Tips on How to Make a Scientic Poster

1. Tips on How to Make a Scientic Poster July 8, 2011

2. Template Options • 1) Use a ‘lab’ (i.e., Erin, Rina, Kadie) template and input your own words, pictures, etc. • 2) Download a template • http://www.posterpresentations.com/html/free_poster_templates.html • Edit in Powerpoint • http://www.studentposters.co.uk/templates.html • Edit in PowerPoint OR Word •  I would recommend makesigns.com

3. Makingsigns.com • http://www.makesigns.com/SciPosters_Home.aspx • (Main website) • http://www.makesigns.com/SciPosters_Templates.aspx • (Template) • Can order poster to be printed and shipped to your house or to conference • Standard (Within 6 business days): $9.00 • FedEx Next Day Shipping: $32.00 • Poster Prices: See Pricing table

4. How to Use PowerPoint • http://www.makesigns.com/tutorial/ • Size: • File • Page Setup • Put in desired width and height • Text Box: • Insert • Text Box (OR insert table, chart, etc.) • Background: • Format • Slide Background (OR theme colors) • Logo: • Copy and paste from lab template

5. Color Choices • Use a light color background and dark color letters for contrast. • Avoid dark backgrounds with light letters - very tiring to read. • If you use multiple colors, use them in a consistent pattern - otherwise viewers will spend their time wondering what the pattern is rather than reading your poster. • Overly bright colors will attract attention - and then wear out readers' eyes. • Consider people who have problems differentiating colors, especially when designing graphics - one of the most common is an inability to tell green from red.

6. RESULTS • Objective 1 • Is racism-related stress predictive of physical health and/or depression after accounting for general stress? STRESS, RACISM, AND HEALTH AMONG AFRICAN AMERICAN AND HISPANIC AMERICAN WOMENErin L. Merza; Vanessa L. Malcarneabc; Natasha Rileyd; Georgia Robins Sadlerac aSDSU/UCSD Joint Doctoral Program in Clinical Psychology; bSan Diego State University; cMoores UCSD Cancer Center; dVista Community Clinic OBJECTIVES Is racism-related stress predictive of physical health and/or depression after accounting for general stress levels? Is the relationship of racism-related stress to physical and/or mental health different for AAs and HAs, after accounting for general stress? Objective 2 Is the relationship of racism-related stress to physical and/or mental health different for AAs and HAs, after accounting for general stress? • METHODS • Participants • 119 women from San Diego county • Age. range = 21-81; M(SD) = 40.42 (3.87) • Language. English = 76%, Spanish = 24% • Ethnicity. AA = 34%; HA = 66% • Marital status. single = 36%, married = 30%, • divorced/separated/widowed = 34% • Education. high school or less = 45%; some college = 45%; • college = 7%; more than college = 3% • Income. < $20,000 = 59%, $20,001 - $35,000 = 29%, • $35,001 - $50,000 = 3%; > $50,000 = 9% • Design • Cross-sectional data were taken from surveys conducted at the baseline step of a larger randomized controlled trial • Measures • Self-report questionnaires included the following instruments: • Perceived Stress Scale-10 (PSS) • Total Score: 0 (no stress) to 40 (greater stress) • Reactions to Race Module (item 6) from the BRFSS (RtoR) • Within the past 12 months on average, how often have you felt emotionally upset, for example angry, sad, or frustrated, as a result of how you were treated based on your race: 1 (never) to 7 (constantly) • Patient Health Questionnaire-9 (PHQ) • Total Score : 0 (no depressive symptoms) to 27 (more symptoms) • Health Related Quality of Life-4 (HRQOL) • 1: Rating of general health: 1 (excellent) to 5 (poor) • 2: Rating of physical health over past 30 days • 3: Rating of mental health over past 30 days • 4: Functional impairment over past 30 days due to mental/physical health BACKGROUND Racism is a common occurrence for African Americans (AAs) and Hispanic Americans (HAs) Individuals who experience racism are likely to experience high levels of stress above and beyond stress related to the hassles of daily life Both stress and racism-related stress are associated with a decline in psychological and physical health Ethnic minorities may be at an increased risk for poor health outcomes The relationship between racism-related stress and mental/physical health may differ for AAs and HAs ethnicity mental health, physical health racism-related stress • IMPLICATIONS • Future studies should examine causal relationships using prospective designs and the roles of acculturation and/or ethnic identity • Although the racism-related stress and physical/mental health relationships did not differ by ethnic group in this sample, ethnicity may be an important variable to consider when developing culturally competent stress reduction interventions • CONCLUSIONS • Racism-related stress was predictive of depressive symptoms and physical health ratings after accounting for general stress • There was a main association between ethnicity and general health after accounting for general and racism-related stress; HA’s reported poorer general health • The racism-related stress and physical/mental health relationship does not differ depending on ethnic group status between AA and HA women ACKNOWLEDGEMENTS The authors would like to acknowledge the following sources of support for this study: California Breast Cancer Research Program’s 13AB-3500, 14BB-2601; NCI grants U54 CA132384, U54 CA132379, U56 CA92079, U56 CA92081; P60 MD000220-07; and P30 CA023100-23.

