Dataset Information

Information on, knowledge and utilisation of support services during pregnancy and after childbirth: cross-sectional analyses of predictors using data from the KUNO-Kids health study.

ABSTRACT:

Objectives

To investigate mothers' knowledge and utilisation of antenatal and perinatal support services as well as predictors of knowledge and service utilisation.

Design

Cross-sectional study.

Setting

Prospective birth cohort in Regensburg, Eastern Bavaria, Germany.

Participants

2455 mothers after delivery.

Outcome measures

Participants' knowledge of distinct antenatal and perinatal support services (poor vs good, defined by median split). Participants' use of antenatal services provided by midwife (yes, no) and of any other antenatal support services (yes, no).

Results

The vast majority of mothers knew at least some support services. Two-thirds of women (68.4%) reported to have used the services provided by midwives. 23.6% of women reported to have used at least one of the other antenatal services. Good knowledge of services was associated with higher education (OR 1.37, 95% CI 1.13 to 1.67), no migration background (OR 2.26, 95% CI 1.76 to 2.90), better health literacy (OR 1.04, 95% CI 1.03 to 1.06), while being primiparous (OR 0.72, 95% CI 0.60 to 0.86) and being unmarried/living with a partner (OR 0.71, 95% CI 0.57 to 0.89) reduced the chance. Predictors of service utilisation differed with regard to the services considered.

Conclusions

Overall, mothers had a good level of knowledge of antenatal and perinatal support services. However, we found that some groups of women were less well informed. This inequality in social predictors of knowledge of services was also partly reflected in differences in service utilisation during pregnancy.

SUBMITTER: Brandstetter S

PROVIDER: S-EPMC7592309 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Information on, knowledge and utilisation of support services during pregnancy and after childbirth: cross-sectional analyses of predictors using data from the KUNO-Kids health study.

Brandstetter Susanne S Rothfuß David D Seelbach-Göbel Birgit B Melter Michael M Kabesch Michael M Apfelbacher Christian C

BMJ open 20201026 10

<h4>Objectives</h4>To investigate mothers' knowledge and utilisation of antenatal and perinatal support services as well as predictors of knowledge and service utilisation.<h4>Design</h4>Cross-sectional study.<h4>Setting</h4>Prospective birth cohort in Regensburg, Eastern Bavaria, Germany.<h4>Participants</h4>2455 mothers after delivery.<h4>Outcome measures</h4>Participants' knowledge of distinct antenatal and perinatal support services (poor vs good, defined by median split). Participants' use ...[more]

PMID: 33109648

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Project description:Historically, women have been attended and supported by other women during labour. However, in hospitals worldwide, continuous support during labour has become the exception rather than the routine.Primary: to assess the effects of continuous, one-to-one intrapartum support compared with usual care. Secondary: to determine whether the effects of continuous support are influenced by: (1) routine practices and policies; (2) the provider's relationship to the hospital and to the woman; and (3) timing of onset.We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 June 2012).All published and unpublished randomised controlled trials comparing continuous support during labour with usual care.We used standard methods of The Cochrane Collaboration Pregnancy and Childbirth Group. Two review authors independently evaluated methodological quality and extracted the data. We sought additional information from the trial authors. We used random-effects analyses for comparisons in which high heterogeneity was present, and we reported results using the average risk ratio (RR) for categorical data and mean difference (MD) for continuous data.Twenty-two trials involving 15,288 women met inclusion criteria and provided usable outcome data. Results are of random-effects analyses, unless otherwise noted. Women allocated to continuous support were more likely to have a spontaneous vaginal birth (RR 1.08, 95% confidence interval (CI) 1.04 to 1.12) and less likely to have intrapartum analgesia (RR 0.90, 95% CI 0.84 to 0.96) or to report dissatisfaction (RR 0.69, 95% CI 0.59 to 0.79). In addition, their labours were shorter (MD -0.58 hours, 95% CI -0.85 to -0.31), they were less likely to have a caesarean (RR 0.78, 95% CI 0.67 to 0.91) or instrumental vaginal birth (fixed-effect, RR 0.90, 95% CI 0.85 to 0.96), regional analgesia (RR 0.93, 95% CI 0.88 to 0.99), or a baby with a low five-minute Apgar score (fixed-effect, RR 0.69, 95% CI 0.50 to 0.95). There was no apparent impact on other intrapartum interventions, maternal or neonatal complications, or breastfeeding. Subgroup analyses suggested that continuous support was most effective when the provider was neither part of the hospital staff nor the woman's social network, and in settings in which epidural analgesia was not routinely available. No conclusions could be drawn about the timing of onset of continuous support.Continuous support during labour has clinically meaningful benefits for women and infants and no known harm. All women should have support throughout labour and birth.

