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Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire
A satisfying experience is critical for the user to feel motivated over time, especially in mobile health (m-Health) applications. Long-term user experience (UX) assesses more extended periods of use, which may reveal the possible impact of a set of experiences. In this study, using an in-app embed...
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Published in: | Computers in human behavior 2020-03, Vol.104, p.106169, Article 106169 |
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description | A satisfying experience is critical for the user to feel motivated over time, especially in mobile health (m-Health) applications. Long-term user experience (UX) assesses more extended periods of use, which may reveal the possible impact of a set of experiences. In this study, using an in-app embed questionnaire available through a conversational interface, we investigated long-term UX on an m-Health application to identify how it occurs over time. The methods were developed in 4 phases, which included problem characterization, search for UX aspects, elaboration and verification of the questionnaire, test period with questionnaire applied before, during and after use, interview with users, and information mapping. For 3 months, 37 users reported their experiences with the application, describing their impressions regarding usage. Results demonstrated that the most satisfying experiences occurred mainly within the first weeks of the study and were associated with the app's features, charts and visual resources, and the practicality of treatment monitoring. For the less satisfactory experiences, the main reasons identified were technical problems on the application, and the effort and difficulty of use. All users appreciated the use of a character in the conversational interface as a gatherer of the answers to the assessment questionnaire.
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•37 participants reported their long-term UX on a conversational interface for 3 months.•After the app use, users' feeling about their health remained similar to before use.•The most satisfactory experiences occurred mainly during the first weeks of use.•A determining aspect in UX is whether the app features meet users' health needs.•As engagement evolves over time, hedonic aspects gain more weight than pragmatic ones. |
doi_str_mv | 10.1016/j.chb.2019.106169 |
format | article |
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[Display omitted]
•37 participants reported their long-term UX on a conversational interface for 3 months.•After the app use, users' feeling about their health remained similar to before use.•The most satisfactory experiences occurred mainly during the first weeks of use.•A determining aspect in UX is whether the app features meet users' health needs.•As engagement evolves over time, hedonic aspects gain more weight than pragmatic ones.</description><identifier>ISSN: 0747-5632</identifier><identifier>EISSN: 1873-7692</identifier><identifier>DOI: 10.1016/j.chb.2019.106169</identifier><language>eng</language><publisher>Elmsford: Elsevier Ltd</publisher><subject>Chatbot ; Conversational ; Health ; Identification methods ; Long-term assessment ; m-Health ; Mapping ; Questionnaires ; User experience ; User interfaces</subject><ispartof>Computers in human behavior, 2020-03, Vol.104, p.106169, Article 106169</ispartof><rights>2019 Elsevier Ltd</rights><rights>Copyright Elsevier Science Ltd. Mar 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c277t-4fdd131e0eae2d7d10c46f5b1bb32f51356b18ee7106d36d5b79c76cf6459e5a3</cites><orcidid>0000-0002-6020-6356</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Biduski, Daiana</creatorcontrib><creatorcontrib>Bellei, Ericles Andrei</creatorcontrib><creatorcontrib>Rodriguez, João Pedro Mazuco</creatorcontrib><creatorcontrib>Zaina, Luciana Aparecida Martinez</creatorcontrib><creatorcontrib>De Marchi, Ana Carolina Bertoletti</creatorcontrib><title>Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire</title><title>Computers in human behavior</title><description>A satisfying experience is critical for the user to feel motivated over time, especially in mobile health (m-Health) applications. Long-term user experience (UX) assesses more extended periods of use, which may reveal the possible impact of a set of experiences. In this study, using an in-app embed questionnaire available through a conversational interface, we investigated long-term UX on an m-Health application to identify how it occurs over time. The methods were developed in 4 phases, which included problem characterization, search for UX aspects, elaboration and verification of the questionnaire, test period with questionnaire applied before, during and after use, interview with users, and information mapping. For 3 months, 37 users reported their experiences with the application, describing their impressions regarding usage. Results demonstrated that the most satisfying experiences occurred mainly within the first weeks of the study and were associated with the app's features, charts and visual resources, and the practicality of treatment monitoring. For the less satisfactory experiences, the main reasons identified were technical problems on the application, and the effort and difficulty of use. All users appreciated the use of a character in the conversational interface as a gatherer of the answers to the assessment questionnaire.
