The objective of this study was to design a weight loss self-efficacy questionnaire which was multidimensional, with each dimension representing a specific type of relapse situation. The instrument developed contained 41 specific situations or emotional states which were considered to be high-risk for precipitating diet relapse. Two hundred thirty-six usable questionnaires were completed by individuals who attended a weight reduction class at one of eleven Air Force bases in the continental United States. Exploratory principal component analysis using the varimax, rotation method was employed to test for the presence of distinct dimensions of self-efficacy. Three distinct dimensions emerged, Negative Emotional, Urges and Temptations, and Party Situations, which accounted for approximately 56 percent of variance. Reliability coefficients ranged from.96 to.84 indicating that the sampling attributes for the three domains were adequate and there was homogeneity of items constituting each dimension. An instrument of this type has the potential for improving effectiveness of weight reduction therapies by facilitating the targeting of intervention to the situations identified as being high-risk for a specific person.

published_or_final_version / abstract / Clinical Psychology / Master / Master of Social Sciences

Subjective contours provide an opportunity to explore the limits of correspondence matching in motion. A new class of subjective contour which is a by-product of motion processing is examined within the context of the dual process models of retinal motion processing proposed by Braddick (1980) and Anstis (1980), as well as the more recent first-order/second-order formulation proposed by Cavanagh and Mather (1989). These kinetically induced figures are created by displacing a surface defined by dots which change randomly from frame to frame over a static random dot background. Despite the fact that local form information is uncorrelated throughout the motion sequence, the resulting phenomenal percept is that of a "sparkling" surface which translates across the background. The results of five experiments were not, however, fully consistent with predictions based on either model. An extension of the criteria necessary for the long-range system to be operative would accommodate the data within the context of the short-range/long-range model, whereas a more detailed definition of the properties and relationships between second-order attributes would accommodate the data within the framework of the first-order/second-order model.

Adult memory for verbatim and gist information was tested immediately and after a 12-day delay in three experiments within the framework of fuzzy-trace theory, (e.g., Brainerd & Reyna, 1990; Reyna & Brainerd, 1991) using a crossed, within-subjects false recognition design which controlled for the amount of verbatim and gist in recognition stimuli and for the difficulties mentioned by Fletcher (1992). Instruction to recognize gist or verbatim information was a between-subjects factor. Experiment 1 investigated sentence recognition and misrecognition of inferences for spatial and linear sentences. Subjects exhibited both verbatim memory for the presented premises and gist intrusion for sentences that differed in surface form but shared the same gist. Relationships between presented premises and their inferences were independent when subjects interrogated verbatim traces to answer memory questions, and gist traces to answer reasoning (inference) questions. Subjects used gist to verify sentences in the meaning condition, and dependencies between premises and inferences were largely positively dependent. Overall, Experiment 1 replicated Reyna and Kiernan's (in press) findings with children, suggesting that adults do not qualitatively differ from children in the processing of verbatim and gist representations. Experiment 1's results rule out a constructivist account of memory (e.g., Bransford and Franks, 1971). Experiment 2 investigated recognition of inflected (e.g., past tense and plural) verb and noun word pairs, and misrecognition of analogous pairs. Results were similar to Experiment 1 as subjects used verbatim traces for verification in the memory condition. When processing for patterns, however, some subjects appeared to use a phonological rule, whereas others appeared to use a semantic rule. Experiment 3 investigated recognition of interpretations of novel Literal and Perceptual metaphors. Results were largely similar to those of Experiments 1 and 2. However, negative dependencies were found between presented metaphors and their interpretations in the memory condition, supporting the principle of discrepancy detection (e.g., Loftus, 1979). Evidence disconfirmed stage models of metaphor interpretation in which literal precedes figurative interpretation. Results were explained by two models of interpretation depending on metaphor type (Literal or Perceptual). Individual differences in gist versus verbatim processing were found in adults across the three experiments.

