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Publication Years
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1587
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Category
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279
257
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Toolboxes
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JOURNAL OF THE ASSOCIATION OF NURSES IN AIDS CARE, Vol. 28, No. 2, March/April 2017, 186-198
http://dx.doi.org/10.1016/j.jana.2015.09.003
Contraceptive Dynamics Following HIV Testing - DHS Analytical Studies No. 47
MacQuarrie, Kerry L.D., Sarah E.K. Bradley, Alison Gemmill, and Sarah Staveteig
Rockville, Maryland, USA: ICF International
(2014)
CC
Contraceptive Dynamics Following HIV Testing
Child Survival by HIV Status of the Mother: Evidence from DHS and AIS Surveys. DHS Comparative Reports No. 35
Fishel, Joy D., Ruilin Ren, Bernard Barrère, and Trevor N. Croft
Maryland, USA: ICF International
(2014)
C2
DHS Analytical Studies No. 55.
CBM and the Global Campaign for Education 2014
AN ANALYSIS OF UNICEF MICS 3 SURVEY DATA FROM BANGLADESH, LAO PDR, MONGOLIA AND THAILAND
Pan African Medical Journal 2017;27:215. doi: 10.11604/pamj.2017.27.215.12994
This report investigates the impact of potential misclassification of samples on HIV prevalence estimates for 23 surveys conducted from 2010-2014. In addition to visual inspection of laboratory results, we examined how accounting for potential misclassification of HIV status through Bayesian latent
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class models affected the prevalence estimates. Two types of Bayesian models were specified: a model that only uses the individual dichotomous test results and a continuous model that uses the quantitative information of the EIA (i.e., the signal-to-cutoff values). Overall, we found that adjusted prevalence estimates matched the surveys’ original results, with overlapping uncertainty intervals. This suggested that misclassification of HIV status should not affect the prevalence estimates in most surveys. However, our analyses suggested that two surveys may be problematic. The prevalence could have been overestimated in the Uganda AIDS Indicator Survey 2011 and the Zambia Demographic and Health Survey 2013-14, although the magnitude of overestimation remains difficult to ascertain. Interpreting results from the Uganda survey is difficult because of the lack of internal quality control and potential violation of the multivariate normality assumption of the continuous Bayesian latent class model. In conclusion, despite the limitations of our latent class models, our analyses suggest that prevalence estimates from most of the surveys reviewed are not affected by sample misclassification.
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Lancet Glob Health 2018 Published Online September 12, 2018 http://dx.doi.org/10.1016/S2214-109X(18)30407-8
1. MYTH: Sexual violence is just another stressor in populations exposed to extreme stress: there is no need to do anything special to address sexual violence | 2. MYTH: The most important consequence of sexual violence is posttraumatic stress disorder (PTSD) | 3. MYTH. Concepts of mental disorders
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– such as depression and PTSD – and treatment for mental health problems have no relevance outside western cultures | 4. MYTH: All sexual violence survivors need help for mental health problems | 5. MYTH: Mental health and psychosocial supports should specifically target sexual violence survivors | 6. MYTH: Vertical (stand-alone) specialized services are a priority to meet the needs of sexual violence survivors | 7. MYTH: The most important support is specialized mental health care | 8. Only psychologists and psychiatrists can deliver services for sexual violence survivors | 9. MYTH: Any intervention is better than nothing | 10. MYTH: Only the victim/survivor suffers as a result of sexual violence
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Can J Anesth/J Can Anesth June 2018, Volume 65, Issue 6, pp 698–708
How Alcohol harm young people and what you can do about it
World Health Organization (Western Pacific Region)
(2015)
C_WHO
Tobacco control & the sustainable development goals
World Health Organization (Europe)
(2019)
C_WHO
Accessed: 15.03.2019
Developmental disorders
Chapter C.3