7. Relationship of Depression and Management Strategies to Fatigue Levels in African American Cancer Survivors Kadie M. Harry, B.A.1, Maggie L. Syme, Ph.D.1,2, Vanessa L. Malcarne, Ph.D.1,2, Marc Emerson, B.A.1, Georgia Robins Sadler, B.S.N, M.B.A, Ph.D.1,2 1 San Diego State University, 2Moores UCSD Cancer Center Table 1 • OBJECTIVES • To identify and understand management strategies in a sample of African American cancer survivors. • To assess the effect of depression and management strategies on levels of fatigue in African American cancer survivors. • RESULTS • Preliminary analyses: • Fatigue and depression ratings were not significantly • different across medical variables (i.e., stage at diagnosis, number of treatments, time since treatment), or socio-demographic variables (i.e., ethnicity, relationship status, living situation, acculturation) with the exception of age. • Management strategies reported per individual: • M = 3.63 (SD = 1.83) • Main Findings: • The regression model included age, depression score, and number of management strategies reported as predictors of fatigue total score. • Accounted for 55% of the variance in fatigue scores • (Adj R² = .74, F(3,41) = 43.16, p < .001). • The interaction of depression and management strategies was not significant. • * p < .05, ** p <.01 Figure 1 Treatment Type (N = 57) • BACKGROUND • Cancer-related-fatigue and disparities • Cancer-related fatigue (CRF) is the most commonly reported symptom after treatment, affecting up to 96% of patients and survivors. • Research on post-treatment fatigue has focused mainly on Caucasian samples. African Americans have the highest incidence for all cancers combined, making it vital to gain insight into their post-treatment fatigue and coping mechanisms.   • Depression and CRF • Previous research has shown that increased CRF is associated with depression and negatively impacts quality of life by increasing distress, isolation, and other problems. • Due to the high percentage of cancer survivors that experience fatigue, efforts have been made to study various ways to cope with its’ psychological and physical effects. • Management Strategies • Survivors may employ multiple strategies to cope with the effects of fatigue on daily functioning. • This can be effective in decreasing the detrimental effects of CRF and predict successful adjustment in cancer patients. • METHOD • Procedures: • Sample (N = 57) • Mean age = 58.8years (SD = 12.66) • Predominantly female (59.6%) • Highly educated (47.4% with a college or graduate degree) • Mean time since treatment = 36 months • Eligibility requirements: • African American • 18 or older • Completed cancer treatment in the past three months • Participants completed measures to assess fatigue and depression. • Semi-structured interviews were conducted at two times (~4-6 weeks apart) to assess fatigue-management strategies. • Responses from the two interviews were coded into 12 categories (interrater reliability = 93.55%). • Measures: • Center for Epidemiological Studies-Depression scale (CES-D) • 20-items • “0” (rarely/none) to “3” (most/all the time) • Total score = sum of the 20 items, ranging from 0 to 60 • Multi-dimensional Fatigue Symptom Inventory-Short Form (MSFI-SF) • 30-item short form of the MFSI • 5 subscales of 6 items each: • 1) general; 2) physical; 3) emotional; 4) mental fatigue; and 5) vigor • Total score = (general + physical + emotional + mental fatigue) – vigor • Scores range from -24 to 96 • Management Strategies • See Table 1 for description of management strategies and exemplars. • CONCLUSIONS • There are a wide range of fatigue-management strategies employed by this sample of African American cancer survivors • Employed at differential rates • Some are likely more productive/useful than others • Implications: • Self-employing management strategies may add a protective element to those experiencing CRF, though the impact of depression on fatigue is great. • Limitations of the Study: • Small sample size • Did not assess for changes in additional coping strategies across assessment times • Did not measure the magnitude or frequency of management strategies per individual. • Future Directions: • Research exploring the frequency, magnitude, and value of management strategies may help elucidate their role as a protective factor against fatigue. Figure 2 Percentage of Participants Reporting Use of Each Type of Management Strategy Acknowledgements: This research was supported by the following grants: NIH R25CA65745; NIH P30CA023100; NIH U56CA92079/U56CA92081; NIH U54CA132379/U54CA132384; and NIH-NCMHD CRCHD (P60 MD000220). We thank the many survivors who generously gave us their time to participate in this research study.

