Cardiometric evidence data on human self-control of emotional states in the context of the use of metaphoric associative cards.

Vladimir A. Zernov, Elena V. Lobanova, Elvira V. Likhacheva, Lyubov P. Nikolaeva, Diana D. Dymarchuk, Denis S. Yesenin, Nikita V. Mizin, Aleksandr S. Ognev, Mikhail Y. Rudenko, Natalia Y. Galoi, Anna R. Sudarikova. Cardiometric evidence data on human self-control of emotional states in the context of the use of metaphoric associative cards. Cardiometry; Issue 16; May 2020; р.55-61; DOI: 10.12710/cardiometry.2020.16.5561; Available from: cardio-oсulometric-indicators

Metaphoric associative cards have been included for a long time in the repertoire of diagnostic and therapeutic means used by coaches and practical psychologists. The number of various sets of metaphoric associative cards grows rapidly. Observed is an increase in the frequency rate and variety of training courses aimed at their application.

But until now, no systematic studies related to tracing and assessments of psychophysiological responses in testing with the use of metaphoric associative cards have been conducted. The existence of such responses follows from an assumption that due to the associations, actualized by such cards, certain cognitive and affective components of the individual’s life experience begin "to awake” in the tested human subjects. For example, such mobilization can be manifested in a certain pattern of the cardiovascular system performance. If the idea of such associations is not only a theoretical construct, and if, with the use of metaphoric associative cards, some definite, substantively different, psychophysiological states of a human person are really fixed, then the transitions from one emotional state to another are accompanied by significant changes in the performance of the human organism, and, first of all, in the performance pattern of the heart. Taking into account the results of our previously described studies [1-3, 8-11], it can also be assumed that such changes can be recorded by assessing heart rate variability using the Baevsky stress index (SI).

Materials and methods

To verify the hypothesis formulated by us above herein, we have completed a series of experiments, in which various emotional states generated due to facing different life difficulties have been modeled with metaphoric associative cards. The psycho-physiological responses corresponding to these states have been recorded using PC-assisted hemodynamic analyzer Cardiocode. Besides, we have taken into account the results of our previous experiments, which confirm that an increased, in comparison with average values, Baevsky stress index (SI) can be considered as a fingerprint of the sthenic response to a stimulus, and a reduced value thereof can be treated as a fingerprint of the asthenic response to a stimulus [1-3, 8-11].We also have considered that just the SI values are more effec-

Figure 1. Examples of metaphoric cards most often selected by respondents to indicate their negative (images in upper row) and positive emotional states (images in lower row)

tive for the purpose of the evaluation of the person’s emotional response nature than changes in the human individual’s heart rate [1-3, 10].

Standard metaphoric associative cards of Moritz Egetmeyer (Moritz Egetmeyer ОН-Cards) and some other sets of coaching associative cards created by I. Shmelev and S. Gracheva have been used in our experiments. This choice has been made considering the widespread long-term practice of the effective use of precisely these sets of metaphoric associative cards by consultants and psychotherapists of various profiles as well as taking into our successful experience in the use of these sets in evaluating the psychophysiological consistency, when analyzing various ego states [2, 8].

Our study has covered 105 respondents (with an average age of 21, the standard deviation was 4.5 years in the sample as a whole). The same algorithm for the work of all respondents has included the sequential execution of the tasks as described below. To start with, respondents have been asked to select metaphoric cards, which they associate with the following emotional states:

• 1)    highest unreadiness/worst conditioning for an important exam;

• 2)    highest readiness/best conditioning for an important exam;

• 3)    highest unreadiness/worst conditioning for an important examinations period;

• 4)    highest readiness/ best conditioning for an important examinations period;

56 | Cardiometry | Issue 16. May 2020

• 5)    highest unreadiness/ worst conditioning for any important life's trial;

• 6)    highest readiness/ best conditioning for any important life's trial.

To illustrate this, some of the variants of metaphoric cards most often selected by the respondents to indicate their negative and positive emotional states are given in Figure 1 herein.

