19683 research outputs found
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Early Drinking Onset and Subsequent Alcohol Use in Late Adolescence: a Longitudinal Study of Drinking Patterns
No full textPurpose: The age of drinking onset is a central concept for both policy and prevention of alcohol-related harm, yet evidence on the predictive value of the age of onset is lacking. This study compares alcohol outcomes of adolescents who started to drink early with those who started later, and tests if associations are moderated by other explanatory factors. Methods: Data from a two-wave longitudinal prospective cohort survey with a Swedish nationwide sample of 4,018 adolescents aged 15/16 years at baseline (T1) and 17/18 years at follow-up (T2) were used. Outcome variables at T2 were Alcohol Use Disorders Identification Test (AUDIT)–C, risky drinking, and binge drinking monthly or more often. A vast number of explanatory factors at T1 were controlled for. Results: Early drinking onset predicted later higher AUDIT-C scores (β = 0.57, p value < .001), and higher probability of risky drinking (odds ratio = 1.95, 95% confidence interval = 1.56–2.44), and binge drinking (odds ratio = 1.38, confidence interval = 1.06–1.81), controlled for other explanatory factors. If binge drinking frequency at T1 was included, the associations remained for AUDIT-C and risky drinking, but not for binge drinking at T2. No significant interactions between early drinking onset and the explanatory factors were found. Discussion: Early drinking onset predicts subsequent higher alcohol consumption in late adolescence. Adolescents who had an early drinking onset drank more after 2 years than their peers who started later. The age of drinking onset is an independent predictor of alcohol use outcomes, beyond the effect of age of binge drinking onset
Ontology and its double: on the nature of ambiguity and lived experience
No full textNo description supplied.</p
Clinician perspectives on voluntary assisted dying and willingness to be involved: a multisite, cross-sectional survey during implementation in New South Wales, Australia
No full textBackground: In the context of nationwide law reform, New South Wales (NSW) became the last state in Australia to legalise voluntary assisted dying (VAD) – commencing 28 November 2023. Clinicians have divergent views regarding VAD, with varying levels of understanding, support, and willingness to be involved, and these may have a significant impact on the successful implementation. Aims: To understand levels of support, understanding and willingness to be involved in VAD among clinical staff across NSW during implementation of VAD. Methods: A multisite, cross-sectional online survey of clinicians across four local health districts, assessing relevant demographics, awareness of and support for VAD legislation and willingness to be involved in different levels of VAD-related clinical activities. Results: A total of 3010 clinical staff completed the survey. A majority of participants were aware of VAD legislation in NSW (86.35%) and supportive of it (76%), with nursing and allied health clinicians significantly more likely than medical specialists to express support. Among medical specialists, support was statistically more likely in those who did not care for patients at the end of life and those with limited knowledge of the legislation. Willingness of medical specialists to perform key roles was significantly lower, with 41.49% willing to act in coordinating or consulting roles, and only 23.21% as administering practitioners. Conclusions: The majority of clinical staff surveyed across NSW supported VAD legislation. While many eligible clinicians were reluctant to be actively involved, sufficient numbers appear willing to provide VAD services, indicating that successful implementation should be possible
The Effect of a 12 Week Mixed-Modality Training Intervention on the Cardio-Metabolic Health of Rotational Shift Workers
No full textPurpose: To assess the effect of a 12 week resistance or aerobic training intervention on markers of cardio-metabolic function and sleep among male rotational shift workers. Method: Thirty-eight sedentary, apparently healthy, male rotational shift workers were recruited and randomly allocated to a non-exercise control (CON) group, 3 sessions/week of moderate intensity continuous (MICT), or resistance training (RT) for 12 weeks in a semi-supervised setting. Pre- and post-testing assessed markers of cardio-metabolic function including peak oxygen uptake (VO2peak), glucose metabolism, insulin sensitivity, body composition, inflammatory markers, and 14 day actigraphy sleep assessment. Results: Mean session attendance across the intervention was 25 (± 7) of a possible 36 sessions. A significant group by time interaction was observed for MICT, with lower c-reactive protein (CRP) values observed post-training (P = 0.049). A significant effect for time was observed for both MICT (n = 9; P = 0.04) and RT (n = 10; P = 0.021), increasing total sleep time (TST) following a night shift post-intervention. Data redistribution regarding exercise adherence: </p
