Investigator

Maria Luziene de Sousa Gomes

Universidade Federal Do Maranho

MLDMaria Luziene de …
Papers(2)
Applicability of the …Spatial-temporal anal…
Collaborators(9)
Mônica Oliveira Batis…R.R. SilvaWilliam Caracas Morei…Ana Carolina Ribeiro …Eremita Val RafaelJaiza Sousa PenhaJanielle Ferreira de …J.O. SantosLígia Gabryelle da Si…
Institutions(3)
Universidade Federal …Universidade Federal …Secretaria Nacional d…

Papers

Applicability of the levels of the socio-ecological model in the context of cervical cancer prevention: a scoping review

To map the evidence addressing the use of social ecological model (SEM) in cervical cancer (CC) prevention. The Joanna Briggs Institute (JBI) guideline was followed for conducting this scoping review. A search was conducted in thirteen databases, updated in July 2025. Primary quantitative and qualitative studies addressing the use of SEM in CC prevention were included, with no restrictions on time or language. Findings are reported in accordance with the PRISMA-ScR extension for scoping reviews. 80 studies were included. Of these, 56.2% addressed primary prevention, 45% secondary prevention, and 10% tertiary prevention. Regarding SEM levels, 92.5% examined intrapersonal, 86.3% interpersonal, 75% organizational, 67.5% community, and 50% public policy. Overall, 35% addressed all five SEM levels. The barriers to CC prevention include lack of knowledge, low educational level, financial difficulties, lack of trust in healthcare services and professionals, religious and cultural beliefs, fear, absence of professional recommendation and guidance, lack of social and family support, time constraints, limited access to healthcare services, high costs, and lack of health insurance. The facilitators include knowledge and awareness, higher educational level, risk perception, trust in providers and healthcare services, professional recommendation and guidance, social and family support, facilitated access to services, health insurance coverage, and adequate funding. The application of the SEM and the understanding of its multiple levels in the context of CC prevention, as well as the identification of barriers and facilitators, can significantly contribute to the development of targeted interventions and comprehensive strategies aimed at its prevention.

Spatial-temporal analysis of cervical cancer screening and social and health indicators in Brazil.

To identify the spatial-temporal patterns of cervical cancer (CC) screening in Brazil from 2013 to 2022 and its relationship with social and health indicators. This ecological study uses data from the Cancer Information System (SISCAN) of the Brazilian Unified Health System's Department of Informatics. The study analyzed women aged 25 to 64 who underwent CC screening in 5570 municipalities across Brazil. Global Moran's I and the Local Index of Spatial Autocorrelation (LISA) were employed to investigate clustering. The purely spatial scan statistic technique was used for spatial cluster detection. Temporal trends were assessed using joinpoint regression. GeoDa, SaTScan, GWR, and QGIS software were used for the analysis. The global clustering analysis of CC screening proportions revealed significant spatial autocorrelation (Moran's I = 0.530). Clusters of municipalities with low screening rates were significantly observed in the Northern (Amapá, Amazonas, Rondônia, Roraima) and Northeastern (Piauí, Pernambuco) regions. The Gini Index (β = -2.60), the Municipal Human Development Index (MHDI) (β = -10.5), and the Social Vulnerability Index (SVI) (β = -9.14) showed negative associations. Conversely, Family Health Strategy (FHS) coverage (β = 2.18) demonstrated a positive impact on screening rates. In terms of temporal trends, the screening proportion gradually increased from 5.4 % in 2014 to 10.5 % in 2022. Areas with a high risk of low CC screening rates were identified in the Northern and Northeastern regions of Brazil, which are characterized by socioeconomic and demographic disparities, vulnerabilities, and inequalities.

2Papers
9Collaborators

Education

2023

PhD

Universidade Federal do Maranhão · Department of Nursing

Country

BR