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AnteayerNursing Research

Mediation of Self-Management and Treatment Adherence Health-Related Quality of Life for Adolescents With Congenital Heart Disease

imageBackground Improved autonomy, relatedness, competence, self-management, and treatment adherence have been linked to better health-related quality of life (HRQOL) in adolescents with chronic illnesses. Nonetheless, potential mediating relationships among these concepts have not been investigated. Mediation research is necessary to fully examine ways to improve health and other outcomes for adolescents living with chronic illnesses. Objectives The purpose of this study was to examine the relationship among the three innate needs (autonomy, relatedness, and competence) of the self-determination theory (SDT)—self-management and treatment adherence—and its relationship to HRQOL for adolescents with congenital heart disease (CHD). The current study examined the potential mediation effects of self-management and treatment adherence on the relationship between the three SDT variables on HRQOL. Methods Ninety-two adolescents with CHD completed self-report surveys (Basic Psychological Needs Autonomy and Relatedness subscales, Generalized Self-Efficacy Scale, UNC TRxANSITION Scale, and Pediatric Quality of Life 4.0 Generic Core Scale). Exploratory multiple regression and the bootstrap method were used to examine the relationship between the SDT variables and HRQOL and test whether these relationships were mediated by self-management and treatment adherence after controlling for covariates. Results The mediation hypothesis was not supported, indicating that self-management and treatment adherence do not mediate the relationship between the SDT variables and HRQOL for adolescents with CHD. However, multiple regression findings suggest optimizing autonomy and competence contributes to better self-management and treatment adherence and that better autonomy, competence, and relatedness improves HRQOL. Discussion The findings in this study indicate that studies with larger samples are needed if self-management and treatment adherence mediates the innate needs and HRQOL in adolescents with CHD. Future research focusing on other potential mediators affecting the relationship with HRQOL is warranted to improve the transition into adulthood.

Patient-Reported Outcomes for Function and Pain in Total Knee Arthroplasty Patients

imageBackground Some patients undergoing total knee arthroplasty successfully manage their condition postoperatively, whereas others encounter challenges in regaining function and controlling pain during recovery at home. Objective The aim of this study was to use traditional statistics and machine learning to develop prediction models that identify patients likely to have increased care needs related to managing function and pain following total knee arthroplasty. Methods This study included 201 patients. Outcomes were changes between baseline and follow-up in the functional and pain subcomponents of the Oxford Knee Score. Both classification and regression modeling were applied. Twenty-one predictors were included. Tenfold cross-validation was used, and the regression models were evaluated based on root-mean-square error, mean absolute error, and coefficient of determination. Classification models were evaluated based on the area under the receiver operating curve, sensitivity, and specificity. Results In classification modeling, random forest and stochastic gradient boosting provided the best overall metrics for model performance. A support vector machine and a stochastic gradient boosting machine in regression modeling provided the best predictive performance. The models performed better in predicting challenges related to function compared to challenges related to pain. Discussion There is valuable predictive information in the data routinely collected for patients undergoing total knee arthroplasty. The developed models may predict patients who are likely to have enhanced care needs regarding function and pain management. Improvements are needed before the models can be implemented in routine clinical practice.

Dissertation Topics in Nursing

imageBackground Few quantitative studies have documented the types of research topics most commonly employed by nursing PhD students and whether they differ by program delivery (in-person vs. online/hybrid programs). Objectives We examined a large set of publicly available PhD dissertation abstracts to (a) describe the relative prevalence of different research topics and methods and (b) test whether the primary topics and methods used differed between online or hybrid and in-person PhD programs. A secondary goal was to introduce the reader to modern text-mining approaches to generate insights from a document corpus. Methods Our database consisted of 2,027 dissertation abstracts published between 2015 and 2019. We used a structural topic modeling text-mining approach to explore PhD students’ research topics and methods in United States-based doctoral nursing programs. Results We identified 24 different research topics representing a wide range of research activities. Most of the research topics identified did not differ in prevalence between online/hybrid and in-person programs. However, online/hybrid programs were more likely to engage students in research focused on nursing education, professional development, work environment, simulation, and qualitative analysis. Pediatrics, sleep science, older adults and aging, and chronic disease management were more prevalent topics in in-person-only programs. Discussion The range of topics identified highlights the breadth of research nursing PhD students’ conduct. Both in-person and online/hybrid programs offer a range of research opportunities, although we did observe some differences in topic prevalence. These differences could be due to the nature of some types of research (e.g., research that requires an in-person presence) or differences in research intensity between programs (e.g., amount of grant funding or proximity to a medical center). Future research should explore why research topic prevalence may vary by program delivery. We hope that this text-mining application serves as an illustrative example for researchers considering how to draw inferences from large sets of text documents. We are particularly interested in seeing future work that might combine traditional qualitative approaches and large-scale text mining to leverage the advantages of each.

