Modern Pediatrics. Ukraine. (2026).3(155): 111-120. doi: 10.15574/SP.2026.3(155).111120
Nykytyuk S. O., Sverstyuk A. S., Levenets S. S., Hariyan T. V., Synytska V. O., Kulchytskyi V. Y.
I. Horbachevsky Ternopil National Medical University, Ukraine

For citation: Nykytyuk SO, Sverstyuk AS, Levenets SS, Hariyan TV, Synytska VO, Kulchytskyi VY. (2026). Psychological сhanges after complicated viral infections. Modern Pediatrics. Ukraine. 3(155): 111-120. doi: 10.15574/SP.2026.3(155).111120.
Article received: Dec 18, 2025. Accepted for publication: Apr 13, 2026.

Pneumonia remains one of the most pressing medical and social problems worldwide. Epidemiological research indicates that mental disorders, such as depression, bipolar affective disorder and schizophrenia, are risk factors for the development of acute respiratory infections.
Aim – to conduct a review of the literature on psychological changes following complicated viral infections using the Scopus database, and to construct a regression model to predict the risk of psychological changes following complicated viral infections.
Materials and methods. The first stage involved an analytical review and analysis of recent scientific publications. In the second stage, a questionnaire survey was conducted among 100 respondents; based on the results, a multivariate regression model was developed to predict psychological changes following complicated viral infections. The model includes 23 statistically significant factors reflecting psychological changes following complicated viral infections.
Results. A model was built to predict the risk of psychological changes after complicated viral infections, in particular pneumonia. As a result of the analysis, it was found that the studied anthropometric data and clinical indicators are highly significant predictors. The resulting regression equation allows you to predict with high accuracy the level of psychological changes in patients based on the input parameters.
Conclusions. The Scopus database makes it possible to optimise the comprehensiveness of relevant searches for scientific literature on psychological changes following complicated viral infections. For the first time, a regression model has been developed to predict the risk of psychological changes following complicated viral infections and pneumonia. A multidisciplinary approach (neurologist, psychiatrist, GP, psychologist) and early screening for anxiety and depressive disorders are required.
The authors declare no conflict of interest.
Keywords: psychological model, viral infections, pneumonia, psycho-emotional state, ANOVA, regression analysis.

REFERENCES

1. Caliman-Sturdza OA, Gheorghita R, Lobiuc A. (2025). Neuropsychiatric Manifestations of Long COVID-19: A Narrative Review of Clinical Aspects and Therapeutic Approaches. Life. 15: 439. https://doi.org/10.3390/life15030439; PMid:40141784 PMCid:PMC11943530

2. Coughlin SS. (2012). Anxiety and Depression: Linkages with Viral Diseases. Public Health Rev. 34(2): 7. https://doi.org/10.1007/BF03391675; PMid:25264396 PMCid:PMC4175921

3. De Moraes WMAM, de Moura FC, da Costa Moraes TC, Oliveira de Sousa LG, Dos Santos Rosa T et al. (2019, May). Oxidative stress, inflammation, psychological status, and severity of respiratory infections are negatively affected during the pre-contest period in amateur bodybuilders. Appl Physiol Nutr Metab. 44(5): 468-476. Epub 2018 Sep 24. https://doi.org/10.1139/apnm-2018-0430; PMid:30248274

4. Gao Y, Liang Z, Mao B, Zheng X, Shan J, Jin C et al. (2024, Jun). Gut microbial GABAergic signaling improves stress-associated innate immunity to respiratory viral infection. J Adv Res. 60: 41-56. Epub 2023 Jun 22. https://doi.org/10.1016/j.jare.2023.06.008; PMid:37353002 PMCid:PMC10284622

5. Hazumi M, Kataoka M, Narita Z, Usuda K, Okazaki E, Nishi D. (2025, Sep). Psychological distress after COVID-19 recovery and subsequent prolonged post-acute COVID-19 syndrome: A longitudinal study with one-year follow-up in Japan. J Psychosom Res. 196: 112323. Epub 2025 Jul 9. https://doi.org/10.1016/j.jpsychores.2025.112323; PMid:40651324

6. Herasymiuk M, Sverstiuk A, Kit I. (2023, May). Multifactor regression model for prediction of chronic rhinosinusitis recurrence. Wiadomości Lekarskie Medical Advances. LXXVI; 5; I: 928-935. https://doi.org/10.36740/WLek202305106; PMid:37326072

7. Leshchyna IV. (2023, Dec). Phenomenological structure of anxiety disorders in persons who have transferred COVID-19. Medicine Today and Tomorrow. 92(4): 82-86. https://doi.org/10.35339/msz.2023.92.4.les

8. Mathkor DM, Tawil S, Johargy AK, Faidah H, Babalghith AO, Jalal NA et al. (2025, Nov). Respiratory and gastrointestinal infections among Hajj pilgrims during the 2012-2025 seasons: A systematic review. J Infect Public Health. 18(11): 102951. Epub 2025 Sep 3. doi: 10.1016/j.jiph.2025.102951. PMID: 40914991.https://doi.org/10.1016/j.jiph.2025.102951; PMid:40914991

9. Musiienko V, Marushchak M, Sverstuik A, Filipyuk A, Krynytska I. (2021). Prediction Factors For The Risk Of Hypothyroidism Development In Type 2 Diabetic Patients. Pharmacology OnLine. 3: 585-594.

