Reducing Assessment Barriers for Patients With Low Literacy

Reducing Assessment Barriers for Patients With Low Health Literacy

The purpose of this study is to determine the effects of health literacy on questionnaire-based measurement.

Study Overview

• Status: Completed
• Conditions: Health Literacy
• Intervention / Treatment: Other: Computerized Talking Touchscreen; Other: Phone Administration of Questionnaires

Detailed Description

Low health literacy as a barrier to healthcare. Health literacy is defined as "the degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions." A vast body of research shows that lower health literacy is associated with poorer outcomes, including higher hospitalization rates, worse health, and greater mortality. Approximately 75 million U.S. adults have low health literacy. Worse yet, racial and ethnic minorities and older individuals (age 65+) are more likely to have low health literacy, creating another mechanism for health disparities. These data indicate that many people will have difficulties adhering to treatment regimens that require health literacy, as well as completing questionnaires for public health and health research and care.

Improving self-report assessment. Health surveys are ubiquitous, but almost no questionnaires used across the country have been validated for use with people who have low health literacy. This is a glaring shortcoming in current survey validation methodology; inaccurate surveys lead to false conclusions and threaten the empirical foundation of everyone's efforts to understand and improve public health, healthcare, and health outcomes. Our goal is to rectify this shortcoming. This study will 1) determine the effect of health literacy on widely-used questionnaires, 2) determine the stability of psychometric properties of questionnaires over time, and 3) test various testing formats to determine which ones work best for people with low health literacy.

Due to the COVID-19 pandemic, the study will implement phone-based assessments in addition to the original in-person protocol described above. The phone-based assessments will only be available to enrolled or previously enrolled participants. Participants will be asked questionnaires over the phone by a research coordinator at 3 time-points over 6 months.

• Study Type: Interventional
• Enrollment (Actual): 729
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Illinois
    • Chicago, Illinois, United States, 60611
      • Northwestern University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Be 18 years of age or older
• Be willing to provide informed consent, including signing the consent form
• Be willing to be randomized to administration method
• Be willing to complete questionnaires and interviews
• Be fluent in English and/or Spanish
• Be willing to attend three face-to-face sessions
• Have no plans to move out of the study area in the next six months

Exclusion Criteria:

• Significant cognitive or neurologic impairment
• Being a prisoner, detainee, or in police custody
• Unable to complete the consent process
• Inadequate vision to see study materials (worse than 20/80 corrected)
• Inadequate hearing or manual dexterity to use the computer system

Phone-based protocol:

Inclusion criteria:

1. Enrollment in the in-person protocol (including all inclusion/exclusion criteria from in-person protocol)
2. Access to reliable phone connection
3. Be willing to participant in three phone-based sessions

Exclusion criteria:

1. Unable to complete the consent process
2. Inadequate hearing for phone-based assessments

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Active Comparator: Pen-and-paper format; Based on randomization, participants in this group will receive traditional pen-and-paper questionnaires about health.	Other: Phone Administration of Questionnaires; This intervention will pilot questionnaire administration over the phone with currently enrolled or previously enrolled participants from the original intervention. This method was used during the COVID-19 pandemic.
Experimental: Computerized Talking Touchscreen; This group will receive the Computerized Talking Touchscreen intervention. Based on randomization, participants in this group will receive a computerized talking touchscreen version of our health questionnaires, which allows the participant to have questions and answer choices read aloud to them by the computer.	Other: Computerized Talking Touchscreen; The intervention is a computerized talking touchscreen designed to aid people with low health literacy. All Participants in both arms will complete a battery of health questionnaires. One group will complete questionnaires in traditional pen-and-paper format. The other group will receive the computerized talking touchscreen, which reads questions to participants on demand.; Other: Phone Administration of Questionnaires; This intervention will pilot questionnaire administration over the phone with currently enrolled or previously enrolled participants from the original intervention. This method was used during the COVID-19 pandemic.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
The Degree of Differential Item Functioning (DIF) in NIH Patient-Reported Outcomes Measurement Information System (PROMIS Profile 57 v 2.0) Anxiety Subscale	A primary outcome of this study will be the degree of DIF in NIH PROMIS questionnaire Anxiety subscale observed across adequate versus low health literacy. The outcome will be measured by a McFadden pseudo-R-square (R2), which captures the degree to which health-literacy group determines probability of response type for each item. The pseudo R2 is an analogue to R2 used in linear regression. For DIF analysis, each scale is normalized to a theta metric (mean = 0, standard dev. = 1 by definition). PROMIS is scaled by T-scores, referenced against the US population mean. Items are aggregated using item response theory, but aggregation is not relevant here because the McFadden pseudo-R2 is evaluated for each item. We report the maximum DIF value across items by condition. Pseudo-R2 values express how much health literacy and/or health literacy's interaction with anxiety determine the probability of response. Higher values correspond to higher DIF; lower values correspond to lower DIF.	6 months
Patient Health Questionnaire (PHQ-9)	A primary outcome of this study will be the degree of DIF observed in the Patient Health Questionnaire (PHQ-9), a questionnaire used to measure depression across adequate versus low health literacy. The outcome will be measured by a McFadden pseudo-R-square (R2), which captures the degree to which health-literacy group determines probability of response type for each item. Pseudo-R2 is an analogue to R2 used in linear regression. For DIF analysis, each scale is normalized to a theta metric (mean = 0, standard dev. = 1 by definition). Normally items are aggregated by a sum score, but the aggregation is not relevant to this study because the McFadden pseudo-R2 is evaluated for each item, not for aggregate scores. We report the maximum DIF value across items by condition. Pseudo-R2 values express how much health literacy and/or health literacy's interaction with depression determine the probability of response. Higher values correspond to higher DIF; lower values correspond to lower DIF.	6 months
The Degree of Differential Item Functioning (DIF) in NIH Patient-Reported Outcomes Measurement Information System (PROMIS Profile 57 v 2.0) Depression Subscale	A primary outcome will be the degree of DIF in NIH PROMIS questionnaire Depression subscale observed across adequate versus low health literacy. The outcome will be measured by a McFadden pseudo-R-square (R2), which captures the degree to which health-literacy group determines probability of response type for each item. The pseudo R2 is an analogue to R2 used in linear regression. For DIF analysis, each scale is normalized to a theta metric (mean = 0, standard dev. = 1 by definition). PROMIS is scaled by T-scores, referenced against the US population mean. Items are aggregated using item response theory, but aggregation is not relevant here because the McFadden pseudo-R2 is evaluated for each item. We report the maximum DIF value across items by condition. Pseudo-R2 values express how much health literacy and/or health literacy's interaction with depression determine the probability of response. Higher values correspond to higher DIF; lower values correspond to lower DIF.	6 months

