• Journal of Korean Clinical Nursing Research
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• v.28 no.1
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• pp.76-87
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• 2022

Purpose: The purpose of this study was to examine the psychological distress related to quality of life (QoL) of patients with colorectal cancer receiving 5-fluorouracil (5-FU) chemotherapy at home with disposable Elastomeric infusion pumps. Methods: In this study, 179 colorectal outpatients were recruited between September 2019 and January 2021. National Cancer Center Psychological Symptom Inventory scores, general self-efficacy, and the EORTC QLQ-C30 scores were measured. Data were analyzed using Independent t-test, One-way ANOVA with Bonferroni post hoc analysis, and hierarchical multiple linear regression with the SPSS/WIN 26.0 programs. Results: The overall prevalence of psychological distress was 52.0% in colorectal patients. In multiple regression, psychological distress (β=-.20, p=.005), appetite loss (β=-.20, p=.001), chemotherapy cycles (β= .19, p=.002), fatigue (β=-.16, p=.035), physical functioning (β=-.16, p=.024), and emotional functioning (β=-.15, p=.025) were significant factors of QoL, and the final model explained 45.0% of the total variance of QoL. Conclusion: Supporting patients toward decreased psychological distress and increased physical and emotional functioning, especially in the first or second cycle of chemotherapy, could be used to improve their QoL. To consider the thresholds for clinical importance, it is necessary to increase the interpretation of psychological distress in clinical practice and further research.

• Information Systems Review
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• v.18 no.2
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• pp.173-198
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• 2016

Financial distress can damage stakeholders and even lead to significant social costs. Thus, financial distress prediction is an important issue in macroeconomics. However, most existing studies on building a financial distress prediction model have only considered idiosyncratic risk factors without considering systematic risk factors. In this study, we propose a prediction model that considers both the idiosyncratic risk based on a financial ratio and the systematic risk based on a business cycle. Ultimately, we build several IT artifacts associated with financial ratio and add them to the idiosyncratic risk factors as well as address the imbalanced data problem by using an oversampling technique and synthetic minority oversampling technique (SMOTE) to ensure good performance. When considering systematic risk, our study ensures that each data set consists of both financially distressed companies and financially sound companies in each business cycle phase. We conducted several experiments that change the initial imbalanced sample ratio between the two company groups into a 1:1 sample ratio using SMOTE and compared the prediction results from the individual data set. We also predicted data sets from the subsequent business cycle phase as a test set through a built prediction model that used business contraction phase data sets, and then we compared previous prediction performance and subsequent prediction performance. Thus, our findings can provide insights into making rational decisions for stakeholders that are experiencing an economic crisis.

• Research in Community and Public Health Nursing
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• v.32 no.1
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• pp.51-63
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• 2021

Purpose: This study aimed to develop an integrated health promotion program for cancer survivors residing in the community based on the shared care model, and evaluate its effectiveness. Methods: A quasi-experimental trial was conducted. The participants consisted of 35 cancer survivors with completed intensive cancer therapy at the cancer hospital. The intervention group (n=20) and the control group (n=15) were recruited from among a district home cancer patient registrations. The intervention group participated in an integrated health promotion program based on the MAPP (Mobilizing for Action through Planning and Partnership) development process. The program consisted of physical, psycho-social and body image units. The participants were assessed before the program, and immediately after the program. Data were collected between July 1 and September 2, 2018 using FACT-G quality of life (QOL), distress thermometer (DT), and resilience. The data were analyzed by performing a χ2 test, Fisher's exact test, Mann-Whitney test, and ranked ANCOVA using SPSS. Results: The intervention group reported a higher QOL overall and significantly higher social/family well-being than the control group. Distress was significantly lower in intervention group than in the control group. Resilience had no significant difference between the two groups. Conclusion: These findings indicate that the integrated health promotion program base on the shared care model and MAPP development process could be effective intervention for improving social/family well-being and the QOL, and reducing distress of cancer survivors at home. Community health center nurses need to provide intervention to support self-care competency for cancer survivors' comprehensive care with physical, psycho-social, and body image to help them adjust their life to a moderate risk group in the community.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.573-585
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• 2021