Upon presentation of the cards, each respondent for 15 seconds alternately fixed his attention on those cards, which he/she associated with each of the above emotional states. The next task (No. 7 according to the testing procedure) for each respondent was to select all the metaphoric cards that he/she associated with his/ her positive emotional states, referred to the highest readiness/best conditioning for an important exam, an important examination period, for any important life’s trial, and thereupon to fix his/her attention on all such cards for 15 seconds in parallel. The final task (No. 8 according to the testing procedure) for each respondent was to focus his/her most possible attention to a freely swinging pendulum on a tripod and to how the pointed part of the pendulum weight drew elliptical trace designs in sand at the pendulum’s bottom.

When performing the above tasks, cardiograms in the examinees were recorded using PC-assisted hemodynamic analyzer Cardiocode. Upon completion of the recording, utilizing original specific algorithms of the Cardiocode software, values of the Baevsky stress index (SI) were calculated for each examinee.

The statistical analysis of the obtained data has been performed using statistical package STADIA 8.0.

Results and discussion

The obtained statistical patterns in determining the SI values for various emotional states in the respondents are presented in Table 1 herein.

The first column in the present and all the following tables shows the numbers to indicate the following emotional states, which appear, when the respondents have fixed their attention:

• 1)    on those metaphoric cards, which are associated with their highest unreadiness/worst conditioning for an important exam;

• 2)    on those metaphoric cards, which are associated with their highest readiness/best conditioning for an important exam;

• 3)    on those metaphoric cards, which are associated with their highest unreadiness/ worst conditioning for an important examination period;

• 4)    on metaphoric cards, which are associated with their highest readiness/ best conditioning for an important examination period;

• 5)    on metaphoric cards, which are associated with their highest unreadiness/ worst conditioning for any important life’s trial;

• 6)    on metaphoric cards, which are associated with their highest readiness/ best conditioning for any important life’s trial;

• 7)    on all simultaneously considered metaphoric cards, which are associated with their highest readiness/ best conditioning for an important exam, an examination period, any life’s trial;

• 8)    on the freely swinging pendulum on a tripod and on how the pointed part of the pendulum weight draws elliptical trace designs in sand at the pendulum’s bottom.

The static significance of differences in mean values was confirmed using the χ criterion (chi-square), which, as noted above, has been assessed using statistical package STADIA 8.0.

To identify a latent structure of the obtained data collection, a factor analysis has been conducted. Besides, it has been also taken into account that the distribution of the calculated indicators of the heart rate variability SI values differ from the Gauss-Laplace distribution. Therefore, in order to identify the correlation relationships, we have used the Spearman rank correlation and the Kendall concordance coefficients. Since the nature of the identified relationships for each of these coefficients is similar, the data for the Spearman coefficient are given by us herein only because of greater generality of the latter.

In our explorative factor analysis, conducted has been a step-by-step reduction of the number of the main components, followed by Varimax rotation for formulating a hypotheses on the optimal factor structure of the studied latent relations. The obtained data allowed suggesting that, as shown in Table 2 herein, the optimal structure should include 4 factors.

During the confirmatory factor analysis, in order to verify the hypothesis for the optimal factor structure in the studied latent relations, a more detailed calculation of factor loadings, reflecting their geomet-

Table 1

The main statistical parameters of the SI values for various emotional states in the respondents

Ego-states	Arithmetic mean	Standard deviation	Median	Asymmetry	Excess
1	429	378,6	290	2,019	8,042
2	292,1	209,8	231	1,286	4,589
3	343,9	276,2	262	1,874	7,926
4	298,7	250,8	223	2,163	8,904
5	330,7	260,1	290	3,141	19,3
6	273,7	234,4	199	2,21	9,143
7	242,1	166,4	204	1,419	5,453
8	276,7	198,7	256	1,319	4,555

Table 3

Eigenvalues and percentage of an interpretable dispersion of factors after Varimax rotation at the stage of the confirmatory factor analysis

Factor:	1	2	3	4
Eigenvalue	1,02	1,009	0,9981	1,015
Dispersion (%)	12,75	12,61	12,48	12,69
Cumulative %	12,75	25,36	37,84	59,53

Table 5

Eigenvalues and percentage of an interpretable dispersion of factors after Quartimax rotation at the stage of the confirmatory factor analysis

Factor:	1	2	3	4
Eigenvalue	1,85	1, 935	1,324	0,8993
Dispersion (%)	23,13	24,19	16,55	11,24
Cumulative %	23,13	47,32	63,86	75,1

