Telemedicine versus conventional care for nonspecific neck pain: a randomized controlled study

远程医疗与传统治疗非特异性颈痛的比较:一项随机对照研究

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Abstract

BACKGROUND/AIM: Telemedicine (TM) can overcome travel barriers in nonspecific neck pain (NNP), yet a comprehensive, physiatrist-supervised TM model has not been directly compared to standard in-clinic care. The aim of this study was to determine whether a video-based exercise and remote follow-up program is as effective as conventional follow-up in reducing pain and disability in NNP. MATERIALS AND METHODS: This parallel-group randomized controlled trial (registered in ClinicalTrials.gov) included 68 adults (mean age = 40.52 years) with NNP who were randomly allocated 1:1 to the TM group (TG, n = 34) or control group (CG, n = 34). Both received identical exercises via prerecorded video (TG) or printed brochure (CG) to be performed for 3 months. TG visits were via video call; CG visits were in the clinic. Primary outcomes were pain measured by the visual analog scale (VAS) at baseline, day 15, month 1, and 3, and disability measured by the neck disability index (NDI) at baseline and month 3. Secondary outcomes were exercise adherence, patient satisfaction, and travel/time burden. Analyses followed the intention-to-treat principle using linear mixed models. RESULTS: Both groups achieved clinically important VAS reductions (TG: 6.56 to 3.02, CG: 6.44 to 2.96). The only between-group difference appeared at day 15, favoring CG (p = 0.038) and the group × time interaction was nonsignificant overall (p = 0.111). NDI improved similarly in both groups (p = 0.473). Adherence in TG and CG (67.90% and 71.21%, respectively) and satisfaction (4.25 and 4.42, respectively) were comparable. TG participants avoided a mean of 38.88 km/175.74 min of travel across 3 virtual visits. CONCLUSION: A structured TM program with remote physiatrist follow-up matches conventional outpatient care in managing NNP. Larger, long-term studies should define optimal support and assess cost effectiveness across diverse populations.

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