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Validation of an Automated Wearable Camera-Based Image-Assisted Recall Method and the 24-h Recall Method for
Andrea L S Bulungu1, Luigi Palla2,3,4, Jan Priebe5
1Department of Population Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Nutrients
|May 14, 2022
Summary
Accurate maternal time-use data is crucial for nutrition research. Automated wearable cameras and 24-hour recalls are reliable for employment and domestic chores but not for caregiving or socializing.
Area of Science:
- Public Health
- Nutrition Science
- Methodology Research
Background:
- Accurate maternal time-use data is vital for understanding nutritional outcomes.
- Traditional 24-hour recall (24HR) methods may be prone to recall bias.
- Automated wearable cameras with image-assisted recall (AWC-IAR) offer a potential improvement.
Purpose of the Study:
- To evaluate the concurrent criterion validity of AWC-IAR compared to 24HR for assessing women's time use in rural Uganda.
- To compare these methods against direct observation as the criterion standard.
Main Methods:
- Employed Bland-Altman limits of agreement (LOA) and Cronbach's alpha/Cohen's kappa for analysis.
- Compared time allocations from AWC-IAR (n=211) and 24HR against direct observation.
- Assessed systematic bias and LOA for various time-use categories.
Main Results:
- Both 24HR and AWC-IAR showed systematic bias, particularly for caregiving and socializing.
- LOAs exceeded acceptable limits for caregiving and socializing with both methods.
- Accuracy was within 2 hours for employment, own production, and self-care for both methods.
Conclusions:
- 24HR and AWC-IAR are accurate for population-level assessment of employment, own production, and domestic chores.
- Both methods demonstrate poor validity for caregiving and socializing time allocations.
- Previous research on maternal time allocation and nutrition outcomes may need re-evaluation due to method limitations.
