Effects of Gaming on Pain-Related Fear,Pain Catastrophizing,Anxiety,and Depression in Patients with Chronic Musculoskeletal Pain: A Systematic Review and Meta-Analysis

Abstract

The aim was to systematically review the effects of gaming on pain-related fear, pain catastrophizing, anxiety, and depression in patients with chronic musculoskeletal pain. Databases (Medline, EMBASE, PsycInfo, CINAHL, Cochrane Central Register for Controlled Trials [CENTRAL], Web of Science, and SCOPUS) were searched from inception up to October 2021. Two reviewers independently selected randomized controlled trials that compared the effects of any gaming modality with other interventions or no treatment on pain-related fear, pain catastrophizing, anxiety, and depression. For data synthesis, Standardized Mean Differences (SMDs) and 95% confidence interval (CI) were calculated using a random-effects inverse variance model for meta-analysis according to the outcome of interest, comparison group, and follow-up period. The level of evidence was synthesized using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). Thirteen studies were included with a total sample of 680 patients. Gaming was superior to other treatments and no treatment on reducing pain-related fear (SMD: −1.23; 95% CI: −2.02 to −0.44) and anxiety (SMD: −0.55; 95% CI: −1.01 to −0.09), respectively. Gaming was not superior to other treatments on reducing pain catastrophizing, anxiety, and depression, and it was not superior to no treatment on reducing pain-related fear, pain catastrophizing, and depression. Those findings were based on very low or low-quality evidence. In a conclusion, gaming modalities may have positive effects on some mental health outcomes. However, there were conflicting results with low-quality evidence, which indicates that more high-quality randomized controlled trials are needed.

Introduction

Chronic musculoskeletal pain is the most prevalent debilitating condition in the general adult population, placing a heavy burden on society and health care systems with a significant economic impact.¹ According to the World Health Organization, ∼1.71 billion people worldwide have a persistent musculoskeletal condition.² Chronic musculoskeletal pain arises from different etiologies^3,4 and is associated with impaired function, daily living activities, and health-related quality of life.⁵

The management of musculoskeletal pain has been traditionally based on tissue damage.⁴ Current evidence has shown that the painful symptoms and/or disability were not necessarily related to a specific tissue injury,^3,6 and the psychological and social factors have an important role in health-related outcomes.^6,7 The musculoskeletal conditions also negatively impact patients' mental health, associated with depression, anxiety, and other psychological or social-related impairments.^6,8 Additionally, a large number of systematic reviews concluded that psychological factors play an important role in the onset and chronicity of musculoskeletal conditions, including pain-related fear, pain catastrophizing, anxiety, and depression.^9–11

Previous systematic reviews indicated that videogames may have positive effects on biopsychosocial factors. They may decrease pain and improve function in patients with low back pain,¹² enhance cognition and lower depressive symptoms in older adults,¹³ reduce fatigue, improve quality of life and balance in patients with multiple sclerosis,¹⁴ and reduce stress and anxiety in other patients.¹⁵ Exergames are a modality of videogames that require physical activity interaction, and are shown to be effective to counter sedentary lifestyles and are viable to treat patients with musculoskeletal conditions.¹⁶ Virtual Reality is a goal-focused computer-simulated reality, acting on the user's experience of their perceived world through head-mounted displays, headphones, and motion tracking systems.¹⁷

Virtual reality is a useful tool for the assessment and treatment of mental health conditions,¹⁸ and has also been used in different clinical settings to ameliorate pain perception.^19,20 Although gaming modalities may improve mental health-related outcomes in patients with musculoskeletal conditions, this topic has not been previously explored by a systematic review. Therefore, this review aims to summarize and analyze the current evidence regarding the use of games and virtual reality to improve mental health-related outcomes in patients with chronic musculoskeletal pain.

Methods

This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and checklist (Supplementary Data—Prisma Checklist).²¹ The review protocol was registered in the international database PROSPERO (CRD42021285290).

Selection criteria for including studies

Study design

This review included randomized clinical trials. Preliminary reports, feasibility trials, or pilot studies were not included.

Patients

Studies were included if they assessed adults (older than 18 years) of either sex, with chronic musculoskeletal pain (e.g., back, neck, and shoulder pain; osteoarthritis; fibromyalgia).

Intervention

Studies that delivered digital gaming modalities and gaming technology as a treatment were included (e.g., casual games, serious games, gamification, virtual reality, exergames). Digital gaming modalities were defined as any sort of intervention using computerized and graphically manipulated images forming a game,²² to improve health-related outcomes.²³ The duration of the interventions was defined as short term (≤6 months), intermediate term (between 6 months and 1 year), and long term (≥1 year).

