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Finding the Goldilocks Zone for Toddler Accelerometry: How Many Days Are Needed for a Reliable Estimate of Physical
Elyse Letts1, Sarah M da Silva1, Sara King-Dowling2
1Department of Pediatrics, Child Health & Exercise Medicine Program, McMaster University,Hamilton, ON,Canada.
Insights
Four days of 6-hour accelerometer wear is sufficient for reliable estimation of sedentary time and physical activity in toddlers. This approach balances data accuracy with participant retention for machine learning analysis.
Area of Science:
- Pediatrics
- Biomedical Engineering
- Kinesiology
Background:
- Accurate measurement of sedentary time and physical activity (PA) in toddlers is crucial for understanding early development.
- Machine learning (ML) models offer advanced capabilities for analyzing accelerometer data.
Purpose of the Study:
- To determine the optimal duration and daily wear time of accelerometers for reliable estimation of sedentary time and PA in toddlers using ML.
- To establish guidelines for accelerometer wear to maximize data quality and participant retention.
Main Methods:
- One hundred and nine toddlers wore hip-worn accelerometers for 7 days.
- A validated ML model assessed time in sedentary time, light PA, moderate to vigorous PA, and total PA.
- Intraclass coefficients and the Spearman-Brown prophecy equation were used to evaluate reliability across various wear time combinations (3-12 hours/day, 1-10 days).
Main Results:
- Reliability estimates ranged from 0.32 to 0.98, increasing with more hours per day and more days of wear.
- Four days of 6 hours of daily wear achieved a reliability threshold of 0.7.
- This wear protocol retained 94% of participants.
Conclusions:
- A recommendation of 6 hours of accelerometer wear per day for at least 4 days provides a balance between acceptable reliability and participant retention.
- These findings support the use of this protocol for ML-based analysis of toddler sedentary time and PA.
- This approach can facilitate further research into early childhood physical behavior using advanced ML techniques.
Purpose:
To understand how many days and hours per day of accelerometer wear are needed for a reliable estimation of sedentary time and physical activity (PA) using machine learning (ML).
Method:
One hundred and nine toddlers wore an accelerometer on the right hip at home for 7 days. Time in sedentary time, light PA, moderate to vigorous PA, and total PA were assessed using a validated ML model for toddlers. Single-day intraclass coefficients were calculated for each minimum hours per day of wear time and each outcome. These intraclass coefficients were passed to the Spearman-Brown prophecy equation to determine the reliability of each hour per day and days combination (3-12 h, 1-10 d).
Results:
Predicted reliabilities ranged from 0.32 to 0.98, increasing as both numbers of hours per day and number of days increased. Four days of 6 hours of wear balances a 0.7 reliability threshold while retaining 94% of participants.
Conclusion:
Our findings support the recommended 6 hours per day of wear for at least 4 days, as it balances acceptable reliability with participant retention. This recommendation is valid for this ML method, and we anticipate that it can be used to further explore sedentary time and PA in toddlers using ML advances.
