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This study aimed to validate the mediating role of nurses' AI trust in the relationship between AI uncertainties and AI competence.
A cross-sectional study.
A purposive sample of 550 registered nurses with at least 1 year of clinical experience from three tertiary and two secondary hospitals in Jinan and Hangzhou, China, was used. Data were collected using structured questionnaires assessing AI uncertainty, trust and competence. Demographic data included gender, age, education level, years of clinical experience, professional title and hospital level. Mediation analysis.
Most nurses were from tertiary hospitals (88.9%), held a bachelor's degree (87.6%), and had over 6 years of experience. The mediating role of AI trust between AI uncertainties and AI competence is validated. AI uncertainties affected AI trust (B = 0.39, p < 0.0001), explaining 10% of the variance. AI uncertainties and AI trust affected AI competence (B = 0.25 and 0.67, p < 0.0001), explaining 63% of the variation. AI trust's total effect was 0.51, comprising direct and indirect effects of 0.25 and 0.26, respectively.
Hospitals can reduce uncertainty through an AI-transparent decision-making process, providing clinical examples of AI and training nurses to use AI, thereby increasing trust. Second, AI systems should be designed to consider nurses' psychological safety needs. Hospital administrators utilise optimised AI technology training and promotional techniques to mitigate nurses' resistance to AI and enhance their positive perceptions of AI competence through trust-building mechanisms.
Impact: Enhancing nurses' AI trust can reduce uncertainty and improve their competence in clinical use. Strategies such as transparency, explainability and training programmes are crucial for improving AI implementation in healthcare.
This study focused solely on clinical nurses and did not include patients or the public.
The study adhered to STROBE guidelines.
by Yaowen Hu, Faliang Gao, Yuan Yang, Wei Yang, Huibo He, Jie Zhou, Yujie Zhao, Xi Chen, Wenyan Zhao, Xiaopeng He
ObjectiveTo investigate the prevalence of vitamin D deficiency and its relationship with all-cause and cause-specific mortality among middle-aged and elderly populations in the U.S.
MethodsData were sourced from the National Health and Nutrition Examination Survey (NHANES) 2001–2018. A total of 22,130 participants aged 40–70 years were included. Serum 25-hydroxy vitamin D [25(OH)D] concentrations were measured and categorized. The primary outcome was all-cause mortality, and secondary outcomes were cardiovascular disease (CVD) and cancer mortality. Multivariable-adjusted models and various statistical analyses were employed.
ResultsThe prevalence of vitamin D deficiency (≤50.00 nmol/L) was 33.59%, and insufficiency (≤75.00 nmol/L) was 71.74%. For all-cause mortality, the multivariate adjusted hazard ratios (HRs) across different 25(OH)D levels (p = 0.0069, 0.59 (0.49,0.72) p p Conclusion
This study found that higher serum 25-hydroxyvitamin D concentrations are linked to lower all-cause, cardiovascular, and cancer mortality. The relationship is nonlinear: increases in concentration reduce death risk below a certain threshold, but above it, the association weakens. Further research is needed to understand causal mechanisms.
To evaluate the prevalence of frailty and its impact on quality of life (QoL) in older Chinese breast cancer (BC) patients, which have not been thoroughly reported in this population.
A prospective multi-centre cross-sectional registry study.
Data were collected from Cancer Hospital of the Chinese Academy of Medical Sciences, Peking University Third Hospital and Beijing Chaoyang District San Huan Cancer Hospital between October 2021 and July 2023.
BC patients aged over 65 years were enrolled in this study. They completed three assessment scales including the FRAIL scale, Hospital Anxiety and Depression Scale (HADS) and European Organization for Research and Treatment of Cancer Quality of Life questionnaire Core 30 (EORTC QLQ-C30), to screen for frailty, related factors and QoL. Clinical and pathological data were also collected. Analysis of frailty and prefrailty risk factors was performed via logistic regression. A multivariable linear regression model was used to evaluate the mean differences in scores for each QoL domain between patients with different frailty statuses.
A total of 946 patients were enrolled from three hospitals in Beijing between October 2021 and July 2023. Their median age was 69 years and 73.6% of them had early-stage breast cancer. Further, 37.2% of these patients had ≥ 1 comorbidity. The prevalence of frailty was 8.8% and frailty was more common in those with aged ≥ 75 years (22.3%), those with advanced tumours (15.6%), those with anxiety (31.3%) and those with depression (29.3%). More than half (57.2%) of the patients were prefrail. Regression analysis revealed that older age (odds ratio [OR] 1.12 [95% CI 1.07–1.17], p < 0.001), an advanced tumour (OR 2.27 [1.33–3.89], p = 0.003), anxiety (OR 2.74 [1.37–5.48], p = 0.004) and depression (OR 3.84 [1.97–7.49], p < 0.001) were significantly associated with frailty. After adjusting for other factors, different frailty states were shown to be independent influencing factors for QoL in both the functional and the symptom domains (all p < 0.05).
Our study provides data on the prevalence of frailty and prefrailty in older Chinese patients with BC. Both conditions are closely related to poor QoL. It is helpful for oncologist and clinical care to making intervention and better treatment decisions.
The study adhered to the STROBE checklist.
This study provides detailed data on the prevalence of frailty in older Chinese patients with BC and correlative factors. It suggests that clinical care should fully assess patients' frailty before making treatment decisions and provide early intervention for related factors.
Patients participated in the implementation of the project (including the informed consent and questionnaire process). No other public contribution to this research.
This study provides data on the prevalence of frailty in Chinese older BC patients and correlative factors. It indicates that clinicians should fully assess patients' frailty before making treatment decisions and provide early intervention for related factors.
ChiCTR2200056070
While previous research has established that resilience is affected by various factors, these studies have primarily focussed on individual variables associated with resilience, without providing insights into how to influence the rate of change in resilience.
To examine the trajectory of resilience and identify the factors associated with changes in resilience among spousal caregivers of patients with newly diagnosed advanced cancer receiving treatment during the first 6 months.
An observational longitudinal study.
A total of 312 spousal caregivers of patients with newly diagnosed advanced cancer were recruited from January 2022 to December 2022 in Yancheng, China. Three data collection points were established, spanning from the first month to 6 months after initial cancer treatment. A latent growth model was employed to depict the resilience trajectory at various time points. A latent growth model with time-invariant covariates was adopted to determine the factors influencing resilience trajectory. The study adhered to the STROBE checklist for proper reporting.
Throughout the follow-up period, the participants experienced a significant increase in resilience. Gender, family income, the patient's health status, spirituality and belief in familism were significantly associated with the baseline resilience level. Moreover, family income, the patient's health status, spirituality, caregiver burden and belief in familism were significantly associated with the rate of resilience change over time.
Spousal caregivers demonstrated a linear increase in resilience during the first 6 months after initial treatment. Meanwhile, changes in resilience were influenced by multiple factors during the early phase of cancer treatment. Thus, more attention should be paid to early identification and implementation of targeted interventions.
Healthcare professionals should understand the change in resilience among spousal caregivers and conduct timely mental health interventions to enhance the resilience of families affected by cancer.
The Guidance for Reporting Involvement of Patients and the Public-Short Form reporting checklists were used to improve patient and public involvement.
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