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Background: Disrespect and abuse (D & A) during labor and delivery are important issues correlated with human rights, equity, and public health that also affect women’s decisions to deliver in facilities, which provide appropriate management of maternal and neonatal complications. Little is known about interventions aimed at lowering the frequency of disrespectful and abusive behaviors. Methods: Between 2011 and 2014, a pre-and-post study measured D & A levels in a three-tiered intervention at 13 facilities in Kenya under the Heshima project. The intervention involved working with policymakers to encourage greater focus on D & A, training providers on respectful maternity care, and strengthening linkages between the facility and community for accountability and governance. At participating facilities, postpartum women were approached at discharge and asked to participate in the study; those who consented were administered a questionnaire on D & A in general as well as six typologies, including physical and verbal abuse, violations of confidentiality and privacy, detainment for non-payment, and abandonment. Observation of provider-patient interaction during labor was also conducted in the same facilities. In both exit interview and observational studies, multivariate analyses of risk factors for D & A controlled for differences in socio-demographic and facility characteristics between baseline and endline surveys. Results: Overall D & A decreased from 20-13 % (p < 0.004) and among four of the six typologies D & A decreased from 40-50 %. Night shift deliveries were associated with greater verbal and physical abuse. Patient and infant detainment declined dramatically from 8.0-0.8 %, though this was partially attributable to the 2013 national free delivery care policy. Conclusion: Although a number of contextual factors may have influenced these findings, the magnitude and consistency of the observed decreases suggest that the multi-component intervention may have the potential to reduce the frequency of D & A. Greater efforts are needed to develop stronger evaluation methods for assessing D & A in other settings.
Our study used a before-and-after design, without a comparison group, to measure the effect of interventions to reduce the prevalence of D & A during labor and delivery in 13 Kenyan health facilities. Baseline data were collected between September 2011 and February 2012, with endline data collected in January and February 2014. The study conducted two data collection exercises: exit interviews with women who had just delivered and observation of women, from their early labor to post-delivery, conducted by trained nurses and midwives. The 13 purposefully selected facilities constituted different facility types (public, private, faith-based) and different levels of care, comprised of three public referral hospitals, three district (public) hospitals with maternity units, two faith-based hospitals, two private nursing homes, and one (public) health center. Four of the 13 facilities were rural and the rest were in urban or peri-urban areas. Facilities in the study employed 58 specialist doctors, 116 medical doctors, 1,503 nurses or midwives, 27 theater nurses, 48 anesthetists, and 126 pharmacists. The 13 facilities, combined, had 21 delivery couches and a total bed capacity of 194 in the labor wards. Outpatient health facilities (heath centers or clinics) had only one nurse or midwife per shift, while larger ones (hospitals) employed nine to 11 per shift. All women 15–45 years old who had delivered within 24–48 hours in a participating facility were eligible for inclusion, regardless of pregnancy outcome. Heshima researchers approached all postpartum women discharged from the postnatal ward, described the study and its interview process, emphasizing its privacy and confidentiality, and their consent to participate was requested, utilizing a structured consent form in the woman’s preferred language. Women were recruited until the necessary sample sizes were reached for all 13 study facilities [13]. During the September 2011 through January 2012 baseline period, a total of 641 women consented to participate; during the January and February 2014 endline, 728 women consented to participate. Fifty percent (50 %) of all women who delivered in the facilities in the previous 48 hours participated in the study’s baseline survey, and 60 % participated in the endline survey. Interviews were conducted in a specially designated room at each facility by interviewers trained in the study procedures to ensure that patient privacy was maintained. The questionnaire includes modules that examine women’s demographic and household characteristics including their socio-economic status, past service utilization, characteristics of their deliveries, their perceived quality and satisfaction, and experiences of D & A. Table 2 presents the questions used to assess D & A experiences. Portable digital assistant (PDA) devices were used to collect the data, which were downloaded into an MS Access database before their export to Stata 11 for data management. Questions for assessment and corresponding categories For the observations of provider-patient interaction, participants were in early labor, ages 15–45, who provided their informed consent for observation of their labor and delivery, with key actions recorded. In each study location, a trained researcher approached the facility’s patients in early labor as they entered the maternity unit, explained the study and its objectives, and requested their written consent for the observation. The structured, non-participant observations in maternity units measured both process (how patients are treated) and content (what they were told, revealing technical competency, accuracy of information and provision of essential information) of services. Data were collected on paper questionnaires, keyed into EpiData 3.1, and exported to Stata 11 for cleaning and analysis. Researchers were nurses or midwives trained to conduct the observations. A list of potential situations requiring their possible intervention (e.g., emergencies such as heavy vaginal bleeding if staff was otherwise not available) was developed by the Ministry of Health, and if such life-threatening situations occurred, they were allowed to provide immediate emergency care. For all such situations, the observation was terminated and was not included in the analysis. Final analyses of both the exit interviews and observation of provider-patient interaction utilized SAS software, Version 9.4 (Cary, NC, USA). To measure the intervention’s effects in reducing the occurrences of D & A, a Likert scale operationalized an accepted definition of D & A [4]. The key outcome of interest was the percentage of women responding with any answer other than 5 to the question “On a scale of 1 to 5, were you treated in a way that made you feel humiliated or disrespected? 1 means very humiliated and 5 means not humiliated.” The study also sought to examine the intervention’s effects on six categories of D & A including occurrence of physical abuse, violation of privacy as well as confidentiality, verbal abuse, detainment, and abandonment [6]. To assess these categories of D & A, women were asked to provide a “yes” or “no” response to the questions listed in Table 2. A wealth indicator variable was created to represent socio-economic status based on questions assessing a woman’s household ownership of specific items (radio, television, bicycle, phone, refrigerator, scooter, automobile) as well as household characteristics (flooring and roofing materials, water sources, toilet facilities, electricity). Principal component analysis generated factor scores, and an overall asset score was calculated for each participant. Wealth terciles were constructed using the final asset scores, which were based on an analysis of the whole sample, including baseline and endline participants, to control for socio-economic differences between the two groups. Bivariate analyses utilized a chi-square test to determine if baseline and endline participants were significantly different in their socio-demographic and delivery characteristics. Unadjusted and multivariate logistic generalized linear mixed models (GLMM), with the facility as a random effect and all other variables as fixed effects, assessed differences in D & A for baseline and endline participants, as well as the association of D & A with other characteristics. Covariates included in all multivariate models included woman’s age, parity, socio-economic status, time of delivery, marital status, accompaniment by another adult, and facility type. Other covariates considered for inclusion in models included education, any lifetime experience of physical abuse or rape, whether referred or presented at the facility directly, and primary service provider. All of these additional covariates were evaluated in each model and preserved only if statistically significant (p < 0.05), or if their presence altered the magnitude of association between time (baseline/endline) and D & A outcome by at least 10 percent. Seven indicators of the categories of D & A were selected, with matching measures at baseline and endline (Table 2), with three indicators for initial examination (non-consensual care, verbal abuse, lack of privacy), three during delivery (physical aggression, verbal aggression, lack of privacy), and one for postpartum care (bed sharing). Covariates included age, parity, time of delivery, facility type, and voucher status. Analyses of patient and provider observations followed a methodology similar to the patient exit interviews. Bivariate analyses assessed the characteristics of the sample at baseline and endline, while unadjusted and multivariate logistic GLMM assessed differences between baseline and endline for D & A and it’s socio-demographic and facility risk factors. As with other analyses, the facility was included as a random effect. Covariates included all five of the previously enumerated exposure variables.
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