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Colonoscopy is an essential procedure for the early diagnosis of colorectal conditions; however, over 60% of patients undergoing non-sedated colonoscopy report moderate to severe pain. This study aims to investigate the central analgesic mechanisms of transcutaneous electrical nerve stimulation based on wrist-ankle acupuncture theory (TENS-WAA). A multimodal approach combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) will be employed to assess pain-related brain activity, with artificial intelligence applied to model the relationship between objective neurophysiological signals and subjective pain experience.
This is a single-centre, randomised, double-blind, controlled trial involving 60 patients undergoing colonoscopy without anaesthesia. Participants will be randomly allocated (1:1) to either an electrical stimulation group receiving TENS-WAA or a sham stimulation group. EEG and fNIRS data will be acquired before, during and after the procedure. The primary outcome is the analysis of EEG-fNIRS signals to characterise cerebral responses associated with pain modulation. Secondary outcomes include patient-reported pain using the Visual Analogue Scale (VAS), total colonoscopy duration and the correlation between EEG-fNIRS indicators and VAS scores. A deep learning framework will be used to enhance pain prediction accuracy.
This study has received ethical approval from the Ethics Committee of Changhai Hospital, Shanghai (approval reference CHEC2025-006), and has been registered at ClinicalTrials.gov. Written informed consent will be obtained from all participants. Findings will be disseminated in peer-reviewed academic journals and at relevant scientific conferences, regardless of outcome, contributing to evidence-based, non-pharmacological pain management strategies.
ClinicalTrials.gov, NCT06813703.
by Muluken Chanie Agimas, Mekuriaw Nibret Aweke, Berhanu Mengistu, Lemlem Daniel Baffa, Elsa Awoke Fentie, Ever Siyoum Shewarega, Aysheshim Kassahun Belew, Esmael Ali Muhammad
IntroductionMalaria is a global public health problem, particularly in sub-Saharan African countries. It is responsible for 90% of all deaths worldwide. To reduce the impact and complications associated with delayed treatment of malaria among children under five, comprehensive evidence about the magnitude and determinants of delayed treatment for malaria could be the solution. But there are no national-level studies in the Horn of Africa for decision-makers.
ObjectiveTo assess the prevalence and associated factors of delay in seeking malaria treatment among under-five children in the Horn of Africa.
MethodPublished and unpublished papers were searched on Google, Google Scholar, PubMed/Medline, EMBASE, SCOPUS, and the published articles’ reference list. The search mechanism was established using Medical Subject Heading (MeSH) terms by combining the key terms of the title. Joana Brigg’s Institute critical appraisal checklist was used to assess the quality of articles. A sensitivity test was conducted to evaluate the heterogeneity of the studies. The visual funnel plot test and Egger’s and Begg’s statistics in the random effect model were done to evaluate the publication bias and small study effect. The I2 statistics were also used to quantify the amount of heterogeneity between the included studies.
ResultsThe pooled prevalence of delayed treatment for malaria among under-five children in the Horn of Africa was 48% (95% CI: 34%–63%). History of child death (OR =2.5, 95% CI: 1.73–3.59), distance >3000 meters (OR = 2.59, 95% CI: 2.03–3.3), drug side effect (OR = 2.94, 95% CI: 1.86–4.67), formal education (OR = 0.69, 95% CI: 0.49–0.96), middle income (OR = 0.42, 95% CI: 0.28–0.63), expensiveness (OR = 4.39, 95% CI: 2.49–7.76), and affordable cost (OR = 2.13, 95% CI: 1.41–3.2) for transport were factors associated with malaria treatment delay among children.
Conclusion and recommendationsAbout one out of two parents in the Horn of Africa put off getting their kids treated for malaria. High transportation expenses, long travel times (greater than 3,000 meters) to medical facilities, and anxiety about drug side effects were major risk factors that contributed to this delay. On the other hand, a middle-class income was found to be protective of treatment delays. These results highlight how crucial it is to improve access to healthcare services, both financially and physically, to minimize delays in treating malaria in the area’s children.