Urination Frequency Ranges in Healthy Women

imageBackground Limited information on the normal range of urination frequencies in women is available to guide bladder health promotion efforts. Objectives This study used data from the Boston Area Community Health (BACH) Survey to (a) estimate normative reference ranges in daytime and nighttime urination frequencies in healthy women based on two operational definitions of “healthy” and (b) compare urination frequencies by age, race/ethnicity, and fluid intake. Methods A secondary analysis of cross-sectional interview data collected from female participants was performed using less restrictive (“healthy”) and strict (“elite healthy”) inclusion criteria. All analyses were weighted to account for the BACH sampling design. Normative reference values corresponding to the middle 95% of the distribution of daytime and nighttime urination frequencies were calculated overall and stratified by age, race/ethnicity, and fluid intake. Generalized linear regression with a log-link was used to estimate rate ratios of daytime and nighttime urination frequencies by age, race/ethnicity, and fluid intake. Results Of the 2,534 women who completed the BACH follow-up interviews, 1,505 women met healthy eligibility criteria, and 300 met elite healthy criteria. Overall, reference ranges for urination frequencies were 2–10 times/day and 0–4 times/night in healthy women and 2–9 times/day and 0–2 times/night in elite healthy women. Women ages 45–64 years, but not 65+ years, reported a greater number of daytime urination than those aged 31–44 years, whereas women 65+ years reported a greater number of nighttime urination. Black women reported fewer daytime urination and more nighttime urinations than White women. Women who consumed less than 49 oz daily reported fewer daytime and nighttime urinations than those who drank 50–74 oz; drinking 75+ oz had only a small effect on urination frequencies. Discussion Normative reference values for daytime and nighttime urination frequencies were similar in women using strict and relaxed definitions of health. These results indicate a wide range of “normal” urination frequencies, with some differences by age, race/ethnicity, and fluid intake. Future research is needed to examine urination frequencies in minority women and whether fluid intake amount and type influence the development of lower urinary tract symptoms.

Supply Chain for Nursing Science

Por: Pickler · Rita H.
No abstract available

Study Protocol to Evaluate Influences of Stress and Inflammation on Mucositis in Adolescents and Young Adults With Cancer

imageBackground Adolescent and young adult (AYA) cancer diagnoses are rising, and gains in survivorship are falling behind for this age group. Dose-limiting toxicities of therapy, including mucositis, are more frequent in this age group and may be contributing to poorer survivorship. Animal models and observational studies suggest that stress and inflammation may be contributing to the high prevalence of dose-limiting mucositis in this age demographic. The AYA oncology population has been an overlooked and underresearched oncology demographic, leading to poor understanding of why this age group has high side-effect burdens and poorer cancer survival. Objectives This article describes a novel, prospective clinical study in AYAs receiving chemotherapy designed to evaluate if stress at the time of chemotherapy administration predicts the development of dose-limiting mucositis and determines if stress-induced inflammatory profiles mediate this relationship. This is the first study to translate these stress and inflammation findings from animal models to a nurse-centered research design in humans. Methods Persons aged 15–39 years who are receiving chemotherapy with a significant (>20%) risk of developing mucositis will be recruited for a prospective study. Baseline stress is measured through participant questionnaires, and blood is collected to analyze for inflammatory markers. Participants receive chemotherapy as clinically planned and complete a daily survey of mucositis symptoms for 14 days after chemotherapy. Regression and mediation analysis will determine if stress and inflammatory profiles predict the development of dose-limiting mucositis. Results This model of inquiry through a nursing framework uses a biobehavioral model that considers physiological and psychological risk factors for chemotherapy toxicities. This study is also an important translational science study essential in bringing data from laboratory studies to the clinical arena. The study may also be important to implementation science because assessing the ability of critically ill individuals to participate in low-burden clinical studies may yield essential findings to improve care delivery. Discussion Findings from this work will identify potentially modifiable factors that may be manipulated to minimize chemotherapy toxicities and lead to improved survival. Data from this study will inform larger research endeavors to better understand symptom development in this high-risk oncological population.

