Attitude theory and measurement in implementation science: a secondary review of empirical studies and opportunities for advancement

Background Implementation science studies often express interest in “attitudes,” a term borrowed from psychology. In psychology, attitude research has an established methodological and theoretical base, which we briefly summarize here. We then review implementation studies designed to measure attitudes and compare their definitions and methods with those from psychology. Methods A recent review identified 46 studies empirically examining factors associated with implementation. For each of these studies, we evaluated whether authors included attitudes as a construct of interest, and if so, whether and how the construct was defined, measured, and analyzed. Results Most of the articles (29/46 [63%]) mention attitudes as an implementation factor. Six articles include a definition of the construct. Nineteen studies were designed to measure attitudes but lacked clarity in describing how attitudes were measured. Those that explained their measurement approach used methods that differed from one another and from validated methods in social psychology. Few articles described associated analyses or provided results specific to attitudes. Despite the lack of specificity regarding relevant measurement, analysis, and results, the articles often included causal conclusions about the role of attitudes. Conclusions Attitudes may be an important construct to implementation scientists, but studies to date are ambiguous in their definitions of attitudes and inconsistent in the methods used to measure and analyze attitudes. We discuss how implementation studies can apply psychology’s standardized definitions, validated measurement approaches, and causal models that include attitudes. This application of attitude theory and methods could offer implementation research valuable scientific opportunities.

Providing enhanced security in IoT based smart weather system

Weather reporting system consist multiple devices which are playing dynamic role in producing dynamic environmental parameters such as temperature, humidity, and air pollution. It was a tedious task to bring all the devices together and make them interleaving to produce relevant measurement. Recent trends have proven that the IoT has brought all the devices and peripherals in one place to make more flexible and smart measurement. In the traditional weather monitoring system measurement method is not real time, not continuous and also tedious job to take continuous measurement. But, the IoT has completely changed the measurement scenario and improved the consistency of the measurement. In the present work the environmental parameters such rainfall, temperature, humidity, and density of carbon dioxide in the air are measured with sensors. The Arduino Uno card gathers all information from the devices which are associated with its port pins. The information is sent to cloud server for record and future retrieving. At the same time the data security in cloud been assured with encryption and decryption data while retrieving the information from cloud. This enhances the security, ease of accessing the cloud data from mobile applications, provides wise predictions and minimizes the communication overhead.

Rapid, continuous radiocarbon analysis of carbonate archives using laser ablation

<p>While high-precision radiocarbon (<sup>14</sup>C) measurements of carbonaceous samples using Accelerator Mass Spectrometry (AMS) have become routine, achieving a continuous radiocarbon record for carbonate archives (e.g. speleothems, corals) still requires labor-intensive and time-consuming sample preparation. By feeding laser ablation (LA) generated CO<sub>2</sub>/CO online into a gas source AMS, however, these archives can be sampled continuously and with minimal preparation efforts.</p><p>The LA-AMS setup installed in 2013 at ETH Zurich [1] has recently been improved in order to achieve higher signal intensities and consequently higher measurement precision as well as simpler instrumental maintenance. By redesigning the sample cell and reducing the optical path length of the laser, the fluence on the sample could be increased from previously 1-2 J cm<sup>-1</sup> to now 8-23 J cm<sup>-1</sup>, leading to more efficient generation of gaseous carbon from CaCO<sub>3</sub>. The laser spot size was reduced from 110 μm x 680 μm to 75 μm x 140 μm, improving the overall spatial resolution of the setup. The background level of the method has been determined to have a F<sup>14</sup>C of 0.009 ± 0.002 and reaches a precision of less than 1% for modern samples.</p><p>To fully exploit the advantages of this unique technique, a LA-AMS specific data analysis software to disentangle [2] the quasi-continuous data stream is being developed. Features implemented include correlation of data with sampling location and plotting of all relevant measurement parameters as a function of sampling location (F<sup>14</sup>C, </p>

Accounting Standards Compliance and Comparability of Measurement Practices: The Case of Malaysian General Insurers

This study determines the extent of compliance level of Malaysian general insurers towards the requirements stipulated in MAS 3 (Malaysian Accounting Standard No.3: Accounting for General Insurance Business) and GPI (Guidelines on Accounting for Insurance Business, JPI/GPI 3), and subsequently determines the comparability of relevant measurement practices outlined in the Standards and Guidelines. Data from the annual reports of 35 insurers were gathered and 18 measurement practices were examined in the study. The Herfindahl index (known as H-index) was employed in measuring the comparability of measurement practices. Except for the accrual of dividends, results suggest that the compliance level of companies towards most of the other items were high. Nevertheless, results on comparability of measurement practices were rather mixed, having H-indices ranging from a low score of 0.47 to a perfect score of 1.

