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Reproductive Health
Article . 2024 . Peer-reviewed
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Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives

Authors: Sachdeva, Malika; Datchoua, Alida Moukam; Yakam, Virginie Flore; Kenfack, Bruno; Jonnalagedda-Cattin, Magali; Thiran, Jean-Philippe; Petignat, Patrick; +1 Authors

Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives

Abstract

Abstract Background Cervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to screen for cervical cancer; however, its accuracy can be limited. To address this issue, the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are collaborating to develop an automated smartphone-based image classifier that serves as a computer aided diagnosis tool for cancerous lesions. The primary objective of this study is to explore the acceptability and perspectives of women in Dschang regarding the usage of a screening tool for cervical cancer relying on artificial intelligence. A secondary objective is to understand the preferred form and type of information women would like to receive regarding this artificial intelligence-based screening tool. Methods A qualitative methodology was employed to gain better insight into the women’s perspectives. Participants, aged between 30 and 49 were invited from both rural and urban regions and semi-structured interviews using a pre-tested interview guide were conducted. The focus groups were divided on the basis of level of education, as well as HPV status. The interviews were audio-recorded, transcribed, and coded using the ATLAS.ti software. Results A total of 32 participants took part in the six focus groups, and 38% of participants had a primary level of education. The perspectives identified were classified using an adapted version of the Technology Acceptance Model. Key factors influencing the acceptability of artificial intelligence include privacy concerns, perceived usefulness, and trust in the competence of providers, accuracy of the tool as well as the potential negative impact of smartphones. Conclusion The results suggest that an artificial intelligence-based screening tool for cervical cancer is mostly acceptable to the women in Dschang. By ensuring patient confidentiality and by providing clear explanations, acceptance can be fostered in the community and uptake of cervical cancer screening can be improved. Trial registration Ethical Cantonal Board of Geneva, Switzerland (CCER, N°2017–0110 and CER-amendment n°4) and Cameroonian National Ethics Committee for Human Health Research (N°2022/12/1518/CE/CNERSH/SP). NCT: 03757299.

Keywords

Patient perspectives, Adult, Artificial intelligence, Research, Uterine Cervical Neoplasms, Qualitative study ; Female [MeSH] ; Early Detection of Cancer/methods [MeSH] ; Adult [MeSH] ; Humans [MeSH] ; Artificial intelligence ; Patient Acceptance of Health Care/psychology [MeSH] ; Middle Aged [MeSH] ; Artificial Intelligence [MeSH] ; Uterine Cervical Neoplasms/diagnosis [MeSH] ; Cameroon [MeSH] ; Qualitative Research [MeSH] ; Research ; Enhancing equity through digital technologies for sexual and reproductive health in low and middle-income countries ; Cervical cancer ; Focus Groups [MeSH] ; Patient perspectives ; Patient acceptability, Gynecology and obstetrics, Middle Aged, Patient Acceptance of Health Care, Focus Groups, Patient acceptability, Artificial Intelligence, Cervical cancer, RG1-991, Humans, Female, Cameroon, Qualitative study, Early Detection of Cancer, Qualitative Research

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
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gold