Publications

Abstract

Background: Type 2 diabetes (T2D) has an immense disease burden, affecting millions of people worldwide and costing billions of dollars in treatment. As T2D is a multifactorial disease with both genetic and nongenetic influences, accurate risk assessments for patients are difficult to perform. Machine learning has served as a useful tool in T2D risk prediction, as it can analyze and detect patterns in large and complex data sets like that of RNA sequencing. However, before machine learning can be implemented, feature selection is a necessary step to reduce the dimensionality in high-dimensional data and optimize modeling results. Different combinations of feature selection methods and machine learning models have been used in studies reporting disease predictions and classifications with high accuracy. Objective: The purpose of this study was to assess the use of feature selection and classification approaches that integrate different data types to predict weight loss for the prevention of T2D. Methods: The data of 56 participants (ie, demographic and clinical factors, dietary scores, step counts, and transcriptomics) were obtained from a previously completed randomized clinical trial adaptation of the Diabetes Prevention Program study. Feature selection methods were used to select for subsets of transcripts to be used in the selected classification approaches: support vector machine, logistic regression, decision trees, random forest, and extremely randomized decision trees (extra-trees). Data types were included in different classification approaches in an additive manner to assess model performance for the prediction of weight loss. Results: Average waist and hip circumference were found to be different between those who exhibited weight loss and those who did not exhibit weight loss (P=.02 and P=.04, respectively). The incorporation of dietary and step count data did not improve modeling performance compared to classifiers that included only demographic and clinical data. Optimal subsets of transcripts identified through feature selection yielded higher prediction accuracy than when all available transcripts were included. After comparison of different feature selection methods and classifiers, DESeq2 as a feature selection method and an extra-trees classifier with and without ensemble learning provided the most optimal results, as defined by differences in training and testing accuracy, cross-validated area under the curve, and other factors. We identified 5 genes in two or more of the feature selection subsets (ie, CDP-diacylglycerol-inositol 3-phosphatidyltransferase [CDIPT], mannose receptor C type 2 [MRC2], PAT1 homolog 2 [PATL2], regulatory factor X-associated ankyrin containing protein [RFXANK], and small ubiquitin like modifier 3 [SUMO3]). Conclusions: Our results suggest that the inclusion of transcriptomic data in classification approaches for prediction has the potential to improve weight loss prediction models. Identification of which individuals are likely to respond to interventions for weight loss may help to prevent incident T2D. Out of the 5 genes identified as optimal predictors, 3 (ie, CDIPT, MRC2, and SUMO3) have been previously shown to be associated with T2D or obesity.

Abstract

Background: Accurate prediction of risk for chronic diseases like type 2 diabetes (T2D) is challenging due to the complex underlying etiology. Integration of more complex data types from sensors and leveraging technologies for collection of -omics datasets may provide greater insights into the specific risk profile for complex diseases. Methods: We performed a literature review to identify feature selection methods and machine learning models for prediction of weight loss in a previously completed clinical trial (NCT02278939) of a behavioral intervention for weight loss in Filipinos at risk for T2D. Features included demographic and clinical characteristics, dietary factors, physical activity, and transcriptomics. Results: We identified four feature selection methods: Correlation-based Feature Subset Selection (CfsSubsetEval) with BestFirst, Kolmogorov–Smirnov (KS) test with correlation featureselection (CFS), DESeq2, and max-relevance-min-relevance (MRMR) with linear forward search and mutual information (MI) and four machine learning algorithms: support vector machine, decision tree, random forest, and extra trees that are applicable to prediction of weight loss using the specified feature types. Conclusion: More accurate prediction of risk for T2D and other complex conditions may be possible by leveraging complex data types from sensors and -omics datasets. Emerging methods for feature selection and machine learning algorithms make this type of modeling feasible.

