Occupational performance of children with autism spectrum disorder and quality of life of their mothers

Objectives Limited studies were found to investigate the occupational performance of autistic children and their parents’ quality of life. Therefore, this study aimed to investigate occupational performance of children with Autism Spectrum Disorder (ASD) and QoL of their mothers. Results In this study, 88 participants were selected from autism centers in Arak, Iran, 2020. The Canadian Occupational Performance Measure (COPM) and the parent version of Quality of Life in Autism Questionnaire (QoLA-P) were used to assess the occupational performance of ASD children and their mothers QoL. QoLA-P consists of parts A which is related to the quality of life and part-B related to the problems that these children have and are related to the parents or their caregivers. Regarding occupational performance, the first priority of mothers is self-care with frequency 64.8%. The finding suggested a significant correlation between total function score of COPM and the score of part-A (r = 0.227, p = 0.033) of QoLA-P. Also, the results revealed a significant correlation between the total satisfaction score of COPM and the score of part-A (r = 0.236, p = 0.026) and part-B of QoLA-P questionnaire (r = 0.231, p = 0.030). The mothers’ first priority is self-care and, the total satisfaction and function score of COPM showed a significant correlation with mothers’ QoL.

A two-sided gaming model for large-scale stable matching in sharing economy based on the probabilistic linguistic term sets

Sharing economy is significant for economic development, stable matching plays an essential role in sharing economy, but the large-scale sharing platform increases the difficulties of stable matching. We proposed a two-sided gaming model based on probabilistic linguistic term sets to address the problem. Firstly, in previous studies, the mutual assessment is used to obtain the preferences of individuals in large-scale matching, but the procedure is time-consuming. We use probabilistic linguistic term sets to present the preferences based on the historical data instead of time-consuming assessment. Then, to generate the satisfaction based on the preference, we regard the similarity between the expected preferences and actual preferences as the satisfaction. Considering the distribution features of probabilistic linguistic term sets, we design a shape-distance-based method to measure the similarity. After that, the previous studies aimed to maximize the total satisfaction in matching, but the individuals’ requirements are neglected, resulting in a weak matching result. We establish the two-sided gaming matching model from the perspectives of individuals based on the game theory. Meanwhile, we also study the competition from other platforms. Meanwhile, considering the importance of the high total satisfaction, we balance the total satisfaction and the personal requirements in the matching model. We also prove the solution of the matching model is the equilibrium solution. Finally, to verify the study, we use the experiment to illustrate the advantages of our study.

AI-driven Optimization in Healthcare: the Diagnostic Process

Purpose: Process optimization in healthcare using artificial intelligence (AI) is still in its infancy. In this study, we address the research question “To what extent can an AI-driven chatbot help to optimize the diagnostic process?” Design / Method / Approach: First, we developed a mathematical model for the utility (i.e., total satisfaction received from consuming a good or service) resulting from the diagnostic process in primary healthcare. We calculated this model using MS Excel. Second, after identifying the main pain points for optimization (e.g., waiting time in the queue), we ran a small experiment (n = 25) in which we looked at time to diagnosis, average waiting time, and their standard deviations. In addition, we used a questionnaire to examine patient perceptions of the interaction with an AI-driven chatbot. Findings: Our results show that scheduling is the main factor causing issues in a physician’s work. An AI-driven chatbot may help to optimize waiting time as well as provide data for faster and more accurate diagnosis. We found that patients trust AI-driven solutions primarily when a real (not virtual) physician is also involved in the diagnostic process. Practical Implications: AI-driven chatbots may indeed help to optimize diagnostic processes. Nevertheless, physicians need to remain involved in the process in order to establish patient trust in the diagnosis. Originality / Value: We analyze the utility to physicians and patients of a diagnostic process and show that, while scheduling may reduce the overall process utility, AI-based solutions may increase the overall process utility. Research Limitations / Future Research: First, our simulation includes a number of assumptions with regard to the distribution of mean times for encounter and treatment. Second, the data we used for our model were obtained from different papers, and thus from different healthcare systems. Third, our experimental study has a very small sample size and only one test-physician. Paper type: Empirical

Prevention Effects of Chain Management on Pressure Ulcers of Hospitalized Patients

