The Curves method: epidemiological survey in order to screen fitness self-efficacy.

The population under study is referred to 126 female subjects, selected from among 1119 subjects, aged between 15 and 84 years (mean age of 39 years with a standard deviation of 12.9 years) from 19/07 / 01/17/2014 2007 and participated in the Curves method, the minimum duration of 30 minutes to workout at the headquarters of Chiesina Uzzanese (Pistoia), for a consecutive period of 4 months. Were included in the study the women who fell into certain inclusion criteria, or selection criteria that define the main characteristics of the population that was studied, determining what subjects were allowed to enter the study: subjects aged 15 and 64 years; subjects who participated in the training method Curves for at least 4 consecutive months; subjects who practiced at least 3 workouts per week on an ongoing basis; subjects which have been subjected to at least 4 Indexes relating to 9 body measurements. Exclusion criteria: subjects were excluded from underweight, ie those with a BMI <18.5, (only 2 subjects). Inclusion criteria only 11, 3%, ie 126 subjects out of 1119, are back in the studio. The statistical analysis is related to the personal characteristics of the subjects and the descriptive analysis of body measurements. The classification of the age groups shown in table is distributed according to criteria defined by ISTAT. It 'was used analysis of variance for repeated measures, ie a technique of data analysis that allows to test hypotheses about differences between the averages of two or more populations (the term "repeated measures" refers to those data that are collected on the same statistical units in different points in time or under different conditions), with the objective of evaluating over time (T1, T2, T3, T4, ......) the effect of the method of Curves workout. The analysis of variance represents a set of statistical techniques that are part of inferential statistics and is born in the context of experimental research in order to assess the effect of certain factors (independent variables of the continuous type or categorical) at the level of one or more dependent variables when the comparison is done on more than two groups. The development of technology ANOVA, Analysis of variance, was mainly due to the work of Fischer. Through the analysis of variance, the total variability present in a certain set of data (for example, three or more groups subjected to more than two treatments) is decomposed into two components, said internal groups variance and the variance between groups, each of which is attributed to a specific source of variability that makes its contribution to the total variability itself.