Prolegomenon of an (spatial) Epidemiology of Compassion A first look at the potentiality of mapping compassion from a bioethical & epidemiological perspective Público

Kienast, Yvonne (Spring 2020)

Permanent URL: https://etd.library.emory.edu/concern/etds/9c67wn800?locale=pt-BR
Published

Abstract

Compassion is essential for ethics. To evaluate the potential utility of an epidemiology of ethics, definitions and characteristics of compassion in philosophy, world religions, and psychology were reviewed to identify common elements within the fields. This thesis looked at compassion as a key element for mapping ethics. The element of appraisal of one’s own resources and limitations was integral in Buddhism and with philosophers such as Aristotle. Generosity came primarily from the field of Christianity and Islam. The desire to act to alleviate, eliminate or prevent suffering was present in almost all the fields. Next, publicly available data sets matching the characteristics were selected for their use as proxy measurements for compassion. The identified data sets were well-being, volunteering and the Generosity Index for the US, and US hospitals. For the element of relieving suffering, counts of the keyword “compassion” on hospital websites were used as proxy. With the help of the tools of spatial epidemiology, the elements of compassion were mapped to identify spatial clustering of compassion. The resulting maps were examined for overlapping “hot spots” of compassion in the US.

For the element of relieving suffering, the “compassion" counts revealed spatial clustering in the northwestern and southwestern parts of the US, with Southern California and Washington as “hot spots”. The element derived from the Christian and Islamic traditions of giving alms and volunteering depicted higher volunteering rates in the northwestern states of the country and a clear North-South division (lower in the south). For charitable giving, represented by the Generosity Index, over the past twenty years, Utah and Maryland were the top two highest scoring states for individuals giving money to charities. The proxy measure for being in a right state of mind to acknowledge another’s suffering, the well-being score depicts a clear east-western trend, with people in the northwestern parts of the country, indicating a better general satisfaction with life. Through the identification and the use of proxy measurements, spatial epidemiology of compassion can help us understand and develop new questions and hypotheses, such as ‘Utah is a center for compassion in the US’, regarding the spatial clustering of ethics.

Table of Contents

Table of Figures. 9

Table of Tables. 10

Abstract 11

Background. 13

Why map ethics?. 13

Compassion – Why use compassion as a model for mapping ethics. 14

Epidemiology. 17

What can spatial epidemiology contribute?. 18

Why do we need a spatial epidemiology of compassion?. 19

Bioethics thesis and why is the spatial distribution of compassion a valuable exercise for bioethics?. 20

Question(s) and Objectives. 22

Questions. 23

Objectives. 24

Theoretical Perspective. 27

Overview of current theoretical perspectives in traditional philosophical writings on compassion. 27

Overview of current theoretical perspectives in contemporary philosophical writings on compassion. 43

Summary for traditional and contemporary philosophical writings. 48

How does this inform the selection criteria for proxy measures?. 51

Overview of current theoretical perspectives in religious and spiritual writing on compassion. 52

Buddhism.. 53

Christianity. 57

Hinduism.. 65

Islam.. 69

Judaism.. 73

Overview of current theoretical perspectives in psychology writings on compassion. 80

Neuroscience and the discovery of the neuronal network for a compassionate response. 92

Key elements or characteristics of compassion for a spatial epidemiology of compassion. 96

Material and Methods. 103

The use of proxy measures for compassion and spatial epidemiology. 103

The use of proxy measurements. 103

General selection criteria for proxy measures. 104

Data selection reasoning behind proxy measurements for compassion: well-being, generosity, and hospitals. 106

Well-Being and its use as a proxy measurement 110

Generosity. 112

Volunteering and its use as a proxy measurement 112

Charitable Giving – Generosity Index and its use as a proxy measurement 112

Hospitals and Compassion. 113

Data. 114

Well-Being Data. 114

Generosity and Charity Data. 115

Hospital Data. 116

Shape files for Mainland USA.. 117

Methods for the acquisition of the keyword counts for compassion on hospital websites. 118

Search Engine Utilization. 118

Programmatic search of keyword “compassion” counts for each hospital website. 119

ArcMap10.3.1. 121

Global Moran’s I 121

Anselin Local Moran’s I (LISA) 122

Hot spot analysis with Getis-Ord Gi*(d) 123

Additional Questions and Hypothesis for Hospital Data. 124

Results. 125

Well-being Trends (geographically) 125

Generosity and Charity Results. 128

Volunteering in the USA on State Level 128

Generosity Index in the USA on State Level 131

Hospital – Keyword count results for compassion on Hospital websites. 134

Descriptive results for the hospital websites for the term “compassion”. 134

Global Moran’s I - Analyzing Patterns. 139

Local Moran’s I (LISA) – Custer and Outlier Analysis. 140

Getis-Ord Gi*(d) Hot Spot Analysis. 145

Discussion. 149

How can these findings be used in bioethics?. 156

Strengthens and Limitations. 157

Conclusion. 159

References 161

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