Table 2

Eigenvalues and percentage of an interpretable dispersion of factors after Varimax rotation

Factor:	1	2	3	4	5	6	7	8
Eigenvalue	1,02	1,009	0,9981	1,015	1,021	0,9956	0,9721	0,9687
Dispersion (%)	12,75	12,61	12,48	12,69	12,77	12,45	12,15	12,11
Cumulative %	12,75	25,36	37,84	59,53	63,29	75,74	87,89	100

Table 4

Factor structure of the correlation relationships after Varimax rotation at the stage of the confirmatory factor analysis

Ego-states	Number of factor
	1	2	3	4
1		-0,806
2			-0,7626
3		-0,775
4			-0,756
5	0,6129	-0,5775
6	0,7088
7	0,7995
8				0,95

Table 6

Factor structure of the correlation relationships after Quartimax rotation at the stage of the confirmatory factor analysis

Ego-states Number of factor 1 2 3 4 1 -0,8259 2 -0,7325 3 -0,7874 4 -0,7305 5 0,6031 -0,5752 6 0,7308 7 0,8187 8 0,9271 ric closeness to each individual factor, has been completed. In addition to the orthogonal rotation method (Varimax rotation), applied have been the Quarti-max rotation, Equimax rotation and Oblique rotation methods.

The tables given below illustrate the results of various variants for optimizing the factor structure at the stage of the confirmatory factor analysis. The indicated data are obtained by processing the matrix of the Spearman rank correlation coefficients. Tables 4, 6, and 8, according to the recommendations in paper [4], give values of factor loading not lower than 0.5 only.

Tables 3 and 4 show the parameters of the factor structure after using the orthogonal rotation method (Varimax rotation), with which we sought to minimize the number of variables with high loadings on each factor.

Tables 5 and 6 herein present the data obtained after applying the Quartimax rotation method, with which we tried to minimize the number of factors, required for a meaningful interpretation of each of the variables used.

Tables 7 and 8 given herein indicate the results obtained from the Equimax rotation method, which was used to simultaneously minimize the number of 58 | Cardiometry | Issue 16. May 2020

variables with large factor loadings and the number of factors interpreting them.

We have also completed the Oblique rotation procedure, with which we have sought to minimize the number of factors without providing their complete independence (orthogonality). It has turned out that the factor structure of the correlation relationships according to the Oblique rotation method exactly corresponds to that structure which has been obtained upon the Varimax rotation application.

As shown in Tables 3, 5 and 7, the hypothesis for an applicability of employing 4 factors for describing the optimal structure of the latent relations, provided that the analyzed objects with eigenvalues greater than 1 are referred to as the main components of the scattering ellipse axes, is confirmed for the Equimax rotation method only. Therefore, at the final stage of the confirmatory factor analysis, all the above main components calculation procedures and all the above types of their rotation have been performed for models containing only 3 factors. The results from the final stage of the confirmatory factor analysis are presented in Tables 9-14 herein.

As it is the case with all the previous stages, in order to identify the correlation relationships, we have

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 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 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

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 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:

• -    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 readiness/conditioning for successful overcoming life’s trials;

Table 11

Eigenvalues and percentage of an interpretable dispersion of factors after Quartimax rotation at the final stage of confirmatory factor analysis

Factor:	1	2	3
Eigenvalue	2,388	1, 945	1,005
Dispersion (%)	29,85	24,13	12,56
Cumulative %	29,85	54,16	66,72

Table 13

Eigenvalues and percentage of an interpretable dispersion of factors after Equimax rotation at the final stage of the confirmatory factor analysis

Factor:	1	2	3
Eigenvalue	1,854	1, 861	1,623
Dispersion (%)	23,17	23,26	20,29
Cumulative %	23,17	46,43	66,72

Table 12

Factor structure of the correlation relationships after Quartimax rotation at the final stage of the confirmatory factor analysis

Ego-states	Number of factor
	1	2	3
1	0,1671	-0,8282	-0,2114
2	0,3202	-0,4789	-0,6368
3	0,2279	-0,7782
4	0,5261	-0,1929	-0,5858
5	0,5386	-0,5576	-0,3639
6	0,7462	-0,2625
7	0,806
8	0,6575		-0,2702

