Inquiry-The Journal of Health Care Organization Provision and Financing最新文献

The Slovenian experience of establishing community-based mental health (CBMH) services, including expanding CBMH centers, securing funding, enhancing training, and involving mental health workers, offers a valuable example for the Philippines and other LMICs. It shows that community-based mental health reform needs professionals, empowered communities, and capable local leaders. This paper emphasizes the applicability of Slovenian insights in LMICs, using the Philippines as an example. It highlights the roles of barangay officials and BHWs in implementing CBMH, as they can bridge policy and practice, clinic and community, and stigma and understanding. Their effectiveness depends on clear mandates, ongoing funding, and culturally sensitive training that respects local beliefs and evidence-based care. Overall, the future of community mental health in the Philippines and other LMICs could involve transforming community resources, such as barangays, into recovery centers in which mental well-being is integrated into governance, culture, and community life.

The use of complementary and alternative medicine (CAM) is rapidly increasing for various non-communicable diseases, including cancer, presenting a complex challenge. However, few studies have examined CAM utilization in Nepal. A cross-sectional, quantitative, descriptive study design was conducted in a cancer-specialized hospital in Nepal to determine the use of CAM using a 29-item survey questionnaire designed to collect data on demographic and clinical characteristics and CAM utilization practices, based on the existing literature. Descriptive statistics and multivariate binary logistic regression were conducted in SPSS version 29 to identify significant influencing factors, with P-values < 0.05 considered statistically significant. Out of 101 participants, more than half (56.4%) used it for over a year. The commonly observed CAM was naturopathy and herbal products (such as amala, tulushi, aleovera, barley & wheat grass) (53.4%) and dietary supplements (43.6%). Majority of CAM users perceived it as effective (88.1%) and helpful in mostly alleviating nausea (76.4%). In multivariate analysis, only the use of yoga and meditation was independently associated with planning to continue CAM use (AOR: 8.939; 95% CI: 1.68-47.567). Majority of the patients with cancer were using CAM for more than a year, with naturopathy and herbal products among the highest modalities of CAM. The prolonged use of CAM among patients underscores the need to further educate patients on its long-term consequences, along with patient safety.

Robust predictive models are essential for preventing and mitigating risks associated with public drinking water systems (PWS), which pose significant public health threats and incur substantial medical costs. This study introduces a novel approach by comparing the performance of Logit, Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost) models in predicting risks based on PWS characteristics, community attributes, and regulatory developments, rather than relying on water quality and hydrological parameters. The study yields 3 key findings: (1) XGBoost outperforms Logit and SVM, though all models perform less effectively for predicting health-based risks; (2) community and regulatory characteristics exert a greater influence on risk predictions than PWS characteristics; and (3) XGBoost performs comparably to the water parameter-based prediction approach, with the added benefits of lower cost and suitability for long-term forecasting. This innovative approach offers substantial potential for residents, environmental advocates, and policymakers to better anticipate and address PWS risks by focusing on fundamental social determinants.

Post-traumatic stress disorder (PTSD) is often debilitating, with current treatments limited by low adherence, high costs, and accessibility issues. Innovative technologies such as virtual reality (VR), augmented reality (AR), and therapeutic video games provide immersive environments that may improve treatment outcomes. This systematic review and meta-analysis evaluated the efficacy of these approaches and explored their potential advantages over traditional methods. A comprehensive search of PubMed, PsycINFO, CINAHL, Web of Science, and Cochrane identified relevant studies. Two reviewers independently screened articles, extracted data, and assessed quality using the Mixed Methods Appraisal Tool (MMAT). A random-effects model was used to calculate pooled effect sizes (Hedges' g), and heterogeneity was evaluated with the Q test and I² statistic. Publication bias was examined with funnel plots, Egger's, and Begg's tests. Analyses were performed in Stata version 17.0. From 480 records, 21 studies were included in the review and 12 in the meta-analysis. VR-based treatments yielded a pooled effect size of -0.35 (95% CI [-0.57, -0.13]), indicating a small-to-moderate reduction in PTSD symptoms. The effect was statistically significant (z = -3.13, P < .01), with moderate heterogeneity (I² = 46.28%, P = .03). Funnel plots and statistical tests suggested minimal publication bias. Meta-regression showed no moderating effect of gender. Subgroup analyses indicated significant benefits in male-only samples, participants aged 20 to 30 and over 40, and studies with follow-up periods ≤7 months. Larger effects were observed in studies with 15 to 30 participants. VR, AR, and video game interventions significantly reduce PTSD symptoms and may enhance accessibility and engagement compared to traditional treatments. These findings support the integration of immersive technologies into therapeutic practice to improve outcomes for individuals with PTSD.

