Singapore Institute of Technology
Browse
- No file added yet -

Feasibility of Conducting Sit-to-Stand Tests Using Video Consultation

Download (425.42 kB)
journal contribution
posted on 2023-09-28, 13:05 authored by Li Whye Cindy NgLi Whye Cindy Ng, Deng Peng Ng, P. Thiviyan, Sailli Shrida

Objective. This study is aimed at ascertaining the feasibility of conducting the 1-minute sit-to-stand (1MSTS) and 30-second sit-to-stand (30SSTS) tests for healthy participants via video consultation. A secondary aim was to compare the relationship between the 1MSTS and 30SSTS. Methods. A total of 63 participants were recruited via the Singapore Institute of Technology emails and social media in 2020 during the peak of COVID-19. Prior to the sit-to-stand testing, all participants completed the consent form and physical activity questionnaires. Anthropometric data such as height and weight were also collected prior to testing. An instructional video detailing the sit-to-stand (STS) movement and the requirements for the environment set-up were sent to the participants via email. All STS tests were conducted virtually via the Zoom application. Healthy participants aged 21 to 55 years old performed a 1MSTS and 30SSTS each in random order. Results. All recruited participants completed the STS tests with no reported adverse events. Majority of participants were from the 21- to 25-year-old age groups, and the average number of repetitions performed by this group was 21.9±5.6 for the 30SSTS and 44.7±12.6 for the 1MSTS. Conclusion. Conducting the STS tests via video consultation was demonstrated to be safe and feasible. The number of repetitions performed in the 1MSTS is correlated to that of the 30SSTS, but 1MSTS has the ability to elicit a greater HR response among younger adults.

History

Journal/Conference/Book title

International Journal of Telemedicine and Applications

Publication date

2023-07-26

Version

  • Published

Usage metrics

    Categories

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC