The Efficacy and Safety of Telerehabilitation for Fibromyalgia: Systematic Review and Meta-analysis of Randomized Controlled Trials

Introduction

Background

Fibromyalgia is a common chronic pain syndrome characterized by persistent and widespread musculoskeletal pain that is usually accompanied by sleep disruption, fatigue, cognitive dysfunctions, and depressed mood [1,2]. The persistent physical and psychological symptoms of fibromyalgia lead to a decrease in patients’ quality of life (QoL) and cause a huge economic burden on their families and society [3,4]. The main goals of fibromyalgia treatment are to reduce symptoms, maintain function, and improve QoL. Various treatments have been recommended for the management of fibromyalgia, such as medication, exercise, education, and psychotherapy [5-7]. However, patients with fibromyalgia require long-term clinical management and follow-up [8].

Telerehabilitation is defined as “the provision of rehabilitation services through information and telecommunications technology” [9,10], which can provide the assessment, intervention, supervision, education, monitoring, consultation, and prevention of disease [11]. Telerehabilitation can effectively facilitate real-time communication between patients and health care providers and increase patients’ access to medical help from specialized physicians and therapists [12,13]. Telerehabilitation also can tailor long-term and ongoing telerehabilitation services according to the needs of the patients [14]. Telerehabilitation has been widely used in the management of neurological [14], cardiorespiratory [15], and musculoskeletal disorder [16]. In particular, telerehabilitation has been recommended for managing chronic pain worldwide during the current COVID-19 pandemic situation [17].

With the rapid development of telecommunication technology, a number of randomized controlled trials (RCTs) on the application of telerehabilitation in patients with fibromyalgia have been published recently. For example, Hernando-Garijo et al [18] suggested that video-guided, aerobic exercise–based telerehabilitation could effectively reduce pain and improve psychological distress in patients with fibromyalgia. Lee et al [19] made remote real-time pain monitoring and rehabilitation interventions for fibromyalgia using wearable device. In addition, Molinari et al [20] and Yuan et al [21] found a positive effect of a mobile app or multimedia interactive system–based telerehabilitation intervention on individuals with fibromyalgia. However, few systematic reviews have summarized the characteristics, efficacy, and safety of telerehabilitation in fibromyalgia. According to our knowledge, only one review by Bernardy et al [22] has investigated the effects of internet-delivered psychotherapy in individuals with fibromyalgia. However, this study only focused on internet-delivered psychotherapy and ignored other types of telerehabilitation services, such as mobile apps, videoconferencing, web-based education, and wearable devices.

Objectives

Therefore, this study aimed to perform a comprehensive systematic review and meta-analysis of the efficacy and safety of telerehabilitation in patients with fibromyalgia.

Methods

This study was carried out by adhering to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and was registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022338200).

Search Strategy

The PubMed, PEDro, Web of Science, ScienceDirect, Ovid MEDLINE, Cochrane Library, and Embase electronic databases were searched from inception to November 13, 2022. The following keywords and their combinations were used for the literature search: “Telerehabilitation,” “Telemedicine,” “eHealth,” “Videoconferencing,” “Wireless Technology,” “Mobile Health,” “Computer Communication Networks,” “Internet-Based Intervention,” “Fibromyalgia Syndrome,” and “Fibromyalgia.” The detailed search strategy is described in Multimedia Appendix 1. Furthermore, we manually searched the reference lists of eligible studies to identify additional studies.

Study Selection Criteria

Two independent researchers (YQW and Y Long) selected studies following the framework of Population, Intervention, Comparison, Outcomes, and Study Design. Any divergence during the screening process was resolved through consultation between the 2 researchers. If there was still no agreement, a third independent researcher (WJP) decided after group discussion.

All potentially eligible studies were screened following the pre-established criteria. The inclusion criteria were as follows: (1) RCTs; (2) patients were adults aged ≥18 years with a diagnosis of fibromyalgia according to the American College of Rheumatology criteria; (3) the intervention of the experiment group was telerehabilitation, with no restrictions on the specific modality of technology and the content of telerehabilitation; and (4) the control group received non-telerehabilitation including usual care, waiting list, no intervention, or conventional face-to-face treatment. The exclusion criteria were as follows: (1) the study was a case report, conference abstract, or review article; (2) the study was not published in English; and (3) the study only compared different types of telerehabilitation.

