To compose this draft, I combined my introduction draft and my methods draft. Add in the analysis
which you turned in for SM and add the draft of the discussion I outlined in class and the references
from JA 4 + any more I used in the correct order.
Compassion Fade
Compassion fade is a type of cognitive bias that makes people inclined towards
behaving more sympathetically towards smaller groups that are suffering rather than to
a large group with the same needs (Västfjäll et al., 2014).The amount donated to charity
has increased from $390 billion in 2016 to $410 billion in 2017 (Butts et al.,
2019).However, there is a feel of sympathy towards one rather than the group who
suffered as a whole. Research shows a decreasing intent to assist with an increase in
the number of individuals in a group. Although, the instances of compassion fade
challenge the ethics of economic valuation at risk; however further research is required
to acquire a better understanding of how and why compassion fade effect occurs.
There is a long grieving among researchers and practitioners as to why more
sympathy for help or assistance is developed for one as compared to a large group with
the same needs. Empirical data suggest that helping diminish as the size of the
individuals in need increase (Fetherstonhaugh, 1997). However, sympathy for helping
others do exist. In qualitative research conducted by Croker et.al (2017), it was found
that individuals are psychology constructed in a way that they believe that supporting
others can be rewarding while selfishness can be a costly affair despite its material
benefit. However, a negative relationship between helping intent and group size was
further supported by research conducted by Butts et al. (2019). The relationship
between the size of the group size and tendency of people to help those in need seems
trues; however, a causal relationship cannot be determined based on the above
research studies.
The study used correlation analysis to determine if there exists any significant
relationship between the group’s size and helping intent. This correlation design relied
on observations being taken over different periods.
Method
For determining the effect of group size on the amount of donation, a total of 33
observations were recorded. The study is qualitative as the objective is to determine if any
significant relationship exists between group size and helping intent. The research design method
includes using an independent two-sample t-test to determine if any significant difference exists
between the two groups (Kenna child and St Jude’s Hospital).The t-test is appropriate in this case
as both dependent and independent variables are available. The independent variable is
qualitative and measured on a nominal scale. The dependent variable i.e. amount of donation is
quantitative and measured on a ratio/interval scale.
The data included collecting information about the amount of donation over several years
for both Kenna child and St Jude’s hospital. The data were obtained using the already available
data on the amount of donation received by the two groups over different years. The amount of
donation received for St Jude’s hospital was obtained from the hospital’s previous financial
sheets. Similarly, data on the amount of donation of Kenna was obtained from the medical bill of
the child. Thus, the procedure involved using existing data to test the hypothesis. The amount of
donations received by Kenna child (n=16) and St Jude’s hospitals (n=17) were recorded
individually. The data were included in the analysis only if had been fully verified from different
sources. All the missing observations were removed from the study. A comparison between the
two groups with missing and observed values is shown in the below table. The donation amount
was recorded under the same environ
Table 1.Descriptive Statistics of Observations with complete data
Variable
N(missing observation)
Mean (SD)
Kenna child
16(0)
7.06(4.48)
St Jude’s Hospital
17(0)
6.41(2.09)
The potential limitation of the dataset includes the presence of less observation which may have
an impact on the result. The probability of Type II error generally increases with low sample size
selection (Hayslett & Murphy, 2017).
References
Butts, M., Lunt, D., Freling, T., & Gabriel, A. (2019). Helping one or helping many? A
theoretical integration and meta-analytic review of the compassion fade
literature. Organizational Behavior and Human Decision Processes, 151, 16-33.
doi: 10.1016/j.obhdp.2018.12.006
Crocker, J., Canevello, A., & Brown, A. (2017). Social Motivation: Costs and Benefits of
Selfishness and Otherishness. Annual Review Of Psychology, 68(1), 299-325.
https://doi.org/10.1146/annurev-psych-010416-044145
Fetherstonhaugh, D. (1997). Insensitivity to the Value of Human Life: A Study of
Psychophysical Numbing. Journal of Risk And Uncertainty, 14.
Västfjäll, D., Slovic, P., Mayorga, M., & Peters, E. (2014). Compassion Fade: Affect and
Charity Are Greatest for a Single Child in Need. Plos ONE, 9(6), e100115.
https://doi.org/10.1371/journal.pone.0100115
Running head: More Hypothesis Testing
1
Module 5b: More Hypothesis Testing
Lisl Dye
Boise State University
PSYC 321- Research Methods
Cindy McCrea
February 15, 2020
1.
2.
3.
4.
5.
