Associations between literacy proficiency of older adults in Ohio counties and quality of care provided in nursing homes.

          Different populations in Ohio have varying levels of literacy. One example of this difference is among the population of Ohio’s older adults.  This study investigates any possible correlations between low-literacy geographic areas and the quality of care that is received in nursing homes. The knowledge of the impacts of functional illiteracy/low-literacy on aging populations living in nursing homes can be useful for facilities to better serve their residents and provide adequate care. Information regarding effects of low literacy could be distributed to professionals with the intention to instruct how to accommodate residents based on their literacy levels. 

            From the PIAAC model of adult literacy and numeracy, all 88 Ohio counties were examined and ranked from best to worst in terms of literacy of the 65-74 age range. The counties were firstly ranked by examining the Average Scale Score of literacy .In the case of multiple counties sharing an Average Scale Score, the better rank would be assigned to the county with a lower percentage of the population at or under the Level 1 ranking. Individuals at or under Level 1 likely experience difficulty comprehending text. Next, the county with the higher population in Level 3 would be assigned a better literacy rank for this study. Individuals at or above Level 3 are likely proficient at understanding and analyzing text.

    The data gathered and ranked from the PIAAC model was then cross-referenced with the CMS quality data. The CMS quality data is a dataset provided to the public that outlines information on quality of care in nursing homes that benefit from Medicare & Medicaid programs.  This study selected various quality indicators for examination: number of beds, overall 5-star rating, 5-star staffing rating, and reported total nurse staffing hours per resident per weekday. Data for these indicators was gathered from each nursing home in the chosen counties, and the averages were computed by county.

          The results are only based on the nine counties analyzed here. The original hypothesis that the highest-ranked counties would have the highest level of quality turned out to be incorrect.

          The county with the largest number of homes was Mahoning, the 43rd-place county for literacy ranking. The county with the largest average number of beds was Holmes, the last-place county. The county with the highest average 5-star rating was Adams county, the 86th-place county. The county with the highest average staffing rating was Mahoning county. The county with the largest average of nurse staffing hours per resident per weekday was Warren, the 2nd-place county.

          Future directions could include exploring why the specific county groups had better quality ratings in certain areas rather than others.  A possible limitation of this study includes a lack of access to data that could be more specific. Another limitation was that the oldest group that the PIAAC model provided information for was the 65-74 age range. Information regarding older age groups would be worth exploring. 

I, Marshall Meyer, would like to express my appreciation for all individuals and entities involved in aiding in the progression of this research presentation. 

Most importantly, I express my deep gratitude to my mentor, Dr. Heather Menne, for supporting me through this entire product all the way from the beginning. This poster presentation has been my very first step into undergraduate research, and I want to thank Dr. Menne for undergoing the commitment to teach me the necessary steps in the past months I have been working with her. Patiently, she guided me through all of the appropriate measures I had to take during this project, whether that be steering me towards helpful sources, working with me through data sets, explaining gerontological concepts, and much more. Overall, she has been a knowledgeable, patient, encouraging mentor, and I wish to convey my most sincere thanks.

I would like to thank the Office of Undergraduates at Miami for organizing the Undergraduate Research Forum and kindly accepting my request to present my poster alongside my fellow students.

I would also like to acknowledge the organizers of the OAGE conference, for accepting my poster to be presented, and providing an enriching learning experience.

In addition, I would like to thank my lovely roommate, Kai Lewis, for tolerating the various zoom calls and other disruptions that were conducted in our shared room, and would especially like to thank them for the grace they gave me when I accidentally woke him after joining a Zoom call for this project, not realizing he was asleep in his bed. I couldn't ask for a better friend and roommate.

Finally, I would like to thank my parents, Chip and Dawn, and my loving partner, Bella, for always supporting me through times of stress, rest, and everything in between.

1. Organisation for Economic Co-operation and Development (OECD). U.S. PIAAC Skills Map. National Center for Education Statistics (NCES) Home Page, a part of the U.S. Department of Education. (n.d.). https://nces.ed.gov/surveys/piaac/skillsmap/?view=map&skillLevel=A

2. Centers for Medicare & Medicaid Services (CMS). (2025, July). Provider Information - Nursing Homes Including Rehab Services. PQDC. https://data.cms.gov/provider-data/dataset/4pq5-n9py

Critical Thinking: Finding associations between data patterns and navigating difficulties in data acquisition and analysis required critical thinking skills.

Teamwork: This study required working closely with Dr. Menne, requiring collaborating on tasks, negotiating schedules, discussing/deciding on tasks together, and accepting and giving feedback.

Technology: Locating, analyzing, and organizing information for this study required the usage of technology through spreadsheets, inputting functions, and accessing public databases. 

No specific reserach compliance protocols were required for this study.