Data Extraction

Two investigators (YQW and XMP) independently completed the data extraction. The data included the first author, the year of publication, sample size, study design, characteristics of the participants (gender, age, diagnosis, duration of symptoms, etc), interventions, and outcome measures. When data were lacking, we tried to contact the corresponding author to obtain missing data. If there was a divergence between the reviewers, it was resolved by consultation with a third independent researcher (Y Luo).

Methodological Quality Assessment

Two independent reviewers (CG and YQL) assessed the methodological quality using the Cochrane Risk of Bias Tool [23]. The tool includes the following domains: (1) sequence generation (selection bias), (2) allocation concealment (selection bias), (3) blinding of participants and personal (performance bias), (4) blinding of outcome assessment (detection bias), (5) incomplete outcome data (attrition data), (6) selective reporting (reporting bias), and (7) other sources of bias.

Outcome Measures

Efficacy outcomes were evaluated using the Fibromyalgia Impact Questionnaire (FIQ) scale; pain intensity (eg, the Visual Analog Scale [VAS] and Brief Pain Inventory [BPI]); depression (eg, the Patient Health Questionnaire, the Beck Depression Inventory, the Center for Epidemiological Studies Depression Scale, and the Hospital Anxiety and Depression Scale-Depression); pain catastrophizing (Pain Catastrophizing Scale [PCS]); and QoL (Short Form Health Survey and the EQ-5D). Safety outcomes were evaluated based on adverse events.

Statistical Analysis

The statistical analysis was performed using the Stata software (version 15.1 SE; StataCorp). If outcomes were measured using different scales, we used the standardized mean difference (SMD) and 95% CI. Otherwise, when outcomes were measured using the same scales, we used the weighted mean difference (WMD) and 95% CI. Statistical heterogeneity was evaluated using the I² statistic [24]. I² values >75% indicated high levels of heterogeneity, I² values ≥50% indicated medium levels of heterogeneity, and I² values >25% indicated low levels of heterogeneity. If I²≥50%, we used the random effects model. Otherwise, we used the fixed effects model for data analysis. For the results of ≥10 included studies, publication bias in the meta-analysis was detected by performing Egger regression test and Begg rank correlation test [25,26].

Results

Study Inclusion

In total, 1382 records were identified from the 7 databases. After removing duplicates, screening the titles and abstracts, and reviewing the full-text, 1368 articles were excluded and 14 studies were considered eligible for this systematic review and meta-analysis [18-21,27-36] (Figure 1).

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Study Characteristics

Table 1 summarizes the main clinical characteristics of the included studies. The 14 RCTs included 1242 participants diagnosed with fibromyalgia. The mean age of the participants ranged from 39.7 to 55.5 years. The duration of the symptoms ranged from 6.21 to 20 years. The control intervention of the included studies involved a waiting list [30-32], usual care or treatment [18,19,27,28,33,35,36], pharmacologic therapy [29], daily activity [20], standard follow-up [34], and paper-based instruction [21]. The 14 RCTs reported different outcomes: 12 studies measured the FIQ scale [18-21,29-36], 8 assessed pain intensity [18,19,21,27,28,31,32,36], 11 assessed depression [18-20,27,28,30-33,35,36], 3 assessed pain catastrophizing [18,20,33], and 6 assessed QoL [19,28,31,34-36] (Table 1).

Table 2 summarizes the detailed protocols of telerehabilitation among the included studies. Regarding the medium of telerehabilitation, 8 studies used internet-based telerehabilitation [20,28,29,31-33,35,36], 5 used telephone- or mobile app–based telerehabilitation [18,21,27,30,34], and 1 used a wearable device to monitor and record real-time pain [19]. In terms of telerehabilitation programs, 6 studies used psychological interventions–based telerehabilitation [20,27,29,30,32,33], 2 used fibromyalgia self-management–based telerehabilitation [21,28], 3 used video-based guided exercise training telerehabilitation [18,35,36], 1 used a web-based pain course–based telerehabilitation [31], 1 provided real-time pain monitoring by a monitoring system [19], and 1 study provided web-based teleconsultation [34].

