Articles producció científica> Enginyeria Informàtica i Matemàtiques

A method to determine a personalized set of online exercises for improving the positive mental health of a caregiver of a chronically ill patient

  • Identification data

    Identifier: imarina:9162472
    Handle: http://hdl.handle.net/20.500.11797/imarina9162472
  • Authors:

    Ferré-Bergadà Maria
    Valls Aida
    Raigal-Aran Laia
    Lorca-Cabrera Jael
    Albacar-Ribóo Nuria
    Lluch-Canut Teresa
    Ferré-Grau Carme
  • Others:

    Author, as appears in the article.: Ferré-Bergadà Maria; Valls Aida; Raigal-Aran Laia; Lorca-Cabrera Jael; Albacar-Ribóo Nuria; Lluch-Canut Teresa; Ferré-Grau Carme
    Department: Enginyeria Informàtica i Matemàtiques
    e-ISSN: 1472-6947
    URV's Author/s: Albacar Riobóo, Núria Maria / Ferré Bergadà, Maria / Ferré Grau, Carmen / RAIGAL ARAN, LAIA / Valls Mateu, Aïda
    Keywords: Utility measurement Positive mental health Personalization Mobile health Mental health Health environment Caregivers
    Abstract: Background: Taking care of chronic or long-term patients at home is an arduous task. Non-professional caregivers suffer the consequences of doing so, especially in terms of their mental health. Performing some simple activities through a mobile phone app may improve their mindset and consequently increase their positivity. However, each caregiver may need support in different aspects of positive mental health. In this paper, a method is defined to calculate the utility of a set of activities for a particular caregiver in order to personalize the intervention plan proposed in the app. Methods: Based on the caregivers’ answers to a questionnaire, a modular averaging method is used to calculate the personal level of competence in each positive mental health factor. A reward-penalty scoring procedure then assigns an overall impact value to each activity. Finally, the app ranks the activities using this impact value. Results: The results of this new personalization method are provided based on a pilot test conducted on 111 caregivers. The results indicate that a conjunctive average is appropriate at the first stage and that reward should be greater than penalty in the second stage. Conclusions: The method presented is able to personalize the intervention plan by determining the best order of carrying out the activities for each caregiver, with the aim of avoiding a high level of deterioration in any factor.
    Thematic Areas: Saúde coletiva Psicología Medicina ii Medicina i Medical informatics Interdisciplinar Health policy Health informatics Engenharias iv Computer science applications Ciências biológicas i Ciência da computação
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: carme.ferre@urv.cat aida.valls@urv.cat nuria.albacar@urv.cat maria.ferre@urv.cat
    Author identifier: 0000-0002-5307-1553 0000-0001-5229-0394 0000-0003-3616-7809 0000-0001-8306-8702 0000-0003-2600-1362
    Record's date: 2023-02-23
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01445-6
    Licence document URL: http://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Bmc Medical Informatics And Decision Making. 21 (1): 74-
    APA: Ferré-Bergadà Maria; Valls Aida; Raigal-Aran Laia; Lorca-Cabrera Jael; Albacar-Ribóo Nuria; Lluch-Canut Teresa; Ferré-Grau Carme (2021). A method to determine a personalized set of online exercises for improving the positive mental health of a caregiver of a chronically ill patient. Bmc Medical Informatics And Decision Making, 21(1), 74-. DOI: 10.1186/s12911-021-01445-6
    Article's DOI: 10.1186/s12911-021-01445-6
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2021
    Publication Type: Journal Publications
  • Keywords:

    Computer Science Applications,Health Informatics,Health Policy,Medical Informatics
    Utility measurement
    Positive mental health
    Personalization
    Mobile health
    Mental health
    Health environment
    Caregivers
    Saúde coletiva
    Psicología
    Medicina ii
    Medicina i
    Medical informatics
    Interdisciplinar
    Health policy
    Health informatics
    Engenharias iv
    Computer science applications
    Ciências biológicas i
    Ciência da computação
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