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In France, approximaly 3 million children have a chronic disease and require regular care such as paediatric rehabilitation. These cares are provided over long periods of time, most often throughout childhood and often into adulthood. Paediatric rehabilitation care involves multidisciplinary team working closely with families. During follow-up rehabilitation, communication between the children, families and the professionals is essential. To this end, digital health solutions can be helpful.
Digital health solutions are rapidly emerging in the field of paediatric rehabilitation. In this context of emergence of digital health solutions, it is essential to identify the needs and expectations of families of children with a chronic disease.
This project aims to identify the key points in terms of information exchange on rehabilitation monitoring. To identify these needs, a mixed study will be carried out from June 2022 to June 2023 involving focus groups to gather qualitative informations on parent's needs in terms of information exchange through digital apps and quantitative research with a survey that will allow to prioritise these needs.
Full description
For the first part of the study, the researchers will conduct focus groups and interview parents about their experiences and perceptions of information exchange with rehabilitation professionals. All the participants will be parents of a child with a chronic disease, aged between 0 and 18 years and receiving paediatric rehabilitation care. The objective of this first part is to collect qualitative information on the needs of parents in terms of information exchange through digital applications.
With the analysis of the focus group, the researchers will define the hypothesis.
Then, a survey will be built and shared online in France during 3 months (2nd semester 2022).
With this survey, the objective is to identify the key points for the development of paediatric rehabilitation apps in terms of information exchange.
Quantitative data will be described with frequency, mean and standard deviation.
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Christelle Pons, MD, PhD; Emmanuelle Fily
Data sourced from clinicaltrials.gov
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