[Show abstract][Hide abstract] ABSTRACT: The Canadian Community Health Survey (CCHS) is a cross-sectional survey that has collected information on health determinants, health status and the utilization of the health system in Canada since 2001. Several hundred articles have been written utilizing the CCHS dataset. Previous analyses of statistical methods utilized in the literature have focused on a particular journal or set of journals to understand the statistical literacy required for understanding the published research. In this study, we describe the statistical methods referenced in the published literature utilizing the CCHS dataset(s).
A descriptive study was undertaken of references published in Medline, Embase, Web of Knowledge and Scopus associated with the CCHS. These references were imported into a java application utilizing the searchable Apache Lucene text database and screened based upon pre-defined inclusion and exclusion criteria. Full-text PDF articles that met the inclusion criteria were then used for the identification of descriptive, elementary and regression statistical methods referenced in these articles. The identification of statistical methods occurred through an automated search of key words on the full-text articles utilizing the java application.
We identified 4811 references from the 4 bibliographical databases for possible inclusion. After exclusions, 663 references were used for the analysis. Descriptive statistics such as means or proportions were presented in a majority of the articles (97.7%). Elementary-level statistics such as t-tests were less frequently referenced (29.7%) than descriptive statistics. Regression methods were frequently referenced in the articles: 79.8% of articles contained reference to regression in general with logistic regression appearing most frequently in 67.1% of the articles.
Our study shows a diverse set of analysis methods being referenced in the CCHS literature, however, the literature heavily relies on only a subset of all possible statistical tools. This information can be used in identifying gaps in statistical methods that could be applied to future analysis of public health surveys, insight into training and educational programs, and also identifies the level of statistical literacy needed to understand the published literature.
BMC Medical Research Methodology 01/2014; 14(1):15. · 2.17 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: So far, the very meaning of health and therefore, treatment and rehabilitation is benchmarked to the normal or species-typical body. We expect certain abilities in members of a species; we expect humans to walk but not to fly, but a bird we expect to fly. However, increasingly therapeutic interventions have the potential to give recipients beyond species-typical body related abilities (therapeutic enhancements, TE). We believe that the perfect storm of TE, the shift in ability expectations toward beyond species-typical body abilities, and the increasing desire of health consumers to shape the health system will increasingly influence various aspects of health care practice, policy, and scholarship. We employed qualitative and quantitative methods to investigate among others how human enhancement, neuro/cognitive enhancement, brain machine interfaces, and social robot discourses cover (a) healthcare, healthcare policy, and healthcare ethics, (b) disability and (c) health consumers and how visible various assessment fields are within Neuro/Cogno/ Human enhancement and within the BMI and social robotics discourse. We found that health care, as such, is little discussed, as are health care policy and ethics; that the term consumers (but not health consumers) is used; that technology, impact and needs assessment is absent; and that the imagery of disabled people is primarily a medical one. We submit that now, at this early stage, is the time to gain a good understanding of what drives the push for the enhancement agenda and enhancement-enabling devices, and the dynamics around acceptance and diffusion of therapeutic enhancements
[Show abstract][Hide abstract] ABSTRACT: Real-time locating systems (RTLS) have the potential to enhance healthcare systems through the live tracking of assets, patients and staff. This study evaluated a commercially available RTLS system deployed in a clinical setting, with three objectives: (1) assessment of the location accuracy of the technology in a clinical setting; (2) assessment of the value of asset tracking to staff; and (3) assessment of threshold monitoring applications developed for patient tracking and inventory control. Simulated daily activities were monitored by RTLS and compared with direct research team observations. Staff surveys and interviews concerning the system's effectiveness and accuracy were also conducted and analyzed. The study showed only modest location accuracy, and mixed reactions in staff interviews. These findings reveal that the technology needs to be refined further for better specific location accuracy before full-scale implementation can be recommended.
Journal of the American Medical Informatics Association 02/2012; 19(4):674-9. · 3.57 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Social robotics is an emerging field, with many applications envisioned for people with disabilities. This paper explores these applications and the portrayal of people with disabilities within the social robotics discourse. Our review of social robotics literature revealed that social robotics mainly portrays disabled people through a medical/body ability deficiency lens, namely identifying deficient abilities, and then proposing how a certain robot can fix them and give the individual "normal" functioning. However, within the Disabled People Rights Movement, the academic field of disability studies, and existing legal documents, a second narrative is evident which focuses less on 'fixing' the person to the species-typical norm, and more on increasing the participation in society of that person the way they are. We submit that the second type of narrative and its way of defining problems and solutions needs more visibility within the social robotics discourse and in the vision of possible products.
01/2012: chapter 17: pages 168-177; Springer Berlin Heidelberg., ISBN: 9783642341021
[Show abstract][Hide abstract] ABSTRACT: An increasing proportion of critically ill patients are elderly (ie, >or= 65 years of age). This poses complex challenges and choices for the management of elderly patients. Outcome following admission to the ICU has been traditionally concerned with mortality. Beyond mortality, outcomes such as functional status and health-related quality of life (HRQOL) have assumed greater importance. This article reviews the literature, published in English from 1990 to December 2003, pertaining to HRQOL and functional status outcomes of elderly patients. Functional status and HRQOL of elderly survivors of ICUs has been underinvestigated. There is no agreement as to the optimal instrument choice, and differences between studies preclude meaningful comparison or pooling of results.
[Show abstract][Hide abstract] ABSTRACT: We explore the potential of applying machine learning techniques to the management of patient flow in hospitals. For this project, we have obtained the Weka machine learning library and three years of historical ward occupancy data from Rockyview Hospital. We use Weka's classi-fier algorithms and the Rockyview data to build a model of patient flow through each ward. Using Weka, we then attempt to predict ward occu-pancy problems on any given day using the model and the ward conditions from the previous day. This process is repeated for all eighteen wards. Fi-nally, we obtain rules (sets of ward conditions that warn of an impending occupancy problem) for each ward and present the results.