8. Distress Levels of Prostate Cancer Patients’ Spousal Caregivers Rina M. Sobel, BA1; Erin L. Merz, MA1; Vanessa L. Malcarne, PhD123; Celine M. Ko, PhD4; James W. Varni, PhD5; Georgia Robins Sadler, BSN, MBA, PhD2 1SDSU/UCSD Joint Doctoral Program in Clinical Psychology, 2Moores UCSD Cancer Center, 3San Diego State University, 4University of Redlands, 5Texas A&M University Background Results • Spouse/partner caregivers’ emotional states affect patient health. This is especially true in prostate cancer (PC), a “relationship disease.” • Many interventions are designed to target spouse/partner distress, though actual distress levels of spouses/partners are unclear. • In particular, little is known about the distress levels of spouses/partners who seek therapeutic psychosocial interventions offered through cancer centers. Study Aim • To describe the psychosocial distress of spouses/partners of PC patients who sought a therapeutic intervention teaching problem-solving skills to improve cancer-related quality of life. Methods • SUBJECTS • Female spouses/partners (N = 163)of prostate cancer patients • Age: M = 61.54, SD = 10.73 • Ethnicity: Caucasian = 81.7%; Latino= 5.5%; African American = 5.5%; Asian = 4.9%; Other = 2.4% • Education: Some college or less = 59.7%; College graduate = 40.3% • Work Status: Full-time = 23.8%; Part-time = 15.2%; Not working but looking for a job = 3.7%; Retired = 56.7% • Marital Status: Married = 89.6%; Cohabitating = 10.4% • PROCEDURE • Multifaceted recruitment strategy (physician outreach, flyers, etc.) • Both patient and spouse/partner were required to consent before either could enroll • Patients and spouses/partners completed questionnaire packets independently • Only spouse/partner responses were used for this analysis • MEASURES OF DISTRESS • Impact of Event Scale-Revised (IES-R) • 22 item self-report questionnaire examining subjective distress related to a particular recent event • Three subscales: • Subscales sum to produce a total distress score; subscale scores range from 0-4; total score ranges from 0-16 • Higher scores indicate more distress • Profile of Mood States (POMS) • 65 item self-report questionnaire that examines and quantifies transient mood states • Six subscales/Mood states: • Subscales sum to produce a Total Mood Disturbance score; total score ranges from -32 to 228 • Higher scores indicate more distress (reverse for Vigor-Activity subscale) • Mental Outcomes Study Short-Form Health Survey (SF-36) • 36 item self-report questionnaire measuring health related quality of life • Eight subscales: • Subscales sum to produce two Component scores: Physical Health and Mental Health • Subscale and Component scores range from 0 to 100, transformed so normative M = 50 (SD = 10) • Higher scores indicate better quality of life • *POMS normative data from Nyenhuis, Yamamoto, Luchetta, Terrien and Parmentier, 1999; SF-36 normative data based on 1998 U.S. population, from www.sf-36.org • †IES-R clinical cutoff from Creamer, Bella and Failla, 2003; POMS clinical cutoff = 1SD>M; SF-36 clinical cutoff = 1 SD < M • A notable majority of the sample were retired, Caucasian, and married. • 20% of the sample expressed cancer-specific distress (IES-R). • Women were particularly likely to display transient (POMS) and generalized (SF-36) distress. Conclusions and Implications • The majority of spouses/partners had sub-clinical scores on all measures. • Approximately one-fifth to one-third of spouses/partners scored in the clinical range on at least one measure, though fewest did so on the IES-R, which examined PC-specific stress. • Clinicians must recognize that spouses/partners could be far more distressed than data indicate, especially if evaluating only PC-specific distress. • Interventions targeting general life stressors may be more appropriate than PC-specific interventions. • Spouses/partners agreeing to participate in educational interventions appear to already be coping relatively well. The women who most need these interventions may be those who are most difficult to recruit. Acknowledgements and Disclosure This research was supported a grant from the UCSD Cancer Center Foundation, the National Cancer Institute Grant #R25CA65745 and the California Cancer Research Program Grant #1II0049.For more information, please contact Rina M. Sobel at rsobel@ucsd.edu. Disclosure: We, or an immediate family member, including spouse or partner, have no financial relationship(s) relevant to the content of this CME activity.

