The Catlin Seaview Survey – kilometre-scale seascape assessment, and monitoring of coral reef ecosystems

1.Marine ecosystems provide critically important goods and services to society, and hence their accelerated degradation underpins an urgent need to take rapid, ambitious and informed decisions regarding their conservation and management. 2.The capacity, however, to generate the detailed field data required to inform conservation planning at appropriate scales is limited by time and resource consuming methods for collecting and analysing field data at the large scales required. 3.The ‘Catlin Seaview Survey’, described here, introduces a novel framework for large-scale monitoring of coral reefs using high-definition underwater imagery collected using customized underwater vehicles in combination with computer vision and machine learning. This enables quantitative and geo-referenced outputs of coral reef features such as habitat types, benthic composition, and structural complexity (rugosity) to be generated across multiple kilometre-scale transects with a spatial resolution ranging from 2 to 6 m2. 4.The novel application of technology described here has enormous potential to contribute to our understanding of coral reefs and associated impacts by underpinning management decisions with kilometre-scale measurements of reef health. 5.Imagery datasets from an initial survey of 500 km of seascape are freely available through an online tool called the Catlin Global Reef Record. Outputs from the image analysis using the technologies described here will be updated on the online repository as work progresses on each dataset. 6.Case studies illustrate the utility of outputs as well as their potential to link to information from remote sensing. The potential implications of the innovative technologies on marine resource management and conservation are also discussed, along with the accuracy and efficiency of the methodologies deployed.

'Women on a Wiki’ : the role of interactive websites in reflective learning practices for undergraduate women’s health students

Aim Our pedagogical research addressed the following research questions: 1) Can shared ‘cyber spaces’, such as a ‘wiki’, be occupied by undergraduate women’s health students to improve their critical thinking skills? 2) What are the learning processes via which this occurs? 3) What are the implications of this assessment trial for achieving learning objectives and outcomes in future public health undergraduate courses? Methods The students contributed written, critical reflections (approximately 250 words) to the Wiki each week following the lecture. Students reflected on a range of topics including the portrayal of women in the media, femininity, gender inequality, child bearing and rearing, domestic violence, mental health, Indigenous women, older women, and LGBTIQ communities. Their entries were anonymous, but visible to their peers. Each wiki entry contained a ‘discussion tab’ wherein online conversations were initiated. We used a social constructivist approach to grounded theory to analyse the 480 entries posted over the semester. (http://pub336womenshealth.wikispaces.com/) Results The social constructivist approach initiated by Vygotsky (1978) and further developed by Jonasson (1994) was used to analyse the students’ contributions in relation to four key thematic outcomes including: 1) Complexities in representations across contexts; 2) Critical evaluation in real world scenarios; 3) Reflective practice based on experience, and; 4) Collaborative co-construction of knowledge. Both text and image/visual contributions are provided as examples within each of these learning processes. A theoretical model depicting the interactive learning processes that occurred via discussion of the textual and visual stimulus is presented.

Development of an online role-play assessment initiative for nursing students in their bioscience studies

Devising assessment tasks for large units that embrace academic goals of authenticity and assessment variety can be a challenge. We developed an online Role-Play Assessment Initiative for first year nursing students in bioscience. Students responded to a case study by preparing two role-play dialogues: as a nurse with the patient, and between two nurses. The aims were to assess whether the students could: 1) understand the underlying disease process (pathophysiology) and relate it to clinical practice; 2) use language appropriate for lay and medical conversation; and 3) apply information using active learning. We conducted a student survey using quantitative questions (Likert scale: 1=strongly disagree to 5=strongly agree), and qualitative questions. 65 completed surveys were received. 80% of respondents agreed (includes agree or strongly agree) that it was a useful way to learn and understand pathophysiology of the case study. 86% agreed that it was useful to apply pathophysiology from lectures to a clinical setting. Overall, students found it enjoyable, which is beneficial for enhanced student engagement, and agreed that it allowed them to work well in a group (74% and 85%, respectively). Most qualitative suggestions for improvement related to group work, despite the encouraging response to group work in quantitative questions. Most positive comments surrounded different communication with a nurse compared with a patient. These results demonstrate that students developed deeper understanding of pathophysiology through active learning and were able to expand their nursing career skills during the role-play. Learning using role-play to simulate the workforce has fostered active learning.

AITSL pilot projects [Queensland University of Technology : The existing school-based practices and processes for the use of NAPLAN data] Final report

This pilot project investigated the existing practices and processes of Proficient, Highly Accomplished and Lead teachers in the interpretation, analysis and implementation of National Assessment Program – Literacy and Numeracy (NAPLAN) data. A qualitative case study approach was the chosen methodology, with nine teachers across a variety of school sectors interviewed. Themes and sub-themes were identified from the participants’ interview responses revealing the ways in which Queensland teachers work with NAPLAN data. The data illuminated that generally individual schools and teachers adopted their own ways of working with data, with approaches ranging from individual/ad hoc, to hierarchical or a whole school approach. Findings also revealed that data are the responsibility of various persons from within the school hierarchy; some working with the data electronically whilst others rely on manual manipulation. Manipulation of data is used for various purposes including tracking performance, value adding and targeting programmes for specific groups of students, for example the gifted and talented. Whilst all participants had knowledge of intervention programmes and how practice could be modified, there were large inconsistencies in knowledge and skills across schools. Some see the use of data as a mechanism for accountability, whilst others mention data with regards to changing the school culture and identifying best practice. Overall, the findings showed inconsistencies in approach to focus area 5.4. Recommendations therefore include a more national approach to the use of educational data.

