Out-of-Pocket Costs and Payments in Autologous and Implant-Based Breast Reconstruction: A Nationwide Analysis.

BACKGROUND: Many factors influence a patient's decision to undergo autologous versus implant-based breast reconstruction, including medical, social, and financial considerations. This study aims to investigate differences in out-of-pocket and total spending for patients undergoing autologous and implant-based breast reconstruction. METHODS: The IBM MarketScan Commercial Databases were queried to extract all patients who underwent inpatient autologous or implant-based breast reconstruction from 2017 to 2021. Financial variables included gross payments to the provider (facility and/or physician) and out-of-pocket costs (total of coinsurance, deductible, and copayments). Univariate regressions assessed differences between autologous and implant-based reconstruction procedures. Mixed-effects linear regression was used to analyze parametric contributions to total gross and out-of-pocket costs. RESULTS: The sample identified 2079 autologous breast reconstruction and 1475 implant-based breast reconstruction episodes. Median out-of-pocket costs were significantly higher for autologous reconstruction than implant-based reconstruction ($597 vs $250, P < 0.001) as were total payments ($63,667 vs $31,472, P < 0.001). Type of insurance plan and region contributed to variable out-of-pocket costs (P < 0.001). Regression analysis revealed that autologous reconstruction contributes significantly to increasing out-of-pocket costs (B = $597, P = 0.025) and increasing total costs (B = $74,507, P = 0.006). CONCLUSION: The US national data demonstrate that autologous breast reconstruction has higher out-of-pocket costs and higher gross payments than implant-based reconstruction. More study is needed to determine the extent to which these financial differences affect patient decision-making.

HE4-based nomogram for predicting overall survival in patients with idiopathic pulmonary fibrosis: construction and validation.

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61-4.24) (p < 0.001) in the training set. We constructed a model based on the risk-score = 0.16222182 * HE4 + 0/0.37580659/1.05003609 (for GAP index 0-3/4-5/6-8) + (- 1.1183375). In both training and validation sets, high-risk patients had poor prognoses (HR: 3.49, 95%CI 2.10-5.80, p = 0.001) and higher likelihood of dying (HR: 6.00, 95%CI 2.04-17.67, p = 0.001). Analyses of calibration curves and decision curves suggest that the method is effective in predicting outcomes. Furthermore, a similar formulation was used in a protein-based model based on HE4 that also showed prognostic value when applied to IPF patients. Accordingly, HE4 is an independent poor prognosis factor, and it has the potential to predict IPF patient survival.

Can predictive factors determine the time to treatment initiation for oral and oropharyngeal cancer? A classification and regression tree analysis.

This ecological study aimed to identify the factors with the greatest power to discriminate the proportion of oral and oropharyngeal cancer (OOC) records with time to treatment initiation (TTI) within 30 days of diagnosis in Brazilian municipalities. A descriptive analysis was performed on the variables grouped into five dimensions related to patient characteristics, access to health services, support for cancer diagnosis, human resources, and socioeconomic characteristics of 3,218 Brazilian municipalities that registered at least one case of OOC in 2019. The Classification and Regression Trees (CART) technique was adopted to identify the explanatory variables with greater discriminatory power for the TTI response variable. There was a higher median percentage of records in the age group of 60 years or older. The median percentage of records with stage III and IV of the disease was 46.97%, and of records with chemotherapy, radiation, or both as the first treatment was 50%. The median percentage of people with private dental and health insurance was low. Up to 75% had no cancer diagnostic support services, and up to 50% of the municipalities had no specialist dentists. Most municipalities (49.4%) started treatment after more than 30 days. In the CART analysis, treatment with chemotherapy, radiotherapy, or both explained the highest TTI in all municipalities, and it was the most relevant for predicting TTI. The final model also included anatomical sites in the oral cavity and oropharynx and the number of computed tomography services per 100,000. There is a need to expand the availability of oncology services and human resources specialized in diagnosing and treating OOC in Brazilian municipalities for a timely TTI of OOC.

