Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 6 de 6
Más filtros

Base de datos
Intervalo de año de publicación
Issues Ment Health Nurs ; 40(11): 951-956, 2019 Nov.
Artículo en Inglés | MEDLINE | ID: mdl-31381462


Mental health-care delivery to young people with first-episode schizophrenia presents significant challenges especially in underserved areas. This chart review reveals the importance of family support as a predictor for medication and treatment adherence with this vulnerable group. An unexpected disengagement rate of 47% was discovered. It was further discovered that receiving care with telehealth delivery was a significant predictor of lost to follow-up or treatment nonadherence. Recommendations include psychoeducation for families during the initial crisis, initiation of long-acting injectable antipsychotics early in care, a hybrid telehealth intervention with in-home medication delivery, and collaboration with educational, vocational county agencies for employment support. A system of care must be developed to support young people with this severe illness for optimum outcome and protection of long-term cognitive functioning.

Servicios de Salud Mental , Trastornos Psicóticos/prevención & control , Trastornos Psicóticos/terapia , Apoyo Social , Telemedicina , Cumplimiento y Adherencia al Tratamiento , Adolescente , Adulto , Factores de Edad , Familia , Femenino , Humanos , Masculino , Estudios Retrospectivos , Adulto Joven
Sleep ; 42(7)2019 07 08.
Artículo en Inglés | MEDLINE | ID: mdl-31281929


STUDY OBJECTIVES: The main objective for this study was to assess the association of adverse childhood experiences (ACEs) and subsequent short sleep duration among adults. METHODS: This cross-sectional examination used data from the 2011 Behavioral Risk Factor Surveillance System, a nationwide telephone-administered survey. Participants completed a standardized questionnaire to report childhood experiences of abuse, neglect, household challenges, and sleep time. Multinominal logistic regression analyses included survey weighting procedures and adjusted for age, race, education, income, sex, and body mass index; associations were also examined by age strata, using age as a proxy for time since ACEs occurred. RESULTS: Complete data were available for 22 403 adults (mean age = 46.66 years) including 14 587 (65%) with optimum sleep duration (7-9 h/night) and 2069 (9%) with short sleep duration (<6 h/night). Compared with adults with optimum sleep duration, the number of ACEs was associated with the odds of short sleep duration (odds ratio [OR] = 1.22, 95% CI = 1.16 to 1.28), and the odds increased as the number of ACEs increased. The association held for each decade of age until the 60s, although the magnitude attenuated. Mental health challenges or poor physical health did not account for the association. CONCLUSION: ACEs increased the odds of chronic short sleep duration during adulthood and showed both a time-dependent and dose-response nature. These associations were independent of self-reported mental health challenges or poor physical health. The association of ACEs with short sleep duration throughout the adult lifespan emphasizes the importance of child health and identifying underlying psychological challenges in adults with sleep difficulties.

Experiencias Adversas de la Infancia/estadística & datos numéricos , Maltrato a los Niños/psicología , Trastornos del Inicio y del Mantenimiento del Sueño/patología , Trastornos del Inicio y del Mantenimiento del Sueño/psicología , Adolescente , Adulto , Anciano , Sistema de Vigilancia de Factor de Riesgo Conductual , Índice de Masa Corporal , Niño , Estudios Transversales , Composición Familiar , Femenino , Humanos , Renta , Masculino , Salud Mental , Persona de Mediana Edad , Encuestas y Cuestionarios , Adulto Joven
Int J Biostat ; 14(2)2018 11 22.
Artículo en Inglés | MEDLINE | ID: mdl-30465718


Background Many researchers have studied the relationship between diet and health. Specifically, there are papers showing an association between the consumption of sugar sweetened beverages and Type 2 diabetes. Many meta-analyses use individual studies that do not attempt to adjust for multiple testing or multiple modeling. Hence the claims reported in a meta-analysis paper may be unreliable as the base papers do not ensure unbiased statistics. Objective Determine (i) the statistical reliability of 10 papers and (ii) indirectly the reliability of the meta-analysis study. Method We obtained copies of each of the 10 papers used in a metaanalysis paper and counted the numbers of outcomes, predictors, and covariates. We estimate the size of the potential analysis search space available to the authors of these papers; i. e. the number of comparisons and models available. The potential analysis search space is the number of outcomes times the number of predictors times 2 c , where c is the number of covariates. This formula was applied to information found in the abstracts (Space A) as well as the text (Space T) of each base paper. Results The median and range of the number of comparisons possible across the base papers are 6.5 and (2 12,288), respectively for Space A, and 196,608 and (3072-117,117,952), respectively for Space T. It is noted that the median of 6.5 for Space A may be misleading as each study has 60-165 foods that could be predictors. Conclusion Given that testing is at the 5% level and the number of comparisons is very large, nominal statistical significance is very weak support for a claim. The claims in these papers are not statistically supported and hence are unreliable so the meta-analysis paper is also unreliable.

