Factors That Influence Self-Reported Health Changes With Caregiving

Objective: This study examined factors associated with the self-reported change in health status as a result of caregiving. Method: Multinomial logistic regression were performed to examine the sociodemographic characteristics, care recipients’ characteristics, and caregiving experiences that affect caregivers’ perceptions of health affected by caregiving using data from 1,087 caregiver respondents in the Caregiving in the U.S. 2015 data set. Data were collected through an online or telephone survey of randomly selected adults in 50 states. Results: Worsened self-reported health with caregiving occurred for caregivers aged 50 to 64, racial/ethnic minorities, those who lived within 20 min of the care recipient’s home, the presence of cognitive deficits, prolonged caregiving, and limited availability of accessible and affordable care services. Importantly, the feeling of choice in taking on care responsibilities was associated with an over fourfold increase in the odds ratio (OR) of better health in response to caregiving (OR = 4.21; confidence interval [CI] = [1.95, 9.08]; p \u3c .001). Discussion: Results suggest that improving accessibility of social service resources to assist caregivers in being better supported and having more choice in caregiving responsibilities may foster a positive change in health status with caregiving

Education Loans and Wealth Building Among Young Adults

This study examines the association between education loans and postcollege wealth accumulation among young adults. Data come from the 1997 National Longitudinal Survey of Youth, and the analyses control for a number of student characteristics, college experiences, and parental income. Results from a treatment-effect model indicate that having education loans upon leaving college is negatively related to postcollege net worth, financial assets, nonfinancial assets, and value of primary housing. Furthermore, having education loans also has a negative impact on the value of net worth among Black young adults. The relationship between the amount of education loans and wealth accumulation is not statistically significant among those with outstanding loans

An Event History Analysis of Educational Loans and College Graduation: A Focus on Differences by Race and Ethnicity

This study examines the association between educational loans and college graduation rates, with a focus on differences by race and ethnicity. Data come from the 1997 National Longitudinal Survey of Youth (NLSY97). Results from event history analyses that control for a number of student characteristics, college experiences, and financial resources indicate that educational loans are positively related to the rate of college graduation. Larger loan amounts tend to decrease the likelihood of college graduation. The relationship between educational loans and college graduation is stronger among minority (Black and Hispanic) students. Overall, there is little evidence that educational loans reduce racial and ethnic disparities in college graduation rates

Adoption and maintenance of health behaviors among middle-aged and older adults: the role of chronic disease diagnosis and depression

This study is a secondary-data analysis of adoption and maintenance of health behavior changes among U.S. middle-aged and older adults. This investigation focused on the impact of a chronic disease diagnosis on the likelihood of a health behavior change and whether the magnitude of change is modified by major or persistent depression prior to the chronic disease diagnosis. Further analyses assessed whether depression and a new chronic disease diagnosis affected long-term maintenance of health behaviors changes, once made. The study sample came from 1996-2010 waves of the Health and Retirement Study and consisted of 11,439 community-dwelling adults aged 50-80 years who were free of diabetes, heart disease, stroke, cancer, and chronic lung disease in 1996. Depression was measured by the 8-item Center for Epidemiologic Studies Depression Scale and the short form of the World Health Organization’s Composite International Diagnostic Interview. Chronic disease diagnosis was ascertained from self-reported physician diagnosis of a specific condition. Health behaviors included six dichotomous measures of current smoking status, drinking level (moderate or excessive), vigorous physical activity (≥ 3 times per week), receipt of influenza vaccination, blood test for cholesterol, prostate exam for men, and mammography for women. Matched case-control difference-in-differences estimator was used to estimate the effect of each chronic disease diagnosis on the likelihood of change in each health behavior. Mixed-effects logistic regression was applied to analyze the longitudinal impact of depression on health behaviors and to examine whether depression modified the impact of a chronic disease diagnosis on health behaviors. Kaplan-Meier estimator and the marginal risk set model were performed to assess the impact of a chronic disease diagnosis, depression, and their interaction on the likelihood of relapse after a health behavior change had been initiated. Middle-aged and older adults tended to reduce smoking and drinking, and increase utilization of preventive health services after a diagnosis of chronic disease. However, they reported a consistent decline in vigorous physical activity post diagnosis across disease conditions. Participants with major or persistent depression at baseline were more likely to remain smoking and less likely to engage in vigorous physical activity during the 14 years of follow-up. Depression also appeared to modify behavioral responses to a chronic disease diagnosis. Participants with depression experienced smaller increase in influenza vaccination utilization after a chronic disease diagnosis compared to their initially non-depressed counterparts. Depression did not seem to modify the impact of a new chronic disease on other health behaviors. The majority of middle-aged and older adults who initiated a health behavior change adhered to the change in the long-term. A new diagnosis of chronic disease did not appear to affect the likelihood of behavior maintenance. Chronic disease diagnosis may be an important teachable moment that can motivate individuals to spontaneously adopt risk-reducing health behaviors. More focused and intensive interventions are needed for those with chronic disease and comorbid depression to produce meaningful behavior change outcomes. Future research needs to elucidate the mechanisms through which chronic disease diagnosis affects health behaviors, develop and test the effectiveness of interventions utilizing the teachable moment effect of a chronic disease diagnosis, along with identifying population-based strategies to promote physical activity among adults with chronic disease

