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DOI 10.1177/14604582241262251

Медицинская библиотека · Health informatics journal · 2024

User experience of a family health history chatbot: A quantitative analysis.

Soni Hiral, Morrison Heath, Vasilev Dinko, Ong Triton, Wilczewski Hattie, Allen Caitlin, Hughes-Halbert Chanita, Ritchie Jordon B, Narma Alexa, Schiffman Joshua D, Ivanova Julia, Bunnell Brian E, Welch Brandon M

СтатьяПоддержка NIH: внешняя программаПеревод в очереди

Аннотация

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 11,065 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 s. Users spent the highest median time on Proband Cancer History (124.00 s) and Family Cancer History (119.00 s) subflows. Search list questions took the longest to complete (median 19.50 s), followed by free text email input (15.00 s).

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.

Для цитирования: Soni Hiral, Morrison Heath, Vasilev Dinko, Ong Triton, Wilczewski Hattie, Allen Caitlin, Hughes-Halbert Chanita, Ritchie Jordon B, Narma Alexa, Schiffman Joshua D, Ivanova Julia, Bunnell Brian E, Welch Brandon M. User experience of a family health history chatbot: A quantitative analysis.. Health informatics journal. 2024. DOI: 10.1177/14604582241262251.

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