We will recruit 478 paediatric patients with newly diagnosed IgAV across multiple centres. Participants will undergo prospective longitudinal assessment at disease onset and at 1, 3, 6 and 12 months postdiagnosis. Standardised evaluations will include clinical manifestations, physical examinations, laboratory parameters and patient-reported outcomes. The data will be analysed statistically with SPSS software (V.27.0), adopting a significance threshold of p
This study has been approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (2024-K0480), the Ethics Committee of the First People’s Hospital of Yulin (YLSY-IRB-SR-2025060), the Medical Research Ethics Committee of the Liuzhou Workers’ Hospital (KY2024356) and the Ethics Committee of the Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region (No. (2025–1)003) and written informed consent was obtained from all the parents or guardians of the patients involved. It will be disseminated by publication of peer-reviewed manuscripts and presentation in abstract form at national and international scientific meetings.
ChiCTR2500099716.
by Mengzhen Qin, Mengyuan Qiao, Yuying Dong, Haiyan Wang
ObjectiveCompared with those without such impairment, middle-aged and older adults with sensory impairment (SI) demonstrate a greater prevalence and severity of depressive symptoms, significantly affecting their mental health. We aimed to develop and validate a depression risk prediction model for middle-aged and elderly individuals with SI.
MethodsData from the 2018 China Health and Retirement Longitudinal Study were randomly partitioned into training and validation sets at a 7:3 ratio. Within the training set, least absolute shrinkage and selection operator (LASSO) regression analysis and binary logistic regression were used to identify predictor variables, and a risk prediction column‒line graph was subsequently developed, with depression status among middle-aged and elderly individuals with SI as the dependent variable. Predictive performance of the training and validation sets was assessed via receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis.
ResultsIn total, 5308 middle-aged and older adults with SI were included, with 50.1% (n = 2657) developing depression. Multifactorial logistic regression analysis identified several depression predictors, including sex, education level, place of residence, marital status, self-rated health, life satisfaction, pension insurance status, nighttime sleep duration, functional impairment status, and pain (all P CI = 0.783–0.811) and 0.778 (95% CI = 0.755–0.800), respectively. The Hosmer–Lemeshow values were P = 0.176 and P = 0.606 (P > 0.05), and the calibration curves revealed significant agreement between the model and actual observations. ROC and DCA curves indicated good predictive performance for the column‒line graph.
ConclusionThis study presents a reliable, validated, and acceptable predictive model for depression risk in middle-aged and elderly individuals with SI, and the identified predictors have potential applications in public health policy and clinical practice.
by Mengqi Yuan, Yajing Yuan, Xiangqun Zhang, Zhenghao Zhu, Chenxi Zhao, Xiangqian Gao, Genyuan Du
Millimeter-wave (mmWave) radar has become an important research direction in the field of object detection because of its characteristics of all-time, low cost, strong privacy and not affected by harsh weather conditions. Therefore, the research on millimeter wave radar object detection is of great practical significance for applications in the field of intelligent security and transportation. However, in the multi-target detection scene, millimeter wave radar still faces some problems, such as unable to effectively distinguish multiple objects and poor performance of detection algorithm. Focusing on the above problems, a new target detection and classification framework of S2DB-mmWave YOLOv8n, based on deep learning, is proposed to realize more accuracy. There are three main improvements. First, a novel backbone network was designed by incorporating new convolutional layers and the Simplified Spatial Pyramid Pooling - Fast (SimSPPF) module to strengthen feature extraction. Second, a dynamic up-sampling technique was introduced to improve the model’s ability to recover fine details. Finally, a bidirectional feature pyramid network (BiFPN) was integrated to optimize feature fusion, leveraging a bidirectional information transfer mechanism and an adaptive feature selection strategy. A publicly available 5-class object mmWave radar heatmap dataset, including 2,500 annotated images, were selected for data modeling and method evaluation. The results show that the mean average precision (mAP), precision and recall of the S2DB-mmWave YOLOv8n model were 93.1% mAP@0.5, 55.8% mAP@0.5:0.95, 89.4% and 90.6%, respectively, which is 3.3, 1.6, 4.5 and 7.7 percentage points higher than the baseline YOLOv8n network without increasing the parameter count.Thirst is the most common self-reported symptom in intensive care unit (ICU) patients. There is evidence that oral cooling interventions may alleviate thirst symptoms in ICU patients. However, the evidence needs to be critically evaluated.
To investigate the effect of oral cooling interventions on alleviating thirst symptoms of ICU patients and explore the effectiveness of different types of oral cooling by subgroup analysis.
The PubMed, Ovid Embase, the Cochrane Library, Wanfang Data and China National Knowledge Infrastructure databases were searched from inception to 29 October 2023. Randomised controlled trials (RCTs) that reported thirst intensity or thirst distress as outcomes were included. The certainty of the evidence was evaluated by the GRADE approach.
The meta-analysis comprised eight RCTs that included 813 ICU patients. The pooled analysis from eight RCTs showed that oral cooling interventions had significant beneficial effects on thirst intensity (weighted mean difference [WMD] = −2.73, 95% confidence interval [CI] = −3.62 to −1.85, p < 0.01; moderate certainty). The pooled analysis from four RCTs showed that oral cooling interventions could significantly lower the thirst distress scores (standardised mean difference = −0.80, 95% CI = −1.13 to −0.47, p < 0.01; low certainty). Subgroup analysis indicated that cold stimulation (WMD = −3.12) and cold combined with menthol stimulation (WMD = −1.72) could significantly lower the thirst intensity scores.
Oral cooling interventions including cold and menthol had beneficial effects on thirst intensity and thirst distress in ICU patients. The high heterogeneity in methods should be considered when interpreting the results.
This study provides references for the application of oral care strategy in the ICU care field, and encourages nurses to apply the oral cooling plan to improve patients' comfort.
This was a meta-analysis based on data from previous studies.
PROSPERO: CRD42023416059
The global healthcare landscape is undergoing a significant shift in demographics, evolving disease epidemiology and an ageing population, prompting the expansion of healthcare roles, including the healthcare assistant (HCA). However, there remains limited clarity regarding the scope and standards of their competence.
A scoping review will be conducted following the updated Joanna Briggs Institute methodological framework. Five databases encompassing PubMed, Cumulative Index to Nursing and Allied Health Literature Complete (EBSCOhost), EMBASE, Web of Science and PsycINFO (EBSCOhost) will be searched. Selected studies will include all types of studies on the competence of HCAs. Two reviewers will independently perform the screening and data extraction process. The quality of evidence in this review will be assessed by the Crowe Critical Appraisal Tool. Data synthesis will be presented using the narrative descriptions and tabular illustrations. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews will be employed for transparent reporting.
No ethical clearance is required for this review. The final review will be submitted for publication to a peer-reviewed journal. Additionally, the results of the final review will be disseminated both locally and nationally to inform clinical practice.
This protocol has been registered with the Open Science Framework. Registration number is OSF.IO/5RGUC.
To develop a structured intervention aimed at enhancing family communication to reduce relapse in adolescents with depression.
This study follows a multi-stage process guided by the Intervention Mapping procedure with the Medical Research Council framework, assessing the layers of complexity. Its design comprises four interrelated stages to construct a family communication intervention, culminating in a pilot randomised controlled trial.
The program has four stages: (1) Identifying family interaction gaps through literature review and expert input; (2) Investigating communication needs of depressed adolescents and their families via a mixed methods study to develop a model intervention; (3) Refining the intervention with focus groups and expert e-Delphi; and (4) Finalising the intervention based on pilot randomised controlled trial outcomes. The research will be conducted in Greater Accra, Ghana.
The process will result in a family communication intervention tailored to the needs of adolescents with depression and their families. It will be pilot tested, and the results will inform a nationwide efficacy trial.
This research integrates qualitative and quantitative data to inform the development of an evidence-based family communication intervention. The program will carefully examine data integration and contextual challenges encountered during its implementation.
The intervention has the potential to enhance family communication, thus playing a crucial role in adolescent depression recovery by reducing relapse rates. Healthcare professionals will benefit from a structured, evidence-based communication tool that can be used in clinical settings.
The study focuses on improving communication between families of adolescents with depression, aiming to develop a family communication package for clinical and community use. This intervention may enhance recovery outcomes and reduce relapse risk for adolescents.
This study adhered to the GUIDED guideline for reporting intervention development studies.
No Patient or Public Contribution.
To develop and validate a machine learning-based risk prediction model for delirium in older inpatients.
A prospective cohort study.
