Medical and social aspects of vocational guidance for persons with disabilities: assessing types of work activity using large language models
- Authors: Ryabtcev M.V.1, Ponomarenko G.N.1,2, Sokurov A.V.1, Mikhaylishin V.V.1
-
Affiliations:
- Albrecht Federal Scientific and Educational Center for Medical and Social Expertise and Rehabilitation
- North-Western State Medical University named after I.I. Mechnikov
- Issue: Vol 29, No 1 (2026)
- Pages: 25-35
- Section: Original study articles
- Submitted: 25.03.2026
- Accepted: 20.04.2026
- Published: 22.04.2026
- URL: https://rjmseer.com/1560-9537/article/view/704964
- DOI: https://doi.org/10.17816/MSER704964
- EDN: https://elibrary.ru/GBXQMH
- ID: 704964
Cite item
Abstract
BACKGROUND: Vocational guidance for persons with disabilities requires comparable and reproducible criteria that allow correlating persistent impairments of body functions with the requirements of specific types of work activity and factors of the working environment.
AIM: To form and validate a database of assessment indicators for types of work activity as a tool for their ranking within the framework of vocational guidance.
METHODS: A total of 435 types of work activity from the initial groups of the All-Russian Classifier of Occupations were analyzed. For each of them, a profile was formed based on 21 medico-social indicators, grouped into blocks of safety, ability to perform work functions, and working conditions. Primary assessments were obtained using several large language models on a unified ten-point scale; post-processing was performed for unified interpretation (“the higher, the more suitable”) and calculation of integral values by averaging inter-model assessments. External validation was conducted on independent expert survey data (87 questionnaires): in each question, five professions were compared on a 0–100 scale; a total of 9,135 assessments were processed. Comparisons were made after intra-question min-max normalization; the consistency of ranking (Spearman coefficient, Kendall coefficient), the proportion of concordant pairs, and the normalized rank difference were assessed.
RESULTS: The proportion of informative comparison blocks was 92.3%, and constant expert assessments were identified in 7.6% of cases. The consistency of the model ranking with experts was moderate: average Spearman coefficient ρ = 0.416, average Kendall coefficient τ-b = 0.363, proportion of concordant pairs 0.653, average normalized rank difference 0.278. The highest validity was demonstrated by indicators related to impairments of neuromuscular, skeletal, and movement-related (statodynamic) functions (necessity of using a wheelchair), while the indicator of emotional tension showed minimal consistency.
CONCLUSION: The formed assessment database is applicable for profiling and preliminary selection of types of work activity in the vocational guidance of persons with disabilities. For contextual factors of working conditions, clarification of operational definitions and expert calibration are required.
Full Text
About the authors
Mikhail V. Ryabtcev
Albrecht Federal Scientific and Educational Center for Medical and Social Expertise and Rehabilitation
Author for correspondence.
Email: ryabtcevmv@yandex.ru
ORCID iD: 0000-0001-5564-6093
SPIN-code: 2490-5403
Russian Federation, Saint Petersburg
Gennadiy N. Ponomarenko
Albrecht Federal Scientific and Educational Center for Medical and Social Expertise and Rehabilitation; North-Western State Medical University named after I.I. Mechnikov
Email: ponomarenko_g@mail.ru
ORCID iD: 0000-0001-7853-4473
SPIN-code: 8234-7005
MD, Dr. Sci. (Medicine), Professor, Сorresponding Member of the Russian Academy of Sciences
Russian Federation, Saint Petersburg; Saint PetersburgAndrey V. Sokurov
Albrecht Federal Scientific and Educational Center for Medical and Social Expertise and Rehabilitation
Email: ansokurov@yandex.ru
ORCID iD: 0000-0002-3736-2895
SPIN-code: 3376-1261
MD, