Background: Patient safety critically influences both quality of life and disease progression in older adults with cognitive impairment, yet large-scale multicenter data remain scarce. This study aims to systematically analyze the types of safety incidents experienced by patients with Alzheimer's disease and related cognitive impairments, and explore the network associations of different safety incidents. Methods: Initiated by the Alzheimer's Disease China (ADC), this survey recruited 1057 older individuals with Alzheimer's and related cognitive impairments, along with their families, across 31 provinces, autonomous regions, and municipalities. The safety incidents evaluated in this study included falls, getting lost, medication errors, verbal aggression, physical aggression, household fire, aspiration, and choking. Incidence rates for overall and specific safety incidents were calculated. Correlation analyses and network analysis were performed to examine relationships between safety incidents. Results: A high proportion (73.5%) of participants reported at least one safety incident in the past year, with over one-third (36.0%) experiencing three or more concurrent incidents. Medication errors (55.9%) and verbal aggression (39.6%) were most frequent, followed by falls (32.5%) and physical aggression (22.7%). Incidence rates varied significantly by cognitive impairment stage, care setting, and geographic region. Network analysis highlighted medication errors and getting lost as central nodes bridging other incidents. Conclusions: This study reveals an alarmingly high incidence of safety incidents among cognitively impaired patients, affecting their physical, psychological, and familial well-being. A collaborative, multidisciplinary effort involving healthcare professionals, family caregivers, fire and police emergency responders, and public health policymakers is essential to develop individualized safety strategies aligned with patient needs and contextual considerations.

Background The relationship between cognitive function and hip fracture risk among middle-aged and older adults in China remains unclear, with limited longitudinal evidence. Objective To investigate the association between cognitive function and hip fracture risk among Chinese middle-aged and elderly adults. Study design Prospective longitudinal study. Methods We analyzed 8257 participants (aged ≥45) from China Health and Retirement Longitudinal Study (CHARLS). The present analysis used Wave 3 (2015) as the study entry and followed participants through Wave 5 (2020). Cognitive function was assessed across four domains: orientation, memory, calculation and drawing. All cognitive z-scores were standardized to the metrics of Wave 3. The calculation formula involved subtracting the Wave 3 average score from each participant’s test score per wave, followed by division using the Wave 3 standard deviation. Hip fracture status served as the outcome measure. Potential confounding effects stemming from demographic attributes and other covariates were controlled for during the analysis. Longitudinal logistic regression was used to analyze the relationship between the cognitive z-scores and their dimensions and hip fracture incidence at two follow-up surveys. Results Participants (mean age 56.62 ± 8.92 years; 53.8% male) were followed for up to 5 years. Each standard deviation decrease in global cognitive z-scores was associated with increased hip fracture risk at Wave 4 (odds ratio [OR] = 0.71, 95% CI:0.57–0.89) and Wave 5 (OR = 0.72, 95% CI:0.58–0.87). Decline in orientation demonstrated consistent associations (Wave 4: OR = 0.82, 95% CI:0.70–0.96; Wave 5: OR = 0.82, 95% CI:0.68–0.99). Declines in calculation were associated with hip fracture at Wave 4 only, while declines in memory and drawing showed such an association only at Wave 5. Conclusion Independent associations exist between impaired global cognitive function, weakened orientation and increased hip fracture risk in this Chinese middle-aged and older population. These findings highlight the need to integrate cognitive assessments with fracture risk evaluations.

ObjectivesTo examine the association between speech and facial features with depression, anxiety, and apathy in older adults with mild cognitive impairment (MCI).MethodsSpeech and facial expressions of 319 MCI patients were digitally recorded via audio and video recording software. Three of the most common neuropsychiatric symptoms (NPS) were evaluated by the Public Health Questionnaire, General Anxiety Disorder, and Apathy Evaluation Scale, respectively. Speech and facial features were extracted using the open-source data analysis toolkits. Machine learning techniques were used to validate the diagnostic power of extracted features.ResultsDifferent speech and facial features were associated with specific NPS. Depression was associated with spectral and temporal features, anxiety and apathy with frequency, energy, spectral, and temporal features. Additionally, depression was associated with facial features (action unit, AU) 10, 12, 15, 17, 25, anxiety with AU 10, 15, 17, 25, 26, 45, and apathy with AU 5, 26, 45. Significant differences in speech and facial features were observed between males and females. Based on machine learning models, the highest accuracy for detecting depression, anxiety, and apathy reached 95.8%, 96.1%, and 83.3% for males, and 87.8%, 88.2%, and 88.6% for females, respectively.ConclusionDepression, anxiety, and apathy were characterized by distinct speech and facial features. The machine learning model developed in this study demonstrated good classification in detecting depression, anxiety, and apathy. A combination of audio and video may provide objective methods for the precise classification of these symptoms.