Abstract

(1) Background: The COVID-19 pandemic has exacerbated incidents of burnout among academics in various fields and disciplines. Although burnout has been the subject of extensive research, few studies have focused on nursing faculty. This study aimed to investigate the differences in burnout scores among nursing faculty members in Canada. (2) Method: Using a descriptive cross-sectional design, data were collected via an online survey in summer 2021 using the Maslach Burnout Inventory general survey and analyzed using the Kruskal-Wallis test. (3) Result: Faculty members (n = 645) with full-time employment status, worked more than 45 h, and taught 3–4 courses reported high burnout (score ≥ 3) compared to those teaching 1–2 courses. Although education levels, tenure status or rank, being on a graduate committee, or the percentage of hours dedicated to research and services were considered important personal and contextual factors, they were not associated with burnout. (4) Conclusions: Findings suggest that burnout manifests differently among faculty and at varying degrees. As such, targeted approaches based on individual and workload characteristics should be employed to address burnout and build resilience among faculty to improve retention and sustain the workforce.

Abstract

The SARS-CoV-2 coronavirus pandemic has led to increased food insecurity levels. This cross-sectional study examines the prevalence and determinants of food insecurity during the two-month (1 April to 1 June 2022) city-wide lockdown in Shanghai. The data was collected via an online questionnaire from 3230 adult Shanghai residents during the lockdown. Food insecurity was measured using an adapted version of the Household Food Insecurity Access Scale. Nearly 70% of participants reported being exposed to food insecurity. Using multivariable logistic regressions, we examined the associations between key correlates (i.e. age, income, lockdown-related income loss, migration, employment status, social capital, preparedness, and received social support) and overall food insecurity while adjusting for ethnicity, gender, education, household size, and marital status. Results showed that compared to local Shanghai residents, migrants (i.e, permanent migrants with Hukou (OR = 2.16), permanent migrants without Hukou (OR = 2.06), temporary migrants (OR = 2.74)), and participants with less than or greather than 50% lockdown-related income loss (OR = 2.60, OR = 3.09), were associated with higher odds of overall food insecurity. Participants with greater preparedness (OR = 0.66), greater bonding social capital (OR = 0.93), and greater bridging social capital (OR = 0.94), had lower odds of overall food insecurity. Targeted interventions are needed to enhance food resilience and health equity among vulnerable populations.

Abstract

BACKGROUND: Limited evidence exists about the prevalence and incidence of mild cognitive impairment (MCI) in individuals with diabetes in the U.S. We aimed to address such knowledge gaps using a nationally representative study dataset.METHOD: We conducted a secondary analysis from the Health and Retirement Study (HRS) (1996-2018). The sample for examining the prevalence of MCI was14,988, with 4,192 (28.0%) having diabetes, while the sample for the incidence was 21,824, with 1,534 (28.0%) having diabetes.RESULTS: Participants with diabetes had a higher prevalence of MCI than those without diabetes (19.9% vs. 14.8%; odds ratio [95% confidence interval] (OR[95%CI]): 1.468 [1.337, 1.611], p<.001). The incidence of MCI in participants with/without newly diagnosed diabetes was 42.9% vs. 31.6% after a mean 10-year follow-up, with the incidence rate ratio (IRR) [95%CI] (1.314 [1.213, 1.424], p<.001). Newly diagnosed diabetes was associated with elevated risks of MCI compared with non-diabetes, with the uncontrolled hazard ratio (HR) [95%CI] (1.498 [1.405, 1.597], p<.001).CONCLUSIONS: Using a nationally representative study data in the U.S., participants with diabetes had a higher prevalence and incidence of MCI than those without diabetes. Findings show the importance of developing interventions tailored to the needs of individuals with diabetes and cognitive impairment.