Latent Profile/Class Analysis Identifying Differentiated Intervention Effects

imageBackground The randomized clinical trial is generally considered the most rigorous study design for evaluating overall intervention effects. Because of patient heterogeneity, subgroup analysis is often used to identify differential intervention effects. In research of behavioral interventions, such subgroups often depend on a latent construct measured by multiple correlated observed variables. Objectives The purpose of this article was to illustrate latent class analysis/latent profile analysis as a helpful tool to characterize latent subgroups, conduct exploratory subgroup analysis, and identify potential differential intervention effects using clinical trial data. Methods After reviewing different approaches for subgroup analysis, latent class analysis/latent profile analysis was chosen to identify heterogeneous patient groups based on multiple correlated variables. This approach is superior in this specific scenario because of its ability to control Type I error, assess intersection of multiple moderators, and improve interpretability. We used a case study example to illustrate the process of identifying latent classes as potential moderators based on both clinical and perceived risk scores and then tested the differential effects of health coaching in improving health behavior for patients with elevated risk of developing coronary heart disease. Results We identified three classes based on one clinical risk score and four perceived risk measures for individuals with high risk of developing coronary heart disease. Compared to other classes we assessed, individuals in the class with low clinical risk and low perceived risk benefit most from health coaching to improve their physical activity levels. Discussion Latent class analysis/latent profile analysis offers a person-centered approach to identifying distinct patient profiles that can be used as moderators for subgroup analysis. This offers tremendous opportunity to identify differential intervention effects in behavioral research.

A Multilevel Approach to Investigate Relationships Between Healthcare Resources and Lung Cancer

imageBackground Screening for lung cancer is an evidence-based but underutilized measure to reduce the burden of lung cancer mortality. Lack of adequate data on geographic availability of lung cancer screening inhibits the ability of healthcare providers to help patients with decision-making and impedes equity-focused implementation of screening-supportive services. Objectives This analysis used data from the 2012–2016 Surveillance, Epidemiology, and End Results (SEER) Program, the Behavioral Risk Factor Surveillance System, and the county health ranking to examine (a) which cancer resources and county-level factors are associated with late-stage lung cancer at diagnosis and (b) associations between county rurality and lung cancer incidence/mortality rates. Methods Using the New York state SEER data, we identified 68,990 lung cancer patients aged 20–112 years; 48.3% had late-stage lung cancers, and the average lung cancer incidence and mortality rates were 70.7 and 46.2 per 100,000, respectively. There were 144 American College of Radiology-designated lung cancer screening centers and 376 Federally Qualified Health Centers identified in New York state. County rurality was associated with a higher proportion of late-stage lung cancers and higher lung cancer mortality rates. Discussion Visual geomapping showed the scarcity of rural counties’ healthcare resources. County rurality is a significant factor in differences in lung cancer screening resources and patient outcomes. Use of publicly available data with geospatial methods provides ways to identify areas for improvement, populations at risk, and additional infrastructure needs.