Comparison

Studies were considered eligible if the control group was no treatment (waiting list, sham, or placebo) or other intervention. Studies that used any gaming modality in the comparison group were not included.

Outcome measures

Studies were included if at least one of the following mental health-related outcomes was assessed: pain-related fear (e.g., kinesiophobia, fear avoidance), pain catastrophizing, anxiety, and depression. These outcomes are related to worse health-related outcomes in patients with chronic pain and are often assessed through patient self-reported outcome measures.¹⁰

Search methods for identification of randomized controlled trials

Electronic searches

The databases, MEDLINE, Embase, PsycInfo, CINAHL, Cochrane Central Register for Controlled Trials (CENTRAL), Web of Science, and Scopus, were searched from their inception to October 2021. A search strategy was developed using relevant keywords, which were combined with Boolean terms. The detailed search strategy is described in Supplementary File S1.

Data collection and analysis

Study selection

Two independent reviewers (V.G. and H.R.F.F.) selected the studies and a third reviewer (G.M.B.) was consulted in case of any disagreement. The primary studies were initially assessed by title and abstract to exclude those that did not fit the eligibility criteria. Afterward, the full texts of the remaining studies were assessed. Reference lists from the included trials were screened for potential additional trials that fit the inclusion criteria.

Methodological quality assessment

The Physiotherapy Evidence-Based Database (PEDro) scale was used to assess the methodological quality. PEDro is considered a reliable critical appraisal tool for experimental studies in physical therapy,²⁴ contains 11 criteria to assess the methodological quality of clinical trials, and the final score ranges from 0 to 10. If a criterion was not described or was unclear, no point was awarded. The previously indexed studies in the PEDro database had their score maintained. The non-indexed studies were independently evaluated by two reviewers (V.G. and H.R.F.F.), and a third reviewer (G.M.B.) solved inconsistencies of the rating when necessary. Studies scored 5 or more were classified as having high methodological quality.²⁵

Data extraction and management

Two reviewers (V.G. and H.R.F.F.) independently extracted data according to the Cochrane data collection form, and a third reviewer (G.M.B.) checked data in case of discrepancies. Data regarding patients, interventions, trial methods, outcome measures, the dose of interventions, duration of follow-ups, loss to follow-ups, and results, were extracted. The authors of the primary studies with missing or unclear data were contacted if necessary. In case the contacted authors did not respond, the missing data were calculated from mean change, graphical data, standard error (SE), or baseline standard deviation (SD).²⁶

The studies were initially analyzed according to the outcome of interest (pain-related fear, pain catastrophizing, anxiety, and depression) and control group (non-treatment or other interventions). Subsequently, a subgroup analysis was performed according to the gaming modality used in the studies, such as virtual reality or exergame.

Data synthesis and analysis

Meta-analyses were conducted using RevMan (version 5.4.1; The Nordic Cochrane Center, Copenhagen, Denmark) to summarize the effects of gaming on mental health outcomes in patients with chronic musculoskeletal pain. Meta-analysis was conducted using means and SDs of the data after the intervention from each of the eligible trials. Standardized Mean Differences (SMDs) and 95% confidence intervals (CIs) were calculated using a random-effects inverse variance model for meta-analysis. Based on similar systematic reviews,^27,28 subgroup analyses were used to verify differences between interventions (virtual reality or exergame) on the pooled treatment effect. I² statistic was used to assess heterogeneity between trials.²⁶ SMDs were classified as small (<0.20), medium (between 0.21 and 0.80), and large (>0.80).²⁹

The evidence synthesis for each meta-analysis was performed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) approach,³⁰ according to the following domains.

Risk of bias: quality of the evidence was downgraded by one level if more than 25% of the patients were from trials with low methodological quality. It was downgraded by two levels if more than 50% of the patients were from studies with low methodological quality.

Inconsistency: quality of the evidence was downgraded by one level if significant heterogeneity was observed in the results (i.e., I² > 50% and P < 0.05 on the heterogeneity test), minimal or no overlap of CIs, and wide variance of point estimates across studies. It was downgraded by two levels in case of serious inconsistency (heterogeneity in the I² test >75%).

Indirectness: quality of the evidence was downgraded if patients, interventions, or outcome measures from included studies were essentially different. This domain was not downgraded by two levels.

