20 resultados para Multivariate Adaptive Regression Splines (MARS)


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Abstract Background: Little is known about how sitting time, alone or in combination with markers of physical activity (PA), influences mental well-being and work productivity. Given the need to develop workplace PA interventions that target employees’ health related efficiency outcomes; this study examined the associations between self-reported sitting time, PA, mental well-being and work productivity in office employees. Methods: Descriptive cross-sectional study. Spanish university office employees (n = 557) completed a survey measuring socio-demographics, total and domain specific (work and travel) self-reported sitting time, PA (International Physical Activity Questionnaire short version), mental well-being (Warwick-Edinburg Mental Well-Being Scale) and work productivity (Work Limitations Questionnaire). Multivariate linear regression analyses determined associations between the main variables adjusted for gender, age, body mass index and occupation. PA levels (low, moderate and high) were introduced into the model to examine interactive associations. Results: Higher volumes of PA were related to higher mental well-being, work productivity and spending less time sitting at work, throughout the working day and travelling during the week, including the weekends (p < 0.05). Greater levels of sitting during weekends was associated with lower mental well-being (p < 0.05). Similarly, more sitting while travelling at weekends was linked to lower work productivity (p < 0.05). In highly active employees, higher sitting times on work days and occupational sitting were associated with decreased mental well-being (p < 0.05). Higher sitting times while travelling on weekend days was also linked to lower work productivity in the highly active (p < 0.05). No significant associations were observed in low active employees. Conclusions: Employees’ PA levels exerts different influences on the associations between sitting time, mental well-being and work productivity. The specific associations and the broad sweep of evidence in the current study suggest that workplace PA strategies to improve the mental well-being and productivity of all employees should focus on reducing sitting time alongside efforts to increase PA.

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Background: Scientific evidence on treatments of chronic diseases in patients 85 years old or older is very limited, as is available information on inappropriate prescription (IP) and its associated factors. The study aimed to describe medicine prescription, potentially inappropriate medicines (PIM) and potentially prescribing omissions (PPO) and their associated factors on this population. Methods: In the context of an observational, prospective and multicentric study carried out in elderly patients admitted to seven Spanish hospitals for a year, a sub-analysis of those aged 85 years and over was performed. To assess PIMs, the Beers and STOPP criteria were used, and to assess PPOs, the START and the ACOVE-3 criteria were used. To assess factors associated with IP, a multivariate logistic regression analysis was performed. Patients were selected randomly every week on consecutive days from the hospitalization lists. Results: A total of 336 patients were included in the sub-analysis with a median (Q1-Q3) age of 88 (8690) years. The median medicines taken during the month prior to admission was 10 (713). Forty-seven point two per cent of patients had at least one Beers-listed PIM, 63.3% at least one STOPP-listed PIM, 53.6% at least one START-listed PPO, and 59.4% at least one ACOVE-3-listed PPO. Use of benzodiazepines in patients who are prone to falls (18.3%) and omission of calcium and vitamin D supplements in patients with osteoporosis (13.3%) were the most common PIM and PPO, respectively. The main factor associated with the Beers-listed and the STOPP-listed PIM was consumption of 10 or more medicines (OR = 5.7, 95% CI 1.8-17.9 and OR = 13.4, 95% CI 4.0-44.0, respectively). The main factors associated with the START-listed PPO was a non-community dwelling origin (OR 2.3, 95% CI 1.0-5.0), and multimorbidity (OR1.8, 95% CI 1.0-3.1). Conclusions: Prescribed medicines and PIM and PPO prevalence were high among patients 85 years and over. Benzodiazepine use in those who are prone to falls and omission of calcium and vitamin D in those with osteoporosis were the most frequent PIM and PPO, respectively. Factors associated with PIM and PPO differed with polypharmacy being the most important factor associated with PIM.

