Tips on How to Make a Scientic Poster

July 8, 2011

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

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

 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

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.

RESULTS

STRESS, RACISM, AND HEALTH AMONG AFRICAN AMERICAN AND HISPANIC AMERICAN WOMEN

Erin 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

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

ACKNOWLEDGEMENTSThe 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.

METHODSParticipants 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%

DesignCross-sectional data were taken from surveys conducted at the baseline step of a larger randomized controlled trial

MeasuresSelf-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

Objective 1Is racism-related stress predictive of physical health and/or

depression after accounting for general stress?

OBJECTIVES1.Is racism-related stress predictive of physical health and/or depression after accounting for general stress levels?

2.Is the relationship of racism-related stress to physical and/or mental health different for AAs and HAs, after accounting for general stress?

CONCLUSIONS1.Racism-related stress was predictive of depressive symptoms and physical health ratings after accounting for general stress

2.There was a main association between ethnicity and general health after accounting for general and racism-related stress; HA’s reported poorer general health

3.The racism-related stress and physical/mental health relationship does not differ depending on ethnic group status between AA and HA women

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

Objective 2Is the relationship of racism-related stress to physical and/or mental health different for AAs and HAs, after accounting for general stress?

Table 3. Hierarchical multiple regression models predicting mental and physical health outcomes from the interaction of racism-related stress and ethnicity

Outcome F df R2 ΔR2 Racism-related stress b

Ethnicity b

Interaction b

PHQ 29.02*** 4, 110 .513 .000 .62 .74 -.04

HRQOL-1 28.74*** 4, 114 . 235 .007 .19 .51** -.12

HRQOL-2 24.29*** 4, 111 .134 .001 1.41 .76 -.32

HRQOL-3 18.25*** 4, 113 .392 .025 3.45* .99 -1.40

HRQOL-4 29.24*** 4, 111 .250 .011 2.18 -.39 -1.14

Note. * p < 05; ** p < .01; *** p < .001; Models were adjusted for PSS scores in the first step, and main effect of ethnicity in the second step

Table 2. Hierarchical multiple regression models predicting mental and physical health outcomes from racism-related stress

Outcome F df R2 ΔR2 β

PHQ 58.10*** 2, 112 .509 .020 .15*

HRQOL-1 12.61*** 2, 116 .179 .000 -.02

HRQOL-2 8.47*** 2, 113 .130 .033 .19*

HRQOL-3 33.10*** 2, 115 .365 .004 .07

HRQOL-4 17.64*** 2, 113 .238 .007 .09

Note. * p < 05; ** p < .01; *** p < .001; Models were adjusted for PSS scores in the first step

Descriptive Analyses

Table 1. Study variables M (SD)

Variables Total (N = 119) AA (n = 41) HA (n = 78)

Predictors PSS 18.03 (7.11) 18.83 (7.30) 17.60 (7.03)

RtoR 2.32 (1.48) 2.61 (1.76) 2.17 (1.30)

Outcomes PHQ 5.05 (5.34) 5.25 (5.02) 4.95 (5.53)

HRQOL-1 2.88 (1.06) 2.61 (1.12) 3.03 (0.97)

HRQOL-2 4.45 (6.98) 4.41 (7.30) 4.47 (6.85)

HRQOL-3 5.92 (8.88) 6.25 (8.88) 5.74 (8.93)

HRQOL-4 4.16 (7.88) 5.09 (7.52) 3.67 (8.06)

Note. ANOVAs did not reveal significant differences between AAs and HAs on any variables

racism-related stress

ethnicity

mental health, physical health

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, 2 Moores UCSD Cancer Center

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.

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.

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

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

METHOD

Procedures:•Sample (N = 57)

•Mean age = 58.8 years (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.

METHOD

Procedures:•Sample (N = 57)

•Mean age = 58.8 years (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.

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.

OBJECTIVES

1) To identify and understand management strategies in a sample of African American cancer survivors. 2) To assess the effect of depression and management strategies on levels of fatigue in African American cancer survivors.

