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Method of assessing parent-child grocery store purchasing interactions using a micro-camcorder
Eric E Calloway1, Cindy Roberts-Gray2, Nalini Ranjit3
1The University of Texas at Austin, 200 W. 24th Street, Gearing Hall, Austin, TX 78712, USA.
Appetite
|August 6, 2014
Summary
Participant worn micro-camcorders (PWMC) effectively capture parent-child food purchasing interactions in grocery stores. This method is more sensitive than in-person observation and shows high agreement with purchasing data.
Area of Science:
- Behavioral Science
- Nutritional Science
- Human-Computer Interaction
Background:
- Understanding parent-child interactions in food purchasing is crucial for public health.
- Traditional observational methods may miss key details of in-store behaviors.
- Participant-worn technology offers a novel approach to ecological data collection.
Purpose of the Study:
- To validate the use of participant worn micro-camcorders (PWMC) for collecting data on parent-child food and beverage purchasing interactions.
- To compare the sensitivity and validity of PWMC data against in-person observations and purchase receipts.
Main Methods:
- 32 parent-child dyads participated, with children aged 2-6 years wearing a micro-camcorder.
- Data collected via PWMC and in-person observation were coded for behavioral and environmental variables.
- PWMC data validity was assessed against in-person observation and receipt data.
Main Results:
- PWMC revealed significantly more parent-child food purchasing interactions (1.4 more per trip) compared to in-person observation.
- Inter-rater reliability for PWMC data coding ranged from moderate to almost perfect (Cohen's kappa = 0.461-0.937).
- PWMC showed strong correlations with in-person observations (rho = 0.911) and substantial agreement with receipt data (Cohen's kappa = 0.787).
Conclusions:
- Participant worn micro-camcorders are a valid and sensitive tool for studying parent-child food purchasing behaviors in grocery settings.
- PWMC offers a reliable method for capturing detailed interactions and purchasing decisions.
- This technology enhances the accuracy of data collection in real-world environments.