The banking sector is one of the most important sectors in Pakistan's struggling economy. Recent studies have recommended that suitable methods can be applied to predict bankruptcy. In this context, this work analyzes Pakistan's banking sector's financial status through the five-factor Altman Z-score model, which determines the probability of bankruptcy for an organization. Banking data has been collected through the Pakistan Stock Exchange (PSX) in the period 2013-2017. The Z-score assessment criteria is defined as: Z> 2.99 - "safe" zone; Z> 1.8 Z>2.98- "grey" zone; and Z <1.8 - "distress" zone. Results show good predictions for the local banking industry, while most foreign Pakistani banks were found bankrupt with the Z-score below 1.1. One of the financial risks investors face when investing in any company is the risk of bankruptcy. One of the most used models for predicting financial distress for any company is Altman's Z-score model. On the other hand, the Z-score analysis suggests that all banking establishments are not bankrupt because they have sufficient ability to control bankruptcy. At the same time, foreign banks failed financially and would not be able to be sustained in the future because they do not have the ability to pay the short-term and long-term debt.

• Journal of Korean Academy of Nursing
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• v.53 no.3
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• pp.309-323
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• 2023

Purpose: This study aimed to develop and test a model for posttraumatic growth among cured patients with COVID-19. This model was based on Calhoun and Tedeschi's Posttraumatic Growth model and a literature review. Methods: The participants comprised 223 patients cured from COVID-19 who were ≥ 19 years of age. The data were collected through an online questionnaire from March 21 to 24, 2022. The assessment tools included the Impact of Event Scale: Revised Korean version, the Connor-Davidson Resilience Scale, the Distress Disclosure Index, the Multidimensional Scale of Perceived Social Support, the Korean version of the Event-related Rumination Inventory, and the Korean version of the Post-traumatic Growth Inventory. Data were analyzed using the IBM SPSS version 24.0 and IBM AMOS 26.0. Results: The modified model showed appropriate goodness of fit (χ² = 369.90, χ² /degree of freedom = 2.09, SRMR = .09, RMESA = .07, CFI = .94, TLI = .93). The post-traumatic growth of cured patients with COVID-19 was explained through distress perception, self-disclosure, and deliberate rumination, with the explanatory power being 70.0%. Conclusion: This study suggests preparing a disaster psychology program involving experts who can activate deliberate rumination is necessary. Further, this study may serve as basic data for developing a program to enhance the post-traumatic growth of patients cured from COVID-19.

• Korean Journal of Social Welfare
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• v.67 no.2
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• pp.85-112
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• 2015

This study examined the relationship structure among personal and social cognitive factors contributing to professional help-seeking decisions to relieve distress of those in low-income, then suggested an appropriate model to inform knowledge for better social work practice. Using data of a purposive sampling from 331 low-income people, covariance structural analyses were conducted in two stages of model exploration, one for TPB model and another for its extended model including the level of distress, family support, and willingness. As results, in the path analyses with the observed variables of the basic components of the TPB, subjective norm showed the strongest effect on the intention, following by attitudes towards help-seeking, then behavioral control the least; in turn both the intention, positively, and behavioral control, negatively, contributed to help-seeking decisions. In the second stage of the path analyses with the extended model of the TPB, each of distress and family support demonstrated direct positive effect on each of attitudes, subjective norm, and behavioral control; each of the attitudes, subjective norm, and behavioral control showed positive effect on both intention and willingness; in turn, while intention showed strong positive effect on help-seeking decisions, willingness had no significant effect and behavioral control had negative effect on decisions. There were significant indirect effects of behavioral control on intention through willingness and of willingness on decisions through intention. These results suggested that the TPB model is useful for modeling help-seeking decisions through personal and social cognitions, especially the significance of subjective norm implied the importance of social cognition for the people in low-income with distress. Further, it was implied that the extended model needs to address particularity of those people in low-income and the mechanism shown by behavioral control and willingness implied the importance of practicing respect for the client's autonomy and will for self-support in social work practice.