Abstract

Primary care physicians are well-positioned to integrate lifestyle interventions into the management of patients with unhealthy substance use, who may also have mental and physical chronic health comorbidities. However, the COVID-19 pandemic exacerbated the U.S.’s poor state of health, revealing that its current approach to chronic disease management is neither effective nor sustainable. Today’s full spectrum comprehensive care model requires an expanded toolkit. Lifestyle interventions broaden current treatment approaches and may enhance Addiction Medicine care. Primary care providers have the potential to have the greatest impact on unhealthy substance use care because they are experts in chronic disease management and their frontline accessibility minimizes healthcare barriers. Individuals with unhealthy substance use are at an increased risk of chronic physical conditions. Incorporating lifestyle interventions with unhealthy substance use care at every level of medicine, from medical school through practice, normalizes both as part of the standard care of medicine and will drive evidence-based best practices to support patients through prevention, treatment, and reversal of chronic diseases.

Abstract

Work ability, or the perception of one’s ability to work presently and in the future, may impact quality of life (QOL) among young adult (YA) cancer survivors. Through a convergent mixed methods design, we explored work ability, work-related goals, and QOL among YA hematologic cancer survivors within five years of diagnosis. We described associations at the individual- and microsystem (work)- levels; and compared factors across low and high work ability groups. Participants (N = 40) completed a survey and interview via digital platforms. Qualitative analysis revealed self-assessed declines in work ability led to questioning work-related goals and influenced QOL. Integrated analysis led to the development of four profiles, growing our understanding of work’s influence on QOL for YA cancer survivors, and identifying components YAs considered when contemplating work-related goals after a cancer diagnosis. Larger studies are needed to elucidate these profiles and identify modifiable factors to inform targeted interventions to improve QOL.

Abstract

The prevalence of behavioral health conditions among older adults continues to rise while the number of specialty providers remains low. Nurses caring for aging populations across care settings have opportunities to integrate behavioral healthcare into their practice with adults to promote wellness and avoid negative outcomes. Priority issues for integrated behavioral health among older adults include depression, substance use disorders, and neurocognitive conditions. Connections to professional organizations, timely continuing education, and integration of evidenced-based clinical protocols are vital for nurses to provide effective integrated care.

Abstract

Background: Half of all stroke survivors experience hemiparesis on the contralateral side, resulting in chronic upper extremity (UE) impairment. Remote rehabilitation is a promising approach to optimize the gains made in the clinic to maximize function and promote UE use at home. This paper describes the study protocol for a remote home-based UE self-training program. Design: This was a feasibility study that used a convergent mixed methods approach. Methods: We collected data on 15 community-dwelling individuals with UE hemiparesis after stroke. The study used motivational interviewing (MI) and ecological momentary assessments (EMA) to maximize engagement in a 4-week personalized UE self-training program. The study consisted of three phases: 1) training in MI for the interventionists 2) creating customized treatment plans using shared decision making, and 3) four weeks of UE self-training. Measures and analysis: To evaluate feasibility, we will summarize recruitment and retention rates, intervention delivery, acceptance, adherence, and safety. Quantitative UE outcomes will measure change in UE status after the intervention (Fugl-Meyer Assessment, Motor Activity Log, Canadian Occupational Performance Measure, and bilateral magnitude ratio). Qualitative data (1:1 semi-structured interviews) will capture participants’ perceptions and experience with the intervention. Quantitative and qualitative data will be integrated to gain a deeper understanding of the facilitators and barriers for engagement and adherence to UE self-training. Conclusion: The results of this study will advance the scientific knowledge for use of MI and EMA as methods for enhancing adherence and engagement in UE self-training in stroke rehabilitation. The ultimate impact of this research will be to improve UE recovery for individuals with stroke transitioning back into community. Clinical trials registration: NCT05032638.

