Warthog - Are You A Functioning Human In A Functioning World?
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Metrics details. Functioning and disability are universal human experiences. However, our current understanding of functioning from a comprehensive perspective is limited. The development of the International Classification of Functioning, Disability and Health ICF on the one hand and recent developments in graphical modeling on the other hand might be combined and open the door to a more comprehensive understanding of human functioning.
The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data for a range of applications. We show the applicability of graphical models on ICF data for different tasks: Visualization of the dependence structure of the data set, dimension reduction and comparison of subpopulations.
Moreover, we further developed and applied recent findings in causal inference using graphical models to estimate bounds on intervention effects in an observational study with many variables and without knowing the underlying causal structure.
In each field, graphical models could be applied giving results of high face-validity. In particular, graphical models could be used for visualization of functioning in patients with spinal cord injury. The resulting graph consisted of several connected Warthog - Are You A Functioning Human In A Functioning World?
which can be used for dimension reduction. Moreover, we found that the differences in the dependence structures between subpopulations were relevant and could be systematically analyzed using graphical models. Finally, when estimating bounds on causal effects of ICF categories on general health perceptions among patients with I Dont Wanna Lose - Eiffel 65 - Contact! health conditions, we found that the five ICF categories Warthog - Are You A Functioning Human In A Functioning World?
showed the strongest effect were plausible. Graphical Models are a flexible tool and lend themselves for a wide range of applications. In particular, studies involving ICF data seem to be suited for analysis using graphical models. In recent years, research in health conditions with high impact such as cancer, cardiovascular, and Change And Be Yourself - Roots Of Madness - Before The Darkness diseases has been redefined from simplistic cause models towards a systems approach.
This permits complex interactions of multiple components embedded in the cellular machinery of the body, and hence a new understanding of disease and aetiology. Similar to this new approach to genomic and cellular disease mechanisms, macroscopic views on health and disease are changing. Health is increasingly understood as a complex interaction of functioning with a multifaceted environment. Functioning and disability are universal human experiences in which body, behavior and society are inextricably intertwined [ 12 ].
In our lifespan we all will experience limitations in functioning due to acute or chronic health conditions, or aging. Modern societies aim to optimize functioning and quality of life through rehabilitative efforts on the clinical, service and policy level [ 34 ]. Our current understanding of functioning from a comprehensive perspective is limited. The World Health Organization WHO has recently made a compelling case to develop human functioning and rehabilitation research in its resolution R on 'disability, including prevention, management and rehabilitation' [ 4 ].
All substantive articles of the UN Convention on the Rights of Persons with Disabilities refer to specific domains of human functioning. Human rights require appropriate levels of functioning.
Significantly implementing a right means to know and analyze all the relevant levels of human functioning in concert with a facilitating environment. The right to education, for example, can only be implemented by enabling mobility, communication, access to appropriate facilities and support. We require, in short, a comprehensive understanding of human functioning. Likewise, the "Rehabilitation Medicine Summit: Building Research Capacity" which was organized by the Foundation for Physical Medicine and Rehabilitation, the American Academy of Physical Medicine and Rehabilitation, the American Congress of Rehabilitation Medicine, and the Association of Academic Physiatrists stated the need to increase investment in human functioning and rehabilitation research [ 5 ].
Still, there has been considerable progress into the understanding of functioning. Among the recent developments is the International Classification of Functioning, Disability and Health ICF; see [ 3 ]and as a consequence the possibility for innovative modeling strategies in that context.
With the ICF it is possible to systematically define the prototypical spectrum of functioning and health domains for specific health conditions, therapy targets, and age Love Kills - Freddie Mercury - The Solo Collection (Box Set). Likewise, the association of elements of functioning on the level of single categories can be analyzed beyond the study of the incidence and prevalence of disease.
It is a difficult task to catch the complex associations encountered in human functioning research. This methodological problem has been solved for the domain of genomic medicine by using graphical modeling. Graphical models were identified as a promising new approach to modeling clinical data [ 6 ], and thus the systems approach to health and disease.
Beyond association, this method has also been developed for estimating causal effects [ 7 ]. Based on current work [ 8 ], graphical models have Never Ever (Decoy & DJ Bonka Remix) - Ayumi Hamasaki - RMX Works From Cyber Trance Presents Ayu Tran for a range of Warthog - Are You A Functioning Human In A Functioning World?.
Firstly, the dependence structure of complex data can be visualized by graphs thus facilitating intuitive understanding. Secondly, graphical models can be used for dimension reduction of complex data. Thirdly, differences in dependence structures between subpopulations can be clarified.
Fourthly, under stricter assumptions, bounds on the causal effects of interventions can be estimated from observational data using graphical models. Yet, so far there is no systematic road-map to describe the potential applications of graphical models for the study of functioning.
The objective of our paper therefore is to explore how graphical models can be used in the study of ICF data in order to develop a more detailed understanding of human functioning. Specifically, our first aim was to develop and improve statistical approaches to the visualization of complex associations. Our second aim was to examine how graphical models can be used for dimension reduction. Our third aim was to examine how differences in association structures between subpopulations can be clarified.
