Open Access e-Journal Cardiometry No.16 May 2020
We should mention that Cardiometry is a fine diagnostics tool to assess heart life expectancy. Our experts, using Cardiocode in “red zones” in intensive care units, have confirmed effectiveness of noninvasive measuring of the hemodynamics data on the cardiovascular system performance in critical patients with different severity degrees. The medical staff involved had a possibility not only to monitor the state in each critical patient, but also to predict and control the progression of a disease. We are going to publish some results of this pilot study in our next issues. We should mention that Cardiometry is a fine diagnostics tool to assess heart life expectancy. Our experts, using Cardiocode in “red zones” in intensive care units, have confirmed effectiveness of noninvasive measuring of the hemodynamics data on the cardiovascular system performance in critical patients with different severity degrees. The medical staff involved had a possibility not only to monitor the state in each critical patient, but also to predict and control the progression of a disease. We are going to publish some results of this pilot study in our next issues.
have been calculated for each examinee. Illustrationsof this stage are shown in Figure 2 further herein.The following psychological tests have been usedas questionnaires in the study:- Self-efficacy score by R. Schwarzer and M. Jerusalem(translated and adapted by V.G. Romek);- the Keirsey Temperament Sorter (KTS);- identification of subjective conditioning or readinessto stress tests;- the TIPI-RU questionnaire- self-estimate of susceptibility to stressful factors(M. Friedman, R.Rosenman);- an analysis of life style (the Boston Stress Test);In total, the study has covered 258 participants.The statistical analysis of the obtained data hasbeen performed using statistical package STADIA 8.0.Results and discussionThe average SI values for various visual stimuli arepresented in Table 1.The first column of the present and all the followingtables shows the numbers to indicate the visualstimuli as follows:1 - toothy jaws of an attacking vampire bat;2 - a pretty image of a giant panda;3 - a huge spider devouring a wasp;4 - a rattlesnake preparing to attack;5 - a funny kitten playing around;6 - 150-point typed word EXAMINATION;7 - 190-point typed word SESSION;8 - a standard form of answers, which is used duringthe USE procedure.The static significance of differences in mean valueswas confirmed using the χ criterion (chi-square)that, as noted above, was evaluated using statisticalpackage STADIA 8.0.The obtained distributions differ from theGauss-Laplace distribution. Therefore, in order toidentify correlation relationships, we applied the Spearmanand Kendall coefficients. Since the nature of theidentified relationships for each of these coefficientsand the factor structure revealed for each of them aresimilar, in the further analysis the data for the Spearmancoefficient only are given because of its greatergenerality.Table 2 shows the parameters of the factor structureafter using the orthogonal rotation method (VarimaxRotation), with which we sought to minimize thenumber of variables with high loads on each factor.Table 1The main statistical parameters of the SI for various ego-statesof respondentsNumber Arithmetic Standardof stimuli mean deviationMedian1 207,9 257 175,52 519,9 371,4 4043 386,2 284,8 374,54 308,4 358,3 323,55 417,7 347,1 4006 239,5 242,2 1897 212,4 138 1848 279,1 266,8 196Table 2Factor structure of the correlation relationships after thevarimax rotationNumber of visual stimuliNumber of factor1 2 31 0,7647 -0,24732 0,84383 -0,5264 0,519 -0,41965 0,28216 0,93057 0,76448 -0,5418Table 3Factor structure of the correlation relationships after theequimax rotationEgo-statesNumber of factor1 2 31 -0,85572 0,91653 0,4447 -0,70314 0,6404 -0,57155 0,51076 0,88767 0,8342 -0,44068 0,3703 -0,7449In addition to the orthogonal rotation method(Varimax Rotation), we have also employed the methodsas listed below:- the quartimax rotation, with which we tried tominimize the number of factors, which are requiredfor a meaningful interpretation of each of the variablesinvolved;- the equimax rotation (Equimax Rotation), whichwas used to simultaneously minimize the number ofvariables with large factor loads and the number offactors to interprete them;- the oblique rotation (Оblique Rotation), withwhich we sought to minimize the number of factorswithout ensuring their full independence (orthogonality).30 | Cardiometry | Issue 16. May 2020
Figure 2. Demonstration of the parallel recording mode of respondent's cardiooculometric indicators of response to the USE formpresentation.Table 4.Test scores 1 2 3The USE results 0,367Stress tolerance (Boston test) 0,418 0,523Susceptibility to stress of type A (Friedman-Rosenman methodology) 0,462Subjective conditioning/readiness to USE 0,704Extraversion (TIPI-RU questionnaire) 0,277 0,693Friendliness(TIPI-RU questionnaire) 0,654Fairness(TIPI-RU questionnaire) 0,388 0,539Emotional stability(TIPI-RU questionnaire) 0,402 0,528Openness to experience (intelligence) (TIPI-RU questionnaire) 0,477 0,398Self-efficacy 0,307 0,706E score Extravertion (Keirsey questionnaire) 0,354 0,803I score Introvertion (Keirsey questionnaire) 0,364 0,743 -0,396S score Sensation(Keirsey questionnaire) 0,694 0,414N score Intuition (Keirsey questionnaire) 0,734T score Thinking (Keirsey questionnaire) 0,727F score Feeling (Keirsey questionnaire) 0,756 0,328J score Judging (Keirsey questionnaire) 0,623 0,307P score Perceiving (Keirsey questionnaire) 0,686 0,401It has been found that the factor structure of thecorrelation relationships upon the oblique rotation(Оblique Rotation) exactly corresponds to the structureobtained after the varimax rotation (Varimax Rotation).When optimizing the factor structure of therevealed correlation relationships, we analyzed variants,which included from 3 (covered up to 80% of thedispersion and associated with larger losses of information)to 7 factors (covered over 90% of the dispersionand characterized by the presence of a significantTable 5variables 1 2 3 4SI 1 0,462 -0,883SI 2 0,338 -0,618SI 3 0,782SI 4 0,894 -0,285USE mark 0,887Issue 16. May 2020 | Cardiometry | 31
- Page 1 and 2: 124 | Cardiometry | Issue 16. May 2
- Page 3 and 4: Dear Reader!Our life dictates what
- Page 5 and 6: Prof. Mohammad AleemCairo Universit
- Page 7 and 8: 74808597The study of hemodynamics i
- Page 9 and 10: We commemorate great Russian scient
- Page 11 and 12: and, in particular, activated is th
- Page 13 and 14: decline in the rate of those who fo
- Page 15 and 16: Table 1.Mass parameters of some org
- Page 17 and 18: REVIEW Submitted: 20.02.2020; Accep
- Page 19 and 20: teides. As a rule, under the hypoxi
- Page 21 and 22: Table 1Changes in ratios between th
- Page 23 and 24: Consequences of anaerobic formation
- Page 25 and 26: receptor SUCNR1 [72], which is call
- Page 27 and 28: acid and oxalacetic acid. J. Biol.
