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In order to be positioned to address the increasing strain of burnout and worsening nurse shortage, a better understanding of factors that contribute to nursing workload is required. This study aims to examine the difference between order-based and clinically perceived nursing workloads and to quantify factors that contribute to a higher clinically perceived workload.
A retrospective cohort study was used on an observational dataset.
We combined patient flow, nurse staffing and assignment, and workload intensity data and used multivariate linear regression to analyze how various shift, patient, and nurse-level factors, beyond order-based workload, affect nurses' clinically perceived workload.
Among 53% of our samples, the clinically perceived workload is higher than the order-based workload. Factors associated with a higher clinically perceived workload include weekend or night shifts, shifts with a higher census, patients within the first 24 h of admission, and male patients.
The order-based workload measures tended to underestimate nurses' clinically perceived workload. We identified and quantified factors that contribute to a higher clinically perceived workload, discussed the potential mechanisms as to how these factors affect the clinically perceived workload, and proposed targeted interventions to better manage nursing workload.
By identifying factors associated with a high clinically perceived workload, the nurse manager can provide appropriate interventions to lighten nursing workload, which may further reduce the risk of nurse burnout and shortage.
With the prolongation of the COVID-19 pandemic, more individuals are experiencing sequelae after COVID-19 infection, also known as post-acute COVID-19 syndrome (PCS). The aims of this study were to describe the prevalence and characteristics of PCS symptoms such as fatigue, anxiety, and depression and to compare these symptoms according to participant characteristics in patients who had been previously hospitalized due to COVID-19.
A descriptive cross-sectional study design was used.
We included 114 individuals who had been hospitalized for COVID-19 and were discharged from the hospital at least 4 weeks before. Symptoms were assessed using the Fatigue Severity Scale, the Hospital Anxiety-Depression Scale, and the PCS symptom questionnaire developed by the authors. We used descriptive statistics, the Student's t-test, the Wilcoxon rank-sum test, and the Kruskal–Wallis test for statistical analyses.
The most prevalent symptoms were anxiety (66.7%), fatigue (64.0%), headache (57.9%), and concentration or memory difficulties (57.9%). Concentration or memory difficulties and sleep disturbances had the highest mean frequency. Concentration or memory difficulties were rated with the highest mean severity, and cough, loss of taste, and muscle and joint pain had the highest mean distress scores. Female participants, individuals hospitalized for more than 2 weeks, individuals discharged more than 9 months ago, unvaccinated patients, and those who tried at least one symptom relief method reported higher symptom distress.
The findings of this investigation into the frequency, severity, and distress of symptoms shed light on the identification of post-COVID symptoms in detail. To objectively evaluate and comprehend the symptom trajectories of PCS, prospective studies about the development of symptom assessment tools and studies with a longitudinal design should be conducted.
A substantial number of respondents reported numerous symptoms and expressed symptom distress; therefore, the development of nursing interventions and treatments to alleviate PCS symptoms is crucial.
Previous systematic reviews and meta-analyses have mainly focused on improvements in the number of metabolic syndrome risk factors and individual changes in each risk factor, making it challenging to examine the impact of comprehensive lifestyle modification interventions on adherence to recommended health behaviors. To address this gap, we conducted a systematic and meta-analysis aimed at identifying clinical parameter levels associated with lifestyle modification outcomes and adherence to recommended health behaviors for individuals with metabolic syndrome.
A total of seven studies retrieved from four databases (CINAHL, Medline via PubMed, American Psychological Association PsycINFO, and Embase) were included in the review. The selected studies, which demonstrated improvements in health behaviors, all included diet and exercise as main factors of comprehensive lifestyle modification in home settings.
Our findings suggest that a 6-month comprehensive intervention including diet and exercise can be effective in decreasing glucose levels and systolic blood pressure. However, given the limited available data, further studies investigating the efficacy of interventions of varying durations are needed.
Although our review included a small number of studies, comprehensive lifestyle modifications consisting of at least two components (primarily diet and exercise) can improve health behaviors and some clinical parameters among individuals with metabolic syndrome. Future studies are needed to investigate the long-term effects of lifestyle modifications on health behavior adherence and explore effective interventions to address certain clinical parameters, such as high-density lipoprotein levels. Also, we recommend using objective and quantifiable measure to compare adherence to recommended lifestyle modifications across studies.
This research provides empirical evidence of the effectiveness of comprehensive lifestyle modification and emphasizes the need to develop long-term nursing strategies in public health that can be used to effectively manage metabolic syndrome.
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