Mobile monitoring parents’ behaviors for supporting self-management in children with disabilities
One of the main factors affecting autonomy in children with disabilities is parents’ behaviors. Understanding parents’ behaviors is important for their effects over time. However, measuring and quantifying parents’ behaviors through ubiquitous technology has remained largely unexplored. In this work, we use mobile sensing to monitor behaviors in parents of individuals with Down syndrome. Through our approach, we identified some behaviors that have been reported to be associated with directive and facilitating behaviors of mothers of children with Down syndrome. We also discuss how this mobile sensing-based approach can be used as a supplementary technique to enhance behavioral analysis with these types of populations. This work offers a promising approach for deploying mobile sensing technology for advancing research in this area.
KeywordsMonitoring behavior Parents’ behavior Children with Down syndrome Mobile sensing
This work has been partially funded by the National Council for Science and Technology (CONACYT) in Mexico through a scholarship provided to the second author. Also, this work has been partially funded by the Instituto Tecnológico de Sonora (ITSON) through the PROFAPI program.
- Cuskelly M, Gilmore L, Carroll A (2013) Self-regulation and mastery motivation in individuals with developmental disabilities: Barriers, supports, and strategies. In: Fox NA, Morgan GA, Fidler DJ, Daunhauer LA, Barrett KC (eds) Handbook of self-regulatory processes in development: new directions and international perspectives. Taylor and Francis, New York, pp 381–404Google Scholar
- Félix IR, Castro LA, Rodríguez L-F, Ruíz EC (2016) Component-based model for on-device pre-processing in mobile phone sensing campaigns. In: García CR, Caballero-Gil P, Burmester M, Quesada-Arencibia A (eds) Ubiquitous computing and ambient intelligence: 10th international conference, UCAmI 2016, Part I. Springer International Publishing, Cham, pp 201–206. https://doi.org/10.1007/978-3-319-48746-5_20
- Frenken T, Vester B, Brell M, Hein A (2011) aTUG: fully-automated timed up and go assessment using ambient sensor technologies. In: 5th International conference on pervasive computing technologies for healthcare (PervasiveHealth 2011), Dublin. IEEE, pp 55–62Google Scholar
- Madan A, Cebrian M, Lazer D, Pentland A (2010) Social sensing for epidemiological behavior change. In: Paper presented at the 12th ACM international conference on ubiquitous computing (Ubicomp 2010), Copenhagen, Sep 26–29Google Scholar
- Perez M, Castro LA, Favela J (2011) InCense: a research kit to facilitate behavioral data gathering from populations of mobile phone users. In: Paper presented at the 5th international symposium of ubiquitous computing and ambient intelligence (UCAmI 2011), Riviera Maya, Dec 5–9Google Scholar
- Ramos-Monteon J, Castro LA, Rodriguez L-F, Banos O (2018) InCense IoT: a collective sensing system for behavior data in shared spaces. In: Paper presented at the 12th international conference on ubiquitous computing and ambient intelligence (UCAmI 2018) Punta Cana (accepted) Google Scholar
- Ryan RM, Deci EL, Grolnick WS, La Guardia JG (2006) The significance of autonomy and autonomy support in psychological development and psychopathology. In: Cicchetti D, Cohen DJ (eds) Developmental psychopathology, vol 1, 2nd edn. Wiley, HobokenGoogle Scholar
- Sansour T (2016) Interactional style and subjective stress in mothers of young children with fragile X syndrome, Down’s syndrome or typical development. Eur J Spec Educ Res 1:100–119Google Scholar
- Xie L, Antle AN, Motamedi N (2008) Are tangibles more fun? Comparing children’s enjoyment and engagement using physical, graphical and tangible user interfaces. In: Paper presented at the 2nd international conference on Tangible and embedded interaction, Bonn, Feb 18–21Google Scholar