Data Collection Methodology Research Articles

Status of Smoking Research in Jordan: Scoping Review and Evidence Synthesis

Background Jordan has one of the highest smoking rates in the world. Despite this, there is a limited understanding of the scope and nature of smoking research in Jordan. In this scoping review, we assessed the status of research on smoking in Jordan, identifying research gaps and opportunities for future studies, and informing the development of evidence-based interventions to reduce smoking prevalence and related health harms in the country. Methods We searched Scopus database to identify papers covering various aspects of smoking research in Jordan, including nicotine, smoke, cigarette, tobacco, and waterpipe. We assessed several outcomes, including sample characteristics size, data characteristics included data type (quantitative, qualitative), data collection methodology (survey, clinical measurements) and data collection sites. Results From 410 studies screened, we included 125 studies. We classified included studies according to the main topics covered in the articles, where 32 studies assessed the clinical impact of smoking, 24 studies assessed aspects of smoking cessation, 19 articles included the perception and knowledge of smoking, 19 studied the prevalence of different types of smoking in different age population, 16 articles studied the factors affecting smoking, 9 studied the relation with oral health, diseases, and cancer, 6 of them handled different aspects of smoking and smoking research tools and training of healthcare workers. Conclusions This scoping review provided valuable insights into the various aspects of smoking research among Jordanians and highlighted gaps where research is needed. The results can be used to inform policies and programs on areas of needed evidence.

Increasing disclosure of school-related gender-based violence: lessons from a systematic review of data collection methods and existing survey research

BackgroundSchool-related gender-based violence (SRGBV) includes sexual, physical or psychological violence occurring in and around schools often perpetrated by teachers or peers. In this review, we focus on studies comparing how data collection methodologies affect children’s disclosures of SRGBV.MethodsWe conducted a systematic review, searching nine databases for studies from high, middle and low-income countries using search terms related to violence, disclosure and data collection methodology. Records were initially screened by abstract and then full-texts were retrieved and data from eligible reports extracted. In this paper, we draw on results from this larger systematic review highlighting studies conducted with children which either collected data in schools or asked about violence in schools. We also describe methods compared and results of studies that were not conducted in schools, but that included children and young people. Finally, we describe how multi-country nationally representative surveys conducted in at least one low and middle-income country measure children’s experiences of SRGBV.ResultsWe screened 28,780 records, of which fourteen are included in this article. Only four studies compared data collection methodologies in schools or about violence in schools. These showed a 0 to more than 500-percent variation in the prevalence of violence measured using different data collection methodologies. An additional ten studies which were not conducted in schools, examined disclosure of violence in children and young people that was not specifically school-related. We assessed five multi-country national surveys that measured SRGBV. This limited evidence suggests that methods allowing increased anonymity (e.g. audio computer assisted self-interview, online surveys) may result in higher disclosure of violence, including SRGBV, than face-to-face interviewing. No studies included reported on safety, experiences of young people, or the costs of different methods. Multi-country national surveys used self-completion methods if completed in schools or face-to-face interviewing if completed in households, to measure SRGBV.ConclusionEvidence on the impact of data collection method on SRGBV disclosure is limited, however current prevalence of SRGBV in international surveys used to monitor SDG progress may be underestimated due to data collection methods used. Further research on SRGBV should aim to test the effects of data collection methodology on the disclosure of violence. Efforts to improve the measurement of SRGBV is central to understanding the epidemiology, monitoring changes, and developing school and community-based programs as well as policies to prevent and respond to SRGBV.