OBJECTIVES

1) To identify and understand management strategies in a sample of African American cancer survivors. 2) To assess the effect of depression and management strategies on levels of fatigue in African American cancer survivors.

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.

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.

Table 1

Treatment Type (N = 57)

Figure 1

Surgery

Chemo Radiation

Watch and Wait

75.4%(n=43)

54.4%(n=31)

50.9%(n=29)

19.3%(n=11)

Percentage of Participants Reporting Use of Each Type of Management Strategy

Figure 2

R2 change F p β

Age .077 3.597 (1, 43) .065 -.008

Depression .646 97.79 (1, 42) <.001 .792 **

Management Strategies (#)

.037 6.264 (1, 41) .016 -.200 *

Categories Examples

I- Obtaining therapy

o Sought help from a psychiatrist, psychologist, social worker, or other mental health professionalo Attending a support group led by health professionals, one that is hospital- or clinic-based, or a peer-led support group

II- Seeking Relaxation

o Listening to/creating musico Non-educational readingo Use of alcohol or marijuana

III- Managing/ Limiting Activity and Time

o Breaking tasks into smaller stepso Planning a scheduleo Accepting fewer commitments

IV- Seeking and Using Social Support

o Informal conversation with relatives and friendso Physical gestures of support (e.g., holding, hugging, etc.)

V- Increasing Rest

o Napping/going to bed earlier

VI- Seeking Information

o Reading from or listening to sources that educate about fatigue and fatigue intervention including articles, Internet sites, books, television, etc.o Obtaining information from qualified sources such as medical doctors/health professionals or established agencies/ organizations (e.g., the American Cancer Society).

VII- Improving Dietary Practices

o Eating energy producing foodso Modifying diet to including healthier food consumptiono Use of any type of vitamins

VIII- Increasing Exercise

o Walking and runningo Working out/ sports

IX- Taking Medications/ Following Medical Regiments

o Antidepressantso Sleeping aidso Complementary and Alternative Medicines (e.g. acupuncture)

X- Avoidance/ Apathy

o Try not to think about ito Avoiding social commitments or events

XI- Spirituality/ Religion

o Prayero Attending religious services

XII- Cognitive o Increasing motivation through changing one’s thoughtso Learning from mistakes

Distress Levels of Prostate Cancer Patients’ Spousal CaregiversRina 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

BackgroundBackground• 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.

• 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.

MethodsMethods

ResultsResults

Conclusions and ImplicationsConclusions 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 DisclosureAcknowledgements and DisclosureThis 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.

Study AimStudy Aim

*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.

Measure Observed M (SD)

Normative M (SD)*

“Clinical Cutoff”†

% in “clinical range”†

IES-R Avoidance 0.8 (0.9) --- > 1.5 18.4Intrusion 1.1 (0.9) --- > 1.5 25.8Hyperarousal 0.7 (0.8) --- > 1.5 17.2Total Distress 2.6 (2.3) --- > 1.5 20.2

POMSTension-Anxiety 10.4 (7.3) 7.0 (5.5) > 12.5 28.7Depression-Dejection 10.0 (10.5) 7.1 (8.4) > 15.5 21.3Anger-Hostility 7.8 (8.2) 6.6 (6.7) > 13.3 18.9Vigor-Activity (reversed) 17.5 (7.2) 20.2 (6.2) > 26.4 8.5Fatigue-Inertia 8.8 (7.3) 7.3 (5.7) > 13.0 23.2Confusion-Bewilderment 7.1 (5.3) 5.2 (4.1) > 9.3 23.8Total Mood Disturbance 26.4 (37.3) 12.7 (29.6) > 42.3 30.5

