<p> In the United States, 397,000 children received foster care services in 2012. Some states successfully achieved permanent homes for children with diagnosed disabilities who exited care while others were less successful. Using change theory and social ecological theory as the foundations, the purpose of this study was to determine the impact that diagnosed disabilities had on permanent home placements among Pennsylvania&rsquo;s foster care children who were discharged and were between ages of 0 to 6 years in 2012. Hernandez&rsquo;s and Hodges&rsquo;s theory of change was used to evaluate the 1982 standards that license foster care agencies, while Stokol&rsquo;s ecological theory provided the framework to assess whether there were measurable increases in child welfare outcomes for permanent placements among children with diagnosed disabilities. Following a retrospective, nonexperimental, quantitative design, data were acquired from a purposive sample of 344 archived foster care files across the state. These data were analyzed using bivariate correlation procedures to evaluate the strength of the relationship between medically diagnosed conditions and permanent placement. The findings indicated a statistically significant association between medically diagnosed conditions and permanent placements (p=0.01). Additionally, length of stay in care was also found to be statistically associated with permanent placement (p=0.019). The theoretical constructs evaluation with a theory of change found the 1982 standards were outdated to authorize the licensing of foster care agencies; the social ecological theory identified evidence for change to achieve the intended goal. Findings of this study may provide guidance to policymakers in term of improving standards related to oversight and licensing foster care agencies in order to better support permanent placement of children with disabilities.</p><p>

abstract: Statistical mediation analysis has been widely used in the social sciences in order to examine the indirect effects of an independent variable on a dependent variable. The statistical properties of the single mediator model with manifest and latent variables have been studied using simulation studies. However, the single mediator model with latent variables in the Bayesian framework with various accurate and inaccurate priors for structural and measurement model parameters has yet to be evaluated in a statistical simulation. This dissertation outlines the steps in the estimation of a single mediator model with latent variables as a Bayesian structural equation model (SEM). A Monte Carlo study is carried out in order to examine the statistical properties of point and interval summaries for the mediated effect in the Bayesian latent variable single mediator model with prior distributions with varying degrees of accuracy and informativeness. Bayesian methods with diffuse priors have equally good statistical properties as Maximum Likelihood (ML) and the distribution of the product. With accurate informative priors Bayesian methods can increase power up to 25% and decrease interval width up to 24%. With inaccurate informative priors the point summaries of the mediated effect are more biased than ML estimates, and the bias is higher if the inaccuracy occurs in priors for structural parameters than in priors for measurement model parameters. Findings from the Monte Carlo study are generalizable to Bayesian analyses with priors of the same distributional forms that have comparable amounts of (in)accuracy and informativeness to priors evaluated in the Monte Carlo study. / Dissertation/Thesis / Doctoral Dissertation Psychology 2017

<p> This study explored the perceived effects of microaggressions on Peer Support Specialists (PSS). Although some research exists on the perceived effects of microaggression on individuals with lived experience of mental illness, known culturally as a marginalized group (Sue, 2010); none exists on PSS. The mental health movement began in the early 1900&rsquo;s, which later evolved into mental health recovery and psychiatric rehabilitation. This movement brought forth the development of psychopharmacology, supportive services, and mental health programs. During the early phases of mental health recovery and treatment, individuals with lived experience of mental illness were utilized as peers and eventually as peer support specialists, or liaisons. Peer support specialists (PSS) provide an invaluable resource to individuals struggling with mental illness, as the literature supports. Despite strides towards societal acceptance, individuals with mental illness, continue to experience discrimination, stigma and microaggressions. Research on historical trauma, although beyond the scope of this research will be reviewed to provide an understanding of how microaggressions are passed on and additionally a narrative review of Adverse Childhood Experiences (ACEs) and the Connor-Davidson Resilience Scale (CD-RISC-25), aimed to contribute to the understanding of the history of trauma, engagement, and recovery. This research qualitatively explored the experience of sixteen participants who are PSS and in active recovery of mental illness. Semi structured focus group interviews revealed five major themes: Category 1&ndash;Microinvalidation: (1.1) Invalidation; (1.2) Second Class Citizen; Category 2&ndash;Resilience: (2.1) Advocacy; (2.2) Belonginess; (2.3) Perseverance.</p><p>

abstract: Random Forests is a statistical learning method which has been proposed for propensity score estimation models that involve complex interactions, nonlinear relationships, or both of the covariates. In this dissertation I conducted a simulation study to examine the effects of three Random Forests model specifications in propensity score analysis. The results suggested that, depending on the nature of data, optimal specification of (1) decision rules to select the covariate and its split value in a Classification Tree, (2) the number of covariates randomly sampled for selection, and (3) methods of estimating Random Forests propensity scores could potentially produce an unbiased average treatment effect estimate after propensity scores weighting by the odds adjustment. Compared to the logistic regression estimation model using the true propensity score model, Random Forests had an additional advantage in producing unbiased estimated standard error and correct statistical inference of the average treatment effect. The relationship between the balance on the covariates' means and the bias of average treatment effect estimate was examined both within and between conditions of the simulation. Within conditions, across repeated samples there was no noticeable correlation between the covariates' mean differences and the magnitude of bias of average treatment effect estimate for the covariates that were imbalanced before adjustment. Between conditions, small mean differences of covariates after propensity score adjustment were not sensitive enough to identify the optimal Random Forests model specification for propensity score analysis. / Dissertation/Thesis / Ph.D. Psychology 2013

