808 resultados para concurrent validity


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Thesis (Ph.D.)--University of Washington, 2016-08

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Purpose. Anastomotic strictures occur in 3-30% of colorectal anastomosis and one of the main causes may be a reaction to the presence of the metal staples used for suturing. The aim of this study was to evaluate the efficacy of a compression anastomosis ring using the memoryshaped device in initial, i.e. nickel-titanium alloy (NiTi) for the prevention of colorectal anastomotic strictures. Patients and methods. A compression anastomosis ring device (NiTi CAR 27™) was used to perform compression anastomosis in 20 patients underwent left hemicolectomy and anterior resection of the rectum for carcinoma. An endoscopic check of the anastomosis was carried out at one month and at six months after surgery. Results. In 2 patients (10%) a dehiscence of the anastomosis occurred on the fifth and the eighth postoperative day. No anastomotic strictures were observed in any of the other 18 patients at six months follow-up after surgery. Conclusion. Our preliminary results suggest that the use of a compression anastomosis ring might well be a valid method of preventing anastomotic strictures in colorectal surgery. Further studies involving a larger number of patients are needed in order to confirm these preliminary results.

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Negative symptoms are related to worse psychosocial functioning in schizophrenia. The current study evaluates two behavioral affiliation tasks—the video-based Social Affiliation Interaction Task (SAIT) and the in-vivo Conversation Task (CT)—and explores whether behavioral ratings of social affiliation are associated with negative symptoms and community functioning. Participants, 20 with schizophrenia/schizoaffective disorder (SZ) and 35 healthy controls (HC), completed both tasks and measures of negative symptoms and functioning. SZ evidenced lower behavioral affiliation on the SAIT compared to HC. There were no group differences in behavioral affiliation on the CT. Within groups, behavioral affiliation was not correlated between tasks or with symptoms and functioning. Across groups, behavioral affiliation from the SAIT was correlated with symptoms and functioning. Post hoc analyses revealed higher ratings of positive facial expression and valence in the CT for HC compared to SZ. Results suggest that the method of assessing behavioral affiliaton may influence research findings.

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Previous research found personality test scores to be inflated on average among individuals who were motivated to present themselves in a desirable fashion in high stakes situations, such as during the employee selection process. One apparently effective way to reduce the undesirable test score inflation in such situations was to warn participants against faking. This research set out to investigate whether warning against faking would indeed affect personality test scores in the theoretically expected fashion. Contrary to expectations, the results did not support the hypothesized causal chain. Results across three studies show that while a warning may lower test scores in participants motivated to respond desirably (i.e., to fake), the effect of warning on test scores was not fully mediated by: a reduction in motivation to do well and self-reports of exaggerated responses in the personality test. Theoretical and practical implications are discussed.

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Simultaneous Localization and Mapping (SLAM) is a procedure used to determine the location of a mobile vehicle in an unknown environment, while constructing a map of the unknown environment at the same time. Mobile platforms, which make use of SLAM algorithms, have industrial applications in autonomous maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. A typical SLAM consists of four main components, namely, experimental setup (data gathering), vehicle pose estimation, feature extraction, and filtering. Feature extraction is the process of realizing significant features from the unknown environment such as corners, edges, walls, and interior features. In this work, an original feature extraction algorithm specific to distance measurements obtained through SONAR sensor data is presented. This algorithm has been constructed by combining the SONAR Salient Feature Extraction Algorithm and the Triangulation Hough Based Fusion with point-in-polygon detection. The reconstructed maps obtained through simulations and experimental data with the fusion algorithm are compared to the maps obtained with existing feature extraction algorithms. Based on the results obtained, it is suggested that the proposed algorithm can be employed as an option for data obtained from SONAR sensors in environment, where other forms of sensing are not viable. The algorithm fusion for feature extraction requires the vehicle pose estimation as an input, which is obtained from a vehicle pose estimation model. For the vehicle pose estimation, the author uses sensor integration to estimate the pose of the mobile vehicle. Different combinations of these sensors are studied (e.g., encoder, gyroscope, or encoder and gyroscope). The different sensor fusion techniques for the pose estimation are experimentally studied and compared. The vehicle pose estimation model, which produces the least amount of error, is used to generate inputs for the feature extraction algorithm fusion. In the experimental studies, two different environmental configurations are used, one without interior features and another one with two interior features. Numerical and experimental findings are discussed. Finally, the SLAM algorithm is implemented along with the algorithms for feature extraction and vehicle pose estimation. Three different cases are experimentally studied, with the floor of the environment intentionally altered to induce slipping. Results obtained for implementations with and without SLAM are compared and discussed. The present work represents a step towards the realization of autonomous inspection platforms for performing concurrent localization and mapping in harsh environments.