Imprecision: quality of the evidence was downgraded by one level if (A) pooled sample was smaller than 400 patients in the comparison and/or a single study with less than 400 patients; (B) wide CIs (95% of CI crossed an effect size of SMD = 0.5 in either direction). This domain was downgraded by two levels duo to both (A) and (B).

Publication bias: quality of the evidence was downgraded if the funnel plot presented asymmetrical distribution (when 10 or more studies were available), small studies were sponsored, or the investigators stated conflict of interest (publication bias criteria).

After assessing all domains, the quality of evidence for each meta-analysis was classified as one of the following levels.³¹

High quality: very confident that the true effect lies close to an estimate of effect;

Moderate quality: moderately confident that the true effect is likely to be close to an estimate of effect; but there is a possibility that it is substantially different;

Low quality: confidence in the effect estimate is limited and the true effect may be substantially different from an estimate of effect;

Very-low quality: little confidence in the estimate of effect and the true effect is likely to be substantially different from an estimate of effect;

Results

The electronic search retrieved 6530 studies. Twenty-five studies were considered in the full-text eligibility assessment and 12 were excluded. The detailed reasons for exclusion are described in Figure 1. After the full reviewing process, 13 articles were included for analysis.^32–44

FIG. 1.

PRISMA flow diagram of search strategies and results. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses; RCT, randomized controlled trial.

Methodological quality

The scores from 11 studies were obtained in PEDro database, and scores from 2 other studies^41,44 were assessed by the researchers. All 13 studies presented high methodological quality, with all studies satisfying the items related to random allocation, baseline comparison, and point estimates and variability (Table 1). The final PEDro score of the included studies ranged from 5 to 8 points.

Table 1.

Methodological Quality Evaluated According to the Physiotherapy Evidence-Based Database Scale

Studies	1	2	3	4	5	6	7	8	9	10	11	Total score
Carvalho et al. (2020)	Y	Y	N	Y	N	N	Y	N	Y	Y	Y	6
Collado-Mateo et al. (2017)	Y	Y	N	Y	N	N	Y	Y	Y	Y	Y	7
Gulsen et al. (2020)	Y	Y	N	Y	N	N	Y	Y	N	N	Y	5
Kim et al. (2014)	N	Y	N	Y	N	N	N	Y	N	Y	Y	5
Lin et al. (2020)	N	Y	Y	Y	N	N	Y	Y	Y	Y	Y	8
Nambi et al. (2021)	Y	Y	N	Y	N	N	N	Y	Y	Y	Y	6
Nambi et al. (2021)	Y	Y	N	Y	Y	N	Y	Y	Y	Y	Y	8
Polat et al. (2021)	Y	Y	Y	Y	N	N	N	Y	Y	Y	Y	7
Sarig Bahat et al. (2018)	N	Y	Y	Y	N	N	Y	N	Y	Y	Y	7
Sato et al. (2021)	Y	Y	Y	Y	N	N	Y	Y	Y	Y	Y	8
Tejera et al. (2020)	Y	Y	N	Y	N	N	N	Y	Y	Y	Y	6
Yilmaz Yelvar et al. (2017)	Y	Y	N	Y	N	N	Y	Y	N	Y	Y	6
Zadro et al. (2019)	Y	Y	Y	Y	N	N	Y	Y	Y	Y	Y	8

Eligibility criteria item does not contribute to the total score.

1, Eligibility criteria; 2, random allocation; 3, concealed allocation; 4, baseline comparability; 5, blinding of individuals; 6, blinding of therapists; 7, blinding of assessors; 8, adequate follow-up; 9, intention-to-treat analysis; 10, between-group comparisons; 11, point estimates and variability.

N, no; Y, yes.

Patients

The characteristics of the patients from the included studies are listed in Table 2. The pooled sample was 680 patients and the dropout during the intervention period was 72 patients (10.58%). The number of patients in the included studies ranged from 20 to 90 (average sample size of 52.30 patients). The patients' mean age was 45.2 years (ranging from 21.4 to 68.8), and 393 patients were women (57.79%). The included studies investigated treatments for patients with chronic low back pain,^{35,36,39,41,42,44} chronic neck pain,^32,34 fibromyalgia,^33,37,38,43 and knee osteoarthritis.⁴⁰

Table 2.