Predictors of maternal health services uptake in West African region: a multilevel multinomial regression analysis of demographic health survey reports.

BACKGROUND: Pursuant to studies, receiving the three key maternal health services (Antenatal Care, Skilled Delivery Service, and Postnatal Care) in a continuum could prevent 71% of global maternal deaths. Despite the Western African region being known for its high maternal death and poor access to maternal health services, there is a dearth of studies that delve into the spectrum of maternal health services uptake. Hence, this study aimed to assess the level and predictors of partial and adequate utilization of health services in a single analytical model using the most recent Demographic and Health Survey (DHS) data (2013-2021). METHODS: This study was based on the appended women's (IR) file of twelve West African countries. STATA software version 16 was used to analyze a weighted sample of 89,504 women aged 15-49 years. A composite index of maternal health service utilization has been created by combining three key health services and categorizing them into 'no', 'partial', or 'adequate' use. A multilevel multivariable multinomial logistic regression analysis was carried out to examine the effects of each predictor on the level of service utilization. The degree of association was reported using the adjusted relative risk ratio (aRRR) with a corresponding 95% confidence interval, and statistical significance was declared at p < 0.05. RESULTS: 66.4% (95% CI: 64.9, 67.7) and 23.8% (95% CI: 23.3, 24.2) of women used maternal health services partially and adequately, respectively. Togo has the highest proportion of women getting adequate health care in the region, at 56.7%, while Nigeria has the lowest proportion, at 11%. Maternal education, residence, wealth index, parity, media exposure (to radio and television), enrolment in health insurance schemes, attitude towards wife beating, and autonomy in decision-making were identified as significant predictors of partial and adequate maternal health service uptake. CONCLUSION: The uptake of adequate maternal health services in the region was found to be low. Stakeholders should plan for and implement interventions that increase women's autonomy. Program planners and healthcare providers should give due emphasis to those women with no formal education and from low-income families. The government and the private sectors need to collaborate to improve media access and increase public enrolment in health insurance schemes.

Development and validation of the relational behavior interactions scale for couples.

In this research, we developed and validated a measure of couple-based reported behavior interactions (RBI). Specifically, Study 1 was designed to describe the development of the scale and to examine its reliability; Study 2 (N = 222), was designed to examine factors that could differentiate men and women. Additionally, we tested if women's behaviors could predict their partner's behavior. Results from the exploratory factor analysis (EFA) revealed a three-factor structure for couples' RBI which were labelled: Social Companionship and Affective Behavior Interactions (SAI) (Factor 1), Fulfilling Obligations and Duties of the Partner (FOD) (Factor 2) and Openness in the Relationship (OR) (Factor 3). In linear regression analyses, there was a significant difference between men and women in the second factor, which represents behaviors associated with fulfilling the responsibilities of a partner. On the other hand, neither the SAI factor nor the OR factor showed any distinct gender differences. The SPSS PROCESS analysis revealed that women's Social Companionship and Affective Behavior Interactions (Factor 1), and Openness in the Relationship (Factor 3) significantly predicted their male partner's behaviors. The relationship duration significantly moderated the association between women's and men's behaviors for both factors. Results are discussed in light of the need for a broader understanding of romantic behavioral interactions.

Improving the robustness of the Sequentially Optimized Reconstruction Strategy (SORS) for visual field testing.

Perimetry, or visual field test, estimates differential light sensitivity thresholds across many locations in the visual field (e.g., 54 locations in the 24-2 grid). Recent developments have shown that an entire visual field may be relatively accurately reconstructed from measurements of a subset of these locations using a linear regression model. Here, we show that incorporating a dimensionality reduction layer can improve the robustness of this reconstruction. Specifically, we propose to use principal component analysis to transform the training dataset to a lower dimensional representation and then use this representation to reconstruct the visual field. We named our new reconstruction method the transformed-target principal component regression (TTPCR). When trained on a large dataset, our new method yielded results comparable with the original linear regression method, demonstrating that there is no underfitting associated with parameter reduction. However, when trained on a small dataset, our new method used on average 22% fewer trials to reach the same error. Our results suggest that dimensionality reduction techniques can improve the robustness of visual field testing reconstruction algorithms.

