Effectiveness of acute geriatric units in the real world: The case of short-term mortality among seniors hospitalized for pneumonia

2012 ◽  
Vol 13 (1) ◽  
pp. 55-62
Author(s):  
Yew Yoong Ding ◽  
John Abisheganaden ◽  
Wai Fung Chong ◽  
Bee Hoon Heng ◽  
Tow Keang Lim
Keyword(s):  
Real World ◽  
Short Term ◽  
The Real ◽  
Short Term Mortality

Short-Term Results For Intermittent Vagal Nerve Blocking (vBloc) In The “Real-World”, Nonresearch Environment

2017 ◽  
Vol 13 (10) ◽  
pp. S195
Author(s):  
Scott Shikora ◽  
Collin Brathwaite ◽  
Frank Chae ◽  
John Dietrick ◽  
Guillermo Gomez ◽  
...  
Keyword(s):  
Real World ◽  
Vagal Nerve ◽  
Short Term ◽  
The Real ◽  
Vagal Nerve Blocking

scholarly journals You don’t have to tell a story! A registered report testing the effectiveness of narrative versus non-narrative misinformation corrections

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Ullrich K. H. Ecker ◽  
Lucy H. Butler ◽  
Anne Hamby
Keyword(s):  
Real World ◽  
Mental Model ◽  
Potential Benefit ◽  
Inferential Reasoning ◽  
Short Term ◽  
The Real ◽  
Complex Information ◽  
Influence Effect ◽  
Narrative Format ◽  
Test Delay

AbstractMisinformation often has an ongoing effect on people’s memory and inferential reasoning even after clear corrections are provided; this is known as the continued influence effect. In pursuit of more effective corrections, one factor that has not yet been investigated systematically is the narrative versus non-narrative format of the correction. Some scholars have suggested that a narrative format facilitates comprehension and retention of complex information and may serve to overcome resistance to worldview-dissonant corrections. It is, therefore, a possibility that misinformation corrections are more effective if they are presented in a narrative format versus a non-narrative format. The present study tests this possibility. We designed corrections that are either narrative or non-narrative, while minimizing differences in informativeness. We compared narrative and non-narrative corrections in three preregistered experiments (total N = 2279). Experiment 1 targeted misinformation contained in fictional event reports; Experiment 2 used false claims commonly encountered in the real world; Experiment 3 used real-world false claims that are controversial, in order to test the notion that a narrative format may facilitate corrective updating primarily when it serves to reduce resistance to correction. In all experiments, we also manipulated test delay (immediate vs. 2 days), as any potential benefit of the narrative format may only arise in the short term (if the story format aids primarily with initial comprehension and updating of the relevant mental model) or after a delay (if the story format aids primarily with later correction retrieval). In all three experiments, it was found that narrative corrections are no more effective than non-narrative corrections. Therefore, while stories and anecdotes can be powerful, there is no fundamental benefit of using a narrative format when debunking misinformation.

Transnationalism, Multilingualism, and Identity

2015 ◽  
Vol 35 ◽  
pp. 57-80 ◽  
Author(s):  
Patricia A. Duff
Keyword(s):  
Life Span ◽  
Real World ◽  
Literacy Practices ◽  
Applied Linguistics ◽  
Language And Literacy ◽  
Short Term ◽  
The Real ◽  
The People ◽  
At Home

ABSTRACTApplied linguistics is a field concerned with issues pertaining to language(s) and literacies in the real world and with the people who learn, speak, write, process, translate, test, teach, use, and lose them in myriad ways. It is also fundamentally concerned withtransnationalism, mobility, andmultilingualism—the movement across cultural, linguistic, and (often) geopolitical or regional borders and boundaries. The field is, furthermore, increasingly concerned withidentityconstruction and expression through particular language and literacy practices across the life span, at home, in diaspora settings, in short-term and long-term sojourns abroad for study or work, and in other contexts and circumstances. In this article, I discuss some recent areas in which applied linguists have investigated the intersections of language (multilingualism), identity, and transnationalism. I then present illustrative studies and some recurring themes and issues.