Characteristics of the Studies

Study	Number (sex)	Health status	Dropout	Mean age ± SD (years)	Interventions	Session duration	Dose (No. of sessions, frequency, and period)	Mental health-related outcomes	Other outcomes
Lin et al. (2020)	n = 80 (41 women)	Knee osteoarthritis	n = 1 (3 Months after the intervention)	(A) 55.9 ± 15.8 (B) 58.1 ± 16.9	(A) Active videogames using Hot Plus system. Two sessions that required patients to move their trunk and lower limbs as fast as possible. (B) Stretching warm-up+stabilization exercises for strength, balance, and posture+weight-shift training focusing on the knee joints while incorporating the pelvis in the trunk area+cycling for 10′+stretching cool down. All patients received hot packs to be applied to both knees (20′)+transcutaneous electrical nerve stimulation (20′).	(A) 20 minutes (B) 20 minutes	12 Sessions, 3 times per week, 4 weeks	HADS	WOMAC Balance using Biodex Stability System 10 m walk and ascend/descend stairs WHOQOL-BREF WAI Chronic Pain Grade Questionnaire MFI
Sato et al. (2021)	n = 40 (19 women)	Chronic low back pain (>3 months)	No dropouts	(A) 49.3 ± 12.5 (B) 55.6 ± 10.9	(A) Nintendo Ring Fit Adventure for 30′ (fitness role playing game that uses a ring-shaped controller as a device for resistance training)+low back pain improvement program for 10′. (B) No exercises or exergames. Previously prescribed medication was continued. In addition, new oral treatments were given to each patient in the following order: (1) NSAIDs, (2) tramadol, and (3) duloxetine. All patients continued any prior drug therapy at the same dose in addition to new therapeutic intervention.	(A) 40 minutes	8 Sessions, 1 time per week, 8 weeks	PCS TSK	VAS 11-Point scale for leg numbness Body weight (kg), body fat (%) and muscle mass (%) using BIA PSEQ Grip strength (kg) using a dynamometer
Polat et al. (2021)	n = 40 (all women)	Fibromyalgia	n = 6 (8 weeks after the intervention)	(A) 47.0 ± 7.1 (B) 42.6 ± 8.7	(A) Aerobic +15′ virtual reality exercise (Microsoft Xbox Kinect, a semi-immersive system, Beach Volleyball). (B) Aerobic +15′ muscle strengthening, balance, and flexibility exercises. All patients were informed about fibromyalgia syndrome. Both groups performed an aerobic exercise program (cycling) for 20′.	(A) 35 minutes (B) 35 minutes	12 Sessions, 3 times per week, 4 weeks	HADS	VAS SSS FSS 6MWT EQ-5D FIQ—Total score only
Tejera et al. (2020)	n = 44 (23 women)	Nonspecific chronic neck pain	No dropouts	(A) 32.72 ± 11.63 (B) 26.68 ± 9.21	(A) Vox Play glasses+Smartphone (LG Q6), where two virtual reality mobile applications were installed (Fulldive virtual reality and virtual reality Ocean Aquarium 3D). (B) 10 rep/3 times of neck flexion, extension, rotation, and tilt.	ND	8 Sessions, 2 times per week, 4 weeks	PCS TSK FABQ PASS-20	VAS COM TS Cervical range of motion NDI Pain Pressure Thresholds
Yilmaz Yelvar et al. (2017)	n = 44 (28 women)	Nonspecific chronic low back pain (>2 months)	n = 2 (during the intervention)	(A) 46.3 ± 3.4 (B) 52.8 ± 11.5	Both groups: hot pack (15 minutes), transcutaneous electrical nerve stimulation (TENS) (15 minutes), deep heat with ultrasound (5 minutes), and therapeutic exercises (extension exercise, posterior pelvic tilt, cat–camel exercise, and stretching of the lumbar extensor muscle). Patients were also instructed to perform them at home 3 times/day. (A) Passively watch a virtual walking video clip in a sitting position (Vita Digital Productions) played through an iPod (Apple, Inc.) with video glasses (Wrap920; Vuzix Corporation) at each therapy session during hot pack application.	ND	10 Sessions, 5 times per week, 2 weeks	TSK	VAS ODI NHP TUG 6MWT Single-leg balance test
Collado-Mateo et al. (2017)	N = 83 (83 women)	Fibromyalgia	7	(A) 52.52 ± 9.73 (B) 52.47 ± 8.75	(A) Kinect exercise group: VirtualEx-FM, specifically designed to improve physical conditioning in women with fibromyalgia, focusing on postural control and coordination of upper and lower limbs, aerobic conditioning, strength, and mobility. (B) Nonexercise group.	(A) 1 hour	16 Sessions, 2 times per week, 8 weeks	FIQ (Fibromyalgia Impact Questionnaire)	EQ-5D-5L
