A Critical Review of Adversity Quotient Instruments: Using the Cosmin Checklist

Adversity intelligence and adversity quotient is the critical ability and robust predictor of a person’s success. However, no consensus and generalized instrument have been established. Hence, the study aims to assess the methodological quality and measurement features of the existing tools for adversity intelligence by identifying and evaluating the instruments following the consensus-based standards for selecting health measurement instruments (COSMIN) checklist. From 255 research studies, six tools were eligible by a systematic review of online databases and books. For three or more of the nine COSMIN criteria, only two of the instruments had strong to moderate levels of evidence. Meanwhile, none of the instruments met any of the criteria. These results demonstrate that no single instrument outperforms all others in all circumstances. Tools that will be refined in the future should capture the development, methodology, and quality during the development of the instrument and achieve a high measurement quality and a generalized tool of measuring adversity intelligence.

Measurement Quality Appraisal Instrument for Evaluation of Walkability Assessment Tools Based on Walking Needs

Walking is a sustainable commute mode, and walkability is considered an essential sign of sustainable mobility. To date, many walkability assessment tools have been developed to assess the walkability conditions across the world. However, there is a paucity of comprehensive methods to assess current walkability tools based on walking needs and ensure all walking requirements are included. Thus, researchers and experts are unable to select the most comprehensive tool systematically. The present study attempts to develop a system to evaluate the quality of the existing tools. The instrument focuses on factors related to walking needs frequently observed in all types of walkability assessment tools. Hence, a pilot measurement quality appraisal instrument (MQAI) is developed and tested by a research team with planning and public health backgrounds. The final MQAI is tested by suitable reliability, criterion, and content validity tests. Most appraisal scales display moderate to high reliability for both audits and questionnaires. The MQAI appears as ready for use in several applications, including meta-analyses and systematic reviews. Additionally, the MQAI can be used by practitioners and planners to identify the most comprehensive and efficient assessment tools based on their needs.

Quantifying Metrology’s Real Value

Where practicable, the total end-to-end test-and-calibration program cost would serve as the ultimate measurement quality metric (MQM). Total cost includes both the capitalization and ongoing costs that support product quality (sometimes called cost of quality) and the consequence costs (sometimes called cost of poor quality) that result from imperfect measurement and products. End-to-end means capturing costs from the entire traceability chain: from measurement standards to end products. Minimizing this MQM, total end-toend cost (TETEC), equates to optimizing measurement quality assurance (MQA). Lacking easily available measurement and performance data automatically fed to modeling software, organizations have found cost metrics unimaginable or impracticable, so their measurement programs instead target more easily computed MQMs, such as false-accept risk or simpler proxies thereof, setting minimum, but sub-optimal, quality levels. However, modern computing systems and software, such as laboratory management systems with testpoint- level traceability, rapidly approach the point at which the TETEC MQM will become practicable. Preparing for this eventuality, the NCSLI 173 Metrology Practices Committee has developed models that relate costs to measurement program information such as product specifications, test and measurement uncertainties, calibration intervals and reliability targets. Applications include optimizing overall program MQA, but also estimating the value of metrology and return on equipment investments, selecting instruments, designing test and calibration processes, designing products. This paper applies the cost models to case studies and examples to illustrate some applications.

Sandia’s Uncertainty Calculator: A Case Study in the Graded Approach to Software Quality Assurance

Where practicable, the total end-to-end test-and-calibration program cost would serve as the ultimate measurement quality metric (MQM). Total cost includes both the capitalization and ongoing costs that support product quality (sometimes called cost of quality) and the consequence costs (sometimes called cost of poor quality) that result from imperfect measurement and products. End-to-end means capturing costs from the entire traceability chain: from measurement standards to end products. Minimizing this MQM, total end-toend cost (TETEC), equates to optimizing measurement quality assurance (MQA). Lacking easily available measurement and performance data automatically fed to modeling software, organizations have found cost metrics unimaginable or impracticable, so their measurement programs instead target more easily computed MQMs, such as false-accept risk or simpler proxies thereof, setting minimum, but sub-optimal, quality levels. However, modern computing systems and software, such as laboratory management systems with testpoint- level traceability, rapidly approach the point at which the TETEC MQM will become practicable. Preparing for this eventuality, the NCSLI 173 Metrology Practices Committee has developed models that relate costs to measurement program information such as product specifications, test and measurement uncertainties, calibration intervals and reliability targets. Applications include optimizing overall program MQA, but also estimating the value of metrology and return on equipment investments, selecting instruments, designing test and calibration processes, designing products. This paper applies the cost models to case studies and examples to illustrate some applications.

