Bakgrund: Det finns i nuläget inget svenskt self-efficacy instrument för barn och ungdomar med smärta. Den här undersökningen syftade till att översätta samt reliabilitets- och validitetstesta en engelskspråkig self-efficacy skala för barn och ungdomar med smärta. Metod: Urvalet bestod av 62 elever från tre olika klasser i Uppsala. Skalan översattes till svenska och ett frågeformulär utformades för att möjliggöra en utvärdering av test-retest reliabilitet samt kriterie- och ögonblicksvaliditet. Resultat: Värdena på viktad kappa för överensstämmelsen av två skattningar (S1 och S2) med self-efficacy instrumentet (SEIS) varierade mellan Kw= 0,37 -  Kw=0,75. Sambandet mellan Functional disability inventory (FDI) och SEIS beräknades med Spearmans rangkorrelation där rs = 0,364 (p<0,05). Ögonblicksvaliditeten för SEIS beskrevs som att den var lättförståelig, innehöll vardagliga aktiviteter men att vissa aktiviteter saknades. Konklusion: Slutsatsen av denna undersökning var att frågorna i SEIS bör omarbetas för att bli mer specifika och kunna användas. Det kan även utarbetas nya aktiviteter till instrumentet eftersom resultaten av undersökningen visade att vissa aktiviteter saknades. På grund av urvalets karaktär var resultaten troligtvis inte generaliserbara.

Empati kan beskrivas som en förmåga att veta vad en person känner och tänker. Denna studies huvudsyfte var att översätta C. Daniel Bat-sons empatiskala till svenska. Syftet var även att testa om det fanns skillnader vid perspektivtagande samt skillnader i empati när den and-re är snäll jämfört med elak. Deltagarna var 111 gymnasiestudenter som fick inta ett perspektiv, objektivt eller med inlevelse, och läsa en historia. Resultatet visade att det inte fanns könsskillnad, men det fanns interaktion mellan historia och läsarperspektiv; skillnaden mellan perspektiven fanns när personen var snäll. Det fanns också skillnad i empati beroende vilken historia deltagarna hade läst. Det var lättare att känna empati för en snäll person än för en person som var elak.

“Homeostatic beliefs” (HBs) denote a sense that one’s life path will remain stable in the long-term despite short-term disruptions. Two studies have been undertaken to explore whether HBs exist independent of other constructs, and to develop a scale with which to measure them. In Study 1, 158 undergraduate students completed a draft HB scale and theoretically related scales. Convergent and divergent validity were assessed with correlational and regression analyses: HBs are most strongly related to, but not redundant with, optimism, trait extraversion, and satisfaction with life. Using exploratory factor analysis, a six-item HB scale was derived. Study 2 is in progress, and will assess the construct validity of the HB scale by attempting to manipulate HBs to possibly influence individuals’ reactions to a mortality salience manipulation. We hypothesize that high HBs may buffer individuals from transient disrupting stimuli such as a mortality salience cue.

It has been demonstrated that people often feel happier, healthier, and more relaxed after a vacation. However, there is still lack of research on how people perceive the benefits of travel and how these perceptions influence their travel behavior. Thus, the primary purpose of this research was to examine the effects of perceived tourism benefits on travel behavior based on the model of attitude importance. Since existing scales of tourism benefits failed to incorporate some important items or factors, particularly the health benefits of tourism, this dissertation involved three online panel surveys, including: (1) a preliminary study (n=566) to elicit new benefit items, (2) a pilot study (n=434) to trim down the number of items, and (3) a main survey (n=559) to finalize the scale. As a result, several items associated with health benefits were elicited from the preliminary study; in the later stages of scale development, these items were identified and validated as a convergent dimension of perceived health benefits. Further, several hypotheses pertaining to the effect of perceived tourism benefits and the applicability of the attitude-importance model in tourism were tested. The results showed that: (1) the premise of the attitude-importance model that important attitudes can instigate the process of knowledge accumulation was supported; (2) the applicability of the attitude-importance model in tourism was supported; (3) the three factors of perceived tourism benefits – experiential, health, and relaxation benefits, had positive effects on travel behavior through attitude importance. These results had theoretical and practical implications. First, while previous tourism studies on tourists’ information search have tended to incorporate information search behavior in the context of vacation planning, this research demonstrated that the accumulation of product-related knowledge can be on a regular basis. Second, while previous tourism studies have a strong preference for the evaluative features of attitudes, this research demonstrated that attitude importance as a dimension of attitude strength is relevant in tourism. Finally, the experiential, health, and relaxation benefits were shown to have positive effects on travel behavior, which indicates that the tourism industry can encourage people to travel more by convincing them taking vacations is beneficial.