BACKGROUND:The trend of interdisciplinary education is becoming increasingly prominent. Nursing informatics and nursing engineering have received much attention and development at different levels of nursing education in many Western countries. Meanwhile, in China, the cultivation of interdisciplinary nursing talents has either not been initiated or has only entered an initial stage. OBJECTIVES:This study aims to explore experts' opinions from nursing, informatics and engineering on the feasibility of interdisciplinary education at graduate master's level in nursing through interview. DESIGN:This was a descriptive qualitative study. SETTING:Interviews were conducted online or face to face. PARTICIPANTS:Experts in the fields of nursing, informatics, and engineering who met the study qualifications were enrolled. METHODS:This study used a purposive sampling method and collected data via semi-structured interviews. A total of 14 experts were involved based on data saturation, which eight were interviewed face-to-face and six were interviewed online. A content analysis method was used to summarize and analyze the attitudes, opinions, and suggestions of experts. RESULTS:A total of 579 min of interviews with 66,387 words were transcribed and analyzed after 30-50 min time range of each interview, and 4 themes were established. A consensus was obtained on the necessity and importance of interdisciplinary education. Policy guidance, financial support, and mutual recognition were the prerequisites for the cultivation. Moreover, feasibility of interdisciplinary education depends on multi-cooperation, including society, university, and hospital. Finally, a linkage mechanism among relevant stakeholders was required. CONCLUSION:The necessity and feasibility of such integrated training was concluded. Learning from the experience of relevant countries, China should launch an interdisciplinary training model suitable for its national condition.

Background: Depression, anxiety, and apathy are highly prevalent in older people with preclinical dementia and mild cognitive impairment. These symptoms have also proven valuable in predicting the progression from mild cognitive impairment to dementia, enabling a timely diagnosis and treatment. However, objective and reliable indicators to detect and distinguish depression, anxiety, and apathy are relatively scarce. Objective: This study aimed to develop a machine learning model to detect and distinguish depression, anxiety, and apathy based on speech and facial expressions. Design: An observational, cross-sectional study design. Setting(s): The memory outpatient department of a tertiary hospital. Participants: 319 older adults diagnosed with mild cognitive impairment. Methods: Depression, anxiety, and apathy were evaluated by the Public Health Questionnaire, General Anxiety Disorder, and Apathy Evaluation Scale, respectively. Speech and facial expressions of older adults with mild cog-nitive impairment were digitally captured using audio and video recording software. Open-source data analysis toolkits were utilized to extract speech, facial, and text features. The multiclass classification was used to develop classification models, and shapely additive explanations were used to explain the contribution of each feature within the model. Results: The random forest method was used to develop a multiclass emotion classification model, which per-formed well in classifying emotions with a weighted-average F1 score of 96.6 %. The model also demonstrated high accuracy, precision, and recall, with 87.4 %, 86.6 %, and 87.6 %, respectively. Conclusions: The machine learning model developed in this study demonstrated strong classification perfor-mance in detecting and differentiating depression, anxiety, and apathy. This innovative approach combines text, audio, and video to provide objective methods for precise classification and remote monitoring of these symptoms in nursing practice. Registration: This study was registered at the Chinese Clinical Trial Registry (registration number: ChiCTR1900023892; registration date: June 19th, 2019). & COPY; 2023 Elsevier Ltd. All rights reserved.