COVID-19 vaccine intercountry distribution inequality and its underlying factors: a combined concentration index analysis and multiple linear regression analysis.

Introduction: Inequitable access to COVID-19 vaccines among countries is a pressing global health issue. Factors such as economic power, political power, political stability, and health system strength contribute to disparities in vaccine distribution. This study aims to assess the inequality in vaccine distribution among countries based on these factors and identify their relationship with COVID-19 vaccine distribution. Methods: A Concentration Index (CI) analysis was conducted to evaluate inequalities in the distribution of COVID-19 vaccines among countries based on four separate variables: GDP per capita, political stability (PS), World Power Index (WPI), and Universal Health Coverage (UHC). Additionally, Multiple Linear Regression (MLR) analysis was employed to explore the relationship between vaccine distribution and these independent variables. Two vaccine distribution variables were utilized for result reliability. Results: The analysis revealed significant inequalities in COVID-19 vaccine distribution according to the countries' GDP/capita, PS, WPI, and UHC. However, the multiple linear regression analysis showed that there is no significant relationship between COVID-19 vaccine distribution and the countries' GDP/capita and that UHC is the most influential factor impacting COVID-19 vaccine distribution and accessibility. Discussion: The findings underscore the complex interplay between economic, political, and health system factors in shaping vaccine distribution patterns. To improve the accessibility to vaccines in future pandemics, Global Health Governance (GHG) and countries should consider working on three areas; enhance political stabilities in countries, separate the political power from decision-making at the global level and most importantly support countries to achieve UHC.

The burden of traumatic brain injury on caregivers: exploring the predictive factors in a multi-centric study.

BACKGROUND: Traumatic brain injury (TBI) is a significant cause of mortality and morbidity worldwide. With survivors often exhibiting degrees of function loss, a significant burden is exerted on their caregivers. The purpose of this study was to explore the predictive factors of caregiver burden among caregivers of patients with TBI. METHODS: Sixty-eight family members of individuals with a TBI who had been admitted to three hospitals were assessed in terms of caregiver burden using the Zarit Burden Interview. The association of caregiver burden with patients' baseline cognitive function according to the Montreal Cognitive Assessment (MoCA) test, as well as caregivers' sociodemographic characteristics, were evaluated using multiple regression analysis. RESULTS: Based on the multiple regression model, the MoCA score of the patients (std ß=-0.442, p < 0.001), duration of caregiving (std ß = 0.228, p = 0.044), and higher education of the caregivers (std ß = 0.229, p = 0.038) were significant predictors of caregiver burden. CONCLUSION: Overall, our findings highlight the importance of taking caregivers' psychosocial needs into account. Long-term caregivers of TBI patients with cognitive impairment should be viewed as vulnerable individuals who could benefit from psychosocial intervention programs, to improve their well-being and enabling them to enrich their care of the TBI patient.

Can routine assessment of older people's mental health lead to improved outcomes: A regression discontinuity analysis.