Abstract

Patients with chronic obstructive pulmonary disease (COPD) experience a high risk for psychological distress. Understanding what factors contributing to this risk is vital for developing effective interventions to address COPD-related psychological distress. To examine psychological distress and its associated factors in COPD patients in China. This is a cross-sectional study. Using cluster random sampling, 351 COPD patients participated in and completed a questionnaire survey from June 2021 to January 2022. Instruments used in this research included a self-designed social-demographic questionnaire, the Kessler Psychological Distress Scale (K10), the COPD Knowledge Question, the Type D Personality Scale (DS-14), the COPD Assessment Test (CAT), and modified Medical Research Council Dyspnea Score (mMRC). Multivariate linear regressions were used in the final analysis. Among 351 COPD patients, 307 (or 87.5%) had psychological distress. Our univariate analysis indicated that psychological distress scores were significantly associated with monthly household income (F = 2.861, P < 0.05), exercise frequency (F = 4.039, P < 0.01), type D personality (t = 5.843, P < 0.01), years with COPD (rs = 0.156, P < 0.01), frequency of acute exacerbation (rs = 0.114, P < 0.05), mMRC score (rs = 0.301, P < 0.01), and CAT score (rs = 0.415, P < 0.01). Our final multivariate linear regression showed that exercise frequency (coefficient = −1.012, P < 0.01) was an independent protective factor of psychological distress in COPD patients, while type D personality (coefficient = 3.463, P < 0.001), mMRC score (coefficient = 1.034, P < 0.001) and CAT score were independent risk factors (coefficient =.288, P < 0.001). No relationship was observed between psychological distress and knowledge of COPD. Psychological distress is commonly presented among COPD patients in China. Findings from this study suggest promoting and increasing frequency of exercise will be beneficial in reducing psychological distress among COPD patients. This study also highlights the importance of assessing personality type, dyspnea, and impact of COPD on daily living for preventing and managing psychological distress due to COPD. In addition, Given the high rate of psychological distress among COPD patients, policymakers should consider making mental health resources easily available and accessible to this vulnerable population.

Abstract

The occurrence of HIV-related posttraumatic stress disorder (PTSD) compromises the physical and mental health of people living with HIV (PLWH). This study examined the psychological pathways of HIV-related PTSD symptoms considering the influence of rumination in PLWH of China. A cross-sectional survey was conducted in Changsha, China. The data were collected using the PTSD Checklist−Civilian Version, the Ruminative Response Scale, the Multidimensional Scale of Perceived Social Support, and measures of sociodemographic and HIV-related clinic characteristics. A total of 602 PLWH were surveyed. The average score of HIV-related PTSD symptoms was (34.54 ± 13.58). The mediation model showed that perceived social stigma and physical health exhibited direct associations with PTSD symptoms (β = 0.093, −0.145, respectively), while the direct relations of family support, friend support and significant others support to PTSD symptoms were not significant. Rumination mediated the effect of perceived social stigma (β = 0.077), physical health (β = −0.150), family support (β = −0.144) and friend support (β = −0.105) on PTSD symptoms. The study findings underscore the importance of routinely assessing PTSD for PLWH, and developing trauma-focused interventions that alleviate HIV-related PTSD symptoms and reduce rumination while improving social support and physical health and reducing social stigma.

Abstract

Background: In this updated Self-Care of Coronary Heart Disease Inventory (SC-CHDI) v3.0, items were added to better reflect the theory of self-care of chronic illness and revised based on recent research. The expanded SC-CHDI now reflects the theoretical concepts of self-care maintenance, monitoring, and management. Objective: The aim of this study was to evaluate the psychometric properties of the SC-CHDI v3.0. Methods: In a sample of adults with coronary heart disease, we tested the SC-CHDI v3.0 validity with confirmatory factor analysis. Reliability was calculated using Cronbach α, factor score determinacy coefficient, and global reliability index for multidimensional scales, with values > 0.70 considered adequate. Results: The sample (n = 205) was predominantly male (79%) with a mean age of 65.3 ± 11.1 years. The self-care maintenance scale encompassed 2 distinct behaviors, namely, “illness related behaviors” and “health promoting behaviors,” which reflect consulting and autonomous dimensions, respectively. The goodness-of-fit indices were adequate: χ2(25, N = 205) =31.86, P = .16, comparative fit index = 0.97, Tucker-Lewis Index = 0.95, root mean square error of approximation = 0.04 (90% confidence interval, 0.00–0.07), P = .705, and standardized root mean square residual = 0.045. Analysis of the new self-care monitoring scale yielded a single factor; goodness-of-fit indices were excellent: χ2(12, N = 205) =11.56, P = .48, comparative fit index = 1.00, Tucker-Lewis Index = 1.00, root mean square error of approximation < 0.001 (90% confidence interval, 0.000–0.07), P = .86, and standardized root mean square residual = 0.02. The self-care management scale had 2 dimensions of autonomous and consulting behavior with strong goodness-of-fit indices: χ2(7, N = 205) =6.57, P = .47, comparative fit index = 1.00, Tucker-Lewis Index = 1.00, root mean square error of approximation ≤ 0.001 (90% confidence interval, 0.00–0.08), P = .76, and standardized root mean square residual = 0.02. Reliability estimates were ≥0.80 for all scales. Conclusions: Our testing suggests that the SC-CHDI v3.0 is a sound measure of the essential elements of self-care for adults with coronary heart disease.