A prospective cohort study was conducted. Eighteen clinical features were prospectively collected from electronic medical records during hospitalisation to inform the model. Four machine learning algorithms were employed to develop and validate risk prediction models. The performance of all models in the training and test sets was evaluated using a combination of the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, Brier score, and other metrics before selecting the best model for SHAP interpretation.
A total of 973 older inpatient data were utilised for model construction and validation. The AUC of four machine learning models in the training and test sets ranged from 0.869 to 0.992; the accuracy ranged from 0.931 to 0.962; and the sensitivity ranged from 0.564 to 0.997. Compared to other models, the Random Forest model exhibited the best overall performance with an AUC of 0.908 (95% CI, 0.848, 0.968), an accuracy of 0.935, a sensitivity of 0.992, and a Brier score of 0.053.
The machine learning model we developed and validated for predicting delirium in older inpatients demonstrated excellent predictive performance. This model has the potential to assist healthcare professionals in early diagnosis and support informed clinical decision-making.
By identifying patients at risk of delirium early, healthcare professionals can implement preventive measures and timely interventions, potentially reducing the incidence and severity of delirium. The model's ability to support informed clinical decision-making can lead to more personalised and effective care strategies, ultimately benefiting both patients and healthcare providers.
This study was reported in accordance with the TRIPOD statement.
No patient or public contribution.
by Yanxuan Wu, Fu Li, Hao Chen, Liang Shi, Meng Yin, Fan Hu, Gongchang Yu
BackgroundMetabolic syndrome (MetS) and sarcopenia are major global public health problems, and their coexistence significantly increases the risk of death. In recent years, this trend has become increasingly prominent in younger populations, posing a major public health challenge. Numerous studies have regarded reduced muscle mass as a reliable indicator for identifying pre-sarcopenia. Nevertheless, there are currently no well-developed methods for identifying low muscle mass in individuals with MetS.
MethodsA total of 2,467 MetS patients (aged 18–59 years) with low muscle mass assessed by dual-energy X-ray absorptiometry (DXA) were included using data from the 2011–2018 National Health and Nutrition Examination Survey (NHANES). Least Absolute Shrinkage and Selection Operator (LASSO) regression was then used to screen for important features. A total of nine Machine learning (ML) models were constructed in this study. Area under the curve (AUC), F1 Score, Recall, Precision, Accuracy, Specificity, PPV, and NPV were used to evaluate the model’s performance and explain important predictors using the Shapley Additive Explain (SHAP) values.
ResultsThe Logistic Regression (LR) model performed the best overall, with an AUC of 0.925 (95% CI: 0.9043, 0.9443), alongside strong F1-score (0.87) and specificity (0.89). Five important predictors are displayed in the summary plot of SHAP values: height, gender, waist circumference, thigh length, and alkaline phosphatase (ALP).
ConclusionThis study developed an interpretable ML model based on SHAP methodology to identify risk factors for low muscle mass in a young population of MetS patients. Additionally, a web-based tool was implemented to facilitate sarcopenia screening.
This study aims to explore the trajectories and co-occurrence of perceived control and caregiver self-efficacy among patients with heart failure (HF) and their caregivers within 3 months post-discharge and identify associated risk factors.
A prospective cohort design.
A prospective cohort study was conducted from March to June 2024 in Tianjin, China. Information on perceived control and caregiver self-efficacy was collected 24 h before discharge, 2 weeks, 1 month, and 3 months after discharge. Group-Based Dual Trajectory Modelling (GBDTM) and logistic regression were used for analysis.
The study included 203 dyads of patients with HF and their caregivers (HF dyads). Perceived control identified three trajectories: low curve (15.3%), middle curve (57.1%) and high curve (27.6%). Caregiver self-efficacy demonstrated three trajectories: low curve (17.2%), middle curve (56.7%) and high stable (26.1%). GBDTM revealed nine co-occurrence patterns, with the highest proportion (36.7%) being ‘middle-curve group for perceived control and middle-curve group for caregiver self-efficacy’, and 16.7% being ‘high-curve group for perceived control and high-stable group for caregiver self-efficacy’. Age, gender, household income, NYHA class, symptom burden and psychological resilience were identified as risk factors for perceived control trajectories; marital status, regular exercise and psychological resilience were identified as risk factors for caregiver self-efficacy trajectories.