“Homeostatic beliefs” (HBs) denote a sense that one’s life path will remain stable in the long-term despite short-term disruptions. Two studies have been undertaken to explore whether HBs exist independent of other constructs, and to develop a scale with which to measure them. In Study 1, 158 undergraduate students completed a draft HB scale and theoretically related scales. Convergent and divergent validity were assessed with correlational and regression analyses: HBs are most strongly related to, but not redundant with, optimism, trait extraversion, and satisfaction with life. Using exploratory factor analysis, a six-item HB scale was derived. Study 2 is in progress, and will assess the construct validity of the HB scale by attempting to manipulate HBs to possibly influence individuals’ reactions to a mortality salience manipulation. We hypothesize that high HBs may buffer individuals from transient disrupting stimuli such as a mortality salience cue.

Grid computing is a virtualized distributed computing environment aimed at enabling the sharing of geographically distributed resources. Grid resources have traditionally consisted of dedicated supercomputers, clusters, or storage units. With the present ubiquitous network connections and the growing computational and storage capabilities of modem everyday-use computers, more resources such as PCs, devices (e.g., PDAs and sensors), applications, and services are on grid networks. Grid is expected to evolve from a computing and data management facility to a pervasive, world-wide resource-sharing infrastructure. To fully utilize the wide range of grid resources, effective resource discovery mechanisms are required. However, resource discovery in a global-scale grid is challenging due to the considerable diversity, large number, dynamic behavior, and geographical distribution of the resources. The resource discovery technology required to achieve the ambitious global grid vision is still in its infancy, and existing applications have difficulties in achieving both rich searchability and good scalability. In this thesis, we investigate the resource discovery problem for open-networked global-scale grids. In particular, we propose a distributed semantics-based discovery framework. We show how this framework can be used to address the discovery problem in such grids and improve three aspects of performance: expressiveness, scalability, and efficiency. Expressiveness is the first characteristic that a grid resource-searching mechanism should have. Most existing search systems use simple keyword-based lookups, which limit the searchability of the system. Our framework improves search expressiveness from two directions: First, it uses a semantic metadata scheme to provide users with a rich and flexible representation mechanism, to enable effective descriptions of desired resource properties and query requirements. Second, we employ ontological domain knowledge to assist in the search process. The system is thus able to understand the semantics of query requests according to their meanings in a specific domain; this procedure helps the system to locate only semantically related results. The more expressive the resource description and query request, however, the more difficult it is to design a scalable and efficient search mechanism. We ensure scalability by reconfiguring the network with respect to shared ontologies. This reconfiguration partitions the large unorganized search space into multiple well-organized semantically related sub-spaces that we call semantic virtual organizations. Semantic virtual organizations help to discriminatively distribute resource information and queries to related nodes, thus reducing the search space and improving scalability. To further improve the efficiency of searching the virtual organizations, we propose two semantics-based resource-integrating and searching systems: GONID and OntoSum. These two systems address searching problems for applications based on different network topologies: structured and unstructured peer-to-peer overlay networks. Queries in the search systems are processed in a transparent way, so that users accessing the data can be insulated from the fact that the information is distributed across different sources and represented with different formats. In both systems, ontological knowledge is decomposed into different coarse-grained elements, and then these elements are indexed with different schemes to fit the requirements of different applications. Resource metadata reasoning, integrating, and searching are based on the index. A complex query can be evaluated by performing relational operations such as select, project, and join on combinations of the indexing elements. We evaluate the performance of our system with extensive simulation experiments, the results of which confirm the effectiveness of the design. In addition, we implement a prototype that incorporates our ontology-based virtual organization formation and semantics-based query mechanisms. Our deployment of the prototype verifies the system's feasibility and its applicability to real-world applications.

The Multidimensional Model for Coping with Bullying (MMCB; Parris, in development) was conceptualized based on a literature review of coping with bullying and by combining relevant aspects of previous models. Strategies were described based on their focus (problem-focused vs. emotion-focused) and orientation (avoidance, approach – self, approach – situation). The MMCB provided the framework for the development of the Coping with Bullying Scale for Children (CBSC; Parris et al., 2011), which was administered as part of a research project in an urban, southeastern school district. The Student Survey of Bullying Behaviors – Revised 2 (SSBB-R2; Varjas et al., 2008) and the Behavior Assessment System for Children, 2nd Edition (BASC-2; Kamphaus & Reynolds, 2004) also were completed. The first research aim was to examine the factor structure of the CBSC in relation to the MMCB and investigate the relationship between coping style and student outcomes of depression, anxiety, and social stress. This study also examined the relationships between coping, victimization, and student engagement in bullying behavior, as well as the moderating effect of age, gender, and ethnicity on these relationships. The fourth research question was is there a relationship between student coping with bullying and their perceptions of control or self-reliance? Data analysis resulted in a four factor coping structure: constructive, externalizing, cognitive distancing, and self-blame. Externalizing coping was found to be a predictor of depression while constructive and self-blame coping was associated with more social stress. Self-blame also predicted higher rates of anxiety. Results indicated that more frequent victimization predicted the use of constructive and self-blame strategies, while students more often engaged in bullying behaviors indicated a higher use of externalizing and self-blame. Gender, age, and ethnicity were not found to be associated with levels of victimization, bullying behaviors, or the use of any of the four types of coping. Further, these demographic variables did not moderate the relationship between victimization and coping or bullying and coping. Finally, feelings of control were not associated with student coping; however, more self-reliance was predictive of constructive coping, cognitive distancing, and self-blame. Implications for future research and interventions for students involved in bullying are discussed.

