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Brain and Behavior Jan 2021The Danish Multiple Sclerosis Registry is the oldest operative and nationwide MS registry. We present The Danish Multiple Sclerosis Registry with its history, data...
OBJECTIVES
The Danish Multiple Sclerosis Registry is the oldest operative and nationwide MS registry. We present The Danish Multiple Sclerosis Registry with its history, data collection, scientific contribution, and national and international research collaboration.
MATERIALS AND METHODS
Detailed description of data collection, completeness, quality optimizing procedures, funding, and legal, ethical and data protection issues are provided.
RESULTS
The total number of registered cases with clinical isolated syndrome and multiple sclerosis since 1956 was by start of May 2020 30,023 of whom 16,515 cases were alive and residing in Denmark, giving a prevalence rate of about 284 per 100,000 population. The mean annual number of new cases receiving an MS diagnosis was 649 per year in the period 2010 to 2019. In total, 7,945 patients (48.1%) are receiving disease modifying therapy at the start of May 2020.
CONCLUSIONS
Multiple Sclerosis registers are becoming increasingly important, not only for epidemiological research but also by quantifying the burden of the disease for the patients and society and helping health care providers and regulators in their decisions. The Danish Multiple Sclerosis Registry has served as data source for a number of scientific publications including epidemiological studies on changes in incidence and mortality, cohort studies investigating risk factors for developing MS, comorbidities and socioeconomic outcomes in the MS population, and observational studies on effectiveness of disease modifying treatments outside the narrow realms of randomized clinical trials.
Topics: Denmark; Humans; Incidence; Multiple Sclerosis; Prevalence; Registries
PubMed: 33128351
DOI: 10.1002/brb3.1921 -
American Journal of Public Health Dec 2021
Topics: COVID-19; Data Accuracy; Data Collection; Humans; Influenza, Human; Public Health Surveillance; SARS-CoV-2; Self Report; Surveys and Questionnaires; Time Factors; United States; Zika Virus Infection
PubMed: 34878882
DOI: 10.2105/AJPH.2021.306553 -
JCO Clinical Cancer Informatics Mar 2021For central cancer registries to become a more significant public health resource, they must evolve to capture more timely, accurate, and extensive data. Key...
For central cancer registries to become a more significant public health resource, they must evolve to capture more timely, accurate, and extensive data. Key stakeholders have called for a faster time to deliver work products, data extensions such as social determinants of health, and more relevant information for cancer control programs at the local level. The proposed model consists of near real-time reporting stages to replace the current time and labor-intensive efforts to populate a complete cancer case abstract on the basis of the 12- and 24-month data submission timelines. The first stage collects a cancer diagnosis minimum data set sufficient to describe population incidence and prevalence, which is then followed by a second stage capturing subsequent case updates and treatment data. A third stage procures targeted information in response to identified research projects' needs. The model also provides for further supplemental reports as may be defined to gather additional data. All stages leverage electronic health records' widespread development and the many emerging standards for data content, including national policies related to healthcare and technical standards for interoperability, such as the Fast Healthcare Interoperability Resources specifications to automate and accelerate reporting to central cancer registries. The emergence of application programming interfaces that allow for more interoperability among systems would be leveraged, leading to more efficient information sharing. Adopting this model will expedite cancer data availability to improve cancer control while supporting data integrity and flexibility in data items. It presents a long-term and feasible solution that addresses the extensive burden and unsustainable manual data collection requirements placed on Certified Tumor Registrars at disease reporting entities nationally.
Topics: Data Collection; Data Management; Electronic Health Records; Humans; Neoplasms; Registries
PubMed: 33760641
DOI: 10.1200/CCI.20.00177 -
BMC Medical Research Methodology Aug 2023Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations...
BACKGROUND
Epidemiologic and medical studies often rely on evaluators to obtain measurements of exposures or outcomes for study participants, and valid estimates of associations depends on the quality of data. Even though statistical methods have been proposed to adjust for measurement errors, they often rely on unverifiable assumptions and could lead to biased estimates if those assumptions are violated. Therefore, methods for detecting potential 'outlier' evaluators are needed to improve data quality during data collection stage.
