Understanding 'missed appointments' for pills and injectables: a mixed methods study in Senegal
Understanding 'missed appointments' for pills and injectables: a mixed methods study in Senegal
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DOI：
10.1136/bmjgh-2018-000975
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发表时间：
2018-11-01
影响因子：
8.1
通讯作者：
Lynch, Caroline A.
中科院分区：
文献类型：
--
作者：
Cavallaro, Francesca L.;Duclos, Diane;Lynch, Caroline A.
引言 撒哈拉以南非洲地区避孕方法的停用率很高。然而，尽管方法使用的个别事件对意外怀孕有影响，但人们对它们的差距知之甚少。这项混合方法研究的目的是调查塞内加尔药物和注射剂重复预约延误的流行情况，并探讨导致延迟的因素。方法首先，我们使用塞内加尔 67 个机构的常规记录构建了女性避孕咨询的纵向数据集。根据自上次预约以来的时间，药丸和注射剂的咨询被分为准时、延迟或未知延迟状态。我们描述了延迟预约的普遍情况，并使用向后逐步回归建立了一个混合效应模型来调查延迟的风险因素。其次，我们与计划生育 (FP) 提供者举办了研讨会，并对育龄妇女进行了深入访谈和焦点小组讨论，以探讨导致延误的因素。结果 近三分之一 (30%) 的药物和注射药物预约被延误，导致怀孕风险。先前的延误、药物使用、较低的教育水平、较高的奇偶性、第三次及随后的就诊以及伊斯兰信仰是延误的独立预测因素（p
Introduction High discontinuation rates of contraceptive methods have been documented in sub-Saharan Africa. However, little is known about gaps within individual episodes of method use, despite their implications for unintended pregnancies. The objective of this mixed methods study was to examine the prevalence of, and explore the factors contributing to, delays in repeat appointments for pills and injectables in Senegal.Methods First, we constructed a longitudinal data set of women's contraceptive consultations using routine records from 67 facilities in Senegal. Consultations for pills and injectables were classified as on time, delayed or with unknown delay status based on time since previous appointment. We described the prevalence of delayed appointments and used backward stepwise regression to build a mixed-effects model to investigate risk factors for delay. Second, we conducted workshops with family planning (FP) providers, and indepth interviews and focus group discussions with women of reproductive age, to explore factors contributing to delays.Results Almost one-third (30%) of appointments for pills and injectables were delayed, resulting in risk of pregnancy. Previous delay, pill use, lower educational level, higher parity, third and subsequent visits, and Islamic faith were independently predictive of delays (p