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BackgroundUnguided, web-based psychoeducational interventions are gaining interest as a way to reach patients while reducing pressure on clinical resources. However, there has been little research on how patients with cancer use these interventions. ObjectiveThe objective of this analysis was to evaluate how women newly diagnosed with breast cancer used the unguided web-based, psychoeducational distress self-management program CaringGuidance After Breast Cancer Diagnosis while enrolled in a pilot feasibility study. MethodsWomen with stage 0 to II breast cancer diagnosed within the prior three months were recruited from clinics primarily in the Northeastern United States for participation in a 12-week pilot study of CaringGuidance plus usual care versus usual care alone. Usage prompts included sets of emails sent weekly for 12 weeks; standardized congratulatory emails after every two hours of program use, and informative emails for each cognitive-behavioral exercise. Individual user activity on the site was automatically tracked by an analytics system and recorded directly in the CaringGuidance database. ResultsComplete usage data were available for 54 subjects. Ninety-eight percent of the intervention group logged into CaringGuidance independently at least once. Thirty-eight (70%) logged in during all three months, 15 (28%) were intermittent users, and one (2%) was a non-user. Users (n=53) averaged 15.6 (SD 9.85) logins. Mean logins were greatest in month 1 (7.26, SD 4.02) and declined in months 2 (4.32, SD 3.66) and month 3 (4.02, SD 3.82). Eleven (21%) used CaringGuidance with both the frequency and activity level intended at study outset, 9 (17%) exceeded intended frequency and activity (high-high users), and 10 (19%) were below expected usage on both login frequency and activity (low-low users). Low-low users and high-high users differed significantly (P

Learning objects (LOs) are important online resources for both learners and instructors and usage for LOs is growing. Automatic LO tracking collects large amounts of metadata about individual students as well as data aggregated across courses, learning objects, and other demographic characteristics (e.g. gender). The challenge becomes identifying which of the many variables derived from tracked data are useful for predicting student learning. This challenge has prompted considerable research in the field of educational data mining and learning analytics. This work advances such research in four ways. First, we bring together two approaches for finding salient variables from separate research areas: hierarchical linear modeling (HLM) from education and Lasso feature selection from computer science. Second, we show that these two approaches have complimentary and synergistic results with some variables considers salient by both and others salient by only one. Third, and most importantly, we demonstrate the benefits of a combined approach that considers a variable salient when either HLM or Lasso consider that variable salient. This combined approach both improves model predictive accuracy and finds additional variables considered salient in previous datasets on student learning. Lastly, we use the results to provide insights into the salient variables to the learning outcome in undergraduate CS education. Overall, this work suggests a combined approach that improves the identification of salient variables in big data and also improves the design of LO tracking systems for learning management systems.

OBJECTIVE: A rural primary care clinic implemented an advance practice providers, including nurse practitioner (APRN)-led integrated behavioral health program to facilitate holistic health care delivery. METHODS: Implementation was facilitated by Health Resources and Services Administration Grant funding to a state University College of Nursing. The College formed an academic-practice partnership with a Federally Qualified Health Center (FQHC) to implement integrated care in a rural satellite clinic administered by the FQHC. An interdisciplinary team (two family APRNs, a psychiatric APRN, a licensed behavioral health provider, and the Grant Project Director who is a Psychiatric APRN and a licensed Psychologist) provided the integrated care based on the University of Washington's Collaborative Care Model. RESULTS: This brief report describes the implementation of integrated care during the clinic's first year, services provided, lessons learned, community response, and improvement in anxiety and depressive symptoms for patients who were treated for behavioral health problems. An exemplar illustrates how collaborative care addressed one patient's behavioral health and primary care needs. CONCLUSIONS: APRN-led collaborative care can expand access to holistic, affordable care in rural areas to improve mental health. Adaptation and flexibility in traditional roles may be necessary and determining post-grant access to funding for services will be necessary for sustainability. [ABSTRACT FROM AUTHOR]

