RU2268649C2 - Method for determining professional fitness - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: method involves determining the number of testees of high professional success whose results exceed standard level on informative indices used in various methods. Integral distribution law is built on the testee set and error threshold is determined. The value is used for dividing the testees having passed the tests according to the same methods into employment-fit and unfit ones. Boundary dividing the set into employment-fit and unfit persons is determined on total error number being less than 0.8-0.9.

EFFECT: high reliability in determining employment fitness in single group.

4 cl, 1 dwg

Description

The present invention relates to medicine, in particular to occupational health and occupational diseases, and may find application in the selection of personnel according to the level of development of psychophysiological indicators.

Ways to determine professional suitability are widely known (see Intersectoral guidelines for the organization and conduct of psychophysiological professional selection. All-Union Scientific Research Institute of Labor Protection of the All-Union Central Council of Trade Unions in Sverdlovsk, 1984. UDC 613.62-08). They consist in dividing the subjects into groups according to the level of professional success, and the criterion for dividing, depending on the task, may be various indicators, such as productivity, injury rate, driving class and others. Most often, subjects are divided into two groups - with high and low levels of professional success. Both groups are tested by a set of psychophysiological methods: measuring the time of simple and complex differentiating reactions, attention, memory, etc., as well as personality tests: Eysenck, Cattell, MMPI, etc. On the basis of the test results, informative psychophysiological indicators are distinguished, for example, by comparing the distributions of indicators for x ² in groups with a good and poor level of professional success and for the correlation coefficient of indicators with the level of professional success. Then, using the method of pattern recognition, a “decisive rule” is built, with which, on the basis of an examination of a candidate for a profession, he is assigned to the group of “good” or “bad” specialists.

Closest to the claimed combination of features is a method for determining the professional suitability of firefighters (AS No. 1445695, class A 61 B 5/16, Bull. No. 47, 1988), in which firefighters measure parameters of a high and low level of professional skill organism before and after performing physical and emotional stress with obtaining a generalized quantitative assessment of the results and comparing it with a threshold value. The described method is adopted as a prototype.

A disadvantage of the known methods for determining professional suitability is the need to distinguish two alternative representative groups from among the subjects for professional success, which is not always possible in practice. Objectively, there are always more “good” specialists. In some cases, it is simply not possible to single out a representative group with low professional success.

The objective of the invention is to create a method that allows you to determine professional suitability, using one group of subjects with high professional success.

To solve the problem in the method of determining professional suitability, which consists in presenting the subject with psychophysiological methods and personality tests, recording and analyzing psychophysiological data, obtaining an integrated assessment of their performance according to the test results and comparing it with threshold values, according to the invention, using one group of subjects with high the level of professional success, determine the number of subjects who went beyond the norm for one, two, three, etc. indicators or that have never gone beyond the norm until the total number of cases reaches a probability of 0.8-0.9, while the number of cases corresponding to this probability is considered the boundary between high and low level of professional success.

In the analysis of the prior art, no analogue has been identified, characterized by features identical to all the essential features of the claimed solution, thus, the claimed solution meets the requirement of "novelty."

Not detected are also signs that are distinctive in the claimed solution, i.e. the claimed solution meets the requirement of "inventive step".

The method for determining professional suitability includes the following operations.

1. A group of professionally important qualities of specialists is determined using expert opinions.

2. Select a group of subjects with high production success according to the personnel department.

3. The selected group is examined using psychophysiological techniques and personality tests implemented, for example, on a personal computer.

4. Analyze the data obtained, examining them for multicollinearity and highlighting informative indicators.

5. Determine the number of subjects from the group with high professional success, the results of which went beyond the norm for certain indicators.

6. Build the integral distribution law of such subjects and determine the threshold error values, on the basis of which the subjects passing the same set of methods are divided into “good” and “bad”. The threshold of the subjects is determined with a probability of 0.8-0.9.

Example. Conducted a professional psycho-physiological selection of bus drivers. A group of drivers of 54 people (n = 54) with a high professional level was examined using 10 methods implemented on a personal computer:

- speed and accuracy of hand-eye reactions;

- eye;

- short-term and random access memory;

- the accuracy of the reaction to a moving object;

- mobility of nervous processes;

- stability, switchability and distribution of attention;

- attitude to risk;

- emotional stability;

- self-control and normative behavior;

- frustration anxiety.

After analysis of the data obtained, 23 indicators were selected (N = 23).

Obtained by examination of the data are shown in table 1.

Table 1 Methodology Short-term memory RAM ("Encryption") Attention Stability (Proof Test) ... Methodology "Scales" N / n number of correctly named words number of correct answers task execution time, s number of mistakes task execution time, s ... number of correct answers task execution time, s one 7 39 153 9 143 6 176 2 6 40 149 0 193 b 89 3 7 39 169 7 185 9 120 . .. .. .. .. .. .. .. .. 52 7 39 168 2 187 8 160 53 6 38 147 0 319 3 132 54 9 39 152 2 153 9 151

Based on the data given in Table 1, the boundaries were found for each indicator, in determining which the values of the 10th and 90th percentiles were used.

table 2 Methodology Short-term memory RAM ("Encryption") Attention Sustainability (Corrective Test) ... Methodology "Scales" N number of correctly named words number of correct answers task execution time, s number of mistakes task execution time, s ... number of correct answers task execution time, s Boundary values ≤4 ≤3.7 ≥180 ≥16 ≥230 ... ≤4 ≥270

Next, the number of subjects was calculated, the test results of which did not go beyond the boundary values for any indicator or went for one indicator, two indicators, etc., as well as the relative values of these values.

Table 3 The number of exceeding the limit values 0 one 2 3 four 5 6 7 8 Number of subject 7 fourteen 8 16 5 2 one 0 one Relative value 0.13 0.26 0.15 0.296 0.090 0.037 0.018 0 0.018 Accumulated frequencies 0.130 0.390 0.540 0.836 0.92 0.96 0.98 0.98 1.00

The drawing shows a curve approximating the integral discrete distribution law of the number of indicators that go beyond the norm.

The facet of two groups characterizing the degree of professional suitability was identified: suitable (X≤4) and unsuitable (X> 4).

The proposed method for determining professional suitability was successfully applied at the Yekaterinburg Production Association of Passenger Cars No. 1. Its implementation has shown high efficiency of professional selection of drivers: according to the company, the number of accidents among professionally fit is 3 times lower, and the number of traffic violations is 5 times less than among professionally unsuitable drivers.

Claims (2)

1. The method of determining professional suitability, which consists in presenting the subjects with a set of methods and personality tests, registering and analyzing psychophysiological data with identifying informative indicators, obtaining an integral score and comparing it with a threshold value, characterized in that the number of subjects is determined from the group with high professional success , the results of which went beyond the norm in terms of informative indicators of methods, build the integral distribution law of such subjects and determine they determine the threshold value of errors, on the basis of which subjects passing the same set of techniques are divided into suitable and unsuitable. 2. The method for determining professional suitability according to claim 1, characterized in that the boundary of the division into suitable and unsuitable is determined when the total number of errors does not reach a probability of 0.8-0.9.