OBJECTIVE: To assess whether case finding for depression among people aged 65 and above improves mental health. DESIGN: Opportunistic evaluation using a regression discontinuity analysis with data from a randomised controlled trial. SETTING: The REFORM trial, a falls prevention study that recruited patients from NHS podiatry clinics. PARTICIPANTS: 1010 community-dwelling adults over the age of 65 with at least one risk factor for falling (recent previous fall or fear of falling). INTERVENTION: Letter sent to patient's General Practitioner if they scored 10 points or above on the 15-item Geriatric Depression Scale (GDS-15) informing them of the patient's risk of depression. MAIN OUTCOME MEASURE: GDS-15 score six months after initial completion of GDS-15. RESULTS: 895 (88.6%) of the 1010 participants randomised into REFORM had a valid baseline and six-month GDS-15 score and were included in this study. The mean GDS-15 baseline score was 3.5 (SD 3.0, median 3.0, range 0-15); 639 (71.4%) scored 0-4, 204 (22.8%) scored 5-9 indicating mild depression, and 52 (5.8%) scored 10 or higher indicating severe depression. At six months follow-up, those scoring 10 points or higher at baseline had, on average, a reduction of 1.08 points on the GDS-15 scale (95% confidence interval -1.83 to -0.33, p = 0.005) compared to those scoring less than 10, using the simplest linear regression model. CONCLUSION: Case finding of depression in podiatry patients based on a GDS-15 score of 10 or more followed by a letter to their General Practitioner significantly reduced depression severity. Whether this applies to all older patients in primary care is unknown. Further research is required to confirm these findings. Regression discontinuity analyses could be prespecified and embedded within other existing research studies.

Effects of physical and psychological symptoms on cancer-related fatigue among esophageal cancer patients.

BACKGROUND: Cancer-related fatigue (CRF) is considered one of the most prevalent and distressing symptoms among cancer patients and may vary among patients with different cancer types. However, few studies have explored the influence of physical and psychological symptoms on CRF among esophageal cancer (EC) patients without esophagectomy. Therefore, this study aimed to examine the effects of physical and psychological symptoms on CRF among EC patients without esophagectomy. METHODS: In the present study, a cross-sectional study was conducted from February 2021 to March 2022 in Liaoning Province, China. Among the 112 included participants, 97 completed our investigation. The questionnaires used consisted of the Brief Fatigue Inventory (BFI), the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and demographic and clinical information. Multivariate linear regression was conducted to test the relationships between physical and psychological symptoms and CRF. RESULTS: Of the 97 EC patients, 60.8% reported CRF (BFI ≥ 4). The mean age of the participants was 64.92 years (SD = 8.67). According to the regression model, all the variables explained 74.5% of the variance in CRF. Regression analysis indicated that physical symptoms, including constipation, diarrhoea, and difficulty swallowing, contributed to CRF. On the other hand, depressive symptoms increased the level of CRF among EC patients without esophagectomy. CONCLUSIONS: Given the high prevalence of CRF among EC patients without esophagectomy, it is urgent to emphasize the importance of fatigue management interventions based on physical and psychological symptoms to alleviate CRF in EC patients.

Effect of metformin on anti-mullerian hormone levels in women with polycystic ovarian syndrome: a systematic review and meta-regression analysis of randomized controlled trials with.

BACKGROUND: Several interventional studies have evaluated the potential anti-Mullerian hormone (AMH)-reduction effect of metformin. However, the results are still contradictory. In order to obtain a better viewpoint from them, this study aimed to comprehensively investigate the effects of metformin on AMH in the women with with polycystic ovarian syndrome (PCOS). METHODS: Scopus, PubMed/Medline, Web of Science, Cochrane, and Embase databases were searched using standard keywords to identify all controlled trials investigating the AMH levels following metformin administration. Pooled weighted mean difference and 95% confidence intervals were achieved by random-effects model analysis for the best estimation of outcomes. RESULTS: Sixteen studies with 484 participants' were included in this article. The pooled findings showed that AMH levels in the single arm clinical trials were significantly reduced (pooled WMD of -3.06 ng/ml; 95% confidence interval [CI] -4.03 to -2.10; P < 0.001) after use of metformin. Furthermore, compared to the control group, in randomized clinical trials, a reduced significant effect on AMH levels was observed following use of metformin (pooled WMD of -3.47 ng/ml; 95% CI -7.14 to -0.19; P = 0.047). Furthermore, higher reduction in the AMH levels with a metformin dosage ≤ 1500 mg/day and duration of treatment ≤ 12 weeks when compared to higher dosages and duration of intervention, observed in this meta-analysis. CONCLUSIONS: In conclusion, results this meta-analysis of clinical trials confirms the beneficial effect of the treatment with metformin in the reduction of the AMH levels in women.

