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To identify factors associated with health behaviours among stroke survivors, through a multi-centre study.
A sequential mixed methods design.
In the quantitative research phase, a total of 350 participants were recruited through multi-stage sampling from December 2022 to June 2023. General information questionnaires, The Stroke Prevention Knowledge Questionnaire (SPKQ), Short Form Health Belief Model Scale (SF-HBMS), Health Promoting Lifestyle Profile (HPLPII), and the WHOQOL-BREF (World Health Organization Quality of Life Questionnaire, Brief Version) were distributed across five tertiary hospitals in Henan province, China. For the qualitative research component, semi-structured interviews were conducted to explore the barriers and facilitators of health behaviour. This study adheres to the GRAMMS guidelines.
A total of 315 participants (90.0%) completed the survey. Identified barriers to health behaviour included residing in rural areas, higher scores on the Charlson Comorbidity Index (CCI) and mRS, as well as lower scores on SPKQ, SF-HBMS and WHOQOL-BREF. Twenty-four individuals participated in qualitative interviews. Twenty-eight themes were identified and categorised by frequency, covering areas such as knowledge, skills, intentions, social influences, social/professional role and identity, environmental context and resources, beliefs about capabilities, beliefs about consequences and behavioural regulation. Both quantitative and qualitative data suggested that health behaviour among stroke survivors is at a moderate level, and the identified barrier factors can be mapped into the COM-B model (Capability, Opportunity, Motivation and Behaviour).
The study indicates that key barriers to health behaviour among stroke survivors align with the COM-B model. These identified factors should be carefully considered in the planning of future systematic interventions aimed at improving health behaviours among stroke survivors.
Patients were invited to completed questionnaires in the study and semi-structured interviews. The investigators provided explanation of this study’ content, purpose and addressed issues during the data collection.
Diabetic foot ulcers (DFUs) are chronic, difficult-to-heal wounds with a very high incidence of amputation. For patients with DFUs, prevention of amputation is crucial. However, the risk factors associated with DFU amputation and the extent to which different risk factors increase the risk of amputation are still uncertain. This study intends to provide a clinical basis for early intervention in DFU by retrospectively analysing the risk factors for DFU amputation. A retrospective analysis of 200 patients with DFUs admitted between October 2019 and October 2023 was conducted. Sixty-eight of the 200 underwent amputations. The overall amputation rate was 34%. Multiple logistic regression model showed that neutrophil/lymphocyte ratio (OR = 1.943; 95% CI:1.826–2.139), white blood cell (OR = 1.143; 95% CI:1.034–1.267), C-reactive protein (OR = 1.307; 95% CI:1.113–2.194) and Wagner grading (OR = 2.783; 95% CI: 1.751–4.302) were independent risk factors for amputation, while haemoglobin (OR = 0.742; 95% CI:0.638–0.965) and high density lipoprotein were independent protective factors for amputation (OR = 0.168; 95% CI:0.037–0.716), and further Receiver Operating Characteristic Curve curves showed that they showed high accuracy and were good predictors of amputation of DFUs.
In this study, we explored the use of thermal imaging technology combined with computer vision techniques for assessing surgical incision healing. We processed 1189 thermal images, annotated by experts to define incision boundaries and healing statuses. Using these images, we developed a machine learning model based on YOLOV8, which automates the recognition of incision areas, lesion segmentation and healing classification. The dataset was divided into training, testing and validation sets in a 7:2:1 ratio. Our results show high accuracy rates in incision location recognition, lesion segmentation and healing classification, indicating the model's effectiveness as a precise and automated diagnostic tool for surgical incision healing assessment. Conclusively, our thermal image-based machine learning model demonstrates excellent performance in wound assessment, paving the way for its clinical application in intelligent and standardized wound management.
Facial soft tissue injuries, often resulting in scarring, pose a challenge in reconstructive and aesthetic surgery due to the need for functional and aesthetic restoration. This study evaluates the efficacy of recombinant human growth factors (rhGFs) in scar remodelling for such injuries. A retrospective evaluation was conducted from January 2020 to January 2023, involving 100 patients with facial soft tissue injuries. Participants were divided equally into a control group, receiving standard cosmetic surgical repair, and an observation group, treated with rhGFs supplemented cosmetic surgery. The study assessed scar characteristics (pigmentation, pliability, vascularity, height), hospital stay duration, tissue healing time, complication rates and patient satisfaction. The observation group demonstrated significant improvements in all scar characteristics, with notably better pigmentation, pliability, vascularity and height compared with the control group. The rhGF treatment also resulted in reduced hospital stay duration and faster tissue healing. Notably, the total complication rate was significantly lower in the observation group (10%) compared with the control group (34%). Additionally, patient satisfaction levels were higher in the observation group, with 98% combined satisfaction compared with 76% in the control group. The application of rhGFs in treating facial soft tissue injuries significantly enhances scar remodelling, expedites healing, reduces complications and improves patient satisfaction. These findings establish rhGFs as a valuable tool in the management of facial soft tissue injuries, highlighting their potential in improving both functional and aesthetic outcomes.
by Junyu Zhang, Zhixi Hu, Yuquan Tan, Jiahao Ye
BackgroundHeart Failure (HF) is a widespread condition that affects millions of people, and it is caused by issues with the heart and blood vessels. Even though we know hypertension, coronary artery disease, obesity, diabetes, and genetics can increase the risk of HF and Chronic Kidney Disease (CKD), the exact cause of these conditions remains a mystery. To bridge this gap, we adopted Mendelian Randomization (MR), which relies on genetic variants as proxies.
