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

Overview of attention for article published in BMC Medical Informatics and Decision Making, April 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)

Mentioned by

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8 tweeters

Citations

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19 Dimensions

Readers on

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321 Mendeley
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Title
Implementing 360° Quantified Self for childhood obesity: feasibility study and experiences from a weight loss camp in Qatar
Published in
BMC Medical Informatics and Decision Making, April 2017
DOI 10.1186/s12911-017-0432-6
Pubmed ID
Authors

Luis Fernandez-Luque, Meghna Singh, Ferda Ofli, Yelena A Mejova, Ingmar Weber, Michael Aupetit, Sahar Karim Jreige, Ahmed Elmagarmid, Jaideep Srivastava, Mohamed Ahmedna

Abstract

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

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 321 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 321 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 52 16%
Student > Bachelor 36 11%
Student > Ph. D. Student 33 10%
Researcher 32 10%
Student > Doctoral Student 28 9%
Other 40 12%
Unknown 100 31%
Readers by discipline Count As %
Medicine and Dentistry 58 18%
Nursing and Health Professions 44 14%
Psychology 22 7%
Computer Science 22 7%
Social Sciences 16 5%
Other 48 15%
Unknown 111 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 08 March 2018.
All research outputs
#3,778,775
of 15,921,538 outputs
Outputs from BMC Medical Informatics and Decision Making
#343
of 1,450 outputs
Outputs of similar age
#74,766
of 268,995 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#2
of 4 outputs
Altmetric has tracked 15,921,538 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,450 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done well, scoring higher than 76% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 268,995 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.