Exploratory Analysis of Associations Between Whole Blood Mitochondrial Gene Expression and Cancer-Related Fatigue Among Breast Cancer Survivors

imageBackground Cancer-related fatigue is a prevalent, debilitating, and persistent condition. Mitochondrial dysfunction is a putative contributor to cancer-related fatigue, but relationships between mitochondrial function and cancer-related fatigue are not well understood. Objectives We investigated the relationships between mitochondrial DNA (mtDNA) gene expression and cancer-related fatigue, as well as the effects of fish and soybean oil supplementation on these relationships. Methods A secondary analysis was performed on data from a randomized controlled trial of breast cancer survivors 4–36 months posttreatment with moderate–severe cancer-related fatigue. Participants were randomized to take 6 g fish oil, 6 g soybean oil, or 3 g each daily for 6 weeks. At pre- and postintervention, participants completed the Functional Assessment of Chronic Illness Therapy–Fatigue questionnaire and provided whole blood for assessment of mtDNA gene expression. The expression of 12 protein-encoding genes was reduced to a single dimension using principal component analysis for use in regression analysis. Relationships between mtDNA expression and cancer-related fatigue were assessed using linear regression. Results Among 68 participants, cancer-related fatigue improved and expression of all mtDNA genes decreased over 6 weeks with no effect of treatment group on either outcome. Participants with lower baseline mtDNA gene expression had greater improvements in cancer-related fatigue. No significant associations were observed between mtDNA gene expression and cancer-related fatigue at baseline or changes in mtDNA gene expression and changes in cancer-related fatigue. Discussion Data from this exploratory study add to the growing literature that mitochondrial dysfunction may contribute to the etiology and pathophysiology of cancer-related fatigue.

Reviewer List

No abstract available

Association of Fear of Falling With Cognition and Physical Function in Community-Dwelling Older Adults

imageBackground Fear of falling (FOF) might be associated with physical and cognitive function, but there is a lack of understanding of the specific relationship between the three variables. Objectives The aim of this study was to accurately investigate the association of FOF with cognitive and physical function in community-dwelling older adults. Methods Six hundred sixty-nine older adults (>60 years old) participated in this study. A self-report questionnaire collected information about demographic characteristics, lifestyle, and behavioral habits. FOF was evaluated through the Shortened Version of the Falls Efficacy Scale International. Global cognitive function and the subdomains of cognitive function (including memory, visual–spatial, language, attention, and executive function) were assessed using the Montreal Cognitive Assessment scale, the Auditory Verbal Learning Test, the Clock Drawing Test (CDT), the Verbal Fluency Test, and the Trail Making Test. Subjective memory complaints were assessed using the Subjective Memory Complaints Questionnaire. Physical function was evaluated by measuring muscle strength and balance ability, and muscle strength was indicated by hand grip strength. In contrast, balance was assessed using the Timed Up and Go (TUG) Test. Results After adjustment for potential confounding factors, the linear or ordinal regression analysis showed that the values of hand grip strength, Montreal Cognitive Assessment, Auditory Verbal Learning Test, and CDT were significantly and negatively correlated with the score of FOF. On the other hand, Subjective Memory Complaints Questionnaire and TUG Test values showed significant positive correlations with FOF scores. Moreover, compared with other cognitive or physical measures, the CDT and TUG Test values showed a greater association with the FOF scores. Discussion Low subjective or objective cognitive ability and low physical function, especially low visuospatial and balance ability, were positively associated with the risk of FOF in a community-dwelling older population.

Sex Differences in Depressive Symptom Networks Among Community-Dwelling Older Adults

imageBackground Compared to male individuals, an increased prevalence of depression has been reported in older female individuals consistently over time. Sex (male/female) differences in depressive symptom networks may help explain the underlying causes of this increased vulnerability for female individuals. Objective This cross-sectional study investigated the sex (male/female) differences in depressive symptom networks among community-dwelling older adults in South Korea. Methods The analysis was based on the 2019 Korean Community Health Survey data targeting adults aged 65 years or older. Using network analysis, depressive symptom networks were constructed according to the items listed in the Patient Health Questionnaire-9 for propensity score-matched male and female groups. Strength centrality and network stability were tested. A network comparison test was performed to investigate the difference between the networks based on the invariance of global strength, network structure, edge strength, and specific centrality measures. Results Symptoms central to the network were similar between sexes, which were suicidal ideation, hopelessness, and psychomotor retardation/agitation. However, the global structure and network structure differed between sexes. The female symptom network showed more strengthened edges. Notably, four edges—loss of interest–hopelessness, sleep disturbance; low energy/fatigue; loss of interest–concentration difficulty; and worthlessness–concentration difficulty—were more pronounced in the female network. Strength centrality did not differ between the two networks. Discussion Our results may help guide future research and clinical interventions for female depression. In addition, educating health professionals on the differences in depressive symptom presentation will be crucial to ensuring that older female adults receive appropriate treatment.