To investigate the predictive value of the C-reactive protein-triglyceride-glucose index (CTI) for liver disease events in a community-based middle-aged and older population. Based on data from 5 waves of the China Health and Retirement Longitudinal Study (CHARLS) database, this study utilized data from the 2011 and 2015 waves, which included blood samples. A time-dependent Cox regression model was employed to analyze the association between CTI and the risk of liver disease events. Rigorous model testing, along with robustness and heterogeneity analyses, were conducted. A total of 733 incident liver disease events were documented during the follow-up period. After full adjustment for confounding factors, each 1-unit increment in CTI was significantly associated with a 21.0% increased risk of liver disease (Hazard Ratio [HR] = 1.210, 95% Confidence Interval [CI]: 1.109-1.321). In addition, each quartile increase in baseline CTI was associated with a statistically significant 12.2% elevated risk of incident liver disease. This association remained robust in sensitivity analyses after excluding events with potential reverse causality and replacing biomarkers. Subgroup analyses further identified consistent patterns of this association across different populations. This study is the first to demonstrate, within a nationally representative community-based cohort of middle-aged and older adults, that the CTI is an independent and robust predictor of incident liver disease. As a composite metabo-inflammatory marker, the CTI model exhibited slightly better model fit (lower AIC/BIC) and marginally higher discriminatory ability (C-index) than the single-marker models of TyG index and CRP alone. It can be utilized to identify high-risk individuals in middle-aged and older populations, providing a novel epidemiological tool for the early warning of liver disease.

Multiple sclerosis is a progressive neurological disorder characterised by sensory and motor impairments. This study was conducted to investigate the relationship between lower extremity sensation, muscle strength and endurance, balance, gait, and risk of falling in patients with MS. Light touch sensation (LTS) was evaluated using the Semmes-Weinstein monofilament test (threshold: ≥2/3 correct responses). Vibration sensation was tested using a 128 Hz vibration fork. Muscle strength was measured in Newtons using a hand-held dynamometer, and core muscle endurance was assessed using a pressure biofeedback device. Static balance was assessed using the single leg stand test (SLST), dynamic balance using the Y balance test (YBT), gait by the footprint method, and fall risk using the Falls Efficacy Scale-International (FES-I). Back extensor muscle strength showed a significant correlation with non-dominant YBT performance (P = .030). Abdominal muscle strength correlated with SLST performance (eyes open/closed), while lower extremity strenght correlated with both SLST and YBT outcomes (P < .05). Gait parameters were significantly related to trunk and lower extremity strength (P < .05). Back extensors, hip flexors, gluteus maximus, and hamstring muscle strength were associated with fall risk (P < .05). Importantly, LTS showed a positive association with YBT scores and a negative association with risk of falling (P < .05). Sensory and motor factors interactively contribute to balance, gait, and fall risk in MS. To reduce the risk of falls and improve functional outcomes in MS, a targeted rehabilitation programme combining sensory and motor assessments is required.