• 한국도로학회:학술대회논문집
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• 2004.10a
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• pp.95-100
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• 2004

• International Journal of Highway Engineering
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• v.7 no.2 s.24
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• pp.77-86
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• 2005

A spalling model for jointed connote pavements(JCP) was developed using the data of distresses, climates, and materials at the sections of long-term pavement performance(LTPP) investigation. The total of forty-four spatting distress data was collected at twenty-two JCP LTPP sections in 1999 and in 2004. In addition, the data of climates, geometric shapes of the slabs, and material properties was also collected at those times. Factors significantly influencing the spalling distress were found by a sensitivity analysis for the data. Consequently, a spatting model was developed by a multi-regression analysis for the factors. The model showed reasonable trend of the spatting development comparing to other foreign models.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1451-1466
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• 2023

In the context of maritime emergencies, the utilization of drones has rapidly increased, with a particular focus on their application in search and rescue operations. Deep learning models utilizing drone images for the rapid detection of distressed vessels and other maritime drift objects are gaining attention. However, effective training of such models necessitates a substantial amount of diverse training data that considers various weather conditions and vessel states. The lack of such data can lead to a degradation in the performance of trained models. This study aims to enhance the performance of deep learning models for distress ship detection by developing a maritime environment simulator to augment the dataset. The simulator allows for the configuration of various weather conditions, vessel states such as sinking or capsizing, and specifications and characteristics of drones and sensors. Training the deep learning model with the dataset generated through simulation resulted in improved detection performance, including accuracy and recall, when compared to models trained solely on actual drone image datasets. In particular, the accuracy of distress ship detection in adverse weather conditions, such as rain or fog, increased by approximately 2-5%, with a significant reduction in the rate of undetected instances. These results demonstrate the practical and effective contribution of the developed simulator in simulating diverse scenarios for model training. Furthermore, the distress ship detection deep learning model based on this approach is expected to be efficiently applied in maritime search and rescue operations.

• Journal of Hospice and Palliative Care
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• v.3 no.1
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• pp.60-73
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• 2000

Purpose : The purpose of this study was to describe a total pain model in patients with terminal cancer and to identify factors relating to total pain using the Twycross Pain Management Model, which included physical, psycho-social and spiritual pain. Method : The study was a retrospective descriptive study. The first stage included 87 patients who received hospice service at Y hospital in 1997. The second stage included five model patients who suffer severe pain as selected by the four hospice nurses. Data collection was from 1) chart analysis and 2) in-depth interviews with the hospice nurses about their selected patients. Data analysis was performed using SPSS-WIN and content analysis. Result : 1) The main problems of 3 patient with terminal cancer were pain(77%), constipation (25.3%), family coping(35.6%), psycho-spiritual distress(17.2%)and other symptoms. 2. The Twycross model was a useful model. However, new items were added; loneliness, depression, and no improvement in condition as depression factors. In anger, new items were anger due to family neglect, at God and in relationships. The case studies identified the followsing; 1) Patient suffer from physical pain as well as multiple other symptoms when cancer is advanced. 2) Body concept, role change, threat to self concept, fear of pain, fear of death, anxiety, family conflict, financial burden, spiritual distress, hope for a cure, are all affected. Conclusion : 1) It is believed that the Twycross model is useful but further tests and revisions are necessary for deciding priorities in the care plan. 2) Pain management must improve culturally appropriate and family support, psychological, spiritual care are imperative for patient with terminal cancer. 3) Further study is recommended to test correlations of depression, anxiety, spiritual distress and family coping using valid instruments. A qualitative study on the spiritual journey of the patient with terminal cancer is also recommended.