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AIM: To describe psychometric validation of the newly developed Advanced Practice Nurse Task Questionnaire. DESIGN: Cross-sectional quantitative study. METHODS: The development of the questionnaire followed an adapted version of the seven steps described in the guide by the Association for Medical Education in Europe. A nationwide online survey tested the construct and structural validity and internal consistency using an exploratory factor analysis, Cronbach's alpha coefficient and a Kruskal-Wallis test to compare the hypotheses. RESULTS: We received 222 questionnaires between January and September 2020. The factor analysis produced a seven-factor solution as suggested in Hamric's model. However, not all item loadings aligned with the framework's competencies. Cronbach's alpha of factors ranged between .795 and .879. The analysis confirmed the construct validity of the Advanced Practice Nurse Task Questionnaire. The tool was able to discriminate the competencies of guidance and coaching, direct clinical practice and leadership across the three advanced practice nurse roles clinical nurse specialist, nurse practitioner or blended role. CONCLUSION: A precise assessment of advanced practice nurse tasks is crucial in clinical practice and in research as it may be a basis for further refinement, implementation and evaluation of roles. IMPACT: The Advanced Practice Nurse Task Questionnaire is the first valid tool to assess tasks according to Hamric's model of competencies independently of the role or the setting. Additionally, it distinguishes the most common advanced practice nurse roles according to the degree of tasks in direct clinical practice and leadership. The tool may be applied in various countries, independent of the degree of implementation and understanding of advanced nursing practice. REPORTING METHOD: The STARD 2015 guideline was used to report the study. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Background: Patients in intensive care units are prone to the occurrence of medication errors. Look-alike, sound-alike drugs with similar drug names can lead to medication errors and therefore endanger patient safety. Capitalisation of distinct text parts in drug names might facilitate differentiation of medication labels. The aim of this study was to test whether the use of such ‘tall man’ lettering (TML) reduces the error rate and to examine effects on the visual attention of critical care nurses while identifying syringe labels. Methods: This was a prospective, randomised in situ simulation conducted at the University Hospital Zurich, Zurich, Switzerland. Under observation by eye tracking, 30 nurses were given 10 successive tasks involving the presentation of a drug name and its selection from a dedicated set of 10 labelled syringes that included look-alike and sound-alike drug names, half of which had TML-coded labels. Error rate as well as dwell time, fixation count, fixation duration and revisits were analysed using a linear mixed-effects model analysis to compare TML-coded with non-TML-coded labels. Results: TML coding of syringe labels led to a significant decrease in the error rate (from 5.3% (8 of 150 in non-TML-coded sets) to 0.7% (1 of 150 in TML-coded sets), p<0.05). Eye tracking further showed that TML affects visual attention, resulting in longer dwell time (p<0.01), more and longer fixations (p<0.05 and p<0.01, respectively) on the drug name as well as more frequent revisits (p<0.01) compared with non-TML-coded labels. Detailed analysis revealed that these effects were stronger for labels using TML in the mid-to-end position of the drug name. Conclusions: TML in drug names changes visual attention while identifying syringe labels and supports critical care nurses in preventing medication errors.

OBJECTIVE: Nosocomial transmission of influenza is a major concern for infection control. We aimed to dissect transmission dynamics of influenza, including asymptomatic transmission events, in acute care. DESIGN: Prospective surveillance study during 2 influenza seasons. SETTING: Tertiary-care hospital. PARTICIPANTS: Volunteer sample of inpatients on medical wards and healthcare workers (HCWs). METHODS: Participants provided daily illness diaries and nasal swabs for influenza A and B detection and whole-genome sequencing for phylogenetic analyses. Contacts between study participants were tracked. Secondary influenza attack rates were calculated based on spatial and temporal proximity and phylogenetic evidence for transmission. RESULTS: In total, 152 HCWs and 542 inpatients were included; 16 HCWs (10.5%) and 19 inpatients (3.5%) tested positive for influenza on 109 study days. Study participants had symptoms of disease on most of the days they tested positive for influenza (83.1% and 91.9% for HCWs and inpatients, respectively). Also, 11(15.5%) of 71 influenza-positive swabs among HCWs and 3 (7.9%) of 38 influenza-positive swabs among inpatients were collected on days without symptoms; 2 (12.5%) of 16 HCWs and 2 (10.5%) of 19 inpatients remained fully asymptomatic. The secondary attack rate was low: we recorded 1 transmission event over 159 contact days (0.6%) that originated from a symptomatic case. No transmission event occurred in 61 monitored days of contacts with asymptomatic influenza-positive individuals. CONCLUSIONS: Influenza in acute care is common, and individuals regularly shed influenza virus without harboring symptoms. Nevertheless, both symptomatic and asymptomatic transmission events proved rare. We suggest that healthcare-associated influenza prevention strategies that are based on preseason vaccination and barrier precautions for symptomatic individuals seem to be effective.

