Health Promotion for Childhood Obesity: An Approach Based on Self-Tracking of Data

被引:13
|
作者
Gomez-del-Rio, Nazaret [1 ]
Gonzalez-Gonzalez, Carina S. [2 ]
Toledo-Delgado, Pedro A. [2 ]
Munoz-Cruz, Vanesa [2 ]
Garcia-Penalvo, Francisco [1 ]
机构
[1] Univ Salamanca, Inst Univ Ciencias Educ, Grp GRIAL, Paseo Canalejas 169, Salamanca 37008, Spain
[2] Univ La Laguna, Comp Engn & Syst Dept, Grp ITED, Avda Astrofis Sanchez S-N,Phys & Math Bldg, Tenerife 38204, Spain
关键词
child obesity; physical activity; user model; recommender system; UX; QS; QUANTIFIED-SELF;
D O I
10.3390/s20133778
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
At present, obesity and overweight are a global health epidemic. Traditional interventions for promoting healthy habits do not appear to be effective. However, emerging technological solutions based on wearables and mobile devices can be useful in promoting healthy habits. These applications generate a considerable amount of tracked activity data. Consequently, our approach is based on the quantified-self model for recommending healthy activities. Gamification can also be used as a mechanism to enhance personalization, increasing user motivation. This paper describes the quantified-self model and its data sources, the activity recommender system, and the PROVITAO App user experience model. Furthermore, it presents the results of a gamified program applied for three years in children with obesity and the process of evaluating the quantified-self model with experts. Positive outcomes were obtained in children's medical parameters and health habits.
引用
收藏
页码:1 / 28
页数:28
相关论文
共 50 条
  • [31] Illness and health in times of self-tracking, wellness and self-optimization. On the way to the health society?
    Kleineberg, M.
    VESTNIK SANKT-PETERBURGSKOGO UNIVERSITETA-FILOSOFIYA I KONFLIKTOLOGIYA, 2018, 34 (01): : 17 - 23
  • [32] Barriers in Nursing Interventions and Health Promotion in Childhood Obesity
    Gallardo, Abigail Mora
    Bonilla, Leonel Cuamatzin
    Salazar, Jose Rodrigo Roman
    PHYSIOLOGY, 2024, 39
  • [33] Self-tracking Reloaded: Applying Process Mining to Personalized Health Care from Labeled Sensor Data
    Sztyler, Timo
    Carmona, Josep
    Voelker, Johanna
    Stuckenschmidt, Heiner
    TRANSACTIONS ON PETRI NETS AND OTHER MODELS OF CONCURRENCY XI, 2016, 9930 : 160 - 180
  • [34] Adjusting Reality. The Contingency Dilemma in the Context of Popularised Practices of Digital Self-Tracking of Health Data
    Achatz, Johannes
    Selke, Stefan
    Wulf, Nele
    HISTORICAL SOCIAL RESEARCH-HISTORISCHE SOZIALFORSCHUNG, 2021, 46 (01): : 206 - 229
  • [35] Technical osmosis with the living body: Health self-tracking of the immersive patient
    Andrieu, Bernard
    EVOLUTION PSYCHIATRIQUE, 2016, 81 (02): : 253 - 265
  • [36] Personal metrics: Users' experiences and perceptions of self-tracking practices and data
    Ajana, Btihaj
    SOCIAL SCIENCE INFORMATION SUR LES SCIENCES SOCIALES, 2020, 59 (04): : 654 - 678
  • [37] SELF-TRACKING OPTICAL-DATA STORAGE AND RETRIEVAL-SYSTEM
    BEISER, L
    JOURNAL OF THE OPTICAL SOCIETY OF AMERICA, 1979, 69 (10) : 1481 - 1482
  • [38] Mobile Health in the Retinal Clinic Population: Access to and Interest in Self-Tracking
    Ludwig, Cassie A.
    Callaway, Natalia F.
    Park, Joyce Ho
    Leng, Theodore
    OPHTHALMIC SURGERY LASERS & IMAGING RETINA, 2016, 47 (03): : 252 - 257
  • [39] COMBINED METHOD OF METROLOGICAL SELF-TRACKING OF MEASUREMENT DATA PROCESSING PROGRAMS
    Semenov, K. K.
    Solopchenko, G. N.
    MEASUREMENT TECHNIQUES, 2011, 54 (04) : 378 - 386
  • [40] Combined method of metrological self-tracking of measurement data processing programs
    K. K. Semenov
    G. N. Solopchenko
    Measurement Techniques, 2011, 54 : 378 - 386