BACKGROUND:Older adults with mild cognitive impairment (MCI) and depression have a higher dementia conversion rate, which requires timely intervention.OBJECTIVES:A non-randomized controlled trial was conducted to explore the effect of a nurse-led positive psychological intervention (PPI) in relieving depression and promoting cognition in this population.METHODS:A total of 70 older adults were enrolled, with 35 each in the intervention and control groups. The control group received one-to-one health education, and the intervention group received a 40- to 60-minute PPI for eight successive weeks.RESULTS:During the intervention, most participants reached the standard of active participation, and 2.86% continued to complete homework every day during follow-up. The Patient Health Questionnaire-9 (PHQ-9) score in the intervention group was significantly lower than that in the control group at the end of intervention (t = -3.64, p < 0.05) and at 3-month follow-up (t = -4.48, p < 0.05). Interaction effects of time and group on PHQ-9 scores (F = 8.11, p < 0.001), with significant differences between the groups in scores (F = 9.11, p < 0.05) and times (F = 23.58, p < 0.05) was observed. In the Montreal Cognitive Assessment (MoCA) scale, the intervention group had significantly higher scores than controls at the end of intervention (t = 7.28, p < 0.05) and 3-month follow-up (t = 8.01, p < 0.05). Cognition in the two groups was significantly affected by intergroup effects (F = 42.80, p < 0.001), interaction effects (F = 30.38, p < 0.001), and time effects (F = 33.67, p < 0.05).CONCLUSIONS:Although the effects tended to decrease in follow-up, the nurse-led PPI was feasible and valid in relieving depression and promoting cognition among older participants with MCI and depression. The present findings warrant further exploration.TWEETABLE ABSTRACT:A nurse-led positive psychological intervention was applicable among elderly MCI adults with depression and effective in relieving depression and promoting cognition.

OBJECTIVES:This study aimed to develop a classification model to detect and distinguish apathy and depression based on text, audio, and video features and to make use of the shapely additive explanations (SHAP) toolkit to increase the model interpretability.METHODS:Subjective scales and objective experiments were conducted on 319 mild cognitive impairment (MCI) patients to measure apathy and depression. The MCI patients were classified into four groups, depression only, apathy only, depressed-apathetic, and the normal group. Speech, facial and text features were extracted using the open-source data analysis toolkits. Multiclass classification and SHAP toolkits were used to develop a classification model and explain the contribution of specific features.RESULTS:The macro-averaged f1 score and accuracy for overall model were 0.91 and 0.90, respectively. The accuracy for the apathetic, depressed, depressed-apathetic, and normal groups were 0.98, 0.88, 0.93, and 0.82, respectively. The SHAP toolkit identified speech features (Mel-frequency cepstral coefficient (MFCC) 4, spectral slopes, F0, F1), facial features (action unit (AU) 14, 26, 28, 45), and text feature (text 6 semantic) associated with apathy. Meanwhile, speech features (spectral slopes, shimmer, F0) and facial expression (AU 2, 6, 7, 10, 14, 26, 45) were associated with depression. Apart from the shared features mentioned above, new speech (MFCC 2, loudness) and facial (AU 9) features were observed in the depressive-apathetic group.CONCLUSIONS:Apathy and depression shared some verbal and facial features while also exhibited distinct features. A combination of text, audio, and video could be used to improve the early detection and differential diagnosis of apathy and depression in MCI patients.

Objective:To understand the incidence of mild cognitive impairment (MCI) of elderly patients with subjective memory impairment and analyze its influencing factors.Methods:A total of 322 patients with subjective memory impairment in elderly frail cognitive management clinic in General Hospital of Chinese PLA were selected by the convenient sampling method. According to the 2018 Diagnostic Criteria for Diagnosis and Treatment of Dementia and Cognitive Impairment in China, the subjects were divided into the MCI group and the non-MCI group. Demographic data, physiological factors, psychological factors, lifestyle and nutritional status of patients were collected using self-designed questionnaires. The Barthel Index Rating Scale was used to assess activity of daily living, 9-item Patient Health Questionnaire (PHQ-9) was used to assess depression and Generalized Anxiety Disorder Questionnaire (GAD-7) was used to to assess anxiety. The Pittsburgh Sleep Quality Index was used to assess sleep disturbances and Mini Nutritional Assessment Short Form (MNA-SF) was used to assess nutritional status. Univariate analysis and multivariate binary logistic regression analysis were used to explore the influencing factors of MCI in patients. Results:Among the 322 elderly patients with subjective memory impairment, 173 (53.73%) had MCI and 149 (46.27%) were non-MCI patients. Binomial Logistic regression analysis showed that reading habits, housework, social interaction, anxiety, age, depression, and sleep disturbance were the influencing factors of MCI in the elderly with subjective memory impairment ( P<0.05) . Conclusions:The incidence of MCI in elderly patients with subjective memory impairment is relatively high. The cognitive management clinic should comprehensively evaluate and analyze the influencing factors of such patients and assist patients to establish a healthy lifestyle according to their personal conditions, so as to improve their cognitive status.

