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User experience of a family health history chatbot: A quantitative analysis
OBJECTIVE: Family health history (FHx) is an important tool in assessing one’s risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quant...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187455/ https://www.ncbi.nlm.nih.gov/pubmed/37205400 http://dx.doi.org/10.21203/rs.3.rs-2886804/v1 |
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author | Allen, Caitlin |
author_facet | Allen, Caitlin |
author_sort | Allen, Caitlin |
collection | PubMed |
description | OBJECTIVE: Family health history (FHx) is an important tool in assessing one’s risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns. METHODS: We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement. RESULTS: Of 11065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 seconds. Users spent the highest median time on Proband Cancer History (124.00 seconds) and Family Cancer History (119.00 seconds) subflows. Search list questions took the longest to complete (median 19.50 seconds), followed by free text email input (15.00 seconds). CONCLUSION: Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection. |
format | Online Article Text |
id | pubmed-10187455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-101874552023-05-17 User experience of a family health history chatbot: A quantitative analysis Allen, Caitlin Res Sq Article OBJECTIVE: Family health history (FHx) is an important tool in assessing one’s risk towards specific health conditions. However, user experience of FHx collection tools is rarely studied. ItRunsInMyFamily.com (ItRuns) was developed to assess FHx and hereditary cancer risk. This study reports a quantitative user experience analysis of ItRuns. METHODS: We conducted a public health campaign in November 2019 to promote FHx collection using ItRuns. We used software telemetry to quantify abandonment and time spent on ItRuns to identify user behaviors and potential areas of improvement. RESULTS: Of 11065 users who started the ItRuns assessment, 4305 (38.91%) reached the final step to receive recommendations about hereditary cancer risk. Highest abandonment rates were during Introduction (32.82%), Invite Friends (29.03%), and Family Cancer History (12.03%) subflows. Median time to complete the assessment was 636 seconds. Users spent the highest median time on Proband Cancer History (124.00 seconds) and Family Cancer History (119.00 seconds) subflows. Search list questions took the longest to complete (median 19.50 seconds), followed by free text email input (15.00 seconds). CONCLUSION: Knowledge of objective user behaviors at a large scale and factors impacting optimal user experience will help enhance the ItRuns workflow and improve future FHx collection. American Journal Experts 2023-05-03 /pmc/articles/PMC10187455/ /pubmed/37205400 http://dx.doi.org/10.21203/rs.3.rs-2886804/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. https://creativecommons.org/licenses/by/4.0/License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | Article Allen, Caitlin User experience of a family health history chatbot: A quantitative analysis |
title | User experience of a family health history chatbot: A quantitative analysis |
title_full | User experience of a family health history chatbot: A quantitative analysis |
title_fullStr | User experience of a family health history chatbot: A quantitative analysis |
title_full_unstemmed | User experience of a family health history chatbot: A quantitative analysis |
title_short | User experience of a family health history chatbot: A quantitative analysis |
title_sort | user experience of a family health history chatbot: a quantitative analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187455/ https://www.ncbi.nlm.nih.gov/pubmed/37205400 http://dx.doi.org/10.21203/rs.3.rs-2886804/v1 |
work_keys_str_mv | AT allencaitlin userexperienceofafamilyhealthhistorychatbotaquantitativeanalysis |