The presence of stress and anxiety during simulation-based learning may affect the performance outcomes. This study takes advantage of infrared thermal imaging to study the relationship between differences in facial skin temperature and the perception of anxiety throughout a cardiac arrest simulated scenario. The analysis of facial temperature variations showed good correlations with either the anxiety scale or standard quality resuscitation parameters, showing consistent thermographic profiles for the forehead, maxillary and periorbital areas.
The extent of anxiety and psychological stress can impact upon the optimal performance of simulation-based practices. The current entry describes that the association between differences in skin temperature and perceived anxiety by under- (n = 21) and post-graduate (n = 19) nursing students undertaking a cardiopulmonary resuscitation (CPR) training. Thermal facial gradients from selected facial regions were correlated with the scores assessed by the State-Trait Anxiety Inventory (STAI) and the chest compression quality parameters measured using mannequin-integrated accelerometer sensors. A specific temperature profile was obtained depending on thermal facial variations before and after the simulation event. Statistically significant correlations were found between STAI scale scores and the temperature facial recordings in the forehead (r = 0.579; p < 0.000), periorbital (r = 0.394; p < 0.006), maxillary (r = 0.328; p < 0.019) and neck areas (r = 0.284; p < 0.038). Significant associations were also observed by correlating CPR performance parameters with the facial temperature values in the forehead (r = 0.447; p < 0.002), periorbital (r = 0.446; p < 0.002) and maxillary areas (r = 0.422; p < 0.003). These preliminary findings suggest that higher anxiety levels result in poorer clinical performance and can be correlated to temperature variations in certain facial regions.
Sociodemographic Characteristics | Undergraduate Bachelor Students (BS) |
Postgraduate Master Students (MS) |
Statistic Values χ2/t |
p Value | ||
---|---|---|---|---|---|---|
N = 21 mean ± SD (%) | N = 19 mean ± SD (%) | |||||
Sex | Female | 18 (85.7) | 16 (84.2) | 0.018 b | 0.894 b | |
Male | 3 (14.3) | 3 (15.8) | ||||
Age | 21.0 (4) | 23.85 (1.61) | −2.890 a | 0.006 *,a | ||
Educational level | Baccalaureate | 17 (81) | 0 | 0.000 *,b | ||
Professional training | 3 (14.3) | 0 | 36.190 b | |||
Other Bachelor of Science | 1 (4.8) | 19 (100) | ||||
Practicum in special health services | Yes | 0 | 19 (100) | 0.000 *,b | ||
No | 21 (100) | 0 | 40.0 b | |||
Number of special health services in practicum | 0 | 1.84 (0.83) | −9.625 a | 0.000 a | ||
Work in special health services | Yes | 0 | 10 (52.6) | 14.737 b | 0.000 *,b | |
No | 21 (100) | 9 (47.4) | ||||
Number of special health services working | 0 | 0 | 0.84 (1.05) | −3.618 a | 0.002 *,a | |
Training on basic CPR (basic life support) | Yes | Last two years | 1 (4.8) | 6 (31.6) | 6.686 b | 0.010 *,b |
More than two years | 2 (9.5) | 2 (10.5) | ||||
No | 18 (85.7) | 9 (47.4) | ||||
Duration basic CPR training | 37.67 (46.11) | 56.33 (37.67) | 6.750 b | 0.455 a | ||
Training on advanced CPR (advanced life support) | Yes | 0 | 4 (21.1) | 4.912 b | 0.027 *,b | |
No | 21 (100) | 15 (78.9) |
Facial Region | Temperature Value | Moment | Temperature Mean (SD) | Undergraduate Bachelor Students (BS) | Temperature Mean (SD) | Postgraduate Master Students (MS) | t | p Value Groups |
||
---|---|---|---|---|---|---|---|---|---|---|
t-Paired | Significance | t-Paired | Significance | |||||||
Nose | Average | Pre-test | 27.87 (2.56) | −1.014 | 0.323 | 28.76 (3.20) | 4.095 | 0.001 ** | −0.972 | 0.337 |
Post-test | 28.17 (2.31) | 27.06 (2.21) | −0.961 | 0.129 | ||||||
Difference | 0.30 (1.36) | - | −1.70 (1.81) | - | 1.553 | 0.000 * | ||||
Forehead | Maximum | Pre-test | 35.79 (0.76) | 0.982 | 0.338 | 35.79 (0.76) | 2.362 | 0.030 * | 1.557 | 0.072 |
Post-test | 35.59 (0.89) | - | 34.95 (0.66) | 3.980 | 0.014 * | |||||
Difference | −0.20 (0.91) | - | −0.39 (0.72) | - | 3.923 | 0.462 | ||||
Average | Pre-test | 34.90 (0.77) | 1.291 | 0.211 | 34.13 (1.34) | 2.939 | 0.009 ** | 1.851 | 0.031 * | |
