ABSTRACT
Background: The pandemic has increased the rates of violent behavior towards women by their partners worldwide. Increased time spent living with the abusive partner, working at home and limited social contact combined with socioeconomic characteristics contributed to the increase in this type of violence. Objective: To investigate the impact of pandemic COVID-19 and social determinants of health (SDOH) on the intimate partner violence (IPV) experienced by women from their partners. Methods: A systematic review was conducted to investigate the impact of COVID-19 and social determinants of health on violence experienced by women from their partner(s) as a consequence of incarceration. The Pubmed and Scopus databases were searched during December 2022, using the keywords "intimate partner violence", "women", "COVID-19", "socioeconomic factors", "social determinants of health". Results: Of the 917 studies initially retrieved, 38 studies found an increased prevalence of women's reported violence by their partners, 10 found a low prevalence, and 9 found no difference in prevalence before and during restraint. The most common forms of violence were psychological, physical and sexual. In 30 studies, social determinants such as socioeconomic level, education and living conditions were found to be associated with the prevalence of violence. Conclusion: There was an increase in violence against women during quarantine which was associated with the effect of social determinants. However, due to research limitations of the studies, additional research is needed to draw firm conclusions that can be generalized to the population.
ABSTRACT
Relations between mind-mindedness (assessed using the describe-your-child interview) and stress were investigated in parents of children with developmental disorders (ADHD, n = 51, ASD, n = 23, Down's Syndrome, n = 38, and 22q11.2 Deletion Syndrome, 22q11.2DS, n = 32) and typically-developing children (n = 89). Mind-mindedness did not differ across diagnostic groups, and mind-mindedness predicted parenting stress across groups. Parenting stress was lowest in the typically-developing and Down's Syndrome groups. Across all groups, mind-minded and positive descriptions predicted lower parenting stress, and negative descriptions predicted higher stress. In the developmental disorder groups, describing the children with reference to their disorder was negatively correlated with mind-mindedness. Results are discussed with regard to interventions for families where children have developmental disorders.
Subject(s)
Developmental Disabilities/psychology , Mindfulness/methods , Parenting/psychology , Parents/psychology , Stress, Psychological/psychology , Thinking/physiology , Adolescent , Adult , Child , Child, Preschool , Developmental Disabilities/diagnosis , Female , Humans , Male , Stress, Psychological/diagnosisABSTRACT
Tree bole volumes of 89 Scots pine (Pinus sylvestris L.), 96 Brutian pine (Pinus brutia Ten.), 107 Cilicica fir (Abies cilicica Carr.) and 67 Cedar of Lebanon (Cedrus libani A. Rich.) trees were estimated using Artificial Neural Network (ANN) models. Neural networks offer a number of advantages including the ability to implicitly detect complex nonlinear relationships between input and output variables, which is very helpful in tree volume modeling. Two different neural network architectures were used and produced the Back propagation (BPANN) and the Cascade Correlation (CCANN) Artificial Neural Network models. In addition, tree bole volume estimates were compared to other established tree bole volume estimation techniques including the centroid method, taper equations, and existing standard volume tables. An overview of the features of ANNs and traditional methods is presented and the advantages and limitations of each one of them are discussed. For validation purposes, actual volumes were determined by aggregating the volumes of measured short sections (average 1 meter) of the tree bole using Smalian's formula. The results reported in this research suggest that the selected cascade correlation artificial neural network (CCANN) models are reliable for estimating the tree bole volume of the four examined tree species since they gave unbiased results and were superior to almost all methods in terms of error (%) expressed as the mean of the percentage errors.
