7 research outputs found
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The role of posttraumatic stress and depression symptoms in mother-infant bonding
Background: There is some evidence posttraumatic stress disorder (PTSD) following childbirth may impact on the mother-infant bond. However, the evidence is inconsistent over whether PTSD or co-morbid depressive symptoms are primarily related to impaired bonding. This study therefore aimed to examine the relationship between PTSD symptoms, depressive symptoms and mother-infant bonding.
Methods: A cross-sectional online study included 603 mothers of infants aged 1–12 months. Measures were taken of PTSD (City Birth Trauma Scale, Ayers et al., 2018) which has two subscales of birth-related PTSD symptoms and general PTSD symptoms; depression (Edinburgh Postnatal Depression Scale, Cox et al., 1987) and mother-infant bonding (Postpartum Bonding Questionnaire, Brockington et al., 2001).
Results: Impaired bonding was related to both dimensions of PTSD symptoms and depressive symptoms in bivariate analysis. Path analysis testing the model of whether depressive symptoms mediated the effect of PTSD symptoms on mother-infant bonding found a differential role of birth-related and general PTSD symptoms. Birth-related PTSD symptoms did not have any effect on bonding or depressive symptoms. In contrast, general PTSD symptoms had a direct effect on bonding and an indirect effect on bonding via depressive symptoms.
Limitations: Self-report measures of PTSD and depression symptoms were used.
Conclusions: Further research regarding different aspects of postpartum PTSD, depression and other disorders in the context of mother-infant bonding are needed. Future preventive programs should focus on diminishing symptoms of postpartum PTSD and depression so that the mother-infant bonding remains optimal
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Measuring and conceptualizing PTSD following childbirth: Validation of the City Birth Trauma Scale
OBJECTIVE: City Birth Trauma Scale is a recently developed scale specifically designed for evaluation of posttraumatic stress disorder (PTSD) following childbirth based on the DSM-5 criteria (Ayers, Wright, & Thornton, 2018). Previous studies showed a two-factor structure of PTSD symptoms in postpartum women; however, more complex models were not tested. This study aimed to validate the Croatian version of the City Birth Trauma Scale and determine the latent factor structure of postpartum PTSD.
METHOD: In a cross-sectional study, 603 women completed online questionnaires comprising the City Birth Trauma Scale, Impact of Event Scale-Revised (IES-R), Edinburgh Postnatal Depression Scale (EPDS), and the anxiety subscale from the Depression, Anxiety, and Stress Scale (DASS-21).
RESULTS: Confirmatory factor analysis confirmed the bifactor model of birth-related symptoms and general symptoms had an excellent fit to the data. Both subscales and the total scale showed high internal consistency (α = .92). Convergent and divergent validity testing showed high validity, especially for birth-related symptoms. Discriminant validity was confirmed with primiparous women and women who gave birth by instrumental vaginal delivery and emergency caesarean section having significantly higher scores on birth-related symptoms, but not on general symptoms, suggesting high discriminant validity of the birth-related symptoms subscale.
CONCLUSIONS: The City Birth Trauma Scale is a reliable and valid measure. Both total scale score and subscale scores can be calculated. It is highly recommended for use in postpartum population. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
Cultural inter-population differences do not reflect biological distances: an example of interdisciplinary analysis of populations from Eastern Adriatic coast
Aim To compare the population group from the Šopot
graveyard with population groups from traditional Croatian
medieval graveyards by using anthropological, craniometrics,
and mitochondrial (mtDNA) analysis and to examine
if the cultural differences between population groups
reflect biological differences.
Methods We determined sex, age at death, pathological,
and traumatic changes of skeletal remains from the Šopot
graveyard and compared them with a cumulative medieval
sample from the same region. We also performed
principal component analysis to compare skeletal remains
from Šopot with those from Ostrovica and other Central
European samples according to 8 cranial measurements.
Finally, we compared 46 skeletons from Šopot with medieval
(Ostrovica) and contemporary populations using
mDNA haplogroup profiling.
Results The remains from Šopot were similar to the cumulative
sample in lifestyle and quality of life markers. Principal
component analysis showed that they were closely
related to Eastern Adriatic coast sites (including Ostrovica
and Šopot) in terms of cranial morphology, indicating similar
biological makeup. According to mDNA testing, Šopot
population showed no significant differences in the haplogroup
prevalence from either medieval or contemporary
populations.
Conclusion This study shows that the Šopot population
does not significantly differ from other medieval populations
from this area. Besides similar quality of life markers,
these populations also had similar biological markers. Substantial
archeological differences can therefore be attributed
to apparent cultural influences, which in this case do
not reflect biological differences
Efficiency of the Adjusted Binary Classification (ABC) Approach in Osteometric Sex Estimation: A Comparative Study of Different Linear Machine Learning Algorithms and Training Sample Sizes
The adjusted binary classification (ABC) approach was proposed to assure that the binary classification model reaches a particular accuracy level. The present study evaluated the ABC for osteometric sex classification using multiple machine learning (ML) techniques: linear discriminant analysis (LDA), boosted generalized linear model (GLMB), support vector machine (SVM), and logistic regression (LR). We used 13 femoral measurements of 300 individuals from a modern Turkish population sample and split data into two sets: training (n = 240) and testing (n = 60). Then, the five best-performing measurements were selected for training univariate models, while pools of these variables were used for the multivariable models. ML classifier type did not affect the performance of unadjusted models. The accuracy of univariate models was 82–87%, while that of multivariate models was 89–90%. After applying ABC to the crossvalidation set, the accuracy and the positive and negative predictive values for uni- and multivariate models were ≥95%. Sex could be estimated for 28–75% of individuals using univariate models but with an obvious sexing bias, likely caused by different degrees of sexual dimorphism and between-group overlap. However, using multivariate models, we minimized the bias and properly classified 81–87% of individuals. A similar performance was also noted in the testing sample (except for FEB), with accuracies of 96–100%, and a proportion of classified individuals between 30% and 82% in univariate models, and between 90% and 91% in multivariate models. When considering different training sample sizes, we demonstrated that LR was the most sensitive with limited sample sizes (n < 150), while GLMB was the most stable classifier
A Forensic Genomics Approach for the Identification of Sister Marija Crucifiksa Kozulić
Sister Marija Krucifiksa Kozulić (1852–1922) was a Croatian nun who is in consideration for beatification by the Vatican, which is facilitated by the identification of her 20th-century remains. Sister Marija was buried in a tomb in Rijeka, Croatia, along with other nuns including her biological sister, Tereza Kozulić (1861–1933). When the remains were exhumed in 2011, they were found in a deteriorated state and commingled with several other sets of remains. Thus, mitochondrial genome sequencing of the long bones was performed to sort the remains by mitochondrial haplotype. Two similar but unique haplotypes belonging to haplogroup H1bu were identified, and samples from these bones were subjected to autosomal short tandem repeat (STR) and single nucleotide polymorphism (SNP) sequencing. Although only partial profiles were obtained, the data were sufficient for kinship analysis with the profile of a paternal niece of Sister Marija (Fides Kozulić). The data indicate that it is 574,195-fold more likely that the two sets of skeletal remains represent 2nd-degree relatives of Fides than sisters who are unrelated to Fides. Although it is impossible to discern which set of remains belongs to Marija and which belongs to Tereza, forensic genomics methods have enabled identification of the sisters