A deep learning algorithm to prevent burnout risk in Family Caregivers of patients undergoing dialysis treatment
| Autor: | Valeria Cioffi, Anna Esposito, Raffaele Sperandeo, Giuseppina di Ronza, Martina Messina, Vania Costa, Mario Bottone, Nelson Mauro Maldonato, Pasquale Dolce, Enrico Moretto, Daneiela Iennaco |
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| Přispěvatelé: | Costa V, Messina M, Bottone M, Sperandeo R, Esposito A, Maldonato MN, Cioffi V, Di Ronza G, Iennaco D, Dolce P, Moretto E, Costa, Vania, Messina, Martina, Bottone, Mario, Sperandeo, Raffaele, Esposito, Anna, Maldonato, Nelson Mauro, Cioffi, Valeria, Di Ronza, Giuseppina, Iennaco, Daneiela, Dolce, Pasquale, Moretto, Enrico, Iennaco, Daniela |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
medicine.medical_treatment
Cognitive Neuroscience Experimental and Cognitive Psychology Burnout Dialysis patients 03 medical and health sciences caregivers burnout 0302 clinical medicine Artificial Intelligence medicine Sustenance 030212 general & internal medicine Dialysis Family caregivers business.industry Deep learning Communication Mobile apps deep learning Human-Computer Interaction Distress Computer Networks and Communication hemodialysi Artificial intelligence business Algorithm 030217 neurology & neurosurgery |
| Popis: | Continuous management of dialysis patients exposes family caregivers to significant psychophysical risks. Having demonstrated the effectiveness of artificial intelligence in the care and assistance processes, it was hypothesized the implementation of a mobile app which would detect the distress of these Family Caregivers in order to activate support actions and adequate sustenance. In order to identify the Burnout risk factors of the Family Caregivers of dialysis patients, 31 items were selected, from the questionnaires recognized in the literature, and submitted to a sample of 713 subjects. The four components extracted through factor analysis identify critical aspects of the family caregiver’s experience. The neural network implemented on these four dimensions shows that overall they have an excellent ability to predict the stress state of the subjects (82%). From this study emerged the basic structure of a psychometric instrument suitable for the assessment of the stress of the family caregivers of patients undergoing dialysis treatment. This reagent can be administered through a mobile app and, using a deep learning algorithm, can report in real time the discomfort of the family caregivers. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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