Carvalho et al. (2020)	N = 35 (all women)	Fibromyalgia	14	(A) 55.64 ± 9.16 (B) 47.70 ± 15.46	(A) Nintendo Wii exergames group: Six subgames of Wii Fit Plus using Wii remote plus and Wii balance board. (B) Control group: chain muscle stretching.	(A) 1 hour (B) 1 hour	20 Sessions, 3 times per week, 7 weeks	FIQ	Pressure Pain Threshold 25 cm step climbing and descending: Lower limb fatigue—Borg category ratio 10 Scale Peripheral oxygen saturation Heart rate Systolic blood pressure Respiratory rate before, during the exercise and after exercise
Kim et al. (2014)	N = 30 (all women)	Chronic lower back pain (≥2 months)	ND	(A) 44.33 (SD ND) (B) 50.46 (SD ND)	(A) Virtual reality: a virtual reality-based yoga program using Wii Fit activities. (B) Trunk stabilizing exercises and usual physical therapy.	(A) 30 minutes (B) 60 minutes total	12 Sessions, 3 times per week, 4 weeks	FABQ	VAS Pressure Pain Threshold ODI RDQ
Nambi et al. (2021)	N = 60 (all men)	Chronic low back pain (≥3 months)	0	(A) 23.2 ± 1.5 (B) 22.8 ± 1.6 (C) 23.3 ± 1.5	(A) Virtual Reality Training: exercises focused on balance and stability of core muscles in sitting position. Game difficulty was adjustable. (B) Isokinetic Training: trunk exercise was performed at 3 different angular speeds, with 3 sets of 15 repetitions for each. (C) Control: conventional training of core muscles. All patients were prescribed a home-based exercise protocol and underwent hot pack therapy and ultrasound therapy.	(A) 30 minutes (B) ND (C) ND	20 Sessions, 5 times per week, 4 weeks	TSK	VAS Blood serum level of stress hormones
Zadro et al. (2018)	N = 60 (31 women)	Chronic low back pain	8 Weeks: 2 3 months: 4 6 months: 3	(A) 68.8 ± 5.5 (B) 67.8 ± 6.0	(A) Videogame exercise group: unsupervised home-based exercise program using Nintendo Wii console with Wii Fit U software. (B) Control group: maintain usual activities.	(A) 60 minutes	24 Sessions, 3 times per week, 8 weeks	Outcome collected at baseline and 8 weeks TSK	Outcomes collected at baseline, 8 weeks, 3 months, and 6 months PSEQ Care-seeking—3-item questionnaire developed for the trial Rapid Assessment of Physical Activity questionnaire Outcomes collected at baseline and 8 weeks Pain with 11-point numeric rating scale PSFS RDQ 16-item Falls Efficacy Scale-International questionnaire
Gulsen et al. (2020)	N = 16 (all women)	Fibromyalgia	4	Median (IQR 25–75) (A) 46.50 (36.50–49.50) (B) 38.50 (29.50–50.00)	(A) Immersive Virtual Reality+exercise group: in addition to aerobic training and Pilates, an Immersive Virtual Reality Training was performed. Equipment included Oculus head-mounted display used in association with Xbox Kinect sensor and a computer. Two games were developed to improve balance and mobility. Game difficulty was adjustable. (B) Exercise group: aerobic training and Pilates.	(A) 80 minutes (B) 60 minutes	16 Sessions, 2 times per week, 8 weeks	TSK	VAS MSOT FSS IPAQ 6MWT FIQ—Total score only SF-36
Nambi et al. (2021)	N = 54 (all men)	Chronic low back pain (≥3 months)	4 Weeks: 0 6 months: 2	(A) 22.3 ± 1.6 (B) 21.4 ± 1.8 (C) 21.9 ± 1.8	(A) Virtual Reality Training: Pro-Kin system PK 252 N, focusing on balance of core stability muscles. Training was given on sitting position. Difficulty was adjustable. (B) Combined physical rehabilitation: balance training through a Swiss ball for core muscles. (C) Control: conventional exercises for core muscles. All patients were prescribed a home-based exercise protocol and underwent hot pack therapy and ultrasound therapy.	(A) 30 minutes (B) ND (C) ND	20 Sessions, 5 times per week, 4 weeks	TSK	VAS Blood serum level of stress hormones
Sarig Bahat et al. (2018)	N = 90 (63 women)	Chronic neck pain (≥3 months)	14	Median (IQR Q1–Q3) (A) 48 (38.5–57.5) (B) 48 (35.5–59) (C) 48 (35–59)	(A) Virtual Reality training group: a customized neck Virtual Reality (VR) system with the Oculus Rift DK1 head-mounted display equipped with 3D motion tracking. A software was developed using Unity-pro software, which included virtual reality and motion tracking data analysis in real time. Three modules were developed, for range of motion, velocity, and accuracy. Patients were trained and instructed to perform exercises at home. (B) Laser training group: a kinematic training with a head-mounted laser beam. Tasks in the laser group were similar to the Virtual Reality group. Patients were trained and instructed to perform exercises at home. (C) Control group: waiting for intervention at second phase.	(A) 20 minutes (B) 20 minutes	4 Times a day for 5 minutes, 4 times per week, 4 weeks	TSK	NDI GPE VAS EQ-5D Cervical range of motion and kinematics

