Feasibility of a Smartphone-Based Exercise Program for Office Workers With Neck Pain: An Individualized Approach Using a Self-Classification Algorithm

Abstract

ObjectiveTo 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). DesignSingle-group, repeated-measures design. SettingThe laboratory and participants' home and work environments. ParticipantsOffices workers with neck pain (N=23; mean age ± SD, 28.13±2.97y; 13 men). InterventionParticipants were classified as having 1 of 4 types of neck pain through a self-classification algorithm implemented as a smartphone application, and conducted corresponding exercise programs for 10 to 12min/d, 3d/wk, for 8 weeks. Main Outcome MeasuresThe visual analog scale (VAS), Neck Disability Index (NDI), Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), Fear-Avoidance Beliefs Questionnaire (FABQ), and cervical ROM were measured at baseline and postintervention. ResultsThe VAS (P<.001) and NDI score (P<.001) indicated significant improvements in pain intensity and functional disability. Quality of life showed significant improvements in the physical functioning (P=.007), bodily pain (P=.018), general health (P=.022), vitality (P=.046), and physical component scores (P=.002) of the SF-36. The FABQ, cervical ROM, and mental component score of the SF-36 showed no significant improvements. ConclusionsThe 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.