Objectives: To evaluate a method for collecting data concerning low back pain (LBP) using daily text messages and to characterize the reported LBP in terms of intensity, variability, and episodes.
Study design and setting: We conducted a cohort study of LBP among workers used by a mining company. The participants were asked to answer the question "How much pain have you had in your lower back in the last 24 hours on a scale from 0 to 10, where 0 = no pain and 10 = the worst pain imaginable" once a day for 5 weeks, with this process being repeated 6 months later.
Results: A total of 121 workers participated in the first period of data collection, and 108 participated in the second period. The daily response rate was 93% for both periods, and cluster analysis was shown to be a feasible statistical method for clustering LBP into subgroups of low, medium, and high pain. The daily text messages method also worked well for assessing the episodic nature of LBP.
Conclusion: We have demonstrated a method for repeatedly measuring of LBP using daily text messages. The data permitted clustering into subgroups and could be used to define episodes of LBP.
Keywords: Cluster analysis; Episode; Low back pain; Pain intensity; Temporal characteristics; Text messaging.
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