Post-test | 34.60 (1.10) | 33.52 (1.26) | 1.849 | 0.006 * | ||||||
Difference | −0.30 (−0.30) | −0.61 (0.91) | 2.578 | 0.317 | ||||||
Minimum | Pre-test | 32.62 (1.64) | −0.432 | 0.671 | 30.40 (2.75) | 0.789 | 0.440 | 2.617 | 0.005 * | |
Post-test | 32.77 (1.03) | 30.09 (2.54) | 0.743 | 0.000 * | ||||||
Difference | 0.15 (1.57) | −0.31 (1.72) | 0.752 | 0.383 | ||||||
Periorbital | Maximum | Pre-test | 35.91 (0.63) | 1.142 | 0.267 | 35.93 (0.70) | 2.560 | 0.020 * | 2.247 | 0.935 |
Post-test | 35.67 (0.64) | 35.57 (0.67) | 2.190 | 0.346 | ||||||
Difference | −0.15 (0.59) | −0.36 (0.62) | 2.906 | 0.267 | ||||||
Average | Pre-test | 34.01 (0.90) | 0.294 | 0.771 | 33.93 (0.82) | 3.670 | 0.002 ** | 2.886 | 0.764 | |
Post-test | 33.96 (0.85) | 33.35 (0.59) | 1.013 | 0.012 * | ||||||
Difference | −0.05 (0.81) | −0.58 (.69) | 1.021 | 0.033 * | ||||||
Minimum | Pre-test | 28.84 (2.10) | 0.366 | 0.718 | 29.28 (2.07) | 3.596 | 0.002 ** | 3.137 | 0.509 | |
Post-test | 28.73 (1.77) | 28.18 (1.66) | 3.062 | 0.323 | ||||||
Difference | −0.11 (1.43) | −1.10 (1.33) | 4.443 | 0.030 * | ||||||
Maxillary | Maximum | Pre-test | 35.29 (0.99) | 0.579 | 0.569 | 35.11 (0.94) | 2.109 | 0.049 * | 4.282 | 0.548 |
Post-test | 35.177 (0.90) | 34.70 (0.73) | 0.883 | 0.074 | ||||||
Difference | −0.11 (0.90) | −0.41 (0.85) | 0.879 | 0.294 | ||||||
Average | Pre-test | 33.27 (1.30) | 1.285 | 0.214 | 33.10 (1.25) | 2.872 | 0.010 * | −0.082 | 0.681 | |
Post-test | 32.93 (1.08) | 32.42 (1.12) | −0.082 | 0.153 | ||||||
Difference | −0.34 (1.21) | −0.68 (1.03) | 0.953 | 0.345 | ||||||
Minimum | Pre-test | 27.59 (2.25) | 0.287 | 0.777 | 28.20 (2.55) | 4.011 | 0.001 ** | 0.951 | 0.424 | |
Post-test | 27.46 (1.74) | 26.57 (2.08) | 1.126 | 0.148 | ||||||
Difference | −0.12 (1.98) | −1.63 (1.77) | 1.123 | 0.016 * | ||||||
Neck/ Upper chest |
Maximum | Pre-test | 36.05 (0.92) | 2.177 | 0.042 * | 35.85 (0.71) | 2.189 | 0.042 * | 0.302 | 0.436 |
Post-test | 35.652 (0.99) | 35.47 (0.74) | 0.304 | 0.514 | ||||||
Difference | −0.40 (0.84) | −0.38 (0.75) | 2.635 | 0.934 | ||||||
Average | Pre-test | 34.50 (0.91) | 1.711 | 0.103 | 34.23 (0.62) | 2.547 | 0.020 * | 2.681 | 0.279 | |
Post-test | 34.21 (0.93) | 33.84 (0.62) | 2.210 | 0.158 | ||||||
Difference | −0.30 (0.79) | −0.38 (0.66) | 2.228 | 0.703 | ||||||
Minimum | Pre-test | 31.21 (1.91) | −0.054 | 0.957 | 30.69 (2.01) | 0.763 | 0.455 | −0.667 | 0.407 | |
Post-test | 31.23 (1.65) | 30.17 (1.93) | −0.668 | 0.069 | ||||||
Difference | 0.02 (2.01) | −0.51 (2.94) | 1.001 | 0.499 |
Dependent Variable: STAI Pre-Test | Unstandardized Coefficients | Standardized Coefficients | |
---|---|---|---|
B | Standard Error | Beta | |
Constant | −63.284 | 37.913 | |
Nose temperature | 0.182 | 0.278 | 0.107 |
Forehead temperature | 6.555 | 1.826 | 1.056 |
Periorbital temperature | −2.310 | 2.096 | −0.309 |
Maxillary temperature | −0.806 | 1.175 | −0.157 |
Neck/upper chest temperature | −1.117 | 1.098 | −0.187 |
The presence of stress and anxiety during simulation-based learning may affect the performance outcomes. Taking advantage of infrared thermal imaging to study the relationship between differences in facial skin temperature and the perception of anxiety throughout a cardiac arrest simulated scenario. The analysis of facial temperature variations showed good correlations with either the anxiety scale or standard quality resuscitation parameters, showing consistent thermographic profiles for the forehead, maxillary and periorbital areas. Consequently, the utilization of facial temperature values should be taken into consideration to predict the influence of anxiety during simulation training. Despite being a pilot experiment, the results are expected to improve assessment performance prior to a simulation practice by providing valuable information on the anxiety traits of simulation participants. Further research is needed to examine the reliability of infrared imaging technology as a valid screening tool for the objective quantification and diagnosis of emotional and cognitive load in simulation training practices.
This entry is adapted from the peer-reviewed paper 10.3390/healthcare8030206