Collaborators and Investigators

• Sponsor: Northwestern University
• Collaborators: National Institute on Minority Health and Health Disparities (NIMHD); National Institutes of Health (NIH)
• Investigators: Principal Investigator: James Griffith, PhD, Northwestern University

Publications and helpful links

General Publications

• Osborn CY, Paasche-Orlow MK, Davis TC, Wolf MS. Health literacy: an overlooked factor in understanding HIV health disparities. Am J Prev Med. 2007 Nov;33(5):374-8. doi: 10.1016/j.amepre.2007.07.022.
• Health literacy: report of the Council on Scientific Affairs. Ad Hoc Committee on Health Literacy for the Council on Scientific Affairs, American Medical Association. JAMA. 1999 Feb 10;281(6):552-7.
• Schillinger D, Grumbach K, Piette J, Wang F, Osmond D, Daher C, Palacios J, Sullivan GD, Bindman AB. Association of health literacy with diabetes outcomes. JAMA. 2002 Jul 24-31;288(4):475-82. doi: 10.1001/jama.288.4.475.
• Wolf MS, Davis TC, Osborn CY, Skripkauskas S, Bennett CL, Makoul G. Literacy, self-efficacy, and HIV medication adherence. Patient Educ Couns. 2007 Feb;65(2):253-60. doi: 10.1016/j.pec.2006.08.006. Epub 2006 Nov 21.
• Paasche-Orlow MK, Wolf MS. The causal pathways linking health literacy to health outcomes. Am J Health Behav. 2007 Sep-Oct;31 Suppl 1:S19-26. doi: 10.5555/ajhb.2007.31.supp.S19.
• Omachi TA, Sarkar U, Yelin EH, Blanc PD, Katz PP. Lower health literacy is associated with poorer health status and outcomes in chronic obstructive pulmonary disease. J Gen Intern Med. 2013 Jan;28(1):74-81. doi: 10.1007/s11606-012-2177-3. Epub 2012 Aug 14.
• Baker DW, Parker RM, Williams MV, Clark WS. Health literacy and the risk of hospital admission. J Gen Intern Med. 1998 Dec;13(12):791-8. doi: 10.1046/j.1525-1497.1998.00242.x.
• Davis TC, Arnold C, Berkel HJ, Nandy I, Jackson RH, Glass J. Knowledge and attitude on screening mammography among low-literate, low-income women. Cancer. 1996 Nov 1;78(9):1912-20. doi: 10.1002/(sici)1097-0142(19961101)78:93.0.co;2-0.
• Bennett CL, Ferreira MR, Davis TC, Kaplan J, Weinberger M, Kuzel T, Seday MA, Sartor O. Relation between literacy, race, and stage of presentation among low-income patients with prostate cancer. J Clin Oncol. 1998 Sep;16(9):3101-4. doi: 10.1200/JCO.1998.16.9.3101.
• Wolf MS, Knight SJ, Lyons EA, Durazo-Arvizu R, Pickard SA, Arseven A, Arozullah A, Colella K, Ray P, Bennett CL. Literacy, race, and PSA level among low-income men newly diagnosed with prostate cancer. Urology. 2006 Jul;68(1):89-93. doi: 10.1016/j.urology.2006.01.064.
• Williams MV, Baker DW, Parker RM, Nurss JR. Relationship of functional health literacy to patients' knowledge of their chronic disease. A study of patients with hypertension and diabetes. Arch Intern Med. 1998 Jan 26;158(2):166-72. doi: 10.1001/archinte.158.2.166.
• Wolf MS, Davis TC, Arozullah A, Penn R, Arnold C, Sugar M, Bennett CL. Relation between literacy and HIV treatment knowledge among patients on HAART regimens. AIDS Care. 2005 Oct;17(7):863-73. doi: 10.1080/09540120500038660.
• Kalichman SC, Ramachandran B, Catz S. Adherence to combination antiretroviral therapies in HIV patients of low health literacy. J Gen Intern Med. 1999 May;14(5):267-73. doi: 10.1046/j.1525-1497.1999.00334.x.
• Mancuso CA, Rincon M. Impact of health literacy on longitudinal asthma outcomes. J Gen Intern Med. 2006 Aug;21(8):813-7. doi: 10.1111/j.1525-1497.2006.00528.x.
• Coyne KS, Kaplan SA, Chapple CR, Sexton CC, Kopp ZS, Bush EN, Aiyer LP; EpiLUTS Team. Risk factors and comorbid conditions associated with lower urinary tract symptoms: EpiLUTS. BJU Int. 2009 Apr;103 Suppl 3:24-32. doi: 10.1111/j.1464-410X.2009.08438.x.