IADC Code Upgrade: Data Collection and Workflow Required to Conduct Bit and BHA Forensics to Create Effective Changes in Practices or Design

Summary This paper introduces a forensic workflow that can be used to link drill-bit and bottomhole assembly (BHA) damage to drilling dysfunction. This paper will also discuss the data that should be collected and how it should be processed to enable operational practices and engineering design changes to address these issues. There is a vast amount of data collected in all drilling operations that can be used to improve performance if utilized within an effective forensic workflow. Several drilling forensic case studies were developed and critically reviewed by subject matter experts from across the industry. From the causal analysis for each case study, an assessment was performed on what information was (1) available, (2) required to diagnose the cause, and (3) not available but would have been preferred. The way the team communicated and acted on the data was also documented. By combining the learnings from these case studies, it was observed that a guided approach can improve data collection and lead to a more consistent, accurate, timely, and causal analysis with appropriate remedial actions. The process discussed within has been refined to support data collection for forensic analysis and provides a reference for field- and office-based drilling professionals. These practical guidelines have been developed to offer a foundation for a drilling forensic data collection methodology as well as training for the industry—they have been created such that they can grow organically and will form part of the International Association of Drilling Contactors (IADC) Bit Dull Grading Recommended Practice to support the IADC dull grade manual. In the future, these can be used for developing subsequent industry publications. The work described in this paper is part of a joint IADC/Society of Petroleum Engineers industry effort to revise the IADC dull grade manual.

A concept for application of integrated digital technologies to enhance future smart agricultural systems

Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems.

Intensive assessment of executive functions derived from performance in cognitive training games

Traditional neuropsychological tests accurately describe the current cognitive state but fall short to characterize cognitive change over multiple short time periods. We present an innovative approach to remote monitoring of executive functions on a monthly basis, which leverages the performance indicators from self-administered computerized cognitive training games (NUP-EXE). We evaluated the measurement properties of NUP-EXE in N= 56 individuals (59% women, 60-80 years) at increased risk of Alzheimer's disease (APOE-ϵ4 carriers with subjective cognitive decline) who completed a 12-month multimodal intervention for preventing cognitive decline. NUP-EXE presented good psychometric properties and greater sensitivity to change than traditional tests. Improvements in NUP-EXE correlated with improvements in functionality and were affected by participants' age and gender. This novel data collection methodology is expected to allow a more accurate characterization of an individual's response to a cognitive decline preventive intervention and to inform development of outcome measures for a new generation of intervention trials.

Workforce training in family therapy and systemic practices: An evaluation framework and case study

AbstractInternationally, while the interdisciplinary field of family therapy and systemic practices is well established and evidence for therapeutic impact is advanced, evaluation of training and measurement of its impact lags behind. This paper addresses this gap, utilising a single case study at the Bouverie Centre, the largest family therapy and workforce development service in Australia. We describe (a) the scope of workforce training and implementation at the Centre, (b) the development of our training research and evaluation framework, and (c) standardised data collection methodology, including a pre‐post training reflective survey. Collectively, this work comprises our current evaluation framework through which we will subsequently examine training impact. Future research and practice recommendations are offered to address challenges to workforce training evaluation and progress efficacy of family therapy training.

PERAN GURU PAI DALAM PEMBINAAN MENTAL SPIRITUAL SISWA DI MTs NUSANTARA SUMBERTAMAN PROBOLINGGO

Education is a person's conscious effort to seek knowledge and experience that initially did not know to know. Teachers as the main actors in the implementation of education have a very important role in achieving educational goals. Spiritual mental development of students is very important in order to fortify students so that they are not easily affected by negative things. PAI teachers play an important role in developing students' mental and spiritual development. The purpose of this study: to determine the role of PAI teachers in fostering the mental and spiritual development of students at MTs Nusantara Sumbertaman Probolinggo. This study used descriptive qualitative data collection methodology interviews, observations and documents. The data source used is primary by interviewing school principals, PAI teachers, and student guardians. The results of this study indicate that the role of PAI teachers in mental-spiritual development is very important for students at MTs Nusantara. The forms of mental and spiritual development of students at MTs Nusantara are discipline, giving directions about science, teaching students to care about the environment and getting used to praying in congregation.