Project description:ObjectivesDigital support services may provide informal caregivers with remote access to information and training about care issues. However, there is limited specific data on how factors such as demographics, socioeconomic resources and the caregiving context may influence caregivers' use of digital support services. The aim of this study is to identify associations between informal caregiver's characteristics and the use of the internet to access digital support services in two countries: Italy and Sweden.Setting and participantsA sample of 663 respondents who have access to the internet participated in a cross-sectional survey by completing the online questionnaire. Respondents were recruited by the Italian National Institute of Health and Science on Ageing and the Swedish Family Care Competence Centre.Primary and secondary outcome measuresLogistic regression analyses were performed to assess predictors of caregivers' frequent use of the internet to access digital support services.ResultsEducational attainment (OR 3.649, 95% CI 1.424 to 9.350, p=0.007), hours per week spent caring (OR 2.928, 95% CI 1.481 to 5.791, p=0.002), total household income (OR 0.378, 95% CI 0.149 to 0.957, p=0.040), care recipient relationship to the caregiver (OR 2.895, 95% CI 1.037 to 8.083, p=0.042) and gender of care recipient (OR 0.575, 95% CI 0.356 to 0.928, p=0.023) were significant predictors in the multivariate analysis for the Italian caregivers group. Hours per week spent caring (OR 2.401, 95% CI 1.105 to 5.218, p=0.027) and age of caregiver (OR 2.237, 95% CI 1.150 to 4.352, p=0.018) were significant predictors in the multivariate analysis for the Swedish caregivers group.ConclusionsDigital support services could be important tools to empower informal caregivers. When it comes to policy and practice in relation to caregivers, similarly to other broad vulnerable groups, there is no 'one-size-fits-all' approach, and it is therefore important to consider the specific characteristics and needs of both caregivers and care recipients.

Project description:BACKGROUND:We introduce the decision support system for Protein (Structure) Comparison, Knowledge, Similarity and Information (ProCKSI). ProCKSI integrates various protein similarity measures through an easy to use interface that allows the comparison of multiple proteins simultaneously. It employs the Universal Similarity Metric (USM), the Maximum Contact Map Overlap (MaxCMO) of protein structures and other external methods such as the DaliLite and the TM-align methods, the Combinatorial Extension (CE) of the optimal path, and the FAST Align and Search Tool (FAST). Additionally, ProCKSI allows the user to upload a user-defined similarity matrix supplementing the methods mentioned, and computes a similarity consensus in order to provide a rich, integrated, multicriteria view of large datasets of protein structures. RESULTS:We present ProCKSI's architecture and workflow describing its intuitive user interface, and show its potential on three distinct test-cases. In the first case, ProCKSI is used to evaluate the results of a previous CASP competition, assessing the similarity of proposed models for given targets where the structures could have a large deviation from one another. To perform this type of comparison reliably, we introduce a new consensus method. The second study deals with the verification of a classification scheme for protein kinases, originally derived by sequence comparison by Hanks and Hunter, but here we use a consensus similarity measure based on structures. In the third experiment using the Rost and Sander dataset (RS126), we investigate how a combination of different sets of similarity measures influences the quality and performance of ProCKSI's new consensus measure. ProCKSI performs well with all three datasets, showing its potential for complex, simultaneous multi-method assessment of structural similarity in large protein datasets. Furthermore, combining different similarity measures is usually more robust than relying on one single, unique measure. CONCLUSION:Based on a diverse set of similarity measures, ProCKSI computes a consensus similarity profile for the entire protein set. All results can be clustered, visualised, analysed and easily compared with each other through a simple and intuitive interface.ProCKSI is publicly available at http://www.procksi.net for academic and non-commercial use.

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Dataset Information

Information on, knowledge and utilisation of support services during pregnancy and after childbirth: cross-sectional analyses of predictors using data from the KUNO-Kids health study.

Objectives

Design

Setting

Participants

Outcome measures

Results

Conclusions

Publications

Information on, knowledge and utilisation of support services during pregnancy and after childbirth: cross-sectional analyses of predictors using data from the KUNO-Kids health study.

Similar Datasets

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