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To explore and analyse the adaptation process of patients and their families at the point of lung cancer diagnosis.
Totally 23 operable lung cancer patients were included in this study. Colaizzi's method of phenomenology was employed for data analysis.
This study found two different aspects of family adaptation at the diagnosis of lung cancer. For family resilience, three themes emerged: (1) Positive family belief systems (giving meaning to a cancer diagnosis and maintaining a positive/optimistic attitude), (2) Flexible family organizational patterns (maintaining the stability of family structure and function, adjusting the relationship between patients and family members and receiving external support and help) and (3) Good communication and problem-solving strategies (open communication on an equal basis, positive and open expression of emotions and collaborative problem-solving). For family vulnerability, three themes were as follows: (1) Negative family belief systems (negative attitudes and concealment and self-isolation due to stigma), (2) Rigid family organizational patterns (adaptation lost, conflicts between family support and patients' willingness and pressure upon social support) and (3) Unhealthy communication and problem-solving (poor communication, emotional asymmetry of family members and tendency to solve problems alone).
The study highlights the existence of the family resilience and family vulnerability at the point of lung cancer diagnosis and provides patient's perspective for understanding family resilience in specific cultural contexts.
The data were collected through face-to-face interviews.
Trail registration number: ChiCTR2300074801.
Early identification and intervention of the frailty of the elderly will help lighten the burden of social medical care and improve the quality of life of the elderly. Therefore, we used machine learning (ML) algorithm to develop models to predict frailty risk in the elderly.
A prospective cohort study.
We collected data on 6997 elderly people from Chinese Longitudinal Healthy Longevity Study wave 6–7 surveys (2011–2012, 2014). After the baseline survey in 1998 (wave 1), the project conducted follow-up surveys (wave 2–8) in 2000–2018. The osteoporotic fractures index was used to assess frailty. Four ML algorithms (random forest [RF], support vector machine, XGBoost and logistic regression [LR]) were used to develop models to identify the risk factors of frailty and predict the risk of frailty. Different ML models were used for the prediction of frailty risk in the elderly and frailty risk was trained on a cohort of 4385 elderly people with frailty (split into a training cohort [75%] and internal validation cohort [25%]). The best-performing model for each study outcome was tested in an external validation cohort of 6997 elderly people with frailty pooled from the surveys (wave 6–7). Model performance was assessed by receiver operating curve and F2-score.
Among the four ML models, the F2-score values were similar (0.91 vs. 0.91 vs. 0.88 vs. 0.90), and the area under the curve (AUC) values of RF model was the highest (0.75), followed by LR model (0.74). In the final two models, the AUC values of RF and LR model were similar (0.77 vs. 0.76) and their accuracy was identical (87.4% vs. 87.4%).
Our study developed a preliminary prediction model based on two different ML approaches to help predict frailty risk in the elderly.
The presented models from this study can be used to inform healthcare providers to predict the frailty probability among older adults and maybe help guide the development of effective frailty risk management interventions.
Detecting frailty at an early stage and implementing timely targeted interventions may help to improve the allocation of health care resources and to reduce frailty-related burden. Identifying risk factors for frailty could be beneficial to provide tailored and personalized care intervention for older adults to more accurately prevent or improve their frail conditions so as to improve their quality of life.
The study has adhered to STROBE guidelines.
No patient or public contribution.
The early warning scores (EWS), quick Sequential Organ Failure Assessment (qSOFA) and systemic inflammatory response syndrome (SIRS) criteria have been proposed as sepsis screening tools. This review aims to summarise and compare the performance of EWS with the qSOFA and SIRS criteria for predicting sepsis diagnosis and in-hospital mortality in patients with sepsis.
A systematic review with meta-analysis.
Seven databases were searched from January 1, 2016 until March 10, 2022. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Sensitivity, specificity, likelihood ratios and diagnostic odd ratios were pooled by using the bivariate random effects model. Overall performance was summarised by using the hierarchical summary receiver–operating characteristics curve. This paper adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines.
Ten studies involving 52,474 subjects were included in the review. For predicting sepsis diagnosis, the pooled sensitivity of EWS (65%, 95% CI: 55, 75) was similar to SIRS ≥2 (70%, 95% CI: 49, 85) and higher than qSOFA ≥2 (37%, 95% CI: 20, 59). The pooled specificity of EWS (77%, 95% CI: 64, 86) was higher than SIRS ≥2 (62%, 95% CI: 41, 80) but lower than qSOFA ≥2 (94%, 95% CI: 86, 98). Results were similar for the secondary outcome of in-hospital mortality.
Although no one scoring system had both high sensitivity and specificity, the EWS had at least equivalent values in most measures of diagnostic accuracy compared with SIRS or qSOFA.
Healthcare systems in which EWS is already in place should consider whether there is any clinical benefit in adopting qSOFA or SIRS.
This systematic review did not directly involve patient or public contribution to the manuscript.
This study aimed to describe the knowledge, attitudes and practices (KAP) of nurses in implementing advance directives (ADs) for older patients and analyze the influencing factors before the establishment of the first advance directives act in China.
