School of Nursing Class of 1981

Top Row: Mary Jo Ambrozy, Carolyn, Ashley, Gail Marie Barbaza, Jeanne Barr, Susan Bauer, Lynn Eva Becker, Christine Bibilikow, Kathy Biehl, Lisa Bloomfield, Bail M. Borowiak, Susan, M. Browning, Diane Louise Burgoon, Camille Carlson, Cindy marie Chaltry, Kathleen Anne Clegg, Ann cline

Row 2: Wendy Cogan, Annette Robin Cole, Barbara Compton, Elizabeth Connors, Norma K. Marshall, Michele Betts, Donna Jean Holihan, Pamela S. Harden, Kathleen McLaughlin, Mary M. Walker, Mary Lohr, Julia Cooney, Carol Crapo, Deborah D. Davis, Mary Dreisig

Row 3: Athena Eary, Eleanor Eckrich, Patti M. Eidenberger, Catherine Elmlinger, Annette Englund, Cynthis Fellencer, Karen Fischer, Carolyn B. Forbes, Nancy Ellen Freedman, Susan P. George, Annette Gervaix, Beverly Glogowski

Row 4: Jayne Goodrich, June A. R. Grimm, Marie Guerrini, Douglas Leon Hankins, Yvonne M. Harwoor, Linda Hecimovich, Catherine M. Herbel, Kelly Hocker, Brenda Lee Horness, Theresa A. Hosey, Karin E. Hunt, Beth Jackson

Row 5: Karen Sue Jaffe, Roland Jemerson, Tamera Johnson, Susan Kaczmarek, Laura S. Keverian, Julie A. Kimbrough, Eva Marie Kline, Nancy L. Kuehn, Margaret J. Labadie, Lori K. Lane, Elizabeth Lang, Linda Lawton, Judy Linden, Peggy Little, Sharon Lois Longe, Claire Lonstein

Row 6: Deloris Macon, Karen Marie Macsay, Susan E. Mapley, Maria Y. Maquera, Ann McCullough, Michael Meade, Barbara Messink, Mary Elizabeth Mick, Susie E. Mikolajewski, Marilyn Millman, Debra A. Mills, Lu Ann Minore, Jean M. Mischel, Terri Ann Mitchell, Catherine Jean Moore, Michelle A. Mourad

Row 7: Mary Lynn Musial, Kathleen Myles, Denise Oliphint, Patrice M. Orlowski, Susan Orne, Carolyn Pernell, Holly Perry, Paula L. Petkoff, Arlene Ann Popovich, Barbara A. Quinn, Carol Reid, Sandra J. Remington, Gisselle Rodriguez, Susan Roelant, Laura S. Rogers, Nancy Rudd

Row 8: Karen Beth Salem, Barbara Santavy, Linda Schairer, Marie B. Schneider, Julie Schoettley, Julie Rose Schuster, Mary V. Seibert, Tracy Shafer, Claire E. Sharda, Susan D. Shortino, Judith Simon, Phillis Simpson, Donna Sledz, Cynthia Smith, Diane L. Smith, Mary Kay Smith

Row 9: Susan R. Smith, Sharon stansberry, Linda Suchocki, Susan Swoiskin, Leslie Ann Urban, Mary B. Van Wingen, Gretchen M. Vermeulen, Verland Z. Walker, Jayne Walworth, Elaine Devorah Webber, Julie Ann Webster, Sora Weller, Julie L. Weyburne, Malorie Whitefield, Frances Wiecha, Anne C. Wise

School of Nursing Class of 1990

Top Row: Mary D. Acosta, Stephanie A. Alexovich, Lisa K. Astalos, Sandra L. Barbish, Jaine Bieda, Jennifer L. Blair, Victoria L. Brace, Debbie R. Brown, Sandra D. Carlson, Timothy J. Cockerham, Polly A. Cook, Suzanne M. Delisio, Jefferey Deloach

Row 2: Susan L. Dill, Tami Dykstra, Roberta E. Figgs, Roberta Jo Franzese, Dianer Szczerowski, Kimberly M. Schymik, Michelle F. Bingham, Lynnette A. Golen, Paola G. Pieri, Donna L. Fordanich, Teri L. Freedman, Kara L. Gathmann

