Abrahamsenhartley5060

Furthermore, we observed that test-taking behaviors and performance change as students progress through the assessment. MS177 We provide recommendations for identifying and filtering out data from students with low test-taking motivation so that the filtered data set better represents student understanding.Anxiety can impact overall performance and persistence in college. Student response systems (SRSs), real-time active-learning technologies used to engage students and gauge their understanding, have been shown to elicit anxiety for some students. Kahoot! is an SRS technology that differs from others in that it involves gamification, the use of gamelike elements. Recent studies have explored the impact of active-learning strategies on student anxiety across different institutions, but there is little known about how Kahoot! impacts student perceived anxiety, especially in comparison with other active-learning strategies. In two complementary yet parallel studies of introductory biology courses at a western research-intensive institution (n = 694) and a southeastern research-intensive institution (n = 60), we measured students' perceived anxiety. We then explored how students were influenced by nongraded Kahoot! play and other elements of instruction. Using previously developed and course-specific pre- and post-course surveys, we found students at both universities agreed that nongraded Kahoot! play caused less anxiety compared with other pedagogical practices, such as working in small groups or reading the textbook. After playing Kahoot!, lower-performing students demonstrated greater engagement and lower levels of anxiety compared with their peers, suggesting that Kahoot! may be a particularly engaging active-learning strategy for these students.Metacognition is awareness and control of thinking for learning. Strong metacognitive skills have the power to impact student learning and performance. While metacognition can develop over time with practice, many students struggle to meaningfully engage in metacognitive processes. In an evidence-based teaching guide associated with this paper (https//lse.ascb.org/evidence-based-teaching-guides/student-metacognition), we outline the reasons metacognition is critical for learning and summarize relevant research on this topic. We focus on three main areas in which faculty can foster students' metacognition supporting student learning strategies (i.e., study skills), encouraging monitoring and control of learning, and promoting social metacognition during group work. We distill insights from key papers into general recommendations for instruction, as well as a special list of four recommendations that instructors can implement in any course. We encourage both instructors and researchers to target metacognition to help students improve their learning and performance.

Patients with ADHD are at increased risk of acquiring COVID-19. The present study assessed the possibility that ADHD also increases the risk of severe COVID-19 infection.

We assessed 1,870 COVID-19 positive patients, aged 5 to 60 years, registered in the database of Leumit Health Services (LHS, Israel), February to -June 2020, of whom 231 with ADHD. Logistic regression analysis models evaluated the association between ADHD and the dependent variables of being symptomatic/referral to hospitalization, controlling for demographic and medical variables.

Age, male sex, and BMI were confirmed to be significant risk factors for increased COVID-19 severity. ADHD was found to be associated with increased severity of COVID-19 symptoms (

 = 1.81, 95% CI [1.29, 2.52],

 < .05) and referral to hospitalization (

=1.93, 95% CI [1.06, 3.51],

 = .03).

ADHD is associated with poorer outcomes in COVID-19 infection.

ADHD is associated with poorer outcomes in COVID-19 infection.

We investigated whether an in-hospital intervention consisting of fall risk screening and tailored advice could prompt patients to take preventive action.

Patients (≥70) attending the emergency department and nephrology outpatient clinic in a Dutch hospital were screened. Patients at high risk received tailored advice based on their individual risk factors. Three months after screening, preventive steps taken by patients were surveyed.

Two hundred sixteen patients were screened. Of the 83 patients completing a 3-month follow-up, 51.8% took action; among patients who received tailored advice (

= 20), 70% took action. Patients most often adhered to advice on improving muscle strength and undergoing vision checkups (20%). Tailored advice and a reported low quality of life were associated with consulting a health care provider.

Patients at risk in these settings are inclined to take action after screening. However, they do not always adhere to the tailored prevention advice.

Patients at risk in these settings are inclined to take action after screening. However, they do not always adhere to the tailored prevention advice.

There is no consensus in the foot and ankle literature regarding how to measure pronation of the first metatarsal in patients with hallux valgus. The primary purpose of this study was to compare 2 previously published methods for measuring pronation of the first metatarsal and a novel 3-dimensional measurement of pronation to determine if different measurements of pronation are associated with each other.

Thirty patients who underwent a modified Lapidus procedure for their hallux valgus deformity were included in this study. Pronation of the first metatarsal was measured on weightbearing computed tomography (WBCT) scans using the α angle with reference to the floor, a 3-dimensional computer-aided design (3D CAD) calculation with reference to the second metatarsal, and a novel method, called the triplanar angle of pronation (TAP), that included references to both the floor (floor TAP) and base of the second metatarsal (second TAP). Pearson's correlation coefficients were used to determine if the 3 calculated angles of pronation correlated to each other.

Preoperative and postoperative α angle and 3D CAD had no correlation with each other (

= 0.094,

= .626 and

= 0.076,

= .694, respectively). Preoperative and postoperative second TAP and 3D CAD also had no correlation (

= 0.095,

= .624 and

= 0.320,

= .09, respectively). However, preoperative and postoperative floor TAP and α angle were found to have moderate correlations (

= 0.595,

= .001 and

= 0.501,

= .005, respectively).

The calculation of first metatarsal pronation is affected by the reference and technique used, and further work is needed to establish a consistent measurement for the foot and ankle community.

Level III, retrospective cohort study.

Level III, retrospective cohort study.