Using Gameplay and Players Data to Recommend Strategies to Reduce Cybersickness

Virtual Reality (VR) is an upcoming trend in games and entertainment applications as the use of head-mounted displays becomes accessible for the mass market. These systems aim to provide immersive experiences, but they still do not provide a completely seamless experience, mostly due to sickness symptoms that can be experienced by the players. Cybersickness (CS) is one of the most critical problems that make the game industry fearful for higher investments. In this work, we made a critical study on the theories and causes of CS in virtual environments. We unified in a paper most of the leading hardware and software proposals to identify, quantify and minimize the main sickness problems. We also provide clarification about the most relevant measurement tools used to quantify the level of sickness for one or more players through specific questionnaires. We also developed a demo plugin for a commercial game engine to collect relevant data in a VR game to use as a database to future research approaches to enhance user experience in head-mounted displays.

JOB INSECURITY – CONCEPTUALIZATION OF THE NOTION AND METHODS OF MEASUREMENT

Increasing globalization and transformation of the modern labour market have changed the traditional employment model, introducing insecurity associated with taking up and maintaining work. Job insecurity, understood as a “perceived threat of job loss and concerns related to this threat” is an unavoidable and widespread phenomenon in today’s professional world. Job insecurity has been of great interest to researchers since the 1980s. Job insecurity is one of the emerging research directions in economic theory. The aim of the article is to try and provide an interdisciplinary conceptualization of job insecurity. The article presents different ways of understanding job insecurity and discusses the methods of its measurement. A systematic review of world literature was conducted to identify and assess the current state of knowledge in this area. The analysis of scholarly publications on job insecurity confirms the existence of a relatively small number of scientific and research studies in this field in Poland. Therefore, a cognitive gap is identified which invites a more indepth investigation of job uncertainty, in particular its integrated review and conceptual framework as well as designing the relevant measurement tool. The article is analytical and conceptual, and can be a contribution to the discussion on job insecurity and a starting point for empirical research in economic sciences.

Does Fair Value Accounting Provide More Useful Financial Statements than Current GAAP for Banks?

ABSTRACT Standard setters contend that fair value accounting yields the most relevant measurement for financial instruments. We examine this claim by comparing the value relevance of banks' financial statements under fair value accounting with that under current GAAP, which is largely based on historical costs. We find that the combined value relevance of book value of equity and income under fair value is less than that under GAAP. We also find that fair value income is less value-relevant than GAAP income because of the inclusion of transitory unrealized gains and losses in fair value income. More surprisingly, we find that book value of equity under fair value is not more value-relevant than under GAAP, due both to divergence between exit value and value-in-use and to measurement error in fair value estimates. Overall, our results suggest that financial statements under fair value accounting provide less relevant information for bank valuation than financial statements under current GAAP.

Agreement between Perometry and Sequential Arm Circumference Measurements in Objective Determination of Arm Volume

Background Limb circumference measurements (CM) and perometry are the preferred methods for objectively measuring arm volume in lymphedema surgery research. Understanding the measurement bias involved in these measuring systems is important to properly interpret and compare studies and their results. Methods Arm volumes from 91 patients were measured using sequential girths and the truncated cone formula (CM) and with the use of an automated perometer (perometry). The absolute volume of the largest arm (V), the volume difference between the arms (VD), and the relative difference between them (percentage of excess volume [PEV]) were calculated with both methods. The agreement between methods was assessed by the Pearson's correlation test and the Bland–Altman's method. Results Correlations were strong for V (r = 0.99), VD (r = 88), and PEV (r = 0.86). Volumes measured by perometry were, on average, 10.6 mL smaller than volumes calculated from CM, while their limits of agreement (LOA) ranged from −202 to 181 mL. The LOA represents the range we could expect the arm volumes measured with the two methods to differ by chance alone, 95% of the times. For VD, LOA was −101 to 141 mL, with a mean difference of 19.9 mL, while PEV had a mean difference of 0.9%, with LOA ranging from −5 to 6.8%. Conclusion There is considerable measurement error between arm volume estimated by perometry and by CM. Volumes calculated with these methods should be compared with caution. Furthermore, we observed an increasingly relevant measurement bias in outcomes that are mathematically derived from arm volumes.

Un viaje alrededor de alfa y omega para estimar la fiabilidad de consistencia interna

<p>Based on recent psychometric developments, this paper presents a conceptual and practical guide for estimating internal consistency reliability of measures obtained as item sum or mean. The internal consistency reliability coefficient is presented as a by-product of the measurement model underlying the item responses. A three-step procedure is proposed for its estimation, including descriptive data analysis, test of relevant measurement models, and computation of internal consistency coefficient and its confidence interval. Provided formulas include: (a) Cronbach’s alpha and omega coefficients for unidimensional measures with quantitative item response scales, (b) coefficients ordinal omega, ordinal alpha and nonlinear reliability for unidimensional measures with dichotomic and ordinal items, (c) coefficients omega and omega hierarchical for essentially unidimensional scales presenting method effects. The procedure is generalized to weighted sum measures, multidimensional scales, complex designs with multilevel and/or missing data and to scale development. Four illustrative numerical examples are fully explained and the data and the R syntax are provided.</p>