices. Our results demonstrate that organizational sustainability practices are a function of the extent of engagement with core stakeholders. This study contributes to understanding how stakeholders’ engagement relates to organizational sustainability reporting processes

Effect of home telemonitoring on glycemic and blood pressure control in primary care clinic patients with diabetes

Objective: Patient self-management support may be augmented by using home-based technologies that generate data points that providers can potentially use to make more timely changes in the patients' care. The purpose of this study was to evaluate the effectiveness of short-term targeted use of remote data transmission on treatment outcomes in patients with diabetes who had either out-of-range hemoglobin A1c (A1c) and/or blood pressure (BP) measurements. Materials and Methods: A single-center randomized controlled clinical trial design compared in-home monitoring (n=55) and usual care (n=53) in patients with type 2 diabetes and hypertension being treated in primary care clinics. Primary outcomes were A1c and systolic BP after a 12-week intervention. Results: There were no significant differences between the intervention and control groups on either A1c or systolic BP following the intervention. Conclusions: The addition of technology alone is unlikely to lead to improvements in outcomes. Practices need to be selective in their use of telemonitoring with patients, limiting it to patients who have motivation or a significant change in care, such as starting insulin. Attention to the need for effective and responsive clinic processes to optimize the use of the additional data is also important when implementing these types of technology

Development of a clinical decision model for thyroid nodules

<p>Abstract</p> <p>Background</p> <p>Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people) has a palpable thyroid nodule, however the majority (>95%) of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm) with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80%) of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery.</p> <p>Methods</p> <p>Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US), electrical impedance scanning (EIS) and fine needle aspiration cytology (FNA) prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records) and a test set (10% of records). A receiver-operating-characteristics (ROC) curve of these predictions and area under the curve (AUC) were calculated to determine model robustness for predicting malignancy in thyroid nodules.</p> <p>Results</p> <p>Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of malignancy. Cross validation of the model created with Bayesian Network Analysis effectively predicted malignancy [AUC = 0.88 (95%CI: 0.82–0.94)] in thyroid nodules. The positive and negative predictive values of the model are 83% (95%CI: 76%–91%) and 79% (95%CI: 72%–86%), respectively.</p> <p>Conclusion</p> <p>An integrated predictive decision model using Bayesian inference incorporating readily obtainable thyroid nodule measures is clinically relevant, as it effectively predicts malignancy in thyroid nodules. This model warrants further validation testing in prospective clinical trials.</p

Using habitat models for chinstrap penguins Pygoscelis antarctica to advise krill fisheries management during the penguin breeding season

Aim: To predict the at‐sea distribution of chinstrap penguins across the South Orkney Islands and to quantify the overlap with the Southern Ocean krill fishery. Location: South Orkney Islands, Antarctica. Methods: Penguins from four colonies across the South Orkney Islands were tracked using global positioning systems (GPSs) and time depth recorders (TDRs). Relationships between a variety of environmental and geometric variables and the at‐sea distribution of penguins were investigated using general additive models for the three main phases of the breeding season. Subsequently, the final models were extrapolated across the South Orkney archipelago to predict the at‐sea distribution of penguins from colonies where no tracking data are available. Finally, the overlap between areas used by chinstrap penguins and the krill fishery was quantified. Results: The foraging distribution of chinstrap penguins can be predicted using two simple and static variables: the distance from the colony and the direction of travel towards the shelf‐edge, while avoiding high densities of Pygoscelis penguins from other colonies. Additionally, we find that the chinstrap penguins breeding on the South Orkney Islands use areas which overlap with frequently used krill fishing areas and that this overlap is most prominent during the brood and crèche phases of the breeding season. Main conclusions: This is the first step in understanding the potential impacts of the krill fishery, for all colonies including those where no empirical tracking data are available. However, with the available data, it is not currently possible to infer an impact of the krill fisheries on penguins. With this in mind, we recommend the implementation of monitoring schemes to investigate the effects of prey depletion on predator populations and to ensure that management continues to follow a precautionary approach and is addressed at spatial and temporal scales relevant to ecosystem operation

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London