Results From Quality Assessments

The risk of bias assessment according to the Cochrane criteria is shown in Figures 2 and 3. All trials reported a randomized method, providing a random sequence generation method, and one trial [36] reported an unclear allocation concealment method. One trial [33] was not blinded to the outcome assessment, and 5 trials [19,27,29,31,36] did not elaborate on whether the outcome assessment was blinded. Only three [20,29,32] of the 14 trials did not explicitly report whether they blinded the subjects. In addition, only 2 trials [27,33] mentioned dropout, but only 1 trial [27] did not elaborate on information processing.

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Effect of Telerehabilitation on the FIQ Scale

Twelve studies with 1076 participants [18-21,29-36] reported FIQ scale data. Owing to the existence of medium heterogeneity (I²=59.9%; P=.004), a random effects model was used. A meta-analysis showed that telerehabilitation had significantly reduced the FIQ scale score compared to the control group (WMD –8.32, 95% CI –11.72 to –4.91; P<.001; Figure 4).

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Effect of Telerehabilitation on Pain Intensity

Eight studies with 769 participants assessed pain intensity. Four studies used the VAS [18,19,21,36], 2 used FIQ-pain [27,32], and 2 used the BPI [28,31]. Due to the low heterogeneity (I²=0%; P=.61), a fixed effects model was used in the meta-analysis (Figure 5). The pooled results indicated that telerehabilitation had significantly improved pain intensity compared to the control group (SMD –0.62, 95% CI –0.76 to –0.47; P<.001).

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Effect of Telerehabilitation on Depression

Eleven studies with 1058 participants assessed the depression levels. Two studies used the Patient Health Questionnaire [27,32], 2 used the Center for Epidemiological Studies Depression Scale [28,33], 3 used the Beck Depression Inventory [19,20,30], and 4 used the Hospital Anxiety and Depression Scale-Depression scale [18,31,35,36]. Due to the medium heterogeneity (I²=51.7%; P=.02), pooled results under a random effects model (Figure 6) indicated that telerehabilitation reduced the depression levels of patients with fibromyalgia (SMD –0.42, 95% CI –0.62 to –0.22; P<.001).

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Effect of Telerehabilitation on Pain Catastrophizing

Pain catastrophizing was measured using the PCS. Three studies with 139 participants reported PCS data [18,20,30]. Because of the low heterogeneity (I²=40.2%; P=.19), a fixed effects model was used in the meta-analysis (Figure 7). The pooled results showed that telerehabilitation had significantly reduced PCS scores compared to the control group (WMD –5.81, 95% CI –9.40 to –2.23; P=.001).

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Effect of Telerehabilitation on QoL

Six studies with 764 participants assessed QoL. The QoL was assessed using the Short Form Health Survey in 5 studies [28,31,34-36] and the EQ-5D in 1 study [19]. In these studies, we found no significant heterogeneity in the QoL (I²=0%; P=.56). Pooled results under a fixed effects model (Figure 8) indicated that telerehabilitation had significantly improved the QoL compared with the control group (SMD 0.32, 95% CI 0.18 to 0.47; P<.001).

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Adverse Events

Only 1 RCT [32] reported an adverse event; the other 13 RCTs did not mention it. Hedman-Lagerlöf et al [32] reported that 34% of participants who received internet-based telerehabilitation experienced mild pain, but regression analysis showed no significant relationship between adverse events and telerehabilitation intervention.

Publication Bias

No publication bias was found for the FIQ (Egger: P=.11; Begg: P=.30) and depression (Egger: P=.44; Begg: P=.44) in the funnel plot (Multimedia Appendix 2).

Discussion

Principal Findings

The aim of this meta-analysis was to summarize the current evidence about the efficacy and safety of telerehabilitation for patients with fibromyalgia. The results of this meta-analysis indicated that telerehabilitation can improve the FIQ score, pain intensity, depression, and QoL in patients with fibromyalgia compared to control interventions (eg, waiting list, pharmacologic therapy, and other active nonpharmacological therapies). Importantly, we also considered another important factor applied to patients with fibromyalgia: the safety of telerehabilitation. Only 1 study of the included studies reported mild adverse events after telerehabilitation [32]. Therefore, the evidence is not yet sufficient to draw firm conclusions about the safety of telerehabilitation for patients with fibromyalgia.