Software Methodology for Data Control and Collection for Autonomous Monitoring Systems with a Large Amount of Generated Information on the Example of Software for a Hydrological Radiolocation System

Introduction . The current data monitoring and collection systems produce a growing amount of generated information. Such factors, as the increasing sampling rate of ADCs and the increasing speed of systems for primary processing, receiving, and transmitting information, etc., make the systems operate almost at the bandwidth limit of data transmission interfaces. In some applications, such a flow is redundant and can be optimized through the use of various algorithms for the primary processing of information. However, in some applications, reducing the data flow is impossible, since the received information is processed with a delay. Therefore, the development of a software methodology for controlling and collecting data in the system of automatic monitoring of the sea surface by a hydrological radiolocation system seems a relevant research task. Aim . To synthesize a methodology and to develop software for controlling the information system of radar monitoring of the sea surface. Materials and methods . System approach, software architectural and algorithmic design, software quality management methods, system analysis, Qt framework, C++ programming language. Results . A working methodology for designing software for controlling information and measurement technologies with a large amount of generated data was obtained. The effectiveness of the methodology and software quality were confirmed by control tests. A 3-month autonomous testing of the stability and reliability of the system was carried out. Detection of data loss in the system comprised less than 0.002 %, thus not exceeding the specified critical level of 0.5 %. Conclusion . The developed methodology can be used in designing software for controlling information and measuring systems generating a large amount of data. The approaches used to build a multithread software architecture with asynchronous data flow control has shown their high efficiency.

LibCity-Dataset: a standardized and comprehensive dataset for urban spatial–temporal data mining

Abstract The LibCity-Dataset represents a significant contribution to the field of urban spatial-temporal data mining. This dataset uniquely integrates macro traffic state data with micro trajectory data, providing researchers with comprehensive and diverse urban spatial-temporal data. Specifically, we begin by collecting and processing existing open-source spatial-temporal data. Subsequently, we independently collected Beijing taxi trajectory data through third-party interfaces. This data bridges the gap in the scarcity of current open-source vehicle trajectory data. The distinctive aspect of the LibCity-Dataset lies in its innovative approach of standardizing the storage format, achieved through the implementation of atomic files. By adopting this standardized format, diverse data sources are harmonized, enabling effortless application of spatial-temporal prediction models across various datasets. The uniform storage format not only simplifies experimentation but also expedites the advancement of spatial-temporal prediction research, acting as a catalyst for further innovation. This Data Note provides a comprehensive insight into the creation methodology of the LibCity-Dataset, including data collection and processing methodology, data description, data validation, and usage notes. By facilitating open-source collaboration and setting a benchmark for standardization within the spatial-temporal prediction domain, this dataset aims to foster increased research cooperation and knowledge sharing. The open-source link of our dataset is https://drive.google.com/drive/folders/1g5v2Gq1tkOq8XO0HDCZ9nOTtRpB6-gPe.

Drawing New Cards or Standing Pat: Antecedents, Dynamics, and Consequences of Project Manager Replacement

The majority of projects—even ultimately successful ones—run into significant problems during their development. While organizations have a variety of mechanisms at their disposal to correct projects that are experiencing difficulties, one of the most radical is replacing the project manager. Replacing a project manager “mid-stream” involves a major change to an ongoing project with the potential benefits of onboarding an individual with a different perspective or set of managerial and/or technical skills. Using agency theory as our critical evaluative lens and a qualitative data collection methodology, we interviewed 19 key informants who had experience as part of project manager replacement efforts. This article reports of the dynamics of replacing project managers, identifying the critical decision criteria and mechanisms involved in such decisions. We found that three themes emerged with regard to project manager replacement decision making: 1) replacement is a common correction practice for troubled projects; 2) replacement is viewed by decision makers and team members alike as a message for change; and 3) in reestablishing processes and trust in governance, project size is an important moderator when deciding on a course of action. We finally propose a process model, based on our analysis, which identifies the critical antecedents, effects, and consequences of project manager replacement.