[Display omitted]
•37 participants reported their long-term UX on a conversational interface for 3 months.•After the app use, users' feeling about their health remained similar to before use.•The most satisfactory experiences occurred mainly during the first weeks of use.•A determining aspect in UX is whether the app features meet users' health needs.•As engagement evolves over time, hedonic aspects gain more weight than pragmatic ones.</description><subject>Chatbot</subject><subject>Conversational</subject><subject>Health</subject><subject>Identification methods</subject><subject>Long-term assessment</subject><subject>m-Health</subject><subject>Mapping</subject><subject>Questionnaires</subject><subject>User experience</subject><subject>User interfaces</subject><issn>0747-5632</issn><issn>1873-7692</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp9kE1LAzEQhoMoWKs_wFvA89Zk0yRdPJXiFxS86DnkY7ZN2SZrsi168bebtp49DTPvvPPxIHRLyYQSKu43E7s2k5rQpuSCiuYMjehMskqKpj5HIyKnsuKC1ZfoKucNIYRzIkboZ54z5OzDCncxrKoB0hbvMiQMXz0kD8ECjgFrvI3Gd4DXoLthjXXfd97qwRdtWKe4W5VawD5URcGwNeAcOGxj2EPKx77K6FxKnzvIhzRon-AaXbS6y3DzF8fo4-nxffFSLd-eXxfzZWVrKYdq2jpHGQUCGmonHSV2KlpuqDGsbjllXBg6A5Dld8eE40Y2VgrbiilvgGs2RnenuX2KxwPUJu5SKCtVzTgTpDnAGiN66rIp5pygVX3yW52-FSXqgFltVMGsDpjVCXPxPJw8UM7fe0gq2yM1V96zg3LR_-P-Bb29h80</recordid><startdate>202003</startdate><enddate>202003</enddate><creator>Biduski, Daiana</creator><creator>Bellei, Ericles Andrei</creator><creator>Rodriguez, João Pedro Mazuco</creator><creator>Zaina, Luciana Aparecida Martinez</creator><creator>De Marchi, Ana Carolina Bertoletti</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-6020-6356</orcidid></search><sort><creationdate>202003</creationdate><title>Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire</title><author>Biduski, Daiana ; Bellei, Ericles Andrei ; Rodriguez, João Pedro Mazuco ; Zaina, Luciana Aparecida Martinez ; De Marchi, Ana Carolina Bertoletti</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c277t-4fdd131e0eae2d7d10c46f5b1bb32f51356b18ee7106d36d5b79c76cf6459e5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Chatbot</topic><topic>Conversational</topic><topic>Health</topic><topic>Identification methods</topic><topic>Long-term assessment</topic><topic>m-Health</topic><topic>Mapping</topic><topic>Questionnaires</topic><topic>User experience</topic><topic>User interfaces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Biduski, Daiana</creatorcontrib><creatorcontrib>Bellei, Ericles Andrei</creatorcontrib><creatorcontrib>Rodriguez, João Pedro Mazuco</creatorcontrib><creatorcontrib>Zaina, Luciana Aparecida Martinez</creatorcontrib><creatorcontrib>De Marchi, Ana Carolina Bertoletti</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Computers in human behavior</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Biduski, Daiana</au><au>Bellei, Ericles Andrei</au><au>Rodriguez, João Pedro Mazuco</au><au>Zaina, Luciana Aparecida Martinez</au><au>De Marchi, Ana Carolina Bertoletti</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire</atitle><jtitle>Computers in human behavior</jtitle><date>2020-03</date><risdate>2020</risdate><volume>104</volume><spage>106169</spage><pages>106169-</pages><artnum>106169</artnum><issn>0747-5632</issn><eissn>1873-7692</eissn><abstract>A satisfying experience is critical for the user to feel motivated over time, especially in mobile health (m-Health) applications. Long-term user experience (UX) assesses more extended periods of use, which may reveal the possible impact of a set of experiences. In this study, using an in-app embed questionnaire available through a conversational interface, we investigated long-term UX on an m-Health application to identify how it occurs over time. The methods were developed in 4 phases, which included problem characterization, search for UX aspects, elaboration and verification of the questionnaire, test period with questionnaire applied before, during and after use, interview with users, and information mapping. For 3 months, 37 users reported their experiences with the application, describing their impressions regarding usage. Results demonstrated that the most satisfying experiences occurred mainly within the first weeks of the study and were associated with the app's features, charts and visual resources, and the practicality of treatment monitoring. For the less satisfactory experiences, the main reasons identified were technical problems on the application, and the effort and difficulty of use. All users appreciated the use of a character in the conversational interface as a gatherer of the answers to the assessment questionnaire.
[Display omitted]
•37 participants reported their long-term UX on a conversational interface for 3 months.•After the app use, users' feeling about their health remained similar to before use.•The most satisfactory experiences occurred mainly during the first weeks of use.•A determining aspect in UX is whether the app features meet users' health needs.•As engagement evolves over time, hedonic aspects gain more weight than pragmatic ones.</abstract><cop>Elmsford</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.chb.2019.106169</doi><orcidid>https://orcid.org/0000-0002-6020-6356</orcidid></addata></record> |
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subjects | Chatbot Conversational Health Identification methods Long-term assessment m-Health Mapping Questionnaires User experience User interfaces |
title | Assessing long-term user experience on a mobile health application through an in-app embedded conversation-based questionnaire |
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