Abstract

Background: Understanding alcohol use among nurses may inform interventions related to the coping mechanisms nurses use for workplace stress and trauma. Alcohol use can be caused by a variety of factors and has serious implications on a nurse's personal health and professional practice. Understanding psychosocial factors and preventive measures may assist in the development of interventions to improve coping mechanisms and reduce the incidence of alcohol misuse. Purpose: To review the psychosocial factors and preventive measures associated with alcohol use among nurses. Methods: For this integrative review, systematic searches were conducted in CINAHL, PubMed, PsychNet, and ProQuest Central. Included studies were peer-reviewed and addressed alcohol use among nurses in the United States. Articles were appraised using methods-specific tools indicated by the Whittemore and Knafl framework. Data were extracted and themes identified using constant comparison. Results: Of 6,214 nonduplicate articles screened, 78 were selected for full-text review and 13 were included after application of inclusion criteria. Synthesis resulted in four themes: (1) occupational stress and trauma, (2) workplace characteristics, (3) mental health implications, and (4) protective factors. The data show that workplace stress and trauma contribute to alcohol use among nurses. Night shifts, rotating shifts, and shift length are factors related to alcohol use, as are mental health problems such as anxiety, depression, trauma, and suicide. Protective factors that reduce alcohol use among nurses include faith, resilience, and perceived organizational support. Conclusion: Alcohol use among nurses presents challenges for the nursing profession and regulatory bodies with specific and interrelated phenomena related to the role and identity of nurses. A better understanding of these factors through research will facilitate a healthier nursing workforce that is better prepared to take on the rewards and challenges of a nursing career.

Abstract

e18760Background: Rapidly expanding knowledge of molecular drivers of cancer helps facilitate effective, targeted cancer therapy (i.e. precision oncology), but research suggests that precision oncology is underused. We conducted a qualitative study of barriers and facilitators of precision oncology use within the Veterans Health Administration (VHA). Methods: We conducted a pragmatic qualitative study involving semi-structured interviews with both patients and providers at VA medical centers with low, medium, and high guideline concordant molecular testing. The interview guide was constructed by a multidisciplinary team of oncologists, qualitative health researchers and patient representatives using modified grounded theory (MGT) and the Theoretical Domains Framework (TDF). Summative and directed content analyses were conducted. Codes for the directed content analysis came from the framework and others evolved iteratively. Consensus-based approaches finalized the codebook. Results: Thirty-three interviews were conducted (17 patient and 16 provider interviews). A total of 1889 unique phrases were identified and categorized into 255 meaningful statement codes. The codes were mapped to 10 TDF domains. The most frequently cited determinants, representing 59% (1110 of 1889 statements) of all coded data, included the domains environmental context and resources, knowledge, and goals. Both patients and providers shared similar goals of improved outcomes and quality of care, but systems barriers were frequently cited impediments to precision oncology use. An additional 27% of codes (510 of 1889) represented the TDF domains of emotions (predominantly patient “fear of genetics” and confidence in providers), memory/attention (task priority in clinic visits), and interpersonal skills (both patient-provider, and interdisciplinary provider-provider). Additional frequently cited determinants, each comprising 6% of coded statements, included social influences (for both providers and patients) and reinforcement (perceived consequences). Conclusions: We identified determinants of precision oncology use at the patient, provider, and system level. Attempts to improve implementation of precision oncology will need to address systems barriers to care, as well as knowledge and patient-provider interactions, but can build on a foundation of shared goals.

