Datasets Describing the Effect of Educational Program about Isometric and Stretching Exercises On Neck Pain among Information Technology Employees

Research Hypothesis
H1: There would be a lack of IT employees' knowledge about the importance of good neck posture, isometric and stretching exercises.
H2: Isometric and stretching exercises would be a good effect on improving neck pain
Background: Neck pain is one of the most prevalent musculoskeletal concerns among men and women, particularly those who use computers all day. Aim to evaluate the effect of an educational program about isometric and stretching exercises on neck pain among Information Technology employees at new Assuit city. Method and material: Quasi-experimental research design and a single population proportion formula to calculate sample size using Open Epi, Version 3. The total final size was 118 employees and the program was implemented on (73) employees having neck pain according to exclusion criteria. The period of collecting data was from the mid of April 2021 to mid of December 2021. Three tools were used, tool I: A structured questionnaire that consisted of three parts: 1st part: socio-demographic data, 2nd part: assessment of the nature of the work, and 3rd part: assessment of knowledge of employees. Tool (II): The neck Pain Questionnaire(NPQ) was used to evaluate the degree of neck pain and functional disability, and tool (III): the observational checklist. Data entry and data analysis were done using SPSS version 22 (Statistical Package for Social Science) (SPSS Inc., Chicago, II., USA). Data were presented as a number, percentage, mean, standard deviation, median, and range. The chi-square test was used to compare qualitative variables. In the case of parametric data, Paired samples t-test was done to compare quantitative data between the pre-test and post-test. Pearson correlation was done to measure the correlation between quantitative variables. While in the case of non-parametric data, Wilcoxon Signed Rank Test was done to compare quantitative variables between the pre-test and post-test. The P-value is considered statistically significant when P < 0.05.