Detecting Language Associated With Home Healthcare Patient’s Risk for Hospitalization and Emergency Department Visit

imageBackground About one in five patients receiving home healthcare (HHC) services are hospitalized or visit an emergency department (ED) during a home care episode. Early identification of at-risk patients can prevent these negative outcomes. However, risk indicators, including language in clinical notes that indicate a concern about a patient, are often hidden in narrative documentation throughout their HHC episode. Objective The aim of the study was to develop an automated natural language processing (NLP) algorithm to identify concerning language indicative of HHC patients’ risk of hospitalizations or ED visits. Methods This study used the Omaha System—a standardized nursing terminology that describes problems/signs/symptoms that can occur in the community setting. First, five HHC experts iteratively reviewed the Omaha System and identified concerning concepts indicative of HHC patients’ risk of hospitalizations or ED visits. Next, we developed and tested an NLP algorithm to identify these concerning concepts in HHC clinical notes automatically. The resulting NLP algorithm was applied on a large subset of narrative notes (2.3 million notes) documented for 66,317 unique patients (n = 87,966 HHC episodes) admitted to one large HHC agency in the Northeast United States between 2015 and 2017. Results A total of 160 Omaha System signs/symptoms were identified as concerning concepts for hospitalizations or ED visits in HHC. These signs/symptoms belong to 31 of the 42 available Omaha System problems. Overall, the NLP algorithm showed good performance in identifying concerning concepts in clinical notes. More than 18% of clinical notes were detected as having at least one concerning concept, and more than 90% of HHC episodes included at least one Omaha System problem. The most frequently documented concerning concepts were pain, followed by issues related to neuromusculoskeletal function, circulation, mental health, and communicable/infectious conditions. Conclusion Our findings suggest that concerning problems or symptoms that could increase the risk of hospitalization or ED visit were frequently documented in narrative clinical notes. NLP can automatically extract information from narrative clinical notes to improve our understanding of care needs in HHC. Next steps are to evaluate which concerning concepts identified in clinical notes predict hospitalization or ED visit.

Neural Processing of Health Information and Hypertension Self-Management in African Americans

imageBackground Uncontrolled blood pressure (BP) rates are persistently high among African Americans with hypertension. Although self-management is critical to controlling BP, little is known about the brain–behavior connections underlying the processing of health information and the performance of self-management activities. Objectives In this pilot study, we explored the associations among neural processing of two types of health information and a set of self-management cognitive processes (self-efficacy, activation, decision-making, and hypertension knowledge) and behaviors (physical activity, dietary intake, and medication taking) and health status indicators (BP, health-related quality of life, anxiety, and depression). Methods Using a descriptive cross-sectional design, 16 African Americans with uncontrolled hypertension (mean age = 57.5 years, 68.8% women) underwent functional magnetic resonance imaging to assess activation of two neural networks, the task-positive network and the default mode network, and a region in the ventromedial prefrontal cortex associated with emotion-focused and analytic-focused health information. Participants completed self-reports and clinical assessments of self-management processes, behaviors, and health status indicators. Results Our hypothesis that neural processing associated with different types of health information would correlate with self-management cognitive processes and behaviors and health status indicators was only partially supported. Home diastolic BP was positively associated with ventromedial prefrontal cortex activation (r = .536, p = .09); no other associations were found among the neural markers and self-management or health status variables. Expected relationships were found among the self-management processes and behaviors and health status indicators. Discussion To advance our understanding of the neural processes underlying health information processing and chronic illness self-management, future studies are needed that use larger samples with more heterogeneous populations and additional neuroimaging techniques.