Background: The impact of the COVID-19 pandemic on the mental health of healthcare workers throughout the world has been reported, but most studies have been cross-sectional and excluded the Midwestern U.S. healthcare workforce. Objective: This study aimed to longitudinally assess the psychological wellbeing and wellness strategies used by a Midwestern academic health system's workforce at multiple points throughout waves of the COVID-19 pandemic to inform ongoing implementation of appropriate wellness activities. Methods: An anonymous REDCap survey linked within our team-developed wellness education was posted in the employee online newsletter in April (T1), July (T2), October 2020 (T3), and May 2021 (T4). Surveys were open to all employees (approx. 9000) for approximately 12 days at each time point. Anxiety, depressive symptoms, stress, self-efficacy, and self-care activities were assessed. Following each data collection, team members discussed findings and planned wellness education implementation. Results: Response ranged from n = 731 (T1) to n = 172 (T4). Moderate to severe stress was reported by 29.5% (n = 203) of respondents at T1 and 34.0% (n = 108) at T2. At T3, all psychological symptoms significantly increased (p <.001) as COVID-19 surged, with 48.5% (n = 141) of respondents reporting moderate to severe stress. At T4, stress significantly declined (p <.001). Exercise was the most frequently reported coping strategy. Conclusions: Mental health symptoms reported by a Midwestern healthcare workforce increased during surges of COVID-19 hospitalizations. Individuals in non-patient contact roles experienced symptom levels similar to and at times with greater severity than healthcare personnel with patient contact roles. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to examine self-management of rural dwelling adults with multimorbidity. Sample: Participant sample (N=40) was recruited from 5 primary care clinics located in rural communities in the Midwestern United States. All participants resided in isolated rural communities based on zip code of residence (RUCA: 10). Methods: This cross-sectional descriptive study measured four self-management outcomes (self-efficacy, social support, self-regulation, patient activation) and perceptions of rural community dwelling adults with multimorbidity (N=40). All participants resided in rural/isolated rural communities designated as RUCA 10 (Rural-Urban Commuting Area [RUCA] code). Findings: Study sample was primarily female (n=32), Caucasian (n=40), with a mean age of 62.13 years of age (range 37-90). Participants self-reported multimorbidity (2-7 chronic conditions) differed significantly from care-based (ICD-10 medical record) multimorbidity (range of 2-11 chronic conditions). This sample self-reported high levels of self-efficacy, patient activation, and social support. However, low self-regulation ability was noted in this sample. Participants perceptions of multimorbidity focused primarily on the emotional effects and prioritization required for daily management. Conclusion: Findings from this study elucidate the self-management outcomes and perceptions of rural community dwelling adults with multimorbidity giving a voice to this population to better inform development of interventions tailored to their contextual needs. [ABSTRACT FROM AUTHOR]

Background: Nursing students are diverse in culture, abilities, and challenges. Universal Design for Learning is a logical and social model to support diverse learning methods. Accessibility tools help measure the efficacy of faculty efforts to make nursing courses accessible to all. Purpose: The study examines using accessibility software to measure faculty improvements and student engagement in nursing courses over 2 academic semesters. Methods: One hundred courses were analyzed 1 year apart for accessibility improvements by nursing faculty. Results: Course accessibility scores significantly rose year after year in almost all courses. Student usage also increased significantly. Lessons learned are presented. Conclusion: Accessibility improvements are worthwhile for enhancing inclusion in nursing programs and student engagement. [ABSTRACT FROM AUTHOR]

