BackgroundPerson-centered care during childbirth is recognized as a critical component of quality of maternity care. But there are few validated tools to measure person-centered maternity care (PCMC). This paper aims to fill this measurement gap. We present the results of the psychometric analysis of the PCMC tool that was previously validated in Kenya using data from India. We aim to assess the validity and reliability of the PCMC scale in India, and to compare the results to those found in the Kenya validation.MethodsWe use data from a cross-sectional survey conducted from August to October 2017 with recently delivered women at 40 government facilities in Uttar Pradesh, India (N = 2018). The PCMC measure used is a previously validated scale with subscales for dignity and respect, communication and autonomy, and supportive care. We performed psychometric analyses, including iterative exploratory and confirmatory factor analysis, to assess construct and criterion validity and reliability.ResultsThe results provide support for a 27-item PCMC scale in India with a possible score range from 0 to 81, compared to the 30-item PCMC scale in Kenya with a 0 to 90 possible score range. The overall PCMC scale has good reliability (Cronbach alpha = 0.85). Similar to Kenya, we are able to group the items in to three conceptual domains representing subscales for “Dignity and Respect,” “Communication and Autonomy,” and “Supportive Care.” The sub-scales also have relatively good reliability (Cronbach alphas range from 0.67 to 0.73). In addition, increasing scores on the scale is associated with future intentions to deliver in the same facility, suggesting good criterion validity.ConclusionsThis research extends the PCMC literature by presenting results of validating the PCMC scale in a new context. The psychometric analysis using data from Uttar Pradesh, India corroborates the Kenya analysis showing the scale had good content, construct, and criterion validity, as well as high reliability. The overlap in items suggests that this scale can be used across different contexts to compare women’s experiences of care, and to inform and evaluate quality improvement efforts to promote comprehensive PCMC.

In India, most women now delivery in hospitals or other facilities, however, maternal and neonatal mortality remains stubbornly high. Studies have shown that mistreatment causes delays in care-seeking, early discharge and poor adherence to post-delivery guidance. This study seeks to understand the variation of women’s experiences in different levels of government facilities. This information can help to guide improvement planning. We surveyed 2018 women who gave birth in a representative set of 40 government facilities from across Uttar Pradesh (UP) state in northern India. Women were asked about their experiences of care, using an established scale for person-centred care. We asked questions specific to treatment and clinical care, including whether tests such as blood pressure, contraction timing, newborn heartbeat or vaginal exams were conducted, and whether medical assessments for mothers or newborns were done prior to discharge. Women delivering in hospitals reported less attentive care than women in lower-level facilities, and were less trusting of their providers. After controlling for a range of demographic attributes, we found that better access, higher clinical quality, and lower facility-level, were all significantly predictive of patient-centred care. In UP, lower-level facilities are more accessible, women have greater trust for the providers and women report being better treated than in hospitals. For the vast majority of women who will have a safe and uncomplicated delivery, our findings suggest that the best option would be to invest in improvements mid-level facilities, with access to effective and efficient emergency referral and transportation systems should they be needed.

Abstract While it is mandated that reproductive and child health services be provided for free at public facilities in India, qualitative evidence suggests it is common for facilities to request bribes and other informal payments for medicines, medical tests or equipment. This article examines the prevalence of bribe requests, total out-of-pocket expenditures (OOPEs) and associations between bribe requests and total OOPEs on the experience of quality of care and maternal complications during childbirth. Women who delivered in public facilities in Uttar Pradesh, India were administered a survey on sociodemographic characteristics, bribe requests, total OOPEs, types of health checks received and experience of maternal complications. Data were analysed using descriptive, bivariate and multivariate statistics. Among the 2018 women who completed the survey, 43% were asked to pay a bribe and 73% incurred OOPEs. Bribe requests were associated with lower odds of receiving all health checks upon arrival to the facility (aOR = 0.49; 95% CI: 0.24–0.98) and during labour and delivery (aOR = 0.44; 95% CI: 0.25–0.76), lower odds of receiving most or all health checks after delivery (aOR = 0.44; 95% CI: 0.31–0.62) and higher odds of experiencing maternal complications (aOR = 1.45; 95% CI: 1.13–1.87). Although it is mandated that maternity care be provided for free in public facilities in India, these findings suggest that OOPEs are high, and bribes/tips contribute significantly. Interventions centred on improving person-centred care (particularly guidelines around bribes), health system conditions and women’s expectations of care are needed.

Cochlear implants use electrical stimulation of the auditory nerve to restore the sensation of hearing to deaf people. Unfortunately, the stimulation current spreads extensively within the cochlea, resulting in "blurring" of the signal, and hearing that is far from normal. Current spread can be indirectly measured using the implant electrodes for both stimulating and sensing, but this provides incomplete information near the stimulating electrode due to electrode-electrolyte interface effects. Here, we present a 3D-printed "unwrapped" physical cochlea model with integrated sensing wires. We integrate resistors into the walls of the model to simulate current spread through the cochlear bony wall, and "tune" these resistances by calibration with an in-vivo electrical measurement from a cochlear implant patient. We then use this model to compare electrical current spread under different stimulation modes including monopolar, bipolar and tripolar configurations. Importantly, a trade-off is observed between stimulation amplitude and current focusing among different stimulation modes. By combining different stimulation modes and changing intracochlear current sinking configurations in the model, we explore this trade-off between stimulation amplitude and focusing further. These results will inform clinical strategies for use in delivering speech signals to cochlear implant patients.

Purpose The purpose of this paper is to develop an integrated engineering process control (EPC)–statistical process control (SPC) methodology for simultaneously monitoring and controlling autocorrelated multiple responses, namely, brightness and viscosity of the pulp bleaching process. Design/methodology/approach The pulp bleaching is a process of separating cellulose from impurities present in cooked wood chips through chemical treatment. More chemical dosage or process adjustments may result in better brightness but adversely affect viscosity. Hence, the optimum chemical dosage that would simultaneously minimize the deviation of pulp brightness and viscosity from their respective targets needs to be determined. Since the responses are autocorrelated, dynamic regression is used to model the responses. Then, the optimum chemical dosage that would simultaneously optimize the pulp brightness and viscosity is determined by fuzzy optimization methodology. Findings The suggested methodology is validated in 12 cases. The validation results showed that the optimum dosage simultaneously minimized the variation in brightness and viscosity around their respective targets. Moreover, suggested solution has been found to be superior to the one obtained by optimizing the responses independently. Practical implications This study provides valuable information on how to identify the optimum process adjustments to simultaneously ensure autocorrelated multiple responses on or close to their respective targets. Originality/value To the best of the authors’ knowledge, this paper is the first to provide application of the integrated EPC–SPC methodology for simultaneously monitoring multiple responses. The study also demonstrates the application of dynamic regression to model autocorrelated responses.