Rapid detection of bedding boundaries based on borehole images

Abstract The bedding is an important sedimentary structure phenomenon. The rock bedding structure, the direction of sedimentary transportation and the ancient sedimentary environment analysis can be studied by extracting the bedding boundaries and dips. Electric imaging logging can provide rich information of a borehole wall and circumference, which reflects formation resistivity variations. The bedding boundaries are detected by using the electrical imaging logging data based on an image recognition method in this paper. On an oriented, unwrapped image of a cylindrical borehole, the trace of a planar-bedding boundary appears as a sine wave. The bedding boundaries are detected by the recognition of the sine curves in borehole image. The influence problems of bedding boundary detection caused by fractures and other geological events are solved by statistical analysis technology. Through the techniques of the slope fitting, the speed and accuracy problems of bedding boundary detection are solved, which has good anti-interference performance. The processed results of the theoretical models and the measured borehole images at the varied dip segment indicate that the detected bedding boundaries reflect the real situation, which are identical to those derived by the Autodip

A Field Test of Popular Chatbots’ Responses To Questions Concerning Negative Body Image

Background: Chatbots are computer programs, often built upon large artificial intelligence models, that employ dialogue systems to enable online, natural language conversations with users via text, speech, or both. Body image, broadly defined as a combination of thoughts and feelings about one’s physical appearance, has been implicated in many risk behaviors and health problems, especially among adolescents and young adults. Little is known about how chatbots respond to questions about body image. Methods: This study assessed the responses of 14 widely-used chatbots (eight companion and six therapeutic chatbots) to ten body image-related questions developed upon validated instruments. Chatbots’ responses were documented, with qualities systematically assessed by nine pre-determined criteria. Results: The overall quality of the chatbots’ responses was modest (an average score of five out of nine), with substantial variations in the content and quality of responses across chatbots (individual scores ranging from one to eight). Companion and therapeutic chatbots systematically differed in their responses (e.g., focusing on comforting users vs. trying to identify the causes of negative body image and recommending potential remedies). Some therapeutic chatbots recognized potential mental health crises (self-harm) in test users’ messages. Conclusion: Substantial heterogeneities in the responses were present across chatbots and assessment criteria. Adolescents and young adults struggling with body image could be vulnerable to misleading or biased remarks made by chatbots. Still, the technical and supervision challenges to prevent those adverse consequences remain paramount and unsolved

Antonym-Synonym Classification Based on New Sub-space Embeddings

Distinguishing antonyms from synonyms is a key challenge for many NLP applications focused on the lexical-semantic relation extraction. Existing solutions relying on large-scale corpora yield low performance because of huge contextual overlap of antonym and synonym pairs. We propose a novel approach entirely based on pre-trained embeddings. We hypothesize that the pre-trained embeddings comprehend a blend of lexical-semantic information and we may distill the task-specific information using Distiller, a model proposed in this paper. Later, a classifier is trained based on features constructed from the distilled sub-spaces along with some word level features to distinguish antonyms from synonyms. Experimental results show that the proposed model outperforms existing research on antonym synonym distinction in both speed and performance

The constructive approach on existence of time optimal controls of system govered by nonlinear equations on Banach spaces

In this paper, a new approach to the existence of time optimal controls of system governed by nonlinear equations on Banach spaces is provided. A sequence of Meyer problems is constructed to approach a class of time optimal control problems. A deep relationship between time optimal control problems and Meyer problems is presented. The method is much different from standard methods