The study focused on the preventive effects of the chain management model on pressure ulcers in the operating room. Sqoop big data collection module is used to collect patient information from various hospital information systems in a distributed manner. The data were from the clinical data center of the Zhongshan Hospital Xiamen University General Hospital, and 268 patients were selected as the research subjects. A chain management model is constructed, concerning the preventive measures, the management of each link, the perioperative pressure ulcer management, and the reporting of pressure ulcers. Then, the two groups were compared for the SAS and SDS scores before and after nursing, the pressure ulcer sites, pressure ulcer reporting rate, pressure ulcer staging, and nursing satisfaction. The results show that it is not that more collection modules will lead to better cluster performance and that the execution delay is caused by MapReduce requiring the JAVA virtual machine, and after reaching a certain point, the increase in the number of tasks will slow down the process, and as data size increases, DataNote has an expanded capability to analyze data. After nursing treatment, the SAS and SDS scores of the two groups of patients were significantly lower than before treatment ( P < 0.05 ). The pressure ulcers were mainly distributed in the forehead, mandible, cheeks, front chest, and knees in the two groups, and the difference between the two groups was statistically significant ( P < 0.05 ). The total satisfaction of the observation group was 93.28%, and the total satisfaction of the control group was 92.54%. The patients’ satisfaction with the chain management model was higher than that of conventional nursing.

Loyalty of Paratransit Users in the Era of Competition with Ride Sourcing

As a mode serving urban mobility in developing countries, paratransit is experiencing competition with the fast and massive growth of ride sourcing. This study aims to investigate the loyalty of paratransit users in Bandung, Indonesia, in the era of competition with ride sourcing. Data collected by questionnaires and distributed to 400 paratransit users in Bandung were analysed using hierarchical structural equation modelling. The analysis shows that satisfaction is positively influenced by service quality variables. Though there is less satisfaction compared to the previous decade, satisfaction with the service still has a positive influence on total satisfaction with the mode. It can also be concluded that loyalty is positively influenced by satisfaction. Satisfaction with the image and the unique characteristics of paratransit retains passengers' intentions toward loyalty in the future, including current personal characteristics (i.e., age, income, occupation) and travel characteristics (i.e., fare, vehicle ownership) of passengers. This study warns of the high probability of mode-changing behaviour from paratransit to another mode.

Influence of MRI on Diagnostic Efficacy and Satisfaction of Patients with Alzheimer’s Disease

Objective. To inquire into the influence of magnetic resonance imaging (MRI) on the diagnostic efficacy and satisfaction of patients with Alzheimer’s disease (AD). Methods. This study included 42 healthy people (control group) and 66 patients with AD (AD group). The hippocampus volume, temporal sulcus spacing, left-right brain diameter, brain lobe volume, hippocampal height, temporal horn width, lateral fissure width, and degree of leukoaraiosis were all measured using an MRI scan. After diagnosis, the satisfaction of patients in both arms was investigated and the satisfaction degree was recorded. Results. Compared with the control group, the left and right hippocampal volumes and hippocampal height of AD patients were smaller, while the temporal sulcus spacing, temporal horn width, lateral fissure width, and left-right brain diameter were remarkably higher. A statistical difference was present in the degree of leukoaraiosis between the two arms. The frontal and temporal lobe volumes of AD patients were notably lower while the volumes of parietal and occipital lobes were similar, versus the control group. The total satisfaction was 83.33% in the control group and 86.36% in the AD group, with no statistical difference between the two arms. Conclusions. MRI can effectively mine the brain information of AD patients with a high patient satisfaction, which has potential value in clinical application.

A User-Priority-Driven Multi-UAV Cooperative Reconnaissance Strategy

This paper considers a reconnaissance scenario where multiple unmanned aerial vehicles (UAVs) provide services cooperatively for multiple users with different priorities. Although users all expect to acquire their needed information in a short time, the degree of urgency to meet their demands is different when taking their diverse priorities into account. A priority-driven multiuser satisfaction model is designed, where users’ satisfaction is quantified based on their different priorities, information acquisition demands, and the time they obtain their desired information. To ensure high priority users’ fast information acquisition while avoiding excessive delay in low priority users’ information acquisition, a batchwise information backhaul strategy is adopted. In each batch, a UAV is selected as the data ferry through a consultative mechanism to carry information back to users. This reconnaissance process is formulated as a cooperative path planning problem, where the optimization objective is maximizing users’ total satisfaction, while an intelligent algorithm is proposed to solve this problem effectively. The simulation results show that compared with traditional path planning algorithms without considering user satisfaction, our proposed algorithm can guarantee faster information acquisition for users with higher priorities, which leads to higher satisfaction. In addition, the applicability of our proposed reconnaissance strategy and path planning algorithm in different situations is also analyzed.

