Dissertation Defense - Xiaoli Li

Dissertation Defense: Resident satisfaction indicators in long-term care settings

Xiaoli Li

Ph.D. Candidate in Health Services Research

Concentration: Applied Gerontology

Department of Rehabilitation and Health Services

College of Health and Public Service

Date: Dec. 20, 2022

Time: 1-3 p.m.

Place: Chilton Hall, Room 220

Major Professor: Dr. Liam O'Neill

Dissertation Committee:

Dr. Liam O’Neil, Ph.D., Chair
Dr. Denise Catalano, Ph.D.
Dr. Stan Ingman, Ph.D.

Background and Aim 

Due to an increasingly aging population and long-term care available, the number of older adults seeking long-term care facilities is growing. Resident satisfaction indicators have become essential measurements of service quality. However, few studies have investigated the evidence on prevalent resident satisfaction indicators and associated factors.


In order to understand what are the types of resident satisfaction measurements utilized in long-term care facilities in the United States and how these types of care services influence resident satisfaction, the researcher conducted the first study, which consists of a systematic scoping review by summarizing the evidence on the types of resident satisfaction indicators utilized in long-term care settings in the United States. The second study completed a further systematic review to summarize how nursing assistants impact resident satisfaction in long-term care settings. The third study aims to translate and validate a Chinese version of the resident satisfaction assessment based on the Ohio Long-term Care Resident Satisfaction Survey (OLCRSS). The fourth study will apply hierarchical regression to predict older adults' satisfaction with individual factors and care services factors in long-term care settings. The dissertation provided a holistic solution to measure resident satisfaction in long-term care settings, assist health providers in meeting the residents' needs and improve the quality of the care.


These studies are significant because they provide fundamental data for using evidence-based indicators of resident satisfaction to enhance the residents' quality of life. Findings could also add to the existing literature regarding resident satisfaction indicators.

Event Date: 
Tuesday, December 20, 2022 - 01:00pm to 03:00pm
Event Location: 
Chilton Hall, Room 220