AUTISM AND SELF-DETERMINATION: MEASUREMENT AND CONTRAST WITH OTHER DISABILITY GROUPS

This dissertation consists of four chapters. Chapter 1 provides an introduction to the self-determination literature documenting the importance of promoting the self-determination of transition and secondary age students with disabilities, as well as a summary of research examining the self-determination of students with disabilities across disability categories, with a particular focus on students with autism spectrum disorders (ASD) and the need for additional research with this latter population. Chapter 2 investigates the factor structures of two instruments measuring the self-determination of students with ASD. Ninety-five middle and high school students (17% female and 83% male) ages 13 through 22 years participated in the investigation of the validity of two instruments, The Arc's Self-Determination Scale (SDS) and AIR Self-Determination Scale (AIR). A Confirmatory Factor Analysis (CFA) was conducted separately for the SDS and AIR data. The findings of this study indicated that the parameter estimates and the model fit results supported the hypothesized factor structure in this sample, at least for the first three of four factors of the SDS and fully supported the two factors of the AIR. Chapter 3 builds on the findings of Chapter 2 and examines the differences in self-determination among students with ASD, students with intellectual disability (ID), and students with learning disabilities (LD). A total of 222 participants with an equal size group for each of the three disability categories (ASD, ID, LD) were selected to participate in the comparison of total self-determination and domain scores. One-way between-subjects multivariate analysis of variance (MANOVA) was performed on six dependent variables/factors, including autonomy, self-regulation, psychological empowerment, self-realization, capacity, and opportunity. The results indicated that (a) students with ASD and ID and LD were different in their scores in these domains, and (b) students with ASD had lower levels of autonomy when compared to students with LD. Chapter 4 presents the conclusions and implications of the findings of Chapter 2 and 3. The primary implications for future research indicate that the factors of the two self-determination measures can be used as reliable outcome variables useful for detecting treatment effects of experimental design studies promoting the self-determination of students with ASD. Also, future research is encouraged to investigate the items that loaded negatively onto Self-Realization domain of the SDS. In addition to significant group differences in self-determination among three disability groups, future research should examine group differences in each essential characteristic of self-determination or in the component elements of self-determined behavior to provide a more completed profile of relative self-determination for this group. The primary implications for educators were that the two commonly used instruments are applicable to the population of students with ASD. Also, students with ASD, ID, and LD need instruction to promote self-determination, but students with ASD also need instructional emphases on several component elements as shown by the domain-level differences found in this study

Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task.

Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions' temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions' neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed

Predicting protein-protein interactions in unbalanced data using the primary structure of proteins

<p>Abstract</p> <p>Background</p> <p>Elucidating protein-protein interactions (PPIs) is essential to constructing protein interaction networks and facilitating our understanding of the general principles of biological systems. Previous studies have revealed that interacting protein pairs can be predicted by their primary structure. Most of these approaches have achieved satisfactory performance on datasets comprising equal number of interacting and non-interacting protein pairs. However, this ratio is highly unbalanced in nature, and these techniques have not been comprehensively evaluated with respect to the effect of the large number of non-interacting pairs in realistic datasets. Moreover, since highly unbalanced distributions usually lead to large datasets, more efficient predictors are desired when handling such challenging tasks.</p> <p>Results</p> <p>This study presents a method for PPI prediction based only on sequence information, which contributes in three aspects. First, we propose a probability-based mechanism for transforming protein sequences into feature vectors. Second, the proposed predictor is designed with an efficient classification algorithm, where the efficiency is essential for handling highly unbalanced datasets. Third, the proposed PPI predictor is assessed with several unbalanced datasets with different positive-to-negative ratios (from 1:1 to 1:15). This analysis provides solid evidence that the degree of dataset imbalance is important to PPI predictors.</p> <p>Conclusions</p> <p>Dealing with data imbalance is a key issue in PPI prediction since there are far fewer interacting protein pairs than non-interacting ones. This article provides a comprehensive study on this issue and develops a practical tool that achieves both good prediction performance and efficiency using only protein sequence information.</p