We identified distinct trajectories, co-occurrence patterns and risk factors of perceived control and caregiver self-efficacy among HF dyads. These findings help clinical nurses to better design and implement interventions, strengthening the comprehensive management and care outcomes for HF dyads.
These findings highlighted the interactive relationship between perceived control and caregiver self-efficacy trajectories, suggesting that interventions should boost both to improve personalised treatment plans and outcomes for HF dyads.
This study adhered to the STROBE checklist.
Patients and their caregivers contributed by participating in the study and completing the questionnaire.
To clarify the definition and evolution of Patient and Public Involvement and Engagement (PPIE) and identify its attributes, antecedents, and consequences in health-related research.
This study follows Rodgers' evolutionary concept analysis with a seven-step framework.
Datasets were searched using terms related to PPIE and key categories (i.e., attributes, antecedents, and consequences). Data were sourced from CINAHL, PsycInfo, Scopus, PubMed, and Web of Science covering publications from inception to October 31, 2024. Document titles, abstracts, and keywords were manually screened to identify relevant studies for full-text review.
A total of 1751 documents were screened, resulting in 38 eligible studies included in the final analysis. PPIE has evolved from a narrow focus on patient inclusion and participation, where patients had minimal influence on research and researchers resisted sharing control of research, to a collaborative model emphasising sustained partnerships, shared contributions, equitable power distribution, and active involvement across research stages. This shift has been driven by research innovation, a growing emphasis on healthcare equity and patient-centred care, technological advances, and stakeholder advocacy (e.g., patients, funders, ethics committees). While PPIE enhances research relevance and impact, barriers, such as resource constraints, power imbalances, patient limited research capabilities and increased researcher workload persist. Facilitators, such as training programmes, standardised guidelines, flexible arrangements and transparent communication can enable meaningful partnerships.
The concept of PPIE is evolving toward greater clarity and consistency in research, positioning patients and the public as active, essential contributors rather than passive participants. Barriers and facilitators were identified to inform its utilisation in research.
This study clarifies the conceptual ambiguities of PPIE, informs theory development, and provides actionable insights. Healthcare and nursing researchers can draw on its findings to utilise PPIE to enhance collaborative and inclusive research practices that align with the needs of patients and the public.
This study adheres to the PRISMA (2020) reporting guidelines for systematic reviews.
One of our co-authors is a patient with lived experience of cancer, who contributed valuable comments and suggestions to enhance this paper.
To explore the complex relationships among non-suicidal self-injury, depression and anxiety symptoms in adolescents, identify key symptoms and provide a theoretical foundation for targeted interventions.
A cross-sectional study.
In total, 1126 adolescents from a tertiary hospital in Shandong Province were assessed using the Adolescent Self-Injury Questionnaire, Patient Health Questionnaire and Generalised Anxiety Disorder Scale. Network analysis was employed to construct symptom networks and identify central and bridging symptoms.
The network analysis revealed that nodes GAD5 (Restlessness), GAD2 (Uncontrollable worry), and GAD4 (Trouble relaxing) exhibited the highest centrality indices, establishing them as core symptoms within the overall symptom network. The highest bridge intensity nodes were GAD1 (Nervousness), GAD5 (Restlessness) and non-suicidal self-injury.
By accurately identifying core and bridging symptoms, a scientific foundation is provided for developing precise and effective symptom management plans.
The study identified the most influential nodes in anxiety and depression among adolescents with non-suicidal self-injury. The findings would help in carrying out personalised and precise interventions to reduce non-suicidal self-injury occurrence and alleviate anxiety and depression symptoms among adolescents.
This study adheres to the STROBE guideline of reporting.
This study did not include patient or public involvement in its design, conduct or reporting.
To evaluate the effects of the organisational environment on hospital discharge readiness during public health emergencies.
An observational study.
A regression-discontinuity design approach was employed to assess the impact of the organisational environment on hospital discharge readiness. Adult patients diagnosed with acute myocardial infarction and discharged from the Cardiac Critical Care Unit of a tertiary hospital in Shanghai, China, were recruited. Spearman correlation analysis was conducted to examine the associations between multiple factors at individual and organisational levels and hospital discharge readiness across three stages of pandemic policy changes.
