Quality of life of patients with complete loss of teeth and the psychometric properties of the OHIP-20 DG questionnaire. Part 3. Investigation of latent variables

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Abstract

BACKGROUND: In the rehabilitation of patients with complete loss of teeth, an important aspect is the study of their quality of life (QL) as an indicator reflecting the effectiveness of treatment.

AIM: Use latent variables and control their magnitude to control the development or suppression of symptoms in patients.

MATERIAL AND METHODS: Within the framework of the modern theory of latent variables, the study examined the QL of patients with complete loss of teeth at various stages of dental orthopedic treatment.

RESULTS: The average relative error of the forward and reverse conversion of the “polytomic score indicators, i.e., latent variables,” was 3.69%, which indicated a very high accuracy of measurements of latent variables. The QL estimates obtained by different methods were in good agreement with each other, and the Pearson correlation coefficients were 0.991, 0.999, and 0.982 before and after prosthetics. The characteristic curves of the questionnaire items were close to the experimental score indicators (p <0.05). The parameters of the latent variables at various stages of treatment were calculated using the Kolmogorov–Smirnov criterion, which showed that their distributions were normal, and the medians moves in different directions, which corresponded to an increase in QoL during treatment and adaptation. The interpretation of latent variables is proposed: θi is the resistance (“reserve level”) of the body of the i-th patient before prosthetics or the effectiveness of treatment and adaptation after prosthetics; βj presents the severity and intensity of pathogenic factors in the development of the j-th symptom, and Pij is the probability of the removal of the j-th symptom in the i-th patient.

CONCLUSION: It has been established that by identifying and measuring latent variables, as well as controlling their magnitude, we can control the level of development or suppression of symptoms in patients.

About the authors

Sergey A. Muslov

A.I. Evdokimov Moscow State Medical and Dental University

Author for correspondence.
Email: muslov@mail.ru
ORCID iD: 0000-0002-9752-6804

канд. мед. наук, доцент

Russian Federation, 20, Delegatskaya str., buil. 1, Moscow, 127018

Nurmukhamet S. Ruzuddinov

Al-Farabi Kazakh National University

Email: ruzuddinov@rambler.ru
ORCID iD: 0000-0001-8778-2401

MD, Cand. Sci. (Med.), аssociate professor

Kazakhstan, Almaty

Sergey D. Arutyunov

A.I. Evdokimov Moscow State Medical and Dental University

Email: sd.arutyunov@mail.ru
ORCID iD: 0000-0001-6512-8724

MD, Dr. Sci. (Med.), professor

Russian Federation, 20, Delegatskaya str., buil. 1, Moscow, 127018

Evgeny A. Chizhmakov

A.I. Evdokimov Moscow State Medical and Dental University

Email: evgeniychigmakov@yandex.ru
ORCID iD: 0000-0003-1313-3307
Russian Federation, 20, Delegatskaya str., buil. 1, Moscow, 127018

Sergey I. Moiseev

Voronezh State Technical University

Email: moiseevs@mail.ru
ORCID iD: 0000-0002-6136-9763

Cand. Sci. (Physico-Mathematical), associate professor

Russian Federation, Voronezh

Anatoliy A. Maslak

Kuban State University

Email: rasch_measurement@mail.ru
ORCID iD: 0000-0002-3189-4858

Dr. Sci. (Technical), professor

Russian Federation, Slavyansk-on-Kuban

Anton A. Pivovarov

A.I. Evdokimov Moscow State Medical and Dental University

Email: pivovarovanton@mail.ru
ORCID iD: 0000-0001-9778-0258

MD, Cand. Sci. (Med.), associate professor

Russian Federation, 20, Delegatskaya str., buil. 1, Moscow, 127018

Maria S. Platonova

A.I. Evdokimov Moscow State Medical and Dental University

Email: platonovamaria@yandex.ru
ORCID iD: 0000-0002-0137-857X
Russian Federation, 20, Delegatskaya str., buil. 1, Moscow, 127018

References

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Supplementary files

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2. Fig. 1. Variation of the integral indicator of the quality of life of patients before prosthetics, obtained by different methods.

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3. Fig. 2. Variation of the integral indicator of the quality of life of patients immediately after prosthetics, obtained by different methods.

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4. Fig. 3. Variation of the integral indicator of the quality of life of patients after (after 3 months) prosthetics, obtained by different methods.

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5. Fig. 4. Characteristic curves of the questionnaire items (m=20). Points are the average values of 3 consecutive groups of ranked experimental data (score indicators of quality of life). Results after prosthetics. Matlab algebraic computing system.

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6. Fig. 5. Characteristic curves of categories and thresholds of the 1st item of the questionnaire (1st indicator).

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7. Fig. 6. Normalized severity of patients’ symptoms before prosthetics.

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8. Fig. 7. Distribution of latent variables θ and β of quality of life on the numerical axis before prosthetics. The logits of variables are postponed horizontally. Dotted lines — medians.

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9. Fig. 8. Distribution of latent variables θ and β of quality of life on the numerical axis immediately after prosthetics. The logits of variables are postponed horizontally. Dotted line — medians.

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10. Fig. 9. Distribution of latent variables θ and β of quality of life on the numerical axis after adaptation (after 6 months). The logits of latent variables are postponed horizontally. Dotted line — medians.

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11. Fig. 10. Variation of latent variables before (a) and after (b) prosthetics.

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12. Fig. 11. Evolution of medians of latent variables before and after prosthetics.

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13. Fig. 12. Comparison of measurement results of latent variables and scoring indicators.

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14. Fig. 13. Scheme of action and counteraction in the theory of latent variables.

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Copyright (c) 2022 Muslov S.A., Ruzuddinov N.S., Arutyunov S.D., Chizhmakov E.A., Moiseev S.I., Maslak A.A., Pivovarov A.A., Platonova M.S.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
 


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