Active Life Engagement in Relation to Health-related Outcomes Among Community-dwelling Chinese Older Adults

1. Participants

This study will recruit 70 participants from the community with the help from staffs from community service center. Investigators recruited participants who aged 60 or older and lived in the community independently, and screened participants for eligibility based on the following exclusionary criteria: (1) unable to complete brief survey presented in mobile devices (e.g., have severe visual deficits or other self-report difficulty reading the screen), (2) diagnosed with a cognition disorder, (4) diagnosed with a mental disorder.

Study protocol

1. Self-administered questionnaire survey

All the participants will be asked to complete the baseline self-administrated survey on line (in some cases, participants could be organized to complete the survey under the guide of the research staff).

II. Training sessions/orientation

All the eligible participants will be invited to attend the training session/orientation. The research staff will assign each participant a Android phone installed with a researcher-developed application and a mobile-electrocardiogram (ECG) recording device. The participants will be briefed on its basic functions and how to use the application and device to provide data. The whole session will take steps proactively to increase participants' confidence and comfort with using the electronic band and the real-time assessment application through in-person training and mutual support between participants. Detailed take-home handbook (hardcopy or electronic version) that cover the use guidelines of the electronic bans and the real-time assessment application, and troubleshooting help, will be distributed to participants. Then, two warm-up days prior to the main study will be conducted and on-call help will be provided.

III. Real-time assessment survey of daily experiences

The real-time assessment application will allow each user to register a personal account, and to define their person-specific time-frame for the procedure, in specific, the start and the end time in a typical day they accept the signaling. The time frame will basically cover the user's waking hours (approximately 7 ± 3 hours). Within the defined time frame, the mobile device with the application will randomly prompt the user to complete a report for 6 times. The minimum and the maximum time between two consecutive signals will be 30 and 150 minutes respectively. The device will correctly record each response time once sending the signal. If the device receives no response for over 20 minutes, substitute prompts will be automatically sent every 5 minutes for 2 times. If still no response, a missing will be recorded. This procedure will be repeated on 7 consecutive days, with different random patterns for each day. For answering one signaling report, it will take approximately 3 to 5 minutes for most users (a total of less than 30 min per day). The content of report will be the same each time, which will comprise questions on engagement in daily activities, individual distractions, mood, and social systems.

IV. Physiological data provision

Physiological data will be collected concurrently during the 7 consecutive days for real-time data collection. All participants will be required to carry the mobile-ECG device assigned to them during the whole process of data collection. They will use the smartphone-based application and the mobile-ECG device to provide a 30-second ECG recording for six times each day.

1. In-person follow-up survey

All participants will be asked to complete the open-ended questions focusing on the feasibility/acceptability of the method.

No drug usage and medical treatment will be involved in the study. Intensive assessment do not impose any physical or medical risk to participants. The only possible problem is that the intensive assessment may interfere with the participants' normal daily routines. Participants can voluntarily drop out the study at any time, without giving any reason.

Data analyses:

Intra-individual variability in the activity engagement will be analyzed by calculating the standard-deviation for each participant's timing of each domains of engagement resulting in an intra-individual standard deviation (iSD). In order to model within-person change and between-person factors simultaneously, two alternative statistical methods, namely, time series analysis and random coefficient multilevel modelling will be used. Multiple hierarchical regression analyses will be conducted with activity indicators predicting health and well-being outcomes.