Jerome L Belinson1, Guixiang Wang2, Xinfeng Qu3, Hui Du2, Jingjing Shen2, Jiajia Xu4, Liqun Zhong5, Ji Yi4, Xin Yi4, Ruifang Wu2. 1. Preventive Oncology International, Cleveland Heights, OH, USA; The Women's Health Institute, Cleveland Clinic, Cleveland, OH, USA. Electronic address: jlb@poiinc.org. 2. Dept of Ob/Gyn, Peking University Shenzhen Hospital, Shenzhen, PR China. 3. Preventive Oncology International, Cleveland Heights, OH, USA. 4. BGI Shenzhen, Shenzhen, PR China. 5. The Maternity and Child Health Hospital, Heshan, Guangdong, PR China.
Abstract
OBJECTIVE: To develop and implement a community based model for cervical cancer prevention that allows the communities to manage the screening and the healthcare system to focus resources on evaluation and management of the positives. METHODS: Using self-sampling and the concepts founded in Community Based Participatory Research (CBPR), we progressively developed a model to efficiently reach the women, especially rural communities; and collect the volume of samples needed to support high throughput centralized low cost per case processing. RESULTS: 8382 eligible women, ages 35 to 59, in 130 rural communities participated. The screening was organized by the local government administration and conducted by the community leaders (CLs). The model used was progressively designed through detailed assessment of key elements at 6 decision points in 26 workshops that were used to train the CLs and the local promoters. The communities were able to accurately conduct the screening; in the final model a local medical worker conducted a 50-minute workshop featuring instructional posters and structured role-play. A manual and a workshop DVD were created for distribution to and implementation by local governments. The average callback rate was 84.3%, without involvement of the local doctors in the management of the positives. CONCLUSION: An efficient community based model capable of massive screening events was developed. We believe that the callback rate will be further improved when local doctors are trained in the management of the positives. Many elements impact coverage and further research is needed to define the influence of the identified key variables.
OBJECTIVE: To develop and implement a community based model for cervical cancer prevention that allows the communities to manage the screening and the healthcare system to focus resources on evaluation and management of the positives. METHODS: Using self-sampling and the concepts founded in Community Based Participatory Research (CBPR), we progressively developed a model to efficiently reach the women, especially rural communities; and collect the volume of samples needed to support high throughput centralized low cost per case processing. RESULTS: 8382 eligible women, ages 35 to 59, in 130 rural communities participated. The screening was organized by the local government administration and conducted by the community leaders (CLs). The model used was progressively designed through detailed assessment of key elements at 6 decision points in 26 workshops that were used to train the CLs and the local promoters. The communities were able to accurately conduct the screening; in the final model a local medical worker conducted a 50-minute workshop featuring instructional posters and structured role-play. A manual and a workshop DVD were created for distribution to and implementation by local governments. The average callback rate was 84.3%, without involvement of the local doctors in the management of the positives. CONCLUSION: An efficient community based model capable of massive screening events was developed. We believe that the callback rate will be further improved when local doctors are trained in the management of the positives. Many elements impact coverage and further research is needed to define the influence of the identified key variables.
Authors: Barrett Sewali; Kolawole S Okuyemi; Asli Askhir; Jerome Belinson; Rachel I Vogel; Anne Joseph; Rahel G Ghebre Journal: Cancer Med Date: 2015-02-04 Impact factor: 4.452
Authors: Hongfei Long; Wenting Huang; Pinpin Zheng; Jiang Li; Sha Tao; Shenglan Tang; Abu S Abdullah Journal: Int J Environ Res Public Health Date: 2018-10-26 Impact factor: 3.390
Authors: J Andrew Dykens; Jennifer S Smith; Margaret Demment; E Marshall; Tina Schuh; Karen Peters; Tracy Irwin; Scott McIntosh; Angela Sy; Timothy Dye Journal: Cancer Causes Control Date: 2020-03-17 Impact factor: 2.506