Depression in the elderly is an important health factor that requires intervention in the form of social support resources. The purpose of this study was to conduct a systematic review, while synthesizing available evidence on what kind of social support, such as social participation and social connection/network, is effective for depression in the elderly. We performed a quality assessment of the included studies using the revised Risk of Bias for Non-randomized Studies tool and a meta-analysis of studies published up to 14 May 2021. Of the 3449 studies, 52 were relevant to this study. The various types of social resource applications reported in these were classified into three types: social support, social participation, and social connection/network. The social support group had significantly lower depression compared to the control group (0.72 [0.65, 0.81], p < 0.00001, I² = 92%). There was a significant decrease in depression in the social participation group compared to the control group (0.67 [0.56, 0.80], p < 0.00001, I² = 93%) (2.77 [1.30, 5.91], p = 0.008, I² = 97%) (0.67 [0.56, 0.80], p < 0.00001, I² = 93%). Finally, the social connection/network group showed decreased depression compared to the control group (2.40 [1.89, 3.05], p < 0.00001, I² = 24%) (0.83 [0.76, 0.90], p < 0.00001, I² = 94%). The results of this systematic review confirmed the effects of various social support interventions in reducing depression among the elderly living in the community.
Recently, metallic particulate pollutants floating underground have been reported to negatively affect the human body. Thus, there is an urgent need for a public health policy pertaining to the air quality in subway stations. In this study, we investigated whether a vegetation biofilter is effective in reducing metal particle contaminants, especially iron oxide. After selecting a subway station, a vegetation biofilter system was installed, and samples were collected three times, at three intake areas and one exhaust area. The average weight ratio of the detected elements was calculated. The iron oxide reduction effect was evaluated using the Wilcoxon signed rank test. In the return air, C, O, and Fe were detected at 64.9, 27.3, and 5.2 wt.%, respectively; in the supply air, C, O, and Fe were detected at 67.2, 30.4, and 0.7 wt.%, respectively. The difference in the average Fe weight ratio was statistically significant. Air quality has a considerable effect on human health. We confirmed the possibility of reducing Fe in particulate matter using biofilters. However, we could not confirm whether the air quality was improved enough to not have a negative effect on the human body. This should be elucidated through follow-up studies.
AimThis study aimed to develop a valid and reliable new intensive care unit nursing classification tool, including direct and indirect nursing activities, by measuring the nursing intensity provided to patients.BackgroundPrior tools primarily examine patients' medical records or disease severity/interactions, systematically failing to reflect comorbidity risk factors.DesignThe Delphi technique was used to test the content validity of the Korean Patient Classification System on Nursing Intensity for Critical Care Nurses (KPCSNIC).MethodsData were collected from four hospitals in two provinces from 26 December 2017 to 30 January 2018. To verify construct validity, staff nurses classified 365 patients, comparing differences by medical department and type of stay. To verify interrater reliability, data collectors and the head nurses of three intensive care units classified 87 patients.ResultsThe KPCSNIC had 8 categories, 44 nursing activities and 105 criteria. Reliability was high (r = .84). Construct validity was verified by revealing differences according to medical department and type of patient. Using total scores, four KPCSNIC groups were identified.ConclusionThe KPCSNIC developed in this study can support staffing for nursing intensity by providing more specific evaluation criteria. Moreover, it reflects nursing intensity, including direct and indirect nursing activities.
Aim The aim of this study was to identify the patient and hospital characteristics related to nursing needs and nursing hours in acute hospital settings. Background To determine appropriate staffing levels, accumulating empirical data through direct observation and surveys reflecting the actual situation is necessary. Methods In this cross‐sectional study, we conducted direct observations of nurses in acute care hospitals from 1 May to 31 August 2020. Twenty‐six hospitals in five cities participated, and 747 nursing personnel collected 1,681 patients' data while performing nursing activities. The data of 1,605 nurses were analysed using descriptive statistics, t tests, analysis of variance and linear regression. Results Hospital size, admission day, patients' dependence level, high fall risk and disease diagnoses were variables associated with nursing needs (F = 73.49, P < .001) and nursing hours (F = 57.7, P < .001). Comparing the correlates of nursing needs and nursing hours revealed that, unlike nursing needs, nursing hours were not significantly associated with surgery and certain diagnoses. Conclusion This study confirmed the variables associated with nursing needs and nursing hours in acute hospitals; based on this, determining appropriate staffing levels, which is an important step in improving inpatients' health outcomes, is necessary. Implications for Nursing Management In acute hospitals, an increased number of nurse staffing should be employed based on the number of newly hospitalized patients, patients with high dependence levels and specific diagnoses, and those at high risk of falling.
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