Effect of birthweight measurement quality improvement on low birthweight prevalence in rural Ethiopia

Background Low birthweight (LBW) (< 2500 g) is a significant determinant of infant morbidity and mortality worldwide. In low-income settings, the quality of birthweight data suffers from measurement and recording errors, inconsistent data reporting systems, and missing data from non-facility births. This paper describes birthweight data quality and the prevalence of LBW before and after implementation of a birthweight quality improvement (QI) initiative in Amhara region, Ethiopia. Methods A comparative pre-post study was performed in selected rural health facilities located in West Gojjam and South Gondar zones. At baseline, a retrospective review of delivery records from February to May 2018 was performed in 14 health centers to collect birthweight data. A birthweight QI initiative was introduced in August 2019, which included provision of high-quality digital infant weight scales (precision 5 g), routine calibration, training in birth weighing and data recording, and routine field supervision. After the QI implementation, birthweight data were prospectively collected from late August to early September 2019, and December 2019 to June 2020. Data quality, as measured by heaping (weights at exact multiples of 500 g) and rounding to the nearest 100 g, and the prevalence of LBW were calculated before and after QI implementation. Results We retrospectively reviewed 1383 delivery records before the QI implementation and prospectively measured 1371 newborn weights after QI implementation. Heaping was most frequently observed at 3000 g and declined from 26% pre-initiative to 6.7% post-initiative. Heaping at 2500 g decreased from 5.4% pre-QI to 2.2% post-QI. The percentage of rounding to the nearest 100 g was reduced from 100% pre-initiative to 36.5% post-initiative. Before the QI initiative, the prevalence of recognized LBW was 2.2% (95% confidence interval [CI]: 1.5–3.1) and after the QI initiative increased to 11.7% (95% CI: 10.1–13.5). Conclusions A QI intervention can improve the quality of birthweight measurements, and data measurement quality may substantially affect estimates of LBW prevalence.

Measuring satisfaction with democracy: how good are different scales across countries and languages?

The Satisfaction With Democracy (SWD) indicator is very often used in social sciences’ research. However, while there is debate about which concept it measures, the discussion about the size of its measurement errors (how well it measures the underlying concept ‘satisfaction with the way democracy works’) is scarce. Nonetheless, measurement errors can affect the results and threaten comparisons across studies, countries and languages. Thus, in this paper, we estimated the measurement quality (complement of measurement errors) of the SWD indicator for 7 response scales across 38 country-language groups, using three multitrait-multimethod experiments from the European Social Survey. Results show that measurement errors explain from 16% (11-point scale) to 54% (4-point scale) of the variance in the observed responses. Additionally, we provide insights to improve questionnaire design and evaluate the indicator’s comparability across scales, countries and languages.

GNSS AND PHOTOGRAMMETRY BY THE SAME TOOL: A FIRST EVALUATION OF THE LEICA GS18I RECEIVER

Leica Geosystems recently introduced a multi-constellation GNSS sensor named GS18i. It is capable to perform tilt compensation and has an integrated photogrammetric camera, allowing the users to measure inaccessible features: this is called visual positioning. The Laboratory of Geomatics, at the University of Pavia – Italy, performed a first evaluation of the rover. Five accessible points were measured repeatedly with the pole having different tilt angles; measurements’ total number was 2077. After moderate blunder detection, RMSE values are 12, 10 and 18 mm, for the East, North and height components.Measurement quality is substantially independent from the pole’s tilt angle. Moreover, ten points belonging to a building’s façade were repeatedly measured by photogrammetry, through the integrated camera, from distances in the range between 4 and 12 meters. In total, 1436 measurements were acquired. After blunder detection, RMSE values are 45, 25 and 66 mm, for the x, y and z components of a local cartesian system. Measurement quality mildly depend on the object-camera distance. Despite a good overall accuracy, results show some surprising aspects: the high ratio between the planimetric component x and y, the counterintuitive behaviour of the y dispersion, which decreases when the distance increases. While the present paper aims at simply being a first evaluation of the rover, next activities will deal with rigorous and controlled photogrammetric processing of the images and will also include simulations, in order to ascertain the role played by the various error sources involved.