scholarly journals A digital decision support system (selfBACK) for improved self-management of low back pain: a pilot study with 6-week follow-up

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Louise Fleng Sandal ◽  
Cecilie K. Øverås ◽  
Anne Lovise Nordstoga ◽  
Karen Wood ◽  
Kerstin Bach ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Decision Support ◽  
Pilot Study ◽  
Decision Support System ◽  
Support System ◽  
Self Management ◽  
Low Back

scholarly journals A Decision Support System to Enhance Self-Management of Low Back Pain: Protocol for the selfBACK Project (Preprint)

2017 ◽  
Author(s):  
Paul Jarle Mork ◽  
Kerstin Bach
Keyword(s):  
Physical Activity ◽  
Low Back Pain ◽  
Back Pain ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Patient Data ◽  
Self Management ◽  
Low Back ◽  
Design And Implementation

BACKGROUND Low back pain (LBP) is a leading cause of disability worldwide. Most patients with LBP encountered in primary care settings have nonspecific LBP, that is, pain with an unknown pathoanatomical cause. Self-management in the form of physical activity and strength and flexibility exercises along with patient education constitute the core components of the management of nonspecific LBP. However, the adherence to a self-management program is challenging for most patients, especially without feedback and reinforcement. Here we outline a protocol for the design and implementation of a decision support system (DSS), selfBACK, to be used by patients themselves to promote self-management of LBP. OBJECTIVE The main objective of the selfBACK project is to improve self-management of nonspecific LBP to prevent chronicity, recurrence and pain-related disability. This is achieved by utilizing computer technology to develop personalized self-management plans based on individual patient data. METHODS The decision support is conveyed to patients via a mobile phone app in the form of advice for self-management. Case-based reasoning (CBR), a technology that utilizes knowledge about previous cases along with data about the current patient case, is used to tailor the advice to the current patient, enabling a patient-centered intervention based on what has and has not been successful in previous patient cases. The data source for the CBR system comprises initial patient data collected by a Web-based questionnaire, weekly patient reports (eg, symptom progression), and a physical activity-detecting wristband. The effectiveness of the selfBACK DSS will be evaluated in a multinational, randomized controlled trial (RCT), targeting care-seeking patients with nonspecific LBP. A process evaluation will be carried out as an integral part of the RCT to document the implementation and patient experiences with selfBACK. RESULTS The selfBACK project was launched in January 2016 and will run until the end of 2020. The final version of the selfBACK DSS will be completed in 2018. The RCT will commence in February 2019 with pain-related disability at 3 months as the primary outcome. The trial results will be reported according to the CONSORT statement and the extended CONSORT-EHEALTH checklist. Exploitation of the results will be ongoing throughout the project period based on a business plan developed by the selfBACK consortium. Tailored digital support has been proposed as a promising approach to improve self-management of chronic disease. However, tailoring self-management advice according to the needs, motivation, symptoms, and progress of individual patients is a challenging task. Here we outline a protocol for the design and implementation of a stand-alone DSS based on the CBR technology with the potential to improve self-management of nonspecific LBP. CONCLUSIONS The selfBACK project will provide learning regarding the implementation and effectiveness of an app-based DSS for patients with nonspecific LBP. REGISTERED REPORT IDENTIFIER RR1-10.2196/9379

scholarly journals Reducing sedentary behaviour to decrease chronic low back pain: the stand back randomised trial

2018 ◽  
Vol 75 (5) ◽  
pp. 321-327 ◽  
Author(s):  
Bethany Barone Gibbs ◽  
Andrea L Hergenroeder ◽  
Sophy J Perdomo ◽  
Robert J Kowalsky ◽  
Anthony Delitto ◽  
...  
Keyword(s):  
Low Back Pain ◽  
Back Pain ◽  
Sedentary Behaviour ◽  
Chronic Low Back Pain ◽  
Controlled Trial ◽  
Randomised Trial ◽  
Sitting Time ◽  
Self Management ◽  
Low Back

ObjectiveThe Stand Back study evaluated the feasibility and effects of a multicomponent intervention targeting reduced prolonged sitting and pain self-management in desk workers with chronic low back pain (LBP).MethodsThis randomised controlled trial recruited 27 individuals with chronic LBP, Oswestry Disability Index (ODI) >10% and desk jobs (sitting ≥20 hours/week). Participants were randomised within strata of ODI (>10%–<20%, ≥20%) to receive bimonthly behavioural counselling (in-person and telephone), a sit-stand desk attachment, a wrist-worn activity-prompting device and cognitive behavioural therapy for LBP self-management or control. Self-reported work sitting time, visual analogue scales (VAS) for LBP and the ODI were assessed by monthly, online questionnaires and compared across intervention groups using linear mixed models.ResultsBaseline mean (SD) age was 52 (11) years, 78% were women, and ODI was 24.1 (10.5)%. Across the 6-month follow-up in models adjusted for baseline value, work sitting time was 1.5 hour/day (P<0.001) lower comparing intervention to controls. Also across follow-up, ODI was on average 8 points lower in intervention versus control (P=0.001). At 6 months, the relative decrease in ODI from baseline was 50% in intervention and 14% in control (P=0.042). LBP from VAS was not significantly reduced in intervention versus control, though small-to-moderate effect sizes favouring the intervention were observed (Cohen’s d ranged from 0.22 to 0.42).ConclusionAn intervention coupling behavioural counselling targeting reduced sedentary behaviour and pain self-management is a translatable treatment strategy that shows promise for treating chronic LBP in desk-bound employees.Trial registration numberNCT0224687; Pre-results.

scholarly journals The Role of a Decision Support System in Back Pain Diagnoses: A Pilot Study

2019 ◽  
Vol 2019 ◽  
pp. 1-5 ◽  
Author(s):  
Achim Benditz ◽  
Florian Faber ◽  
Gabriela Wenk ◽  
Tina Fuchs ◽  
Natalie Salak ◽  
...  
Keyword(s):  
Back Pain ◽  
Decision Support ◽  
Pilot Study ◽  
Decision Support System ◽  
Support System ◽  
Medical Doctor

It is the main goal of this study to investigate the concordance of a decision support system and the recommendation of spinal surgeons regarding back pain. 111 patients had to complete the decision support system. Furthermore, their illness was diagnosed by a spinal surgeon. The results showed significant medium relation between the DSS and the diagnosis of the medical doctor. Besides, in almost 50% of the cases the recommendation for the treatment was concordant and overestimation occurred more often than underestimation. The results are discussed in relation to the “symptom checker” literature and the claim of further evaluations.

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