Hypothesis 1
State the hypothesis (1pt)
Individuals who have experienced any childhood emotional abuse have high self-harm rates
State the independent/predictor variable (1pt) and if it is scale, ordinal or nominal (1pt)
The independent variable experienced emotional abuse in childhood. The scale of measurement
for this variable is the nominal scale
State the dependent/outcome variable (1pt) and if it is scale, ordinal or nominal (1pt)
The dependent variable is self-harm. The scale of measurement for this variable is the nominal
scale of measurement
Choose and state the correct statistical test (1pt)
The statistical test that will be used is the Chi-square test
Run the correct test using SPSS – prove by copy and pasting your output table (1pt)
Chi-Square Tests
Asymptotic
Significance Exact Sig. (2- Exact Sig. (1Value
df
(2-sided)
sided)
sided)
a
14.182
1
.000
11.098
1
.001
17.662
1
.000
.000
.000
Pearson Chi-Square
Continuity Correctionb
Likelihood Ratio
Fisher’s Exact Test
Linear-by-Linear
13.591
1
.000
Association
N of Valid Cases
24
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 3.67.
b. Computed only for a 2×2 table
6. Write 1-2 sentences explaining your results
A chi-square test of independence was used to test if there was any difference between the selfharm rates of individuals who had experienced childhood emotional abuse and those who did not
experience any childhood emotional abuse. The test of independence was significant (X2(1, N=
24) = 14.182, p < .05). The proportion of individuals who had experienced childhood emotional
abuse (81.25 %) and had purposefully hurt themselves was significantly different than that of
individuals who had not experienced childhood emotional abuse (0%). There were no other
significant differences.
More Hypothesis Testing
7. Make the correct figure to display your results(1pt)
Figure 1. Predicted likelihood to purposely hurt your body having experienced emotional abuse
in childhood
2
More Hypothesis Testing
1.
2.
3.
4.
5.
3
Hypothesis 2
State the hypothesis (1pt)
Men are more likely than women to engage in self-harm behaviors.
State the independent/predictor variable (1pt) and if it is scale, ordinal or nominal (1pt)
The independent variable is Biological sex and its scale of measurement is the nominal scale of
measurement
State the dependent/outcome variable (1pt) and if it is scale, ordinal or nominal (1pt)
The dependent variable is self-harm and its scale of measurement is the nominal scale of
measurement
Choose and state the correct statistical test (1pt)
The statistical test that will be used is the correlation test
Run the correct test using SPSS - prove by copy and pasting your output table (1pt)
Chi-Square Tests
Asymptotic
Significance Exact Sig. (2- Exact Sig. (1Value
df
(2-sided)
sided)
sided)
a
.621
1
.431
.142
1
.706
.623
1
.430
.682
.353
Pearson Chi-Square
Continuity Correctionb
Likelihood Ratio
Fisher's Exact Test
Linear-by-Linear
.595
1
.440
Association
N of Valid Cases
24
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 5.04.
b. Computed only for a 2x2 table
6. Write 1-2 sentences explaining your results. This sentences needs to
A chi-square test of independence was used to test if there was any difference between men and
women. The test of independence was not significant (X2(1, N= 24) = 0.621, p > .05). The
proportion of men (45.5% %) who had purposefully hurt themselves was not significantly
different than the proportion of women (61.5%). There were no other significant differences
7. Make the correct figure to display your results(1pt)
More Hypothesis Testing
Figure 2. Predicted likelihood to purposely hurt your body as a function of gender
4
Running head: SPSS EXPERIMENT DATASET
Module 7: SPSS Experiment Dataset
Lisl Dye
Boise State University
PSYC 321- Research Methods
Cindy McCrea
February 29, 2020
2)
1
SPSS EXPERIMENT DATASET
5.
2
SPSS EXPERIMENT DATASET
3
a.
The average amount of donation for donation of child (M=7.06, SD=4.48) was found to be
higher than the average donation of St. Jude Children’s Hospital (M=6.41, SD=2.09).
b.
The test is the independent sample t-test which was used to check whether the average amount of
donations across two different groups (Kenna and St. Jude) differs significantly or not.
Both variables are independent and not related to one another. Thus, the best test will be
independent sample t-test.
c.
There appears to be no significant difference in the mean amount of donation of Kenna and St.
Jude.
d.
t(20.97)= 0.529,p =0.602
e.
There does not appear to exist significant difference in the scores between Kenna and St. Jude
(t(30)=0.54,p>0.05).
SPSS EXPERIMENT DATASET
1.
Figure 1. Box plot showing a comparison for the scores of Kenna and St. Jude.
4
Running head: STATISTICAL ANALYSIS FOR OUR ECPERIENCE
1
Module 6: Stat for Experiment
Lisl Dye
Boise State University
PSYC 321- Research Methods
Cindy McCrea
February 21, 2020
1. According to the compassion fade effect, we hypothesize that compassion and empathy
decrease as the number of those in need increases
2. The independent variable for this research study is number of those in need because it
determines the level of compassion and empathy that one will depict through their
donation. This variable is a scale variable because it has order and differences between
values can be determined. The variable will be manipulated through the use of two
settings with varying number of people who are in need of help acquired from donations.
The two settings are St. Jude Children’s Hospital, and a homeless child living on the
streets. The univariate test that will be used to come up with descriptive statistics for the
variable is the frequency distribution test.
3. The dependent variable is the amount of money one donates to either St. Jude Children’s
Hospital, or a homeless child living on the streets. This variable is also a scale variable
because it has order and differences between values can be determined. The variable will
be measured by determining the amount of money one is willing to donate to St. Jude
Children’s Hospital, and the amount they are to give a homeless child living on the
streets. The univariate test that will be used to come up with descriptive statistics for the
variable is the frequency distribution test
4. The statistical test that will be used to test the hypothesis that compassion and empathy
decrease as the number of those in need increases is the paired samples t-test because
there are two groups i.e., the amount of money one is willing to donate to St. Jude
Children’s Hospital and the amount of money the same individual will be willing to give
to a homeless child living on the streets, whose means will be compared to each other.
