Thesis (M.P.H.)--University of Hong Kong, 2009. / Includes bibliographical references (p. 36-38).

No description available.

The economic and public health benefits of improving return to work outcomes after workplace injury remain major goals for employers, injured workers and compensation administrators. A step to improving return to work outcomes is identifying which workers have the greatest risk of not being successful. While there has been considerable study in this area there has not been a bringing together of current knowledge, nor is there consensus regarding predictors of return to work. / The purpose of this Meta-Analytic review was to achieve the bringing together of current knowledge and to provide: greater understanding of predictive measures available, guide development of policy and procedures, increase usage of predictive measures as part of the service delivery model, progress the knowledge base about predictive measures, and renew interest in developing risk assessment tools and associated services to improve return to work outcomes for injured workers. / Eighty-four predictor variables were identified from thirty-four studies that researched return to work after workplace injury. The six most studied variables were then critically reviewed. The variables were age, sex, living arrangements, employment maintenance, delay to rehabilitation, and employment type. Due to the lack of statistical analysis, either undertaken or available in the literature, effect sizes and associated analysis was not undertaken. Based on the number of statistical findings, and on review of the articles, age, employment maintenance, and delay to rehabilitation demonstrated strong relationships with return to work. The variables of sex, living arrangements and employment type did not demonstrate such relationships. / While the current research brought together the current knowledge base the inability to quantitatively analyse previous results was a major limitation. It was recommended that ongoing research in this area ensures that analysis and publication of results provides information that would allow such secondary analysis in the future. It was also recommended that the current research focus on demographic variables be shifted to include a larger focus on prospective intervention based research. / Thesis (MRehabilitationCounselling)--University of South Australia, 2005.

Thesis (Ph. D., Education)--University of Idaho, December 2007. / Major professor: Lee Ostrom. Includes bibliographical references (leaves 96-104). Also available online (PDF file) by subscription or by purchasing the individual file.

Thesis (M.S.)--West Virginia University, 2009. / Title from document title page. Document formatted into pages; contains vi, 73 p. : ill., col. map. Includes abstract. Includes bibliographical references (p. 47-48).

Thesis (doctoral)--Philipp-Universität Marburg.

Thesis (doctoral)--Universität Erlangen.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 139-148). Also available in electronic version.

No description available.

The rapidly increasing loss of industrial accidents has become a big barrier to the development of modern industry. Therefore, safety and reliability in the industry should be treated seriously. Although there are many achievements in safety and reliability research, still many challenges are waiting for people to address. Human reliability is one of the most representative challenges. The source idea and methodology of human reliability are very different with facility reliability analysis, so in most system reliability analysis, facility reliability and human reliability are isolated with each other, and sometimes, human reliability is even neglected, which decrease the quality of system reliability analysis. However, according to many safety reports, human factors are always playing the root reason or one of the root reasons to activate the accidents. Regarding that, the integrated model, which involves human reliability and facility reliability, should be constructed. Therefore, in this Ph.D. research, a Markov chain based mathematical model, which contains human reliability and facility reliability, is established. Besides, only a simple model is not enough in solving the integrated reliability analysis problem, so the mathematical will be taken in optimization to find the best solutions for system reliability with the consideration on reliability requirements and budget requirements. Afterwards, based on the optimized result on human reliability, a Cognitive Reliability and Error Analysis Method (CREAM) based method is adopted to predict the real human reliability data, and if the real data fails to meet the optimized human reliability data, the CREAM will be used as a method to reasonably and logically provide a variety of human reliability promotion plans for people use. Finally, facing those plans, a decision supporting model should be built to help people choose the most reasonable plan for current use and future updating. Overall, an integrated model for both human and facility factors is constructed for industry use. This new proposed model has been tested on Beihai LNG Terminal in Guangxi China.