RESUMO
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.
RESUMO
PURPOSE: This study describes the 10 steps followed to produce the information architecture of a user-centered design (UCD) counseling mobile application, the first phase to develop an app. The app aims to reduce the psychosocial impact of the human papillomavirus test result and improve women's knowledge of human papilloma virus and cervical cancer. METHODS: We used a UCD approach to produce the information architecture of the app (ie, how to organize contents into features). We analyzed field notes, meeting agendas, and documentation produced during each stage of the design process. We described the goals, methods, and outcomes of each step. We also discussed the critical challenges and the strategies to address them. RESULTS: The steps are (1) knowledge, attitudes, and beliefs mapping: reanalysis of team's research findings from prior studies; (2) environmental scanning of apps available on the market; (3) stakeholders' point of view: The International Advisory Committee; (4) potential user's profile: building archetypes through the Persona method; (5) women's interviews: user's preferences and experiences; (6) effective features: scoping review to select app's features that address psychosocial impact; (7) the user journey: ideal interaction with the gynecological service and the counseling app; (8) women's focus groups: using Personas and Scenarios to discuss app's mock-up; (9) women's design sessions: prototype test and card-sorting techniques; and (10) team's design session: translating results into visual objects and features. CONCLUSION: We provide here detailed descriptions of the UCD process of an app for human papillomavirus-tested women for those venturing into the area of mHealth strategies work. Our experience can be used as a guide for future mHealth app development for a low- and middle-income setting.