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Rationale, Design, and Baseline Characteristics of Participants in the Health@NUS mHealth Augmented Cohort Study Examining Student-to-Work Life Transition: Protocol for a Prospective Cohort Study. | LitMetric

AI Article Synopsis

  • Integration of mobile health data collection in cohort studies allows for more detailed tracking of health and lifestyle behaviors over time, particularly during the transition from university to the workforce, which can impact young adults' mental well-being.
  • The Health@NUS study aims to investigate the health behaviors and well-being trajectories of young adults during this transition by using mobile health technology to gather data over two years.
  • A total of 776 participants were enrolled, primarily female, Chinese, and undergraduate students, with regular assessments and data collection through devices like Fitbit and smartphone apps.

Article Abstract

Background: Integration of mobile health data collection methods into cohort studies enables the collection of intensive longitudinal information, which gives deeper insights into individuals' health and lifestyle behavioral patterns over time, as compared to traditional cohort methods with less frequent data collection. These findings can then fill the gaps that remain in understanding how various lifestyle behaviors interact as students graduate from university and seek employment (student-to-work life transition), where the inability to adapt quickly to a changing environment greatly affects the mental well-being of young adults.

Objective: This paper aims to provide an overview of the study methodology and baseline characteristics of participants in Health@NUS, a longitudinal study leveraging mobile health to examine the trajectories of health behaviors, physical health, and well-being, and their diverse determinants, for young adults during the student-to-work life transition.

Methods: University students were recruited between August 2020 and June 2022 in Singapore. Participants would complete biometric assessments and questionnaires at 3 time points (baseline, 12-, and 24-month follow-up visits) and use a Fitbit smartwatch and smartphone app to continuously collect physical activity, sedentary behavior, sleep, and dietary data over the 2 years. Additionally, up to 12 two-week-long bursts of app-based ecological momentary surveys capturing lifestyle behaviors and well-being would be sent out among the 3 time points.

Results: Interested participants (n=1556) were screened for eligibility, and 776 participants were enrolled in the study between August 2020 and June 2022. Participants were mostly female (441/776, 56.8%), of Chinese ethnicity (741/776, 92%), undergraduate students (759/776, 97.8%), and had a mean BMI of 21.9 (SD 3.3) kg/m, and a mean age of 22.7 (SD 1.7) years. A substantial proportion were overweight (202/776, 26.1%) or obese (42/776, 5.4%), had indicated poor mental well-being (World Health Organization-5 Well-Being Index ≤50; 291/776, 37.7%), or were at higher risk for psychological distress (Kessler Psychological Distress Scale ≥13; 109/776, 14.1%).

Conclusions: The findings from this study will provide detailed insights into the determinants and trajectories of health behaviors, health, and well-being during the student-to-work life transition experienced by young adults.

Trial Registration: ClinicalTrials.gov NCT05154227; https://clinicaltrials.gov/study/NCT05154227.

International Registered Report Identifier (irrid): DERR1-10.2196/56749.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11292158PMC
http://dx.doi.org/10.2196/56749DOI Listing

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