Row 3: Marilyn S. Granner, Ann Marie Hartmus, Melissa Hoheb, Susan M. Hutchins

Row 4: Amy S. Jacobs, Renee M. Jannette, Wendy J. Jenuwine, Lori B. Kantor

Row 5: Kristine E. Karfis, Jenny G. Kist, Susan M. Kistka, Kaye M. Kowalske, Marilyn A. Krage, Roberta E. Kumm

Row 6: Ianya A. Lattimore, Andrea S. Lipian, Wendy J. Lipinski, Wendi M. Lisman

Row 7: Susan E. Little, Donna M. Markos, Rita S. Mayle, Lynn M. Mccall, Nancy J. Montange, Aimee J. Myers

Row 8: Clare H. Nagle, Michelle L. Noble, Janice B. Lindbers, Violet Barkauskas, Rhetaugh G. Dumas, Beverly Jones, Shake Kettfian, Elisabeth Pennington, Joyce V. Perry, Darlene L. Phelps

Row 9: Donna M. Piccolo, Lisa A. Richmond, Lisa A. Rowlison, Brent E. Runyon, Rebecca A. Seiffert, Lucinda E. Smith, Amy E. Spangler, Dan C. Steele, Beth Stephens, Kim D. Tiedrich, Lisa J. Wallace, Jennifer P. York, Christine C. Zielke

Dept. of Sociology faculty, October 1959

First row: Meyer, Kish, Aberle, Janowitz, Hawley, Campbell, Miner, Newcomb, Angell, Landecker, Freedman. Second row: Yellin, Bordua, Sharp, Varley, Lenski, Marsh, Blood, Swanson, Wilensky, Blalock, Goldberg

Genomewide Linkage Scan of 409 European-ancestry and African American Families with Schizophrenia: Suggestive Evidence of Linkage at 8p23.3-p21.2 and 11p13.1-q14.1 in the Combined Sample

We report the clinical characteristics of a schizophrenia sample of 409 pedigrees-263 of European ancestry ( EA) and 146 of African American ancestry ( AA)-together with the results of a genome scan ( with a simple tandem repeat polymorphism interval of 9 cM) and follow-up fine mapping. A family was required to have a proband with schizophrenia ( SZ) and one or more siblings of the proband with SZ or schizoaffective disorder. Linkage analyses included 403 independent full-sibling affected sibling pairs ( ASPs) ( 279 EA and 124 AA) and 100 all-possible half-sibling ASPs ( 15 EA and 85 AA). Nonparametric multipoint linkage analysis of all families detected two regions with suggestive evidence of linkage at 8p23.3-q12 and 11p11.2-q22.3 ( empirical Z likelihood-ratio score [ Z(lr)] threshold >= 2.65) and, in exploratory analyses, two other regions at 4p16.1-p15.32 in AA families and at 5p14.3-q11.2 in EA families. The most significant linkage peak was in chromosome 8p; its signal was mainly driven by the EA families. Z(lr) scores >= 2.0 in 8p were observed from 30.7 cM to 61.7 cM ( Center for Inherited Disease Research map locations). The maximum evidence in the full sample was a multipoint Z(lr) of 3.25 ( equivalent Kong-Cox LOD of 2.30) near D8S1771 ( at 52 cM); there appeared to be two peaks, both telomeric to neuregulin 1 ( NRG1). There is a paracentric inversion common in EA individuals within this region, the effect of which on the linkage evidence remains unknown in this and in other previously analyzed samples. Fine mapping of 8p did not significantly alter the significance or length of the peak. We also performed fine mapping of 4p16.3-p15.2, 5p15.2-q13.3, 10p15.3-p14, 10q25.3-q26.3, and 11p13-q23.3. The highest increase in Z(lr) scores was observed for 5p14.1-q12.1, where the maximum Z(lr) increased from 2.77 initially to 3.80 after fine mapping in the EA families.