(A) Experimental group; (B) control group.

3D, three-dimensional; 6MWT, Six-Minute Walk Test; BIA, bioelectrical impedance analysis; COM, Conditioned Pain Modulation; EQ-5D, EuroQol-5 Dimensions; EQ-5D-5L, EuroQol-5 Dimensions-5 Levels; FABQ, Fear-Avoidance Beliefs Questionnaire; FIQ, Fibromyalgia Impact Questionnaire; FSS, Fatigue Severity Scale; GPE, global perceived effect; HADS, Hospital Anxiety and Depression Scale; IPAQ, International Physical Activity Questionnaire; IQR, interquartile range; MFI, Multidimensional Fatigue Inventory; MSOT, Modified Sensory Organization Test; ND, not defined; NDI, Neck Disability Index; NHP, Nottingham Health Profile; NSAID, nonsteroidal anti-inflammatory drug; ODI, Oswestry Low Back Pain Disability Index; PASS-20, Pain Anxiety Symptoms Scale—20-items version; PCS, Pain Catastrophizing Scale; PSEQ, Pain Self-Efficacy Questionnaire; PSFS, Patient-Specific Functional Scale; RDQ, Roland Morris Disability Questionnaire; SD, standard deviation; SF-36, Short Form 36; SSS, Symptom Severity Scale; TS, Temporal Summation; TSK, Tampa Scale of Kinesiophobia; TUG, Timed-up and go Test; VAS, Visual Analog Scale; WAI, Work Ability Index; WHOQOL-BREF, World Health Organization Quality of Life-Brief Vision; WOMAC, Western Ontario and McMaster Universities Osteoarthritis Index.

Interventions

Characteristics of the interventions of each included study are described in Table 2. Gaming interventions used virtual reality,^{32,34,35,38,39,41,42} exergames through videogame consoles,^{33,36,37,43,44} or other gaming devices (a step-sensing platform).⁴⁰ In one study, the game intervention did not involve actual active movement by the patient.³⁵ Most of the included trials performed the experimental treatment sessions in the clinical setting, and only two trials prescribed gaming interventions at home.^32,36 Gaming interventions often included some form of aerobic, mobility, or strengthening exercises. Adherence was similar between groups across all groups when reported. The gaming interventions were classified as “Virtual Reality” when treatments involved virtual reality immersion (e.g., Oculus Rift, Pro-Kin system) or “Exergame” when other hardware was used (e.g., Nintendo Wii, Xbox Kinect).

All studies verified the short-term effects of the interventions and the duration of experimental interventions ranged between 20 and 80 minutes per session, frequency of 1–5 times per week for 2–8 weeks, with a total of 8–24 sessions. Games were compared with exercise therapy (84.61%) or no intervention (15.38%). When exercise therapy was performed, aerobic, mobility, and strengthening exercises were included in a similar manner to the experimental group.

Outcome measures

Pain-related fear was assessed with the Tampa Kinesiophobia Scale^{32,34–36,38,41,42,44} and the Fear-Avoidance Beliefs Questionnaire.^34,39 The Pain Catastrophizing Scale was used to assess pain catastrophizing^34,44 and the Pain Anxiety Symptoms Scale was used to assess anxiety.³⁴ The Hospital Anxiety and Depression Scale^39,43 and the Fibromyalgia Impact Questionnaire were used to assess both anxiety and depression.^33,37

Effects of interventions

Effects of games on pain-related fear

Seven studies^{32,34,35,38,39,41,42} compared the effects of games (virtual reality) with other treatment on pain-related fear (Fig. 2). Very low-quality evidence (Supplementary File S2) indicated that the games were superior to other treatments (SMD: −1.23; 95% CI: −2.02 to −0.44). Two studies^32,36 compared the effects of games (virtual reality and exergames) with no treatment on pain-related fear (Fig. 2). Very low-quality evidence indicated that games were not superior to no treatment (SMD: −0.33; 95% CI: −0.77 to 0.11). Subgroup analysis showed no significant difference (P = 0.25) between the effects of virtual reality³² or exergames.³⁶

FIG. 2.

