Why Peer Tutoring is Essential in the Classroom

For Longwood University’s 2020 Spring Showcase, we chose to present on why Peer Tutoring is essential in the classroom environment. Each of us has participated in a Classroom Management course this semester, taught by Dr. Katherine Matthews, that informed us about what Peer Tutoring means for both students and teachers. In our presentation, we look at various sources that explain what Peer Tutoring is and offer scientific studies that show its direct results. In addition to exploring what it is and how it benefits the classroom, we also look into potential setbacks as well as which content areas are best suited for Peer Tutoring. We hope you enjoy our presentation and we encourage everyone to ask questions or make comments in the Digital Commons space; one of our team members will answer in a timely fashion. Thank you in advance for viewing our presentation on Peer Tutoring

Conversing or Diffusing Information? An Examination of Public Health Twitter Chats

This study examines the one-way information diffusion and two-way dialogic engagement present in public health Twitter chats. Network analysis assessed whether Twitter chats adhere to one of the key principles for online dialogic communication, the dialogic loop (Kent & Taylor, 1998) for four public health-related chats hosted by CDC Twitter accounts. The features of the most retweeted accounts and the most retweeted tweets also were examined. The results indicate that very little dialogic engagement took place. Moreover, the chats seemed to function as pseudoevents primarily used by organizations as opportunities for creating content. However, events such as #PublicHealthChat may serve as important opportunities for gaining attention for issues on social media. Implications for using social media in public interest communications are discussed

Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge

Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

A cognitive behavioral digital therapeutic for anxiety and depression in patients with cancer: A decentralized randomized controlled trial

1507 Background: Patients with cancer often experience clinically elevated levels of distress, including anxiety and depression. Psychological interventions, such as Cognitive Behavioral Stress Management (CBSM), have evidenced benefits on distress, quality of life, and long-term health outcomes, however, they are not widely available or easily accessible. Digitizing these interventions may be a means of democratizing access to cancer-focused and empirically-supported mental health care. Methods: This double-blind randomized controlled trial (RCT) compared the impact of a 10-module digitized CBSM app [attune] vs. a health education control app [cerena] on anxiety and depression symptoms in patients with cancer (n=449). Patients with non-metastatic (stage I-III) and hematological cancers who were receiving or recently (≤6 months) completed systemic treatment and reported a PROMIS-A T-Score >60 were recruited to participate in this decentralized clinical trial through a nationwide online advertising campaign. The pre-specified primary outcome was change in anxiety symptoms (PROMIS-A) across conditions over time (week 0, 4, 8, and 12) in the intention-to-treat population analyzed using a linear mixed effects model with repeated measures. Secondary outcomes included change in depression symptoms (PROMIS-D) and global impression of change in anxiety and depression (PGI-C). Results: Patients in the study were 80.6% female, 76.5% white, and the mean (SD; range) age was 52.44 (11.46; 25-80) years. Compared to the control, attune participants showed significantly greater reductions in anxiety (β=-0.03; p=0.019) and depression (β=-0.02; p=0.042) symptoms over 12-weeks, and at end-of-study (week 12) there was a greater proportion of attune participants in the PROMIS-A (χ 2 =7.13; p=0.004) and PROMIS-D (χ 2 =3.53; p=0.035) mild-none symptom severity category. There were also significant group differences in PGI-C, with attune participants more likely to report ‘much’ or ‘very much’ improvement in their anxiety (χ 2 =31.76; p<0.001) and depression symptoms (χ 2 =19.70; p<0.001). Conclusions: Digital therapeutics have the potential to improve access to empirically supported psychological treatments for symptoms of anxiety and depression in patients with cancer. In this decentralized, double-blind RCT, we show that compared with a visually and functionally similar sham app, patients who used attune had significantly greater reductions in anxiety and depression symptoms over time. Moreover, at the end of the study, participants who used attune were significantly more likely to report their anxiety and depression symptoms were ‘much’ or ‘very much’ improved, indicating clinically meaningful change. Future work aims to explore implementation strategies to maximize benefit and accessibility of this cancer-specific digital therapeutic. Clinical trial information: NCT05227898

Effects of a Cognitive Behavioral Digital Therapeutic on Anxiety and Depression Symptoms in Patients With Cancer: A Randomized Controlled Trial.