Abstract

Background: Implementation of the Surviving Sepsis Campaign (SSC) guidelines into practice has demonstrated improved outcomes. Local Problem: Compliance with a sepsis protocol, based on the SSC guidelines, in an urban teaching hospital was below the national average. Methods: A pre- and posttest intervention design was used to improve clinician knowledge, confidence, and compliance with the protocol. Interventions: Educational modules were developed on the SSC guidelines and reminder system alerts (RSA) for timely revaluation of patients with sepsis and lactate monitoring were implemented. Results: A total of 33 (48%) clinicians participated. There was an increase in knowledge, documentation of sepsis reassessment, and serum lactate monitoring. There was an improvement in clinician perceptions following the initiative. Conclusions: The results demonstrate that education, combined with RSAs, can improve protocol knowledge and compliance.

Abstract

While home health agencies (HHAs) can seek accreditation to recognize their quality of service, it is unknown whether agencies with accreditation perform better in providing care than those without accreditation. Using 5-year data from national data sources, the aims of this study were: 1) to depict characteristics of HHAs with and without accreditation; and 2) to examine the relationship between accreditation status and HHA performance on quality-of-care metrics. This study analyzed 7,697 agencies in the US and found that 1) agencies that were for-profit, urban, not-hospital-affiliated, single-branch, Medicare enrolled only, and without hospice program were more likely to have accreditation; and 2) overall, accredited agencies performed better on the three commonly used quality indicators, timely initiation of care, hospitalization, and emergency department visit, though not all the observed differences were substantial in absolute value. Our results provide unique empirical information to agencies considering seeking accreditation.

Abstract

Medical expenses in the last year of life consume a large portion of healthcare expenditures, yet little is known about the relationship between medical expenditures in the last year of life and quality of death. Few empirical studies have investigated the association between timely medical treatment before dying and quality of death. This study aimed to examine the associations between medical expenditures in the last year of life, timely medical treatment before dying, and quality of death. Data derived from the Chinese Longitudinal Healthy Longevity Survey (CLHLS), the largest national representative study of the oldest-old in China. Results from multinomial logistic regression suggested that higher medical expenses in the last year of life and lack of timely medical treatment before dying are associated with lower quality of death. These findings highlight an urgent need for strengthening education on death and dying, developing hospice and palliative care services, and improving pain management at the end of life in China.

Abstract

Context: Consequent to increasing COVID-19 infection rates, the Palliative Care (PC) service at a large New England hospital shifted from in-person to telehealth-delivered PC (TPC). Objectives: We compared the quality of TPC to in-person PC during the early COVID-19 pandemic. Methods: We conducted an electronic health record review of PC consultations of patients hospitalized during three periods: pre-COVID January, 2020-February, 2020 (in-person); peak-COVID March, 2020-June, 2020 (majority TPC); and post-peak September, 2020-October, 2020 (majority in-person). We examined the relationship between these periods and PC delivery characteristics and quality measures using descriptive and bivariate statistics. Results: Of 377 patients, 50 were pre-COVID (TPC=0%), 271 peak-COVID (TPC=79.3%), and 56 post-peak (TPC<2%) (representation of PC consult: pre- and post-peak=samples; peak-COVID=all consults). Mean age was 69.3 years (standard deviation=15.5), with 54.9% male, 68.7% White, and 22.8% Black. Age and sex did not differ by period. PC consultations were more likely for goals of care (pre=30.0% vs. peak=53.9% vs. post=57.1%; P = 0.005) or hospice (4.0% vs. 14.4% vs. 5.4%, P = 0.031) during peak-COVID compared to pre-COVID. Rates of assessment of physical (98.0% vs. 63.5% vs. 94.6%, P < 0.001) and psychological symptoms (90.0% vs. 33.1% vs. 67.9%, P < 0.001) were lower during peak relative to pre-COVID and post-peak periods. There were no differences in assessment of patients’ social needs, family burden, or goals of care across periods. Conclusion: The PC service provided high-quality inpatient PC using TPC despite significant strain during the early COVID-19 pandemic. Developing and testing strategies to promote comprehensive symptom control using TPC remains a priority to adjust to potential unmet PC needs.

