Context: Women who attend sexually transmitted disease (STD) clinics are at high risk for unintended pregnancy. Little information is available, however, on the rates of discontinuation of effective contraceptive method use among this population.
Methods: As part of a study on contraceptive services offered by an STD clinic in Denver, 406 clients who accepted these services in 1996-1999 were interviewed about their contraceptive practice, experience of side effects and method-use problems at baseline and at four, eight and 12 months of follow-up. Multivariate survival analysis was used to assess predictors of discontinuation of effective contraceptive use.
Results: Twenty-nine percent of women discontinued use by the end of one year. Coxproportional hazards models show that compared with women who reported no method-use problems, those who experienced one problem were three times as likely (hazard ratio, 3.0) to discontinue effective use, and women who had at least two problems were five times as likely (5.0) to discontinue use. The experience of side effects with either a past or a current method, however, was not associated with the risk of discontinuation. Furthermore, women who reported risky sexual behavior in the year before enrollment were significantly less likely to discontinue effective method use (hazard ratio, 0.4), as were women who were covered by medical insurance or who gained such coverage during a follow-up interval (hazard ratio, 0.5 for each).
Conclusions: In this study population of STD clinic users, method-use problems appear to be a more fundamental issue for contraceptive compliance than the pastor current experience of side effects. The unexpected association between method-use problems and the risk of discontinuation needs to be further delineated so that effective interventions addressing these problems can be developed and implemented.
Download full-text PDF |
Source |
---|
Interact J Med Res
November 2024
School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, United Kingdom.
Background: Co-creation is increasingly recognized for its potential to generate innovative solutions, particularly in addressing complex and wicked problems in public health. Despite this growing recognition, there are no standards or recommendations for method use in co-creation, leading to confusion and inconsistency. While some studies have examined specific methods, a comprehensive overview is lacking, limiting the collective understanding and ability to make informed decisions about the most appropriate methods for different contexts and research objectives.
View Article and Find Full Text PDFSci Rep
May 2024
Department of Epidemiology, School of Public Health, College of Medicine and Health Sciences, Wachemo University, Hossana, Ethiopia.
Long-acting reversible contraceptive (LARC) method use is an ideal strategy for longer protection against unintended pregnancies, unsafe abortions, maternal morbidities, and mortalities related to pregnancies and childbirth. Despite low utilization of LARC methods in Ethiopia, early discontinuation remains a problem. This study aimed to assess prevalence of early discontinuation of LARC methods and associated factors in Hossana town.
View Article and Find Full Text PDFBMC Public Health
July 2022
Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
Background: Anaemia among women is a public health problem with associated adverse outcomes for mother and child. This study investigates the determinants of women's anaemia in two Bengals; West Bengal (a province of India) and Bangladesh. These two spaces are inhabitated by Bengali speaking population since historic past.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
March 2022
With the development of deep learning and medical imaging technology, many researchers use convolutional neural network(CNN) to obtain deep-level features of medical image in order to better classify Alzheimer's disease (AD) and predict clinical scores. The principal component analysis network (PCANet) is a lightweight deep-learning network that mainly uses principal component analysis (PCA) to generate multilevel filter banks for the centralized learning of samples and then performs binarization and generates blockwise histograms to obtain image features. However, the dimensions of the extracted PCANet features reaching tens of thousands or even hundreds of thousands, and the formation of the multilevel filter banks is sample data dependent, reducing the flexibility of PCANet.
View Article and Find Full Text PDFThe input data of energy system models are, in many cases, aggregated data used to represent regions of interest. This paper presents a method of using energy-related spatial data and the max-p-regions method to define regions. The method aims to assign areas to regions that are similar in how much they consume, produce and store electricity.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!