Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

Moderators of the Relationship between Family Caregiver Proxy-Ratings and Person with Dementia Self-Ratings of Quality of Life

As the dementia spectrum lacks any viable cure, quality of life is typically regarded as an essential measure of assessing the clinical course and evaluating interventions. With caregivers typically providing this rating to health professionals, the literature has noted inconsistencies between caregiver and person with dementia (PwD) ratings of quality of life and suggested several factors may moderate the rating relationship. To investigate this, an intraclass correlation coefficient was calculated to observe rating agreement and moderator regression analysis was conducted to explore potential moderators. Potential moderators of caregiver burden, caregiver age, caregiver income, PwD IADLs/ADLs, PwD education, PwD cognitive impairment, PwD depressive symptom severity, PwD behavioural symptom severity, as well as relationship between caregiver and PwD. Utilizing secondary data from 107 recruited dyads, analyses conducted found fair agreement between caregivers and those with dementia while none of the hypothesized factors were found to moderate the rating relationship.

The association between maternity insurance, residence status and selected perinatal outcomes among Chinese women

Objective: To investigate the impact of maternity insurance and maternal residence on birth outcomes in a Chinese population. Methods: Secondary data was analyzed from a perinatal cohort study conducted in the Beichen District of the city of Tianjin, China. A total of 2364 pregnant women participated in this study at approximately 12-week gestation upon registration for receiving prenatal care services. After accounting for missing information for relevant variables, a total of 2309 women with single birth were included in this analysis. Results: A total of 1190 (51.5%) women reported having maternity insurance, and 629 (27.2%) were rural residents. The abnormal birth outcomes were small for gestational age (SGA, n=217 (9.4%)), large for gestational age (LGA, n=248 (10.7%)), birth defect (n=48 (2.1%)) including congenital heart defect (n=32 (1.4%)). In urban areas, having maternal insurance increased the odds of SGA infants (1.32, 95%CI (0.85, 2.04), NS), but decreased the odds of LGA infants (0.92, 95%CI (0.62, 1.36), NS); also decreased the odds of birth defect (0.93, 95%CI (0.37, 2.33), NS), and congenital heart defect (0.65, 95%CI (0.21, 1.99), NS) after adjustment for covariates. In contrast to urban areas, having maternal insurance in rural areas reduced the odds of SGA infants (0.60, 95%CI (0.13, 2.73), NS); but increased the odds of LGA infants (2.16, 95%CI (0.92, 5.04), NS), birth defects (2.48, 95% CI (0.70, 8.80), NS), and congenital heart defect (2.18, 95%CI (0.48, 10.00), NS) after adjustment for the same covariates. Similar results were obtained from Bootstrap methods except that the odds ratio of LGA infants in rural areas for maternal insurance was significant (95%CI (1.13, 4.37)); urban residence was significantly related with lower odds of birth defect (95%CI (0.23, 0.89)) and congenital heart defect (95%CI (0.19, 0.91)). Conclusions: whether having maternal insurance did have an impact on perinatal outcomes, but the impact of maternal insurance on the perinatal outcomes showed differently between women with urban residence and women with rural residence status. However, it is not clear what are the reason causing the observed differences. Thus, more studies are needed.