Factors Influencing Therapists' Adoption of Virtual Reality for Brain Injury Rehabilitation

Virtual reality (VR) is an important emerging technology that is increasingly being introduced in health centers as a rehabilitation intervention. Quantitative research is needed to identify the factors influencing therapists' adoption of VR for brain injury rehabilitation, including barriers and facilitators to VR use, in order to inform successful implementation strategies. A measure based on the decomposed theory of planned behavior (DTPB) was developed and administered to 42 therapists; early psychometric properties are reported. Mean or median composite scores and correlations were calculated for each DTPB construct. Overall, therapists had positive attitudes toward VR, perceived it as being useful, and had positive intentions to use it more in the future. The self-efficacy composite yielded the lowest scores. The most significant barrier to adoption was time, while social influences and knowledge were the primary facilitators. Future research will explore the impact of knowledge translation interventions on these mediators of VR adoption.

[1]  Kieran Mathieson,et al.  Predicting User Intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior , 1991, Inf. Syst. Res..

[2]  Mark Hallett,et al.  Cortical reorganization and associated functional motor recovery after virtual reality in patients with chronic stroke: an experimenter-blind preliminary study. , 2005, Archives of physical medicine and rehabilitation.

[3]  J. McComas,et al.  Benefits of activity and virtual reality based balance exercise programmes for adults with traumatic brain injury: Perceptions of participants and their caregivers , 2005, Brain injury.

[4]  Katherine M. White,et al.  Utilizing the Theory of Planned Behavior to Inform Change Management , 2008 .

[5]  E. A. Attree,et al.  Virtual Reality: A New Prosthesis for Brain Injury Rehabilitation , 1998, Scottish medical journal.

[6]  Heidi Sveistrup,et al.  Motor rehabilitation using virtual reality , 2004, Journal of NeuroEngineering and Rehabilitation.

[7]  Patrice L. Weiss,et al.  Video capture virtual reality: A decade of rehabilitation assessment and intervention , 2009 .

[8]  M. Conner,et al.  Applying an extended version of the Theory of Planned Behaviour to physical activity , 2003, Journal of sports sciences.

[9]  A. Bandura.  Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychology Review.

[10]  David Geerts,et al.  Videogames in therapy: a therapist's perspective , 2010, Fun and Games '10.

[11]  Ya-Ming Shiue,et al.  Investigating the Sources of Teachers' Instructional Technology Use Through the Decomposed Theory of Planned Behavior , 2007 .

[12]  Hamza Niaz,et al.  Investigating the possible role and usefulness of video capture virtual reality in motor impairment rehabilitation , 2011, The 2nd International Conference on Next Generation Information Technology.

[13]  L. Portney,et al.  Foundations of Clinical Research: Applications to Practice , 2015 .

[14]  Maureen K. Holden,et al.  Virtual Environments for Motor Rehabilitation: Review , 2005, Cyberpsychology Behav. Soc. Netw..

[15]  Danielle Levac,et al.  Facilitating clinical decision-making about the use of virtual reality within paediatric motor rehabilitation: Describing and classifying virtual reality systems , 2011, Developmental neurorehabilitation.

[16]  A. Colman,et al.  Optimal number of response categories in rating scales: reliability, validity, discriminating power, and respondent preferences. , 2000, Acta psychologica.

[17]  Peter A. Todd,et al.  Assessing IT usage: the role of prior experience , 1995 .

[18]  Rachel Kizony,et al.  Using video-capture virtual reality for children with acquired brain injury , 2011, Disability and rehabilitation.

[19]  D. Cervone,et al.  Self-efficacy theory of behavioral change: Foundations, conceptual issues, and therapeutic implications. , 1995 .

[20]  S. Dean,et al.  Theory development and a science of rehabilitation , 2005, Disability and rehabilitation.

[21]  Inga Carboni,et al.  On Measuring Individual Knowledge in Organizations , 2007 .

[22]  Sung Ho Jang,et al.  Use of Virtual Reality to Enhance Balance and Ambulation in Chronic Stroke: A Double-Blind, Randomized Controlled Study , 2009, American journal of physical medicine & rehabilitation.

[23]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[24]  Susan M. Jegley,et al.  Clinician perceptions of virtual reality to assess and treat returning veterans. , 2010, Psychiatric services.

[25]  M. Hallett,et al.  Virtual Reality–Induced Cortical Reorganization and Associated Locomotor Recovery in Chronic Stroke: An Experimenter-Blind Randomized Study , 2005, Stroke.

[26]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[27]  Chao-Min Chiu,et al.  Predicting electronic service continuance with a decomposed theory of planned behaviour , 2004, Behav. Inf. Technol..

[28]  Noomi Katz,et al.  Video capture virtual reality as a flexible and effective rehabilitation tool , 2004, Journal of NeuroEngineering and Rehabilitation.

[29]  I. Ajzen,et al.  Prediction of goal directed behaviour: Attitudes, intentions and perceived behavioural control , 1986 .

[30]  I. Ajzen.  The theory of planned behavior , 1991 .

[31]  Snunith Shoham,et al.  Intentions of Hospital Nurses to Work With Computers: Based on the Theory of Planned Behavior , 2008, Computers, informatics, nursing : CIN.

[32]  Patrice L. (Tamar) Weiss,et al.  Evaluation of virtual shopping in the VMall: Comparison of post-stroke participants to healthy control groups , 2007, Disability and rehabilitation.

[33]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[34]  P. Weiss,et al.  Training Caregivers to Provide Virtual Reality Intervention for Adults With Severe Intellectual and Developmental Disability , 2011 .

[35]  Oscar Gutierrez,et al.  Information technology acceptance in the social services sector context: an exploration. , 2007, Social work.

[36]  E. Bisson,et al.  Outcomes of intervention programs using flatscreen virtual reality , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[37]  J. Whyte.  A grand unified theory of rehabilitation (we wish!). The 57th John Stanley Coulter Memorial Lecture. , 2008, Archives of physical medicine and rehabilitation.

[38]  M. Mazis,et al.  Determinants of scale response: Label versus position. , 1978 .

[39]  Hsiu-Fen Lin,et al.  Understanding Behavioral Intention to Participate in Virtual Communities , 2006, Cyberpsychology Behav. Soc. Netw..

[40]  Min Ho Chun,et al.  The Effect of Virtual Reality Training on Unilateral Spatial Neglect in Stroke Patients , 2011, Annals of rehabilitation medicine.

[41]  Charles D. Barrett.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[42]  Yogesh Kumar Dwivedi,et al.  Investigating Factors Influencing Adoption of Broadband in the Household , 2006, J. Comput. Inf. Syst..

[43]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[44]  Abdelkader Gouaïch,et al.  Mixed Reality as a Means to Strengthen Post-stroke Rehabilitation , 2011, HCI.

[45]  E. S. Casper.  The theory of planned behavior applied to continuing education for mental health professionals. , 2007, Psychiatric services.

[46]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[47]  Paul Jen-Hwa Hu,et al.  Information Technology Acceptance by Individual Professionals: A Model Comparison Approach , 2001, Decis. Sci..

[48]  M. Schurr,et al.  Virtual reality: feasibility of implementation in a regional burn center. , 2009, Burns : journal of the International Society for Burn Injuries.