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Background and Purpose: Patients with advanced noncancer diseases or advanced cancer diseases may experience similar symptom burdens during the end of their lives. This study aimed to evaluate the differences in receiving hospice care service and in receiving aggressive end-of-life care between patients who died of cancer diseases and those who died of noncancer diseases. Methods: This cross-sectional population-based study used data from the Taiwan National Health Insurance Research Database. Subjects who died of cancers or noncancer diseases from 2010 through 2019 were analyzed to identify the information on patient's characteristics, receipt of hospice care service, receipt of cardiopulmonary resuscitation (CPR) during the last hospitalization, and receipt of airway support interventions during the last hospitalization. The independent effects of various characteristics on the receipt of hospice care, CPR during the last hospitalization, and airway support interventions during the last hospitalization were evaluated using multivariate logistic regressions. Results: A total of 587,490 patients were included, of which 434,142 died of cancers and 153,348 died of noncancer diseases. There were significant trends of increase in receiving hospice care service and significant trends of decrease in receiving CPR or airway support interventions during the last hospitalization in both patients who died of cancers and those who died of noncancer diseases. Compared with patients who died of cancers, those who died of noncancer diseases were less likely to receive hospice care service (adjusted odds ratio [AOR]: 0.087; 95% confidence interval [CI]: 0.085–0.089) and had a higher risk of receiving CPR (AOR: 3.610; 95% CI: 3.521–3.704) or airway support interventions during the last hospitalization (AOR: 3.086; 95% CI: 3.021–3.165). Conclusions: Hospice care service should be promoted for all patients with end-stage diseases especially those with noncancer diseases. [ABSTRACT FROM AUTHOR]

This study investigates keyword extraction using a compiled Buddhist corpus. It sets out the fundamental mode of generation and refinement of keywords with statistical measures and manual screening with specific criteria. The Buddhist Word List contains 1244 keywords with 375 Pali words in Buddhist literacy. We compared the results of applying occurring frequency, log-likelihood (LL), and odds ratio (OR) in keyword analyses, each of which resulted in different keyword rankings. Our results show that statistical measures are useful for the identification of particular keywords in specific fields and OR is more effective in identifying technical terms. We demonstrate that multilevel keyword analysis is more effective at the identification of high-frequency technical words than either of these methods used alone. Multilevel methods are recommended for the creation of future domain-specific vocabulary lists to overcome the inherent flaws of individual analytic methods. [ABSTRACT FROM AUTHOR]

Principal instructional leadership (PIL) refers to the management of school curriculum, instruction, and assessment by the principal of a school. It is essential to measure the extent of the instructional leadership provided by principals and to propose means of improving instructional leadership. The principal instructional leadership scale (PILS) has been put forward to achieve these goals. In the current study, we validated the PILS on a sample of Taiwanese teachers using a multilevel approach involving expert reviews and three studies. Following two stages in confirmation of content validity by 20 experts, the initial 30-item PILS with five core concepts was subjected to discrimination analysis, exploratory factor analysis, and internal consistency reliability analysis utilizing SPSS 13.0 for Windows and AMOS 22.0 (n  =  339). This resulted in the deletion of nine items. In the second study, the individual item reliability of the remaining 21 items was examined, and the composite reliability, convergent validity, and discriminant validity confirmed the selection of the optimal model (n  =  672). The results of the third study (n  =  1438) supported metric invariance, scalar invariance, and factor variance-covariance invariance and confirmed scalar measurement invariance across genders. Finally, cross-validation analysis verified that the scale was stable and well-constructed. [ABSTRACT FROM AUTHOR]