Forest plots of the overall effect of virtual reality and exergame on pain-related fear compared with other treatments or no treatment. Squares represent point estimates of treatment effect and the diamonds represent the pooled treatment effect.

Effects of games on catastrophizing

One study³⁴ compared the effects of games (virtual reality) with other treatments on pain catastrophizing (Fig. 3). Low-quality evidence indicated that the games were not superior to other treatments (SMD: 0.26; 95% CI: −0.34 to 0.85). Another study⁴⁴ compared the effects of games (exergames) with no treatment on pain catastrophizing (Fig. 3). Low-quality evidence indicated that games were not superior to no treatment on pain catastrophizing (SMD: −0.30; 95% CI: −0.92 to 0.33).

FIG. 3.

Forest plots of the overall effect of virtual reality or exergame on catastrophizing compared with other treatments or no treatment. Squares represent point estimates of treatment effect and the diamonds represent the pooled treatment effect.

Effects of games on anxiety

Four studies^33,34,40,43 compared the effects of games with other treatments on anxiety (Fig. 4). Low-quality evidence suggests no difference between interventions (SMD: −0.10; 95% CI: −0.44 to 0.23). Subgroup analysis showed no significant difference between the effects of virtual reality^34,43 or exergame^33,40 (P = 0.40; I² = 0%). One study³⁷ compared the effects of games (exergames) with no treatment on anxiety (Fig. 4). Low-quality evidence indicated that games were superior to no treatment (SMD: −0.55; 95% CI: −1.01 to −0.09).

FIG. 4.

Forest plots of the overall effect of virtual reality and exergame on anxiety compared with other treatments or no treatment. Squares represent point estimates of treatment effect and the diamonds represent the pooled treatment effect.

Effects of games on depression

Three studies^33,40,43 compared the effects of games with other treatments on depression (Fig. 5). Very low-quality evidence indicated that games were not superior to other treatments on depression (SMD: −0.41; 95% CI: −1.05 to 0.22). Subgroup analysis showed no significant difference between the effects of virtual reality⁴³ or exergames^33,40 (P = 0.83; I²: 0%). One study³⁷ compared the effects of games (exergames) with no treatment on depression (Fig. 5). Low-quality evidence indicated no difference between interventions (SMD: −0.38; 95% CI: −0.84 to 0.07).

FIG. 5.

Forest plots of the overall effect of virtual reality and exergame on depression compared with other treatments or no treatment. Squares represent point estimates of treatment effect and the diamonds represent the pooled treatment effect.

Discussion

This review aimed to summarize the current evidence regarding the effects of games on mental health, including pain-related fear, pain catastrophizing, anxiety, and depression in patients with chronic musculoskeletal pain. Low and very-low quality evidence suggested that games are superior to other treatments to improve pain-related fear, and superior to no treatment to improve anxiety. Very low and low evidence suggests no difference between games and other treatments or no treatment for the other outcomes. Previous systematic reviews showed positive effects of gaming interventions on emotions and mental health in individuals with a variety of conditions,^45–47 but to our knowledge, this is the first systematic review that analyzed the effects of gaming in patients with chronic musculoskeletal pain.

Chronic musculoskeletal pain negatively impacts patients' physical health, as well as psychological and social aspects, with a consequent poor quality of life.^6,7,48 The effects of interventions on mental health may provide important information to assist clinicians in planning treatments for patients with musculoskeletal pain disorders. Therefore, future studies should assess these outcome measures to examine the effects of different treatments on those behavioral and psychological constructs. In our study, virtual reality interventions were superior to other treatments (e.g., exercise therapy) to improve pain-related fear in short term. Although the large effect size indicated clinically relevant results, those findings should be interpreted cautiously due to the very low quality of evidence. Additionally, gaming interventions (virtual reality and exergames) were not superior to no treatment, based on two studies^32,36 that provided very-low quality evidence. Those findings indicated that more studies are necessary to strengthen the evidence.