This scoping review examined barriers and facilitators influencing dental care access among adolescents (ages 10-19) using a multilevel health disparities framework to capture behavioral, social, and structural determinants. Following the Arksey and O'Malley framework and Joanna Briggs Institute methodology, 6 databases and gray literature were searched for English-language studies (2011-present) on dental care access among adolescents. Data were categorized at individual, interpersonal, community, and societal levels. Fifty-eight studies met inclusion criteria. Common barriers included dental anxiety, minority status, low parental education, limited income, weak peer support, geographic disparities, unstable insurance, and provider shortages. Facilitators included public insurance programs, school-based dental clinics, culturally tailored education, caregiver modeling, and community engagement. An ecomap illustrated multilevel predictors and research gaps, identifying strategies such as peer-led programs, safety-net investment, patient navigation, and policy reforms to strengthen access. Adolescent dental access is shaped by intersecting determinants at behavioral, social, and systemic levels. Coordinated efforts integrating infrastructure, health education, and policy interventions are essential to reduce oral health disparities and inform future research directions. The multilevel ecomap presented in this review provides an adaptable, evidence-based foundation for developing actionable strategies to improve adolescent oral health across different social backgrounds and geographic regions.

Young and middle-aged patients with coronary heart disease who have undergone percutaneous coronary intervention often find it difficult to participate in secondary cardiac rehabilitation. This study examines patient experiences in cardiac rehabilitation using health empowerment theory as a framework. Purposive sampling was used to collect data through semi-structured interviews, which were analysed using Colaizzi's phenomenological approach. Five themes emerged from the data: (1) Personal growth, (2) Self-acceptance, (3) Life Purpose and motivation, (4) Social support, and (5) Utilisation of social services. The findings are consistent with all dimensions of health empowerment theory. The results of the study emphasise the importance of individualised empowerment and highlight the need to address the requirements for cardiac rehabilitation benefits, providing a new perspective for improving cardiac rehabilitation intervention programmes.

Women remain significantly underrepresented in the Merchant Marine workforce, and little empirical research has examined how gendered occupational settings influence their perceived well-being. Guided by Bronfenbrenner's Ecological Systems Theory, this mixed-methods study explored how individual experiences, organizational culture, and policy frameworks interact to shape gender inclusion and occupational well-being among Colombian women seafarers. Seventeen officers (73.9% of the accessible population) completed a descriptive survey and in-depth interviews. Quantitative data profiled demographic and professional characteristics, while qualitative narratives revealed experiences of restricted technical duties, harassment, and limited institutional support within male-dominated environments. Despite these barriers, participants demonstrated strong agency and adaptive coping strategies that sustained professional engagement. Findings highlight that perceived well-being is shaped by micro-level personal factors, meso-level organizational dynamics, and macro-level regulatory contexts. The study contributes to Gender Equity and Occupational Health scholarship by linking individual experiences to institutional and regulatory environments and recommends gender-responsive maritime training, independent reporting mechanisms, and integrated mental-health policies to promote equitable and sustainable seafaring careers.

Timely identification of critically ill patients for do-not-resuscitate (DNR) decisions is crucial to support shared decision-making and ethical end-of-life care. This study developed an explainable multitask learning (MTL) model using the MIMIC-IV database to predict the DNR decision within 24 h. The model was trained on data from 7789 adult patients who were admitted to the intensive care units (ICUs) with a length of stay longer than 3 days, using features including clinical parameters and nursing assessments across a 72-h window. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), calibration plots, and decision curve analysis. Interpretability was illustrated by SHapley Additive exPlanations (SHAP) plots and partial dependence plots (PDP). Error analysis was performed to explore the strengths and limitations of the established model. The MTL model achieved superior performance compared to single-task learning (AUROC: 0.798 vs 0.764). SHAP and PDP plots demonstrated that verbalization ability, ventilatory support, and muscle strength as key features. Error analysis identified a subgroup of patients with extreme ventilatory demand and muscle weakness who contributed to misclassification; excluding this subgroup improved AUROC from 0.792 to 0.827. We developed a DNR prediction model and demonstrated the feasibility of integrating an explainable model into ICU care for a nudge to consider the DNR-relevant issue.