Health-Related Data Sources Accessible to Health Researchers From the US Government: Mapping Review

Big data from large, government-sponsored surveys and data sets offers researchers opportunities to conduct population-based studies of important health issues in the United States, as well as develop preliminary data to support proposed future work. Yet, navigating these national data sources is challenging. Despite the widespread availability of national data, there is little guidance for researchers on how to access and evaluate the use of these resources. Our aim was to identify and summarize a comprehensive list of federally sponsored, health- and health care-related data sources that are accessible in the public domain in order to facilitate their use by researchers. We conducted a systematic mapping review of government sources of health-related data on US populations and with active or recent (previous 10 years) data collection. The key measures were government sponsor, overview and purpose of data, population of interest, sampling design, sample size, data collection methodology, type and description of data, and cost to obtain data. Convergent synthesis was used to aggregate findings. Among 106 unique data sources, 57 met the inclusion criteria. Data sources were classified as survey or assessment data (n=30, 53%), trends data (n=27, 47%), summative processed data (n=27, 47%), primary registry data (n=17, 30%), and evaluative data (n=11, 19%). Most (n=39, 68%) served more than 1 purpose. The population of interest included individuals/patients (n=40, 70%), providers (n=15, 26%), and health care sites and systems (n=14, 25%). The sources collected data on demographic (n=44, 77%) and clinical information (n=35, 61%), health behaviors (n=24, 42%), provider or practice characteristics (n=22, 39%), health care costs (n=17, 30%), and laboratory tests (n=8, 14%). Most (n=43, 75%) offered free data sets. A broad scope of national health data is accessible to researchers. These data provide insights into important health issues and the nation's health care system while eliminating the burden of primary data collection. Data standardization and uniformity were uncommon across government entities, highlighting a need to improve data consistency. Secondary analyses of national data are a feasible, cost-efficient means to address national health concerns.

Saudization Barriers in Labor Market: An Analytical Study

This study identifies Saudization barriers. According to the literature review, thirteen key barriers were identified and classified as Individual, Organizational and Governmental barriers, including: Refusal to work in low-skilled positions (1), Inactive job seeking (2), Lack of interest in vocational training (3), Preference of governmental sector jobs (4), Deficit in educational requirements and qualifications (5), Insufficient skilled Saudi workers (6), Low-cost hiring process (7), Lack of Labor market-driven requirements and qualifications (8), Lack of soft-skills and work ethics (9), Low job commitment and Ghost jobs among Saudi female worker (10), Unclear policies and data collection strategies (11), Forced Saudization in specific occupations (12), and Deficit in interministerial collaboration (13). The Interpretive Structural Modeling (ISM) approach was used to understand the inter-relationships between the identified factors, after collecting the opinion of human resources experts in different industries in the Saudi labor market. This study also identified the “driving barriers” (i.e, the barriers influenced by the other barriers) according to MICMAC analysis. The findings of the ISM model indicate that the top barriers are three; Lack of interest in vocational training (3), Preference of governmental sector jobs (4) and Deficit in educational requirements and qualifications (5), hence at the top of this model. This study identified and showed the interrelationships between barriers, which is helpful for decision-makers to be able to direct future initiatives to overcome top barriers and develop inter-sectorial and inter-ministerial coordination plans to develop clear strategies and data collection methodologies to support the country Vision 2030 in reducing unemployment rates among Saudi workers.

Crowdsourcing Samples for Research on Violent Extremism: A Research Note

ABSTRACT As research on violent extremism continues to progress beyond some of the field’s earlier challenges, new ways of gathering primary source data are becoming increasingly popular. One such data collection methodology implemented widely across parallel fields is crowdsourcing: the process of gathering information, or input, from large numbers of people, either for payment or not, online. In this research note, we present a brief introduction to crowdsourcing, highlight a popular platform for gathering samples online, Prolific, and present four studies conducted by the research team to demonstrate the unique benefits and challenges of crowdsourcing samples online for research on violent extremism.

