The Common Core State Standards and the Previous NYS Standards Case Study: What Can We Learn About the Math and ELA Common Core State Standards and the Previous NYS Standards through Lessons Conducted with One Child?

This paper examines research concerning the Common Core State Standards (CCSS) and the previous NYS Standards. The authors of the different articles presented in this literature review Main (2011), Wurman & Wilson (2012), Liebtag (2013), Conley (2014), and McLaughlin & Overturf (2012), take different stances as to whether or not the Common Core is beneficial for our students or detrimental to our students as they progress through school. The ultimate goal of the CCSS is for students to be college and career ready. This paper explores the English Language Arts (ELA) and Math Common Core State Standards and previous NYS Standards through lessons conducted with a fourth-grade child. After conducting the case study, the findings were that neither set of standards provide the level of challenge the child needs; both sets of standards need to allow more time for creativity and hands-on learning opportunities; the child preferred the previous NYS Standard math lessons I created over the Common Core math lessons; and lastly, in contrast, the child preferred the Common Core ELA lessons versus the previous NYS ELA lessons I created

Lithium Abundances in the Solar Twins 16 CYG A and B and the Solar Analog alpha CEN A, Calibration of the 6707 Angstrom Li Region Linelist, and Implications

We present high resolution (R ˜45,000-70,000) and very high S/N (˜1,000) spectroscopy of the Li I 6707 Å region in each component of the binary solar twins 16 Cyg A and B, the solar analog alpha Cen A, and alpha Cen B. Spectra of 16 Cyg were obtained with the University of Hawai\u27i 2.2-m, McDonald Observatory 2.1-m, and Keck 10-m telescopes and have been independently reduced. Comparison of spectral synthesis and the 16 Cyg data, and corresponding similarly obtained solar data, yields 7Li abundances which show excellent concordance between the various data sets. Despite differing in Teff by only 35-40 K, the Li abundances of 16 Cyg A and B differ by a factor of \u3e=4.5. The solar photospheric abundance is intermediate to the two values. This intermediacy indicates that the Sun, whose highly depleted photospheric Li abundance is in gross conflict with standard stellar models, is not an isolated anomaly in its Li abundance evolution. A similar conclusion is reached via comparison of alpha Cen A and metal-rich Hyades dwarfs. The difference in the 16 Cyg components\u27 abundances suggests, though does not directly establish, a slow (possibly rotationally-induced) mixing mechanism operating below the surface convection zone in these stars. Indeed, the Li abundance difference can be viewed as an analog to the Li abundance dispersion seen in cool stars of similar Teff in open and globular clusters, and in Galactic field halo stars. It is possible, in principle anyway, that the low Li abundances of the Sun and 16 Cyg B with respect to 16 Cyg A may be related to the presence of a planetary companion; Li abundances of 47 UMa, and HD 114762 might further support such a connection between planets/disks, angular momentum evolution, and photospheric Li abundances. Due to a variety of uncertainties, however, any conclusions remain tenuous and speculative at this time. Finally, as an interesting aside, we show that current line list uncertainties in the delta6707 region suggest that claims of very small 6Li/7Li ratios ( 0.01) inferred from analysis of the solar photospheric spectrum are overly optimistic-though not necessarily incorrect

Video-Based Communication Assessment: Development of an Innovative System for Assessing Clinician-Patient Communication

Good clinician-patient communication is essential to provide quality health care and is key to patient-centered care. However, individuals and organizations seeking to improve in this area face significant challenges. A major barrier is the absence of an efficient system for assessing clinicians\u27 communication skills and providing meaningful, individual-level feedback. The purpose of this paper is to describe the design and creation of the Video-Based Communication Assessment (VCA), an innovative, flexible system for assessing and ultimately enhancing clinicians\u27 communication skills. We began by developing the VCA concept. Specifically, we determined that it should be convenient and efficient, accessible via computer, tablet, or smartphone; be case based, using video patient vignettes to which users respond as if speaking to the patient in the vignette; be flexible, allowing content to be tailored to the purpose of the assessment; allow incorporation of the patient\u27s voice by crowdsourcing ratings from analog patients; provide robust feedback including ratings, links to highly rated responses as examples, and learning points; and ultimately, have strong psychometric properties. We collected feedback on the concept and then proceeded to create the system. We identified several important research questions, which will be answered in subsequent studies. The VCA is a flexible, innovative system for assessing clinician-patient communication. It enables efficient sampling of clinicians\u27 communication skills, supports crowdsourced ratings of these spoken samples using analog patients, and offers multifaceted feedback reports

DCE-MRI for pre-treatment prediction and post-treatment assessment of treatment response in sites of squamous cell carcinoma in the head and neck

Background and Purpose It is important to identify patients with head and neck squamous cell carcinoma (SCC) who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE)-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck. Material and Methods Forty-nine patients with 83 SCC sites (primary and/or nodal) underwent pre-treatment DCEMRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and %change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years. Results None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF) (29/83 sites) or site control (SC) (54/83 sites). Post-treatment residual masses with SF (14/33) had significantly higher kep (p = 0.05), higher AUGC (p = 0.02), and lower % reduction in AUGC (p = 0.02), than residual masses with SC (19/33), with the% change in AUGC remaining significant on multivariate analysis. Conclusion Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment

DCE-MRI for pre-treatment prediction and post-treatment assessment of treatment response in sites of squamous cell carcinoma in the head and neck

