China
Africa
Explore chapters and articles related to this topic
Data Collection Methods
Published in Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2018
Neville A. Stanton, Paul M. Salmon, Guy H. Walker, Chris Baber, Daniel P. Jenkins
Observation (and observational studies) are used to gather data regarding activity conducted in complex, dynamic systems. In its simplest form, observation involves observing an individual or group of individuals performing work-related activity. A number of different types of observational study exist, such as direct observation, covert observation and participant observation. Observation is attractive due to the volume and utility of the data collected, and also the fact that the data is collected in an operational context. Although at first glance simply observing an operator at work seems to be a very simple approach to employ, it is evident that this is not the case, and that careful planning and execution are required (Stanton 2003). Observational methods also require the provision of technology, such as video and audio recording equipment. The output from an observational analysis is used as the primary input for most HF methods, such as task analysis, error analysis and charting techniques.
Organic Chemicals
Published in William J. Rea, Kalpana D. Patel, Reversibility of Chronic Disease and Hypersensitivity, Volume 4, 2017
William J. Rea, Kalpana D. Patel
Any misclassification of longer-term BPA body burden is likely to have resulted in a smaller (diluted) estimate of the strength of association between BPA and CAD; the true association is likely to be stronger. Some273 have suggested that BPA disease associations are driven by higher dietary intakes, which would result in obesity-related risks and incidental higher BPA excretions. However, our sensitivity analyses show that exclusion of those with obesity and adjustment for blood lipid concentrations and levels of physical activity have little effect on the association, making such an explanation unlikely. Similarly, the lack of effect of adjustment for vitamin C makes diets poor in fruits and vegetables an unlikely explanation.274 Liver and kidney function changes, resulting in altered BPA metabolism or excretion, are also possible confounding factors, but excluding those with high blood creatinine concentrations or adjusting for live enzymes sensitive to cell damage show these as unlikely explanations. In any observational study, it is impossible to exclude the possibility that some unmeasured confounder is present. It is clear, however, that any such confounder must be independent of classic CAD risk factors.
Data Collection Methods
Published in Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins, Human Factors Methods, 2017
Neville A. Stanton, Paul M. Salmon, Laura A. Rafferty, Guy H. Walker, Chris Baber, Daniel P. Jenkins
Observation (and observational studies) is used to gather data regarding activity conducted in complex, dynamic systems. In its simplest form, it involves observing an individual or group of individuals performing work-related activity. A number of different types of observational study exist, such as direct observation, covert observation and participant observation. Observation is attractive due to the volume and utility of the data collected, and also the fact that the data is collected in an operational context. Although, at first glance, simply observing an operator at work seems to be a very simple technique to employ, it is evident that this is not the case, and that careful planning and execution are required (Stanton 2003). Observational techniques also require the provision of technology, such as video and audio recording equipment. The output from an observational analysis is used as the primary input for most HF techniques, such as task analysis, error analysis and charting techniques.
Resource utilization and costs for robotic-assisted and manual total knee arthroplasty – a premier healthcare database study
Published in Expert Review of Medical Devices, 2023
Timothy B. Alton, Abhishek S. Chitnis, Laura Goldstein, Sidharth Kovilakam Rajappan, Anshu Gupta, Kristian Michnacs, Chantal E Holy, Daniel P. Hoeffel
This study is also limited in that the findings from the Premier Healthcare Database may not be generalizable to all hospitalized patients with mTKA and rTKA, particularly those in other countries. Also, Patients treated in non-Premier Inc. hospitals for post-op care will be lost to follow-up in this study. The study has tried to capture as many patient, provider, surgeon and procedure characteristics as available; however, there might be other unmeasured variables (e.g. surgical technique, administrative policy, implants used) that may lead to residual confounding. The study has limitations associated with observational study design and as such the study showcases association in outcomes instead of causal relationship. Despite these limitations, this study provides an informative perspective of the hospital-based experience of care that patients had with rTKA and mTKA up to 90 days post-surgery.
Cycling near misses: a review of the current methods, challenges and the potential of an AI-embedded system
Published in Transport Reviews, 2021
Mohamed R. Ibrahim, James Haworth, Nicola Christie, Tao Cheng, Stephen Hailes
Self-report studies are the dominant design for most cycling near miss studies. The core element that that identifies a self-report study, in the scope of this research, is how data is gathered, not what types of data are gathered. In an observational study, data are gathered and statistically analysed to show associations and draw conclusions. There are three main ways in which data are collected for an self-reporting study: (1) using a self-reporting mechanism based on a questionnaire survey for a group of participants (Aldred & Crosweller, 2015; Chaurand & Delhomme, 2013; Fuller, Gauvin, Morency, Kestens, & Drouin, 2013; Lawson, Pakrashi, Ghosh, & Szeto, 2013; Paschalidis et al., 2016), or (2) using a self-reporting mechanism based on crowdsourcing platforms where data can be uploaded (Nelson et al., 2015; Poulos et al., 2012). Data gathered based on crowdsourcing have led to significant progress in mapping cycling ridership and safety measures (Jestico, Nelson, & Winters, 2016; Nelson et al., 2015). However, while observational studies can offer insights about the behaviour of people on bikes over a longer period, the data gathered is limited by potential biases such as over or under-representation of certain cyclist groups or the types of risk factors, in addition to limitation and biases due to manual labelling and processing based on the collectors’ interpretations (Dozza & Werneke, 2014).
Trace elements exposure and risk in age-related eye diseases: a systematic review of epidemiological evidence
Published in Journal of Environmental Science and Health, Part C, 2021
Onyinyechi Bede-Ojimadu, Chinna N. Orish, Beatrice Bocca, Flavia Ruggieri, Chiara Frazzoli, Orish E. Orisakwe
Epidemiological and postmortem studies were included in this review if they fulfilled the following eligibility criteria: (a) subjects aged over 40 years, (b) use of biomarkers of exposure to trace elements in subjects (c) comparison of trace elements levels between individuals with (cases) and without eye diseases (controls); (d) measures of association between trace elements and risk of age-related eye diseases (e) observational study design (cohort, case-control, cross-sectional). Two of the authors independently screened the articles for eligibility based on these criteria.