Intelligent Personalized Exercise Prescription Based on an eHealth Promotion System to Improve Health Outcomes of Middle-Aged and Older Adult Community Dwellers: Pretest–Posttest Study
Authors: Sun Ting , Xu Yang , Xie Hui , Ma Zuchang , Wang Yu 
Published: April 2021

Background

A scientific, personalized, and quantitative exercise prescription that has the potential to be an important therapeutic agent for all ages in the prevention of chronic disease is highly recommended. However, it is often poorly implemented, as clinicians lack the necessary knowledge and skills while participants have low adherence due to design defects (eg, prescriptions fail to take individual willingness, the appeal of exercise, and complex physical conditions into account). Intelligent personalized prescription is thus worth exploring.

Objective

The aim of this study was to investigate whether a year-long cloud platform–based and intelligent personalized exercise prescription intervention could improve Chinese middle-aged and older adult community dwellers’ health outcomes.

Methods

A total of 177 participants (aged 52-85 years; mean 67.93, SD 7.05) were recruited from 2 Chinese community health service centers in Anhui Province, China. The exercise intervention was delivered over 12 months with a single-group pretest–posttest design. After being assessed in terms of physical activity, health-related lifestyle, history of chronic diseases and drug use, family history of disease and cardiovascular function, body composition, bone mineral density, and physical fitness through an eHealth promotion system, participants with relative contraindications for exercise were personally prescribed the health care exercise mode by an intelligent system, while those without relative contraindication and who had a regular exercise habit were prescribed the scientific fitness mode. Paired t tests were used for the analysis.

Results

A total of 97 participants were classified into the health care mode, and the remaining 80 participants were assigned to the scientific fitness mode. Significant changes in heart rate (mean difference [MD] 2.97; 95% CI 1.1-4.84; P=.002), subendocardial viability ratio (MD –0.13; CI: –1.19 to –0.63; P<.001), weight (MD 0.99; CI 0.29-1.69; P=.006), BMI (MD 0.38; CI 0.11-0.64; P=.006), body fat rate (MD 0.88; CI 0.24-1.51; P=.007), fat mass (MD 0.92; CI 0.33-1.53; P=.003), and brachial-ankle pulse wave velocity (MD: –0.72; CI –1.17 to –0.27; P=.002) were observed among participants with the health care mode exercise prescriptions at the 12-month postintervention versus the baseline assessment, while no changes in systolic blood pressure, diastolic blood pressure, muscle mass, bone mineral density, t value, z value, balance, or ability were discerned. The results showed a functional decline in the physical fitness of both groups, including in handgrip strength (healthcare mode: MD 4.41; scientific fitness mode: MD 3.11), vital capacity (healthcare mode: MD 261.99; scientific fitness mode: MD 250.78), and agility (healthcare mode MD=–0.35; scientific fitness mode: MD=–0.39) with all P values <.001, except handgrip strength in the scientific fitness mode (P=.002). There were no significant differences in other parameters among participants with scientific fitness mode exercise prescriptions.

Conclusions

The observations suggest that our exercise prescription intervention program might promote certain health outcomes in Chinese middle-aged and older adult community dwellers, yet we are unable to recommend such a program given the existing limitations. Future randomized controlled trials with diverse samples are warranted to confirm our findings.