A influência das tecnologias digitais de saúde sobre a aderência e ativação individuaisuma análise baseada em elaboration likelihood model

Resumo

Noncommunicable diseases (CNCD) represent 71% of all deaths and are a global threat. Chronic NCDs affect the elderly and adults of working age, generating a great economic impact. Its mitigation is one of the United Nations (UN) Sustainable Development Goals (SDGs). The World Health Organization (WHO) established in 2019 recommendations and standards for Digital Health Interventions (ISD) that seek to institutionalize and improve these approaches in Health Systems. Generations of individuals interact with technology differently and the study of these groups is relevant to improve interventions, especially in middle age, since they are potentially the individuals most affected by the incidence of preventable chronic conditions. In the tradition of the Information Systems field, the TAM and UTAUT models have been widely used to analyze the antecedents of systems adoption by individuals. This study, however, uses the Elaboration Likelihood Model (ELM), which allows a more focused view on information processing that precedes intentions and behaviors, such as adherence to treatments, changes in lifestyle and appropriate health or activation behaviors, mainly in individuals with chronic conditions and diseases related to middle age. This approach can improve the understanding of the functioning of these mechanisms beyond the simple perceptions of usefulness and ease of use, contributing to the theory in the field. The study also provides indications of how health applications can, in practice, address users of different age groups, with a perspective more focused on behavioral aspects. The study used PLS-SEM, based on a survey of US citizens, with the aim of analyzing a structural model built from the ELM, which contemplates the processing of information in peripheral and central routes, demonstrating how different behaviors occur in groups of middle-aged and chronic individuals. The proposed structural model was able to detect a distinction in the way information is processed between different groups of individuals with statistical significance. The study also provides indications of how health applications can, in practice, address users of different age groups, with a perspective more focused on behavioral aspects

Ficha do documento

Tipo

Dissertação

Ano

2020

Instituição

Fundação Getulio Vargas

Fonte

Repositório da FGV

Idioma

Português

Acesso

Acesso restrito

Identificador

oai:repositorio.fgv.br:10438/28973

Temas

TecnologiaSaúde

Palavras-chave

Health information technologiesHealthcare behaviorDigital health interventionsMiddle-age individuals healthcareElaboration likelihood modelTecnologia da informação em saúdeComportamento em saúdeSaúde digitalIntervenção digital em saúdeDoenças crônicasCuidados em saúde na meia-idadeAdministração de empresasTecnologia da informaçãoSistemas de suporte de decisãoPromoção da saúdeServiços de saúde