BACKGROUND:As the COVID-19 pandemic continues, safe and effective vaccines with high coverage remain the most effective way of controlling the infection. Therefore, the intention to get vaccinated is a critical issue for nursing students because they will act as health care providers and educators due to their future profession.OBJECTIVES:This study aimed to explore factors associated with COVID-19 vaccination intention among Chinese nursing students.DESIGN:A cross-sectional online survey was used.PARTICIPANTS:A total of 1070 Chinese nursing students participated in this study.METHODS:The study used structured self-administered questionnaires to assess the effects of the following elements; sociodemographic factors, vaccination status, beliefs on general vaccination, beliefs and attitudes towards COVID-19 and COVID-19 vaccination, and COVID-19 vaccination intention. Hierarchical regression analysis was conducted to examine the relationship between these variables and COVID-19 vaccination intention.RESULTS:More than half (51.9%) of nursing students were willing to vaccinate against COVID-19, while 43.4% were uncertain and 4.7% were unwilling to get vaccinated. Increased likelihood of intention to get vaccinated was associated with positive beliefs towards general vaccination and COVID-19 vaccination, perceived less adverse effects following vaccination, the greater impact of COVID-19 on daily life, and less clinical practice experience in healthcare settings. Those hesitant to vaccinate raised concerns about the safety of vaccines, doubted the efficacy, believed that vaccination was unnecessary, or had insufficient information on COVID-19 vaccines.CONCLUSIONS:More efforts are needed to enhance vaccine confidence and increase the vaccination rates against COVID-19 in nursing students by organizing effective educational campaigns and establishing positive vaccination beliefs.

Objective:To evaluate the sensitivity and specificity of the Geriatric Depression Scale-3-Apathy Subscale (GDS-3A) in the assessment of apathy in the aged by taking the Apathy Evaluation Scale-Clinician (AES-C) as a reference.Methods:From May 2019 to October 2020, convenience sampling was used to select 475 elderly patients who attended the Outpatient Department of the People's Liberation Army General Hospital and Hepingli Community Health Service Center in Dongcheng District, Beijing as the research object. The 15-item Geriatric Depression Scale (GDS-15) , GDS-12-Depression Subscale (GDS-12D) and the AES-C were used for investigation. The statistical analysis was conducted by using the correlation analysis and receiver operating characteristic (ROC) curve comparison analysis.Results:When GDS-3A selected 2 points as the boundary value, the corresponding sensitivity and specificity were 70.99% and 87.54%, respectively, and the area under the ROC curve was 0.77. GDS-3A was positively correlated with AES-C ( r=0.46, P<0.001) , GDS-12D ( r=0.67, P<0.001) , and GDS-15 ( r=0.87, P<0.001) . Conclusions:GDS-3A has high sensitivity and specificity, and can be used as a screening tool for large-scale epidemiological investigations or community elderly apathy manifestations.

OBJECTIVE:To synthesize the findings of qualitative research on help-seeking in people with subjective cognitive decline. METHODS:Relevant qualitative studies were identified by searching the PubMed, CINAHL, Ovid Medline, PsycInfo, Embase, and Web of Science databases. Studies that investigated help-seeking behavior in older adults with subjective cognitive decline were retrieved. The systematic review was conducted in line with JBI methodology for systematic reviews of qualitative evidence. RESULTS:11 studies were included and three themes related to the process of help-seeking for cognitive problems emerged. These themes included: detected changes, challenges in identifying the need for help and decision to seek professional help. CONCLUSION:Making decisions to seek help for people with subjective cognitive decline is a multi-stage process. A better understanding of the complex psychological responses to subjective cognitive decline among older adults may help health care professionals to develop strategies to improve help-seeking in clinical practice.

目的 对国内外痴呆患者就医延迟现状及影响因素进行综述,为今后开展痴呆患者就医相关研究提供参考,为制定促进痴呆患者就医的有效干预措施提供依据.方法 通过检索中国知网、万方、维普、PubMed、Embase、Web of Science等数据库,回顾国内外痴呆患者就医相关文献,对纳入的相关研究内容进行提取与归纳.结果 不同国家和地区的痴呆患者就医延迟的时间均较长,出现症状至就医的时间在1.77～2.40年.就医延迟的影响因素包括:痴呆类型、疾病症状、疾病相关知识及信息、病耻感、就医态度、医疗保健系统的形象、认知相关基层医疗服务资源和跨文化差异.患者年龄、家族史、受教育程度、居住状况、财务状况对就医延迟的影响尚无一致结论.结论 痴呆患者就医延迟现象严重、影响因素繁杂,未来的研究应进一步考虑因素间的相互作用关系,为构建干预方案提供理论基础.

