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A huge portion of what we know about how humans develop, learn, behave, and interact is based on survey data. Researchers use longitudinal growth modeling to understand the development of students on psychological and social-emotional learning constructs across elementary and middle school. In these designs, students are typically administered a consistent set of self-report survey items across multiple school years, and growth is measured either based on sum scores or scale scores produced based on item response theory (IRT) methods. Although there is great deal of guidance on scaling and linking IRT-based large-scale educational assessment to facilitate the estimation of examinee growth, little of this expertise is brought to bear in the scaling of psychological and social-emotional constructs. Through a series of simulation and empirical studies, we produce scores in a single-cohort repeated measure design using sum scores as well as multiple IRT approaches and compare the recovery of growth estimates from longitudinal growth models using each set of scores. Results indicate that using scores from multidimensional IRT approaches that account for latent variable covariances over time in growth models leads to better recovery of growth parameters relative to models using sum scores and other IRT approaches. (PsycInfo Database Record (c) 2020 APA, all rights reserved).The randomized pretest posttest design is common in psychology, as is the corresponding missing data concern. Although missing data handling has seen advances over the past several decades, effective and practical solutions for handling missing data in randomized pretest posttest designs are lacking, particularly when assumptions of commonly used statistical models are violated. Although analysis of covariance can capture the average treatment effect with complete data, even when assumptions are tenuous, this becomes more difficult with missing data. This investigation fills this gap in the literature by comparing a variety of analysis models for estimating the average treatment effect under violations of linearity and homogeneity of regression slopes, when data are missing by several plausible, but understudied, missing at random patterns for randomized pretest posttest studies. Two missing data handling techniques, listwise deletion and multiple imputation, were considered. Listwise deletion provided maximum likelihood estimates (unbiased and appropriately precise) of the average treatment effect as long as the analysis model was appropriately specified to handle the violated assumption and the pretest mean was estimated using all cases. Although multiple imputation was effective as long as the imputation model was correct, the results highlight to the importance of model specification in the context of missing data. Importantly, the specific pattern of missing at random data had implications for results, emphasizing the need to consider the particular pattern of missingness beyond the general appropriateness of the missing at random assumption. (PsycInfo Database Record (c) 2020 APA, all rights reserved).Qualitative interviews were conducted with veterans to understand their experiences and perceptions about insomnia and its treatment, with a focus on cognitive-behavioral therapy for insomnia (CBT-I) and brief behavioral treatment for insomnia (BBTI). There is a lack of knowledge about veterans' understanding of this prevalent disorder, yet their experiences and perceptions can influence treatment delivery and treatment outcomes. The Department of Veterans Affairs (VA) can improve insomnia care by considering and responding to this valuable information from veteran stakeholders. Twenty veterans with an insomnia diagnosis or complaint were interviewed about their experiences with insomnia, its treatment, and their preferences for care. Transcripts from the audio-recorded interviews were independently analyzed by 2 coders using content analysis, and discrepancies were resolved through negotiated consensus. The 20 veterans were mostly male (85%), older (60.4 years ± 9.0), and white (60%). Experiences with insomnia and perspectives regarding treatment focused on (a) insomnia symptoms, (b) comorbid symptoms, (c) seeking treatment, (d) intervention experiences, (e) intervention preferences and expectations, and (f) patient attributes. Barriers to care included a lack of knowledge about treatment and a lack of options that fit veterans' preference for delivery. These results provide insight into veterans' experiences with and perspectives on insomnia treatment that is crucial to the support, development, and implementation of interventions. A focus on increasing knowledge of, and expectations for, insomnia treatments as well as offering multiple delivery options has the potential to improve utilization and access to quality insomnia care. (PsycInfo Database Record (c) 2020 APA, all rights reserved).The U.S. Department of Veterans Affairs (VA)/Department of Defense (DoD) Clinical Practice Guideline (CPG) for the Management of Posttraumatic Stress Disorder (PTSD) and Acute Stress Disorder strives to advance the VA's practice of recovery-oriented, evidence-based, patient-centered care (PCC) for veterans with PTSD. [https://www.selleckchem.com/products/SB939.html Selleck SB939] A core foundation of PCC is that care is individually tailored to meet the needs and preferences of each patient. Accordingly, the 2017 update to the CPG specifically recommends the use of shared decision making (SDM), an individualized collaborative approach to treatment planning, in the PTSD treatment planning process. Although SDM has been promoted by the CPG throughout the VA and SDM training is being developed, no systemic training was available at the time the guidelines were updated. Additionally, while early research has studied the impact and experience of SDM for the patient, no work has explored provider experiences with SDM for those who work with trauma populations. This project bridges this gap by examining survey data collected 6 months following a formal SDM training to staff and trainees working with veterans who have experienced trauma within a trauma clinic at a large VA hospital. After the training, clinicians understood SDM and were engaging in SDM with their patients. Patients indicated that they were satisfied with and felt like an active participant in the treatment planning process. Clinician assumptions about the SDM process and barriers to SDM shown in previous research were also demonstrated. Implications for future research and practice, such as using decision aids in PTSD treatment planning and targeting clinician beliefs about SDM, are discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).