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1.
Hum Mov Sci ; 83: 102947, 2022 Jun.
Article in English | MEDLINE | ID: mdl-35378431

ABSTRACT

OBJECTIVES: The aim of the present study was to determine the effects of performing a dual task on the sway density plot parameters in Parkinson's disease and control subjects. METHODS: A cross-sectional design was used to establish differences in the mean peak, mean time, and mean distance between a group with Parkinson's disease and a control group without Parkinson's disease. The subjects performed, in a unique measurement session, two trials under three different randomized conditions: i. eyes open, ii. eyes closed, and iii. Eyes open with foam base. One trial was performed as a single task (i.e., the subjects completed one of the balance test), while the other trial was performed as a dual task (i.e., the subjects performed a cognitive task at the same time that they maintained the static balance). RESULTS: There was a group x dual task x condition effect in mean peak (F1.5, 51.1 = 5.21; p = 0.015; η2p = 0.13) and mean time (F1.4, 47.3 = 4.43; p = 0.03; η2p = 0.11) variables. According dual-task cost analysis, there was a main effect of the condition (F6,134 = 2.44; p = 0.05; η2p = 0.34) on MD (F2,68 = 6.90; p < 0.01; η2p = 0.17). CONCLUSIONS: This result indicates differences in the dual task interference in the postural control mechanisms between the Parkinson's disease population and healthy pairs. For easy dual tasks, the Parkinson subjects used anticipatory control responses for longer periods of time, and for more difficult tasks, their control strategy did not change regarding single balance task.


Subject(s)
Parkinson Disease , Case-Control Studies , Cross-Sectional Studies , Humans , Parkinson Disease/psychology , Postural Balance/physiology
2.
Fisioterapia (Madr., Ed. impr.) ; 40(5): 241-248, sept.-oct. 2018. tab, graf
Article in Spanish | IBECS | ID: ibc-178850

ABSTRACT

Objetivo: El objetivo de este estudio se centrará en la elaboración de un árbol de decisión como una técnica de análisis de datos que permita establecer combinaciones de factores de riesgo que puedan predisponer a padecer dolor de espalda en esta población. Material y métodos: La muestra del estudio estuvo formada por 337 jóvenes con una edad de entre 12 y 17 años de un centro escolar de Castellón. Los sujetos cumplimentaron el Adolescent Sedentary Activity Questionnaire y el cuestionario Nórdico de Kuorinka. Además, se realizó una valoración del índice de masa corporal, del porcentaje de grasa corporal, de las características de la mochila escolar y del tiempo de transporte de esta y de la actividad física habitual (esta última mediante acelerometría). Estos factores se utilizaron como variables de entrada en un árbol de decisión, con el objetivo de clasificar a los adolescentes en función de si habían tenido o no algún episodio de dolor de espalda. Resultados: El árbol mostró una exactitud del 78,39% en la clasificación de los estudiantes. La sensibilidad de la clasificación fue del 90,77% mientras que la especificidad fue del 63,21%. Conclusiones: El árbol de decisión es una técnica de análisis que ha permitido encontrar combinaciones de factores de riesgo que están relacionados con la aparición de dolor de espalda en adolescentes. Los resultados hallados indican que la práctica de actividad física, el índice de masa corporal, el porcentaje de grasa, el tiempo de transporte de la mochila a la escuela, los minutos de actividades sedentarias realizados a la semana y los antecedentes familiares de dolor de espalda son factores relacionados con el dolor de espalda en la adolescencia


Objective: The aim of this study was to use a decision tree as a data analysis technique in order to establish combinations of risk factors that may predispose schoolchildren to suffer back pain. Material and methods: The study sample consisted of 337 young people between 12 and 17 years of age from a high school in Castellon, Spain. The subjects completed the Adolescent Sedentary Activity Questionnaire and the Kuorinka Nordic questionnaire. The study also included an assessment of the body mass index, body fat percentage, the characteristics of the school backpack, the time of transportation of the backpack, and habitual physical activity (latter by means of accelerometers). These factors were used as input variables in a decision tree, with the objective of classifying adolescents according to whether they had or had not a back pain episode. Results: The tree showed an accuracy of 78.39% in student classification. The sensitivity of the classification was 90.77%, while the specificity was 63.21%. Conclusions: The decision tree is a useful analysis technique that has allowed finding combinations of risk factors associated with low back pain in adolescents. The findings suggest that practicing physical activity, the body mass index, body fat percentage, time of transportation of the backpack, minutes of sedentary activities, and family history of back pain are factors related to back pain in adolescents


Subject(s)
Humans , Male , Female , Child , Adolescent , Back Pain/etiology , Decision Trees , Risk Factors , Students , Adolescent , Multivariate Analysis , Body Mass Index , Exercise
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