Abstract

Objective: In a large multi-racial/ethnic cohort of women, we examined racial/ethnic disparities in preterm birth (PTB) risk stratified by autoimmune rheumatic disease (ARD) type, which included systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Methods: Birth records linked to hospital discharge data of singleton births in California from 2007 to 2012 were leveraged for a retrospective cohort study including women with SLE or RA. The relative risk of PTB (< 37 versus ≥ 37 weeks’ gestation) was compared among different racial/ethnic groups (Asian, Hispanic, Non-Hispanic (NH) Black, and NH White) and stratified by ARD type. Results were adjusted for relevant covariates using Poisson regression. Results: We identified 2874 women with SLE and 2309 women with RA. NH Black, Hispanic, and Asian women with SLE were 1.3 to 1.5 times more likely to have PTB compared to NH White women. NH Black women with RA were 2.0 to 2.4 times more likely to have PTB compared to Asian, Hispanic, or NH White women. The NH Black-NH White and NH Black-Hispanic disparity in PTB risk was significantly higher in women with RA compared to SLE or the general population. Conclusion: Our findings highlight the racial/ethnic disparities for risk of PTB among women with SLE or RA and highlight that several of the disparities are higher for women with RA compared to those with SLE or the general population. These data may provide important public health information for addressing racial/ethnic disparities in the risk of preterm birth, particularly among women with RA.Key Points• There is an unmet need for studies that evaluate racial/ethnic disparities in birth outcomes specifically in women with RA or SLE.• This is one of the first studies describing racial/ethnic disparities in PTB risk for women with RA, and to draw conclusions regarding Asian women in the USA with rheumatic diseases and PTB.• These data provide important public health information for addressing racial/ethnic disparities in the risk of preterm birth among women with autoimmune rheumatic diseases.

Abstract

This paper aims to present and discuss the issues, challenges, and strategies related to recruitment and retention in clinical trials involving participants with chronic pain. The randomized controlled clinical trial (RCT) is widely regarded as the gold standard for evaluating clinical interventions. However, it is crucial to acknowledge and address the challenges associated with recruiting and retaining participants. To prioritize the experience of the study population, targeted outreach strategies and a patient-centric approach are necessary. Researchers should consider incorporating recruitment and retention strategies during the study design phase. Implementing multi-pronged recruitment methods, leveraging relationships with community providers, and involving representatives of the patient population are helpful approaches. Effective communication and maintaining a professional environment are vital for optimizing engagement and supporting the successful execution of clinical trials involving participants with chronic pain.

Abstract

While safety should be a lifetime concern, aging brings it into sharper focus when a slow decline in all human functions commences and accommodations must be made to continue life with health, quality, and competence in life tasks and relationships. These normal declines, magnified by chronic diseases and health conditions increase vulnerability in older adults to the effects of commonly used substances. Safety can then be compromised using alcohol, tobacco, psychoactive drugs, medications, and food supplements which people ingest to alter state of mind, emotional well-being, and alleviate disease conditions and infirmities. Compromised safety can be the untoward side effect of seeking more optimal states, and older adults make choices to experience pleasure and attain pain-free states and freedom of movement. The most commonly used substance worldwide, alcohol, is legal, socially sanctioned, widely promoted, and relatively inexpensive but also the most damaging to health and safety. Tobacco is the mostly deadly, resulting in the deaths of close to 500,000 people annually and a contributing factor to 200 diseases and health conditions. This chapter identifies the scope of health and safety consequences of substances commonly used by adults over 60, detailing the safety risks of each class of drug and its detrimental health effects. While a relatively small proportion of older adults (5–6%) are ever diagnosed with a substance use disorder, many more engage in binge drinking and unhealthy levels of alcohol consumption and combine alcohol with prescribed and over-the-counter medications resulting in unsafe and at times, lethal results. Excessive levels of opioid analgesic prescribing have resulted in loss of life and severe opioid use disorders which compromise safety and quality of life for many older adults. Models of care that integrate screening and drug and alcohol interventions into primary care, expand harm reduction, and use public health approaches to raise awareness about the health implications of substance use hold promise for deterring upward trends in substance use among older adults. Policy initiatives are described as frameworks for additional interventions.

