Measuring dynamical resilience indicators based on time series data may improve the prediction of health deterioration in older adults after hospital discharge. We examined the feasibility of an intensive prospective cohort study examining dynamical resilience indicators based on time series data of symptoms and physical activity in acutely ill older adults who visited the Emergency Department (ED).
This is a prospective cohort study with time series data from symptom questionnaires and activity trackers. Thirty older adults (aged 75.9 ± 5.5 years, 37% female) who were discharged from the ED of a tertiary hospital in the Netherlands were included in the study. We monitored self-reported symptoms using a daily online questionnaire, and physical activity using an activity tracker for 30 days. Descriptive data on participant eligibility and adherence to and acceptability of the assessments were collected.
Of 134 older patients visiting the ED, 109/134 (81%) were eligible for inclusion and 30/109 (28%) were included. Twenty-eight (93%) of the included participants completed follow-up. Regarding the adherence rate, 78% of participants filled in the questionnaire and 80% wore the activity tracker. Three (10%) participants completed fewer than three questionnaires. Most participants rated the measurements as acceptable and seven (23%) participants experienced an adverse outcome in the 30 days after discharge.
Such an intensive prospective cohort study examining dynamical resilience indicators in older adults was feasible. The quality of the collected data was sufficient, some adjustments to the measurement protocol are recommended. This study is an important first step to study resilience in older adults.
© 2024. The Author(s).