A population-based urinary and plasma metabolomics study of environmental exposure to cadmium.

BACKGROUND: The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies. METHOD: We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure. RESULT: Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle). CONCLUSION: These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Understanding the effects of sub-inhibitory antibiotic concentrations on the development of ß-lactamase resistance based on quantile regression analysis.

AIMS: Quantile regression is an alternate type of regression analysis that has been shown to have numerous advantages over standard linear regression. Unlike linear regression, which uses the mean to fit a linear model, quantile regression uses a data set's quantiles (or percentiles), which leads to a more comprehensive analysis of the data. However, while relatively common in other scientific fields such as economic and environmental modeling, it is infrequently used to understand biological and microbiological systems. METHODS AND RESULTS: We analyzed a set of bacterial growth rates using quantile regression analysis to better understand the effects of antibiotics on bacterial fitness. Using a bacterial model system containing 16 variant genotypes of the TEM ß-lactamase enzyme, we compared our quantile regression analysis to a previously published study that uses the Tukey's range test, or Tukey honestly significantly difference (HSD) test. We find that trends in the distribution of bacterial growth rate data, as viewed through the lens of quantile regression, can distinguish between novel genotypes and ones that have been clinically isolated from patients. Quantile regression also identified certain combinations of genotypes and antibiotics that resulted in bacterial populations growing faster as the antibiotic concentration increased-the opposite of what was expected. These analyses can provide new insights into the relationships between enzymatic efficacy and antibiotic concentration. CONCLUSIONS: Quantile regression analysis enhances our understanding of the impacts of sublethal antibiotic concentrations on enzymatic (TEM ß-lactamase) efficacy and bacterial fitness. We illustrate that quantile regression analysis can link patterns in growth rates with clinically relevant mutations and provides an understanding of how increasing sub-lethal antibiotic concentrations, like those found in our modern environment, can affect bacterial growth rates, and provide insight into the genetic basis for varied resistance.

Psychosocial correlates of flourishing in the late lifespan.

BACKGROUND: Flourishing is a primary dimension of psychological well-being that contributes massively to the development of an active, purposeful, and respectful life, full of meaning, values, and personal interests that nurture social ties. AIMS: This study primarily intended to examine the contribution of satisfaction with family relations, resilience, metacognitive efficiency, and crystallized intelligence in predicting a flourishing measure in cognitively healthy older adults. Moreover, the impact of gender was investigated on flourishing, satisfaction with family ties, resilience, and metacognitive efficiency. METHODS: One hundred and eighty 65-94-year-old community dwellers were recruited in Sardinia (Italy). Participants self-rated their flourishing, satisfaction with their family connections, psychological hardness (i.e., a dimension of resilience), and cognitive function, whereas global cognitive efficiency and vocabulary were assessed through two internationally validated objective tests. RESULTS: A hierarchical regression analysis revealed that 30% of the variance in the flourishing condition was explained by satisfaction with family ties, resilience, and metacognitive efficiency. In addition, males exhibited higher flourishing and satisfaction with family ties than females, and the former group also reported being more autonomous and acting proactively to influence its destiny. CONCLUSION: Emotional support and rewarding relations with family members, the ability to face stressful events, and a good perception of one's cognitive efficiency play a crucial role in promoting flourishing in late adulthood.

The relationship between earthquake risk perceptions, religious orientation, spiritual well-being in individuals with and without earthquake experience: a cross-sectional study.