abstract: Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not in statistical analyses. Bayesian methods incorporate prior knowledge into the statistical analysis in the form of a prior distribution. When prior information about a relationship is available, the estimates obtained could differ drastically depending on the choice of Bayesian or frequentist method. Study 1 in this project compared the performance of five methods for obtaining interval estimates of the mediated effect in terms of coverage, Type I error rate, empirical power, interval imbalance, and interval width at N = 20, 40, 60, 100 and 500. In Study 1, Bayesian methods with informative prior distributions performed almost identically to Bayesian methods with diffuse prior distributions, and had more power than normal theory confidence limits, lower Type I error rates than the percentile bootstrap, and coverage, interval width, and imbalance comparable to normal theory, percentile bootstrap, and the bias-corrected bootstrap confidence limits. Study 2 evaluated if a Bayesian method with true parameter values as prior information outperforms the other methods. The findings indicate that with true values of parameters as the prior information, Bayesian credibility intervals with informative prior distributions have more power, less imbalance, and narrower intervals than Bayesian credibility intervals with diffuse prior distributions, normal theory, percentile bootstrap, and bias-corrected bootstrap confidence limits. Study 3 examined how much power increases when increasing the precision of the prior distribution by a factor of ten for either the action or the conceptual path in mediation analysis. Power generally increases with increases in precision but there are many sample size and parameter value combinations where precision increases by a factor of 10 do not lead to substantial increases in power. / Dissertation/Thesis / Masters Thesis Psychology 2014

<p> Alcoholism and alcohol use disorders are a major problem worldwide. Excessive alcohol consumption has been associated with cognitive impairment not only in drinkers but also in their offspring. Previous clinical reports have suggested that inherited drug use behavior in individuals, including the overall amount of alcohol consumed, originates from parents who engage in the consumption of alcohol both during and prior to conception. For example, mothers exposed to alcohol during pregnancy have been shown to produce offspring with neurodevelopmental, physiological, and behavioral deficits, in rodents. Additionally, several studies now support the idea that fathers exposed to alcohol prior to mating produce male offspring with developmental, physiological, and cognitive deficits as well. With this said, alcohol exposed fathers appear to pass different phenotypes to their sons than they do their daughters. To date, little research has been dedicated to examining cognitive deficits associated with paternal alcohol exposure or the volume of alcohol intake in daughters of male alcoholics. The purpose of this set of experiments is to explore possible changes in cognitive function and alcohol acceptance in both male and female offspring of alcohol-exposed fathers. Adult male rats were exposed to a repeated binge dose of alcohol and later mated with non-manipulated females. Offspring of exposed fathers were assessed for levels of alcohol consumption via Intraoral Cannulation, followed by a series of cognitive function tests via T-maze task performance. Accuracy percentage within the T- maze and volume of alcohol accepted were compared and analyzed using an ANOVA. Our findings suggest that paternal binge doses of ethanol exposure prior to breeding results in offspring that consume significantly more ethanol than controls, exhibit greater latency time to reach criterion in a T-maze, and having significantly fewer percent correct responses in T-maze task performance when including all trials. The results presented here add to the growing body of literature aimed at understanding the consequences of paternal pre-conception ethanol exposure and the effects on subsequent generations.</p><p>

<p> Psychotropic medications rank among the most widely prescribed, largest-selling, and fastest-growing classes of drugs in the U.S. today. Largely attributed to the role of primary care providers in mental health care and the use of psychotropic medications for non-psychiatric conditions, the prevalence of psychotropic medication prescribing is a problem due to side effects, drug-to-drug interactions, and withdrawal effects. Previous research has not reliably explained why practitioners vary in prescribing behavior. This non-experimental cross-sectional quantitative research investigation compared the psychotropic medication prescribing behavior of primary care prescribers from the perspective of the theoretical domains framework (TDF), a validated theoretical framework for identifying factors influencing clinical behavior. The inquiry was guided by four research questions that explored prescribing behavior between primary care physicians (MDs, DOs), physician assistants (PAs), and nurse practitioners (NPs), between high and low prescribers, among high prescribers, and among low prescribers. The Determinants of Implementation Behavior Questionnaire: Psychotropic Medication Prescribing Behavior (DIBQ: PMPB), a unique psychotropic medication prescribing behavior version of the TDF-based Determinants of Implementation Behavior Questionnaire (DIBQ) template was administered to 49 Pennsylvania primary care MDs, DOs, PAs, and NPs. Due to low sample size, the groups were aggregated and compared between MDs/DOs and PAs/NPs. Data were analyzed with the non-parametric Kruskal-Wallis H test. Results revealed that mean ranks were significantly different only among low prescribers in which MDs/DOs were significantly higher than PAs/NPs in Socio-political context and Innovation strategy. However, PAs/NPs were higher than MDs/DOs in Social/professional role and identity and Intentions. Findings suggest that differences may be related to division of labor, primary care setting, and age and gender of provider. MDs/DOs may focus more on protocol, organization, and practice-based aspects of running a business, whereas PAs/NPs may have a holistic mindset that is more flexible, accommodating, and sensitive to the patient. These factors should be thoroughly investigated in randomized controlled trials to more fully understand a provider&rsquo;s motivation and pattern for prescribing psychotropic medications, particularly in situations where safer evidence-based treatments exist.</p><p>