Background: Virus outbreaks such as the current SARS-CoV-2 pandemic are challenging for health care workers (HCWs), affecting their workload and their mental health. Since both, workload and HCW's well-being are related to the quality of care, continuous monitoring of working hours and indicators of mental health in HCWs is of relevance during the current pandemic. The existing investigations, however, have been limited to a single study period. We examined changes in working hours and mental health in Swiss HCWs at the height of the pandemic (T1) and again after its flattening (T2). Methods: We conducted two cross-sectional online studies among Swiss HCWs assessing working hours, depression, anxiety, and burnout. From each study, 812 demographics-matched participants were included into the analysis. Working hours and mental health were compared between the two samples. Results: Compared to prior to the pandemic, the share of participants working less hours was the same in both samples, whereas the share of those working more hours was lower in the T2 sample. The level of depression did not differ between the samples. In the T2 sample, participants reported more anxiety, however, this difference was below the minimal clinically important difference. Levels of burnout were slightly higher in the T2 sample. Conclusions: Two weeks after the health care system started to transition back to normal operations, HCWs' working hours still differed from their regular hours in non-pandemic times. Overall anxiety and depression among HCWs did not change substantially over the course of the current SARS-CoV-2 pandemic.

Delirium screening in acute care settings is a resource intensive process with frequent deviations from screening protocols. A predictive model relying only on daily collected nursing data for delirium screening could expand the populations covered by such screening programs. Here, we present the results of the development and validation of a series of machine-learning based delirium prediction models. For this purpose, we used data of all patients 18 years or older which were hospitalized for more than a day between January 1, 2014, and December 31, 2018, at a single tertiary teaching hospital in Zurich, Switzerland. A total of 48,840 patients met inclusion criteria. 18,873 (38.6%) were excluded due to missing data. Mean age (SD) of the included 29,967 patients was 71.1 (12.2) years and 12,231 (40.8%) were women. Delirium was assessed with the Delirium Observation Scale (DOS) with a total score of 3 or greater indicating that a patient is at risk for delirium. Additional measures included structured data collected for nursing process planning and demographic characteristics. The performance of the machine learning models was assessed using the area under the receiver operating characteristic curve (AUC). The training set consisted of 21,147 patients (mean age 71.1 (12.1) years; 8,630 (40.8%) women|) including 233,024 observations with 16,167 (6.9%) positive DOS screens. The test set comprised 8,820 patients (median age 71.1 (12.4) years; 3,601 (40.8%) women) with 91,026 observations with 5,445 (6.0%) positive DOS screens. Overall, the gradient boosting machine model performed best with an AUC of 0.933 (95% CI, 0.929 - 0.936). In conclusion, machine learning models based only on structured nursing data can reliably predict patients at risk for delirium in an acute care setting. Prediction models, using existing data collection processes, could reduce the resources required for delirium screening procedures in clinical practice.