BACKGROUND: Women use various coping strategies to deal with stress and depression. These strategies are shaped by social contexts over the life course and may attenuate and/or exacerbate the physiologic effects of depression. AIMS: The purpose of this study was to determine whether coping strategies (active, disengaged, or social support coping) moderate depression-related diurnal cortisol dysregulation and to explore how social context influences women's use of coping. METHODS: This was a mixed-methods study of pregnant women (N = 65) during mid-pregnancy. Cortisol was measured in saliva collected during the waking hours of the day. Participants completed the Edinburgh Depression Scale and the Brief COPE. A subset of the sample participated in semistructured qualitative interviews (n = 20). RESULTS: Social support coping, but not active or disengaged coping, moderated end-of-day cortisol levels. Among depressed women, higher use of social support was associated with lower and more dynamic (i.e., less flat) diurnal cortisol rhythms. The qualitative findings revealed how complex social dynamics related to financial insecurity, lack of mutuality, and social identity affected women's use of and access to social support. CONCLUSION: These findings support theories of the stress-buffering effects of social support. Future research is needed to examine how social determinants affect access to social support, and how early life social experiences condition women's adaptive formation of social support coping strategies over the life course. Clinically, these findings underscore the value of relationship-centered nursing care for depressed women. [ABSTRACT FROM AUTHOR]

We examined emotional expressivity (i.e., happiness, sadness, and anger) and emotion regulation (regulation of exuberance, sadness, and anger) as they relate to academic functioning (motivation, engagement, and achievement). Also, we tested the premise that emotional expressivity and emotion regulation are indirectly associated with achievement through academic motivation and engagement. Participants included 417 elementary school students (M[subscript age] = 10 years; 52% female; 60% Black) and their teachers from a Midwestern metropolitan area. We used child and teacher questionnaires, and data were analyzed with structural equation modeling. Regarding emotionality, happiness was positively associated with multiple aspects of academic functioning whereas an inverse association was found for anger; sadness was not associated with academic functioning. Also, happiness and anger were indirectly related to achievement through academic engagement. Emotion regulation was positively associated with multiple aspects of academic functioning; it was also indirectly associated with achievement through engagement. Implications are discussed regarding how social and emotional learning programs in schools can further benefit from research on children's emotions.

Objective: To assess college students' knowledge and perception of cardiovascular risk factors and to screen for their cardiovascular risks. Participants: The final sample that responded to recruitment consisted of 158 college students from a midwestern university. Methods: A cross-sectional, descriptive study was performed using convenience sampling. Results: College students were knowledgeable about cardiovascular risk factors but did not perceive themselves at risk for cardiovascular disease (CVD). Knowledge of cardiovascular risk factors was correlated with the lifetime risk estimates (? = 0.17, p = 0.048), and perception of cardiovascular risk was positively associated with 30-year CVD risk estimates (? = 0.16, p = 0.048). More than 50% of the participants had 1 or more cardiovascular risk factors. Conclusions: High knowledge level of cardiovascular risk factors was not sufficient to lower cardiovascular risks within this study population, but changing perception of cardiovascular risk factors may play a bigger role in reducing long-term cardiovascular risks.

In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and use of propensity scores become a challenge. Traditional methods of propensity score estimation delete cases listwise. Missing data estimation, by multiple imputation, can be used to alleviate problems due to missing values, if performed correctly. Longitudinal studies are another situation where propensity score use may be difficult because of attrition and needing to account for data when propensities may vary over time. This article discusses the issues of missing data and longitudinal designs in the context of propensity scores. The syntax, datasets, and output used for these examples are available on http://jea.sagepub.com/content/early/recent for readers to download and follow.

Research Findings: This study reports the results of a randomized trial of a parent engagement intervention (the Getting Ready intervention) on directly observed learning-related social behaviors of children from low-income families in the context of parent-child interactions. The study explored the moderating effect of parental depression on intervention outcomes. Participants were 204 children and their parents as well as 29 Head Start teachers. Semistructured parent-child interaction tasks were videotaped 2 times annually over the course of 2 academic years. Observational codes of child behaviors included agency, persistence, activity level, positive affect, distractibility, and verbalizations. Practice or Policy: When gender and disability concerns were controlled, those in the treatment condition experienced a significant decline in activity level relative to children in the control group. Furthermore, compared to children of nondepressed mothers and to control children, those in the experimental condition whose parent reported elevated levels of depression showed greater gains in positive affect and in verbalizations.