The physical and psychological effects of earthquakes on individuals with their experience dimension are important. This study aimed to examine the relationship between earthquake risk perception, religious orientation, and spiritual well-being among individuals with and without earthquake experience. The data collection instruments included a socio-demographic information questionnaire, earthquake risk perception scale, religious orientation scale, and three-factor spiritual well-being scale. Statistical evaluations were performed using independent samples t test, one-way ANOVA test, Mann-Whitney U test, Kruskal-Wallis test (Levene), Pearson correlation, and multiple linear regression analyses. About 59.9% of the participants had experienced an earthquake. Individuals with earthquake experience scored 33.04 ± 7.80 on the earthquake risk perception scale, 100.65 ± 20.80 on the religious orientation scale, and 119.66 ± 18.87 on the three-factor spiritual well-being scale. Those without earthquake experience scored 31.57 ± 7.74, 96.70 ± 18.46, and 114.09 ± 18.04 on the respective scales. The average scores on the earthquake risk perception scale were found to be statistically significant with respect to gender, while the average scores on the religious orientation scale and the three-factor spiritual well-being scale were found to be statistically significant with respect to both gender and substance use. The regression analysis revealed that religious orientation and three-factor spiritual well-being significantly predicted 13.5% of the variance in earthquake risk perception. Studies to increase individuals' risk perception are important in minimizing the destructive effects of earthquakes in countries in the earthquake zone.

Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer.

Depending on the source of the blastophore, there are various subtypes of laryngeal cancer, each with a unique metastatic risk and prognosis. The forecasting of their prognosis is a pressing issue that needs to be resolved. This study comprised 5953 patients with glottic carcinoma and 4465 individuals with non-glottic type (supraglottic and subglottic). Five clinicopathological characteristics of glottic and non-glottic carcinoma were screened using univariate and multivariate regression for CoxPH (Cox proportional hazards); for other models, 10 (glottic) and 11 (non-glottic) clinicopathological characteristics were selected using least absolute shrinkage and selection operator (LASSO) regression analysis, respectively; the corresponding survival models were established; and the best model was evaluated. We discovered that RSF (Random survival forest) was a superior model for both glottic and non-glottic carcinoma, with a projected concordance index (C-index) of 0.687 for glottic and 0.657 for non-glottic, respectively. The integrated Brier score (IBS) of their 1-year, 3-year, and 5-year time points is, respectively, 0.116, 0.182, 0.195 (glottic), and 0.130, 0.215, 0.220 (non-glottic), demonstrating the model's effective correction. We represented significant variables in a Shapley Additive Explanations (SHAP) plot. The two models are then combined to predict the prognosis for two distinct individuals, which has some effectiveness in predicting prognosis. For our investigation, we established separate models for glottic carcinoma and non-glottic carcinoma that were most effective at predicting survival. RSF is used to evaluate both glottic and non-glottic cancer, and it has a considerable impact on patient prognosis and risk factor prediction.

The association between quality of life and diabetes: the Bushehr Elderly Health Program.