• Subak LL, Wing R, West DS, Franklin F, Vittinghoff E, Creasman JM, Richter HE, Myers D, Burgio KL, Gorin AA, Macer J, Kusek JW, Grady D; PRIDE Investigators. Weight loss to treat urinary incontinence in overweight and obese women. N Engl J Med. 2009 Jan 29;360(5):481-90. doi: 10.1056/NEJMoa0806375.
• Yost KJ, Webster K, Baker DW, Choi SW, Bode RK, Hahn EA. Bilingual health literacy assessment using the Talking Touchscreen/la Pantalla Parlanchina: Development and pilot testing. Patient Educ Couns. 2009 Jun;75(3):295-301. doi: 10.1016/j.pec.2009.02.020. Epub 2009 Apr 21.
• Meade CD, Menard J, Martinez D, Calvo A. Impacting health disparities through community outreach: utilizing the CLEAN look (culture, literacy, education, assessment, and networking). Cancer Control. 2007 Jan;14(1):70-7. doi: 10.1177/107327480701400110.
• McKee MM, Paasche-Orlow MK. Health literacy and the disenfranchised: the importance of collaboration between limited English proficiency and health literacy researchers. J Health Commun. 2012;17 Suppl 3(Suppl 3):7-12. doi: 10.1080/10810730.2012.712627.
• Braveman P. Health disparities and health equity: concepts and measurement. Annu Rev Public Health. 2006;27:167-94. doi: 10.1146/annurev.publhealth.27.021405.102103.
• Institute of Medicine (US) Committee on Health Literacy; Nielsen-Bohlman L, Panzer AM, Kindig DA, editors. Health Literacy: A Prescription to End Confusion. Washington (DC): National Academies Press (US); 2004. Available from http://www.ncbi.nlm.nih.gov/books/NBK216032/
• Wolf MS, Gazmararian JA, Baker DW. Health literacy and functional health status among older adults. Arch Intern Med. 2005 Sep 26;165(17):1946-52. doi: 10.1001/archinte.165.17.1946.
• Sudore RL, Yaffe K, Satterfield S, Harris TB, Mehta KM, Simonsick EM, Newman AB, Rosano C, Rooks R, Rubin SM, Ayonayon HN, Schillinger D. Limited literacy and mortality in the elderly: the health, aging, and body composition study. J Gen Intern Med. 2006 Aug;21(8):806-12. doi: 10.1111/j.1525-1497.2006.00539.x.
• Kalichman SC, Rompa D. Functional health literacy is associated with health status and health-related knowledge in people living with HIV-AIDS. J Acquir Immune Defic Syndr. 2000 Dec 1;25(4):337-44. doi: 10.1097/00042560-200012010-00007.
• Scott TL, Gazmararian JA, Williams MV, Baker DW. Health literacy and preventive health care use among Medicare enrollees in a managed care organization. Med Care. 2002 May;40(5):395-404. doi: 10.1097/00005650-200205000-00005.
• Dolan NC, Ferreira MR, Davis TC, Fitzgibbon ML, Rademaker A, Liu D, Schmitt BP, Gorby N, Wolf M, Bennett CL. Colorectal cancer screening knowledge, attitudes, and beliefs among veterans: does literacy make a difference? J Clin Oncol. 2004 Jul 1;22(13):2617-22. doi: 10.1200/JCO.2004.10.149.

Study record dates

Study Major Dates

• Study Start (Actual): September 14, 2018
• Primary Completion (Actual): September 9, 2021
• Study Completion (Actual): July 31, 2023

Study Registration Dates

• First Submitted: May 29, 2018
• First Submitted That Met QC Criteria: June 28, 2018
• First Posted (Actual): July 12, 2018

Study Record Updates

• Last Update Posted (Estimated): December 5, 2023
• Last Update Submitted That Met QC Criteria: November 14, 2023
• Last Verified: November 1, 2023

More Information

Terms related to this study

• Other Study ID Numbers: STU00202907; 1R01MD010440-01A1 (U.S. NIH Grant/Contract)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No