Caregivers' Burden on Patients with Dementia Having Multiple Chronic Diseases.

Purpose: This study aimed to find the caregiving burden level for patients with dementia who had multiple chronic diseases by simultaneously considering both patient and caregiver factors. Participants and Methods: A cross-sectional study with 284 patients with dementia having multiple chronic diseases managed by the dementia collaborative care team at Changhua Christian Hospital in Taiwan was conducted. The input variables were from patients, such as age, gender, mood symptoms, and behavioral and psychological symptoms, and caregivers, including age, relation to the patient, caregiver's mood, and caregiving burden. The Apriori algorithm was employed to determine the association between patient and caregiver factors and different caregiving burden levels by setting up the minimum support of 1% and confidence of 90% along with lift >1. Results: When caring for patients with dementia, twenty scenarios were found for caregivers with a severe burden. In addition, 1936 scenarios were related to caregivers with a moderate-to-severe burden. Specifically, there were eight scenarios for patients with three chronic diseases which could be further categorized into five general rules. Two hundred and fifty scenarios belonging to patients with two chronic diseases could be classified into 16 different combinations from eight chronic diseases of the database. Conclusion: Caregiver's mood, patients with mild dementia, and patients aged 75-84 years were associated with a severe caregiving burden. College and above education of the caregiver, the patient aged 85 years or more, and at least one of caregiver's moods were the variables to result in a moderate-to-severe burden for caregivers caring for patients with three multiple chronic diseases. Moreover, college and above education of the caregiver, mood symptom, age of the caregiver, and age of the patient were important variables for caregivers who had a moderate-to-severe burden taking care of patients with two chronic diseases.

Care Need Combinations for Dementia Patients with Multiple Chronic Diseases.

Purpose: The purpose of this study was to find care need combinations for dementia patients with multiple chronic diseases and their caregivers. Patients and Methods: A cross-sectional study was conducted with 83 patients who had multiple chronic diseases. Variables from patients included age, gender, severity of clinical dementia rating, feeding, hypnotics, mobility, getting lost, mood symptoms, and behavioral and psychological symptoms. Moreover, 26 types of care needs were included in this study. The Apriori algorithm was employed to first identify care need combinations and then to find the relationships between care needs and variables from dementia patients with multiple chronic diseases. Results: Six rules were generated for care need combinations. Four care needs could be formed as a basic care need bundle. Moreover, two additional care needs could be added to provide a wider coverage for patients. In the second stage, 93 rules were found and categorized into three groups, including 2, 6, and 28 general rules with support of 30% but less than 40%, 20% but less than 30%, and 10% but less than 20%, respectively. When the support value is 10% but less than 20%, more variables from patients were found in rules which help the dementia collaborative care team members provide tailor-made care need bundles. Conclusion: Four basic care needs were social resources referral and legal support (Care (1)), drug knowledge education (Care (3)), memory problem care (Care (5)), and fall prevention (Care (8)). Besides, disease knowledge education (Care (2)) and hypertension care (Care (16)) were frequent unmet needs in this specific population. Moreover, care for the mood of the caregiver (Care (11)) should be considered especially in dementia patients with preserved ambulatory function or with symptoms of hallucination. The collaborative care team should pay more attention to those care needs when assessing this specific population.

Applying Apriori algorithm to explore long-term care services usage status-Variables based on the combination of patients with dementia and their caregivers.

Purpose: The aim of this study was to identify the combination of patients with dementia and their caregivers' characteristics associated with long-term care (LTC) services usage. Patients and methods: A cross-sectional study was conducted with 475 patients with mild, moderate, and severe dementia at Changhua Christian Hospital, Taiwan. Eleven types of variables from patients with dementia, nine types of variables from patients' caregivers, and 15 types of LTC services were used for this study. The Apriori algorithm was employed to identify the attributes from the patients and their caregivers who used a particular LTC service from a comprehensive viewpoint. Results: A total of 75 rules were generated by the Apriori algorithm with support of 2%, confidence of 80%, and lift >1. Among these rules, 25 rules belonged to home personal care services which were summarized further into four general rules for home personal care services. On the other hand, 50 rules belonged to assistive devices that were summarized further into 21 general rules based on their similarities. Patient's walking ability, patient's emotional liability, unemployed or retired caregivers, caregivers' feelings with either helplessness or hopelessness, and caregivers who cared for patients with dementia solely were found to be the critical variables to use home personal care services. In contrast, patient's walking ability, age, and severity as well as caregivers' age, mood, marital status, caregiving burden, and the patient being cared for mainly by a foreign care helper were found to be the critical variables to use assistive devices. Conclusion: This study showed preliminary results on the LTC service usage from patients with dementia and their caregivers residing in the community. Understanding the patient-caregiver dyad's profile leads the service providers, policymakers, and the referral team to tailor service provisions better to meet the needs and identify the potential target groups. The findings in this study serve as references to reduce caregivers' burden as well as to improve the quality of care for patients with dementia.

Texture mapping with hard constraints using warping scheme.

Texture mapping with positional constraints is an important and challenging problem in computer graphics. In this paper, we first present a theoretically robust, foldover-free 2D mesh warping algorithm. Then we apply this warping algorithm to handle mapping texture onto 3D meshes with hard constraints. The proposed algorithm is experimentally evaluated and compared with the state-of-the-art method for examples with more challenging constraints. These challenging constraints may lead to large distortions and foldovers. Experimental results show that the proposed scheme can generate more pleasing results and add fewer Steiner vertices on the 3D mesh embedding.