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Healthcare Policy = Politiques de Sante Feb 2019
Topics: Biomedical Research; Canada; Data Collection; Health Policy; Humans
PubMed: 31017861
DOI: 10.12927/hcpol.2019.25797 -
Public Health Research & Practice Sep 2015
Topics: Data Collection; Public Health; Statistics as Topic
PubMed: 26536501
DOI: 10.17061/phrp2541539 -
Proceedings of the National Academy of... Mar 2018Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these...
Some aspects of science, taken at the broadest level, are universal in empirical research. These include collecting, analyzing, and reporting data. In each of these aspects, errors can and do occur. In this work, we first discuss the importance of focusing on statistical and data errors to continually improve the practice of science. We then describe underlying themes of the types of errors and postulate contributing factors. To do so, we describe a case series of relatively severe data and statistical errors coupled with surveys of some types of errors to better characterize the magnitude, frequency, and trends. Having examined these errors, we then discuss the consequences of specific errors or classes of errors. Finally, given the extracted themes, we discuss methodological, cultural, and system-level approaches to reducing the frequency of commonly observed errors. These approaches will plausibly contribute to the self-critical, self-correcting, ever-evolving practice of science, and ultimately to furthering knowledge.
Topics: Data Collection; Humans; Quality Control; Reproducibility of Results; Research Design; Science; Scientific Experimental Error; Statistics as Topic
PubMed: 29531079
DOI: 10.1073/pnas.1708279115 -
Journal of Medical Internet Research Jun 2020The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil,... (Meta-Analysis)
Meta-Analysis
BACKGROUND
The most commonly used means to assess pain is by patient self-reported questionnaires. These questionnaires have traditionally been completed using paper-and-pencil, telephone, or in-person methods, which may limit the validity of the collected data. Electronic data capture methods represent a potential way to validly, reliably, and feasibly collect pain-related data from patients in both clinical and research settings.
OBJECTIVE
The aim of this study was to conduct a systematic review and meta-analysis to compare electronic and conventional pain-related data collection methods with respect to pain score equivalence, data completeness, ease of use, efficiency, and acceptability between methods.
METHODS
We searched the Medical Literature Analysis and Retrieval System Online (MEDLINE), Excerpta Medica Database (EMBASE), and Cochrane Central Register of Controlled Trials (CENTRAL) from database inception until November 2019. We included all peer-reviewed studies that compared electronic (any modality) and conventional (paper-, telephone-, or in-person-based) data capture methods for patient-reported pain data on one of the following outcomes: pain score equivalence, data completeness, ease of use, efficiency, and acceptability. We used random effects models to combine score equivalence data across studies that reported correlations or measures of agreement between electronic and conventional pain assessment methods.
RESULTS
A total of 53 unique studies were included in this systematic review, of which 21 were included in the meta-analysis. Overall, the pain scores reported electronically were congruent with those reported using conventional modalities, with the majority of studies (36/44, 82%) that reported on pain scores demonstrating this relationship. The weighted summary correlation coefficient of pain score equivalence from our meta-analysis was 0.92 (95% CI 0.88-0.95). Studies on data completeness, patient- or provider-reported ease of use, and efficiency generally indicated that electronic data capture methods were equivalent or superior to conventional methods. Most (19/23, 83%) studies that directly surveyed patients reported that the electronic format was the preferred data collection method.
CONCLUSIONS
Electronic pain-related data capture methods are comparable with conventional methods in terms of score equivalence, data completeness, ease, efficiency, and acceptability and, if the appropriate psychometric evaluations are in place, are a feasible means to collect pain data in clinical and research settings.
Topics: Adult; Data Collection; Electronics; Female; Humans; Male; Middle Aged; Pain; Surveys and Questionnaires; Young Adult
PubMed: 32348259
DOI: 10.2196/16480 -
Journal of Occupational and... Jun 2018Despite substantial financial and personnel resources being devoted to occupational exposure monitoring (OEM) by employers, workers' compensation insurers, and other...
