Article

OBJECTIVE: 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).
DESIGN: Single-group, repeated-measures design.
SETTING: The laboratory and
participants' home and work environments. PARTICIPANTS: Offices workers with neck
pain (N=23; mean age +/- SD, 28.13+/-2.97y; 13 men). INTERVENTION: Participants
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 MEASURES:
The 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. RESULTS: The 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. CONCLUSIONS: 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.
CI - Copyright (c) 2016 American Congress of Rehabilitation Medicine. Published by
Elsevier Inc. All rights reserved.

Langue : ANGLAIS