1,729 research outputs found

    The Effect of Agricultural Growing Season Change on Market Prices in Africa

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    Local agricultural production is a key element of food security in many agricultural countries in Africa. Climate change and variability is likely to adversely affect these countries, particularly as they affect the ability of smallholder farmers to raise enough food to feed themselves. Seasonality influences farmers' decisions about when to sow and harvest, and ultimately the success or failure of their crops. At a 2009 conference in the United Kingdom hosted by the Institute of Development Studies, Jennings and Magrath (2009) described farmer reports from East Asia, South Asia, Southern Africa, East Africa and Latin America. Farmers indicate significant changes in the timing of rainy seasons and the pattern of rains within seasons, including: More erratic rainfall, coming at unexpected times in and out of season; Extreme storms and unusually intense rainfall are punctuated by longer dry spells within the rainy season; Increasing uncertainty as to the start of rainy seasons in many areas; Short or transitional second rainy seasons are becoming stronger than normal or are disappearing altogether. These farmer perceptions of change are striking in that they are geographically widespread and are remarkably consistent across diverse regions (Jennings and Magrath, 2009). The impact of these changes on farmers with small plots and few resources is large. Farming is becoming riskier because of heat stress, lack of water, pests and diseases that interact with ongoing pressures on natural resources. Lack of predictability in the start and length of the growing season affects the ability of farmers to invest in appropriate fertilizer levels or improved, high yielding varieties. These changes occur at the same time as the demand for food is rising and is projected to continue to rise for the next fifty years (IAASTD, 2008). Long-term data records derived from satellite remote sensing can be used to verify these reports, providing necessary analysis and documentation required to plan effective adaptation strategies. Remote sensing data can also provide some understanding of the spatial extent of these changes and whether they are likely to continue. Given the agricultural nature of most economies on the African continent, agricultural production continues to be a critical determinant of both food security and economic growth (Funk and Brown, 2009). Crop phenological parameters, such as the start and end of the growing season, the total length of the growing season, and the rate of greening and senescence are important for planning crop management, crop diversification, and intensification. The World Food Summit of 1996 defined food security as: "when all people at all times have access to sufficient, safe, nutritious food to maintain a healthy and active life". Food security roughly depends on three factors: 1) availability of food; 2) access to food and 3) appropriate use of food, as well as adequate water and sanitation. The first factor is dependent on growing conditions and weather and climate. In a previous paper we have investigated this factor by evaluating the effect of large scale climate oscillation on land surface phenology (Brown et al., 2010). We found that all areas in Africa are significantly affected by at least one type of large scale climate oscillations and concluded that these somewhat predictable oscillations could perhaps be used to forecast agricultural production. In addition, we have evaluated changes in agricultural land surface phenology over time (Brown et al., 2012). We found that land surface phenology models, which link large-scale vegetation indices with accumulated humidity, could successfully predict agricultural productivity in several countries around the world. In this chapter we are interested in the effect of variability in peak timing of the growing season, or phenology, on the second factor of food security, food access. In this chapter we want to determine if there is a link between market prices and land surface phenology and to determine which markets are vulnerable to land surface phenology changes and variability and which market prices are not correlated

    Effectiveness of web-based guided self-help cognitive behavioral therapy-enhanced for binge-eating disorder:An implementation study

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    Introduction: Web-based guided self-help cognitive behavioral therapy-enhanced (CBT-E) is a 12-weeks, 12-sessions, digitalized version of part II of the self-help book Overcoming Binge Eating. This intervention is effective when offered under controlled circumstances in a randomized-controlled-trial. It is unknown how patients with binge-eating disorder (BED) respond to this intervention when offered in real-world clinical-settings. The aim of this study is to examine post-intervention effectiveness of guided self-help CBT-E for BED in real-world settings.Method: The present study used a cohort-design examining the effectiveness of web-based guided self-help CBT-E according to an intention-to-treat (ITT) analysis. BED patients (n = 278) were assessed pre- and post-intervention. The primary outcome was reduction in binge-eating episodes. Other outcomes were full-recovery (EDE-Q score <2.77 and abstinence from binge-eating episodes), impaired psychosocial functioning, defined as secondary impairment, and general psychopathology post-intervention.Results: The number of binge-eating episodes reduced by an average of 16 binge-eating episodes per 4 weeks pre-intervention to five binge-eating episodes during the last 4 weeks of treatment. Abstinence from binge eating was reported by 30%, and 28% reported full recovery. Effect sizes (Cohen's d) were large (d >= 1.0) for all outcome measures. There were no differences in outcomes between the ITT and the completers sample.Discussion: Guided self-help CBT-E is associated with significant improvements. The effects of guided self-help CBT-E offered in a real-world-setting are comparable to self-help CBT-E offered in a randomized-controlled-trial. However, it should be noted that comparisons with randomized-controlled-trials requires caution. Longer-term follow-up data are necessary to measure persistence of treatment benefits.Public Significance: Offering CBT-E as a web-based guided self-help intervention has several benefits for patients with BED. Guided self-help CBT-E is associated with significant improvements on the short term when offered in real-world clinical settings

