Aim 2. Is abuse (sexual, emotional and physical) associated with attachment? When testing the relationship between history of abuse and attachment, it was found that experiencing abuse significantly predicted a lower attachment score in the study sample. This finding correlates to research assessing child maltreatment and attachment. Research has shown that exposure to childhood maltreatment disrupts attachment and varies based on type of abuse. Based on the literature review, emotional abuse negatively impacts secure attachments with mothers, fathers and peers, and is the largest predictor of adverse health outcomes among adolescents (Oshri et al., 2015; XxXxxxx and Xxxxxx, 2006; Xxxxxx et al., 2014). Emotional abuse was the most frequent form of abuse reported by the females in this study, which might be a factor in the relationship between abuse and attachment in this sample. Aim 3: Is attachment associated with depressive symptoms and substance use? Findings from this study show that attachment is a statistically significant predictor of depressive symptoms in this sample; each unit increase in attachment resulted in a decrease in depressive symptoms. This relates to the attachment theory, highlighting the importance of secure attachments in potentially protecting against the development of adverse mental health (depression) among this population (Xxxxxx et al., 2009; Xxxxxxx et al., 2010; Xxxxx-Xxxxxx et al., 2011). Attachment however, did not significantly predict substance use in the sample. This finding was surprising given the literature on connectedness as protective factors against substance use (XxXxxx & Xxxxxxxxxxx, 2005; Xxxxxxx et al., 1997). The attachment variable in this study however, is a composite score of questions meassuring secure, dismissing, preoccupied and fearful adolescemt attahment styles that were summed to create an overall attachment score (Xxxxxxxxxxx et al., 1991). These questions do not explicitly measure connectedness at the family, peer or school levels which could be important factors to assess when measuring attachment. This could explain the lack of significant association between these variables. Furthermore, this sample reported low substance use; possible scores ranged from 0-46 with a mean score of 5.35. Females in this study were minors between the ages of 13 and 17, and were thus below the legal drinking age in this country. This could partially contribute to the low substance use score. These factors likely account ...
Aim 2. To perform regression analysis for each of the fire inventories with emergency department visits and acute hospitalizations for asthma and the dependent variable and PM2.5 as the independent variable controlling for temperature, day of the week, and ozone. Hypothesis: XXXX 12 km resolution and XXXX 4 km resolution will produce similar significant results. There are several reasons for making this assertion. Mainly, the theory is that the similar method of detecting wildfires and vegetation layers will play the most important role in determining effect estimates in fire epidemiological models, than the horizontal resolution. We postulate that the horizontal resolution is an unpredictable variable in the fire inventory equations. Xxxxxxxxxx, X., et al 2015 has found that time series analyses produced noticeable biases caused by spatial variability and spatial heterogeneity in outdoor air pollutant concentrations, instrument imprecision, and choice of daily pollutant metric on effect estimates. The study found that the biases were lessened, although not eliminated, by scaling results to interquartile range (IQR) increases in concentration. In Aim 3, we use the increases in IQR values in concentration for PM2.5 for each inventory to obtain the effect estimates. Aim 3: To perform the same regression analysis as that of Aim 2, but using increases in IQR values for analyzing effect estimates. Hypothesis: Scaling the concentrations of PM2.5 to individual IQRs will produce similar patterns of effect estimates across the models as those seen in Aim 2. The reason for this is that horizontal resolutions still remain the same, and the only variable that changed in the epidemiological model is the unit change for the air pollutant concentration.
Aim 2. Describe the psychometric properties of these tools Measures rated using COSMIN guidelines (13/97) Measures that were not rated using COSMIN guidelines (28/97)
Examples of Aim 2 in a sentence
Aim 2 - To work in partnership to reduce the level of crime and disorder so that the community is and feels safer.
Conforms to Council Aim 2 of the Council’s Aims and Targets – “To manage the Council’s finances and assets in a responsible manner”.
Aim 2 “To manage the Council’s finances and assets in a responsible manner”.
Thus, pulse data will be safely stored and will be retrieved when the Pulsewatch is returned for Aim 2 after 14 days.
The activities of Aim 2 (study being conducted in HeH) and Aim 3 (N-of-1 Evaluation) are outlined in separate protocols.
The primary endpoint of Aim 2 is application of a known 100-gene classifier to test whether transcriptomic endotypes exist in pediatric ARDS.
In Aim 2, we will determine genome-wide differential gene expression.
Conforms to Aim 2 of the Council’s Strategic Aims and Targets – “To manage the Council’s finances and assets in a responsible manner”.
User Workgroup| CHIA User Support Website Release Updates ▪ Updates on the production of APCD and Case Mix databases and status of data requests are now posted to CHIA’s website!⮚ Aim #1 is to provide weekly or bi-weekly status update on CHIA data products as they are in development.⮚ Aim #2 is to provide applicants with information about expected fulfillment status for individual data requests.⮚ Request IDs will be communicated to Data Requestors via email.
Cefepime was dosed146 once daily and plasma samples were collected at various times before and after folic acid147 administration to mimic pre and post-AKI conditions.148 Maximum tolerated dosing (Aim 2): Rats received increasing doses of cefepime ranging from149 500-2000 mg/kg/day as IV infusions given over approximately 2 minutes to determine the150 maximum tolerated dose (MTD)24.