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It is important to assess young children's perceived Fundamental Movement Skill (FMS) competence in order to examine the role of perceived FMS competence in motivation toward physical activity. Children's perceptions of motor competence may vary according to the culture/country of origin; therefore, it is also important to measure perceptions in different cultural contexts. The purpose was to assess the face validity, internal consistency, test–retest reliability and construct validity of the 12 FMS items in the Pictorial Scale for Perceived Movement Skill Competence for Young Children (PMSC) in a Portuguese sample. Methods Two hundred one Portuguese children (girls, n = 112), 5 to 10 years of age (7.6 ± 1.4), participated. All children completed the PMSC once. Ordinal alpha assessed internal consistency. A random subsamples (n = 47) were reassessed one week later to determine test–retest reliability with Bland–Altman method. Children were asked questions after the second administration to determine face validity. Construct validity was assessed on the whole sample with a Bayesian Structural Equation Modelling (BSEM) approach. The hypothesized theoretical model used the 12 items and two hypothesized factors: object control and locomotor skills. Results The majority of children correctly identified the skills and could understand most of the pictures. Test–retest reliability analysis was good, with an agreement ration between 0.99 and 1.02. Ordinal alpha values ranged from acceptable (object control 0.73, locomotor 0.68) to good (all FMS 0.81). The hypothesized BSEM model had an adequate fit. Conclusions The PMSC can be used to investigate perceptions of children's FMS competence. This instrument can also be satisfactorily used among Portuguese children.

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Cybercrime is a growing and worrisome problem, particularly when it involves minors. Cyber-aggression among adolescents in particular can result in negative legal and psychological consequences for people involved. Therefore, it is important to have instruments to detect these incidents early and understand the problem to propose effective measures for prevention and treatment. This paper aims to design a new self-report, the Cyber-Aggression Questionnaire for Adolescents (CYBA), to evaluate the extent to which the respondent conducts aggressions through a mobile phone or the internet and analyse the factorial and criterion validity and reliability of their scores in a sample of adolescents from Asturias, Spain. The CYBA was administered to 3,148 youth aged between 12 and 18 years old along with three self-reports to measure aggression at school, impulsivity, and empathy. Regarding factorial validity, the model that best represents the structure of the CYBA consists of three factors (Impersonation, Visual-sexual Cyber-aggression, and Verbal Cyber-aggression and Exclusion) and four additional indicators of Visual Cyber-aggression-Teasing/Happy Slapping. Regarding criterion validity, the score on the CYBA correlates positively with aggression at school and impulsivity and negatively with empathy. That is the way cyber-aggression correlates with these three variables, according to previous empirical evidence. The reliability of the scores on each item and factor of the CYBA are adequate. Therefore, the CYBA offers a valid and reliable measure of cyber-aggression in adolescents.

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The inclusion of non-ipsative measures of party preference (in essence ratings for each of the parties of a political system) has become established practice in mass surveys conducted for election studies. They exist in different forms, known as thermometer ratings or feeling scores, likes and dislikes scores, or support propensities. Usually only one of these is included in a single survey, which makes it difficult to assess the relative merits of each. The questionnaire of the Irish National Election Study 2002 (INES2002) contained three different batteries of non-ipsative party preferences. This paper investigates some of the properties of these different indicators. We focus in particular on two phenomena. First, the relationship between non-ipsative preferences and the choices actually made on the ballot. In Ireland this relationship is more revealing than in most other countries owing to the electoral system (STV) which allows voters to cast multiple ordered votes for candidates from different parties. Second, we investigate the latent structure of each of the batteries of party preferences and the relationships between them. We conclude that the three instruments are not interchangeable, that they measure different orientations, and that one –the propensity to vote for a party– is by far preferable if the purpose of the study is the explanation of voters’ actual choice behaviour. This finding has important ramifications for the design of election study questionnaires.

