The Comparative Effectiveness of a Model of Job Development versus Treatment as Usual

Job development is critical to assisting people with serious disabilities to obtain jobs, but little is known about the actual methods that make job development effective. Using a post-only quasi-experimental design, this study examined the effects of the Conceptual Selling® method on the number of job development contacts and number of job placements. By controlling for employment specialists' characteristics (age, length of time in current position, years of human service experience, and years of business experience), the authors determined that the employment specialists trained in the Conceptual Selling® method had more job development contacts per employer, leading to more effective job placements for employers contacted, than the control group

3D Markov Process for Traffic Flow Prediction in Real-Time

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further

Challenges for Latina Breast Cancer Patient Survivorship Care in a Rural US-Mexico Border Region

Rural US Latina breast cancer patients experience language barriers, health literacy issues, and limited access to health care resources that negatively impact survivorship care. This study explored the challenges to survivorship care for rural Latina breast cancer (BC) patients and approaches to supporting survivorship care plans (SCP) from the stakeholders’ perspectives. Data were collected via eight focus groups (n = 40) and individual interviews (n = 4) with Latina BC patients, family caregivers, and health care professionals in a rural US-Mexico Border region. Interviews were audio-taped, transcribed, translated, and analyzed using thematic analysis. Themes related to the patient’s SCP challenges included: (1) lack of knowledge of treatment information, (2) lack of proactive health behavior, (3) gaps in information for care coordination, (4) psychological distress, and (5) difficulty retaining health information. Respondents expressed that the SCP document could fill patient information gaps as well as support patient communication with their clinicians and family. Rural BC patients demonstrated an acute need for information and active engagement in their survivorship care. The findings indicate the importance of addressing challenges for survivorship care on multiple dimensions: Cognitive, behavioral, social, and structural. Developing a culturally tailored SCP intervention will be imperative to support survivorship care

A Vision-Based Wayfinding System for Visually Impaired People Using Situation Awareness and Activity-Based Instructions

A significant challenge faced by visually impaired people is ‘wayfinding’, which is the ability to find one’s way to a destination in an unfamiliar environment. This study develops a novel wayfinding system for smartphones that can automatically recognize the situation and scene objects in real time. Through analyzing streaming images, the proposed system first classifies the current situation of a user in terms of their location. Next, based on the current situation, only the necessary context objects are found and interpreted using computer vision techniques. It estimates the motions of the user with two inertial sensors and records the trajectories of the user toward the destination, which are also used as a guide for the return route after reaching the destination. To efficiently convey the recognized results using an auditory interface, activity-based instructions are generated that guide the user in a series of movements along a route. To assess the effectiveness of the proposed system, experiments were conducted in several indoor environments: the sit in which the situation awareness accuracy was 90% and the object detection false alarm rate was 0.016. In addition, our field test results demonstrate that users can locate their paths with an accuracy of 97%

Nursing Students’ Experiences of Gratitude Journaling during the COVID-19 Pandemic

Gratitude journaling has been used to improve grateful disposition. However, there is only limited data available on its application experience. This study aimed to: (1) explore the experiences of nursing students who have participated in gratitude journaling; and (2) assess students’ views of gratitude journaling as a nursing intervention. This study implemented an eight-week program of gratitude journaling with fourth-year nursing students who took a mental health psychiatric nursing course at a South Korean university. Following the eight weeks, students reflected on their gratitude journaling experience in a reflective essay. Using content analysis, 53 essays were analyzed. Five categories were identified from the reflective essay, as follows: “A new beginning”, “The engine that motivates continued participation: gratitude sharing”, “The process driving change”, “Changes brought about by gratitude”, and “Self-reflection”. Based on this experience, nursing students believed that it is important to promote steady participation when administering gratitude journaling as a nursing intervention. The study findings suggest that the gratitude journaling not only helped with nursing students’ perspective, emotional, and behavioral aspects and stress management, but also provided an opportunity to advance a step further based on self-reflection

Survey Data Analysis on Intention to Use Shared Mobility Services

Shared mobility is a service that allows users to share various transportation modes and use them with reservations when necessary. It started with private automotive car-sharing and ride-sharing services. Currently, it operates on a wider range, including personal mobility devices such as electric bicycles and scooters. The purpose of this study is to derive a direction for providing future shared mobility services through analysis of factors affecting the usage intention of both current and prospective users. The survey targets 753 citizens living in Gyeonggi Province, Korea. The survey period is from February 12, 2020, to February 26, 2020. In this study, a logistic regression analysis is conducted to investigate the factors affecting the use intention of shared mobility. The analysis results show that gender, car ownership, and education, among variables reflecting socio-demographic characteristics, have significant effects on intention to use shared mobility. Moreover, we find that experience factors, including mainly used transportation modes, ownership of shared mobility device, past experience in similar services, satisfaction of existing shared mobility services, and distance from the home to the nearest bus stop, are also statistically influential. The analysis results are expected to lay the foundation for the introduction of shared mobility services and can be used as data for planning smart mobility services in the future

Do Older Korean Immigrants Engage in End-of-Life Communication?

End-of-life communication is an important process as it allows individuals\u27 treatment preferences to be known, yet not every culture is receptive to such discussions. Planning for end-of-life care is not readily supported in Asian culture, and little is known about individuals\u27 communication with family and health care professionals among older Korean immigrants related to end-of-life care. A cross-sectional study was conducted with 195 older Korean immigrants on end-of-life communication. Measures include end-of-life communication, attitudes toward end-of-life communication, perceived burden, number of adult children in the United States, health status, and sociodemographic variables. Overall, 21.9% (n = 42) of participants reported to have discussed their end-of-life treatment preferences with others, primarily family members. Attitudes toward end-of-life discussions, perceived burden, religiosity, and the number of children in the U.S. significantly accounted for end-of-life communication. Culturally appropriate interventions are recommended to promote dialogue regarding treatment preferences among older adults, family, and health care professionals

3D Markov Process for Traffic Flow Prediction in Real-Time

Recently, the correct estimation of traffic flow has begun to be considered an essential component in intelligent transportation systems. In this paper, a new statistical method to predict traffic flows using time series analyses and geometric correlations is proposed. The novelty of the proposed method is two-fold: (1) a 3D heat map is designed to describe the traffic conditions between roads, which can effectively represent the correlations between spatially- and temporally-adjacent traffic states; and (2) the relationship between the adjacent roads on the spatiotemporal domain is represented by cliques in MRF and the clique parameters are obtained by example-based learning. In order to assess the validity of the proposed method, it is tested using data from expressway traffic that are provided by the Korean Expressway Corporation, and the performance of the proposed method is compared with existing approaches. The results demonstrate that the proposed method can predict traffic conditions with an accuracy of 85%, and this accuracy can be improved further