Despite substantial financial and personnel resources being devoted to occupational exposure monitoring (OEM) by employers, workers' compensation insurers, and other organizations, the United States (U.S.) lacks comprehensive occupational exposure databases to use for research and surveillance activities. OEM data are necessary for determining the levels of workers' exposures; compliance with regulations; developing control measures; establishing worker exposure profiles; and improving preventive and responsive exposure surveillance and policy efforts. Workers' compensation insurers as a group may have particular potential for understanding exposures in various industries, especially among small employers. This is the first study to determine how selected state-based and private workers' compensation insurers collect, store, and use OEM data related specifically to air and noise sampling. Of 50 insurers contacted to participate in this study, 28 completed an online survey. All of the responding private and the majority of state-based insurers offered industrial hygiene (IH) services to policyholders and employed 1 to 3 certified industrial hygienists on average. Many, but not all, insurers used standardized forms for data collection, but the data were not commonly stored in centralized databases. Data were most often used to provide recommendations for improvement to policyholders. Although not representative of all insurers, the survey was completed by insurers that cover a substantial number of employers and workers. The 20 participating state-based insurers on average provided 48% of the workers' compensation insurance benefits in their respective states or provinces. These results provide insight into potential next steps for improving the access to and usability of existing data as well as ways researchers can help organizations improve data collection strategies. This effort represents an opportunity for collaboration among insurers, researchers, and others that can help insurers and employers while advancing the exposure assessment field in the U.S.
Topics: Data Collection; Humans; Insurance Carriers; Occupational Exposure; Occupational Health; United States; Workers' Compensation
PubMed: 29580189
DOI: 10.1080/15459624.2018.1453140 -
Current HIV/AIDS Reports Dec 2020Short message system (SMS) communication is widespread in low- and middle-income countries (LMICs), and may be a viable approach to address challenges with in-person... (Review)
Review
PURPOSE OF REVIEW
Short message system (SMS) communication is widespread in low- and middle-income countries (LMICs), and may be a viable approach to address challenges with in-person data collection for HIV-related research and monitoring and evaluation. We reviewed the literature to characterize potential benefits and challenges with using SMS for remote data capture, including examples from HIV and sexual and reproductive health.
RECENT FINDINGS
In our review, we found that studies that have used SMS to capture sensitive, self-reported data found this was an acceptable and feasible strategy, and may reduce social desirability bias of self-reported data; but studies are limited. Shared phones and privacy concerns have been described as challenges, but can be addressed with enhanced security features. Response rates to SMS surveys varied significantly by topic, population, and setting. SMS may improve generalizability and precision of health and behavior data for HIV in research and programs, but use in LMICs is limited. SMS systems should be carefully designed to overcome potential implementation hurdles.
Topics: Cell Phone; Counseling; Data Collection; Developing Countries; HIV Infections; Humans; Self Report; Text Messaging
PubMed: 33010003
DOI: 10.1007/s11904-020-00534-x -
Revista Brasileira de Enfermagem 2018construct and validate the content of an instrument to collect data from patients with head and neck cancer (HNC) served in a specialty clinic.
OBJECTIVE
construct and validate the content of an instrument to collect data from patients with head and neck cancer (HNC) served in a specialty clinic.
METHOD
methodological study consisting of four steps. The first step consisted in the preparation of the instrument using databases and the theoretical model of Marjory Gordon. In the second and third steps the content was validated by eight nursing judges. The evaluation used the Content Validity Index (CVI). The fourth step consisted in a pilot test with seventeen HNC patients.
RESULTS
of the 88 questions formulated and organized on the dimensions of structure and process submitted to validation, items with CVI lower than 0.80 were excluded. The final instrument was composed of 56 items, with global CVI calculated as 0.87.
CONCLUSION
the final instrument presented content validity for data collection in head and neck clinic.