METHODS
In this paper, we propose a two-stage algorithm to detect 'outlier' evaluators whose evaluation results tend to be higher or lower than their counterparts. In the first stage, evaluators' effects are obtained by fitting a regression model. In the second stage, hypothesis tests are performed to detect 'outlier' evaluators, where we consider both the power of each hypothesis test and the false discovery rate (FDR) among all tests. We conduct an extensive simulation study to evaluate the proposed method, and illustrate the method by detecting potential 'outlier' audiologists in the data collection stage for the Audiology Assessment Arm of the Conservation of Hearing Study, an epidemiologic study for examining risk factors of hearing loss in the Nurses' Health Study II.
RESULTS
Our simulation study shows that our method not only can detect true 'outlier' evaluators, but also is less likely to falsely reject true 'normal' evaluators.
CONCLUSIONS
Our two-stage 'outlier' detection algorithm is a flexible approach that can effectively detect 'outlier' evaluators, and thus data quality can be improved during data collection stage.
Topics: Humans; Computer Simulation; Algorithms; Data Collection; Risk Factors; Data Accuracy
PubMed: 37528402
DOI: 10.1186/s12874-023-01988-4 -
American Journal of Obstetrics and... Oct 2020
Topics: Coronavirus; Data Collection
PubMed: 32553913
DOI: 10.1016/j.ajog.2020.06.027 -
Behavior Research Methods Apr 2022Web-based data collection is increasingly popular in both experimental and survey-based research because it is flexible, efficient, and location-independent. While...
Web-based data collection is increasingly popular in both experimental and survey-based research because it is flexible, efficient, and location-independent. While dedicated software for laboratory-based experimentation and online surveys is commonplace, researchers looking to implement experiments in the browser have, heretofore, often had to manually construct their studies' content and logic using code. We introduce lab.js, a free, open-source experiment builder that makes it easy to build studies for both online and in-laboratory data collection. Through its visual interface, stimuli can be designed and combined into a study without programming, though studies' appearance and behavior can be fully customized using HTML, CSS, and JavaScript code if required. Presentation and response times are kept and measured with high accuracy and precision heretofore unmatched in browser-based studies. Experiments constructed with lab.js can be run directly on a local computer and published online with ease, with direct deployment to cloud hosting, export to web servers, and integration with popular data collection platforms. Studies can also be shared in an editable format, archived, re-used and adapted, enabling effortless, transparent replications, and thus facilitating open, cumulative science. The software is provided free of charge under an open-source license; further information, code, and extensive documentation are available from https://lab.js.org/ .
Topics: Computers; Data Collection; Humans; Reaction Time; Software
PubMed: 34322854
DOI: 10.3758/s13428-019-01283-5 -
Acta Psychologica Aug 2022There are numerous controversies in research exploring personality dynamics and intrapsychic processes, e.g. insufficient insight provided by available measures such as...
There are numerous controversies in research exploring personality dynamics and intrapsychic processes, e.g. insufficient insight provided by available measures such as self-report questionnaires. As a consequence, new methods are developed. Some of the recent theories indicate that self-esteem is not a stable personality trait, but a dynamic construct fluctuating as a result of (mostly) social interactions. I present a semi-structured interview protocol as a method of data collection which can provide rich verbal and non-verbal material referring to self-esteem regulation. Analysis system is not included as there can be many different approaches to use collected data, e.g. qualitative content analysis or narrative inquiry methods. In this paper, I present exemplary statements of participants corresponding to every part of the interview. The examples are explained considering theoretical background. Finally, the strengths and limitations of presented method are discussed, as well as possible research areas to explore with it.
