Using Health Chatbots for Behavior Change: A Mapping Study.
This study conducts a mapping study to survey the landscape of health chatbots along three research questions: What illnesses are chatbots tackling? What patient competences are chatbots aimed at? Which chatbot technical enablers are of most interest in the health domain? We identify 30 articles rel...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 5 |
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| Autores principales: | , |
| Formato: | research systematic review tables/charts Journal Article |
| Publicado: |
Springer Nature
May2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=136129206&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 136129206 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: May2019 vid: 43 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 136129206 136129206 136129206 10.1007/s10916-019-1237-1 136129206 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Using Health Chatbots for Behavior Change: A Mapping Study. aug: au: Pereira, Juanan Díaz, Óscar affil: ONEKIN Research Group, University of the Basque Country, UPV/EHU, Leioa, Spain sug: subj: Health Care Industry Artificial Intelligence Behavioral Changes Instant Messaging User-Computer Interface Telehealth Nutrition Disorders Nervous System Diseases Scoping Review Human ab: This study conducts a mapping study to survey the landscape of health chatbots along three research questions: What illnesses are chatbots tackling? What patient competences are chatbots aimed at? Which chatbot technical enablers are of most interest in the health domain? We identify 30 articles related to health chatbots from 2014 to 2018. We analyze the selected articles qualitatively and extract a triplet <technicalEnablers, competence, illness> for each of them. This data serves to provide a first overview of chatbot-mediated behavior change on the health domain. Main insights include: nutritional disorders and neurological disorders as the main illness areas being tackled; "affect" as the human competence most pursued by chatbots to attain change behavior; and "personalization" and "consumability" as the most appreciated technical enablers. On the other hand, main limitations include lack of adherence to good practices to case-study reporting, and a deeper look at the broader sociological implications brought by this technology. pubtype: Academic Journal doctype: research systematic review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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