Suchergebnisse

Background: Inaccurate malaria results can lead to patient mismanagement, misperceptions about malaria resistance patterns and public health misinformation. All laboratories need to be able to demonstrate that their results are accurate. Establishing and maintaining a system for monitoring test accuracy is a complex, expensive and technically demanding process, which very few poor countries have been able to implement. This study described the process and assessed the feasibility of establishing a nation-wide system for improving the accuracy of malaria-related tests in peripheral laboratories in Ghana. Programme implementation: A baseline survey of all 693 laboratory staff in 205 sub-regional government and mission health laboratories in Ghana was conducted by a national network of laboratory supervisors. Survey results guided a training programme to improve test accuracy. Outcomes included changes in the quality of laboratory tests and the system was considered to be feasible if > 50% of laboratory staff in each region received training and if test accuracy could be documented. Programme indicators: 74% ( mean) of the 693 laboratory staff were assistants with no professional qualifications. There were marked differences between regions in the availability of essential resources for malaria diagnosis ( e. g. microscopes). 93% of laboratory staff received training; in six months there were increases of 11% and 7% respectively in the number of laboratories producing haemoglobin and malaria microscopy results of acceptable quality. Conclusions: It is possible to establish a system for improving and monitoring test accuracy in peripheral laboratories on a country-wide basis in a developing country using a model that could be adapted for use in other countries and for other components of health care provision.

Spatial autoregressive models are powerful tools in the analysis of data sets from diverse scientific areas of research such as econometrics, plant species richness, cancer mortality rates, image processing, analysis of the functional Magnetic Resonance Imaging (fMRI) data, and many more. An important class in the host of spatial autoregressive models is the class of spatial error models in which spatially lagged error terms are assumed. In this paper, we propose efficient shrinkage and penalty estimators for the regression coefficients of the spatial error model. We carry out asymptotic as well as simulation analyses to illustrate the gain in efficiency achieved by these new estimators. Furthermore, we apply the new methodology to housing prices data and provide a bootstrap approach to compute prediction errors of the new estimators.

Background: Judging whether a youth is at risk for suicide-related behavior (SRB) is considered an extremely challenging task. There are only few studies of helpline counselors, and little is known about their ability to accurately determine the level of risk for SRB. Aims: To examine whether helpline counselors can agree on judgments of risk for SRB, and whether their judgments are consistent with youths' actual behavior in a 6-month period following intake. Methods: 34 helpline counselors, recruited from three helplines, were studied. Information was collected on their judgments of risk for SRB for each of 45 youths over a 6-month period following initial intake. Results: Contrary to expectations, the counselors had a high rate of agreement (k = .56), and their risk judgments could be used quite successfully (80.0% correct classification) in identifying youths who later engaged in SRB. Conclusions: Unlike most other groups represented in the decision-making literature, helpline counselors agree and are accurate in their judgments of risk for SRB. Our findings suggest that it might be beneficial to apply some of the procedures used to train helpline clinicians to other types of clinicians. Further studies of helpline clinicians are suggested.

Abstract. Background: The current research into interoception distinguishes between interoceptive accuracy (IAcc), the accurate detection of internal sensations (e.g., heartbeats) as measured by performance on objective IAcc tasks, and interoceptive sensibility (IS), the subjective belief concerning one's own experience of internal sensations as measured either through self-report questionnaires or through one's confidence in the accuracy during an IAcc task. Aims: As the two measures of IS, however, are usually uncorrelated and show differential relationships to IAcc, we suggest different types of IS, a general IS and a specific IS. Further, based on a growing body of research linking IAcc and IS to physical and mental diseases, the development of interoception across the adult lifespan is of importance. Methods: Using Structural Equation Modeling the present paper investigates the relationships among IAcc assessed by a heartbeat counting task, and the two proposed dimensions of IS in 138 participants ( Mage = 42.67, SDage = 18.77). Furthermore, we examine age-related differences in IAcc, as well as in general and specific IS. Results: In terms of the relationship between the three dimensions, general and specific IS were weakly correlated and exhibited different relationships to IAcc. Further, we found different age effects on the three interoceptive dimensions. Whereas IAcc decreased with age, specific IS tend to increase with age, and general IS remained unaffected by age. Conclusion: The findings provide further empirical support for a dissociation between general and specific IS and raised important questions concerning the relation between interoceptive accuracy and the emergence of physical diseases in older age.

Testimony issued by the Government Accountability Office with an abstract that begins "Biennially, the Judicial Conference, the federal judiciary's principal policymaking body, assesses the need for additional judges. The assessment is based on a variety of factors, but begins with quantitative case-related workload measures. This testimony focuses on (1) whether the judiciary's quantitative case-related workload measures from 1993 were reasonably accurate; and (2) the reasonableness of any proposed methodologies to update the 1993 workload measures. The comments in this testimony are based on a report GAO issued in May 2003."

Testimony issued by the General Accounting Office with an abstract that begins "GAO appeared before the Subcommittee on Courts, the Internet, and Intellectual Property, House Committee on the Judiciary to discuss the results of our review and assessment of case-related workload measures for district court and courts of appeals judges. Biennially, the Judicial Conference of the United States, the federal judiciary's principal policymaking body, assesses the judiciary's needs for additional judgeships. If the Conference determines that additional judgeships are needed, it transmits a request to Congress identifying the number, type (courts of appeals, district, or bankruptcy), and location of the judgeships it is requesting. In assessing the need for additional district and appellate court judgeships, the Judicial Conference considers a variety of information, including responses to its biennial survey of individual courts, temporary increases or decreases in case filings, and other factors specific to an individual court. However, the Conference's analysis begins with the quantitative case-related workload measures it has adopted for the district courts and courts of appeals--weighted case filings and adjusted case filings, respectively. These two measures recognize, to different degrees, that the time demands on judges are largely a function of both the number and complexity of the cases on their dockets. Some types of cases may demand relatively little time and others may require many hours of work."

AbstractThis study was performed to analyze the accuracy of health‐related information on Twitter during the coronavirus disease 2019 (COVID‐19) pandemic. Authors queried Twitter on three dates for information regarding COVID‐19 and five terms (cure, emergency or emergency room, prevent or prevention, treat or treatments, vitamins or supplements) assessing the first 25 results with health‐related information. Tweets were authoritative if written by governments, hospitals, or physicians. Two physicians assessed each tweet for accuracy. Metrics were compared between accurate and inaccurate tweets usingχ2analysis and Mann–WhitneyU. A total of 25.4% of tweets were inaccurate. Accurate tweets were more likely written by Twitter authenticated authors (49.8% vs. 20.9%, 28.9% difference, 95% confidence interval [CI]: 17.7–38.2) with accurate tweet authors having more followers (19,491 vs. 7346; 3446 difference, 95% CI: 234–14,054) versus inaccurate tweet authors. Likes, retweets, tweet length, botometer scores, writing grade level, and rank order did not differ between accurate and inaccurate tweets. We found 1/4 of health‐related COVID‐19 tweets inaccurate indicating that the public should not rely on COVID‐19 health information written on Twitter. Ideally, improved government regulatory authority, public/private industry oversight, independent fact‐checking, and artificial intelligence algorithms are needed to ensure inaccurate information on Twitter is removed.