Model Simulations Challenge Reductionist Research Approaches to Studying Chronic Low Back Pain.
Jacek Cholewicki, Pramod K Pathak, N Peter Reeves and 1 others
PMID 31092125WHAT IT FOUND
A computer model of chronic low back pain suggests that when more than 11 factors contribute, less than 1% of simulated patients can be grouped by one dominant factor, and treating two or more factors may be more effective at population level.
Key findings
01In the simulation, when more than 11 factors contribute, less than 1% of the low back pain population can be subclassified by a single factor reaching a 20% contribution threshold.
02On average, the combined contribution of any two or more factors was greater than the largest single factor for each simulated individual.
03The model indicated that a multimodal intervention addressing any two or more factors would likely be more effective in the population of patients with low back pain than treating one dominant factor.
STILL TO COME
How it was doneWhat they foundWhat it means for PTs
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What it does not show
The study used simulated individuals, not real patients, so it cannot show what treatments work. It assumed all contributing factors were equally likely across the population. It assumed each factor acted independently and was directly linked to low back pain. It assumed treatments completely eliminated the targeted factors, which is not how real interventions behave.
Declared interests
The authors declared no affiliations with or financial involvement in any organization or entity with a direct financial interest in the subject matter or materials.
The easy way to misread this
Do not read this as a trial showing multimodal treatment works. It simulated idealized treatments that completely eliminated factors, not real clinical outcomes.