Evaluation of the micro-carburetor

A prototype sonic, variable-venturi automotive carburetor was evaluated for its effects on vehicle performance, fuel economy, and exhaust emissions. A 350 CID Chevrolet Impala vehicle was tested on a chassis dynamometer over the 1975 Federal Test Procedure, urban driving cycle. The Micro-carburetor was tested and compared with stock and modified-stock engine configurations. Subsequently, the test vehicle's performance characteristics were examined with the stock carburetor and again with the Micro-carburetor in a series of on-road driveability tests. The test engine was then removed from the vehicle and installed on an engine dynamometer. Engine tests were conducted to compare the fuel economy, thermal efficiency, and cylinder-to-cylinder mixture distribution of the Micro-carburetor to that of the stock configuration. Test results show increases in thermal efficiency and improvements in fuel economy at all test conditions. Improve fuel/air mixture preparation is implied from the information presented. Further improvements in fuel economy and exhaust emissions are possible through a detailed recalibration of the Micro-carburetor

The value of migration information for conservation prioritization of sea turtles in the Mediterranean

Aim: Conservation plans often struggle to account for connectivity in spatial prioritization approaches for the protection of migratory species. Protection of such species is challenging because their movements may be uncertain and variable, span vast distances, cross international borders and traverse land and sea habitats. Often we are faced with small samples of information from various sources and the collection of additional data can be costly and time-consuming. Therefore it is important to evaluate what degree of spatial information provides sufficient results for directing management actions. Here we develop and evaluate an approach that incorporates habitat and movement information to advance the conservation of migratory species. We test our approach using information on threatened loggerhead sea turtles (Caretta caretta) in the Mediterranean. Location: The Mediterranean Sea. Methods: We use Marxan, a spatially explicit decision support tool, to select priority conservation areas. Four approaches with increasing amounts of information about the loggerhead sea turtle are compared, ranging from (1) the broad distribution, (2) multiple habitat types that represent foraging, nesting and inter-nesting habitats, (3) mark-recapture movement information to (4) telemetry-derived migration tracks. Results: We find that spatial priorities for sea turtle conservation are sensitive to the information used in the prioritization process. Setting conservation targets for migration tracks altered the location of conservation priorities, indicating that conservation plans designed without such data would miss important sea turtle habitat. We discover that even a small number of tracks make a significant contribution to a spatial conservation plan if those tracks are substantially different. Main conclusions: This study presents a novel approach to improving spatial prioritization for conserving migratory species. We propose that future telemetry studies tailor their efforts towards conservation prioritization needs, meaning that spatially dispersed samples rather than just large numbers should be obtained. This work highlights the valuable information that telemetry research contributes to the conservation of migratory species

Comparison of a Collective Intelligence Tailored Messaging System on Smoking Cessation Between African American and White People Who Smoke: Quasi-Experimental Design

BACKGROUND: The Patient Experience Recommender System for Persuasive Communication Tailoring (PERSPeCT) is a machine learning recommender system with a database of messages to motivate smoking cessation. PERSPeCT uses the collective intelligence of users (ie, preferences and feedback) and demographic and smoking profiles to select motivating messages. PERSPeCT may be more beneficial for tailoring content to minority groups influenced by complex, personally relevant factors. OBJECTIVE: The objective of this study was to describe and evaluate the use of PERSPeCT in African American people who smoke compared with white people who smoke. METHODS: Using a quasi-experimental design, we compared African American people who smoke with a historical cohort of white people who smoke, who both received up to 30 emailed tailored messages over 65 days. People who smoke rated the daily message in terms of perceived influence on quitting smoking for 30 days. Our primary analysis compared daily message ratings between the two groups using a t test. We used a logistic model to compare 30-day cessation between the two groups and adjusted for covariates. RESULTS: The study included 119 people who smoke (African Americans, 55/119; whites, 64/119). At baseline, African American people who smoke were significantly more likely to report allowing smoking in the home (P=.002); all other characteristics were not significantly different between groups. Daily mean ratings were higher for African American than white people who smoke on 26 of the 30 days (P \u3c .001). Odds of quitting as measured by 30-day cessation were significantly higher for African Americans (odds ratio 2.3, 95% CI 1.04-5.53; P=.03) and did not change after adjusting for allowing smoking at home. CONCLUSIONS: Our study highlighted the potential of using a recommender system to personalize for African American people who smoke. TRIAL REGISTRATION: ClinicalTrials.gov NCT02200432; https://clinicaltrials.gov/ct2/show/NCT02200432. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/jmir.6465. Kathleen M Mazor, Thomas K Houston, Rajani S Sadasivam. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 27.04.2020