Effect Observation of Process Diabetes Group Nursing on Patients with Diabetes Mellitus

Objective: Discuss the clinical effect of the process diabetes nurse group in the treatment of diabetes patients. Methods: A total of 58 patients with diabetes who received treatment in our hospital from January 2021 to June 2021 were selected, and the 58 patients were divided into two groups by random number table. In one group, 29 patients were treated with process diabetes group nursing, which was recorded as the observation group; in the other group, 29 patients were treated with conventional care, which was recorded as the control group. Nursing satisfaction, compliance behavior of patients, and adverse incidence were analyzed. Results: After nursing, the data of the two groups were summarized. The score of compliance behavior in the observation group was 91.23 ± 4.56, which was significantly better than that in the control group (75.13 ± 5.23). The t values of the score of compliance behavior were 12.4952, P < 0.05. The qualified rate of fasting blood glucose in the observation group was 100 %, which was significantly higher than that in the control group (62.07 %), P < 0.05. According to the questionnaire analysis, there were 18 patients in the observation group who were very satisfied, 8 patients who were satisfied and 3 patients who were not satisfied, with a total satisfaction rate of 89.66%, and in the control group, there were 4 patients who were very satisfied, 15 patients who were satisfied and 10 patients who were not satisfied, with a total satisfaction rate of 65.52%. The control group was significantly inferior to the observation group, and P< 0.05 was regarded as statistically significant. Conclusion: Adopting the process of diabetes group nursing can effectively enhance the compliance behavior of patients, and effectively control the blood sugar index of patients, and improve the satisfaction degree of patients.

The Influence of Sense of Community on Nursing Students: A Cross-Sectional Study on their Satisfaction in a Distance Learning Environment

Background: The COVID-19 pandemic has caused a sudden shift to distance learning. For many nursing students, distance learning was a new experience. Along with being an essential requirement for retaining students, developing a sense of community is a factor influencing students' success in distance learning. Assessments of the effectiveness of e-learning have been well documented in the literature. However, there is a dearth of research that assessed nursing students’ sense of community. This study aimed to assess students’ sense of community during e-learning, while determining its impact on their level of satisfaction. Methods: This cross-sectional descriptive study used convenience sampling to collect data via a student satisfaction survey and a classroom community scale. Nursing students were recruited from 13 public and private nursing programs in Saudi Arabia. Results: There was a positive and significant correlation between a sense of community and satisfaction with teaching (r = .269, p < .001), satisfaction with assessment (r = .258, p < .001), satisfaction with generic skills and learning experiences (r = .238, p < .001), and total satisfaction with e-learning (r = .07, p < .001). Students who perceived themselves as working collaboratively with their classmates and being more engaged in their learning were more satisfied with e-learning (p<.01). There were no significant variations in the participants’ satisfaction by age (β = −.06, p > .05) and sex (β = −.283, p > .05). However, school level was significantly correlated with satisfaction with e-learning. Specifically, students in lower levels of their nursing school had higher satisfaction rates with e-learning (95% CI [.08, 1.33], [F (3, 99) = 6.96, p < .001, β = −.335, R2 = .174]).Conclusions: Failing to meet student expectations can lead to low levels of student involvement. Thus, students’ engagement and satisfaction are good indicators of the quality and effectiveness of online programs. This study calls for further action through seminars and training sessions to introduce innovative teaching techniques and alternative assessment plans for learners in advanced levels. This study helps educational institutions devise strategies to enhance the level of interaction and cooperation among nursing students.

Improved Patient-Reported Medication Adherence, Patient Satisfaction, and Glycemic Control in a Collaborative Care Pharmacist-Led Diabetes “Tune-Up” Clinic

Diabetes complications remain a leading cause of death, which may be due to poor glycemic control resulting from medication nonadherence. The relationship between adherence status and HbA1c (glycemic control) has not been well-studied for clinical pharmacist interventions. This study evaluated medication adherence, patient satisfaction, and HbA1c, in a collaborative pharmacist-endocrinologist diabetes clinic over 6 months. Of 127 referred, 83 patients met the inclusion criteria. Mean medication adherence scores, considered “good” at baseline, 1.4 ± 1.2, improved by 0.05 points (p = 0.018), and there was a 26% increase in patients with good adherence. A significant improvement of 0.40 percentage points (95% CI: −0.47, −0.34) was observed in mean HbA1c across the three time points (p < 0.001). Mean total satisfaction scores were high and increased, with mean 91.3 ± 12.2 at baseline, 94.7 ± 9.6 at 3 months, and 95.7 ± 10.8 at 6 months (p = 0.009). A multimodal personalized treatment approach from a pharmacist provider significantly and positively impacted glycemic control regardless of self-reported medication adherence, and patient satisfaction remained high despite changing to a clinical pharmacist provider and increased care intensity.