    The Response of African Land Surface Phenology to Large Scale Climate Oscillations

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    Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the African continent. Analysis of changes in phenology can provide quantitative information on the effect of climate variability on growing seasons in agricultural regions. Using a robust statistical methodology, we describe the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), and the Multivariate ENSO Index (MEI). We map the most significant positive and negative correlation for the four climate indices in Eastern, Western and Southern Africa between two phenological metrics and the climate indices. Our objective is to provide evidence of whether climate variability captured in the four indices has had a significant impact on the vegetative productivity of Africa during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by large scale variations in climate. The particular climate index and the timing showing highest correlation depended heavily on the region examined. In Western Africa the cumulative NDVI correlates with PDO in September-November. In Eastern Africa the start of the June-October season strongly correlates with PDO in March-May, while the PDO in December-February correlates with the start of the February-June season. The cumulative NDVI over this last season relates to the MEI of March-May. For Southern Africa, high correlations exist between SOS and NAO of September-November, and cumulative NDVI and MEI of March-May. The research shows that climate indices can be used to anticipate late start and variable vigor in the growing season of sensitive agricultural regions in Africa

    Reliability and validity of the Dutch dimensional assessment of personality pathology-short form(DAPP-SF), a shortened version of the DAPP-Basic questionnaire

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    The Dimensional Assessment of Personality Pathology-Basic Questionnaire (DAPP-BQ) appears to be a good choice for the assessment of personality pathology. However, due to its length, administration of the instrument is rather time-consuming, hindering standard inclusion of the DABB-BQ in a battery of assessment instruments at intake. We developed the 136-item DAPP-SF (Short Form), and investigated its psychometric characteristics in various samples, i.e., a community-based sample (n = 487), patients with mood-, anxiety-, and somatoform disorders (n = 1,329), and patients with personality disorders (n = 1,393). Results revealed high internal consistency for almost all dimensions. The factor structure appeared almost identical as compared to the factor structure of the original DAPP-BQ, and was shown to be invariant across the various patient and community samples. Indices for convergent, discriminant and criterion related validity were satisfactory. It is concluded that the good psychometric characteristics of the original DAPP-BQ were preserved in the shortened version of the instrument

    Dissociative style and directed forgetting.

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    Dissociative style may correspond to an enhanced ability to avoid conscious recollection of traumatic experiences, which may, however, remain dormant in nonconscious memory. This hypothesis was tested in two "directed-forgetting" experiments with affectively neutral words (experiment 1) and sex and threat words (experiment 2) employing a total of 83 first-year psychology students high and low in dissociative style, and 14 dissociative patients. Conscious and nonconscious memory were separated with the process dissociation procedure (L. L. Jacoby, 1991). Instruction to forget was expected to reduce conscious but to enhance nonconscious memory performance in Ss with a high dissociative ability. Results were opposite to predictions. Particularly for sex words, the instruction to forget raised the overall (conscious and nonconscious) memory performance of the patients. An alternative construction hypothesis is proposed that identifies dissociative style with enhanced skills of constructing conscious experiences

    Estimate risk difference and number needed to treat in survival analysis

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    The hazard ratio (HR) is a measure of instantaneous relative risk of an increase in one unit of the covariate of interest, which is widely reported in clinical researches involving time-to-event data. However, the measure fails to capture absolute risk reduction. Other measures such as number needed to treat (NNT) and risk difference (RD) provide another perspective on the effectiveness of an intervention, and can facilitate clinical decision making. The article aims to provide a step-by-step tutorial on how to compute RD and NNT in survival analysis with R. For simplicity, only one measure (RD or NNT) needs to be illustrated, because the other measure is a reverse of the illustrated one (NNT=1/RD). An artificial dataset is composed by using the survsim package. RD and NNT are estimated with Austin method after fitting a Cox-proportional hazard regression model. The confidence intervals can be estimated using bootstrap method. Alternatively, if the standard errors (SEs) of the survival probabilities of the treated and control group are given, confidence intervals can be estimated using algebraic calculations. The pseudo-value model provides another method to estimate RD and NNT. Details of R code and its output are shown and explained in the main text
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