Symptom Clusters and Key Symptoms Among Midlife Perimenopausal and Postmenopausal Women With and Without Metabolic Syndrome

imageBackground Midlife perimenopausal and postmenopausal women with metabolic syndrome experience multiple symptoms concurrently. Objective The study objectives were to examine the relationship among symptoms through network visualization and identify and compare symptom clusters and key symptoms across symptom occurrence and symptom severity dimensions in midlife perimenopausal and postmenopausal women with and without metabolic syndrome. Methods Cross-sectional data from the Study of Women’s Health Across the Nation (Visit 5) were used for analysis. A machine-learning-based network analysis and the Walktrap algorithm were used to fulfill the study objectives. Results The number and types of symptom clusters differed between the groups. Midlife perimenopausal and postmenopausal women with metabolic syndrome experienced the psychological/somatic/genital cluster (key symptom: frequent mood change), the sleep/urinary cluster (sleep disturbance), and the vasomotor cluster (cold sweat) in the symptom occurrence dimension and the psychological/somatic/sexual cluster (anxiety), the sleep/urinary cluster (sleep disturbance), and the vasomotor/genital cluster (night sweat) in the symptom severity dimension. In contrast, midlife perimenopausal and postmenopausal women without metabolic syndrome experienced the psychological cluster (anxiety), the sleep/somatic/genitourinary cluster (sleep disturbance), and the vasomotor cluster (night sweat) in the symptom occurrence dimension and the psychological/somatic cluster (anxiety), the sleep/urinary cluster (sleep disturbance), the vasomotor cluster (night sweat), and the sexual/genital cluster (vaginal dryness) in the symptom severity dimension. Discussion The study findings may serve as a knowledge basis for effective assessment and management of symptom clusters and key symptoms in clinical settings and provide directions for future development of targeted symptom management interventions.

Lifestyle Behaviors and Parents’ Mental Well-Being Among Low-Income Families During COVID-19 Pandemic

imageBackground The coronavirus 2019 (COVID-19) pandemic has negatively altered many families’ lifestyles and the mental well-being of parents, especially those who have a low income and young children. To improve low-income parents’ mental well-being, especially during a pandemic, understanding parents’ and children’s lifestyle behaviors and the relationship between their lifestyle behaviors and parents’ mental well-being is essential. Objective This cross-sectional study examined relationships between lifestyle behaviors (sleep, physical activity, screen time, and eating behavior of parents and children) and low-income parents’ well-being (stress, anxiety, and depression) during COVID-19. Methods Parents were recruited from two Michigan Head Start organizations as well as across the United States; 408 parents completed an online survey. Demographic characteristics were assessed, along with parents’ sleep, physical activity, screen time, and dietary intake; stress, anxiety, and depression were also examined. Children’s sleep time, physical activity, screen time, and fruit/vegetable intake were assessed. Descriptive statistics, correlations, and the multivariate general linear model procedure were used. Results Approximately 69.4% of parents reported moderate stress levels, and 17.2% reported high levels. Most parents had sleep disturbances, attained minimal physical activity, and consumed 2 hours per day. Only 41% of preschoolers were active 7 days a week and slept ≥10 hours per day. Two thirds had >2 hours per day of screen time, and less than one fifth consumed ≥5 fruits/vegetables per day. After adjusting for parents’ demographics and children’s lifestyle behaviors, parents’ sleep disturbance was positively correlated with their levels of stress, anxiety, and depression. After controlling for parents’ demographics and lifestyle behaviors, child sleep time was negatively associated with parents’ stress levels. Family demographics and parents’ and children’s lifestyle behaviors explained 33.4%, 29.8%, and 28.1% of the variances in parents’ stress, anxiety, and depression, respectively. Discussion Most parents and preschoolers were not meeting many lifestyle behavior recommendations, indicating a need for interventions. Improving parents’ sleep quality and reducing bedtime challenges involving their preschoolers may be necessary for enhancing parental mental well-being.