Pain-related fear is a common behavior in patients with chronic musculoskeletal pain, associated with maladaptive learning, activity avoidance, and modified perception of pain,¹⁷ which has a debilitating role in pain experiences.^49,50 Patients with painful motion tend to adopt avoidance behaviors, which might consequently have a negative impact on functionality, quality of life, and willingness to participate in rehabilitation.^51,52 Passive interventions are not effective to reduce psychological factors, including pain-related fear in patients with musculoskeletal pain.^53,54 However, therapeutic exercises (which are prone to be active interventions) may have positive effects on these outcomes.^54,55 Moreover, pain neuroscience education may have larger effects when associated with movement-based therapies.⁵⁶ Interestingly, our results showed that virtual reality may be superior to exercises, but the effects of virtual reality associated with pain neuroscience education, for example, are still unknown.

The theoretical mechanisms of virtual reality to improve psychological factors include distraction and graded exposure.^17,18 Distraction is the redirection of an individual's attention away from pain toward other sensations, including visual, auditory, and tactile stimuli, which reduce cognitive capacity to process pain and avoidance behaviors.^17,18 The graded exposure encourages a confrontation response by exposing patients to specific situations or providing graded movement exposure within simulations of real-life activities or based on the individual's personal needs.¹⁷ It was expected that these strategies may reduce fear avoidance and kinesiophobia in patients with pain during movement, which is confirmed by our results.

Virtual reality has been used as part of the treatment for psychiatric disorders, including anxiety,⁵⁷ being able to reduce anxiety symptoms,⁵⁸ and demonstrating similar efficacy compared with traditional exposure interventions, because it has a powerful real-life impact, and demonstrates good stability of results over time.⁵⁹ Because our patients did not necessarily present psychiatric disorders, our results indicated that exergames may have a positive effect on anxiety, but both virtual reality and exergames were not superior to other interventions to reduce anxiety in short term.

Although gaming has been extensively used with therapeutic purposes with children, chronic musculoskeletal pain is more prevalent in adults than in children,⁶⁰ so this review focused on the effects of gaming in the adult population. However, the results could be different in children, depending on their previous experience with games.

Although the gaming interventions are a promising rehabilitation approach for patients experiencing pain, the current evidence does not support it to improve pain catastrophizing and depression at short-term follow-up. Nevertheless, the effects of gaming in the intermediate and the long terms are still unknown, and studies^46,61 have suggested that interventions with a longer duration might provide superior outcomes on self-perceived depression and anxiety. Future gaming design focused on patients with chronic musculoskeletal pain can take into consideration their psychosocial aspects related to pain.¹⁰ More high-quality randomized controlled trials are needed to strengthen the evidence on the effects of gaming on mental health-related outcomes.

Strengths of the review

To the best of our knowledge, this is the first systematic review that verified the effects of gaming interventions on mental health in patients with chronic musculoskeletal pain. This review provides updated evidence regarding gaming given our consideration of PRISMA, comprehensive search strategy, meta-analysis, and evaluation of the quality of the evidence according to GRADE. The results of this study can assist clinicians in making decisions regarding managing patients with musculoskeletal pain following an evidence-based practice.

Limitations

Even though studies were indicating positive effects of gaming on mental health, the results of this review should be interpreted with caution due to very low or low quality of evidence. Few studies investigated short-term effects and follow-up, and there was heterogeneity of the sample and interventions. Furthermore, publication bias was not assessed using funnel plots due to the limited number of included studies. Future randomized clinical trials with concealed allocation, blinded assessor, intention-to-treat analysis, and appropriate sample size should be performed to provide clearer evidence about the effects of different types of gaming, associated or not with other therapeutic approaches, and compared with no treatment or therapeutic exercises. We limited our population to adults only, and choosing an appropriate gaming intervention must take into consideration the playability and user experience of this specific population.⁶²

Conclusion

The results indicated that gaming modalities are superior to other treatments to improve pain-related fear, and superior to no treatment to improve anxiety. However, gaming was not superior to no treatment to improve pain-related fear and it was not superior to other treatments or no treatment for improving pain catastrophizing, anxiety, and depression. Those findings were based on very low and low-quality evidence, and more studies are necessary to strengthen the evidence.

Footnotes

Authors' Contributions

All persons who meet authorship criteria are listed as authors, and all authors certify that they have participated sufficiently in the work to take public responsibility for the content, including participation in the concept, design, analysis, writing, or revision of the article. Concept and research design: V.G., H.R.F.F., G.M.B., L.B.C., and D.H.K. Search strategy: V.G., H.R.F.F., G.M.B., L.B.C., and D.H.K. Data analysis: V.G. and H.R.F.F. Writing: V.G., H.R.F.F., G.M.B., L.B.C., and D.H.K.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This study was supported by grant 2020/01449-5 from São Paulo Research Foundation (FAPESP) and by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES). The funding source was not involved in the design, interpretation, or writing of this study.

Supplementary Material

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