SF-36Physical Functioning 81.1 (25.6) 83.0 (23.8) < 59.2 18.3Role-Physical 71.9 (37.3) 77.9 (35.3) < 42.6 22.0Bodily Pain 66.7 (25.9) 70.2 (23.4) < 46.8 23.2General Health 72.8 (22.4) 70.1 (21.4) < 48.7 17.7Vitality 56.9 (21.7) 57.0 (21.1) < 35.9 20.1Social Functioning 75.7 (25.2) 83.6 (23.0) < 60.6 25.0Role-Emotional 65.6 (41.0) 83.1 (31.6) < 51.5 34.4Mental Health 71.7 (19.4) 75.2 (17.6) < 57.6 22.0Physical Health Component 50.5 (12.2) 50.0 (10.0) < 40.0 20.2Mental Health Component 44.1 (14.3) 50.0 (10.0) < 40.0 36.2

SUBJECTSSUBJECTS• 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%

PROCEDUREPROCEDURE• Multifaceted recruitment strategy

(physician outreach, flyers, etc.) • Both patient and spouse/partner were

required to consent before either could enroll

• Patients and spouses/partners Patients and spouses/partners completed questionnaire packets completed questionnaire packets independentlyindependently

• Only spouse/partner responses were Only spouse/partner responses were used for this analysisused for this analysis

What did the doctor say?: Health literacy and retention of What did the doctor say?: Health literacy and retention of verbal health information 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

BackgroundBackground

Research Research QuestionQuestion

MethodsMethods

LimitationsLimitations

ConclusionsConclusions

• 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.

• How will health literacy effect patients’ ability to recall orally communicated medical diagnoses and instructions?

SubjectsSubjects• 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

ProcedureProcedure 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 VariablesOutcome 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)

Demographic Characteristics of Sample Demographic Characteristics of Sample (n=380)(n=380)

• 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).

• 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 NORTHWESTERN UNIVERSITY FEINBERG SCHOOL OF MEDICINE, DIVISION OF GENERAL INTERNAL FEINBERG SCHOOL OF MEDICINE, DIVISION OF GENERAL INTERNAL MEDICINEMEDICINE

ResultsResults

Variable β (95% CI)

Literacy Inadequate Literacy -1.21 (-1.94 - -0.48)** Marginal Literacy -0.53 (-1.09 - 0.02) Adequate Literacy --- ---

Age -0.01 (-0.04 - 0.02)

Gender Male -0.53 (-0.92 - -0.14)** Female --- ---

Race African American -0.47 (-1.17 - 0.24) Caucasian 0.29 (-0.39 - 0.97) Other --- ---

Education ≤High School -0.71 (-1.26 - -0.16)* Some college or tech school -0.58 (-1.07 - -0.08)* College graduate -0.38 (-0.83 - 0.07) Graduate degree --- ---

# of comorbid conditions (0-7) -0.25 (-0.40 - -0.09)**

Exposure to GERD Patient has GERD diagnosis 0.23 (-0.17 - 0.62) Family member has GERD 0.17 (-0.29 - 0.63) No experience --- ---

Constant 7.33 (5.20 - 9.47)** CI=confidence intervals; * p<.05; ** p<.01

Sample Questions:

•When does Dr. Baker want you to take your pill?

•What foods and drinks does Dr. Baker say you should avoid?.

Abbreviations – SD

Variable Total Literacy Level Inadequate Marginal Adequate

Age, mean(SD) 63.2(5.4) 64.9(5.4) 65.2(6.4) 62.7(5.1) Gender, % Female 73.2 73.3 81.1 71.7 Male 26.8 26.7 18.9 28.3 Education, % ≥High School 21.05 73.3 49.1 10.8 Some college or technical school 19.74 13.3 26.4 19.2 College graduate 23.68 10.0 11.3 27.3 Graduate degree 35.53 3.3 13.2 42.7 Race, % African American 33.9 76.7 66.0 23.9 Caucasian 58.7 13.3 26.4 69.0 Other 7.4 10.0 7.6 7.1 # of comorbid conditions, mean(SD) 1.7(1.2) 2.5(1.4) 2.1(1.2) 1.5(1.1) Exposure to GERD, % Family member has diagnosis 19.5 13.3 13.2 21.2 Patient has diagnosis 36.0 30.0 43.4 35.4 No experience 44.5 56.7 43.4 43.4

Multivariate ResultsMultivariate Results

•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