BACKGROUND AND OBJECTIVE: Considering the importance of diabetes and its increased prevalence with aging, this study aimed to evaluate the association between diabetes status and quality of life (QOL) and the determining factors in individuals over 60. METHODS: Two thousand three hundred seventy-five individuals including 819 (34.5%) with diabetes, aged 69.4 ± 6.4, from Bushehr Elderly Health Program (BEHP) were enrolled. We categorized the participants as non-diabetic, controlled diabetic, and poorly controlled diabetic. The QOL was assessed using the SF-12 questionnaire. The physical (PCS) and mental (MCS) component summaries of QOL were estimated. We compared the SF-12 domains and components between the categories using ANOVA. Further, the association of diabetes status with PCS and MCS was assessed after adjustment for possible confounders including age, sex, depression, cognitive impairment, physical activity, and other relevant factors using linear regression analysis. RESULTS: Individuals with diabetes had lower PCS (40.9 ± 8.8 vs. 42.7 ± 8.6, p-value < 0.001), and MCS scores (45.0 ± 10.2 vs. 46.4 ± 9.4, p-value < 0.001) compared to participants without diabetes. No significant differences were observed in PCS or MCS scores between controlled or poorly controlled individuals with diabetes. Diabetes status was associated with PCS and MCS scores in univariable analysis. Regarding physical component of QOL, after adjusting for other confounders, poorly controlled diabetes was significantly associated with PCS [beta: -1.27 (-2.02, -0.52)]; some other determinants include depression [-7.66 (-8.51, -6.80)], male sex [3.90 (3.24,4.57)], and good physical activity [1.87 (1.17,2.57)]. As for the mental component, controlled diabetes was significantly associated with MCS [-1.17 (-2.13, -0.22)]; other contributing factors include depression [-14.35 (-15.34, -13.37)], male sex [1.97 (1.20,2.73)], good physical activity [-1.55 (-2.35, -0.75)], and smoking [-1.42 (-2.24, -0.59)]. BMI had an inverse association with PCS [-0.19 (-0.26, -0.13)] and a direct association with MCS [0.14 (0.07,0.21)]. CONCLUSION: Individuals with diabetes exhibited reduced QOL scores. Upon adjusting for other variables, it was found that uncontrolled diabetes correlated with decreased PCS scores, whereas controlled diabetes was linked to lower MCS scores. Factors such as depression and being female were identified as contributors to diminished QOL in both physical and mental aspects. These results have the potential to guide healthcare decision-making, facilitating the creation of tailored interventions aimed at improving the QOL for individuals with diabetes, with a specific focus on women and depression.

On the correlation between gratitude and resilience in medical students.

Objective: Medical students' health and resilience have increasingly been the subject of current research in recent years. A variety of interventions are recommended to strengthen resilience or its known or suspected influencing factors, although the literature shows that the evidence on the effectiveness of the interventions is inconsistent. The present study investigated whether gratitude is a direct protective factor for resilience in medical students or whether resilience factors (optimism, self-efficacy, social support) and stress mediate the effects of gratitude on resilience. Methods: 90 medical students at Witten/Herdecke University took part in the study that determined their gratitude, resilience, optimism, self-efficacy, social support and stress levels using validated questionnaires (GQ-6, RS-25, LOT-R, SWE, F-SozU, PSS). Correlations were analyzed using Pearson correlation coefficients. In addition, a multivariate regression analysis and a path analysis were calculated to determine the direct and indirect effects of gratitude on resilience. Results: Multivariate regression analysis showed that only optimism, social support and stress were significantly associated with resilience (B=0.48, 95% CI: 0.31, 0.66; B=0.23, 95% CI: 0.01, 0.44 and B=-0.02, 95% CI: -0.03, -0.001, respectively). The direct effect of gratitude on resilience was minimal and not significant in the path analysis. However, there was an indirect effect of gratitude on resilience (B=0.321; p<0.05). Mediation via the optimism variable was mainly responsible for this effect (indirect effect B=0.197; p<0.05). Conclusion: This study shows that gratitude has only a minimal direct influence on resilience. However, results indicate that optimism as a mediating factor strengthens the resilience of medical students. Against this background, it may be useful to integrate interventions that promote an optimistic attitude into medical studies in order to strengthen the mental health of future doctors in the long term.

Nursing-care for family caregivers of terminally ill cancer patients to enhance preparedness for death.

Family caregivers of terminally ill cancer patients prepare for a patient's death. Nursing-care for preparedness is effective for their psychological health. This study aims to structuralize nursing-care for preparedness and extract related factors while presenting the implications for improved quality of care. Data from a cross-sectional survey of general ward and palliative care unit nurses in designated cancer care hospitals (n=561) was analyzed with exploratory factor analysis and multiple regression analyses. The results of the analysis, the structure was classified into "Nurse-centered support" and "Support through inter-professional work." Both supports were practiced significantly more frequently in palliative care units than general wards. Related factors in general wards were; communication skills, cooperation with doctors, the existence of certified nurse/certified nurse specialists as consultants, attitudes toward care of the dying, frequency of death conferences, and cooperation with specialist cancer counselors. Therefore, the results can help improve the quality of family care in palliative care, especially in general wards.