Objectives: Among cancer prevention studies, little is known about knowledge, attitudes, and beliefs toward triage adherence in the context of the human papillomavirus self-collection test. This formative research aims to identify knowledge, attitudes, and beliefs related to human papillomavirus and cervical cancer prevention specifically about adherence to Pap triage among women residing in a low-income province in Argentina. Methods: We conducted six focus groups, stratified by residence and age. All participants were aged 30 or older and had performed human papillomavirus self-collection. Data collection and thematic analysis were carried out using constructs from the Health Belief Model. Results: Misinformation regarding human papillomavirus and cervical cancer was common and was a source of distress. Women could not distinguish Pap screening from triage; human papillomavirus risk perception was limited but cervical cancer was perceived as a threatening disease. Women were willing to follow-up after receiving an abnormal screening result. Negative views about clinician-collected screening/triage were common, defined as painful and shameful, and comes with an economic cost (transport/time). Lack of help from family/friends was an obstacle to adhering to triage. Health issues in the family’s records and a physician’s recommendation were a cue to adhere to triage. Conclusion: Lack of knowledge or misinformation of the causes of cervical cancer, human papillomavirus, and the multi-step screening and triage process are barriers to follow-up adherence. Interventions to improve communication between women and health providers about screening results and follow-up are needed. Also, health services should be organized to respond to women’s needs and reduce access barriers to follow-up.
Background
In Argentina, HPV self-collection offered by community health workers was demonstrated to be effective to improve cervical cancer screening uptake. Based on these findings, the EMA strategy was scaled up in nine Argentinian provinces. However, there is no evidence about the degree of fidelity—in relation to the core components proposed by the National Program on Cervical Cancer Prevention—with which this strategy was implemented in the new jurisdictions. We carried out a fidelity evaluation of the EMA strategy scaling-up aimed at evaluating the level of adherence to the core components of the EMA strategy, and how different moderating factors affected the implementation fidelity.
Methods
This descriptive study used a multi-method approach involving quantitative and qualitative evaluations of the implementation fidelity using the Conceptual Framework for Implementation Fidelity. Evaluation of the degree of adherence to the core components of the EMA strategy was carried out through the analysis of a self-administered survey of health promoters, observations, and secondary data from the National Screening Information System. The analysis of moderating factors was carried out through analysis of field notes, and semi-structured interviews with key stakeholders.
Results
Our results showed that the core components with highest fidelity were training, sample handling, and transportation. Regarding the offer of HPV self-collection, we found some adaptations such as locations in which health promoters offered HPV self-collection, and fewer pieces of information provided to women during the offer. In the follow-up and treatment core component, we found a reduced adherence to triage and colposcopy. Some contextual factors had a negative impact on implementation fidelity, such as urban insecurity and the reduction in the number of health promoters that offered HPV self-collection. Moderating factors that contributed to achieve high level of fidelity included a well-defined strategy with clear steps to follow, permanent feedback and high level of engagement among implementers.
Conclusions
Our study shows how the analysis of fidelity and adaptations of HPV self-collection in real-world contexts are key to measure and maximize its effectiveness in low-middle-income settings.
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