PURPOSE: Patients with cancer often experience elevated levels of distress. This double-blind, randomized controlled trial compared the impact of an app-based version of cognitive behavioral stress management (CBSM) versus a health education sham app on anxiety and depression symptoms. METHODS: Patients with nonmetastatic (stage I-III) cancer who were receiving or recently completed (≤6 months) systemic treatment were recruited nationwide. The primary outcome of change in anxiety symptoms (PROMIS-Anxiety) over 12 weeks and the top secondary outcome of change in depression symptoms (PROMIS-Depression) over 12 weeks were analyzed using mixed-effects modeling with repeated measures (weeks 0, 4, 8, 12). Patient global impressions of change in anxiety and depression were reported at weeks 4, 8, and 12. In addition, self-reported adverse events were collected throughout the study and adjudicated by the site principal investigator. RESULTS: Four hundred forty-nine patients were enrolled in the trial (age M [standard deviation] = 52.44 [11.46]; 81% female; 76% White; 53% breast cancer). Patients randomly assigned to digitized CBSM showed significantly greater reductions in anxiety (B = -0.03; P = .019) and depression (B = -0.02; P = .042) symptoms over 12 weeks. Patients who received digitized CBSM were also significantly more likely to perceive much or very much improvement (v no/minimal change or much/very much worse) in their symptoms of anxiety (χ2 = 31.76; P &lt; .001) and depression (χ2 = 19.70; P &lt; .001) compared with the control. CONCLUSION: The use of digitized CBSM led to significant improvements in anxiety and depression outcomes compared with the sham app

Effects of a Cognitive Behavioral Digital Therapeutic on Anxiety and Depression Symptoms in Patients With Cancer:A Randomized Controlled Trial

Results from a clinical trial of a new cognitive behavioral stress management (CBSM) app show a significant benefit for patients with cancer with symptoms of anxiety and depression. The double-blind, randomized controlled trial compared the cancer-specific app with a health education sham app in 449 patients diagnosed with nonmetastatic cancers. Patients who received the cancer-specific app showed significantly greater reductions in symptoms of anxiety and depression over 12 weeks and were significantly more likely to report their symptoms as much or very much improved at the end of the study. Self-reported adverse events were also collected to inform benefit-risk. PURPOSE Patients with cancer often experience elevated levels of distress. This double-blind, randomized controlled trial compared the impact of an app-based version of cognitive behavioral stress management (CBSM) versus a health education sham app on anxiety and depression symptoms. METHODS Patients with nonmetastatic (stage I-III) cancer who were receiving or recently completed (≤6 months) systemic treatment were recruited nationwide. The primary outcome of change in anxiety symptoms (PROMIS-Anxiety) over 12 weeks and the top secondary outcome of change in depression symptoms (PROMIS-Depression) over 12 weeks were analyzed using mixed-effects modeling with repeated measures (weeks 0, 4, 8, 12). Patient global impressions of change in anxiety and depression were reported at weeks 4, 8, and 12. In addition, self-reported adverse events were collected throughout the study and adjudicated by the site principal investigator. RESULTS Four hundred forty-nine patients were enrolled in the trial (age M [standard deviation] = 52.44 [11.46]; 81% female; 76% White; 53% breast cancer). Patients randomly assigned to digitized CBSM showed significantly greater reductions in anxiety ( B = –0.03; P = .019) and depression ( B = –0.02; P = .042) symptoms over 12 weeks. Patients who received digitized CBSM were also significantly more likely to perceive much or very much improvement ( v no/minimal change or much/very much worse) in their symptoms of anxiety (χ 2 = 31.76; P < .001) and depression (χ 2 = 19.70; P < .001) compared with the control. CONCLUSION The use of digitized CBSM led to significant improvements in anxiety and depression outcomes compared with the sham app

Twelve-Month Longitudinal Serology in SARS-CoV-2 Na&iuml;ve and Experienced Vaccine Recipients and Unvaccinated COVID-19-Infected Individuals

Longitudinal data comparing SARS-CoV-2 serology in individuals following infection and vaccination over 12 months are limited. This study compared the magnitude, decay, and variability in serum IgG, IgA, and neutralizing activity induced by natural infection (n = 218) or mRNA vaccination in SARS-CoV-2 na&iuml;ve (n = 143) or experienced (n = 122) individuals over time using enzyme-linked immunosorbent assays and an in vitro virus neutralization assay. Serological responses were found to be highly variable after natural infection compared with vaccination but durable through 12 months. Antibody levels in vaccinated, SARS-CoV-2 na&iuml;ve individuals peaked by 1 month then declined through 9 months, culminating in non-detectable SARS-CoV-2-specific serum IgA. Individuals with both infection and vaccination showed SARS-CoV-2-specific IgG and IgA levels that were more robust and slower to decline than the other groups; neutralizing activity remained highest in this group at 9 months past vaccination. These data reinforce the benefit of vaccination after SARS-CoV-2 recovery