Evidence map›Paper›PMID 38937771›Full record

ArticleReproductive health2024

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

Malika Sachdeva, Alida Moukam Datchoua, Virginie Flore Yakam, Bruno Kenfack, Magali Jonnalagedda-Cattin, Jean-Philippe Thiran, Patrick Petignat, Nicole Christine Schmidt

Abstract read
In one paragraph

Article in Reproductive health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
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  6. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Malika SachdevaFaculty of Medicine, University of Geneva, Geneva, Switzerland. mlksachdeva@gmail.com.
Alida Moukam DatchouaDepartment of Gynaecology and Obstetrics, Dschang Regional Annex Hospital, Dschang, Cameroon.
Virginie Flore YakamDepartment of Gynaecology and Obstetrics, Dschang Regional Annex Hospital, Dschang, Cameroon.
Bruno KenfackDepartment of Gynaecology and Obstetrics, Dschang Regional Annex Hospital, Dschang, Cameroon.
Magali Jonnalagedda-CattinSignal Processing Laboratory LTS5, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Jean-Philippe ThiranSignal Processing Laboratory LTS5, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
Patrick PetignatGynaecology Division, Department of Paediatrics, Gynaecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland.
Nicole Christine SchmidtGynaecology Division, Department of Paediatrics, Gynaecology and Obstetrics, University Hospitals of Geneva, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical 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.

methodsA 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.

resultsA 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.

conclusionThe 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 registrationEthical 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.

Indexed as

Artificial IntelligenceEarly Detection of CancerPatient Acceptance of Health CareQualitative ResearchUterine Cervical NeoplasmsAdultCameroonFemaleFocus GroupsHumansMiddle AgedArtificial intelligenceCervical cancerPatient acceptabilityPatient perspectivesQualitative study

Identifiers

PMID38937771
PMCPMC11212410

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.