In recent years the electric power industry has been challenged by a high level of uncertainty and volatility brought on by deregulation and globalization. A power producer must minimize the life cycle cost while meeting stringent safety and regulatory requirements and fulfilling customer demand for high reliability. Therefore, to achieve true system excellence, a more sophisticated system-level decision-making process with a more accurate forecasting support system to manage diverse and often widely dispersed generation units as a single, easily scaled and deployed fleet system in order to fully utilize the critical assets of a power producer has been created as a response. The process takes into account the time horizon for each of the major decision actions taken in a power plant and develops methods for information sharing between them. These decisions are highly interrelated and no optimal operation can be achieved without sharing information in the overall process. The process includes a forecasting system to provide information for planning for uncertainty. A new forecasting method is proposed, which utilizes a synergy of several modeling techniques properly combined at different time-scales of the forecasting objects. It can not only take advantages of the abundant historical data but also take into account the impact of pertinent driving forces from the external business environment to achieve more accurate forecasting results. Then block bootstrap is utilized to measure the bias in the estimate of the expected life cycle cost which will actually be needed to drive the business for a power plant in the long run. Finally, scenario analysis is used to provide a composite picture of future developments for decision making or strategic planning. The decision-making process is applied to a typical power producer chosen to represent challenging customer demand during high-demand periods. The process enhances system excellence by providing more accurate market information, evaluating the impact of external business environment, and considering cross-scale interactions between decision actions. Along with this process, system operation strategies, maintenance schedules, and capacity expansion plans that guide the operation of the power plant are optimally identified, and the total life cycle costs are estimated.

Related problems of string indexing and sequence analysis have been widely studied for a long time. Recently, researchers turn to consider extended versions of these problems, which provides more realistic applications. In this dissertation, we focus on three problems of recent interest, which are (1)the indexing problem for scaled strings, (2)the merged longest common subsequence problem and its variant with blocks, and (3)the sequence alignment problem with weighted constraints. The indexing problem for scaled strings asks one to preprocess a text string T, so that the matched positions of a pattern string P in T, with some scales £\ applied to P, can be reported efficiently. In this dissertation, we propose efficient algorithms for indexing real scaled strings, discretely scaled strings, and proportionally scaled strings. Our indexing algorithms achieve either significant improvements to previous results, or the best known results. The merged longest common subsequence (merged LCS) problem aims to detect the interleaving relationship between sequences, which has important applications to genomic and signal comparison. In this dissertation, we propose improved algorithms for finding the merged LCS. Our algorithms for finding the merged LCS are also more efficient than the previous results, especially for large alphabets. Finally, the sequence alignment problem with weighted constraints is a newly proposed problem in this dissertation. For this new problem, we first propose an efficient solution, and then show that the concept of weighted constraints can be further used to solve many constraint-related problems on sequences. Therefore, our results in this dissertation have significant contributions to the field of string indexing and sequence analysis.

The stigma scale (The Stigma Scale) can actually measure the degree of stigma of mental health problems nowadays. Although The Stigma Scale is a convenient and effective self-report assessment tool, there is no Chinese version in Taiwan. Therefore, this study aims to: (1) two stage translation of The Stigma Scale; (2) item analysis and streamline the number of items; (3)check the reliability and validity of the streamlining The Stigma Scale. Participants with chronic schizophrenia come from a psychiatric teaching hospital and a hospital center in south of Taiwan. After the exploratory factor analysis and the item analysis of the pre-test by 151 patients and the literature analysis, we found that the stigma of mental health problems includes three domains, discrimination, positive perception and disclosure. According to dimensions of analysis we retained 22 questions after selection, and test to 215 formal samples for confirmatory factor analysis, reliability and validity. Results showing: (1) The content validity is .92; (2) the internal consistency reliability after selection ranged from .83 ~ .93, one-month test-retest reliability Cronbach's coefficient ranged from .55 ~ .73; (3) confirmatory factor analysis showed that the "The Stigma Scale" has an acceptable model fit, ideal reliability and validity, and suitable for assessing the sense of the stigma of domestic patients with mental disorders. Also can be used on medical services and clinical assessment.