A new study from the University of Warwick in the UK has demonstrated that the patient can effectively determine their own back pain using mobile app compared to current paper methods.
The study conducted by the University of Warwick has proved that digital versions of established measurements for evaluating back pain are reliable and responsive, enabling to expand the use of these versions by patients for routine measurements and clinical trials.
Researchers have developed mobile app versions with commonly-used measures in back pain trials, including Roland Morris Disability Questionnaire (RMDQ), visual analogue scale (VAS) of pain intensity, and numerical rating scale (NRS).
The versions have been developed through taking support from the University of Warwick Higher Education Innovation Fund.
Researchers have taken reliability and responsiveness as factors to assess the potential of mobile app versions.
Reliability is attributed to the result of the measure not changing when nothing has changed, while responsiveness refers to a change in the result when a measurable factor has changed.
In the study, the researchers divided participants into groups based on whether they had recorded a change in their pain.
People already secured treatment for their condition and improved, tested for the responsiveness with the apps. People with chronic pain, and less likely to improve, tested the apps for reliability.
According to researchers, Digital tests offer multiple advantages over paper-based versions, including low cost, lower carbon footprint and better information security.
The University of Warwick clinical trials unit lead author Dr Robert Froud said: “We have taken existing outcome measures and shown that they can be migrated to digital media and used in that format just as effectively as their paper-based versions.
“Our intention is to develop technology that allows people to securely complete these kinds of assessments on their own phones and tablets in a way that is safe, secure and accurate.”
“If you can accurately monitor in clinical practice what’s happening to patients’ health, then analytically there is a lot that could be done with the data that will benefit patients. For example, we may be able to detect that particular treatment approaches are working better for certain types of people.”