Feasibility of a smartphone-based exercise program for office workers with neck pain: An individualized approach using a self-classification algorithm.

The aim of this study was to explore the feasibility of a newly developed smartphone-based exercise program with an embedded self-classification algorithm for office workers with neck pain, by examining its effect on the pain intensity, functional disability, quality of life, fear-avoidance, and cervical range of motion (ROM). Participants were classified into one of four types through a self-classification algorithm implemented as a smartphone application, and conducted corresponding exercise programs for 10-12 min/day, three days/week, for eight weeks. The Visual Analogue Scale (VAS), Neck Disability Index (NDI), Short Form Health Survey (SF-36), Fear-Avoidance Belief Questionnaire (FABQ) and cervical ROM were administered at baseline and post-intervention. The VAS (P < 0.001) and NDI score (P < 0.001) indicated significant improvements in pain intensity and functional disability. Quality of life showed significant improvements in the physical functioning (P = 0.007), bodily pain (P = 0.018), general health (P = 0.022), vitality (P = 0.046), and physical component scores (P = 0.002) of SF-36. The FABQ, cervical ROM, and mental component score of SF-36 showed no significant improvements.

The smartphone-based exercise program with an embedded self-classification algorithm improves the pain intensity and perceived physical health of office workers with neck pain, although not enough to affect their mental and emotional states.

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