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

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.

Scott BuxtonResearch article posted by: Scott Buxton

My name is Scott and I am currently the editor of physiospot.

Away from the keyboard I am extended scope physiotherapist working in ED and an acute frailty unit specialising in rapid assessment and discharge of acutely unwell frail older people.

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