Telling the Truth

Por: Pickler · Rita H.
No abstract available

Predictors of Health Promotion Behaviors Among Working Adults at Risk for Metabolic Syndrome

imageBackground Metabolic syndrome has a high global prevalence, affecting 26% of South Koreans. Lifestyle modifications have shown benefits in studies involving health behavior enhancement, specifically through workplace eating and exercise interventions. However, workplace interventions focusing on health behaviors have been inadequately explored. Objectives This study examined factors affecting health promotion behaviors of workers at high risk of metabolic syndrome by applying Theory of Planned Behavior constructs (attitude, subjective norm, perceived behavioral control, and intention). Methods This correlational cross-sectional study collected survey data from 164 hotel workers in South Korea. The study applied factor analysis and structural equation modeling for the data analysis. Results Analysis revealed five health promotion behaviors: exercise, making healthy food choices, avoiding fatty foods, eating a nutritious and balanced diet, and eating regular moderate meals. Participants were grouped as total participants, those with one risk factor, and those with two risk factors. In the “total” group, four behaviors were influenced by perceived behavioral control: exercise, making healthy food choices, eating a nutritious and balanced diet, and eating regular moderate meals. In the “one risk factor” group, intention and attitude influenced the eating regular moderate meals behavior, and two other behaviors were influenced by perceived behavioral control: exercise and eating a nutritious and balanced diet; in the “two risk factor” group, only perceived behavioral control directly affected exercise. Discussion Perceived behavioral control was a key predictor of health behaviors, and theory constructs partially explained behaviors. Perceived behavioral control influenced four behaviors and influenced exercise in all three groups. Also, theory constructs showed a greater effect on behaviors in the one risk factor group than in the two risk factor group, indicating that participants with one risk factor more effectively managed their behaviors on their own and with healthcare providers’ support. Occupational health providers should conduct early assessments of workers showing metabolic syndrome risk factors to identify their particular risks, intention, and behaviors. As the number of risk factors affects behaviors and perceived behavioral control primarily influences exercise, these findings should be incorporated in metabolic syndrome interventions.

Tripartite Analysis: A Data Analysis Technique for Convergent Mixed-Methods Designs

imageBackground Effective data integration is a daunting task in mixed methods research. Several frameworks for data integration exist, but the choice of and the technique for integration depend upon the research question and design. Innovative integration techniques continuously need to be developed to tackle the integration challenge and provide alternative ways for researchers to generate plausible mixed meta-inferences. Objectives The purpose of this study was to describe a new data analysis technique, tripartite analysis (TriPA), and illustrate its use in a convergent mixed-methods study. Methods This technique was developed based on a convergent mixed-methods study underpinned by dialectical pluralism aimed to understand Pakistani nursing students’ perspectives about compassion and compassionate care and how these perspectives are consistent with the conceptualizations of compassion in nursing literature. Results TriPA entails analysis and integration using joint displays at three levels: case-by-case integrated analysis, separate and then merged quantitative and qualitative analysis, and comparative and integrated analysis of Levels I and II findings. Discussion TriPA can enable researchers to develop a more nuanced understanding of a given phenomenon through integration at various levels by identifying linkages within cases and across the whole data set and recognizing relational connections and emerging patterns.

Relationship Between Environmental Air Quality and Congenital Heart Defects

imageBackground Congenital heart defects (CHDs) affect 40,000 U.S. infants annually. One fourth of these infants have a critical CHD, requiring intervention within the first year of life for survival. Over 80% of CHDs have an unknown etiology. Fine particulate matter ≤2.5 (PM2.5) and ozone (O3) may be air pollutants associated with CHD. Objectives The purpose of this study was to explore relationships between first-trimester maternal exposure to air pollutants PM2.5 and O3 and a critical CHD diagnosis. Methods A retrospective cohort study with nested case controls was conducted using data from January 1, 2014, to December 31, 2016, and consisted of 199 infants with a diagnosed critical CHD and 550 controls. Air pollution data were obtained from the U.S. Environmental Protection Agency air monitors. Geographic information system software was used to geocode monitoring stations and infant residential locations. Data analysis included frequencies, chi-square, independent t-test analysis, and binary logistic regression for two time periods: the entire first trimester (Weeks 1–12) and the critical exposure window (Weeks 3–8 gestation). Results Critical CHD odds were not significantly increased by exposure during the first trimester. However, weekly analyses revealed CHD odds were higher in Weeks 5 and 8 as PM2.5 increased and decreased in Week 11 with increased O3 exposure. Discussion Our study shows no evidence to support the overall association between air pollutants PM2.5 and O3 and a critical CHD diagnosis. However, analyses by week suggested vulnerability in certain weeks of gestation and warrant additional surveillance and study.