More Definitions of Aim 2
Aim 2. Is abuse (sexual, emotional and physical) associated with attachment? A simple linear regression was run between the predictor variable (abuse) and the proposed mediator variable (attachment). A significant association of at least p≤ 0.05 between abuse and attachment was required in order to progress to the next step in the model. Aim 3: Is attachment associated with depressive symptoms and substance abuse? A multivariate regression was conducted between the hypothesized mediator and hypothesized health outcomes while controlling for the predictor variable. A significant association of at least p≤ 0.05 between attachment and depressive symptoms was required in order to progress to the next step in the model. Aim 4: If aims 1-3 are confirmed, does attachment mediate the relationship between abuse and health outcomes? After including the proposed mediator in the multivariate regression model from Aim 3, the association between the proposed predictor and proposed health outcomes were reassessed and compared to the results from Aim 1 to determine full or partial mediation, if any.
Aim 2. Is abuse (sexual, emotional and physical) associated with attachment? Aim 3: Is attachment associated with depressive symptoms and substance use? Aim 4: If aims 1-3 are confirmed, does attachment mediate the relationship between abuse and health outcomes (depressive symptoms and substance abuse)? Figure 1: Proposed Mediation Model
Aim 2. To analyze the needs assessment results and utilize the findings to inform the development of specific strategies to adopt TIC at the Clinic in conjunction with local TIC experts. Aim 3: To disseminate needs assessment findings and resultant TIC strategies to multi-‐level Center stakeholders and local CBOs that provide support for trauma survivors to 1) further tailor and prioritize the selection of TIC strategies to implement at the Center, and 2) to develop an implementation and evaluation plan for future piloting. Methods of Sub-‐study:
Aim 2. To determine the predictors of diarrheal disease in children under five in Somalia Characteristics of children under five with and without diarrhea There were a total of 6,305 total observations with 1,232 of those having parental perception or report of diarrhea in the last two weeks. Table 5 shows the distribution of the variables by children who had diarrhea and those who did not. There was a significant difference in the distribution of gender (p=0.012) and age (p<0.001) in those children who had diarrhea vs. those who did not. There were significantly more children who did not have diarrhea who had ever received a measles/MMR vaccine compared to those who had diarrhea (p<0.001). There was a significant difference in the distribution of children who had ever received any vaccine and who diarrhea and those who did not (p=0.001). The distribution of washing hands before feeding the baby (p<0.001) and washing hands after cleaning the baby’s bottom (p<0.001) were significantly different among children who had diarrhea and those who did not. There was no difference in distribution between children who had diarrhea and those who did not with regards to having ever received OPV, vitamin A, ever refused a vaccine, breastfeeding, measure to prevent water contamination, and treatment of water to make it safe for drinking. Of those children who had diarrhea, 9.1% (7.5, 10.9) were treated with fluid from ORS packet, 9.4% (7.9, 11.1) were given the recommended homemade fluid, and 7.3% (5.9, 8.9) were treated with a pre-packaged ORS fluid (Table 6).
Aim 2. To determine the predictors of diarrheal disease in children under five in Somalia Summary and Conclusions This analysis sought to develop a model to predict diarrheal disease among children under five in Somalia, a country that has faced decades of conflict and has faced many CHE with the aim of giving more focus to what interventions are implemented during a CHE. Our final model showed that age, gender, hand washing after cleaning child’s bottom, and receipt of any vaccine. Similar to this analysis, a number of studies have shown that age and gender are significant predictors of diarrheal disease.45,47,48 We also demonstrate that receipt of any vaccine is also a significant predictor of diarrheal disease in both the unadjusted analysis and in our prediction model. The unadjusted analysis also showed that measles/MMR vaccine and receipt of any vaccine are significantly correlated with a decrease risk of diarrheal disease, pointing to the importance of vaccination not only for disease-specific prevention but secondary disease prevention as well. Both measles and polio vaccines have been shown to decrease morbidity and mortality from diarrhea.76-78 A number of studies revealed that poor maternal care giving behaviors, including hygiene behaviors related to sanitation contribute to the leading killers of children under five, including diarrheal disease.79 Interventions to improve hygiene behaviors were reported to reduce diarrhea morbidity by nearly 45%.80,81 There are also studies done on the risk factors for diarrheal disease that have attempted to describe the relationship between parental behavior and the occurrence of childhood diarrhea. They suggested that maternal practices related to hygiene, breastfeeding, food preparation, and health care are important determinants of diarrheal disease incidence.79 Unlike other studies we did not find that breastfeeding significantly decreased the risk of diarrheal disease in the unadjusted analysis nor did it resulted in any additional precision of the model to predict diarrhea.45,82 Vitamin A supplementation was not significantly associated with diarrheal disease in the unadjusted analysis nor did it result in any additional precision of the model to predict diarrhea which is in contrast to previously published studied showing that vitamin A plays a role in the prevention of diarrheal disease.67,82,83 Neither measures taken to prevent contamination of water or treating water to make it safe for drinking are signi...
Aim 2. To identify overall patient characteristics of CAM users and non-users. Aim 3: To assess communication of CAM usage between the patient and the patient’s oncologist, primary care physician or palliative care team.