Farmers tell us how to help improve their mental health help-seeking

Farmers’ mental health help-seeking is reported to be poor. Mental health help-seeking is seeking help from professionals such as GPs and psychologists for issues relating to distress or mental health (Rickwood & Thomas, 2012). Timely mental health help-seeking behaviour is important because it may minimise any negative outcomes. At present, there is no research that has identified how to target farmers to improve their mental health help-seeking. It is known that tailored approaches to intervention are superior and this is likely to be so for intervening with farmers whom have a strong culture and a vastly different situation than metropolitan populations. This study is part of a body of work exploring the factors that influence mental health help-seeking in farmers. Semi-structured interviews were conducted with 10 farmers (farming as their occupation) as well as 10 farmers’ partners (for their additional insight), all of whom resided/worked in Queensland. Braun and Clarke’s (2006) technique of thematic analysis was used to analyse the data. Based on the data three themes were developed regarding intervention: education (what needs to be taught and how to teach it), the medium (which mediums preferred and engagement with them) and multi-faceted programs (Many aspects important such as community input and role of GPs, family, and friends). This research improves the knowledge on how to target interventions, including the medium, specifically to farmers for mental health help-seeking. The findings could be utilised in the design process to create interventions that are more likely to have an impact, specific for farmers to improve their mental health help-seeking behaviour

Farmers are not seeking help: what does service provision have to do with it?

Aim The rate of suicide in farmers is twice that of the general population. Help-seeking from health professionals, if this occurs in a timely manner, can significantly minimise the negative consequences of mental ill-health. However, it has now been demonstrated that farmers as a group are reluctant to seek help for mental ill-health, which likely contributes to this problem. Previous research has demonstrated that General Practitioners are the most commonly visited health professional in rural farming areas, however, they are under-utilised as a means of seeking help. This research aimed to examine the potential barriers and facilitators of mental health help-seeking in farmers, that relate to the provision of service from the perspective of farmers. Methods The present research draws on findings from semi‐structured interviews with 10 farmers residing in Queensland. The techniques of Braun and Clarke (2006) were used to guide the thematic analysis. Results Several key factors relating to services were identified as having the potential to directly or indirectly influence mental health help-seeking. These include: how services are marketed/packaged and delivered, availability and accessibility, continuity of care, having ‘knowledgeable bush practitioners’ as well as perception of good outcomes. Conclusion It is expected that this research will create a better understanding of the farmers’ perspective relating to service provision for the purpose of seeking help for mental health. The outcomes have implications for developing and providing interventions for farmers to promote services for the purpose of mental health help-seeking as well as create awareness in service provider and other stakeholders of issues that prevent timely help-seeking

Deployment of churn prediction model in financial services industry

© 2016 IEEE. Nowadays, data analytics techniques are playing an increasingly crucial role in financial services due to the huge benefits they bring. To ensure a successful implementation of an analytics project, various factors and procedures need to be considered besides technical issues. This paper introduces some practical lessons from our deployment of a data analytics project in a leading wealth management company in Australia. Specifically, the process of building a customer churn prediction model is described. Besides common steps of data analysis, how to deal with other practical issues like data privacy and change management that are encountered by many financial companies are also introduced

Evaluation of a novel method for controlling bovine trypanosomiasis

The problem of controlling tsetse flies in Africa is an old one. The tsetse fly transmits the trypanosome parasites which cause sleeping sickness in humans and disease in cattle. Because cattle are a favoured food source for tsetse much work has been done looking at the use of insecticide treated cattle as a control strategy for the tsetse fly. Such treatment methods possess many advantages; they are safe and relatively environmentally benign, they can be applied by individual farmers without the need for logistically demanding and costly traditional control programmes and, in addition to tsetse flies the insecticides are effective against a wide range of other harmful cattle parasites. The cost of the insecticide is however a significant constraint to the number of livestock keepers who can afford to employ the technique and as a result many cattle remain untreated. Following the discovery that tsetse had a significant predilection for feeding on the legs and belly of cattle, it was hypothesised that restricting the insecticide to only those areas could offer comparable protection to treating the whole animal. Such an approach would use up to 80% less drug and thus make the treatment per animal much cheaper. In addition, preferentially targeting areas favoured by tsetse, and leaving the rest of the animal untreated, preserves some important ecological balances between cattle and their parasites which traditional treatment methods destabilise. This thesis describes the design, implementation and analysis of a longitudinal study run over 8 months in south east Uganda that sought to compare the effect of applying insecticide to cattle only on the regions favoured by tsetse flies. Cattle were recruited to the study and assigned one of four treatment groups; a whole body application of deltamethrin insecticide pour-on; a restricted application of deltamethrin spray, applied to the front legs, ears and belly; a prophylactic trypanocide injection of isometamidium chloride, and a control group, that received no further treatments. All animals in the study were however cleared using twin doses of a trypanocide diminazene aceturate at the start of the study

Digital Metastases of Giant Cell Rich Malignant Fibrous Histiocytoma

Background. Metastatic spread of soft tissue sarcomas to the digits is extremely rare and metastasis of MFH to the fingers and toes has not been documented

A Multiple Source based Transfer Learning Framework for Marketing Campaigns

© 2018 IEEE. The rapid growing number of marketing campaigns demands an efficient learning model to identify prospective customers to target. Transfer learning is widely considered as a major way to improve the learning performance by using the generated knowledge from previous learning tasks. Most recent studies focused on transferring knowledge from source domains to target domains which may result in knowledge missing. To avoid this, we proposed a multiple source based transfer learning framework to do it reversely. The data in target domains is transferred into source domains by normalizing them into the same distributions and then improving the learning task in target domains by its generated knowledge in source domains. The proposed method is general and can deal with supervised and unsupervised inductive and transductive learning simultaneously with a compatibility to work with different machine learning models. The experiments on real-world campaign data demonstrate the performance of the proposed method

Towards new ecologically relevant markers of health for cetaceans

Peer reviewedPublisher PD

Combining heterogeneous features for time series prediction

© 2017 IEEE. Time series prediction is a challenging task in reality, and various methods have been proposed for it. However, only the historical series of values are exploited in most of existing methods. Therefore, the predictive models might be not effective in some cases, due to: (1) the historical series of values is not sufficient usually, and (2) features from heterogeneous sources such as the intrinsic features of data samples themselves, which could be very useful, are not take into consideration. To address these issues, we proposed a novel method in this paper which learns the predictive model based on the combination of dynamic features extracted from series of historical values and static features of data samples. To evaluate the performance of our proposed method, we compare it with linear regression and boosted trees, and the experimental results validate our method's superiority

High resolution visualisation of tiemannite microparticles, essential in the detoxification process of mercury in marine mammals

RvH and AH are funded by the Net Zero Technology Centre and the University of Aberdeen, through their partnership with the UK National Decommissioning Centre, and DEFRA (ETPP-33/C10). RvH received additional funding from the University of Aberdeen under the interdisciplinary project funding and the internal funding to pump-prime interdisciplinary research and impact (CF10723-32). AH received additional funding from the UK Energy Research Centre research programme (UKERC-4, EP/S029575/1). CG is funded by Chevron through its Anchor Partnership with the UK National Decommissioning Centre. The Scottish Marine Animal Stranding Scheme is funded by Marine Scottland with additional support provided by the University of Glasgow.Peer reviewedPublisher PD