Choice between long- and short-term interests: Beyond self-control

1995 ◽  
Vol 18 (1) ◽  
pp. 127-128 ◽  
Author(s):  
Leonard Green ◽  
Joel Myerson
Keyword(s):  
Real World ◽  
Pattern Generation ◽  
Self Control ◽  
Pattern Perception ◽  
Common Element ◽  
Future Research ◽  
Short Term ◽  
The Real ◽  
Patterns Of Behavior ◽  
Key Issues

AbstractIn the real world, there are choices between large, delayed, punctate rewards and small, more immediate rewards as well as choices between patterns and acts. A common element in these situations is the choice between long- and short-term interests. Key issues for future research appear to be how acts are restructured into larger patterns of behavior, and whether, as Rachlin implies, pattern perception is the cause of pattern generation.

Precision of short-term chronic toxicity tests in the real world

1991 ◽  
Vol 10 (2) ◽  
pp. 143-145 ◽  
Author(s):  
Susan L. Anderson ◽  
Teresa J. Norberg-King
Keyword(s):  
Real World ◽  
Chronic Toxicity ◽  
Toxicity Tests ◽  
Short Term ◽  
The Real

scholarly journals Impact of Augmented Intelligence on Utilization of Palliative Care Services in a Real-World Oncology Setting

2021 ◽  
pp. OP.21.00179
Author(s):  
Ajeet Gajra ◽  
Marjorie E. Zettler ◽  
Kelly A. Miller ◽  
John G. Frownfelter ◽  
John Showalter ◽  
...  
Keyword(s):  
Palliative Care ◽  
Mortality Risk ◽  
Real World ◽  
Short Term ◽  
Short Term Mortality ◽  
Medium Risk ◽  
Palliative Care Services ◽  
The Mean ◽  
Oncology Practice ◽  
The Impact

PURPOSE: For patients with advanced cancer, timely referral to palliative care (PC) services can ensure that end-of-life care aligns with their preferences and goals. Overestimation of life expectancy may result in underutilization of PC services, counterproductive treatment measures, and reduced quality of life for patients. We assessed the impact of a commercially available augmented intelligence (AI) tool to predict 30-day mortality risk on PC service utilization in a real-world setting. METHODS: Patients within a large hematology-oncology practice were scored weekly between June 2018 and October 2019 with an AI tool to generate insights into short-term mortality risk. Patients identified by the tool as being at high or medium risk were assessed for a supportive care visit and further referred as appropriate. Average monthly rates of PC and hospice referrals were calculated 5 months predeployment and 17 months postdeployment of the tool in the practice. RESULTS: The mean rate of PC consults increased from 17.3 to 29.1 per 1,000 patients per month (PPM) pre- and postdeployment, whereas the mean rate of hospice referrals increased from 0.2 to 1.6 per 1,000 PPM. Eliminating the first 6 months following deployment to account for user learning curve, the mean rate of PC consults nearly doubled over baseline to 33.0 and hospice referrals increased 12-fold to 2.4 PPM. CONCLUSION: Deployment of an AI tool at a hematology-oncology practice was found to be feasible for identifying patients at high or medium risk for short-term mortality. Insights generated by the tool drove clinical practice changes, resulting in significant increases in PC and hospice referrals.

scholarly journals PLASTIC: Prioritize Long and Short-term Information in Top-n Recommendation using Adversarial Training

2018 ◽  
Author(s):  
Wei Zhao ◽  
Benyou Wang ◽  
Jianbo Ye ◽  
Yongqiang Gao ◽  
Min Yang ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Recommender Systems ◽  
Real World ◽  
Short Term ◽  
Plastic Model ◽  
The Real ◽  
Adversarial Training ◽  
Real World Datasets

Recommender systems provide users with ranked lists of items based on individual's preferences and constraints. Two types of models are commonly used to generate ranking results: long-term models and session-based models. While long-term models represent the interactions between users and items that are supposed to change slowly across time, session-based models encode the information of users' interests and changing dynamics of items' attributes in short terms. In this paper, we propose a PLASTIC model, Prioritizing Long And Short-Term Information in top-n reCommendation using adversarial training. In the adversarial process, we train a generator as an agent of reinforcement learning which recommends the next item to a user sequentially. We also train a discriminator which attempts to distinguish the generated list of items from the real list recorded. Extensive experiments show that our model exhibits significantly better performances on two widely used real-world datasets.

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