Obtaining Experiential Data on Assistive Technology Device Abandonment

There have been few studies of abandonment of Assistive Technology, typically based on surveys and best practices expertise. This paper describes the application of classic experience sampling techniques to gather timely information about mobility aiding assistive technology in day-to-day use especially with respect to causes of abandonment. The paper describes the technical understructure of the system, which uses smartphones to gather, and web services to store, data. Also described is the setup and branching of the question set presented on the smartphone. Beyond details of use of the assistive technology, the system collects a verified scale of responses to determine the emotional affect of the participant. Sampling is taken several times during the day by actively pushing a set of questions that are tailored to the users technology and responses. There is also provision for the participant to push the information to the system when desired.

[1]  Eric Rogers,et al.  Research and development work relating to assistive technology 2007–08: Presented to Parliament pursuant to section 22 of the Chronically Sick and Disabled Persons Act 1970 , 2008 .

[2]  B Phillips,et al.  Predictors of assistive technology abandonment. , 1993, Assistive technology : the official journal of RESNA.

[3]  Chris Lonsdale,et al.  Measurement tools for adherence to non-pharmacologic self-management treatment for chronic musculoskeletal conditions: a systematic review. , 2015, Archives of physical medicine and rehabilitation.

[4]  A. Vanbiervliet,et al.  Predictors of assistive technology use: The importance of personal and psychosocial factors , 2005, Disability and rehabilitation.

[5]  Drew Tiene,et al.  Adoption of Assistive Technology for computer access among college students with disabilities , 2002, Disability and rehabilitation.

[6]  Abigail J. Moss,et al.  The prevalence of need for assistive technology devices and home accessibility features , 1997 .

[7]  M. Csíkszentmihályi,et al.  Experience Sampling Method: Measuring the Quality of Everyday Life , 2006 .

[8]  M. Tremblay,et al.  A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review , 2008, The international journal of behavioral nutrition and physical activity.

[9]  Jan C. Galvin,et al.  Educating the consumer and caretaker on assistive technology. , 2002 .

[10]  E. Thompson.  Development and Validation of an Internationally Reliable Short-Form of the Positive and Negative Affect Schedule (PANAS) , 2007 .

[11]  Edward J. Hamilton,et al.  Living in the State of Stuck: How Technology Impacts the Lives of People with Disabilities. , 1997 .

[12]  Joost Dekker,et al.  Prevalence of hand symptoms, impairments and activity limitations in rheumatoid arthritis in relation to disease duration. , 2010, Journal of rehabilitation medicine.

[13]  Marti L. Riemer-Reiss,et al.  Assistive Technology Use and Abandonment among College Students with Disabilities, 3(23) , 1999 .

[14]  M. Battaglia,et al.  An interdisciplinary approach to evaluating the need for assistive technology reduces equipment abandonment , 2006, Multiple sclerosis.

[15]  D. Watson,et al.  Development and validation of brief measures of positive and negative affect: the PANAS scales. , 1988, Journal of personality and social psychology.

[16]  J. Wyatt,et al.  Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide , 2014, BMJ : British Medical Journal.

[17]  Joel M. Hektner,et al.  Experience sampling method , 2007 .