Abstract

Summary. This study aimed to identify, appraise, and summarize the available evidence relating to nurses’ attitudes, confidence in evidence-based practice (EBP), and facilitators and barriers for implementation of EBP in nursing.Methods. PubMed, The Cochrane Library, EBSCO (Nursing Reference Center Plus), and Google Scholar were searched from January 2010 to January 2021. Studies in English that met the following criteria were considered for inclusion: quantitative and qualitative research that assessed the most common facilitators and barriers for implementation of EBP in nursing practice; andnurses’ attitudes and confidence in using EBP in their daily routine.Results. Seventeen studies were included in the review. In quantitative studies, questionnaires were specifically developed for use in six while the other 10 used validated instruments. One qualitative study was included. In 12 studies, researchers reported elements of nurses’ attitudes and confidence about EBP. Facilitators to the implementation of EBP were explored in 11 studies, andbarriers were identified in 12 studies. Results of this review indicate that nurses face challenges in implementing EBP.Conclusion. To improve the use of EBP in nursing practice, nurses need to understand that nursing practice depends on some fundamental factors such as nurse education, computer literacy, work environment, experience, personal qualities, and colleagues around them. This literature review highlights the necessity of education in finding and accessing evidence, nurses’ autonomyover nursing practice, mentorship for successful implementation, and organizational support.

Abstract

This article aimed to explore the rehabilitation efficacy of intelligent rehabilitation training systems in hemiplegic limb spasms after stroke and provided more theoretical basis for the application of intelligent rehabilitation systems in the rehabilitation of hemiplegic limb spasms after stroke. To explore the rehabilitation efficacy of intelligent rehabilitation training system (RTS for short here) in post-stroke hemiplegic limb spasms, this study selected 99 patients with post-stroke hemiplegic limb spasms admitted to a local tertiary hospital from March 2021 to March 2023 as the research subjects. This article used blind selection to randomly divide them into three groups: control group 1, control group 2, and study group, with 33 patients in each group. Control group 1 used a conventional RTS, group 2 used the brain-computer interface RTS from reference 9, and research group used the intelligent RTS from this article. This article compared the degree of spasticity, balance ability score, motor function score, and daily living activity score of three groups of patients after 10 weeks of treatment. After 10 weeks of treatment, the number of patients in the study group with no spasms at level 0 (24) was significantly higher than the number of patients in group 1 (7) and group 2 (10), with a statistically significant difference (P < 0.05); In the comparison of Barthel index scores, after ten weeks of treatment, the total number of people in the study group with scores starting at 71-80 and 81-100 was 23. The total number of people in the score range of 71-80 and 81-100 in group 1 was 5, while in group 2, the total number of people in this score range was 8. The study group scored considerably higher than the control group and the difference was found to be statistically relevant (P < 0.05). In the Berg balance assessment scale and motor function assessment scale, after 10 weeks of treatment, the scores of the study group patients on both scales were significantly higher than those of group 1 and group 2 (P < 0.05). The intelligent RTS is beneficial for promoting the improvement of spasticity in stroke patients with hemiplegic limb spasms, as well as improving their balance ability, motor ability, and daily life activities. Its rehabilitation effect is good.