Table 14

Factor structure of the correlation relationships after Equimax rotation at the final stage of the confirmatory factor analysis

Ego-states	Number of factor
	1	2	3
1		-0,8043	-0,3287
2		-0,4158	-0,7471
3	0,1709	-0,7709	-0,1912
4	0,3006	-0,1373	-0,7403
5	0,6065	-0,5934	0,1163
6	0,686	-0,2622	-0,2954
7	0,776		-0,2206
8	0,5327		-0,4721

• 2)    cards-indicators of their differentiated emotional unreadiness/unconditioning for successful overcoming the certain life’s trials;

• 3)    cards-indicators of their differentiated emotional readiness/conditioning for successful overcoming the certain life’s trials.

Special attention deserves a significant contribution to the first selected factor (conventionally it may be defined as an integrative readiness/conditioning for life’s trials) among the SI values obtained when the respondents focus on those metaphoric cards, which are associated with their unreadiness/unconditioning for their examination period. The matter is that, in their posttest interviews, many respondents have mentioned their unwillingness to once again retrieve their negative states associated with this kind of the metaphoric cards. They desired to actively use in practice the revealed chance to evoke their positive emotional states with the use of the metaphoric cards. In other words, at this stage the respondents have expressed a constructive form of their supra-situational activity aimed at a positive correction of their own emotional state (the subject-genetic nature of such supra-situational activity is described in more detail in [5-7]). In these cases, the metaphoric associative cards become effective stimulation for the creation and maintenance of positive mindset to achieve a success in overcoming significant life difficulties.

As we see from the data presented, the SI values for positive emotional states form a part of Factor 1 and 3, as a rule. The exception is those SI values recorded when the respondents focus on those metaphoric cards, which are associated with their unreadiness/ unconditioning for their examination period. We have described the possible cause of this exception in the preceding paragraph.

The SI values related to the negative emotional states are the major contributors to factor 2. Moreover, this regularity and this factor structure, as a whole, are retained for all the rotation variants used. This, in addition to the fact of statistically significant differences in average SI values, also demonstrates a substantial commonality of the positive emotional states, which considerably differs from that substantial commonality of those SI values, which have been recorded for the negative emotional states.

It should be noted that the most powerful factors in all variants of rotation include both the SI values for all positive emotional states, when they have been actualized individually, and those SI values, which have been reported, when our respondents have worked with the cards, which are associated with all three positive emotional states. This suggests that the factor structure confirms that at the psycho-physiological level there is a positive training effect produced by alternate actualization of positive emotional states by the respondents using the metaphoric cards selected by them.

Conclusions

The obtained evidence data allow concluding that the metaphoric associative cards can serve not only as a forecasting tool, a sort of predictors of human behavior in certain emotionally charged, stressful situations, but also as a means for active modeling of optimal conditioning for successful overcoming of the above unfavorable situations.

The conducted studies have experimentally confirmed the validity of our hypothesis that the metaphoric associative cards, in addition to the colorful description of the phenomena, personified by the respondents, provide and mobilize the human physiological response to a specific type thereof. It has been shown that such mobilization is manifested in a certain pattern of the cardiovascular system performance.

As it is the case with the theoretical constructs investigated by us earlier in the field of transactional analysis [2, 8], the metaphoric associative cards really assist an individual to activate his/her definite, substantively different, psychophysiological status. The transitions from one ego-state to another are actually accompanied by significant changes in the human organism performance, and, first of all, in the performance of the heart. The reliable marker of such changes is the heart rate variability assessment based on the Baevsky stress index (SI) technique.

Besides, as in [1-3], we have obtained experimental confirmation of the validity of using such a complex cardiometric indicator as the Baevsky stress index (SI) to assess the effectiveness of various psycho-correction methods. But while earlier it has been applicable to the methods of psychosomatic self-regulation and transactional analysis [1-3, 8-11], now an efficient use of the Baevsky stress index has been also demonstrated in relation to the metaphoric associative cards in correction of various types of the human behavior.

Statement on ethical issues

Research involving people and/or animals is in full compliance with current national and international ethical standards.

Conflict of interest

None declared.

Author contributions

The authors read the ICMJE criteria for authorship and approved the final manuscript.