Insights from User Reviews to Improve Suicide Prevention Apps: A Machine Learning and Thematic Analysis-Based Approach.
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| Title: | Insights from User Reviews to Improve Suicide Prevention Apps: A Machine Learning and Thematic Analysis-Based Approach. |
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| Authors: | Okuboyejo, Senanu1, Senanu.okuboyejo@metrostate.edu, Han, Sijie2, Jha, Smriti3, Eneja, Chikwado3, Orji, Rita3 |
| Source: | International Journal of Human-Computer Interaction; Nov2025, Vol. 41 Issue 21, p13771-13791, 21p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 188923586 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=188923586 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10447318.2025.2476711 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 13771 Titles: – TitleFull: Insights from User Reviews to Improve Suicide Prevention Apps: A Machine Learning and Thematic Analysis-Based Approach. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Okuboyejo, Senanu – PersonEntity: Name: NameFull: Han, Sijie – PersonEntity: Name: NameFull: Jha, Smriti – PersonEntity: Name: NameFull: Eneja, Chikwado – PersonEntity: Name: NameFull: Orji, Rita IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 11 Text: Nov2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10447318 Numbering: – Type: volume Value: 41 – Type: issue Value: 21 Titles: – TitleFull: International Journal of Human-Computer Interaction Type: main |
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