Multicenter cross-sectional survey. The standards for reporting the STROBE checklist are used.
This cross-sectional study developed a self-designed structured questionnaire to assess nurses' knowledge, attitudes and practices about ADs. Nurses were recruited by stratified random sampling through the Nursing Departments of 12 hospitals in southwest China and were asked to fill out the questionnaire face to face about knowledge, attitudes and practices. Data were analyzed following descriptive statistics, rank-sum test and multiple linear regression.
This study included 950 nurses. The study found that nurses were extremely supportive of ADs. Unmarried nurses had better knowledge of ADs than married ones. Nevertheless, there was a discrepancy between the participants' knowledge, attitude and practice. The participants' practice was lower (4.3%) compared with their attitude (81.9%) and knowledge (42.2%). Knowledge on, attitudes towards and standardized procedures for ADs in the workplace affected nursing practice.
The study recommends that courses on ADs and appropriate support from medical institutions should be provided to nurses to increase their knowledge and confidence in implementing ADs. Healthcare professionals should be sufficiently equipped to implement ADs and handle their execution appropriately to provide adequate end-of-life care corresponding to patients' wishes.
The study results inform rich insights as it discusses the numerous interrelating factors influencing these three fundamental aspects that affect the success of any AD policy by surveying the knowledge, attitudes and practices of clinical nurses. Furthermore, our results hint at distinct areas of improvement in the nursing practice to facilitate the wider implementation and acceptance of ADs in China.
This study involved no patient.
The aim of the study was to identify and synthesize the contents and the psychometric properties of the existing instruments measuring home-based care (HBC) nurses' competencies.
A hybrid systematic narrative review was performed.
The eligible studies were reviewed to identify the competencies measured by the instruments for HBC nurses. The psychometric properties of instruments in development and psychometric testing design studies were also examined. The methodological quality of the studies was evaluated using the Medical Education Research Study Quality Instrument and COSMIN checklist accordingly.
Relevant studies were searched on CINAHL, MEDLINE (via PubMed), EMBASE, PsychINFO and Scopus from 2000 to 2022. The search was limited to full-text items in the English language.
A total of 23 studies reporting 24 instruments were included. 12 instruments were adopted or modified by the studies while the other 12 were developed and psychometrically tested by the studies. None of the instruments encompassed all of the 10 home-based nursing care competencies identified in an earlier study. The two most frequently measured competencies were the management of health conditions, and critical thinking and problem-solving skills, while the two least measured competencies were quality and safety, and technological literacy. The content and structural validity of most instruments were inadequate since the adopted instruments were not initially designed or tested among HBC nurses.
This review provides a consolidation of existing instruments that were used to assess HBC nurses' competencies. The instruments were generally not comprehensive, and the content and structural validity were limited. Nonetheless, the domains, items and approaches to instrument development could be adopted to develop and test a comprehensive competency instrument for home-based nursing care practice in the future.
This review consolidated instruments used to measure home-based care nurses' competency. The instruments were often designed for ward-based care nurses hence a comprehensive and validated home-based nursing care competency instrument is needed. Nurses, researchers and nursing leaders could consider the competency instruments identified in this review to measure nurses' competencies, while a home-based nursing care competency scale is being developed.
No patient or public contribution was required in this review.
Widespread and sustained adoption of telemedicine in long-term residential care is emerging. Nursing home (NH) nurses play a key role in collaborating with remote physicians to manage residents' medical conditions through videoconferencing. Therefore, understanding of interprofessional collaboration and effective communication between nurses and physicians is critical to ensure quality of care and safety during teleconsultations.
To explore NH nurses' and physicians' experiences of interprofessional collaboration and communication during teleconsultations.
A qualitative descriptive design was adopted. Purposive sampling was conducted to recruit 22 physicians and nurses involved in NH teleconsultations. Semi-structured online interviews were conducted, and data were thematically analyzed.
Three themes were identified: (1) Manner of communication in telemedicine, (2) sociocultural influences in collaborative practice, and (3) role expectations in telemedicine. Both nurses and physicians recognized the importance of building and maintaining trust as physicians heavily depended on nurses for provision of objective information for clinical decision-making. However, practice differences were observed between nurses and physicians during teleconsultations. Sociocultural influences such as power relations and language barriers also affected the nurse–physician relationship and interpersonal communication. Additionally, different performance expectations were identified between nurses and physicians.
Interprofessional collaboration in teleconsultations is challenging because of lack of in-person assessment and dependence on nurses for clinical information. In addition, expectations and communication styles differ among healthcare professionals. This study called for interprofessional telemedicine training with incorporation of shared mental models to improve role clarity and communication. Given the international-dominated healthcare workforce in long-term care, the development of cultural competency could also be considered in telemedicine training to enhance nurse–physician collaborative practice.
Telemedicine is increasingly adopted in long-term care settings, where multidisciplinary healthcare professionals from different health institutions are involved in resident care. Interprofessional collaboration should be incorporated into telehealth education for enhanced clinical practice in this care delivery model.
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