3 results on '"Eijssen, I. C. J. M."'
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2. Three distinct physical behavior types in fatigued patients with multiple sclerosis
- Author
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Braakhuis, H. E. M., Berger, M. A. M., van der Stok, G. A., van Meeteren, J., de Groot, V., Beckerman, H., Bussmann, J. B. J., Malekzadeh, A., van den Akker, L. E., Looijmans, M., Sanches, S. A., Dekker, J., Collette, E. H., van Oosten, B. W., Teunissen, C. E., Blankenstein, M. A., Eijssen, I. C. J. M., Rietberg, M., Heine, M., Verschuren, O., Kwakkel, G., Visser-Meily, J. M. A., van de Port, I. G. L., Lindeman, E., Blikman, L. J. M., Stam, H. J., Hintzen, R. Q., Hacking, H. G. A., Hoogervorst, E. L., Frequin, S. T. F. M., Knoop, H., de Jong, B. A., Bleijenberg, G., de Laat, F. A. J., Verhulsdonck, M. C., van Munster, E. Th L., Oosterwijk, C. J., Aarts, G. J., Academic Medical Center, Rehabilitation Medicine, Neurology, Pediatrics, Urology, Immunology, Gastroenterology & Hepatology, Erasmus School of Health Policy & Management, APH - Societal Participation & Health, APH - Methodology, APH - Mental Health, APH - Aging & Later Life, AMS - Rehabilitation & Development, MOVE Research Institute, Amsterdam Movement Sciences - Restoration and Development, APH - Quality of Care, and APH - Health Behaviors & Chronic Diseases
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Adult ,Male ,030506 rehabilitation ,medicine.medical_specialty ,Neurology ,Evening ,Multiple Sclerosis ,Adolescent ,medicine.medical_treatment ,Psychological intervention ,Health Informatics ,multiple sclerose ,hoofdcomponentenanalyse ,lcsh:RC321-571 ,03 medical and health sciences ,clusteranalyse ,Young Adult ,Cluster analysis ,Accelerometry ,medicine ,Humans ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Fatigue ,Aged ,Behavior ,Principal Component Analysis ,Rehabilitation ,business.industry ,Multiple sclerosis ,Research ,Middle Aged ,medicine.disease ,Checklist ,Clinical trial ,Cross-Sectional Studies ,Ambulatory ,Physical therapy ,lichamelijk gedrag ,Female ,0305 other medical science ,business ,Physical behavior - Abstract
Background Multiple sclerosis often leads to fatigue and changes in physical behavior (PB). Changes in PB are often assumed as a consequence of fatigue, but effects of interventions that aim to reduce fatigue by improving PB are not sufficient. Since the heterogeneous nature of MS related symptoms, levels of PB of fatigued patients at the start of interventions might vary substantially. Better understanding of the variability by identification of PB subtypes in fatigued patients may help to develop more effective personalized rehabilitation programs in the future. This study aimed to identify PB subtypes in fatigued patients with multiple sclerosis based on multidimensional PB outcome measures. Methods Baseline accelerometer (Actigraph) data, demographics and clinical characteristics of the TREFAMS-ACE participants (n = 212) were used for secondary analysis. All patients were ambulatory and diagnosed with severe fatigue based on a score of ≥35 on the fatigue subscale of the Checklist Individual Strength (CIS20r). Fifteen PB measures were used derived from 7 day measurements with an accelerometer. Principal component analysis was performed to define key outcome measures for PB and two-step cluster analysis was used to identify PB types. Results Analysis revealed five key outcome measures: percentage sedentary behavior, total time in prolonged moderate-to-vigorous physical activity, number of sedentary bouts, and two types of change scores between day parts (morning, afternoon and evening). Based on these outcomes three valid PB clusters were derived. Conclusions Patients with severe MS-related fatigue show three distinct and homogeneous PB subtypes. These PB subtypes, based on a unique set of PB outcome measures, may offer an opportunity to design more individually-tailored interventions in rehabilitation. Trial registration Clinical trial registration no ISRCTN 82353628, ISRCTN 69520623 and ISRCTN 58583714. Electronic supplementary material The online version of this article (10.1186/s12984-019-0573-1) contains supplementary material, which is available to authorized users.
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- 2019
3. Energy Conservation Management for People With Multiple Sclerosis-Related Fatigue: Who Benefits?
- Author
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Blikman, L. J. M., van Meeteren, J., Twisk, Jos W. R., de laat, Fred A. J., de Groot, Vincent, Beckerman, Heleen, Stam, Henk J., Bussmann, Johannes B. J., Malekzadeh, A., van den Akker, L. E., Looijmans, M., Sanches, S. A., Dekker, J., Collette, E. H., van Oosten, B. W., Teunissen, C. E., Blankenstein, M. A., Eijssen, I. C. J. M., Rietberg, M., Heine, M., Verschuren, O., Kwakkel, G., Visser-Meily, J. M. A., van de Port, I. G. L., Lindeman, E., Bussmann, J. B. J., Stam, H. J., Hintzen, R. Q., Hacking, H. G. A., Hoogervorst, E. L., Frequin, S. T. F. M., Knoop, H., de Jong, B. A., Bleijenberg, G., Verhulsdonck, M. C., van Munster, E. T. H. L., Oosterwijk, C. J., Aarts, G. J., Rehabilitation Medicine, Erasmus School of Law, Neurology, Pediatrics, Urology, Immunology, Gastroenterology & Hepatology, Public Health, Erasmus School of Health Policy & Management, Academic Medical Center, Epidemiology and Data Science, Rehabilitation medicine, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Neuroscience - Systems & Network Neuroscience, APH - Methodology, APH - Societal Participation & Health, Amsterdam Movement Sciences - Restoration and Development, and ACS - Atherosclerosis & ischemic syndromes
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medicine.medical_specialty ,Multiple Sclerosis ,media_common.quotation_subject ,MEDLINE ,Disease ,Logistic regression ,law.invention ,03 medical and health sciences ,Social support ,0302 clinical medicine ,Occupational Therapy ,Randomized controlled trial ,law ,Perception ,Medicine ,Humans ,Single-Blind Method ,030212 general & internal medicine ,SDG 7 - Affordable and Clean Energy ,Fatigue ,Research Articles ,media_common ,business.industry ,Checklist ,Ambulatory ,Physical therapy ,Fatigue/physiopathology ,business ,030217 neurology & neurosurgery - Abstract
OBJECTIVE. We investigated whether demographic, disease-related, or personal baseline determinants can predict a positive response to energy conservation management (ECM). METHOD. We conducted a secondary analysis of a single-blind, two-parallel-arms randomized controlled trial that included ambulatory adults with severe MS-related fatigue. Therapy responders and nonresponders were categorized by Checklist Individual Strength fatigue change scores between baseline and end of treatment. Logistic regression analyses were used to assess the determinants of response. RESULTS. Sixty-nine participants were included (ECM group, n = 34; control group, n = 35). In the ECM group, fatigue severity, perception of fatigue, illness cognitions about MS, and social support discrepancies were related to the probability of being a responder. CONCLUSION. The results suggest that people with MS-related fatigue who had a less negative perception of fatigue and who perceived fewer disease benefits and a higher discrepancy in social support had the best response to ECM treatment.
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- 2019
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