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The purpose of this systematic review was to reveal the evidence of how the method of flipped classroom was applied in nursing education and examine the results associated with this teaching method.

Peer-reviewed studies published from 2013 to 2020 were selected from the PubMed, Web of Science, and Science Direct databases.

A systematic review was conducted according to the PRISMA Statement Guidelines. Electronic databases were searched using a range of keywords, and the findings were integrated into a narrative synthesis. Quality appraisal was undertaken.

In total, 7470 articles were retrieved including the 24 paper those were finally selected for the systematic reviews. The themes identified were academic performance outcomes, student perceptions, activities, and structures.

It was determined that the flipped classroom method supported learning effectively and increased the quality of teaching. Pracinostat datasheet Nursing courses are suggested to be structured as flipped classrooms.
It was determined that the flipped classroom method supported learning effectively and increased the quality of teaching. Nursing courses are suggested to be structured as flipped classrooms.
Graduating nursing students report lower competence in leadership and delegation skills, which may be due to lack of sufficient opportunities to practice leadership skills such as delegation and supervision. A near-peer clinical supervision model, in which third-year students supervise first-year students on placement, may provide a mechanism to develop graduating students' leadership skills while improving the learning experience for junior students.

To evaluate nursing students' experiences and perceptions of participating in a near-peer clinical supervision model.

A mixed methods design including an anonymous post-placement survey of students, and a group interview.

Medical and surgical wards in three Australian hospitals.

Forty-three first-year nursing students were supervised by 92 third-year nursing students on clinical placement under the supervision of a registered nurse in a near-peer supervision model.

Twenty-seven first-year (69.2%) and 43 third-year (46.7%) students completed the questeadership and delegation skills and a positive experience of placement for junior students. Further attention to preparation of ward registered nurses would improve model delivery.
The timely identification of patients for hospitalization in emergency departments (EDs) can facilitate efficient use of hospital resources. Machine learning can help the early prediction of ED disposition; however, application of machine learning models requires both computer science skills and domain knowledge. This presents a barrier for those who want to apply machine learning to real-world settings.

The objective of this study was to construct a competitive predictive model with a minimal amount of human effort to facilitate decisions regarding hospitalization of patients.

This study used the electronic health record data from five EDs in a single healthcare system, including an academic urban children's hospital ED, from January 2009 to December 2013. We constructed two machine learning models by using automated machine learning algorithm (autoML) which allows non-experts to use machine learning model one with data only available at ED triage, the other adding information available one hour into tdings can optimize ED management, hospital-level resource utilization and improve quality. Furthermore, this approach can support the design of a more effective patient ED flow for pediatric asthma care.
In comparison with the conventional approaches, the use of autoML improved the predictive ability for the need for hospitalization. The findings can optimize ED management, hospital-level resource utilization and improve quality. Furthermore, this approach can support the design of a more effective patient ED flow for pediatric asthma care.
Pes planovalgus is common in children with cerebral palsy. Although severity influences treatment, there still lacks standard clinical measurements to objectively quantify pes planovalgus in this population. The comparison of pedobarographic data and radiographic measurements to clinical evaluation has not been reported in this population.

395 feet were identified from a population of ambulatory pediatric patients with cerebral palsy. Each patient initially underwent clinical evaluation by an experienced physical therapist who classified feet as 136 controls, 116 mild, 100 moderate, and 43 severe pes planovalgus. Quantitative measurements were then calculated from antero-posterior and lateral radiographs of the foot. Pedobarographic analysis included the arch index, center of pressure index, and a newly defined medial index.

A multivariate analysis was performed on the radiographic and pedobarographic measurements collected. It identified seven variables that improved objective classification of pes pladependently. In a clinical setting, radiographs and pedobarographic data may be obtained to enhance assessment of severity and guide treatment.
Pelvic injuries that disrupt the sacroiliac joints often require surgical intervention to restore stability. Quantitative characterization of sacroiliac motion in response to physiologic loading provides important metrics of adequate fixation in the evaluation of newly emerged fixation techniques. The objective of this study was to systematically review and evaluate biomechanical evidence on the motion of the sacroiliac joint in its normal, destabilized, and stabilized states.

We searched the PubMed database for studies available until June 2020 using keywords sacroiliac, biomechanic*, and fixation. Publications of any in vivo or in vitro biomechanical study that included measurements of the range of motion at the sacroiliac joint were considered.

We identified and screened 176 total records, and 13 articles of them met inclusion criteria and were used in this review. The average sacroiliac joint range of motion of the intact pelvis was 1.88° in flexion/extension, 0.85° in lateral bending, 1.26° in axial rotation.
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