Objective: To evaluate the efficacy of a newly developed evidence-based low back pain (LBP) management smartphone application. Design: A double-blinded randomized controlled trial where participants randomly assigned to either an experimental group (EG) or a control group (CG). Setting: Governmental and private institutions. Participants: About 40 office workers, aged 30 to 55 years, had pain due to non-specific LBP > 3 on Visual Analogue Scale, and with pain chronicity > 3 months. Interventions: The EG received full version of the application ‘Relieve my back’ included evidence-based instructions and therapeutic exercises for LBP management, whereas the CG received placebo version included instructions about nutrition. Main measures: Primary outcome measures included pain measured by Visual Analogue Scale (VAS), disability measured by Oswestry Disability Index (ODI), and quality of life measured by Short-Form Health Survey (SF-12). Results: Following six weeks of using the application, compared to CG, the EG group demonstrated significant decrease in pain intensity (−3.45 (2.21) vs −0.11 (1.66), P < 0.001), in ODI score (−11.05 (10.40) vs −0.58 (9.0), P = 0.002), and significant increase in physical component of SF-12 (12.85 (17.20) vs −4.63 (12.04), P = 0.001). Conclusion: ‘Relieve my back’ application might be efficacious in reducing pain and disability and improving the quality of life of office workers with non-specific LBP.

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BackgroundSearch filters aid clinicians and academics to accurately locate literature. Despite this, there is no search filter or Medical Subject Headings (MeSH) term pertaining to paramedics. Therefore, the aim of this study was to create two filters to meet to different needs of paramedic clinicians and academics.MethodsWe created a gold standard from a reference set, which we measured against single terms and search filters. The words and phrases used stemmed from selective exclusion of terms from the previously published Prehospital Search Filter 2.0 as well as a Delphi session with an expert panel of paramedic researchers. Independent authors deemed articles paramedic-relevant or not following an agreed definition. We measured sensitivity, specificity, accuracy and number needed to read (NNR).ResultsWe located 2102 articles of which 431 (20.5%) related to paramedics. The performance of single terms was on average of high specificity (97.1% (Standard Deviation 7.4%), but of poor sensitivity (12.0%, SD 18.7%). The NNR ranged from 1 to 8.6. The sensitivity-maximising search filter yielded 98.4% sensitivity, with a specificity of 74.3% and a NNR of 2. The specificity-maximising filter achieved 88.3% in specificity, which only lowered the sensitivity to 94.7%, and thus a NNR of 1.48.ConclusionsWe have created the first two paramedic specific search filters, one optimised for sensitivity and one optimised for specificity. The sensitivity-maximising search filter yielded 98.4% sensitivity, and a NNR of 2. The specificity-maximising filter achieved 88.3% in specificity, which only lowered the sensitivity to 94.7%, and a NNR of 1.48. A paramedic MeSH term is needed.Electronic supplementary materialThe online version of this article (10.1186/s12911-017-0544-z) contains supplementary material, which is available to authorized users.

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This review reaffirms the need for further research to validate the advantages, disadvantages, and the effects of spinal immobilization on patients' neurological outcomes.