Comparison of mindfulness training and acceptance and commitment therapy in a workplace setting: results from a randomized controlled trial
No full textMindfulness interventions have become a common feature of worksite stress management provision. However, the evidence underpinning these interventions continues to attract scrutiny, with unresolved questions surrounding: the generalizability of mindfulness research findings to real-world workplace training applications, comparability of different mindfulness approaches offered in workplace settings, and effects on job performance. The current trial contributes to the literature by exploring effects of mindfulness training (MT) and acceptance and commitment therapy (ACT), which were delivered to staff in the same healthcare organization. Participants were randomly assigned to a 4-session MT program (n = 63), a 4-session ACT program (n = 67), or a waiting list control group (n = 69). Study measures were administered on five occasions spread across a 6-month period. Results indicated that both MT and ACT reduced perceived stress and improved mindfulness and sleep quality when compared to the control group. ACT showed slight superiority in helping employees align their behaviour with personal values. Neither MT nor ACT was effective in reducing work limitations. We consider explanations for equivocal effects on job performance outcomes, and highlight the importance of testing the effectiveness of worksite mindfulness interventions under ecologically valid conditions.</p
Combining ‘sex-as-dirty work’ and ‘CMM’ frameworks for recruiting cisgender, heterosexual men for a study on sex, sexuality, and intimacy
No full textRecruiting cisgender, heterosexual young men for research participation can be a difficult endeavour. This is more challenging with qualitative research studies that require substantial time commitment, or be of a sensitive nature, such as discussions of sex, intimacy, and emotion. These challenges can be amplified with the shift to online data collection procedures due to COVID-19. In this paper I reflect on the process of recruiting cisgender, heterosexual men for a qualitative study on sex and intimacy that relied solely on online advertising during the ongoing COVID-19 pandemic. I build on a critical men and masculinity (CMM) studies framework by considering a ‘sex-as-dirty-work’ approach which centres the uncomfortable practice of talking about and researching sex. I highlight the success of this approach that counters recommended best practice in getting men to participate. I conclude with a discussion of the implications of this approach, and suggestions for researchers
The Australian Traumatic Brain Injury Initiative: Review and Recommendations for Outcome Measures for Use With Adults and Children After Moderate-to-Severe Traumatic Brain Injury
No full textThe Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to select a set of measures to comprehensively predict and assess outcomes following moderate-to-severe traumatic brain injury (TBI) across Australia. The aim of this article was to report on the implementation and findings of an evidence-based consensus approach to develop AUS-TBI recommendations for outcome measures following adult and pediatric moderate-to-severe TBI. Following consultation with a panel of expert clinicians, Aboriginal and Torres Strait Islander representatives and a Living Experience group, and preliminary literature searches with a broader focus, a decision was made to focus on measures of mortality, everyday functional outcomes, and quality of life. Standardized searches of bibliographic databases were conducted through March 2022. Characteristics of 75 outcome measures were extracted from 1485 primary studies. Consensus meetings among the AUS-TBI Steering Committee, an expert panel of clinicians and researchers and a group of individuals with lived experience of TBI resulted in the production of a final list of 11 core outcome measures: the Functional Independence Measure (FIM); Glasgow Outcome Scale-Extended (GOS-E); Satisfaction With Life Scale (SWLS) (adult); mortality; EuroQol-5 Dimensions (EQ5D); Mayo-Portland Adaptability Inventory (MPAI); Return to Work /Study (adult and pediatric); Functional Independence Measure for Children (WEEFIM); Glasgow Outcome Scale Modified for Children (GOS-E PEDS); Paediatric Quality of Life Scale (PEDS-QL); and Strengths and Difficulties Questionnaire (pediatric). These 11 outcome measures will be included as common data elements in the AUS-TBI data dictionary. Review Registration PROSPERO (CRD42022290954)
Insects as radar targets: size, form, density and permittivity