THE EFFECTS OF FUNGAL MEDIUM ON HATCHING RATE OF BITING MIDGE

The little black mosquitos, Forcipomyia taiwana, bite human and become one of the most annoying pests in Taiwan. Recently, the population of F. taiwana increases and invades urban and countryside. In order to effectively prevent the harassment of F. taiwana, develop control strategy is urgent and necessary. Our study found that the fungal medium influenced the length and width of the F. taiwana eggs. It also significantly decreased the hatching rate of F. taiwana. Besides, this artificial diet was more non-toxic and environment-friendly than general chemical pesticides. Thus, this study provided critical information to develop potentially useful bait of F. taiwana in the future

RISK OF SLEEP DISORDERS IN PATIENTS WITH DECOMPRESSION SICKNESS: A NATIONWIDE, POPULATION-BASED STUDY IN TAIWAN

Background: Decompression sickness (DCS) primarily manifests musculoskeletal pain, cutaneous manifestations, lymphatic symptoms, and neurological symptoms. DCS might affect the central nervous system and induce the stress in the patients, but few studies about the psychiatric morbidity after DCS have been conducted. This study aimed to investigate the association between DCS and the risk of developing psychiatric disorders. Subjects and methods: This study was a population-based, matched cohort design. A total of 738 enrolled patients, with 123 study subjects who had suffered from DCS, and 615 controls matched for sex and age, from the Longitudinal Health Insurance Databank from 2000-2010 in Taiwan, and selected from the National Health Insurance Research Database. After adjusting for the confounding factors, Cox proportional hazards analysis was used to compare the risk of developing psychiatric disorders during the 10 years of follow-up period. Results: Of the study subjects, 10 (8.13%) developed psychiatric disorders when compared to 35 (5.69%) in the control group. The study subjects were more likely to develop psychiatric disorders (crude hazard ratio [HR]: 2.79 (95% CI=1.37-5.69, P<0.01). After adjusting for sex, age, monthly income, urbanization level, geographic region, and comorbidities, the adjusted HR was 3.83 (95% CI=1.60-9.16, P<0.01). Sleep disorders was associated with DCS with the adjusted HR as 5.74 (95% CI=1.04-31.56, P<0.01). Hyperbaric oxygenation therapy was not associated with a lower risk of psychiatric disorders. Conclusions: Patients who suffered from DCS have a 3.8-fold risk of developing psychiatric disorders, and a 5.7-fold risk of sleep disorders. This finding is a reminder for the clinicians that a regular psychiatric follow-up might well be needed for these patients

Association between the mental domain of the comprehensive geriatric assessment and prolonged length of stay in hospitalized older adults with mild to moderate frailty

IntroductionPrevious researches have shown the risk factors of prolonged length of stay (PLOS) in hospitalized older adults, but it is unclear what are the risk factors of PLOS in hospitalized older adults with mild to moderate frailty.ObjectiveTo identify the risk factors of PLOS in hospitalized older adults with mild to moderate frailty.MethodsWe recruited adults aged ≥65 years old with mild to moderate frailty admitted to a tertiary medical center in the southern Taiwan from June 2018 to September 2018. Each individual underwent a structural questionnaire interview within 72 h after admission and 72 h after discharge. The data were collected face-to-face, including demographic characteristics, comorbidities, length of stay (LOS), and multiple domains of the comprehensive geriatric assessment. The main outcome was PLOS.ResultsIndividuals who had two or more drugs, were female, did not have cognitive impairment and had a Geriatric Depression Scale score ≥ 1 had a higher risk of PLOS (probability = 0.81), and these individuals accounted for 29% of the overall study population. Among male individuals younger than 87 years old, those with cognitive impairment had a higher risk of PLOS (probability = 0.76), and among male individuals without cognitive impairment, living alone was associated with a higher risk of PLOS (probability = 0.88).ConclusionEarly detection and management of mood and cognition in older adults, together with comprehensive discharge planning and transition care, may be an important part of reducing LOS in hospitalized older adults with mild to moderate frailty