Health Programming for Clergy: An Overview of Protestant Programs in the United States

The health of clergy is important, and clergy may find health programming tailored to them more effective. Little is known about existing clergy health programs. We contacted Protestant denominational headquarters and searched academic databases and the Internet. We identified 56 clergy health programs and categorized them into prevention and personal enrichment; counseling; marriage and family enrichment; peer support; congregational health; congregational effectiveness; denominational enrichment; insurance/strategic pension plans; and referral-based programs. Only 13 of the programs engaged in outcomes evaluation. Using the Socioecological Framework, we found that many programs support individual-level and institutional-level changes, but few programs support congregational-level changes. Outcome evaluation strategies and a central repository for information on clergy health programs are needed. © 2011 Springer Science+Business Media, LLC.

Of Trustees and Offsprings: A Diasporic Trail of Parsi “Crisis” from Bombay to Hong Kong

This thesis examines the discourse(s) of crisis in the Parsi diaspora. Treating crisis as a common variable, rather than a singular and unique event across various Parsi communities, I investigate the dimensions of crisis that bind separated Parsi communities in anxiety through a shared language, cultural experience, and historical memory. Turning first to India and then Hong Kong as my case studies, I analyze “crisis,” that has often been identified in terms of demographic decay or postcolonial decline, in the context of more subtle debates around racial purity and trust funds. Crisis, for the Parsi diaspora, while indicating a critical moment in the present, also serves to reveal the underlying and pre-existing socio-economic and cultural tensions in the communities. Relying largely on life-story interviews, online blogs and articles, and archival work, I portray the crisis not as a unique and sporadic event, but rather as one of continuity and complexity, albeit manifesting each time in different and unique guises, that continues to disrupt as well as unite the Parsi diaspora today.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Development and Testing of An Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.

Local government revenue from oil and gas production

Oil and gas production generates substantial revenue for state and local governments. This report examines revenue from oil and gas production flowing to local governments through four mechanisms: (i) state taxes or fees on oil and gas production; (ii) local property taxes on oil and gas property; (iii) leasing of state-owned land; and (iv) leasing of federally owned land. We examine every major oil- and gas-producing state and find that the share of oil and gas production value allocated to and collected by local governments ranges widely, from 0.5 percent to more than 9 percent due to numerous policy differences among states. School districts and trust funds endowing future school operations tend to see the highest share of revenue, followed by counties. Municipalities and other local governments with more limited geographic boundaries tend to receive smaller shares of oil and gas driven revenue. Some states utilize grant programs to allocate revenue to where impacts from the industry are greatest. Others send most revenue to state operating or trust funds, with little revenue earmarked specifically for local governments.

Essays in Industrial Organization

This dissertation extends the empirical industrial organization literature with two essays on strategic decisions of firms in imperfectly competitive markets and one essay on how inertia in consumer choice can result in significant welfare losses. Using data from the airline industry I study a well-known puzzle in the literature whereby incumbent firms decrease fares when Southwest Airlines emerges as a potential entrant, but is not (yet) competing directly. In the first essay I describe this so-called Southwest Effect and use reduced-form analysis to offer possible explanations for why firms may choose to forgo profits today rather than wait until Southwest operates the route. The analysis suggests that incumbent firms are attempting to signal to Southwest that entry is unprofitable so as to deter its entry. The second essay develops this theme by extending a classic model from the IO literature, limit pricing, to a dynamic setting. Calibrations indicate the price cuts observed in the data can be captured by a dynamic limit pricing model. The third essay looks at another concentrated industry, mobile telecoms, and studies how inertia in choice (be it inattention or switching costs) can lead to consumers being on poorly matched cellphone plans and how a simple policy proposal can have a considerable effect on welfare.