Willingness to work in rural areas and the role of intrinsic versus extrinsic professional motivations - a survey of medical students in Ghana

<p>Abstract</p> <p>Background</p> <p>Retaining health workers in rural areas is challenging for a number of reasons, ranging from personal preferences to difficult work conditions and low remuneration. This paper assesses the influence of intrinsic and extrinsic motivation on willingness to accept postings to deprived areas among medical students in Ghana.</p> <p>Methods</p> <p>A computer-based survey involving 302 fourth year medical students was conducted from May-August 2009. Logistic regression was used to assess the association between students' willingness to accept rural postings and their professional motivations, rural exposure and family parental professional and educational status (PPES).</p> <p>Results</p> <p>Over 85% of students were born in urban areas and 57% came from affluent backgrounds. Nearly two-thirds of students reported strong intrinsic motivation to study medicine. After controlling for demographic characteristics and rural exposure, motivational factors did not influence willingness to practice in rural areas. High family PPES was consistently associated with lower willingness to work in rural areas.</p> <p>Conclusions</p> <p>Although most Ghanaian medical students are motivated to study medicine by the desire to help others, this does not translate into willingness to work in rural areas. Efforts should be made to build on intrinsic motivation during medical training and in designing rural postings, as well as favour lower PPES students for admission.</p

For money or service? a cross-sectional survey of preference for financial versus non-financial rural practice characteristics among ghanaian medical students

Abstract Background Health worker shortage and maldistribution are among the biggest threats to health systems in Africa. New medical graduates are prime targets for recruitment to deprived rural areas. However, little research has been done to determine the influence of workers' background and future plans on their preference for rural practice incentives and characteristics. The purpose of this study was to identify determinants of preference for rural job characteristics among fourth year medical students in Ghana. Methods We asked fourth-year Ghanaian medical students to rank the importance of rural practice attributes including salary, infrastructure, management style, and contract length in considering future jobs. We used bivariate and multivariate ordinal logistic regression to estimate the association between attribute valuation and students' socio-demographic background, educational experience, and future career plans. Results Of 310 eligible fourth year medical students, complete data was available for 302 students (97%). Students considering emigration ranked salary as more important than students not considering emigration, while students with rural living experience ranked salary as less important than those with no rural experience. Students willing to work in a rural area ranked infrastructure as more important than students who were unwilling, while female students ranked infrastructure as less important than male students. Students who were willing to work in a rural area ranked management style as a more important rural practice attribute than those who were unwilling to work in a rural area. Students studying in Kumasi ranked contract length as more important than those in Accra, while international students ranked contract length as less important than Ghanaian students. Conclusions Interventions to improve rural practice conditions are likely to be more persuasive than salary incentives to Ghanaian medical students who are willing to work in rural environments a priori. Policy experiments should test the impact of these interventions on actual uptake by students upon graduation.http://deepblue.lib.umich.edu/bitstream/2027.42/112499/1/12913_2011_Article_1837.pd

Anopheles larval abundance and diversity in three rice agro-village complexes Mwea irrigation scheme, central Kenya

<p>Abstract</p> <p>Background</p> <p>The diversity and abundance of <it>Anopheles </it>larvae has significant influence on the resulting adult mosquito population and hence the dynamics of malaria transmission. Studies were conducted to examine larval habitat dynamics and ecological factors affecting survivorship of aquatic stages of malaria vectors in three agro-ecological settings in Mwea, Kenya.</p> <p>Methods</p> <p>Three villages were selected based on rice husbandry and water management practices. Aquatic habitats in the 3 villages representing planned rice cultivation (Mbui Njeru), unplanned rice cultivation (Kiamachiri) and non-irrigated (Murinduko) agro-ecosystems were sampled every 2 weeks to generate stage-specific estimates of mosquito larval densities, relative abundance and diversity. Records of distance to the nearest homestead, vegetation coverage, surface debris, turbidity, habitat stability, habitat type, rice growth stage, number of rice tillers and percent <it>Azolla </it>cover were taken for each habitat.</p> <p>Results</p> <p>Captures of early, late instars and pupae accounted for 78.2%, 10.9% and 10.8% of the total <it>Anopheles </it>immatures sampled (n = 29,252), respectively. There were significant differences in larval abundance between 3 agro-ecosystems. The village with 'planned' rice cultivation had relatively lower <it>Anopheles </it>larval densities compared to the villages where 'unplanned' or non-irrigated. Similarly, species composition and richness was higher in the two villages with either 'unplanned' or limited rice cultivation, an indication of the importance of land use patterns on diversity of larval habitat types. Rice fields and associated canals were the most productive habitat types while water pools and puddles were important for short periods during the rainy season. Multiple logistic regression analysis showed that presence of other invertebrates, percentage <it>Azolla </it>cover, distance to nearest homestead, depth and water turbidity were the best predictors for <it>Anopheles </it>mosquito larval abundance.</p> <p>Conclusion</p> <p>These results suggest that agricultural practices have significant influence on mosquito species diversity and abundance and that certain habitat characteristics favor production of malaria vectors. These factors should be considered when implementing larval control strategies which should be targeted based on habitat productivity and water management.</p