Background and Purpose It is important to identify patients with head and neck squamous cell carcinoma (SCC) who fail to respond to chemoradiotherapy so that they can undergo post-treatment salvage surgery while the disease is still operable. This study aimed to determine the diagnostic performance of dynamic contrast enhanced (DCE)-MRI using a pharmacokinetic model for pre-treatment predictive imaging, as well as post-treatment diagnosis, of residual SCC at primary and nodal sites in the head and neck. Material and Methods Forty-nine patients with 83 SCC sites (primary and/or nodal) underwent pre-treatment DCEMRI, and 43 patients underwent post-treatment DCE-MRI, of which 33 SCC sites had a residual mass amenable to analysis. Pre-treatment, post-treatment and %change in the mean Ktrans, kep, ve and AUGC were obtained from SCC sites. Logistic regression was used to correlate DCE parameters at each SCC site with treatment response at the same site, based on clinical outcome at that site at a minimum of two years. Results None of the pre-treatment DCE-MRI parameters showed significant correlations with SCC site failure (SF) (29/83 sites) or site control (SC) (54/83 sites). Post-treatment residual masses with SF (14/33) had significantly higher kep (p = 0.05), higher AUGC (p = 0.02), and lower % reduction in AUGC (p = 0.02), than residual masses with SC (19/33), with the% change in AUGC remaining significant on multivariate analysis. Conclusion Pre-treatment DCE-MRI did not predict which SCC sites would fail treatment, but post-treatment DCE-MRI showed potential for identifying residual masses that had failed treatment

Mobile Technology for Vegetable Consumption: A Randomized Controlled Pilot Study in Overweight Adults.

BACKGROUND: Mobile apps present a potentially cost-effective tool for delivering behavior change interventions at scale, but no known studies have tested the efficacy of apps as a tool to specifically increase vegetable consumption among overweight adults. OBJECTIVE: The purpose of this pilot study was to assess the initial efficacy and user acceptability of a theory-driven mobile app to increase vegetable consumption. METHODS: A total of 17 overweight adults aged 42.0 (SD 7.3) years with a body mass index (BMI) of 32.0 (SD 3.5) kg/m(2) were randomized to the use of Vegethon (a fully automated theory-driven mobile app enabling self-monitoring of vegetable consumption, goal setting, feedback, and social comparison) or a wait-listed control condition. All participants were recruited from an ongoing 12-month weight loss trial (parent trial). Researchers who performed data analysis were blinded to condition assignment. The primary outcome measure was daily vegetable consumption, assessed using an adapted version of the validated Harvard Food Frequency Questionnaire administered at baseline and 12 weeks after randomization. An analysis of covariance was used to assess differences in 12-week vegetable consumption between intervention and control conditions, controlling for baseline. App usability and satisfaction were measured via a 21-item post-intervention questionnaire. RESULTS: Using intention-to-treat analyses, all enrolled participants (intervention: 8; control: 9) were analyzed. Of the 8 participants randomized to the intervention, 5 downloaded the app and logged their vegetable consumption a mean of 0.7 (SD 0.9) times per day, 2 downloaded the app but did not use it, and 1 never downloaded it. Consumption of vegetables was significantly greater among the intervention versus control condition at the end of the 12-week pilot study (adjusted mean difference: 7.4 servings; 95% CI 1.4-13.5; P=.02). Among secondary outcomes defined a priori, there was significantly greater consumption of green leafy vegetables, cruciferous vegetables, and dark yellow vegetables (adjusted mean difference: 2.6, 1.6, and 0.8 servings; 95% CI 0.1-5.0, 0.1-3.2, and 0.3-1.4; P=.04, P=.04, and P=.004, respectively). Participants reported positive experiences with the app, including strong agreement with the statements "I have found Vegethon easy to use" and "I would recommend Vegethon to a friend" (mean 4.6 (SD 0.6) and 4.2 (SD 0.8), respectively, (on a 5-point scale). CONCLUSIONS: Vegethon demonstrated initial efficacy and user acceptability. A mobile app intervention may be useful for increasing vegetable consumption among overweight adults. The small sample size prevented precise estimates of effect sizes. Given the improved health outcomes associated with increases in vegetable consumption, these findings indicate the need for larger, longer-term evaluations of Vegethon and similar technologies among overweight adults and other suitable target groups. TRIAL REGISTRATION: ClinicalTrials.gov NCT01826591; https://clinicaltrials.gov/ct2/show/NCT01826591 (Archived by WebCite at http://www.webcitation.org/6hYDw2AOB)

IDEAS (Integrate, Design, Assess, and Share): A Framework and Toolkit of Strategies for the Development of More Effective Digital Interventions to Change Health Behavior.

Developing effective digital interventions to change health behavior has been a challenging goal for academics and industry players alike. Guiding intervention design using the best combination of approaches available is necessary if effective technologies are to be developed. Behavioral theory, design thinking, user-centered design, rigorous evaluation, and dissemination each have widely acknowledged merits in their application to digital health interventions. This paper introduces IDEAS, a step-by-step process for integrating these approaches to guide the development and evaluation of more effective digital interventions. IDEAS is comprised of 10 phases (empathize, specify, ground, ideate, prototype, gather, build, pilot, evaluate, and share), grouped into 4 overarching stages: Integrate, Design, Assess, and Share (IDEAS). Each of these phases is described and a summary of theory-based behavioral strategies that may inform intervention design is provided. The IDEAS framework strives to provide sufficient detail without being overly prescriptive so that it may be useful and readily applied by both investigators and industry partners in the development of their own mHealth, eHealth, and other digital health behavior change interventions