Maternal adjustment and maternal attitudes in adolescent and adult pregnant women

Study Objective: This study analyzes differences between adolescent and adult pregnant women and the contribution of maternal age to maternal adjustment and maternal attitudes during pregnancy. Design, Setting, and Participants: A sample of 398 Portuguese pregnant women (111 younger than 19 years) was recruited in a Portuguese Maternity Hospital and completed the Maternal Adjustment and Maternal Attitudes Questionnaire between the 24th and 36th weeks of gestation. Main Outcome Measures: Maternal Adjustment and Maternal Attitudes Questionnaire. Results: Adolescent pregnant women show lower maternal adjustment (poorer body image and worse marital relationship) and poorer maternal attitudes (more negative attitudes to sex) than adult pregnant women. When controlling for socio-demographics, age at pregnancy predicts poorer body image and more negative attitudes to sex, but not a worse marital relationship, more somatic symptoms or negative attitudes to pregnancy and the baby. A worse marital relationship was better predicted by living without the partner, and more somatic symptoms and negative attitudes to pregnancy and the baby was predicted by higher education. Conclusion: Adolescent pregnant women show lower maternal adjustment and poorer maternal attitudes than adult pregnant women according to socio-demographics and unfavorable developmental circumstances.

Breastfeeding and postpartum depression: state of the art review

Objective: To review the literature on the association between breastfeeding and postpartum depression. Sources: A review of literature found on MEDLINE/ PubMed database. Summary of findings: The literature consistently shows that breastfeeding provides a wide range of benefits for both the child and the mother. The psychological benefits for the mother are still in need of further research. Some studies point out that pregnancy depression is one of the factors that may contribute to breastfeeding failure. Others studies also suggest an association between breastfeeding and postpartum depression; the direction of this association is still unclear. Breastfeeding can promote hormonal processes that protect mothers against postpartum depression by attenuating cortisol response to stress. It can also reduce the risk of postpartum depression, by helping the regulation of sleep and wake patterns for mother and child, improving mother’s self efficacy and her emotional involvement with the child, reducing the child’s temperamental difficulties, and promoting a better interaction between mother and child. Conclusions: Studies demonstrate that breastfeeding can protect mothers from postpartum depression, and are starting to clarify which biological and psychological processes may explain this protection. However, there are still equivocal results in the literature that may be explained by the methodological limitations presented by some studies.

Escalas de Avaliação da Interação Mãe-Bebé: versão portuguesa das Interaction Rating Scales

As Escalas de Avaliação da Interação Mãe-Bebé constituem a versão portuguesa das Interaction Rating Scales, propostas por Field (1980), e têm por objetivo avaliar a interação mãe-bebé, aos 3 meses de idade do bebé. As Escalas de Avaliação da Interação Mãe-Bebé foram administradas a 51 díades mãe-bebé aos 3, 6 e 12 meses pós-parto. A versão portuguesa das escalas mostrou elevados índices de consistência interna – Alfa de Cronbach 0,85 (IRSff bebé), 0,91 (IRSff mãe), 0,87 (IRSal bebé), 0,82 (IRSal mãe), assim como elevada fidelidade e validade concorrente e preditiva. As Escalas de Avaliação da Interação Mãe-Bebé assume-se, assim, como um instrumento robusto na avaliação da interação mãe-bebé, na situação de interação face-a-face e na situação de interação alimentar, podendo ser utilizadas em diferentes amostras e contextos, clínicos e de investigação.

Predicting triage waiting time in maternity emergency care by means of data mining

Healthcare organizations often benefit from information technologies as well as embedded decision support systems, which improve the quality of services and help preventing complications and adverse events. In Centro Materno Infantil do Norte (CMIN), the maternal and perinatal care unit of Centro Hospitalar of Oporto (CHP), an intelligent pre-triage system is implemented, aiming to prioritize patients in need of gynaecology and obstetrics care in two classes: urgent and consultation. The system is designed to evade emergency problems such as incorrect triage outcomes and extensive triage waiting times. The current study intends to improve the triage system, and therefore, optimize the patient workflow through the emergency room, by predicting the triage waiting time comprised between the patient triage and their medical admission. For this purpose, data mining (DM) techniques are induced in selected information provided by the information technologies implemented in CMIN. The DM models achieved accuracy values of approximately 94% with a five range target distribution, which not only allow obtaining confident prediction models, but also identify the variables that stand as direct inducers to the triage waiting times.