Introduction: Weight gain is a risk factor for poor clinical outcomes following kidney transplantation. Research Question: This study's aim was a first testing of 2 models to identify patients early after kidney transplantation who are at risk for weight gain and increase in adipose tissue mass in the first year after kidney transplantation. Design: The literature-based models were evaluated on longitudinal data of 88, respectively 79 kidney transplant recipients via ordinary and Firth regression, using gains ≥ 5% in weight and adipose tissue mass respectively as primary and secondary endpoints. Results: The models included physical activity, smoking cessation at time of kidney transplantation, self-reported health status, depressive symptomatology, gender, age, education, baseline body mass index and baseline trunk fat as predictors. Area under the curve was 0.797 (95%-CI 0.702 to 0.893) for the weight model and 0.767 (95%-CI 0.656 to 0.878) for the adipose tissue mass model-showing good, respectively fair discriminative ability. For weight gain ≥ 5%, main risk factors were smoking cessation at time of transplantation (OR 16.425, 95%-CI 1.737-155.288) and better self-reported baseline health state (OR 1.068 for each 1-unit increase, 95%-CI 1.012-1.128). For the adipose tissue mass gain ≥ 5%, main risk factor was overweight/obesity (BMI ≥ 25) at baseline (odds ratio 7.659, 95%-CI 1.789-32.789). Conclusions: The models have potential to assess patients' risk for weight or adipose tissue mass gain during the year after transplantation, but further testing is needed before implementation in clinical practice. Keywords: addictive; behavior; cardiovascular disease; clinical outcomes; depression; exercise outcomes; nutrition; performance improvement; quality; quality of life; quantitative methods; regression; research.

Aim: Although the risk factors for delirium in general medicine are well-established, their significance in cardiac diseases remains to be determined. Therefore, we evaluated the predisposing and precipitating risk factors in patients hospitalized with acute and chronic heart disease. Methods and Results: In this observational cohort study, 1,042 elderly patients (≥65 years) admitted to cardiology wards, 167 with and 875 without delirium, were included. The relevant sociodemographic and cardiac- and medical-related clusters were assessed by simple and multiple regression analyses and prediction models evaluating their association with delirium. The prevalence of delirium was 16.0%. The delirious patients were older (mean 80 vs. 76 years; p < 0.001) and more often institutionalized prior to admission (3.6 vs. 1.4%, p = 0.05), hospitalized twice as long (12 ± 10 days vs. 7 ± 7 days; p < 0.001), and discharged more often to nursing homes (4.8 vs. 0.6%, p < 0.001) or deceased (OR, 2.99; 95% CI, 1.53-5.85; p = 0.003). The most relevant risk factor was dementia (OR, 18.11; 95% CI, 5.77-56.83; p < 0.001), followed by history of stroke (OR, 6.61; 95% CI 1.35-32.44; p = 0.020), and pressure ulcers (OR, 3.62; 95% CI, 1.06-12.35; p = 0.040). The predicted probability for developing delirium was highest in patients with reduced mobility and institutionalization prior to admission (PP = 31.2%, p = 0.001). Of the cardiac diseases, only valvular heart disease (OR, 1.57; 95% CI, 1.01-2.44; p = 0.044) significantly predicted delirium. The patients undergoing cardiac interventions did not have higher rates of delirium (OR, 1.39; 95% CI 0.91-2.12; p = 0.124). Conclusion: In patients admitted to a cardiology ward, age-related functional and cognitive impairment, history of stroke, and pressure ulcers were the most relevant risk factors for delirium. With regards to specific cardiological factors, only valvular heart disease was associated with risk for delirium. Knowing these factors c

BACKGROUND: The challenges in dealing with multiple sclerosis (MS) have increased considerably in recent years. In addition to neurologists, MS nurse specialists are key to the management of MS patients, but there is a lack of evidence regarding their quality of counseling. METHODS: The data collection took place between October 2018 and March 2019 in the outpatient clinic of a university hospital. The quality of counseling was assessed using the APN-BQ, an instrument that contains 19 items that can be assigned to 4 dimensions. Participants were asked to rate their satisfaction on a scale from 0 to 3. General satisfaction was assessed on a scale from 0 to 100. RESULTS: The participants (n = 110) rated the quality of counseling and their general satisfaction high. The mean (SD) of the structure quality dimension was 2.64 (0.44), and satisfaction with length and frequency of consultations (2.53 [0.63]) scored better than outcome quality (1.99 [0.62]) and process quality (2.13 [0.60]). CONCLUSION: Overall, there was a high rate of satisfaction with the quality of counseling. In addition to the length and frequency of consultations, MS patients particularly appreciated the availability and expertise of MS nurse specialists.