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Forecasting volatility in bitcoin market

First published online: June 2020In this paper, we revisit the stylized facts of bitcoin markets and propose various approaches for modeling the dynamics governing the mean and variance processes. We first provide the statistical properties of our proposed models and study in detail their forecasting performance and adequacy by means of point and density forecasts. We adopt two loss functions and the model confidence set test to evaluate the predictive ability of the models and the likelihood ratio test to assess their adequacy. Our results confirm that bitcoin markets are characterized by regime shifting, long memory and multifractality. We find that the Markov switching multifractal and FIGARCH models outperform other GARCH-type models in forecasting bitcoin returns volatility. Furthermore, combined forecasts improve upon forecasts from individual models

Small Cell Carcinoma of the Uterine Cervix in a Pregnant Patient Diagnosed with Liquid Based Cytology and Cell Block Immunocytochemistry

Definitive cytomorphologic diagnosis of small cell carcinoma of the uterine cervix is possible but can be challenging in routine cervicovaginal cancer screening specimens. Several small series of reported cases of cervical small cell carcinoma have shown this uncommon malignancy to represent fewer than 2% of all invasive cervical cancers. This tumor type is associated with poor prognosis and rapid disease progression and can develop to an advanced stage in the interval between screening visits. Only rare case reports of small cell carcinoma arising in gravid cervices are known. In the current case a 29-year-old, gravida 6, para 2, pregnant (10-week gestation) female presented with postcoital bleeding. A definitive diagnosis of small cell carcinoma of the cervix was made possible by liquid based Pap testing with ancillary cell block preparation allowing for immunocytochemical characterization of the lesional cell population

Forecasting inflation uncertainty in the G7 countries

Published: 27 April 2018There is substantial evidence that inflation rates are characterized by long memory and nonlinearities. In this paper, we introduce a long-memory Smooth Transition AutoRegressive Fractionally Integrated Moving Average-Markov Switching Multifractal specification [STARFIMA (p, d, q)-MSM (k)] for modeling and forecasting inflation uncertainty. We first provide the statistical properties of the process and investigate the finite sample properties of the maximum likelihood estimators through simulation. Second, we evaluate the out-of-sample forecast performance of the model in forecasting inflation uncertainty in the G7 countries. Our empirical analysis demonstrates the superiority of the new model over the alternative STARFIMA (p, d, q)-GARCH-type models in forecasting inflation uncertainty

Perceived barriers and motivating factors influencing student midwives’ acceptance of rural postings in Ghana

<p>Abstract</p> <p>Background</p> <p>Research on the mal-distribution of health care workers has focused mainly on physicians and nurses. To meet the Millennium Development Goal Five and the reproductive needs of all women, it is predicted that an additional 334,000 midwives are needed. Despite the on-going efforts to increase this cadre of health workers there are still glaring gaps and inequities in distribution. The objectives of this study are to determine the perceived barriers and motivators influencing final year midwifery students’ acceptance of rural postings in Ghana, West Africa.</p> <p>Methods</p> <p>An exploratory qualitative study using focus group interviews as the data collection strategy was conducted in two of the largest midwifery training schools in Ghana<b>.</b> All final year midwifery students from the two training schools were invited to participate in the focus groups. A purposive sample of 49 final year midwifery students participated in 6 focus groups. All students were women. Average age was 23.2 years. Glaser’s constant comparative method of analysis was used to identify patterns or themes from the data.</p> <p>Results</p> <p>Three themes were identified through a broad inductive process: 1) social amenities; 2) professional life; and 3) further education/career advancement. Together they create the overarching theme, <it>quality of life</it>, we use to describe the influences on midwifery students’ decision to accept a rural posting following graduation.</p> <p>Conclusions</p> <p>In countries where there are too few health workers, deployment of midwives to rural postings is a continuing challenge. Until more midwives are attracted to work in rural, remote areas health inequities will exist and the targeted reduction for maternal mortality will remain elusive.</p