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Developing a model for understanding patient collection of observations of daily living: A qualitative meta-synthesis of the Project HealthDesign Program.
Cohen, Deborah J; Keller, Sara R; Hayes, Gillian R; Dorr, David A; Ash, Joan S; Sittig, Dean F.
Afiliação
  • Cohen DJ; Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, FM, Portland, Oregon 97239.
  • Keller SR; Department of Family Medicine, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, FM, Portland, Oregon 97239.
  • Hayes GR; Department of Informatics, Donald Bren School of Information and Computer Sciences, University of California, Irvine, Irvine, California 92697.
  • Dorr DA; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, FM, Portland, Oregon 97239.
  • Ash JS; Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, FM, Portland, Oregon 97239.
  • Sittig DF; University of Texas School of Biomedical Informatics at Houston, UT - Memorial Hermann Center for Healthcare Quality & Safety, 6410 Fannin St., UTPB 1100.43, Houston, TX 77030.
Pers Ubiquitous Comput ; 19(1): 91-102, 2015 Jan 01.
Article em En | MEDLINE | ID: mdl-26949381
We conducted a meta-synthesis of five different studies that developed, tested, and implemented new technologies for the purpose of collecting Observations of Daily Living (ODL). From this synthesis, we developed a model to explain user motivation as it relates to ODL collection. We describe this model that includes six factors that motivate patients' collection of ODL data: usability, illness experience, relevance of ODLs, information technology infrastructure, degree of burden, and emotional activation. We show how these factors can act as barriers or facilitators to the collection of ODL data and how interacting with care professionals and sharing ODL data may also influence ODL collection, health-related awareness, and behavior change. The model we developed and used to explain ODL collection can be helpful to researchers and designers who study and develop new, personal health technologies to empower people to improve their health.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Systematic_reviews Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Qualitative_research / Systematic_reviews Idioma: En Ano de publicação: 2015 Tipo de documento: Article