10. Narayanan SN, Padiyath S, Chandrababu K, Raj L, PS BC, Ninan GA et al. (2025, Jan). Neurological, psychological, psychosocial complications of chronic-COVID and their management. Neurol Sci. 46(1): 1-23. Epub 2024 Nov 9. https://doi.org/10.1007/s10072-024-07854-5; PMid:39516425 PMCid:PMC11698801

11. Nykytyuk S, Levenets S, Gariyan T, Gariyan T, Synytska V, Sverstyuk A. (2025). Quality of life of children with chronic fatigue and stress disorders during war: a systematic review of the literature. Neonatology, Surgery and Perinatal Medicine. 15; 4(58): 204-211. https://doi.org/10.24061/2413-4260.XV.4.58.2025.29

12. Nykytyuk SO, Hariyan TV, Levenets SS. (2024). Hemorrhagic vasculitis in an adolescent induced by the COVID-19 virus. Modern Pediatrics. Ukraine. 6(142): 120-126. https://doi.org/10.15574/SP.2024.6(142).120126

13. Nykytyuk SO, Klymnyuk SI, Pivovarchuk DS, Sverstiuk AS. (2023). Multifactorial model of prediction of severe course and organ and system damage in Lyme borreliosis in children. Modern paediatrics. 2(130): 6-17. https://doi.org/10.15574/SP.2023.130.6

14. Nykytyuk SO, Kuchma PM, Kito VV, Levenets SS, Hariyan TV, Yakymchuk YuB. (2023). Multisystem inflammatory syndrome MIS-C in children after COVID-19 infection article Ukrainian Journal of Perinatology and Pediatrics. 4(96): 128-135. https://doi.org/10.15574/PP.2023.96.128

15. Nykytyuk SO, Sverstiuk AS, Klymnyuk SI, Pyvovarchuk DS, Palaniza YB. (2023). Approach to prediction and receiver operating characteristic analysis of a regression model for assessing the severity of the course of Lyme borreliosis in children. Rheumatology. 61(5): 345-352. https://doi.org/10.5114/reum/173115; PMid:37970115 PMCid:PMC10634403

16. Nykytyuk SO, Sverstiuk AS, Pyvovarchuk DS, Klymnyuk SI. (2023). A multifactorial model for predicting severe course and organ and system damage in Lyme borreliosis in children. Modern pediatrics. Ukraine. 2(130): 6-16. https://doi.org/10.15574/SP.2023.130.6

17. Perestiuk V, Sverstyuk A, Kosovska T, Volianska L, Boyarchuk O. (2025). A Predictive Model for the Development of Long COVID in Children. International Journal of Environmental Research and Public Health. 22(11): 1693. https://doi.org/10.3390/ijerph22111693; PMid:41302639 PMCid:PMC12652589

18. Teixeira AL, Krause TM, Ghosh L, Shahani L, Machado-Vieira R, Lane SD et al. (2021, Nov 1). Analysis of COVID-19 Infection and Mortality Among Patients With Psychiatric Disorders, 2020. JAMA Netw Open. 4(11): e2134969. https://doi.org/10.1001/jamanetworkopen.2021.34969; PMid:34812848 PMCid:PMC8611476

19. Turriziani L, Mancini A, Midiri M, Albertini ML, Butera A. (2025). Association Between Respiratory Infections and Risk of Autism Spectrum Disorder: An Overview, Current Respiratory Medicine Reviews. 21(1): 48-58. https://doi.org/10.2174/011573398X281954240614075538

20. Wang Q, Xu R, Volkow ND. (2021). Increased risk of COVID-19 infection and mortality in people with mental disorders: analysis from electronic health records in the United States. World Psychiatry. 20(1): 124-130. https://doi.org/10.1002/wps.20806; PMid:33026219 PMCid:PMC7675495

21. Zhang Y, Hui FKP, Duffield C, Gao CX. (2025). Profiling factors of occupant behavior change towards indoor respiratory infection control in post-pandemic Australia. Facilities. 43; 910. 616-637. https://doi.org/10.1108/F-07-2024-0093