As more patients with cystic fibrosis (CF) are living into adulthood, patients may need to disclose their CF status to others, such as in romantic or professional settings. Patients who choose not to disclose their CF status may be limited in their closeness with others, which may negatively affect their psychological functioning and health-related quality of life. Few studies, however, have examined disclosure in CF, and currently no validated measures of CF disclosure exist. The purpose of this study was to explore CF disclosure in adults and validate a new assessment of CF disclosure, the Cystic Fibrosis Disclosure Scale (CFDS). Results were consistent with prior research in disclosure in CF, with participants disclosing most often to close others and less often at school or in the workplace. Disclosure to close and casual friends was consistently associated with better psychosocial functioning. Factor analyses determined the CFDS was valid and that all questions should be retained. The Count Group subscale emerged as the “best” subscale grouping and coding method. This study contributed to the literature by serving as the first validation study of a questionnaire of disclosure in CF. Additionally, as disclosure in CF is a new emerging area, this study added information to the sparse literature on this issue. The CFDS as it exists now gathers important research and clinical information from adults with CF, and should be examined further with a larger sample size and more descriptive information.

The use of constructed response (CR) items or performance tasks to assess test takers' ability has grown tremendously over the past decade. Examples of CR items in psychological and educational measurement range from essays, works of art, and admissions interviews. However, unlike multiple-choice (MC) items that have predetermined options, CR items require test takers to construct their own answer. As such, they require the judgment of multiple raters that are subject to differences in perception and prior knowledge of the material being evaluated. As with any scoring procedure, the scores assigned by raters must be comparable over time and over different test administrations and forms; in other words, scores must be reliable and valid for all test takers, regardless of when an individual takes the test. This study examines how longitudinal patterns or changes in rater behavior affect model-based classification accuracy. Rater drift refers to changes in rater behavior across different test administrations. Prior research has found evidence of drift. Rater behavior in CR scoring is examined using two measurement models - latent class signal detection theory (SDT) and item response theory (IRT) models. Rater effects (e.g., leniency and strictness) are partly examined with simulations, where the ability of different models to capture changes in rater behavior is studied. Drift is also examined in two real-world large scale tests: teacher certification test and high school writing test. These tests use the same set of raters for long periods of time, where each rater's scoring is examined on a monthly basis. Results from the empirical analysis showed that rater models were effective to detect changes in rater behavior over testing administrations in real-world data. However, there were differences in rater discrimination between the latent class SDT and IRT models. Simulations were used to examine the effect of rater drift on classification accuracy and on differences between the latent class SDT and IRT models. Changes in rater severity had only a minimal effect on classification. Rater discrimination had a greater effect on classification accuracy. This study also found that IRT models detected changes in rater severity and in rater discrimination even when data were generated from the latent class SDT model. However, when data were non-normal, IRT models underestimated rater discrimination, which may lead to incorrect inferences on the precision of raters. These findings provide new and important insights into CR scoring and issues that emerge in practice, including methods to improve rater training.

The Pseudo Random Arterial Modulation (PRAM) is a non-invasive MRI based method to measure blood flow. It does not require any contrast agent but rather uses water protons in the body as the contrast. PRAM is based on a pseudo random sequence of inversions and non-inversions of the arterial blood using radio frequency (RF) pulses at a labeling plane inferior to the imaging plane. A series of images are taken at the imaging plane and flow reconstructed from the transit time measurements. PRAM does not require separate control and label acquisition as is common in Arterial Spin Labeling (ASL) but rather measures the distribution of transit times to a voxel within one integrated scan. Adiabatic inversion or non-inversion pre-pulses (PRAM pulses) are performed prior to a gradient echo imaging. The PRAM method has been tested on a flow phantom and the results were in confirmation with the theoretical flow and velocity measurements. Subsequently the PRAM method was tested on a human leg and the results were comparable with the Ultrasound measurements. The final testing phase was performed on a human brain and the results were compared with the phased contrast MRA. We have demonstrated here that that the PRAM technique can measure the velocity profile and the transit time accurately and efficiently on any organ such as human brain.

