• Social Workers
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• no.8 s.40
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• pp.40-41
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• 2005

• Social Workers
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• no.1 s.45
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• pp.42-43
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• 2006

• Social Workers
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• no.2 s.46
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• pp.44-45
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• 2006

• Social Workers
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• no.11 s.43
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• pp.44-45
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• 2005

• Social Workers
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• no.12 s.44
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• pp.46-47
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• 2005

• Social Workers
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• no.7 s.39
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• pp.38-39
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• 2005

• Journal of Digital Convergence
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• v.11 no.12
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• pp.639-647
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• 2013

This paper is a methodological research aimed at developing a mental disorder recovery scale (MDRS) and testing its validity and reliability. After three sessions of factor analysis, a total of three factors using an Eigen value of 1.0 or more were drawn. The explanatory power was found to be 58.1%. All the items met the criteria for communality and factor loading with no item removed, and, ultimately, 25 items were selected. Criterion-related validity test showed that Pearson's correlation coefficient was significant at .71 (p<.01) with significant correlation with each factor (p<.01). The reliability test showed that Cronbach's ${\alpha}$ coefficient was .95 and that Cronbach's ${\alpha}$ coefficient for each factor ranged from .87 to .93. MDRS, which was developed in this study and possessing 3 factors and 25 items, had both its validity and reliability confirmed; therefore, the developed scale would be useful to evaluate the recovery of individuals with mental disorder.

• Journal of Korea Society of Industrial Information Systems
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• v.13 no.5
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• pp.44-54
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• 2008

The objective of this research is to develop a measurement instrument for service recovery quality in the Internet commerce setting. To this same end, Parasuraman et al.(2005) have devised a scale called E-RecS-QUAL, which we revised and supplemented to develop another instrument named eSR-Q. To guarantee its reliability and validity, this instrument went through the refinement and validation processes for internal consistency and construct validity in terms of convergent, discriminant, and nomological validity. Our final scale consists of four dimensions including responsiveness, compensation, contact, and apologies altogether with fourteen measures. Overall, this research deals with the related research background, the scale development and validation processes, its limitations, and future research directions.

• Social Workers
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• no.9 s.41
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• pp.42-43
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• 2005

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.713-723
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• 2023

Climate change is significantly affecting coastal areas, and its impacts are expected to intensify. Recent studies on climate change adaptation and risk assessment in coastal regions increasingly integrate the concepts of recovery resilience and vulnerability. The aim of this study is to develop a measurement model for coastal hazard recovery resilience in the context of climate change adaptation. Before constructing the measurement model, a comprehensive literature review was conducted on coastal hazard recovery resilience, establishing a conceptual framework that included operational definitions for vulnerability and recovery resilience, along with several feedback mechanisms. The measurement model for coastal hazard recovery resilience comprised four metrics (MRV, LRV, RTSPV, and ND) and a Coastal Resilience Index (CRI). The developed indices were applied to domestic coastal erosion cases, and regional analyses were performed based on the index grades. The results revealed that the four recovery resilience metrics provided insights into the diverse characteristics of coastal erosion recovery resilience at each location. Mapping the composite indices of coastal resilience indicated that the areas along the East Sea exhibited relatively lower coastal erosion recovery resilience than the West and South Sea regions. The developed recovery resilience measurement model can serve as a tool for discussions on post-adaptation strategies and is applicable for determining policy priorities among different vulnerable regional groups.