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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.

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Table 7

Eigenvalues and percentage of explained dispersion of factors

after Equimax rotation at the stage of the confirmatory factor

analysis

Factor: 1 2 3 4

Eigenvalue 1,633 1, 739 1,509 1,128

Dispersion (%) 20,41 21,73 18,86 14,1

Cumulative % 20,41 42,14 61 75,1

Table 8

Factor structure of the correlation relationships after Equimax

rotation at the stage of the confirmatory factor analysis

Ego-states

Number of factor

1 2 3 4

1 -0,7955

2 -0,7681

3 -0,7665

4 -0,7575

5 0,6116 -0,5729

6 0,6952

7 0,7865

8 0,9692

applied Spearman rank correlation and Kendall concordance

coefficients. Since the nature of the identified

relationships for each of these coefficients is the

same, in our further presentation, the data for the

Spearman rank correlation coefficients are given only

because of greater generality of the latter. Tables 10, 12

and14 herein show factor loading values up to 0.1 for

the purpose of a more detailed analysis of the latent

relations.

Table 9 and 10 given herein indicate the parameters

of the factor structure after using the orthogonal rotation

method (Varimax rotation).

Tables 13 and 14 herein show the results upon

completion of the Equimax rotation procedure.

At the final stage of the confirmatory factor analysis,

the Oblique rotation procedure has been also completed.

As it is the case with the 4 factor model, the factor

structure of the correlation relationships according

to the Oblique rotation method exactly corresponds to

that structure, which has been identified upon completion

of the Varimax rotation procedure.

As shown in Tables 9, 11 and 13, the hypothesis

for the applicability of using 3 factors to describe the

optimal latent relations structure, when the analyzed

objects with eigenvalues greater than 1 are referred to

as the main components of the scattering ellipse axes,

has been verified in full. The marker variables, which

allow us to give a clear interpretation of their possible

nature, remain the same under all types of rotation for

factors similar in structure. The above marker variables

are as follows:

Table 9

Eigenvalues and percentage of an interpretable dispersion of

factors after Varimax rotation at the final stage of confirmatory

factor analysis

Factor: 1 2 3

Eigenvalue 1,914 1,86 1,563

Dispersion (%) 23,93 23,25 19,54

Cumulative % 23,93 47,18 66,72

Table 10

Factor structure of the correlation relationships after Varimax

rotation at the final stage of confirmatory factor analysis

Ego-states

Number of factor

1 2 3

1 -0,8036 -0,3285

2 0,1052 -0,414 -0,7449

3 0,1763 -0,7707 -0,1869

4 0,324 -0,136 -0,7292

5 0,6007 -0,5949 0,1366

6 0,6958 -0,2628 -0,2711

7 0,7833 -0,1926

8 0,5494 -0,4525

- for factor 1: the SI values obtained when the respondents

simultaneously focus on those metaphoric cards,

which are associated with their highest readiness/best

conditioning for their exam, examination period and

successful overcoming a life’s trial;

- for factor 2: the SI values obtained when the respondents

focus on those metaphoric cards, which are associated

with their unreadiness/worst conditioning

for the exam;

- for factor 3: the SI values obtained when the respondents

focus on those metaphoric cards, which are associated

with their highest readiness/best conditioning

for a given exam only.

Thus, the latent relations between the obtained

data may be compactly described with the use of three,

practically unipolar, factors. Closeness to unipolarity

for each of these factors is provided by unidirectionality

of variables projections on each of them, when the

factor model tends to a simple structure. As known,

according to the Thurstone criteria, simple structures

are built in such a way that each variable has a high

loading on one factor and a low one on another in

parallel [4]. As a result, it significantly simplifies an

interpretation of latent relations to be identified. In

our case, the metaphoric cards selected by our respondents,

taking into account the commonality of the

cardiac responses to the related associations, may be

conditionally classified into the following groups:

1) cards-indicators of their integrative emotional

readi ness/conditioning for successful overcoming life’s

trials;

Issue 16. May 2020 | Cardiometry | 59

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