Three decision consistency and accuracy (DC/DA) methods, the Livingston and Lewis (LL) method, LEE method, and the Hambleton and Han (HH) method, were evaluated. The purposes of the study were: (1) to evaluate the accuracy and robustness of these methods, especially when their assumptions were not well satisfied, (2) to investigate the “true” DC/DA indices in various conditions, and (3) to assess the impact of choice of reliability estimate on the LL method. Four simulation studies were conducted: Study 1 looked at various test lengths. Study 2 focused on local item dependency (LID). Study 3 checked the consequences of IRT model-data misfit and Study 4 checked the impact of using different scoring metrics. Finally, a real data study was conducted where no advantages were given to any models or assumptions. The results showed that the factors of LID and model misfit had a negative impact on “true” DA index, and made all selected methods over-estimate DA index. On the contrary, the DC estimates had minimal impacts from the above factors, although the LL method had poorer estimates in short tests and the LEE and HH methods were less robust to tests with a high level of LID. Comparing the selected methods, the LEE and HH methods had nearly identical results across all conditions, while the HH method had more flexibility in complex scoring metrics. The LL method was found sensitive to the choice of test reliability estimate. The LL method with Cronbach’s alpha consistently underestimated DC estimates while LL with stratified alpha functioned noticeably better with smaller bias and more robustness in various conditions. Lastly it is hoped to make the software be available soon to permit the wider use of the HH method. The other methods in the study are already well supported by easy to use software.

Mutual influence within relationships is theorized as central to human development and functioning across the lifespan. Multiple theories posit a process of progressive bidirectional influence that results in greater similarity between dyad members over time, termed attunement. Yet attunement processes, from dyadic synchrony in healthy child development to partner influence within romantic relationships, are difficult to measure and model. One difficulty is that capturing information from both members of a relationship pair, or dyad, requires statistical modeling that appropriately accounts for the interdependence between them. The present study addressed this issue by putting forward a framework for modeling attunement processes between relationship members over time, and applied this framework to two distinct studies. The studies both tested whether attunement occurred in two large-scale dyadic samples, the first in a sample of newly-married couples, the second in a sample of psychotherapy dyads. Attunement was modeled both as an outcome (in Study 1) and a predictor (in Study 2), providing interested researchers with an analytic framework for using measures of dyadic attunement as either an independent or a dependent variable. Findings from Study 1 showed significant attunement in the stress hormone cortisol over the early years of marriage in newlywed couples. This finding is suggestive of bidirectional spousal influence over a longer term than previously tested, as other studies have only inferred attunement processes by finding covariation in spousal cortisol over a matter of days. This study also disaggregated cortisol fluctuations into discrete parts, allowing for tests of spousal attunement not only in cortisol level, but also in physiological response to a stressor. Findings from Study 2 also found significant attunement processes within patient-therapist dyads. Specifically, patient-therapist alliance attunement over time was predictive of better outcome for patients receiving psychotherapy for chronic depression. A major contribution of these studies was that they modeled theorized relationship processes at the level of the dyad, rather than emphasizing individual outcomes. This dyadic-level modeling of bidirectional influence in turn related to outcomes relevant to psychological health, which may have been obscured or undetectable with other modeling techniques.

Attention-deficit/hyperactivity disorder (ADHD) diagnosed during childhood can continue into adulthood, but most research on the topic has been done on children and adolescents. This research focus has thus often left out the population of adults with this disorder. In particular, there is little research on the role that self-regulation plays in the lives of adults on several life domains, especially in the workplace. The purpose of this qualitative, phenomenological study was to understand the role that self-regulation plays in the occupational functioning of adults with ADHD. Self-regulation theory provided the tenets that were used to examine how adults with ADHD self-regulate their emotions in the occupational setting. A modified version of the Stevick-Colaizzi-Keen method of analysis of phenomenological data was used to analyze transcripts of participant interviews with 11 Adults who have an ADHD diagnosis and at least one year of work experience. The results showed that many of the participants had difficulty with self-regulation, particularly with effectively managing the situation by considering the long-term consequences for their actions. The study has several social change implications. First, the findings might add to scholarly literature regarding the later-life impact of adult ADHD, enabling such changes as additional treatment of ADHD in adulthood and potential accommodations, support, and training on the job. Given the centrality of employment issues in the life of an adult, the findings may provide direction and insight to employers in managing employees with ADHD, making them more productive members of the workplace.