The key to whether telerehabilitation can be applied in patients with fibromyalgia is considering the clinical significance and the economic and social benefits. Our results indicate that telerehabilitation can effectively alleviate the symptoms in patients with fibromyalgia. Meanwhile, there are a lot of potential advantages of telerehabilitation, such as improving the efficiency of health professionals and providing people with various health care resources (eg, knowledge, fibromyalgia education, and exercise guidance) about fibromyalgia and personalized rehabilitation recommendations [38]. More importantly, telerehabilitation can overcome geographical barriers and provide medical care services to people in rural and remote communities and patients with fibromyalgia who cannot attend traditional face-to-face rehabilitation services, which is especially essential during the COVID-19 pandemic [39]. In addition, although none of the included studies in this meta-analysis reported cost-effectiveness, several previous studies have demonstrated that telerehabilitation can reduce the monetary and time costs of rehabilitation services [40,41].

Comparison With Prior Work

In this meta-analysis, telerehabilitation was considered as a rehabilitation service of various telecommunication technology [42]. Currently, it is possible to apply telecommunication technology to rehabilitation service in clinical practice through cell phones, applications, virtual reality devices, and other electronic devices [43]. Telerehabilitation can deliver rehabilitation management services such as assessment, intervention, and patient consultation. The studies included in this meta-analysis primarily used the internet, telephone or mobile apps, and wearable devices to provide telerehabilitation services, including consultation, monitoring, education, and intervention. In addition, the conventional face-to-face management of fibromyalgia currently is mainly a nonpharmacological interventions tailored to individual symptoms, such as psychotherapy, exercise, and self-management strategies that involve active patient participation [44]. However, in this meta-analysis, the interventions of the included studies used 3 rehabilitation interventions, with psychological interventions being the mainstay, followed by video-guided exercise training and self-management.

Few systematic reviews have investigated the effects of telerehabilitation in patients with fibromyalgia. To the best of our knowledge, only 1 review by Bernardy et al [22] has investigated the effects of internet-delivered psychotherapy with fibromyalgia. They found that telerehabilitation reduced negative mood and improved QoL, which was consistent with our findings. However, in terms of pain intensity, there was no significant improvement in the telerehabilitation group compared to the control group, which is inconsistent with our results. This is because their study used an established dichotomous variable to assess pain, whereas our study used a continuous variable based on the VAS, BPI, and FIQ-pain to reflect pain improvement. Overall, this meta-analysis indicated that telerehabilitation has a positive effect on the FIQ score, pain intensity, depression, and QoL in patients with fibromyalgia.

Challenges of Telerehabilitation for the Management of Fibromyalgia

Furthermore, there are several challenges to consider when telerehabilitation is applied in clinical settings. First, since telerehabilitation requires patients to be proficient in telecommunication technology, it may be difficult for patients unfamiliar with modern technology (eg, individuals with low IT literacy). In addition, some studies have suggested that the protection of patients’ privacy and supervision of relevant laws and regulations are also important factors influencing their willingness to use telerehabilitation [45,46]. Finally, the safety of telerehabilitation treatment remains unclear in patients with fibromyalgia. More research is required in the future to investigate the safety of telerehabilitation for patients with fibromyalgia.

Limitations

This study had several limitations. First, the studies included in this meta-analysis were heterogeneous with respect to the medium and programs of telerehabilitation in the intervention group. Second, only 2 studies included a 6-month follow-up period, so this meta-analysis only examined the short-term effects of telerehabilitation. Therefore, the long-term effects are still unclear. Third, all eligible studies were published in English, and it is likely that relevant studies published in other languages have been omitted, resulting in a language bias.

Clinical Implications

Our study found that telerehabilitation is an effective treatment approach for patients with fibromyalgia. Telerehabilitation can provide accessible and continuous rehabilitation medical services for patients with fibromyalgia who cannot attend traditional face-to-face services or are geographically remote, and it could enable patients to manage their disease at any time and place in a timely and appropriate manner.

More high-quality studies are required in the future to determine the efficacy of different forms of telerehabilitation and to focus on longer follow-ups to assess long-term outcomes in patients with fibromyalgia.

Conclusion

Telerehabilitation can improve the FIQ score, pain intensity, depression level, pain catastrophizing, and QoL of patients with fibromyalgia. However, there was uncertainty about the safety of telerehabilitation, so rigorously designed trials are needed in the future to verify the safety and efficacy of telerehabilitation in fibromyalgia.