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Rasch Analysis of the Stroke Impact Scale-16
CONCLUSIONS AND RELEVANCE: Results partially support the validity and clinical use of the SIS-16 in subacute stroke clinical settings. Further research is warranted to examine the psychometric properties of the SIS-16 in patients with chronic stroke. What This Article Adds: Our results partially support the use of the SIS-16 in clinical and research settings.PMID:36548001 | DOI:10.5014/ajot.2022.049335
Source: The American Journal of Occupational Therapy - December 22, 2022 Category: Occupational Health Authors: Inga Wang Yi-Ching Wang Tzu-Yi Wu Chia-Yeh Chou Ching-Lin Hsieh Source Type: research
Burdens on caregivers of patients with stroke during a pandemic: relationships with support satisfaction, psychological distress, and fear of COVID-19
Caregivers have faced unprecedented circumstances throughout the COVID-19 pandemic, but previous research only minimally addresses the caregivers' burden. Therefore, this study aimed to investigate the relatio...
Source: BMC Geriatrics - December 13, 2022 Category: Geriatrics Authors: Chieh-hsiu Liu, Yi-Jung Chen, Jung-Sheng Chen, Chia-Wei Fan, Meng-Tsang Hsieh, Chung-Ying Lin and Amir H. Pakpour Tags: Research Source Type: research
IJERPH, Vol. 19, Pages 16514: Predictors for Upper-Limb Functional Recovery Trajectory in Individuals Receiving Stroke Rehabilitation: A Secondary Analysis of Data from Randomized Controlled Trials
Conclusion: These findings may assist healthcare professionals in making optimal therapeutic decisions and in informing clients and caregivers about the outcomes of stroke recovery.
Source: International Journal of Environmental Research and Public Health - December 8, 2022 Category: Environmental Health Authors: Batsaikhan Buyandelger Yu-Wen Chen Yi-Chun Li Chia-Jung Lin Chia-Ling Chen Keh-Chung Lin Tags: Article Source Type: research
Development of a Short-Form Stroke Impact Scale Using a Machine Learning Algorithm for Patients at the Subacute Stage
CONCLUSIONS AND RELEVANCE: The ML-SIS uses about half of the items in the SIS 3.0, has an estimated administration time of 10 min, and provides valid scores comparable to those of the original measure. Thus, the ML-SIS may be an efficient alternative to the SIS 3.0. What This Article Adds: The ML-SIS, a short form of the SIS 3.0 developed using a machine learning algorithm, shows good potential to be an efficient and informative measure for clinical settings, providing scores that are valid and comparable to those of the original measure.PMID:36410404 | DOI:10.5014/ajot.2022.049136
Source: The American Journal of Occupational Therapy - November 21, 2022 Category: Occupational Health Authors: Shih-Chieh Lee Inga Wang Gong-Hong Lin Pei-Chi Li Ya-Chen Lee Chia-Yeh Chou Chien-Yu Huang Ching-Lin Hsieh Source Type: research