The Phenomena of Learning Loss Experienced by Elementary School Students during the Covid-19 Post Pandemic

The COVID-19 pandemic caused most students to experience learning loss after joining online learning for almost 2 years. Learning loss is a student's condition experiencing learning setbacks academically due to the factors of the non-sustainable educational process. The study aimed at analyzing the learning loss phenomenon experienced by elementary school students in the COVID-19 post-pandemic situation. The study used a descriptive qualitative approach. The population of the study was 401,321 distributed students, and the sample was gained through conducting two sampling techniques, such as random cluster sampling and accidental sampling, with a final sample of 1,104 students. The data collection methodologies conducted were interview, observation, and questionnaire. The questionnaire used contained 15 questions that had been validated before. The data analysis of the study was conducted interactively using 3 techniques, such as data reduction, data display, and drawing conclusions. The descriptive analysis was conducted by using the Guttman scale with the percentage statistic technique. The result of the study showed that there were learning loss phenomena in the post-pandemic situation, a condition seen from the researched dimensions in the low and medium categories. Moreover, a high level of learning loss was found in the rural area. This was observed from several things, such as the learning facilities provided, the parent's role, and the learning methodologies conducted. To resolve learning loss, we need to participate all parties in the learning process, which in this context means mending a good relationship with the community and parents to improve the learning quality, which is assisted with innovative learning models. Doi: 10.28991/ESJ-2023-SPER-014 Full Text: PDF

Closing Data Gaps to Measure the Bioeconomy in the EU

The expansion of bio-based value chains is prioritized through various European Union (EU) policy initiatives. Due to the growing awareness of the importance of a sustainable bioeconomy in Europe, the need to increase the availability and quality of statistics is increasing. There are several essential aspects lacking, including (i) comprehensive databases and statistics for bio-based sectors; (ii) transparent methodology for bio-based data collection; and (iii) integrated value chain data and indicators that illustrate the flows of different bio-based commodities. The aim of this paper is to develop a bio-based material flow monitor to measure the physical contribution of industries to the bioeconomy. The material flow monitor describes physical material flows (including biomass) to, from, and within the economy. It is recorded in the form of supply and use tables. To measure the bioeconomy, the BioSAM database, along with disaggregated commodities and activities, are used. Data regarding waste generation/treatment and CO2 emissions/sequestrations are added to assess the impact on climate change. The results indicate that the bioeconomy in the EU is underreported due to a lack of data, leading to an insufficient understanding of its contribution to the economy. It can also be concluded that the data from the BioSAM tables are the most complete and have the highest disaggregation level for commodities and sectors, allowing one to measure the significance of the bioeconomy.

A REVISIT OF VIETNAM-INDIA CULTURAL DIPLOMACY ACTIVITIES (2016–2021) AND ITS PROSPECTS

This article traces the evolution of Vietnam-India cultural relations between 2016 and 2021. The methodology of qualitative research design, data collection, and thematic and textual analysis are used to shed light on the rise of Vietnam’s and India’s cultural diplomacy. The article describes the substantial development in Vietnam-India cultural diplomacy between 2016 and 2021 with clear evidence of cultural events. Based on the closely examined process of India-Vietnam cultural relations and the national policies of Vietnam and India, the author provides an outlook for these bilateral cultural ties in the future.

The Relationship between the Intensity of Worship and the Personality of Elementary School Teachers