- Page 29 and 30: Issue 16. May 2020 | Cardiometry |
- Page 31: 12], we may assume that PC-assisted
- Page 35 and 36: of doubts has been expressed by tho
- Page 37 and 38: ORIGINAL RESEARCH Submitted: 2.04.2
- Page 39 and 40: Table 2. Dependence of SHD profile
- Page 41 and 42: Figure 4Figure 5Figure 6 Figure 7Ta
- Page 43 and 44: The mapping between the SHD profile
- Page 45 and 46: Issue 16. May 2020 | Cardiometry |
- Page 47 and 48: measurement thereof cannot detect a
- Page 49 and 50: AimsThe aim of this study is to ass
- Page 51 and 52: vascular system condition, using an
- Page 53 and 54: 4. Papers devoted to the AH treatme
- Page 55 and 56: 2019;2(12):18-23. https://doi.org/1
- Page 57 and 58: ORIGINAL RESEARCH Submitted: 17.01.
- Page 59 and 60: The statistical analysis of the obt
- Page 61 and 62: Table 7Eigenvalues and percentage o
- Page 63 and 64: but also as a means for active mode
- Page 65 and 66: values [6]. Both groups are homogen
- Page 67 and 68: Table 2No. of ind.BMIAge, yearsHb,
- Page 69 and 70: ORIGINAL RESEARCH Submitted: 18.03.
- Page 71 and 72: а) b)Figure 1. Fragments of the bl
- Page 73 and 74: а)b)cd)Figure 3. Fragments of seru
- Page 75 and 76: zation of the facias and add to the
- Page 77 and 78: PV5 - blood volume (part of SV), pu
- Page 79 and 80: Conflict of interestNone declared.A
- Page 81 and 82: Issue 16. May 2020 | Cardiometry |
Figure 2. Demonstration of the parallel recording mode of respondent's cardiooculometric indicators of response to the USE form
presentation.
Table 4.
Test scores 1 2 3
The USE results 0,367
Stress tolerance (Boston test) 0,418 0,523
Susceptibility to stress of type A (Friedman-Rosenman methodology) 0,462
Subjective conditioning/readiness to USE 0,704
Extraversion (TIPI-RU questionnaire) 0,277 0,693
Friendliness(TIPI-RU questionnaire) 0,654
Fairness(TIPI-RU questionnaire) 0,388 0,539
Emotional stability(TIPI-RU questionnaire) 0,402 0,528
Openness to experience (intelligence) (TIPI-RU questionnaire) 0,477 0,398
Self-efficacy 0,307 0,706
E score Extravertion (Keirsey questionnaire) 0,354 0,803
I score Introvertion (Keirsey questionnaire) 0,364 0,743 -0,396
S score Sensation(Keirsey questionnaire) 0,694 0,414
N score Intuition (Keirsey questionnaire) 0,734
T score Thinking (Keirsey questionnaire) 0,727
F score Feeling (Keirsey questionnaire) 0,756 0,328
J score Judging (Keirsey questionnaire) 0,623 0,307
P score Perceiving (Keirsey questionnaire) 0,686 0,401
It has been found that the factor structure of the
correlation relationships upon the oblique rotation
(Оblique Rotation) exactly corresponds to the structure
obtained after the varimax rotation (Varimax Rotation).
When optimizing the factor structure of the
revealed correlation relationships, we analyzed variants,
which included from 3 (covered up to 80% of the
dispersion and associated with larger losses of information)
to 7 factors (covered over 90% of the dispersion
and characterized by the presence of a significant
Table 5
variables 1 2 3 4
SI 1 0,462 -0,883
SI 2 0,338 -0,618
SI 3 0,782
SI 4 0,894 -0,285
USE mark 0,887
Issue 16. May 2020 | Cardiometry | 31
Change language