Small-scale randomized controlled trials need more powerful methods of mediational analysis than the Baron-Kenny method

Objective: To devise more-effective physical activity interventions, the mediating mechanisms yielding behavioral change need to be identified. The Baron-Kenny method is most commonly used. but has low statistical power and May not identify mechanisms of behavioral change in small-to-medium size Studies. More powerful statistical tests are available, Study Design and Setting: Inactive adults (N = 52) were randomized to either a print or a print-plus-telephone intervention. Walking and exercise-related social support Were assessed at baseline, after file intervention, and 4 weeks later. The Baron-Kenny and three alternative methods of mediational analysis (Freedman-Schatzkin; MacKinnon et al.: bootstrap method) were used to examine the effects of social support on initial behavior change and maintenance. Results: A significant mediational effect of social support on initial behavior change was indicated by the MacKinnon et al., bootstrap. and. marginally. Freedman-Schatzkin methods, but not by the Baron-Kenny method. No significant mediational effecl of social support on maintenance of walking was found. Conclusions: Methodologically rigorous intervention studies to identify mediators of change in physical activity are costly and labor intensive, and may not be feasible with large samples. The Use of statistically powerful tests of mediational effects in small-scale studies can inform the development of more effective interventions. (C) 2006 Elsevier Inc. All rights reserved.

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

Anxiety disorders and depression and risk for drug use disorders across the life course: Sex and ethnic contrasts

The present study examined the linkage between mental (i.e., anxiety disorders and depression) and drug use disorders in a multi-ethnic (i.e., 25% Euro-American, 38% Hispanic/Latino, 33% African American, 4% other) sample of adults (N = 1638, age 18–93 years old). Risk for drug use disorders was examined, while attending to methodological issues of prior research including (1) psychiatric comorbidity, (2) variations in risk associated with sex, ethnicity, and age, and (3) temporal order between mental and drug use disorders. ^ Participants were assessed using the Composite International Diagnostic Interview (CIDI; World Health Organization, 1990). A life history calendar (Freedman et al., 1988) was used to aid the ordering of onsets of all disorders assessed. ^ Preliminary analysis indicated anxiety disorders and depression were significant predictors of drug use disorders, but after controlling for comorbidity and temporal order, anxiety disorders and depression were no longer predictive of drug use disorders. Findings are discussed in terms of their usefulness for prevention and treatment of drug use disorders. ^

American Manna: Religious Responses to the American Industrial Food System

“American Manna: Religious Responses to the American Industrial Food System” is an investigation of the religious complexity present in religious food reform movements. I conducted ethnographic fieldwork at four field sites. These field sites are a Jewish organic vegetable farm where the farmers begin their days with meditation, a Christian raw vegan diet center run by Messianic Jews, a Christian family that raises their cattle on pastures and sends them to a halal processing plant for slaughter, and a Jewish farm where Christian and Buddhist farm staff helped to implement shmita, the biblical agricultural sabbatical year.

The religious people of America do not exist in neatly bound silos, so in my research I move with the religious people to the spaces that are less clearly defined as “Christian” or “Jewish.” I study religious food reformers within the framework of what I have termed “free-range religion” because they organize in groups outside the traditional religious organizational structures. My argument regarding free-range religion has three parts. I show that (1) perceived injustices within the American industrial food system have motivated some religious people to take action; (2) that when they do, they direct their efforts against the American food industry, and tend to do so outside traditional religious institutions; and finally, (3) in creating alternatives to the American food industry, religious people engage in inter-religious and extra-religious activism.

Chapter 1 serves as the introduction, literature review, and methodology overview. Chapter 2 focuses on the food-centered Judaism at the Adamah Environmental Fellowship at the Isabella Freedman Jewish Retreat Center in Falls Village, CT. In Chapter 3, I discuss the Hallelujah Diet as prescriptive literature and as it is put into practice at the Hallelujah Diet Retreat Center in Lake Lure, NC. Chapter 4 follows cows as they move from the grassy hills of Baldwin Family Farms in Yanceyville, NC to the meat counter at Whole Foods Markets. In Chapter 5, I consider the shmita year, the biblical agricultural sabbatical practice that was reimagined and implemented at Pearlstone Center in Baltimore, MD during 2014-2015. Chapter 6 will conclude this dissertation with a discussion of where religious food reform has been, where it is now, and a glimpse of what the future holds.