Finally, our fourth aim was to investigate the possibility of estimating intervention effects from observational data without knowing the underlying causal structure. This study was a post hoc analysis of two data sets collected in the context of the ICF Core Set project.
Methods for data collection and descriptive analyses have been published elsewhere see [ 9 ] and [ 10 ]. The multi center, cross-sectional study of patients with SCI was conducted in 14 countries. Individuals were included if they had sustained a SCI with an acute onset, or if they were receiving rehabilitation in the early post-acute situation, or if they were in a long-term context.
Individuals had to be at least 18 years old and had to be able to understand purpose and reason of the study. Written informed consent was obtained from all included patients. Individuals with significant traumatic brain injury or diagnosed mental disorders prior to SCI were excluded.
Acute onset was defined as injury or disease with the development of SCI within 14 days. The early post-acute context was defined as starting with active rehabilitation and ending with the completion of the first comprehensive rehabilitation after the acute SCI. The long-term context follows the early post-acute context. This working definition was based on a worldwide consensus of researchers involved in the data collection and was approved by the steering committee of the project.
Patients had a mean age of 42 years. For subgroup Warthog - Are You A Functioning Human In A Functioning World?
, we used data from patients: from four European countries Denmark, Germany, Israel, and Switzerland and from four Asian countries India, Malaysia, Thailand, and Vietnam. An extensive description of this data set can be found in [ 9 ].
We obtained permission to reanalyze the data. We used data from a multi center, cross-sectional study involving patients with chronic health conditions. Individuals were included if they were undergoing inpatient or outpatient rehabilitation in 19 German hospitals and rehabilitation centers and had at least one of the following chronic health conditions: low Never Ending Story (Power Club Vocal Mix) - DJ AC DC* - Never Ending Story pain, osteoporosis, rheumatoid arthritis, osteoarthritis, chronic ischemic heart disease, chronic obstructive pulmonary disease, diabetes mellitus, breast cancer, obesity, chronic widespread pain, depression, stroke.
Patients had a mean age of 53 years. Warthog - Are You A Functioning Human In A Functioning World? extensive description of this data set can be found in [ 10 ]. The first part covers functioning and disability with the components "Body Functions" coded with b"Body Structures" s and "Activities and Participation" d. The second part covers contextual factors with the components "Environmental Factors" e and "Personal Factors". The ICF categories of each component, with exception of the "Personal Factors", which are not classified yet, are hierarchically detailed up to four levels.
The hierarchical code system consists of the abbreviation of the component and the chapter number e. The SCI data comprised second level categories. The CHC data comprised second level categories. The ICF suggests qualifiers which range from 0 to 4 for each category in bd and s and from -4 to 4 in e.
The SF is one of the most frequently used instruments for assessing generic health related quality of life [ 11 ]. The scores range from 0 to with higher scores indicating better health status. We used the General Health Perception score ghp as an outcome for predictive modeling. We used the free statistical software R for all our computations. Both R and all mentioned packages are freely available see [ 12 ].
In both data sets, the problem of remaining missing values was addressed by using multiple imputation [ 13 ] assuming noninformative missingness. Multiple imputation generates m versions of the original data set, with varying missing value replacements in each version and Trust In Me - Various - The Bodyguard (Original Soundtrack Album) information from all other variables to generate the replacement.
Simulation studies demonstrated that even with few generated data sets multiple imputation yielded valid results [ 14 ]. The SCI data was imputed ten times using multiple imputation using the option "logistic regression"while the CHC data was imputed five times using the option "predictive mean matching". Different options were used, since the SCI data after removing category e consisted only of binary variables see next sectionwhereas the CHC data consisted of categorical variables with many levels.
In the next step, each of these imputed data sets was analyzed using common complete case methods as described below. For computations, we used the R-package "mice" which implements multiple imputation see [ 13 ]. Because the properties of the qualifiers are not yet evaluated sufficiently, we dichotomized the ICF categories.
In the original study generating the SCI data, only the distinction "no impairment" vs. Since category e was excluded as Children Of The Night - Flotsam And Jetsam - Doomsday For The Deceiver (CD, Album, Album) in the previous section, we didn't have to dichotomize the SCI data set any further.
Graphical models are susceptible to small changes in the data set leading to large variations and hence unstable results. A common method to enhance unstable procedures is to use bootstrap aggregation [ 15 ], which enhances the overall performance of the model building process. Bootstrap aggregation produces several models based on bootstrap replicates of the original data set.
The multiple versions are then aggregated. Bootstrap aggregation can stabilize the outcome of a model and enhance accuracy [ 15 ]. We generated 10 bootstrap replications. Bootstrap aggregation was carried out using R-programs developed by ourselves. Depending on the specific analysis, we aggregated the results on the 50 or data sets as explained in detail below and thus obtained more stable and reliable results.
Graphical models can be thought of as maps of dependence structures of a given probability distribution or a sample thereof see for example [ 16 ]. In order to illustrate the analogy, let us consider a road map.
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