Topics: Humans; Research Design; Self Concept; Self Report; Surveys and Questionnaires
PubMed: 35716626
DOI: 10.1016/j.actpsy.2022.103642 -
Journal of Registry Management 2023The past several years have been marked by substantial growth in pediatric cancer data and collection across the world. In the United States, multiple projects and...
The past several years have been marked by substantial growth in pediatric cancer data and collection across the world. In the United States, multiple projects and standard setters have laid a foundation for the growth of this data, and the need for an overview and explanation of a few of the programs directly relevant to cancer registrars has become apparent. This article will discuss 3 initiatives that highlight many of the efforts and intricacies involved with the collection of pediatric cancer data in the cancer registry world: the National Childhood Cancer Registry, the Toronto Pediatric Cancer Stage Guidelines, and the Pediatric Site-Specific Data Items Work Group.
Topics: Child; Humans; United States; Neoplasms; Registries; Neoplasm Staging; Data Management; Data Collection
PubMed: 37941745
DOI: No ID Found -
Lakartidningen Oct 2019The development of accelerometers has revolutionized measurement of physical activity, and they are used to a large extent in research and have started to be implemented... (Review)
Review
The development of accelerometers has revolutionized measurement of physical activity, and they are used to a large extent in research and have started to be implemented into clinical settings. However, achievement of reliable outcomes requires good methodological knowledge and skills by the user. Otherwise, significant measurement errors may occur, interfering with assessment of the physical activity level in the population, group differences, associations with health parameters or effect of treatments. This paper by the Swedish Network for Objective Measurement of Movement (NORM) provides an overview of physical activity measurement including sections of data collection, processing of raw data into useful metrics and statistical analysis. It targets users of accelerometer in research, health care and national surveys.
Topics: Accelerometry; Data Collection; Data Interpretation, Statistical; Exercise; Humans
PubMed: 31613374
DOI: No ID Found -
BMC Oral Health Oct 2022This scoping review reports on studies that collect survey data using quantitative research to measure self-reported oral health status outcome measures. The objective... (Review)
Review
BACKGROUND
This scoping review reports on studies that collect survey data using quantitative research to measure self-reported oral health status outcome measures. The objective of this review is to categorize measures used to evaluate self-reported oral health status and oral health quality of life used in surveys of general populations.
METHODS
The review is guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) with the search on four online bibliographic databases. The criteria include (1) peer-reviewed articles, (2) papers published between 2011 and 2021, (3) only studies using quantitative methods, and (4) containing outcome measures of self-assessed oral health status, and/or oral health-related quality of life. All survey data collection methods are assessed and papers whose methods employ newer technological approaches are also identified.
RESULTS
Of the 2981 unduplicated papers, 239 meet the eligibility criteria. Half of the papers use impact scores such as the OHIP-14; 10% use functional measures, such as the GOHAI, and 26% use two or more measures while 8% use rating scales of oral health status. The review identifies four data collection methods: in-person, mail-in, Internet-based, and telephone surveys. Most (86%) employ in-person surveys, and 39% are conducted in Asia-Pacific and Middle East countries with 8% in North America. Sixty-six percent of the studies recruit participants directly from clinics and schools, where the surveys were carried out. The top three sampling methods are convenience sampling (52%), simple random sampling (12%), and stratified sampling (12%). Among the four data collection methods, in-person surveys have the highest response rate (91%), while the lowest response rate occurs in Internet-based surveys (37%). Telephone surveys are used to cover a wider population compared to other data collection methods. There are two noteworthy approaches: 1) sample selection where researchers employ different platforms to access subjects, and 2) mode of interaction with subjects, with the use of computers to collect self-reported data.
CONCLUSION
The study provides an assessment of oral health outcome measures, including subject-reported oral health status and notes newly emerging computer technological approaches recently used in surveys conducted on general populations. These newer applications, though rarely used, hold promise for both researchers and the various populations that use or need oral health care.
Topics: Humans; Oral Health; Quality of Life; Schools; Self Report; Surveys and Questionnaires
PubMed: 36192721
DOI: 10.1186/s12903-022-02399-5