Research Methodologies Applied To Evaluate The Impact Of Modern Technology On Eyesight - Essay Example

?Research Methodologies Applied To Evaluate The Impact Of Modern Technology On Eyesight Background In this era of e –technologies vision problems have become very prominent and significant. On an average it has been estimated that the mean usage of computers in daily life of Americans is around 3-4 hours per day. This has led to the concept of the most commonly known computer vision syndrome. This syndrome is featured by burning sensation to the eyes, upper and low back pain, neck pain and fatigue. The main reasons for the vision problems were related to the un- ergonomical work station station design, non usage of proper antiglare screens in the visual display units of the computer, and the distance and elevation of the VDU screen from the persons eye height. It is seen that if the screen is placed 2 cm above vision problems are more as the chances of the diameter of the eye to be opened is much more which will lead to lacrimation and cause evaporative loss of fluid from the surface of the conjunctiva and will cause conjunctivitis, eye irritations, eye pain and later cataracts. The other problem will be that, due to the elevation of the head to see the computer screen one gets affected by upper neck problems. On the other hand placing the screen eye height also showed a normal eye diameter that have to remain open but during prolonged periods of working this can also cause the same taxation to the eyes as described above. On the other hand if the computer screen is kept 2 cm below the eye height and the diameter of eye opening can easily be minimized to prevent lacrimation and vision problems and at the same time since due to the non-elevation of the head to see the computer screen one will not get affected by upper neck problem. The quality of the antiglare screens also causes a problem as because the damaging effects of the uv radiations in the eye are quite dangerous and finally a proper ergonomic work station design is also important. These include provision of propr sitting posture, chair design and foot rest because the design might have been created for the general population as the whole but individual constraints can be present to use the same design dimensions and there should be place of flexibility. Thus we can see the detrimental effects of modern technology on vision problems are quite well recognized. Objectives of Our Study and the Study Design The objective of the study was to found the effect of the various factors that contribute to the vision problems in totality by applying regression logistics and the study design was to include a proper sampling strategy, representation and analysis of the data to draw the logistic regression equations. This would give an idea what proportions of the various factors are related to the vision problems and the weightage that has to be attributed while interpreting the results. Methodology Collection Of Data The first thing for any study is the process of data collection and the method of sampling. Data is collected on the basis of sampling which can be randomized, or purposive with respect to the variable that has to be analyzed. Randomized data means each individual will have equal probability to be included in the sample. Purposive data is considered by some criteria fixed by the experimenter (effects of a drug on diabetic patients).Sampling makes sure that the results are based on non biased assumptions and simply random sampling reduces the chance of bias. So in this study we will fix inclusion criteria with a purposive sampling- that means people who use computers whether desktops and laptops will be included and the others in the population will not be included- thus our purposive sampling will narrow it to population of computer users. The exclusion criteria would be non computer users and having vision problems other than technology related. Data will be collected through a set of questionnaire method:- a. Vision severity score: Rate your vision problems on a scale of 1 to 10 b. Are you ergonomically satisfied with the workstation in which you work= rate in a scale of 1-10( more score more satisfaction) c. Is your vision screen difficult to view rate from 1-10( more score more difficulty) d. Are you a frequent computer user or infrequent user( rate from 1-10 more score more computer usage) e. Age group-If 20-25 Score assigned=1 Age group-If 26-30 Scire assigned =2 And like wise done till 50 years age group. We would see then whether our distribution obtained is symmetrical or asymmetrical and conform to normal distribution and whether undue weightage has been given to extreme values during data collection. Collected data can have a symmetrical representation and in that case mean, median and mode will be the same for a particular variable and when these value changes it is called asymmetrical and this measure is called skewness, On the other hand there can be incidences such the data is collected more on the upper and lower sides of a variable(tails) it will be called leptokurtic data and if the middle values of a variable are collected it is called platykurtic data. In the former the distribution looks pointed and in later it has a plateau shaped. Ideally if a data is ideally collected then the curve should look mesokurtic with frequency of the scores evenly distributed at upper and lower and middle limits. This is called a normal distribution. The normal distribution has a unit area of one and this is helpful to measure testing of hypothesis.(Chance,2005). Thus the need for data representation becomes important Representation of the Data obtained The collected data can be represented in many forms depending upon the type of analysis that may be required in our study. The most common forms of data represented are the histograms and bar diagram which indicates the frequency of occurrence of any event on the Y axis and the type of events are plotted on the X axis. Histogram is normally used for measurement variables which are continuous that means can be measured upto decimal places. Bar diagrams are used for non- continuous data that is which cannot be measured in the form of decimal places. The width of the bars in both of them represents the class interval or the range of the events (range of age group). Then frequency tables and frequency polygons are also plotted but in the form of graphical lines so as to compare between two sets of data or the trend of the data with respect to a particular variable ( comparison of marks obtained by two students in the 3 semesters of examination). So we will use histogram to find the vision problems in various age groups and compare to one another. We will also use a proportionate bar diagram to find given the same vision problems what is the reason they feel that might have caused that height of screen, ergonomical work stations or others. The represented data is also useful for estimating certain measures called measures of central tendency and some are called measures of dispersion. We will be requiring these for various purposes in our study Measures of central tendency will include 1. Mean: represents the arithmetic average of the data. This will be used to compare the bar heights of histogram and also for conducting tests of significance. 2. Median: It is that value of a variable above which and below which 50% of the scores of a population lies and is also called the 50th percentile. By this we can evaluate what is the severity of the vision score that 50% of population is having 3.Mode: represents the events having the maximum frequency of occurrence during a study. A data can be unimodal or bimodal depending on the peaks that are evident.(Anderson et al,1994). This can be used to find which age group has the most frequent and highest vision problems. Measures of Dispersion are: 1 .Standard Deviation: Estimating the variation of raw score from the sample mean. 2. Variance: means square of standard deviations, useful to estimate one sample has equal variance or added variance components due to the independent variable’s effect are studied(example in Anova test) 3. Standard Error: estimating the deviation of an individual raw score from the population (parametric mean) All these will give an idea whether the sample drawn by us conforms to the population and does significant deviations has occurred or not. Confidence Interval: Signifies the range where the upper and lower limits of a data being accepted are specified with respect to the population. There can be a probability limits based on 95% 0r 99% probability estimates. (Anderson et al,1994). This will form the basis of the objective classification of severity of vision scores and we will get a range to estimate the maximum and minimum vision severity scores of the population. Analysis of Data Testing of Hypothesis: Data can be analyzed for statistical significance based on the normal distribution. This means if the computed probability value or p value as measured from t test or Anova is Read More