Application of the gradient boosted method in randomised clinical trials: participant variables that contribute to depression treatment efficacy of duloxetine, SSRIs or placebo

Randomised, placebo-controlled trials of treatments for depression typically collect outcomes data but traditionally only analyse data to demonstrate efficacy and safety. Additional post-hoc statistical techniques may reveal important insights about treatment variables useful when considering inter-individual differences amongst depressed patients. This paper aims to examine the Gradient Boosted Model (GBM), a statistical technique that uses regression tree analyses and can be applied to clinical trial data to identify and measure variables that may influence treatment outcomes.

Exploring associations between parental and peer variables, personal variables and physical activity among adolescents: a mediation analysis

This study aimed to investigate how parental and peer variables are associated with moderate- to-vigorous intensity physical activity (MVPA) on week- and weekend days among Australian adolescents (13-15 y), and whether perceived internal barriers (e.g. lack of time), external barriers (e.g. lack of others to be physically active with) and self-efficacy mediated these associations.

Creating spaces in intensive care for safe communication : a video-reflexive ethnographic study

The built environment in acute care settings is a new focus in patient safety research, with few studies focusing primarily on the design of ward environments and the location and choice of material objects such as light fittings and hand-washing basins.

A unit root model for trending time-series energy variables

In this paper, we propose a GARCH-based unit root test that is flexible enough to account for; (a) trending variables, (b) two endogenous structural breaks, and (c) heteroskedastic data series. Our proposed model is applied to a range of time-series, trending, and heteroskedastic energy variables. Our two main findings are: first, the proposed trend-based GARCH unit root model outperforms a GARCH model without trend; and, second, allowing for a time trend and two endogenous structural breaks are important in practice, for doing so allows us to reject the unit root null hypothesis.

Experience and expression of anger among Australian prisoners and the relationship between anger and reintegration variables

We examined the experience and expression of anger among a group of Australian prisoners prior to and following prison release, as well as the relationship between anger and several reintegration variables. Participants were 79 adult prisoners (54 male, 25 female) who completed the State-Trait Anger Expression Inventory (STAXI-2) 1 month prior to release and again at 1 to 4 weeks and 3 to 4 months post-release. A postrelease questionnaire was also administered at the two postrelease points focusing on the quality of life conditions experienced following release. Mean state and trait anger scores were significantly higher at pre-release than post-release. As well, higher levels of anger expression and anger control were reported at pre-release compared with post-release. Higher age was related to lower state anger at post-release, whereas several variables were related to trait anger at post-release. Theoretical implications for reintegration theory are discussed, together with practical applications.

Reflexive deliberation in international research collaboration: minimising risk and maximising opportunity

International research collaboration raises questions about how groups from different national and institutional contexts can work together for common ends. This paper uses issues that have arisen in carrying out the first stage of an international research project to discuss a framework designed to map different kinds of multi-national research collaboration in terms of increasing complexity and increasing time to research outputs. The paper explores factors that enable and that constrain progress in carrying out collaborative research. The paper highlights the complex interplay within research practice of factors that derive from institutional structures and those that appertain to individuals as agents. It uses the personal and collective reflexive deliberations of the authors, to demonstrate that as the complexity of the research interface increases, and as the time to research outputs increases, so structural risk increasingly develops into agentic risk, and that structural risk becomes increasingly required to be managed through agentic action.

Satellite imagery as a single source of predictor variables for habitat suitability modelling: how Landsat can inform the conservation of a critically endangered lemur

1. Statistical modelling of habitat suitability is an important tool for planning conservation interventions, particularly for areas where species distribution data are expensive or hard to collect. Sometimes however the predictor variables typically used in habitat suitability modelling are themselves difficult to obtain or not meaningful at the geographical extent of the study, as is the case for the Alaotran gentle lemur Hapalemur alaotrensis, a critically endangered lemur confined to the marshes of Lake Alaotra in Madagascar.2. We developed a habitat suitability model where all predictor variables, including vegetation indices and image texture measures at different scales (as surrogates for habitat structure), were derived from Landsat7 satellite imagery. Using relatively few presence records, the maximum entropy (Maxent) approach and AUC were used to assess the performance of candidate predictor variables, for studying the effect of scale, model selection and mapping suitable habitat.3. This study demonstrated the utility of satellite imagery as a single source of predictor variables for a Maxent habitat suitability model at the landscape level, within a restricted geographical extent and with a fine grain, in a case where predictor variables typically used at the macro-scale level (e.g. climatic and topographic) were not applicable.4. In the case of H. alaotrensis, the methodology generated a habitat suitability map to inform conservation management in Lake Alaotra and a replicable protocol to allow rapid updates to habitat suitability maps in the future. The exploration of candidate predictor variables allowed the identification of scales that appear ecologically relevant for the species.5. Synthesis and applications. This study presents a cost-effective combination of maximum entropy habitat suitability modelling and satellite imagery, where all predictor variables are derived solely from Landsat7 images. With a habitat modelling method like Maxent that shows good performance with few presence samples and Landsat images now freely available, the methodology can play an important role in rapid assessments of the status of species at the landscape level in data-poor regions, when typical macro-scale environmental predictors are of little use or difficult to obtain.

Dataset of specific variables from the Mums, Dads, Kids study

Dataset for MDK study including screen time and anxiety scores of participants. Also includes demographic characteristics