Three studies examined context effects on solving probability problems. Variants of word problems were written with cover stories which differed with respect to social or temporal schemas, while maintaining formal problem structure and solution procedure. In the first of these studies it was shown that problems depicting schemas in which randomness was inappropriate or unexpected for the social situation were solved less often than problems depicting schemas in which randomness was appropriate. Another set of two studies examined temporal and causal schemas, in which the convention is that events are considered in forward direction. Pairs of conditional probability (CP) problems were written depicting events E1 and E2, such that E1 either occurs before E2 or causes E2. Problems were defined with respect to the order of events expressed in CPs, so that P(E2|E1) represents the CP in schema-consistent, intact order by considering the occurrence of E1 before E2, while P(E1|E2) represents CP in schema-inconsistent, inverted order. Introductory statistics students had greater difficulty encoding CP for events in schema-inconsistent order than CP of events in conventional deterministic order. The differential effects of schematic context on solving probability problems identify specific conditions and sources of bias in human reasoning under uncertainty. In addition, these biases may be influential when evaluating empirical findings in a manner similar to that demonstrated in this paper experimentally, and may have implications for how social scientists are trained in research methodology.

This research aims to develop an MCMC algorithm for estimating the Q-matrix in a Bayesian framework. A saturated multinomial model was used to estimate correlated attributes in the DINA model and rRUM. Closed-forms of posteriors for guess and slip parameters were derived for the DINA model. The random walk Metropolis-Hastings algorithm was applied to parameter estimation in the rRUM. An algorithm for reducing potential label switching was incorporated into the estimation procedure. A method for simulating data with correlated attributes for the DINA model and rRUM was offered. Three simulation studies were conducted to evaluate the algorithm for Bayesian estimation. Twenty simulated data sets for simulation study 1 were generated from independent attributes for the DINA model and rRUM. A hundred data sets from correlated attributes were generated for the DINA and rRUM with guess and slip parameters set to 0.2 in simulation study 2. Simulation study 3 analyzed data sets simulated from the DINA model with guess and slip parameters generated from Uniform (0.1, 0.4). Results from simulation studies showed that the Q-matrix recovery rate was satisfactory. Using the fraction-subtraction data, an empirical study was conducted for the DINA model and rRUM. The estimated Q-matrices from the two models were compared with the expert-designed Q-matrix.

There has been growing interest in recent years in using cognitive diagnosis models for diagnostic measurement, i.e., classification according to multiple discrete latent traits. The Q-matrix, an incidence matrix specifying the presence or absence of a relationship between each item in the assessment and each latent attribute, is central to many of these models. Important applications include educational and psychological testing; demand in education, for example, has been driven by recent focus on skills-based evaluation. However, compared to more traditional models coming from classical test theory and item response theory, cognitive diagnosis models are relatively undeveloped and suffer from several issues limiting their applicability. This thesis exams several issues related to statistical inference and experimental design for Q-matrix based cognitive diagnosis models. We begin by considering one of the main statistical issues affecting the practical use of Q-matrix based cognitive diagnosis models, the identifiability issue. In statistical models, identifiability is prerequisite for most common statistical inferences, including parameter estimation and hypothesis testing. With Q-matrix based cognitive diagnosis models, identifiability also affects the classification of respondents according to their latent traits. We begin by examining the identifiability of model parameters, presenting necessary and sufficient conditions for identifiability in several settings. Depending on the area of application and the researcher's degree of control over the experiment design, fulfilling these identifiability conditions may be difficult. The second part of this thesis proposes new methods for parameter estimation and respondent classification for use with non-identifiable models. In addition, our framework allows consistent estimation of the severity of the non-identifiability problem, in terms of the proportion of the population affected by it. The implications of this measure for the design of diagnostic assessments are also discussed.