Topics: Adult; Data Collection; Female; Head and Neck Neoplasms; Humans; Male; Middle Aged; Psychometrics; Reproducibility of Results; Surveys and Questionnaires
PubMed: 30156675
DOI: 10.1590/0034-7167-2017-0227 -
Acta Crystallographica. Section D,... May 2018In protein microcrystallography, radiation damage often hampers complete and high-resolution data collection from a single crystal, even under cryogenic conditions. One...
In protein microcrystallography, radiation damage often hampers complete and high-resolution data collection from a single crystal, even under cryogenic conditions. One promising solution is to collect small wedges of data (5-10°) separately from multiple crystals. The data from these crystals can then be merged into a complete reflection-intensity set. However, data processing of multiple small-wedge data sets is challenging. Here, a new open-source data-processing pipeline, KAMO, which utilizes existing programs, including the XDS and CCP4 packages, has been developed to automate whole data-processing tasks in the case of multiple small-wedge data sets. Firstly, KAMO processes individual data sets and collates those indexed with equivalent unit-cell parameters. The space group is then chosen and any indexing ambiguity is resolved. Finally, clustering is performed, followed by merging with outlier rejections, and a report is subsequently created. Using synthetic and several real-world data sets collected from hundreds of crystals, it was demonstrated that merged structure-factor amplitudes can be obtained in a largely automated manner using KAMO, which greatly facilitated the structure analyses of challenging targets that only produced microcrystals.
Topics: Cluster Analysis; Crystallography, X-Ray; Data Collection; Datasets as Topic; Electronic Data Processing; Humans; Proteins; Software; Viral Proteins
PubMed: 29717715
DOI: 10.1107/S2059798318004576 -
Journal of Biological Rhythms Feb 2017This article is part of a Journal of Biological Rhythms series exploring analysis and statistical topics relevant to researchers in biological rhythms and sleep...
This article is part of a Journal of Biological Rhythms series exploring analysis and statistical topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article, we address issues related to the collection of multiple data points from the same organism or system at different times, since such longitudinal data collection is fundamental to the assessment of biological rhythms. Rhythmic longitudinal data require additional specific statistical considerations, ranging from curve fitting to threshold definitions to accounting for correlation structure. We discuss statistical analyses of longitudinal data including issues of correlational structure and stationarity, markers of biological rhythms, demasking of biological rhythms, and determining phase, waveform, and amplitude of biological rhythms.
Topics: Animals; Biomarkers; Biomedical Research; Circadian Rhythm; Data Collection; Humans; Models, Biological; Sleep; Statistics as Topic; Time Factors
PubMed: 27836939
DOI: 10.1177/0748730416670051 -
Demography Oct 2018The digital traces that we leave online are increasingly fruitful sources of data for social scientists, including those interested in demographic research. The...
The digital traces that we leave online are increasingly fruitful sources of data for social scientists, including those interested in demographic research. The collection and use of digital data also presents numerous statistical, computational, and ethical challenges, motivating the development of new research approaches to address these burgeoning issues. In this article, we argue that researchers with formal training in demography-those who have a history of developing innovative approaches to using challenging data-are well positioned to contribute to this area of work. We discuss the benefits and challenges of using digital trace data for social and demographic research, and we review examples of current demographic literature that creatively use digital trace data to study processes related to fertility, mortality, and migration. Focusing on Facebook data for advertisers-a novel "digital census" that has largely been untapped by demographers-we provide illustrative and empirical examples of how demographic researchers can manage issues such as bias and representation when using digital trace data. We conclude by offering our perspective on the road ahead regarding demography and its role in the data revolution.
Topics: Bias; Big Data; Birth Rate; Data Collection; Demography; Ethics, Research; Humans; Mortality; Privacy; Racial Groups; Research; Social Media
PubMed: 30276667
DOI: 10.1007/s13524-018-0715-2