Psychology ethics down under: A survey of student subject pools in Australia

A survey of the 37 psychology departments offering courses accredited by the Australian Psychological Society yielded a 92% response rate. Sixty-eight percent of departments employed students as research subjects, with larger departments being more likely to do so. Most of these departments drew their student subject pools from introductory courses. Student research participation was strictly voluntary in 57% of these departments, whereas 43% of the departments have failed to comply with normally accepted ethical standards. It is of great concern that institutional ethics committees apparently continue to condone, or fail to act against, unethical research practices. Although these committees have a duty of care to all subjects, the final responsibility for conducting research in an ethical manner lies with the individual researcher

The burden is great and the money little: Changing chronic disease management in low– and middle–income countries

Many health conditions are chronic, and only some of those chronic health conditions are NCDs. If the interest is on cause and prevention, then NCDs should be treated separately from other chronic diseases. If the interest is on health systems and management, then NCDs should be joined with other chronic diseases

The effect of door-to-balloon delay in primary percutaneous coronary intervention on clinical outcomes of STEMI: a systematic review and meta-analysis protocol

BACKGROUND: Acute myocardial infarction (AMI) is a medical emergency in which sudden occlusion of coronary artery(ies) results in ischemia and necrosis of the cardiac tissues. Reperfusion therapies that aim at reopening the occluded artery remain the mainstay of treatment for AMI. Primary percutaneous coronary intervention (PCI), which enables the restoration of blood flow by reopening the occluded artery(ies) via a catheter with an inflatable balloon, is currently the preferred treatment for AMI with ST segment elevation (STEMI). The door-to-balloon (D2B) delay refers to the time interval counting from the arrival of a patient with STEMI at a hospital to the time of the balloon inflation (or stent deployment) that reopens the occluded artery(ies). Reducing this delay in primary PCI is thought to be an important strategy toward achieving better patient outcomes. Unfortunately, significant reduction of D2B delay in the USA over the last decade has not been shown to be associated with improved STEMI mortality. It has been suggested that the lack of impact could be due to the expanding use of primary PCI in STEMI as well as the survival cohort effect, leading to a shift toward a higher risk population receiving the procedure. Others have suggested that reduction in D2B delay may not be as impactful as expected, given that it only represents a small fraction of the total ischemic time. Although most existing evidence have pointed to the presence of a beneficial effect of shorter D2B delay, some inconsistencies however exist. This study aims to synthesize available evidence in order to answer the following questions: (1) what is the overall effect of D2B delay on clinical outcomes in patients with STEMI treated with primary PCI? (2) What factors explain the differences of the effect estimates among the studies? (3) What are the important strength and limitation of the existing body of evidence? METHOD: We will search PubMed/MEDLINE, EMBASE, ClinicalTrials.gov, WHO International Clinical Trials Registry, CINAHL Database, and the Cochrane Library using a predefined search strategy. Other sources of literature will include proceedings from the European Society of Cardiology, the American College of Cardiology, the American Heart Association, the EUROPCR, and the ProQuest Dissertations and Theses Database. We will include data from observational studies (case-control and cohort study design) and randomized control trials (that have investigated the relationship of D2B time and clinical outcome(s) in an adult (older than 18) STEMI population). Mortality (cardiac related and all-cause) and incidence heart failure (HF) have been prioritized as the primary outcomes. All eligible studies will be assessed for risk of bias using the Risk Of Bias in Non-randomized Studies - of Interventions tool. The Grading of Recommendations, Assessment, and Evaluation (GRADE) framework will be used to report the quality of evidence and strength of recommendations. We will proceed to analyze the data quantitatively if the pre-specified conditions are satisfied. DISCUSSION: Recent discussion on the negative findings of improved D2B delay over time being unrelated to better STEMI outcomes at the population level has reminded us of an important knowledge gap we have on this domain. This systematic review will serve to address some of these key questions not previously examined. Answers to these questions could clarify the controversies and offer empirical support for or against the suggested hypotheses. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015026069 ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13643-016-0304-7) contains supplementary material, which is available to authorized users