Running head: JOURNAL 3
1
Journal 3- Compassion Fade Effect
Lisl Dye
Boise State University
PSYC 321- Research Methods
Cindy McCrea
February 11, 2020
Article Analysis
Phenomena: Compassion Fade Effect
Compassion fade can be defined as a type of cognitive bias that makes people inclined
towards behaving more sympathetically towards smaller groups that are suffering rather than
to a large group with the same needs. For example, we may feel sympathy for the killing of a
small group of people; however, mass killing is simply given the term “death.”
Article Title
Helping one or helping many? A theoretical integration and meta-analytic review of
the compassion fade literature
Abstract Copy (As written in the Article)
“Researchers and practitioners in the area of charitable giving have long lamented the
tendency to offer greater aid to one person who is suffering rather than to a large group with
the same needs. Demonstrations of such compassion fade are common in the literature,
although different explanations for these findings exist. To reconcile both past theory and
empirical research, we utilized a dual concern framing in conducting a meta-analysis of 41
studies (95 independent samples; 13,259 total sample size) on compassion fade. Results
suggest that victim group size negatively affects both helping intent and helping behavior, as
well as our proposed mediating mechanisms of anticipated positive affect (self-oriented
motivation) and perceived impact (hybrid other-/self-oriented motivation). However,
significant effects were not found for empathetic concern (other-oriented motivation). Results
COMPASSION FADE EFFECT
2
also showed that the indirect effects of victim group size on helping are stronger through
anticipated positive affect and perceived impact than through empathetic concern. Further, as
indicated by supplemental analyses, anticipated positive affect and perceived impact likely
operate as predictors of empathetic concern in a serial mediation process through which
victim groups size affects helping. Finally, we examined calamity scope (number of victims)
and event features (certainty, chronicity, and threat severity) as moderators of the observed
relationships between victim group size and helping. Theoretical implications and directions
for future compassion fade research emanating from these findings are discussed” (Butts,
Lunt, Freling & Gabriel, 2019).
Introduction
The recent data suggests the amount of donations in the US has increased over the
years. For example, the donation amount for the year 2016 was $390 billion, which increased
to $410 billion in 2017 (Giving USA, 2018).However, research studies have shown the
amount of donation is not positively related to the total number of individuals in need. In fact,
helping decreases with the increase in the number of victims. The research question for the
study is;
“Is there any significant relationship between group size and helping?”
The purpose of the study is to test the claim that the amount of donations decreases with the
increase in the group size or the number of people that requires help.
Type of Study
The study is a type of observational as it does not involve any treatment to the
experimental units. The authors collected data from different available works of literature to
determine whether any association exists between the amount of donation and group size.
COMPASSION FADE EFFECT
3
Method Section
The independent variable for the study was the group size, and the dependent variable
for the group size was the amount of donation received. The information about the
independent variable was collected from different electronic databases such as
ABI/INFORM, Google Scholar, ProQuest, Business Source Complete etc. Also, information
about the compassion fade was obtained through different Journal articles by searching for
keywords related to compassion fade. Based on certain criteria, 41 studies were selected
which included a sample size of 13,259.For each of the selected studies, the group size was
then taken as a measurement.
Measuring the Dependent Variable
In order to measure the independent variable “helping (intent and behavior),”studies
considered had to measure the willingness to help or actual help. The helping intent measures
were those that examined an individual’s intent to help. Helping behavior calculation
involved any willingness to help which involves giving donations, goods (e.g., candy), or
giving advice. These helping intent were given scores based on coding schemes.
Main result of the Study
A negative and significant bivariate relationship was found between the helping intent
and behavior and the group size; p=-0.09, 95% CI=-0.06,-0.13 and helping behavior; p=-0.13,
95% CI=-0.08,-0.17
Manipulation of Dependent and Independent Variable
I would also carry out a correlation analysis to check whether any significant
relationship exists between the amount of donations and group size. For the study, I would
consider only the quantitative data of the amount of donation and not any helping behavior
intent. For the independent variable, I would collect data on the number of people who were
victims in a particular event.
COMPASSION FADE EFFECT
Using Reference
In a study by Butts et al. (2018), it was found that the group size of the victim
negatively affects the helping intent and helping behavior.
4
COMPASSION FADE EFFECT
5
References
Butts, M., Lunt, D., Freling, T., & Gabriel, A. (2019). Helping one or helping many? A
theoretical integration and meta-analytic review of the compassion fade
literature. Organizational Behavior and Human Decision Processes, 151, 16-33. doi:
10.1016/j.obhdp.2018.12.006
Giving USA. (2018). Americans gave $410.02 billion to charity in 2017, crossing the $400
billion mark for the first time. Retrieved from: https://givingusa.org/giving-usa2018-americans-gave-410-02-billion-to-charity-in-2017-crossing-the-400billionmark-for-the-first-time/
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