Dissemination of Evidence-based Atypical Antipsychotic Information to Nursing Homes

Background: Accumulating evidence demonstrates minimal benefit and increased risk of off-label use of atypical antipsychotic medications for dementia-related behaviors. Optimal strategy for disseminating evidence-based guides to nursing home (NH) stakeholders is unclear. Our objective is to describe the impact of differing dissemination efforts in Connecticut NHs. Methods: Forty-three Connecticut NHs were randomized to one of 3 arms receiving incrementally intensive dissemination strategies of the Agency for Healthcare Research and Quality Comparative Effectiveness Review Summary Guide on the off-label use of atypical antipsychotic drugs, which was included in a toolkit informed by a needs assessment of NHs. All NHs received the paper-based toolkit and notifications regarding the online toolkit. Additionally, Arm 2 received individualized quarterly audit and feedback reports with atypical antipsychotic prescribing rates; Arm 3 received in-person educational visits and audit and feedback reports. Toolkit reach was assessed using interviews with NH leadership and staff. Online toolkit use was assessed using Google analytics. Results: Eighty leaders and 222 direct care staff were interviewed. Leadership and direct care staff in Arm 3 NHs were more likely to be familiar with the toolkit that those in Arm 1 (p=0.008) and Arm 2 (p Conclusions: Intensive dissemination, using multi-pronged approach including academic detailing and direct care staff trainings, appeared to be associated with higher familiarity with paper-based toolkit, but not Internet-based use of the toolkit in the NH setting

Using a Targeted OSCE Station to Measure Unprofessional Behavior

Standardized patients are widely used in medical education but their use to assess professionalism is limited. With grant support from the Edward J. Stemmler, MD Medical Education Research Fund (“Stemmler Fund”) of the National Board of Medical Examiners (NBME), the usefulness of standardized patients (SPs) in the assessment of professional behavior was investigated. A targeted professionalism OSCE station featuring a values conflict was written. A professionalism instrument was developed and subsequently revised during the course of the study, with the final version containing various components of American Board of Internal Medicine (ABIM) core set of eight professionalism attributes and several other scales in recent medical research. Presented at the Ottawa Conference, 2006

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study

BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians\u27 (PCPs\u27) opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs\u27 InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients\u27 posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs\u27 follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based CTHC with empirical recommender systems could be evaluated as the next frontier for CTHC. OBJECTIVE: The objective of our study was to uncover barriers and challenges to using recommender systems in health promotion. METHODS: We conducted a focused literature review, interviewed subject experts (n=8), and synthesized the results. RESULTS: We describe (1) limitations of current CTHC systems, (2) advantages of incorporating recommender systems to move CTHC forward, and (3) challenges to incorporating recommender systems into CTHC. Based on the evidence presented, we propose a future research agenda for CTHC systems. CONCLUSIONS: We promote discussion of ways to move CTHC into the 21st century by incorporation of recommender systems

Health Information Brokers in the General Population: An Analysis of the Health Information National Trends Survey 2013-2014

BACKGROUND: Health information exchanged between friends or family members can influence decision making, both for routine health questions and for serious health issues. A health information broker is a person to whom friends and family turn for advice or information on health-related topics. Characteristics and online behaviors of health information brokers have not previously been studied in a national population. OBJECTIVE: The objective of this study was to examine sociodemographic characteristics, health information seeking behaviors, and other online behaviors among health information brokers. METHODS: Data from the Health Information National Trends Survey (2013-2014; n=3142) were used to compare brokers with nonbrokers. Modified Poisson regression was used to examine the relationship between broker status and sociodemographics and online information seeking. RESULTS: Over half (54.8%) of the respondents were consulted by family or friends for advice or information on health topics (ie, they acted as health information brokers). Brokers represented 54.1% of respondents earning \u3c $20,000 yearly and 56.5% of respondents born outside the United States. Women were more likely to be brokers (PR 1.34, 95% CI 1.23-1.47) as were those with education past high school (PR 1.42, CI 1.22-1.65). People aged \u3e /=75 were less likely to be brokers as compared to respondents aged 35-49 (PR 0.81, CI 0.67-0.99). Brokers used the Internet more frequently for a variety of online behaviors such as seeking health information, creating and sharing online content, and downloading health information onto a mobile device; and also reported greater confidence in obtaining health information online. CONCLUSIONS: More than 50% of adults who responded to this national survey, including those with low income and those born abroad, were providing health information or advice to friends and family. These individuals may prove to be effective targets for initiatives supporting patient engagement and disease management, and may also be well-positioned within their respective social networks to propagate health messages