Social sciences research in neglected tropical diseases 3: Investment in social science research in neglected diseases of poverty: a case study of Bill and Melinda Gates Foundation

This article has been made available through the Brunel Open Access Publishing Fund.BACKGROUND: The level of funding provides a good proxy for the level of commitment or prioritisation given to a particular issue. While the need for research relevant to social, economic, cultural and behavioural aspects of neglected tropical diseases (NTD) control has been acknowledged, there is limited data on the level of funding that supports NTD social science research. METHOD: A case study was carried out in which the spending of a major independent funder, the Bill and Melinda Gates Foundation (BMGF) - was analysed. A total of 67 projects funded between October 1998 and November 2008 were identified from the BMGF database. With the help of keywords within the titles of 67 grantees, they were categorised as social science or non-social science research based on available definition of social science. A descriptive analysis was conducted. RESULTS: Of 67 projects analysed, 26 projects (39%) were social science related while 41 projects (61%) were basic science or other translational research including drug development. A total of US$697 million was spent to fund the projects, of which 35$ 241 million) went to social science research. Although the level of funding for social science research has generally been lower than that for non-social science research over 10 year period, social science research attracted more funding in 2004 and 2008. CONCLUSION: The evidence presented in this case study indicates that funding on NTD social science research compared to basic and translational research is not as low as it is perceived to be. However, as there is the acute need for improved delivery and utilisation of current NTD drugs/technologies, informed by research from social science approaches, funding priorities need to reflect the need to invest significantly more in NTD social science research

Humans as Animal Sentinels for Forecasting Asthma Events: Helping Health Services Become More Responsive

The concept of forecasting asthma using humans as animal sentinels is uncommon. This study explores the plausibility of predicting future asthma daily admissions using retrospective data in London (2005-2006). Negative binomial regressions were used in modeling; allowing the non-contiguous autoregressive components. Selected lags were based on partial autocorrelation function (PACF) plot with a maximum lag of 7 days. The model was contrasted with naïve historical and seasonal models. All models were cross validated. Mean daily asthma admission in 2005 was 27.9 and in 2006 it was 28.9. The lags 1, 2, 3, 6 and 7 were independently associated with daily asthma admissions based on their PACF plots. The lag model prediction of peak admissions were often slightly out of synchronization with the actual data, but the days of greater admissions were better matched than the days of lower admissions. A further investigation across various populations is necessary. © 2012 Soyiri, Reidpath

HIV, Stigma, and Rates of Infection: A Rumour without Evidence: Authors' Reply

Daniel Reidpath - ORCID: 0000-0002-8796-0420 https://orcid.org/0000-0002-8796-04204pubpub

Evolving forecasting classifications and applications in health forecasting

Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths.Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal/ temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1).The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2)This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept. © 2013 Soyiri, Reidpath

Semistructured black-box prediction: proposed approach for asthma admissions in London

Asthma is a global public health problem and the most common chronic disease among children. The factors associated with the condition are diverse, and environmental factors appear to be the leading cause of asthma exacerbation and its worsening disease burden. However, it remains unknown how changes in the environment affect asthma over time, and how temporal or environmental factors predict asthma events. The methodologies for forecasting asthma and other similar chronic conditions are not comprehensively documented anywhere to account for semistructured noncausal forecasting approaches. This paper highlights and discusses practical issues associated with asthma and the environment, and suggests possible approaches for developing decision-making tools in the form of semistructured black-box models, which is relatively new for asthma. Two statistical methods which can potentially be used in predictive modeling and health forecasting for both anticipated and peak events are suggested. Importantly, this paper attempts to bridge the areas of epidemiology, environmental medicine and exposure risks, and health services provision. The ideas discussed herein will support the development and implementation of early warning systems for chronic respiratory conditions in large populations, and ultimately lead to better decision-making tools for improving health service delivery. © 2012 Soyiri and Reidpath, publisher and licensee Dove Medical Press Ltd