Interpretación Estadística de Datos , Epidemiología/normas , Metaanálisis como Asunto , Fenómenos Fisiológicos de la Nutrición , Evaluación de Resultado en la Atención de Salud/normas , Humanos
Stat Med ; 36(26): 4230-4240, 2017 Nov 20.
Artículo en Inglés | MEDLINE | ID: mdl-28809042


The receiver operating characteristic (ROC) curve is frequently used to evaluate and compare diagnostic tests. As one of the ROC summary indices, the Youden index measures the effectiveness of a diagnostic marker and enables the selection of an optimal threshold value (cut-off point) for the marker. Recently, the overlap coefficient, which captures the similarity between 2 distributions directly, has been considered as an alternative index for determining the diagnostic performance of markers. In this case, a larger overlap indicates worse diagnostic accuracy, and vice versa. This paper provides a graphical demonstration and mathematical derivation of the relationship between the Youden index and the overlap coefficient and states their advantages over the most popular diagnostic measure, the area under the ROC curve. Furthermore, we outline the differences between the Youden index and overlap coefficient and identify situations in which the overlap coefficient outperforms the Youden index. Numerical examples and real data analysis are provided.

Biomarcadores , Pruebas Diagnósticas de Rutina , Modelos Estadísticos , Curva ROC , Área Bajo la Curva , Estudios de Casos y Controles , Simulación por Computador , Femenino , Humanos , Neoplasias Ováricas/genética
US Army Med Dep J ; (1-17): 23-33, 2017.
Artículo en Inglés | MEDLINE | ID: mdl-28511271


Zika virus (ZIKV) was declared an international public health emergency by the World Health Organization on February 1, 2016. Due to the known and estimated range of the ZIKV mosquito vectors, southern and central US states faced increased risk of ZIKV transmission. With the state of Georgia hosting the world's busiest international airport, a climate that supports the ZIKV vectors, and limited surveillance (13 counties) and response capacity, the Department of Public Health (DPH) was challenged to respond and prevent ZIKV transmission. This case study describes and evaluates the state's surveillance capacity before and after the declaration of ZIKV as a public health emergency. METHOD: We analyzed surveillance data from the DPH to compare the geographical distribution of counties conducting surveillance, total number, and overall percentage of mosquito species trapped in 2015 to 2016. Counties conducting surveillance before and after the identification of the ZIKV risk were mapped using ArcMap 10.4.1. Using SAS (version 9.2) (SAS Institute, Inc, Cary, NC), we performed the independent 2 sample t test to test for differences in prevalence in both years, and a χ² analysis to test for differences between numbers of species across the 13 counties. In addition, weighted frequency counts of mosquitoes were used to test (χ²) an association between major mosquito vector species and 7 urban counties. Lastly, using data from 2012-2016, a time-trend analysis was conducted to evaluate temporal trends in species prevalence. RESULTS: From 2015 to 2016, surveillance increased from 13 to 57 (338% increase) counties geographically dispersed across Georgia. A total of 76,052 mosquitoes were trapped and identified in 2015 compared to 144,731 (90.3% increase) in 2016. Significant differences between species (P<.001) and significant associations (P<.0001) between 7 urban counties and major mosquito vectors were found. Significant differences in prevalence were found between several species and year highlighting species-year temporal trends. CONCLUSIONS: The DPH collaborative response to ZIKV allowed a rapid increase in its surveillance footprint. Existing and new partnerships were developed with the military and local health departments to expand and share data. This additional surveillance data allowed DPH to make sound public health decisions regarding mosquito-borne disease risks and close gaps in data related to vector distribution.

Culicidae , Monitoreo Epidemiológico , Control de Mosquitos/métodos , Mosquitos Vectores , Distribución Animal , Animales , Georgia , Humanos , Virus Zika