Bibliographic record
Abstract
While we generally associate spring with a time to turn over a new leaf, any time can be the right time to institute positive changes in self-management. This issue of the International Journal of MS Care (IJMSC) contains a number of articles on enhancing self-care as well as the usual broad mixture of articles pertinent to multiple sclerosis (MS) clinicians.Dr. Gulick of Rutgers University College of Nursing and colleagues have contributed an article on “Monitoring My Multiple Sclerosis,” a patient-administered assessment scale that can provide health status information to the patient as well as health-care providers. Ms. Vore and colleagues of Nazareth College in Rochester, New York, provide a rehabilitation perspective on the idea of self-management through their study on the impact of a 10-week individualized exercise program on physical function and fatigue of individuals with MS. Although it is a pilot study, readers will hopefully take away points that will be helpful to their own practices. From a psychosocial perspective, Dr. Yorkston and colleagues from the University of Washington in Seattle provide insights obtained from focus groups into difficulties people with MS face in self-management. This perspective is also valuable for clinicians and caregivers.Taking more definitively the view of the clinician, Ms. Burke from the Westmead Millennium Institute in Sydney, Australia, and colleagues examine the evolution and expansion of the role of the MS nurse around the world. They discuss the implications of the emergence of new treatments for the disease as well as the growing need for education and empowerment of MS patients.Another timely article in our current climate of increasing cost cutting and cost consciousness is the contribution of Ms. Newton of the University of Oklahoma and Ms. Stica of CoxHealth in Springfield, Missouri, which presents a cost-effectiveness analysis of treatments for MS. While the analysis does not include all of the currently available medications, it provides insights into how this type of analysis may be applied to all MS agents in the future and how policy makers may view treatment data. Whether or not we agree with the assumptions inherent in this type of analysis, it is important to be aware of the techniques applied and the derivation of the results, which we may see implemented in the years to come.Last but not least, Dr. Marrie of the University of Manitoba, Winnipeg, and Dr. Goldman of the University of Virginia in Charlottesville report on their assessment of the validity of the Tremor and Coordination Scale used by the NARCOMS Registry, a special project of the Consortium of Multiple Sclerosis Centers (CMSC). Given that tremor and incoordination can have drastic effects on MS patients and that the therapeutic options for symptomatic treatment of these problems are limited, it is extremely helpful to have a proper measurement tool for further studies in this area.Also in this issue, we mark the passing of Dr. Kenneth Johnson, former chairman of the Department of Neurology at the University of Maryland School of Medicine. Dr. Johnson was internationally known for his contributions to MS care and research, and his work led to the development and approval of two diseasemodifying therapies for the disease.In closing, we are pleased to congratulate Dr. Mary Filipi and colleagues on their receipt of the Herndon Award for the best article published in the IJMSC in the previous calendar year, which was announced at the CMSC annual meeting in June. Dr. Filipi's article, entitled “Impact of Resistance Training on Balance and Gait in Multiple Sclerosis,” published in the Spring 2010 issue, reported on a prospective study on the impact of an exercise program emphasizing resistance training on balance and gait in people with MS. The results showed that participation in the program improved MS patients' ability to walk and to generate muscular forces during locomotion. We would also like to announce the next IJMSC theme issue, which is planned for Summer 2012. Dr. Ralph Benedict of the State University of New York at Buffalo and Dr. Kathleen Fuchs of the University of Virginia will be guest editors of this issue, entitled “Novel Approaches for Assessing and Facilitating Cognition in MS.” We are particularly interested in pilot data looking at new approaches, but we also welcome reviews and other research pertinent to this topic. The deadline for submissions is February 1, 2012, and we encourage you to submit your work via our website, which can be accessed at MSCARE.org.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".