Patient-centered Care in Maternity Services: A Critical Appraisal and Synthesis of the Literature.

BACKGROUND: Patient-centered care (PCC) has been recognized as a marker of quality in health service delivery. In policy documents, PCC is often used interchangeably with other models of care. There is a wide literature about PCC, but there is a lack of evidence about which model is the most appropriate for maternity services specifically. AIM: We sought to identify and critically appraise the literature to identify which definition of PCC is most relevant for maternity services. METHODS: The four-step approach used to identify definitions of PCC was to 1) search electronic databases using key terms (1995-2011), 2) cross-reference key papers, 3) search of specific journals, and 4) search the grey literature. Four papers and two books met our inclusion criteria. ANALYSIS: A four-criteria critical appraisal tool developed for the review was used to appraise the papers and books. MAIN RESULTS: From the six identified definitions, the Shaller's definition met the majority of the four criteria outlined and seems to be the most relevant to maternity services because it includes physiologic conditions as well as pathology, psychological aspects, a nonmedical approach to care, the greater involvement of family and friends, and strategies to implement PCC. CONCLUSION: This review highlights Shaller's definitions of PCC as the one that would be the most inclusive of all women using maternity services. Future research should concentrate on evaluating programs that support PCC in maternity services, and testing/validating this model of care.

Development and initial validation of the Parental PELICAN Questionnaire (PaPEQu) - an instrument to assess parental experiences and needs during their child's end-of-life care.

AIM: To develop and test the Parental PELICAN Questionnaire, an instrument to retrospectively assess parental experiences and needs during their child's end-of-life care. BACKGROUND: To offer appropriate care for dying children, healthcare professionals need to understand the illness experience from the family perspective. A questionnaire specific to the end-of-life experiences and needs of parents losing a child is needed to evaluate the perceived quality of paediatric end-of-life care. DESIGN: This is an instrument development study applying mixed methods based on recommendations for questionnaire design and validation. METHOD: The Parental PELICAN Questionnaire was developed in four phases between August 2012-March 2014: phase 1: item generation; phase 2: validity testing; phase 3: translation; phase 4: pilot testing. Psychometric properties were assessed after applying the Parental PELICAN Questionnaire in a sample of 224 bereaved parents in April 2014. Validity testing covered the evidence based on tests of content, internal structure and relations to other variables. RESULTS: The Parental PELICAN Questionnaire consists of approximately 90 items in four slightly different versions accounting for particularities of the four diagnostic groups. The questionnaire's items were structured according to six quality domains described in the literature. Evidence of initial validity and reliability could be demonstrated with the involvement of healthcare professionals and bereaved parents. CONCLUSION: The Parental PELICAN Questionnaire holds promise as a measure to assess parental experiences and needs and is applicable to a broad range of paediatric specialties and settings. Future validation is needed to evaluate its suitability in different cultures.

Characterisation of anatomical properties of the human basal ganglia using magnetic resonance imaging

The detailed in-vivo characterization of subcortical brain structures is essential not only to understand the basic organizational principles of the healthy brain but also for the study of the involvement of the basal ganglia in brain disorders. The particular tissue properties of basal ganglia - most importantly their high iron content, strongly affect the contrast of magnetic resonance imaging (MRI) images, hampering the accurate automated assessment of these regions. This technical challenge explains the substantial controversy in the literature about the magnitude, directionality and neurobiological interpretation of basal ganglia structural changes estimated from MRI and computational anatomy techniques. My scientific project addresses the pertinent need for accurate automated delineation of basal ganglia using two complementary strategies: ? Empirical testing of the utility of novel imaging protocols to provide superior contrast in the basal ganglia and to quantify brain tissue properties; ? Improvement of the algorithms for the reliable automated detection of basal ganglia and thalamus Previous research demonstrated that MRI protocols based on magnetization transfer (MT) saturation maps provide optimal grey-white matter contrast in subcortical structures compared with the widely used Tl-weighted (Tlw) images (Helms et al., 2009). Under the assumption of a direct impact of brain tissue properties on MR contrast my first study addressed the question of the mechanisms underlying the regional specificities effect of the basal ganglia. I used established whole-brain voxel-based methods to test for grey matter volume differences between MT and Tlw imaging protocols with an emphasis on subcortical structures. I applied a regression model to explain the observed grey matter differences from the regionally specific impact of brain tissue properties on the MR contrast. The results of my first project prompted further methodological developments to create adequate priors for the basal ganglia and thalamus allowing optimal automated delineation of these structures in a probabilistic tissue classification framework. I established a standardized workflow for manual labelling of the basal ganglia, thalamus and cerebellar dentate to create new tissue probability maps from quantitative MR maps featuring optimal grey-white matter contrast in subcortical areas. The validation step of the new tissue priors included a comparison of the classification performance with the existing probability maps. In my third project I continued investigating the factors impacting automated brain tissue classification that result in interpretational shortcomings when using Tlw MRI data in the framework of computational anatomy. While the intensity in Tlw images is predominantly