Teaching and assessment of prescribing medicines : how does pharmacy perform?

BACKGROUND Prescribing is a complex task, requiring specific knowledge and skills combined with effective, context-specific clinical reasoning. Prescribing errors can result in significant morbidity and mortality. For all professions with prescribing rights, a clear need exists to ensure students graduate with a well-defined set of prescribing skills, which will contribute to competent prescribing. AIM To describe the methods employed to teach and assess the principles of effective prescribing across five non-medical professions at Queensland University of Technology. METHOD The NPS National Prescribing Competencies Framework (PCF) was used as the prescribing standard. A curriculum mapping exercise was undertaken to determine how well the PCF was addressed across the disciplines of paramedic science, pharmacy, podiatry, nurse practitioner and optometry. Identified gaps in teaching and/or assessment were noted. RESULTS Prescribing skills and knowledge are taught and assessed using a range of methods across disciplines. A multi-modal approach is employed by all disciplines. The Pharmacy discipline uses more tutorial sessions to teach prescribing principles and relies less on case studies and clinical appraisal to assess prescribing when compared to other disciplines. Within the pharmacy discipline approximately 90% of the PCF competencies are taught and assessed. This compares favourably with the other disciplines. CONCLUSION Further work is required to establish a practical, effective approach to the assessment of prescribing competence especially between the university and clinical settings. Effective and reliable assessment of prescribing undertaken by students in diverse settings remains challenging.

The contribution of major depression to the global burden of ischemic heart disease : a comparative risk assessment

Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

The clinical utility of the Cornell Scale for Depression in Dementia as a routine assessment in nursing homes

Objective To examine the clinical utility of the Cornell Scale for Depression in Dementia (CSDD) in nursing homes. Setting 14 nursing homes in Sydney and Brisbane, Australia. Participants 92 residents with a mean age of 85 years. Measurements Consenting residents were assessed by care staff for depression using the CSDD as part of their routine assessment. Specialist clinicians conducted assessment of depression using the Semi-structured Clinical Diagnostic Interview for DSM-IV-TR Axis I Disorders for residents without dementia or the Provisional Diagnostic Criteria for Depression in Alzheimer Disease for residents with dementia to establish expert clinical diagnoses of depression. The diagnostic performance of the staff completed CSDD was analyzed against expert diagnosis using receiver operating characteristic (ROC) curves. Results The CSDD showed low diagnostic accuracy, with areas under the ROC curve being 0.69, 0.68 and 0.70 for the total sample, residents with dementia and residents without dementia, respectively. At the standard CSDD cutoff score, the sensitivity and specificity were 71% and 59% for the total sample, 69% and 57% for residents with dementia, and 75% and 61% for residents without dementia. The Youden index (for optimizing cut-points) suggested different depression cutoff scores for residents with and without dementia. Conclusion When administered by nursing home staff the clinical utility of the CSDD is highly questionable in identifying depression. The complexity of the scale, the time required for collecting relevant information, and staff skills and knowledge of assessing depression in older people must be considered when using the CSDD in nursing homes.

A comparison between conductive and infrared devices for measuring mean skin temperature at rest, during exercise in the heat, and recovery

Purpose: Skin temperature assessment has historically been undertaken with conductive devices affixed to the skin. With the development of technology, infrared devices are increasingly utilised in the measurement of skin temperature. Therefore, our purpose was to evaluate the agreement between four skin temperature devices at rest, during exercise in the heat, and recovery. Methods: Mean skin temperature (T̅sk) was assessed in thirty healthy males during 30 min rest (24.0± 1.2°C, 56 ± 8%), 30 min cycle in the heat (38.0 ± 0.5°C, 41 ± 2%), and 45 min recovery(24.0 ± 1.3°C, 56 ± 9%). T̅sk was assessed at four sites using two conductive devices(thermistors, iButtons) and two infrared devices (infrared thermometer, infrared camera). Results: Bland–Altman plots demonstrated mean bias ± limits of agreement between the thermistors and iButtons as follows (rest, exercise, recovery): -0.01 ± 0.04, 0.26 ± 0.85, -0.37 ± 0.98°C; thermistors and infrared thermometer: 0.34 ± 0.44, -0.44 ± 1.23, -1.04 ± 1.75°C; thermistors and infrared camera (rest, recovery): 0.83 ± 0.77, 1.88 ± 1.87°C. Pairwise comparisons of T̅sk found significant differences (p < 0.05) between thermistors and both infrared devices during resting conditions, and significant differences between the thermistors and all other devices tested during exercise in the heat and recovery. Conclusions: These results indicate poor agreement between conductive and infrared devices at rest, during exercise in the heat, and subsequent recovery. Infrared devices may not be suitable for monitoring T̅sk in the presence of, or following, metabolic and environmental induced heat stress.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

The rise of low-cost sensing for managing air pollution in cities

Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation.