It is clear that people are mostly faced by numerous situations, which can only be well understood theoretically. If however one is able to understand consciousness experientially, the subjectivity of another individual is a very substantial experience. This research paper presents an experimental study on the empathy phenomenon to investigate the role one’s perception on the levels of empathy. In line with most psychologists and philosophers, empathy has been regarded as a kind of understanding other people’s feelings and thoughts. Empathy is a term of relative recent origin. Theoretically, the idea of empathy grew out of the Lipps’ earlier work in German aesthetics (Lipps, 1905). Evidently, Lipps played a significant role in this connection as he methodically organized the notion of Einfühlung. While historically researchers have emphasized cognition and others affect, empathy has always taken the notion of recognizing the awareness of another. In the methodology section, the sampling, instruments validation, data collection methods, data analysis techniques and mathematical models to be used in the study, will be given. The data was coded and then a data base developed in Statistical software. Due to the type of analysis required, the researcher opted SPSS (Statistical Packages for Social scientists) and R Software
The Effect of Perception on Levels of Empathy
The fact that individuals are faced by various situations can easily be understood theoretically (Davis, 1996). Contrary, to understand consciousness which is outside one’s own experientially is very difficult. If however one is able to understand consciousness experientially, the subjectivity of another individual is a very substantial experience. Incorporating a different subjective world to one’s own literally expands it. According to most psychologists and philosophers, empathy has been regarded as a kind of understanding other people’s feelings and thoughts (Davis, 1996). Most commonly, those who perceive empathy as a kind of understanding argue that the individuals who view empathy as concern or benevolence overlook the difference between caring and understanding. In most cases, it is indeed sensible to distinguish between caring for something and understanding it. However, with the empathy phenomenon, this is not the case. It is impossible to sense another person’s perceptual world accurately unless you highly value this person and his world or you certainly care about this person (Davis, 1996). Despite the fact that it is widely recognized that empathy links the isolated persons, the knowledge about the scope of the phenomena and its relation to other different phenomena is rare (Davis, 1996).
This research paper presents an experimental study on the empathy phenomenon to investigate the role one’s perception on the levels of empathy.
Literature Review
Empathy is a term of relative recent origin. Theoretically, the idea of empathy grew out of the Lipps’ earlier work in German aesthetics (Lipps, 1905). Evidently, Lipps played a significant role in this connection as he methodically organized the notion of Einfühlung. The notion referred to the propensity of the perceivers to project themselves into the objects of opinion which can be termed as a type of animism. Apparently, the particular qualities were faced by the individual as being in the object. Objects were both seen and felt (Davis, 1996). The term was appropriated for use in psychological contexts. It was first applied to the survey of optical illusions, and then, to the procedure by which individuals get to know other people.
Basically, the term empathy was invented as a translation whereby it was coined as a rendering of Lipps’ Einfühlungand defined as the procedure of humanizing objects of feeling and reading our own self into them (Davis, 1996). Empathy theories in psychology were hugely influenced by the views of Lipps and Titchener until 1929 when other researchers argued in a more rational vein (Davis, 1996). Instead of continuing to emphasize on the experiences of other people, Kohler denoted that empathy is more of understanding other people’s feelings than sharing them. Over the same period, other highly influential theorists addressed the issue of empathy. According to the two theorists, empathy is more cognitive than emotional (Mead, 1934: Piaget, 1932). Mead recognized selfother distinction in empathy. As a result he added a cognitive aspect which is the capability to understand empathy. His work placed emphasis on a person’s ability to another person’s role in an attempt to understand their perception of their world. Piaget (1932) with his study on the development of the cognitive functions of a child contributed of the ideas of what is necessary for a person to decenter and assumes the role of another.
While historically researchers have emphasized cognition and others affect, empathy has always taken the notion of recognizing the awareness of another. Generally, it is the capacity of acquiring knowledge of the particular side of another individual (Batson et al, 1995). Empathy is described as the ability to correctly gather the substance of another person’s feeling and thoughts. This can be juxtaposed with the conceptualization of empathy as not only a person’s feelings and thoughts but the person as a whole. In this particular perspective individuals attitude, feelings, thoughts and experiences have greater weight in shaping the a person’s perspective over the subject matter as the persons perspective is made taking an individual as a whole at a particular moment with total disregard of a person’s crucial values and commitment. This definition also incorporates the purpose that gives a person’s life structure and extension. Batson et al, (1995) views these values and commitments as important in a person’s life and promoting them is an integral part of empathy. This generally means considering the other person’s perspective and viewing their feeling just as important as we do to ours.
The main bottleneck in the various conceptualization of empathy is basically whether the object of empathy is the objects present experience or the object entire life including future experiences. Moreover, empathy does not necessarily empathize an individual’s current conscious experiences but also with the unconscious processes (Batson, 1997). It is also worth noting that an individual can empathize with another person’s future or even past experiences. Most of the modern researchers base their definition of empathy on the emotion reactions consistent with those of the target Batson, (1997). Some of these view empathy as feeling the same or harboring the same emotions as the target object. Batson, (1997) according to his research empathizing is experiencing the feelings of another person, in other words putting ourselves in their shoes. Batson, (1997) notes that the empathizer may actually feel the emotions of the target object. In this case empathy is seen as the effective reaction which comes from the comprehension of another person’s state and that is deemed to be analogous with the other persons emotions and feelings or what the person would be expected to feel.
Methodology
This involves the sampling, instruments validation, data collection methods, data analysis techniques and mathematical models to be used in the study.
Sampling
Purposive sampling method was used to come up with sample of 37 respondents to be used in the study. Purposive sampling method leads to precise selection, since it is believed to be a rich source of the data of interest (Gall et al, 1996; Gay, 1996) and is necessitated when the research is interested in certain specified characteristics like in this study. Furthermore, random sampling leads to selection of a sample that represents the larger population, that is, the findings in the sample can be inferred back to the larger population (Thomas and Nelson, 1996).Well structured questionnaire will then be used to collect the information. The research instrument (Questionnaire) will be constructed by the researcher.
Instruments Validation
Two pilot studies were done on the research instruments. The first one through the researcher’s Supervisors reading over the questionnaire. The supervisor provided valuable critiques about the research instruments’ format, content, expression and importance of test items, lead to deletion, addition, and revision of the items where need be.
In the second pilot study, testretest reliability, also referred to as test was used. Testretest reliability is determined by administering the same instrument again to the same subjects after a time period has elapsed. When subjects’ results are statistically compared, the researcher gains evidence of the instruments’ reliability over time or its stability (Tuckman, 1994. The two administrations are to be separated by a time period of 14 days. The results from the pilot study will be subjected to item analysis in which those questions that elicited irrelevant and ambiguous responses and those not responded used to calculate difficulty indices. Those with a difficulty index of .50 and below will be revised. This is concurrent with Thomas and Nelson’s (1996) suggestion that the researcher needs to ensure that the test items can be analyzed in a meaningful way and then ascertain whether some changes may be warranted for easier analysis.
Data Collection Procedures
Data Analysis
The data was coded and then a data base developed in Statistical software. Due to the type of analysis required, the researcher opted SPSS (Statistical Packages for Social scientists) and R Software. In the database a frame in form of matrix will be developed where each question will be given a variable name, type and variable value where need be. The data obtained was first arranged in a logical order followed by drawing tables and graphs. Both descriptive and inferential statistics was used in data analysis.
Regression Analysis
I considered a simple linear regression relationship between the response Y and a regressor x. The simple linear regression model given as: the response Y is related to the independent variable x through equation Y=b0+b1x+εi. Where
Y=overall Empathy
x=Embarrassment
b0=nonzero constant of proportionality and indicates value of Y when x is zero.
b1= the gradient of the slope and
εi=disturbance term.
The relationship is not deterministic since for a given x we do not always get the exact value of Y. The problem is therefore probalistic in nature.
The Disturbance Term Has Mean Zero and Variance One
An important aspect of this regression analysis is to estimate bo and b1, the regression coefficients. This is of paramount importance in determining whether there is any relationship between perception, reliability and browsing speed. R2 is the coefficient of determination, which is a measure of the proportion of the variability explained by the fitted model.
Coefficient of Determination
Coefficient of determination indicates the proportion of variance in the overall empathy that can be statistically explained by the knowledge of other variables. Its square root is the coefficient of correlation, which makes the statistical testing possible because it can define a test statistic distributed when the population correlation is zero.
Discussion
More than half of respondents were male (54.1%) while close to half (48.6%) were BA students and lowest response recorded from PHD Students (5.4%) as indicated below (see Table 1 and 2)
Table 1: Respondent Gender
Gender

%

Male

54.1

female

45.9

Table 2: Respondents Education level
Level

%

BA

48.6

BS

27.0

Masters

13.5

PHD

5.4

Undecided

5.4



Most of the respondents (45.9%) were from Caucasian group with lowest numbers recorded for Asian (8.1%) and NativeAmerican (5.4) races as indicated below (see Table 3).
Table3: Respondents Ethnicity

%

Caucasian

45.9

AfricaAmerican

24.3

Hispanic

16.2

Asian

8.1

NativeAmerican

5.4



Table 4. Descriptive Statistics – Embarrassment Level
Condition

Mean

SD

Good

5.95

1.747

Bad

6.50

0.857




On a Likert scale of 17 with 1 being not embarrassing at all and 7 being extremely embarrassing, Sam’s embarrassment was rated as extreme (Mean 6.5 and SD 0.857)
Table 5: R Squared 0.040 (Adjusted R Squared 0.013)
Source

Sum of squares

DF

MS

F

Sig

Corrected model

2.823

1

2.823

1.465

0.234

Intercept

1432.120

1

1432.120

743.160

0.000

Condition

2.823

1

2.823

1.465

0.234

Error

67.447

35

1.927



Total

1500.00

37




Corrected Total

70.270

36




The dependent variable’s total variation can be measured by its variance. If the regression line is not completely horizontal (i.e. if the b coefficient is different from 0), then some of the total variance is accounted for by the regression line. This part of the variance is measured as the sum of the squared differences between the respondents’ predicted dependent variable values and the overall mean divided by the number of respondents. By dividing this explained variance by the total variance of the dependent variable, we arrive at the proportion of the total variance that is accounted for by the regression equation. This proportion varies between 0 and 1 and is symbolized by R^{2} (R Square). As can be seen from Table 5, the value of our R^{2} is 0.040, which means that 4.0 percent of the total variance in embarrassment has been ‘explained’. The results indicate that the condition (embarrassment) is not statistically significantly different from zero (F = 1.465, p = 0.234)
Table 6. Descriptive Statistics  Empathy level
Condition

mean

SD

Good

5.53

1.775

Bad

4.44

1.542




Table 7. Analysis of Variance  Empathy level
Source

Sum of squares

DF

MS

F

Sig

Corrected model

10.819

1

10.819

3.896

0.056

Intercept

918.927

1

918.927

330.953

0.000

Condition

10.819

1

10.819

3.896

0.056

Error

97.181

35

2.777



Total

1033.00

37




Corrected Total

108.000

36




R Squared 0.100 (Adjusted R Squared 0.074)
Table 8. Descriptive Statistics – Sam’s Badness
Condition

Mean

SD

Good

3.38

1.432

Bad

2.09

1.378

Table 9. Analysis of Variance  Empathy level
Source

Sum of squares

DF

MS

F

Sig

Corrected model

50.957

1

50.957

24.114

0.000

Intercept

219.606

1

219.606

103.921

0.000

Condition

50.957

1

50.957

24.114

0.000

Error

73.962

35

2.113



Total

339.00

37




Corrected Total

124.919

36




R Squared 0.408 (Adjusted R Squared 0.391)