Sammenlign metoder

	Rasch Analysis of Disability Measures	Psychosocial Impact of Assistive Devices Scale
Fagområde	Disability Studies	Disability Studies
Familie	Latent structure	Latent structure
Oprindelsesår	2007	2002
Ophavsperson	Georg Rasch (model); Alan Tennant & Philip Conaghan (rehabilitation application)	Jeffrey Jutai & Hy Day
Type	Probabilistic item-response measurement model applied to disability scales	Assistive-device psychosocial-impact measurement scale
Oprindelig kilde	Tennant, A., & Conaghan, P. G. (2007). The Rasch measurement model in rheumatology: What is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis Care & Research, 57(8), 1358-1362.	Jutai, J., & Day, H. (2002). Psychosocial Impact of Assistive Devices Scale (PIADS). Technology and Disability, 14(3), 107-111.
Aliasser	Rasch Measurement Model for Disability, Rasch Analysis of Outcome Measures, Rasch Modeling in Rehabilitation, Rasch Calibration of Disability Scales	PIADS, Psychosocial Impact of Assistive Devices Scale, Assistive Device Psychosocial Impact Measure
Relaterede	3	3
Resumé	Rasch analysis is a psychometric method, based on Georg Rasch's probabilistic measurement model, used to test and refine the disability, function, and participation scales that pervade disability and rehabilitation research. As set out for clinicians by Alan Tennant and Philip Conaghan in 2007, fitting the Rasch model checks whether a scale's items genuinely measure a single underlying trait at interval level, so that summing item scores into a total is justified. Because so many disability outcome measures simply add ordinal item ratings — assuming items are equally difficult and that ordinal categories behave like interval data — Rasch analysis provides the rigorous test of whether that common practice is actually valid.	The Psychosocial Impact of Assistive Devices Scale (PIADS) measures how an assistive device affects a user's quality of life, not whether they are satisfied with it or what it lets them physically do. Developed by Jeffrey Jutai and Hy Day, the 26-item self-report scale captures the device's perceived effect across three dimensions: competence (feelings of efficacy and usefulness), adaptability (willingness to try new things and take part), and self-esteem (emotional well-being and confidence). Each item is rated on a bipolar scale from a strong decrease to a strong increase, so the instrument registers whether a device improves, leaves unchanged, or harms the user's psychosocial functioning — a distinctively quality-of-life-oriented assistive-technology outcome.