Reducing Assessment Barriers for Patients With Low Literacy

Health Literacy Clinical Trial

Official title:

Reducing Assessment Barriers for Patients With Low Health Literacy

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03584490
• Other study ID #: STU00202907
• Secondary ID: 1R01MD010440-01A
• Status: Completed
• Phase: N/A
• Start date: September 14, 2018
• Est. completion date: July 31, 2023

Study information

• Verified date: November 2023
• Source: Northwestern University
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 729
• Est. completion date: July 31, 2023
• Est. primary completion date: September 9, 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Health Literacy

Intervention

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.
• 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.

Locations

Country	Name	City	State
United States	Northwestern University	Chicago	Illinois

Sponsors (3)

Lead Sponsor	Collaborator
Northwestern University	National Institute on Minority Health and Health Disparities (NIMHD), National Institutes of Health (NIH)

Country where clinical trial is conducted

United States, 

References & Publications (26)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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):261 — View Citation

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. — View Citation

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/b — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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 — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 26 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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
Primary	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
Primary	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