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The aim of this paper was to obtain evidence of the validity of the LSB-50 (de Rivera & Abuín, 2012), a screening measure of psychopathology, in Argentinean adolescents. The sample consisted of 1002 individuals (49.7% male; 50.3% female) between 12 and 18 years-old (M = 14.98; SD = 1.99). A cross-validation study and factorial invariance studies were performed in samples divided by sex and age to test if a seven-factor structure that corresponds to seven clinical scales (Hypersensitivity, Obsessive-Compulsive, Anxiety, Hostility, Somatization, Depression, and Sleep disturbance) was adequate for the LSB-50. The seven-factor structure proved to be suitable for all the subsamples. Next, the fit of the seven-factor structure was studied simultaneously? in the aforementioned subsamples through hierarchical models that imposed different constrains of equivalency?. Results indicated the invariance of the seven clinical dimensions of the LSB-50. Ordinal alphas showed good internal consistency for all the scales. Finally, the correlations with a diagnostic measure of psychopathology (PAI-A) indicated moderate convergence. It is concluded that the analyses performed provide robust evidence of construct validity for the LSB-50

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Dissertação de Mestrado, Neurociências Cognitivas e Neuropsicologia, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2016

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The purpose of the study was to determine the degree of relationships among GRE scores, undergraduate GPA (UGPA), and success in graduate school, as measured by first year graduate GPA (FGPA), cumulative graduate GPA, and degree attainment status. A second aim of the study was to determine whether the relationships between the composite predictor (GRE scores and UGPA) and the three success measures differed by race/ethnicity and sex. A total of 7,367 graduate student records (masters, 5,990; doctoral: 1,377) from 2000 to 2010 were used to evaluate the relationships among GRE scores, UGPA and the three success measures. Pearson’s correlation, multiple linear and logistic regression, and hierarchical multiple linear and logistic regression analyses were performed to answer the research questions. The results of the correlational analyses differed by degree level. For master’s students, the ETS proposed prediction that GRE scores are valid predictors of first year graduate GPA was supported by the findings from the present study; however, for doctoral students, the proposed prediction was only partially supported. Regression and correlational analyses indicated that UGPA was the variable that consistently predicted all three success measures for both degree levels. The hierarchical multiple linear and logistic regression analyses indicated that at master’s degree level, White students with higher GRE Quantitative Reasoning Test scores were more likely to attain a degree than Asian Americans, while International students with higher UGPA were more likely to attain a degree than White students. The relationships between the three predictors and the three success measures were not significantly different between men and women for either degree level. Findings have implications both for practice and research. They will provide graduate school administrators with institution-specific validity data for UGPA and the GRE scores, which can be referenced in making admission decisions, while they will provide empirical and professionally defensible evidence to support the current practice of using UGPA and GRE scores for admission considerations. In addition, new evidence relating to differential predictions will be useful as a resource reference for future GRE validation researchers.

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Concurrent software executes multiple threads or processes to achieve high performance. However, concurrency results in a huge number of different system behaviors that are difficult to test and verify. The aim of this dissertation is to develop new methods and tools for modeling and analyzing concurrent software systems at design and code levels. This dissertation consists of several related results. First, a formal model of Mondex, an electronic purse system, is built using Petri nets from user requirements, which is formally verified using model checking. Second, Petri nets models are automatically mined from the event traces generated from scientific workflows. Third, partial order models are automatically extracted from some instrumented concurrent program execution, and potential atomicity violation bugs are automatically verified based on the partial order models using model checking. Our formal specification and verification of Mondex have contributed to the world wide effort in developing a verified software repository. Our method to mine Petri net models automatically from provenance offers a new approach to build scientific workflows. Our dynamic prediction tool, named McPatom, can predict several known bugs in real world systems including one that evades several other existing tools. McPatom is efficient and scalable as it takes advantage of the nature of atomicity violations and considers only a pair of threads and accesses to a single shared variable at one time. However, predictive tools need to consider the tradeoffs between precision and coverage. Based on McPatom, this dissertation presents two methods for improving the coverage and precision of atomicity violation predictions: 1) a post-prediction analysis method to increase coverage while ensuring precision; 2) a follow-up replaying method to further increase coverage. Both methods are implemented in a completely automatic tool.