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Objetivo: Determinar la percepción de trabajadores de distintos sectores empresariales de Colombia sobre los factores psicosociales presentes en su entorno laboral y la relación entre los factores psicosociales nocivos y los síntomas subjetivos y alteraciones de la salud. Materiales y métodos: Estudio no experimental, transversal y cuantitativo. Participaron 370 trabajadores, de diferentes sectores empresariales de Colombia (Centro-Oriente, Suroccidente y región Caribe). Instrumento: batería para el estudio de las condiciones de trabajo de carácter psicosocial (CTCPS-MAC), validada para población iberoamericana, permite evaluar cuatro dimensiones: Contexto de trabajo, Contenido de trabajo, Factores individuales y Desgaste psíquico e incluye catorce factores psicosociales. Los datos se analizaron con IBM SPSS statistics 21. Se realizó análisis bivariado y regresión logística multivariante de factores psicosociales nocivos y desgaste psíquico. Resultados: Los factores formación, baja médica, contexto de trabajo, contenido de trabajo y factores individuales están asociados en este estudio con desgaste psíquico. El contexto de trabajo es la variable que infiere mayor riesgo (p=0.000; Exp (B)= 5.355) para provocar desgaste psíquico, seguida de la formación técnica o superior y del contenido del trabajo. Conclusiones: Si bien aquellos trabajadores cuya percepción nociva del contexto de trabajo (interrelación trabajo-vida familiar/personal, cultura de la organización, gestión de la empresa, etc.), del contenido de trabajo (concepción tareas, carga y ritmo de trabajo, etc.) y los que tienen formación técnica o superior tienen mayor probabilidad de padecer desgaste psíquico, se observan aspectos positivos de las condiciones de trabajo psicosocial y su influencia en los trabajadores y en las organizaciones.

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Given $n$ independent replicates of a jointly distributed pair $(X,Y)\in {\cal R}^d \times {\cal R}$, we wish to select from a fixed sequence of model classes ${\cal F}_1, {\cal F}_2, \ldots$ a deterministic prediction rule $f: {\cal R}^d \to {\cal R}$ whose risk is small. We investigate the possibility of empirically assessingthe {\em complexity} of each model class, that is, the actual difficulty of the estimation problem within each class. The estimated complexities are in turn used to define an adaptive model selection procedure, which is based on complexity penalized empirical risk.The available data are divided into two parts. The first is used to form an empirical cover of each model class, and the second is used to select a candidate rule from each cover based on empirical risk. The covering radii are determined empirically to optimize a tight upper bound on the estimation error. An estimate is chosen from the list of candidates in order to minimize the sum of class complexity and empirical risk. A distinguishing feature of the approach is that the complexity of each model class is assessed empirically, based on the size of its empirical cover.Finite sample performance bounds are established for the estimates, and these bounds are applied to several non-parametric estimation problems. The estimates are shown to achieve a favorable tradeoff between approximation and estimation error, and to perform as well as if the distribution-dependent complexities of the model classes were known beforehand. In addition, it is shown that the estimate can be consistent,and even possess near optimal rates of convergence, when each model class has an infinite VC or pseudo dimension.For regression estimation with squared loss we modify our estimate to achieve a faster rate of convergence.

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Panel data can be arranged into a matrix in two ways, called 'long' and 'wide' formats (LFand WF). The two formats suggest two alternative model approaches for analyzing paneldata: (i) univariate regression with varying intercept; and (ii) multivariate regression withlatent variables (a particular case of structural equation model, SEM). The present papercompares the two approaches showing in which circumstances they yield equivalent?insome cases, even numerically equal?results. We show that the univariate approach givesresults equivalent to the multivariate approach when restrictions of time invariance (inthe paper, the TI assumption) are imposed on the parameters of the multivariate model.It is shown that the restrictions implicit in the univariate approach can be assessed bychi-square difference testing of two nested multivariate models. In addition, commontests encountered in the econometric analysis of panel data, such as the Hausman test, areshown to have an equivalent representation as chi-square difference tests. Commonalitiesand differences between the univariate and multivariate approaches are illustrated usingan empirical panel data set of firms' profitability as well as a simulated panel data.