9. What did the doctor say?: Health literacy and retention of verbal health information Sobel RM1, Waite KR1, Ross EL1, Curtis LM1, Bojarski EA1,Wolf MS1 1Northwestern University Feinberg School of Medicine, Division of General Internal Medicine, Health Literacy and Learning Program Multivariate Results Background Demographic Characteristics of Sample (n=380) • The relationship between low health literacy and poor health outcomes has been well documented. • The problem of low health literacy has led to increased attention towards how individuals access, understand, and retain health information. Abbreviations – SD • After adjusting for age, gender, education, chronic conditions, and prior exposure to GERD, patients with lower literacy were still less likely to have recalled the information shared during the verbal medical encounter compared to those with higher literacy scores Research Question • How will health literacy effect patients’ ability to recall orally communicated medical diagnoses and instructions? Methods • Subjects • 380 adults, ages 55-74 • Recruited from three sites in the Chicago area; two of the ACCESS Community Health Network’s Federally Qualified Health Centers as well as the Northwestern Memorial Faculty Foundation General Internal Medicine ambulatory care clinic • Procedure • Participants were shown a video simulating a physician, wearing a white doctor’s coat and a stethoscope, verbally diagnosing gastroesophageal reflux disease (GERD) • After viewing the program we immediately administered a functional knowledge assessment. • The same knowledge assessment was administered again twenty minutes after the conclusion of the viewing. • Outcome Variables • Information retention. Measured using a 10-point functional knowledge assessment that was administered both immediately and twenty minutes after viewing the video • Health literacy as measured by the Test of Functional Health Literacy in Adults (TOFHLA) Results • Overall, information retention averaged 5.7 (1.9) out of 10 possible knowledge points. • Those with inadequate and marginal literacy recalled significantly less than those with adequate literacy (3.9(1.8), 4.9(1.5), 6.1(1.8) respectively, p<.001). Limitations Conclusions • Sample Questions: • When does Dr. Baker want you to take your pill? • What foods and drinks does Dr. Baker say you should avoid?. • Individuals, especially those with low literacy skills, would benefit from dissemination of tangible materials that simply express medical instructions to supplement recommendations discussed during a medical encounter. • Clinical screening of patient literacy level should also be considered to identify those at greatest risk for poor retention of verbally conveyed information. NORTHWESTERN UNIVERSITY FEINBERG SCHOOL OF MEDICINE, DIVISION OF GENERAL INTERNAL MEDICINE