Objective: The current SARS-CoV-2 pandemic poses various challenges for health care workers (HCWs). This may affect their mental health, which is crucial to maintain high quality medical care during a pandemic. Existing evidence suggests that HCWs, especially women, nurses, frontline staff, and those exposed to COVID-19 patients, are at risk for anxiety and depression. However, a comprehensive overview of risk and protective factors considering their mutual influence is lacking. Therefore, this study aimed at exploring HCWs' mental health during the SARS-CoV-2 pandemic in Switzerland, investigating the independent effect of various demographic, work- and COVID-related factors on HCWs' mental health.Methods: In an exploratory, cross-sectional, nation-wide online survey, we assessed demographics, work characteristics, COVID-19 exposure, and anxiety, depression, and burnout in 1,406 HCWs during the beginning of the SARS-CoV-2 pandemic in Switzerland. Network analysis was used to investigate the associations among the included variables.Results: Women (compared to men), nurses (compared to physicians), frontline staff (compared to non-frontline workers), and HCWs exposed to COVID-19 patients (compared to non-exposed) reported more symptoms than their peers. However, these effects were all small. Perceived support by the employer independently predicted anxiety and burnout after adjustment for other risk factors.Conclusion: Our finding that some HCWs had elevated levels of anxiety, depression, and burnout underscores the importance to systematically monitor HCWs' mental health during this ongoing pandemic. Because perceived support and mental health impairments were negatively related, we encourage the implementation of supportive measures for HCWs' well-being during this crisis.

Background: Families of critically ill persons face uncertainty and experience distress during and after their close other's stay in an intensive care unit (ICU). Proactive nurse engagement and support is recommended to meet families' needs in the ICU, but little is known about its impact on quality of family care. We introduced a family support intervention that consisted of an interprofessional family support pathway and a new role of an advanced practice family nurse. Objectives: The aim of the study was to examine the effect of an advanced practice nurse-led family support intervention on family members' satisfaction, wellbeing, and psychological distress. Methods: We conducted a quasi-experimental before-and-after study with embedded qualitative interviews in a Swiss University Hospital from March 2018 to July 2019 using a questionnaire (Family Satisfaction in the ICU-24 Survey, Hospital Anxiety and Depression Scale, and Impact of Event Scale-Revised-6) and qualitative interviews (n = 19) after patient discharge. Results: Families in the intervention group (n = 75) showed a trend for increased overall satisfaction (difference of 5.544, 95% confidence interval [CI]: -0.11 to 11.20), a statistically significant increase in satisfaction with decision-making (7.258, 95% CI: 0.89 to 13.63), and a nonsignificant increase in satisfaction with care (4.178, 95% CI: -1.53 to 9.89). Psychological distress was higher in the intervention group, with depression reaching statistical significance (difference of 1.706, 95% CI: 0.16 to 3.25), which may be explained by longer ICU stays and higher proportion of deaths in the intervention group. Families receiving the intervention reported to be feeling cared for, well informed, and better able to cope. Data integration suggests that early onset, fit to need, and quality of intervention were the most important intervention characteristics impacting family wellbeing. Conclusions: Our study found that family members experience a nurs

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), Nursing assessments have been recommended for the daily screening for delirium; however, the utility of individual items have not yet been tested. In a first step in establishing the potential of the electronic Patient Assessment-Acute Care (ePA-AC) as such, the impact of delirium on the functional domains was assessed.

OBJECTIVES: To investigate family and health professional experience with a nurse-led family support intervention in intensive care. DESIGN: Qualitative evaluation study. SETTING: A twelve-bed surgical intensive care unit in a 900-bed University Hospital in Switzerland. MAIN OUTCOME MEASURES: Data were collected through 16 semi-structured interviews with families (n = 19 family members) and three focus group interviews with critical care staff (n = 19) and analysed using content analysis strategies. FINDINGS: Four themes related to the new family support intervention were identified. First, families and staff described it as a valuable and essential part of ICU care. Second, it facilitated staff-family interaction and communication. Third, from staff perspective, it promoted the quality of family care. Fourth, staff believed that the family support intervention enabled them to better care for families through increased capacity for developing and sustaining relationships with families. CONCLUSIONS: An advanced practice family nursing role coupled with a family support pathway is an acceptable, appreciated and beneficial model of care delivery in the inttensive care unit from the perspective of families and critical care staff. Further research is needed to investigate the intervention's effectiveness in the intensive care unit.