MethodsWe used data from European populations for our Bidirectional Two-Sample MR Study, which included 930,014 controls and 47,309 cases of HF from the HERMES consortium, as well as 736,396 controls and 51,256 cases of CKD. We also employed several MR variations, including MR-Egger, Inverse Variance Weighted (IVW), and Weighted Median Estimator (WME), to guarantee the results were accurate and comprehensive.).
ResultsIn this study, the MR analysis found that individuals with a genetic predisposition for HF have an elevated risk of CKD. Our study revealed a significant association between the genetic prediction of HF and the risk of CKD, as evidenced by the IVW method [with an odds ratio (OR) of 1.12 (95% CI, 1.03–1.21), p = 0.009] and the WME [with an OR of 1.14 (95% CI, 1.03–1.26), p = 0.008]. This causal relationship remained robust even after conducting MR analysis while adjusting for the effects of diabetes and hypertension, yielding ORs of 1.13 (IVW:95% CI, 1.03–1.23), 1.12 (MR-Egger: 95% CI, 0.85–1.48), and 1.15 (WME:95% CI, 1.04–1.27) (p = 0.008). However, in the reverse analysis aiming to explore CKD and renal function as exposures and HF as the outcome, we did not observe a statistically significant causal link between CKD and HF.
ConclusionOur study demonstrates the significance of HF in CKD progression, thus having meaningful implications for treatment and the potential for discovering new therapies. To better understand the relationship between HF and CKD, we need to conduct research in a variety of populations.
by Shuang Xu, Qiongyu Zhang, Jiayan Zhou
The objective of this study was to investigate the direct effects of pain-induced depression and anxiety, as well as the mediating role of psychological resilience, on the psychological distress associated with rheumatoid arthritis. The method involved a sample of 196 patients with rheumatoid arthritis and applied the Hospital Anxiety and Depression Scale, Connor–Davidson Resilience Scale, and visual analog scale for pain. Bivariate and path analyses were performed, and a multiple mediational model was utilized. Results showed that all correlations among study variables were significant (pDrawing on the conservation of resources theory, this study examines the underlying process through which servant leadership is associated with nurses' in-role performance. Specifically, we test the indirect effect of servant leadership on in-role performance via a sequential mediating mechanism of job autonomy and emotional exhaustion.
A time-lagged design was implemented using data gathered from two-wave online surveys (1 week apart) of registered nurses from Jiangsu Province, China.
Between September 2022 and February 2023, we used Wenjuanxing and Credma, which are two powerful and user-friendly data collection platforms, to distribute online surveys to potential participants. We received a total of 220 usable responses and employed the PROCESS Model 4 and Model 6 to assess our proposed hypotheses.
Our proposed model was supported. Servant leadership has a positive indirect effect on nurses' in-role performance through job autonomy and emotional exhaustion. Job autonomy has a negative effect on emotional exhaustion. Additionally, job autonomy mediates the negative relationship between servant leadership and emotional exhaustion.
The present research extends existing nursing studies by unravelling the complex mechanisms underlying the relationship between servant leadership and nurses' in-role performance. Our study also identifies the underlying mechanism of how servant leadership mitigates emotional exhaustion by supporting nurses' job autonomy.
The sequential mediation results provide us with a more fine-grained understanding of the relationship between servant leadership and nurses' in-role performance. It further promotes job autonomy and decreases emotional exhaustion, which supports the UN Sustainable Development Goal #3 (Good Health and Well-being).
This study addresses the UN Sustainable Development Goal #3: ‘To ensure healthy lives and promote well-being for all at all ages’ and the healthcare providers will benefit from our study. Therefore, the study contributes to a more sustainable organization and society.
As a devastating neurodegenerative disease, Alzheimer's disease (AD) imposes a considerable direct and indirect financial burden. However, effective drug treatment options are limited. In recent years, game therapy has become a research hotspot in this field.
The purpose of this study was to synthesize the conclusions of existing studies and integrate the data to evaluate the effects of game therapy on people living with dementia (PLWD).
We included randomized clinical trials and quasi-experimental studies which assessed the impacts of game therapy on PLWD and took cognitive function, quality of life, and depression as outcome indicators. Two trained researchers independently screened the studies, evaluated the quality, and extracted the data. Statistical analysis was performed by Review Manager (Revman) 5.3 and STATA16.0 software.
There were 12 studies involving 877 PLWD included, total. The results of the meta-analysis demonstrated that the Mini-Mental State Examination (MMSE) scores of the test group were significantly higher than that of the control group (SMD = 2.69, 95% CI [1.88, 3.51], p < .01), and the Cornell Scale for Depression in Dementia scores of the test group were significantly lower than those of the control group (SMD = −4.28, 95% CI [−6.96, −1.60], p < .01); but in terms of quality of life (SMD = 0.17, 95% CI [−0.82, 1.16], p = .74), the difference was not statistically significant.
Game therapy can improve cognitive function and depression in PLWD. The combination of different types of games can improve the different clinical symptoms of PLWD, and different intervention time also have different effects on the outcome, which shows that we can develop unique, systematic, safe, and scientific game intervention programs for PLWD to improve their cognitive function and depression.
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