Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar

Abstract

Background: The explosion of consumer electronics and social media are facilitating the rise of the Quantified Self (QS) movement where millions of users are tracking various aspects of their daily life using social media, mobile technology, and wearable devices. Data from mobile phones, wearables and social media can facilitate a better understanding of the health behaviors of individuals. At the same time, there is an unprecedented increase in childhood obesity rates worldwide. This is a cause for grave concern due to its potential long-term health consequences (e.g., diabetes or cardiovascular diseases). Childhood obesity is highly prevalent in Qatar and the Gulf Region. In this study we examine the feasibility of capturing quantified-self data from social media, wearables and mobiles within a weight lost camp for overweight children in Qatar.

Methods: Over 50 children (9-12 years old) and parents used a wide range of technologies, including wearable sensors (actigraphy), mobile and social media (WhatsApp and Instagram) to collect data related to physical activity and food, that was then integrated with physiological data to gain insights about their health habits. In this paper, we report about the acquired data and visualization techniques following the 360° Quantified Self (360QS) methodology (Haddadi et al., ICHI 587-92, 2015).

Results: 360QS allows for capturing insights on the behavioral patterns of children and serves as a mechanism to reinforce education of their mothers via social media. We also identified human factors, such as gender and cultural acceptability aspects that can affect the implementation of this technology beyond a feasibility study. Furthermore, technical challenges regarding the visualization and integration of heterogeneous and sparse data sets are described in the paper.

Conclusions: We proved the feasibility of using 360QS in childhood obesity through this pilot study. However, in order to fully implement the 360QS technology careful planning and integration in the health professionals' workflow is needed.

Trial registration: The trial where this study took place is registered at ClinicalTrials.gov on 14 November 2016 ( NCT02972164 ).

Keywords: Quantified Self; Wearable; eHealth.

Figures

Fig. 1

Datasets overview for the 360QS implementation - Volume of collected data from different sources per day. The volume is given in terms of number of participants from which data have been collected for a given day. Each row shows the volume from unique data sources (top five rows) and from combinations of two or three data sources (bottom rows). The combinations of sources are useful to show those data sources for which data is available for the same participants so the complementarity between various data sources can be analyzed in these cases

Fig. 2

Example of food tray before and after meal

Fig. 3

Instagram Photo uploaded by a participant

Fig. 4

Example of WhatsApp educational message sent by the moderator of the intervention. Translation for message 1:” Remember: restaurant food is high in calories and increases weight.” Message 2:” Can you promise to not let your kids eat out this week? Reply yes if you accept the challenge”

Fig. 5

Percentage of food left on trays grouped by food type

Fig. 6

Percentage of food left over all days of the camp

Fig. 7

User interface of the visual analytic tool for actigraphy sensor data The interface allows comparing two participants’ activity level (left side) for the full time period and on daily-based average during week and weekend days (right side). Specific clinical measurements like BMI or body fat can also be compared during the same time period (line charts)

Fig. 8

Instagram posts uploaded by users