Advisory Committee Chair
James Nicholas Dionne-Odom
Advisory Committee Members
Andres Azuero
Arif Kamal
Sidharth Kumar
Frank Puga
Document Type
Thesis
Date of Award
2022
Degree Name by School
Doctor of Philosophy (PhD) School of Nursing
Abstract
Patients with advanced cancer and their family caregivers often experience poor quality of life. Measuring patient and caregiver physical and mental quality of life is typically performed using participant reported outcome measures, especially validated questionnaires. However, this self-report approach has several limitations, including recall bias, respondent burden, and social desirability bias. One potential solution to these limitations may be to use passive data collected by personally owned smartphones (e.g., GPS data) to model and assess the quality of life in family caregivers and patients with advanced cancer. Yet, there is no evidence to date that passively collected smartphone data is able to model fluctuations in caregivers’ and patients’ quality of life in the context of advanced cancer. This study used data collected as part of the Distress Prediction in Advanced Cancer Family Caregivers and their Care Recipients using Digital Phenotyping Study (Cambia Health Foundation; PI Dionne-Odom) to examine associations between passively collected smartphone data and participant reported quality of life among 7 family caregivers and 4 patients with advanced cancer over a 12-week period. We found a medium-to-large correlation between QOL (i.e., physical and mental health) and the daily smartphone GPS data averaged by week in certain time periods. Additionally, we found a medium-to-large correlation between QOL (i.e., physical and mental health) and iv within-person variability (standard deviation) in daily smartphone GPS data collected over a week in certain time periods. Our findings indicate that variation from a within-person’s usual behavior pattern or between-person's behavioral pattern may signal potential changes in one's physical and mental health outcomes. This study showed that digital phenotyping using daily smartphone GPS data is a promising approach with the potential to assess quality of life (i.e., physical and mental health) by measuring PROMIS Global 10. This work may provide a crucial basis and starting point for further research and information to investigate the QOL of advanced cancer patients and their caregivers.
Recommended Citation
Lee, Kyungmi, "Predicting Change in Quality of Life in Patients with Advanced Cancer and Family Caregivers Using GPS Data" (2022). All ETDs from UAB. 184.
https://digitalcommons.library.uab.edu/etd-collection/184