The personality of the teacher is the main focus in the digital era, because students can imitate the teacher's behavior in the real world and in cyberspace. This research examines the practice of daily worship, personality competence and the intensity of daily worship of IT TQ Miftahul Jannah Medan Private Elementary School educators. It is intended to identify the relationship between individual abilities. Gianna Medan. This type of research is quantitative research using correlation methods. The sampling technique is total sampling. This research was conducted at SD IT TQ Miftahul Jannah Medan. The population and sample of this study were all 16 educators. The data collection methodology of this study uses worship formats and questionnaires, and is tested for validity and reliability using IBM SPSS 27. Contribution and R-squared to determine the contribution of variable X to variable Y. The results of this study indicate that there is a correlation value of 0.936 between the intensity of daily worship with the personal performance of educators. This means that the magnitude of the relationship between the intensity of daily worship and the personal competence of educators is classified as very strong. This strengthens the results of the descriptive analysis of data for the intensity of daily worship in the moderate category of 44% and the personality competence of educators in the high category of 56%. The relationship between the practice of daily worship (X) and the personal performance of educators (Y) is 87.6%. Thus it is concluded that there is a significant relationship between the practice of worship, personality competence and the intensity of educators' worship at the basic education level.

“I hope this is your last sorrow”

Abstract The objective of the present study is to examine condolence strategies and the sociocultural norms underlying the realisation of the speech act of condolence in Persian. To achieve this, a three-layered data collection methodology including two focus group interviews (FGIs), field notes, and a discourse completion task (DCT) were used. FGIs and field notes were utilised to shed light on the cultural norms as well as any variables affecting the expressions of condolence. The DCT, on the other hand, was administered to explicate the form and frequency of condolence strategies in Persian. Results indicate that, influenced by six sociocultural variables, 20 distinct condolence strategies are used in Persian. Furthermore, findings show that, while these strategies are used with varying degrees of frequency in different situations, when expressing condolence, Persian speakers place high importance on empathising with the bereaved interlocutor.

A machine learning based approach to identify key drivers for improving corporate’s esg ratings

Investors increasingly non-financial factors as part of their risk analysis process and growth assessments of corporates. Machine learning (ML) models for predicting ESG scores are an extremely useful tool to help investors make more informed decisions on their portfolios. Such a tool with wide-encompassing alternative data can be useful to the investors. The use of such datasets and machine learning models for ESG ratings can continuously improve the accuracy and reliability of those models. Using machine learning algorithms to identify key drivers of ESG ratings is an effective way of improving portfolio performance. Although the current state of ESG ratings is relatively static, data collection and mapping methodologies are evolving. As more data becomes available, the noise in ESG factors will become less important. This unique document provides a machine learning algorithm for predicting an ESG rating based on a company's financial and non-financial attributes. The financial and non-financial attributes of corporations are extracted from Moody's Orbis and Ratings from S&P. The objective here is to predict the ESG rating of companies where the ESG rating is not easily accessible. At the same time, this approach would allow investors to have a suitable framework for investments based on ESG ratings. With the latest financial and non-financial disclosure by a corporate an ESG score can be predicted which can be used to identify its riskiness with a corresponding increase/decrease of ESG score.

Academic Procrastination, Self-Efficacy, and Task Value of Pre-Service Biology Teacher During Online Learnings

Academic procrastination, frequently linked to low self-efficacy and poor assignment performance, is more likely to occur when learning online. This study aims to reveal the level of academic procrastination, self-efficacy, and assignments by semester, areas of academic procrastination, and reasons for delaying assignments, as well as the relationship between academic procrastination, self-efficacy, and task value. This study uses a quantitative approach through a cross-sectional exploratory study. The sample in this study was semester 1, 3, 5, and 7 students who were taken through a stratified random sampling technique. Utilizing the survey method was the data collection methodology. The level of students is described using frequency distribution descriptive data. To use regression analysis to explain the connection between academic procrastination, self-efficacy, and task value. The reasons for procrastination were analyzed qualitatively. According to the findings, pre-service biology teachers who participated in online learning exhibited moderate levels of academic procrastination (37.8%), self-efficacy (39.1%), and task value (29.9%). More than half of the pre-service biology teachers polled stated they would prefer to postpone doing summaries of four pages of foreign language homework over twelve pages of Indonesian homework. Compared to creating a summary of the subject, more than half of biology education students said they would rather put off making a mind map. Reasons for postponing assignments varied among students. Furthermore, in academic procrastination, there is a negative simultaneous association between self-efficacy and task value.