BACKGROUND:Due to the rapid advancements in precision medicine and artificial intelligence, interdisciplinary collaborations between nursing and engineering have emerged. Although engineering is vital in solving complex nursing problems and advancing healthcare, the collaboration between the two fields has not been fully elucidated. OBJECTIVES:To identify the study areas of interdisciplinary collaboration between nursing and engineering in health care, particularly focusing on the role of nurses in the collaboration. METHODS:In this study, a scoping review using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews was performed. A comprehensive search for published literature was conducted using the PubMed, Cumulative Index to Nursing and Allied Health Literature, Scopus, Embase, Web of Science, ScienceDirect, Institute of Electrical and Electronics Engineers Digital Library, and Association for Computing Machinery Digital Library from inception to November 22, 2020. Data screening and extraction were performed independently by two reviewers. Any discrepancies in results were resolved through discussions or in consultation with a third reviewer. Data were analyzed by descriptive statistics and content analysis. Results were visualized in an interdisciplinary collaboration model. RESULTS:We identified 6,752 studies through the literature search, and 60 studies met the inclusion criteria. The study areas of interdisciplinary collaboration concentrated on patient safety (n = 18), symptom monitoring and health management (n = 18), information system and nursing human resource management (n = 16), health education (n = 5), and nurse-patient communication (n = 3). The roles of nurses in the interdisciplinary collaboration were divided into four themes: requirement analyst (n = 21), designer (n = 22), tester(n = 37) and evaluator (n = 49). Based on these results, an interdisciplinary collaboration model was constructed. CONCLUSIONS:Interdisciplinary collaborations between nursing and engineering promote nursing innovation and practice. However, these collaborations are still emerging and in the early stages. In the future, nurses should be more involved in the early stages of solving healthcare problems, particularly in the requirement analysis and designing phases. Furthermore, there is an urgent need to develop interprofessional education, strengthen nursing connections with the healthcare engineering industry, and provide more platforms and resources to bring nursing and engineering disciplines together.

AIMS To examine the distributed characteristics and explore the research themes of Doctor of Nursing Practice (DNP) dissertations during the past two decades. DESIGN A descriptive statistical and visualization bibliometric analysis was conducted. METHODS Doctor of Nursing Practice dissertations submitted between January 2005 and June 2021 were collected from the ProQuest Dissertations and Theses database. A descriptive statistical analysis was conducted to calculate the distribution of the DNP dissertations by granting institution and the published year of publications. The VOSviewer 1.6.13 was used to explore the bibliometric networks and research priorities of the DNP dissertations. RESULTS A total of 4989 DNP dissertations from 90 universities were included in this study, all from the United States. The number of DNP dissertations showed an upward trend, with steady growth from 2005 to 2014 and rapid growth after 2015. The DNP studies focused on five areas: health care management in clinical nursing, advanced practice in nursing education and health education, public health problems, mental health care for adolescents and nurses and the older people care and long-term care. CONCLUSION Parallel to the numerical increase in DNP dissertations is a steady expansion in the range of research topics and scopes, which is aligned with specific specializations of the DNP. Many are interdisciplinary and employ techniques imported from the fields of public health, psychology and social sciences, resulting in nursing educators and practitioners continually broaden their subject perspectives. IMPACT Knowing where, when and why DNP research trends developed will help nursing educators to further develop DNP education and optimize DNP programs in the future, such as paying more attention to the nursing practice. Moreover, this study will inspire DNP students and researchers to expand their subject perspectives and broaden the research scope to solve nursing practice problems based on interdisciplinary theories and methods.

Objective To understand the survival stress of community-dwelling people with mental disorder. Methods Fifteen cases were selected by purposive sampling and received semi-structured individualized interviews.The data were analyzed by Colaizzi framework and themes were extracted. Results Four themes were extracted:physiological stress due to psychiatric symptoms and side effects of drugs;psychological stress due to the outcome of mental illness and to conflict of roles in daily life;social and environmental stress such as social discrimination,lack of job opportunities,and difficulty in obtaining social welfare resources;and interpersonal stress caused by discrimination and deteriorating family relations. Conclusions Community-dwelling people with mental illness have a higher level survival stress after returning to their families and society,with the stressors including symptoms of illness,social discrimination,and interpersonal relationship.Eliminating self-discrimination of the patients,improving social support and social welfare system,and increasing individualized community mental rehabilitation activities may reduce the survival stress of these patients and promote their rehabilitation.