No full textTo make biologically useful interpretations of the echo signals from an entomological radar (a radar designed and operated to observe insects in flight), it is necessary to relate basic properties of insects (i.e. their mass, size, and form) to their radio-wave scattering characters–e.g. their radar cross-section (RCS) and its variation with aspect or beam polarization. Measurements of RCSs of live or freshly dead specimens in laboratory rigs have played an important role in establishing such relationships, but it is desirable to develop and validate methods employing numerical computation, using electromagnetic calculation software, as a more widely applicable and generalizable alternative. In such computations, the insect is represented by a model with specified size, form, and composition; composition appears as the complex relative permittivity, with both polarizability (real) and loss (imaginary) terms. As a preliminary to investigating how adequately different types of electromagnetic model perform, we have collected and analysed morphometric data on adult, flight-capable specimens of a wide range of insect species, including many known to be migratory and to fly at heights where they would be detectable by radar. Our analyses reveal that appropriate densities for prolate-spheroid models of flying insects are in the range 0.60–0.76 g cm−3, which is about half that measured for air-free samples of the solids and liquids from which insect bodies are formed. From this, appropriate permittivities for the material filling the model are found to be in the range 7–11 (real component) and 2.0–3.5 (imaginary); again, these are much lower than measured values for pure insect-body material. These results enable construction of simple electromagnetic models of insects in which both spatial dimensions and masses are accurate. Computation of model RCSs and their aspect and polarization variations, and comparison of these with laboratory measurements, will be the topic of a follow-up validation study
Climate Shifts: The Impacts on Albury-Wodonga's Freshwater Tourism
No full textThis study used a phenomenological approach to understand how Albury-Wodonga businesses, organisations, and clubs with direct and indirect involvement in freshwater tourism have experienced and adapted to a changing climate. Participants reflected on their personal histories of connecting with local waterways and green spaces. They highlighted the impacts of climate events such as floods, bushfires, droughts, and extreme heat on their operations and outlined adaptation strategies. This included diversification of activities, changes in operational schedules, and preparations for extreme weather events. However, challenges in accessing information and coordinating with government agencies were evident. Bridging the gap in understanding and developing adaptive strategies are crucial steps to safeguarding the region’s freshwater tourism industry. However, while individual and industry adaptation is important, it does not take away our over-riding responsibility to address the root causes of climate change and navigate the complexities of water management politics.</p
UAV remote sensing phenotyping of wheat collection for response to water stress and yield prediction using machine learning
No full textWater stress is a significant challenge for global food production. Rainfall pattern is becoming unpredictable due to climate change that causes unprecedent water stress conditions in cereals production including wheat which is one of the important staple food crops. To sustain wheat production under water limiting conditions, there is an urgent need to develop drought-tolerant wheat varieties. For this, screening large numbers of wheat genotype for traits related to growth and yield under water stressed conditions is crucial. In this study, we deployed high-throughput phenotyping approaches, including uncrewed aerial vehicle (UAV)-based multispectral imaging, advanced machine and deep learning regression models. Two separate field experiments, irrigated and rainfed, were conducted comprising 553 wheat genotypes, and collected dataset for traits such as plant height, phenology, grain yield, and timeseries multispectral imaging. UAV-multispectral imagery derived plant height measurements showed a high correlation (R2=0.75) with manual measurements. Vegetation indices derived from multispectral data differentiated growth pattern of genotypes under rainfed and irrigated conditions and were used in yield prediction modeling. Wheat genotypes were effectively ranked, and their response differentiated for water stress tolerance based on yield index, stress susceptibility index, and yield loss%. Importantly, yield prediction in genotypes was computed using four machine learning regression algorithms i.e., linear regression, support vector machine, random forest, and deep learning H2O-3, where H2O-3 was the most accurate model with R2=0.80. Results show that multispectral-driven traits combined with machine learning models effectively phenotyped large wheat population and such approaches can be integrated in crop breeding program to develop varieties tolerant to water stress