| Literature DB >> 34946455 |
Eglė Mazgelytė1, Virginija Rekienė2, Edita Dereškevičiūtė2, Tomas Petrėnas3, Jurgita Songailienė3, Algirdas Utkus3, Gintaras Chomentauskas2, Dovilė Karčiauskaitė1.
Abstract
Various relaxation techniques could benefit from merging with virtual reality (VR) technologies, as these technologies are easily applicable, involving, and user-friendly. To date, it is unclear which relaxation technique using biofeedback combined with VR technology is the most effective. The study aimed to compare the effectiveness of brief VR-based biofeedback-assisted relaxation techniques including electroencephalographic biofeedback, mindfulness-based biofeedback, galvanic skin response biofeedback, and respiratory biofeedback. Forty-three healthy volunteers (age 34.7 ± 7.2 years), comprising 28 (65%) women and 15 (35%) men, were enrolled in the study. All the participants were exposed to four distinct relaxation sessions according to a computer-generated random sequence. The efficacy of relaxation methods was evaluated by examining psychological, physiological, and biochemical stress indicators. All VR-based relaxation techniques reduced salivary steroid hormone (i.e., cortisol, cortisone, and total glucocorticoid) levels and increased galvanic skin response values. Similarly, all interventions led to a significantly reduced subjectively perceived psychological strain level. Three out of the four interventions (i.e., electroencephalographic, respiratory, and galvanic skin response-based biofeedback relaxation sessions) resulted in a decreased self-reported fatigue level. We suggest that newly developed VR-based relaxations techniques are potential tools for stress reduction and might be particularly suitable for individuals who are not capable of adhering to a strict and time-consuming stress management intervention schedule.Entities:
Keywords: biofeedback; relaxation; stress; virtual reality
Year: 2021 PMID: 34946455 PMCID: PMC8701384 DOI: 10.3390/healthcare9121729
Source DB: PubMed Journal: Healthcare (Basel) ISSN: 2227-9032
Sociodemographic and lifestyle characteristics of the study sample.
| Variable | Mean ± SD or |
|---|---|
| Gender | |
| Women | 28 (65.0) |
| Men | 15 (35.0) |
| Age (Years) | 34.7 ± 7.2 |
| Marital status | |
| Single | 17 (39.5) |
| Married | 21 (48.9) |
| Divorced | 5 (11.6) |
| Education | |
| Secondary | 1 (3.3) |
| Tertiary | 42 (97.7) |
| Smoking status 1 | |
| Non-smoker | 31 (75.6) |
| Moderate smoker | 4 (9.8) |
| Heavy smoker | 6 (14.6) |
| Exposure to environmental tobacco smoke 1 | |
| No | 34 (82.9) |
| Yes | 7 (17.1) |
| Physical activity at work 1 | |
| Inactive | 36 (87.8) |
| Active | 5 (12.2) |
| Leisure time physical activity 1 | |
| Inactive | 14 (34.1) |
| Active | 27 (65.9) |
1n = 43 for all variables except for smoking status (n = 41), exposure to environmental tobacco smoke (n = 41), physical activity at work (n = 41), and leisure-time physical activity (n = 41).
Effects of distinct virtual reality-based relaxation techniques on psychological stress measures.
| Variable | Pre-Session ( | Post-Session ( | |
|---|---|---|---|
| Electroencephalographic biofeedback | |||
| Mood | 3.74 ± 0.79 | 3.79 ± 0.83 | 0.643 |
| Fatigue | 3.30 ± 1.12 | 3.67 ± 0.99 | 0.002 |
| Strain | 3.47 ± 1.08 | 3.84 ± 0.92 | 0.022 |
| Mindfulness-based biofeedback | |||
| Mood | 3.93 ± 0.77 | 3.95 ± 0.72 | 0.743 |
| Fatigue | 3.56 ± 1.03 | 3.63 ± 1.09 | 0.596 |
| Strain | 3.88 ± 0.91 | 4.19 ± 0.79 | 0.005 |
| Respiratory biofeedback | |||
| Mood | 3.67 ± 0.92 | 3.86 ± 0.77 | 0.088 |
| Fatigue | 2.91 ± 1.11 | 3.37 ± 1.05 | 4.229 × 10−5 |
| Strain | 3.42 ± 1.05 | 4.09 ± 0.87 | 1.941 × 10−5 |
| Galvanic skin response biofeedback | |||
| Mood | 3.63 ± 0.90 | 3.70 ± 0.86 | 0.498 |
| Fatigue | 3.30 ± 1.06 | 3.63 ± 0.93 | 0.033 |
| Strain | 3.58 ± 1.07 | 3.95 ± 1.02 | 0.048 |
Effects of distinct virtual reality-based relaxation techniques on the absolute concentrations of glucocorticoids in saliva.
| Variable | Pre-Session ( | Post-Session ( | |
|---|---|---|---|
| Electroencephalographic biofeedback | |||
| Cortisol (ng/mL) | 0.98 (0.63) | 0.96 (0.51) | 0.010 |
| Cortisone (ng/mL) | 7.01 (4.44) | 6.66 (2.54) | 0.010 |
| Cortisol + cortisone (ng/mL) | 8.09 (5.28) | 7.61 (2.89) | 0.011 |
| Mindfulness-based biofeedback | |||
| Cortisol (ng/mL) | 1.21 (0.81) | 1.02 (0.77) | 0.004 |
| Cortisone (ng/mL) | 7.36 (3.83) | 7.18 (4.02) | 0.020 |
| Cortisol + cortisone (ng/mL) | 8.67 (4.41) | 8.36 (4.68) | 0.007 |
| Respiratory biofeedback | |||
| Cortisol (ng/mL) | 0.98 (0.67) | 0.94 (0.61) | 0.073 |
| Cortisone (ng/mL) | 6.97 (3.18) | 6.55 (2.64) | 0.009 |
| Cortisol + cortisone (ng/mL) | 7.95 (3.91) | 7.57 (3.00) | 0.010 |
| Galvanic skin response biofeedback | |||
| Cortisol (ng/mL) | 1.26 (1.01) | 0.95 (0.72) | 0.010 |
| Cortisone (ng/mL) | 7.44 (4.39) | 6.78 (3.91) | 0.054 |
| Cortisol + cortisone (ng/mL) | 8.85 (5.24) | 8.00 (4.58) | 0.025 |
Effects of distinct virtual reality-based relaxation techniques on physiological stress biomarkers.
| Variable | Pre-Session ( | Post-Session ( | |
|---|---|---|---|
| Electroencephalographic biofeedback | |||
| GSR | 506 (202.5) | 517 (177.5) | 0.029 |
| HR (bpm) | 72 (12) | 72 (16) | 0.796 |
| Mindfulness-based biofeedback | |||
| GSR | 472 (182.5) | 521 (144.5) | 4.631 × 10−4 |
| HR (bpm) | 72 (12) | 73 (13) | 0.1048 |
| Respiratory biofeedback | |||
| GSR | 492 (162.5) | 573 (84.5) | 2.743 × 10−6 |
| HR (bpm) | 72 (12) | 72 (15) | 0.976 |
| Galvanic skin response biofeedback | |||
| GSR | 504 (156) | 544 (132) | 0.003 |
| HR (bpm) | 74 (10) | 73 (10) | 0.272 |
Figure 1Percentage changes in biochemical (a–c) and physiological (d) stress biomarkers after distinct virtual reality-based relaxation sessions (1—EEG biofeedback, 2—Mindfulness-based biofeedback, 3—Respiratory biofeedback, 4—Galvanic skin response biofeedback).