A total of 411 patients were included in the analysis. The regression-discontinuity analysis revealed a significant discontinuity at the cut-off, indicating that policy-driven changes in the organisational environment during public health emergencies were associated with a 21.61% reduction in hospital discharge readiness. Additionally, family functioning and the quality of nursing discharge education were significantly associated with discharge readiness across all three pandemic stages.
These findings demonstrate that patient-perceived hospital discharge readiness is significantly influenced by changes in the organisational environment during public health emergencies. Future research should focus on developing targeted discharge preparation programmes that allow for organisational adaptation in response to emergencies, such as pandemics or natural disasters.
Organisational responses to public health emergencies need to prioritise enhancing discharge preparedness. This includes bolstering family involvement and ensuring that nurses are adequately trained to provide effective discharge education, especially when healthcare resources are strained.
The findings underscore the importance of adaptable and resilient discharge planning and transitional care, particularly in public health emergencies. Fostering an organisational environment that supports seamless discharge processes can significantly improve patient readiness for post-hospital care.
Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement.
No patient or Public Contributions.
Advance care planning for people with dementia is an important process to ensure that patient preferences are respected throughout disease progression. However, the complexity of advance care planning and the challenges in effective communication hinder its implementation. The lack of clear procedural guidance for health care teams and the limited research on practical issues such as building trust and resolving conflicts further complicate this process.
To explore the key components of and processes for advance care planning for people with dementia.
The authors conducted a comprehensive search of databases, including PubMed, Embase, Web of Science, the Cochrane Library, CINAHL, NICE, Open Grey, CNKI, and Wanfang. The inclusion criteria focused on studies reporting advance care planning practices and stakeholder perspectives related to dementia.
The review included 45 studies and identified key components and processes for successfully implementing advance care planning in dementia care. These components include enhancing readiness, capturing patient wishes, and executing those wishes. The implementation processes cover assessing participation capacity, selecting surrogate decision-makers, and identifying healthcare providers who implement advance care planning. As the condition of people with dementia progresses, the role of healthcare providers who implement advance care planning becomes increasingly important in advance care planning practices.
The success of advance care planning depends on the interconnection of multiple components, and the findings offer practical insights for improving the advance care planning process to ensure that the care preferences of people with dementia are respected throughout the progression of the disease.
PRISMA-ScR.
This is a review without patient and public contribution.
Cognitive decline, including subjective cognitive decline (SCD), mild cognitive impairment (MCI), and dementia, significantly affects social participation, leading to social isolation and reduced quality of life. Enhancing social participation through interventions may mitigate these effects, yet evidence on intervention effectiveness and mechanisms remains inconsistent.
To evaluate the effectiveness of social participation interventions for individuals with cognitive decline and identify effective behavior change techniques (BCTs) supporting social participation.
Our search using the following databases—PubMed, Web of Science, Embase, Cochrane Library, CINAHL, Scopus, CNKI, and Wanfang—was conducted until October 2024. The quality of the included studies was assessed using the Cochrane risk of bias tool for randomized trials. Meta-analyses were conducted using Review Manager 5.4 and Stata18, and the certainty of evidence was rated using the Grading of Recommendations Assessment, Development, and Evaluation approach.
Sixteen RCTs involving 2190 participants were included. Music therapy (SMD = 0.62, 95% CI [0.15, 1.10]) and reminiscence therapy (SMD = 0.34, 95% CI [0.02, 0.66]) demonstrated significant positive effects on social participation. Group-based interventions were particularly effective (SMD = 0.23, 95% CI [0.04, 0.43]). Commonly used BCTs included goal setting, behavioral practice/rehearsal, and social support. However, substantial heterogeneity and limited data on SCD and MCI restricted generalizability.
Interventions promoting social participation may enhance engagement for individuals with cognitive decline, particularly through music therapy, reminiscence therapy, and group-based formats. The complexity and dynamic nature of social interaction require individuals to engage and integrate various cognitive functions and skills, which can present significant challenges for older adults with cognitive impairments in their daily social participation. Further research is needed to optimize intervention components and address gaps in targeting early cognitive decline stages.
FreshRSS 