Phantom limb pain (PLP) is intractable to treatment. Sensory discrimination training (SDT) is a non-pharmacological treatment, which shows potential promise for PLP, but robust clinical trials are lacking. This thesis aimed to develop a robust RCT protocol to investigate the efficacy of an automated, self-management SDT device (SP1X) for the treatment of PLP.
Three studies contributed to the development of an RCT protocol to investigate the efficacy of SP1X. Firstly, a qualitative study explored participants perceptions of PLP self-management. Secondly, a systematic review investigated the efficacy and safety of SDT for chronic musculoskeletal pain conditions. Thirdly, a measurement study investigated the psychometric properties of key outcome measures for use with the PLP population.
Participants experiences of self-management of PLP were positive highlighting self-management as an acceptable and feasible approach. The systematic review found SDT does not appear to be associated with any adverse effects and shows potential regarding its clinical efficacy. However, high-quality evidence upon which to make firm clinical recommendations was lacking. The measurement study found three outcome measures for pain intensity, and one for quality of life, possessed acceptable psychometric properties for use in future research trials. Two sensorimotor outcome measures required further development and subsequent psychometric testing prior to use in future research trials.
Conclusions and implications:
Self-management strategies are an acceptable and feasible approach that could be incorporated into the lives of people with PLP. SDT has the potential to be safe and effective for PLP. Existing outcome measures for pain are sufficiently reliable for use in PLP research but should be interpreted cautiously on an individual patient level. This thesis developed a robust protocol to investigate the efficacy of SP1X. The protocol now needs to be undertaken to investigate the efficacy of SP1X before any recommendations on its use can be made.
|Date of Award||31 Jul 2022|
|Supervisor||Cormac Ryan (Supervisor), Alasdair MacSween (Supervisor) & Denis Martin (Supervisor)|