Measuring the Diversity and the Integration of Film Production in Mercosur: A Social Network Analysis

Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.

Ensinar pela Cultura Visual: relações possíveis entre educação e práticas contemporâneas de visualidade

A experiência humana é a cada dia mais visual e o entendimento acerca das práticas de visualidade, bem como dos artefatos visuais que permeiam nosso cotidiano, torna-se hoje imprescindível, especialmente no âmbito da Escola Pública. Nesse sentido, o presente texto tem por objetivo continuar uma discussão sobre as relações possíveis entre os campos da educação e da Cultura Visual, sugerindo um viés que sistematize uma espécie de epistemologia da cultura visual. Para isso, utilizamos como eixo argumentativo a ideia de um ensino pela Cultural Visual, em oposição ao que seria um ensino da Cultura Visual, construindo, a partir deste termo, três enunciados: de que a cultura visual é um campo transdisciplinar e portanto não pode ser ensinado como um conjunto fechado de conteúdos; que a Cultura Visual pode ser entendida como um tipo de método ou estratégia para interligar os conteúdos da Escola ao cotidiano extraescolar dos alunos; por fim, um manifesto em defesa de uma Educação pela Cultura Visual. Para embasar tais discussões e proposições, lançamos mão das perspectivas teóricas de autores como Hernández (2000; 2005; 2007); Freedman (2006); Mirzoeff (2003); Eisner (2008); Freire (2005); dentre outros.

Un extranjero en la selva

Una de las razones más fuertes que tuve para elegir aColombia para mi año de estudio afuera fue la cantidad de oportunidades para viajar, inclusive viajar a la selva. No es que no haya naturaleza en los Estados Unidos. Hay bosque a la lata. Pero lo que no tenemos es jungla con micos, anacondas. Indrgenas y todo lo que lleva la selva. Siempre habra visto los programas educacionales mostrando cómo viven los animales y cómo sobreviven los Indios en ella

Predictors of Patient Activation Among Underserved Patients in a Nurse-managed Health Center: A Pilot Study

The concept of patient activation has gained traction as the term referring to patients who understand their role in the care process and have “the knowledge, skills and confidence” necessary to manage their illness over time (Hibbard & Mahoney, 2010). Improving health outcomes for vulnerable and underserved populations who bear a disproportionate burden of health disparities presents unique challenges for nurse practitioners who provide primary care in nurse-managed health centers. Evidence that activation improves patient self-management is prompting the search for theory-based self-management support interventions to activate patients for self-management, improve health outcomes, and sustain long-term gains. Yet, no previous studies investigated the relationship between Self-determination Theory (SDT; Deci & Ryan, 2000) and activation. The major purpose of this study, guided by the Triple Aim (Berwick, Nolan, & Whittington, 2008) and nested in the Chronic Care Model (Wagner et al., 2001), was to examine the degree to which two constructs– Autonomy Support and Autonomous Motivation– independently predicted Patient Activation, controlling for covariates. For this study, 130 nurse-managed health center patients completed an on-line 38-item survey onsite. The two independent measures were the 6-item Modified Health Care Climate Questionnaire (mHCCQ; Williams, McGregor, King, Nelson, & Glasgow, 2005; Cronbach’s alpha =0.89) and the 8-item adapted Treatment Self-Regulation Questionnaire (TSRQ; Williams, Freedman, & Deci, 1998; Cronbach’s alpha = 0.80). The Patient Activation Measure (PAM-13; Hibbard, Mahoney, Stock, & Tusler, 2005; Cronbach’s alpha = 0.89) was the dependent measure. Autonomy Support was the only significant predictor, explaining 19.1% of the variance in patient activation. Five of six autonomy support survey items regressed on activation were significant, illustrating autonomy supportive communication styles contributing to activation. These results suggest theory-based patient, provider, and system level interventions to enhance self-management in primary care and educational and professional development curricula. Future investigations should examine additional sources of autonomy support and different measurements of autonomous motivation to improve the predictive power of the model. Longitudinal analyses should be conducted to further understand the relationship between autonomy support and autonomous motivation with patient activation, based on the premise that patient activation will sustain behavior change.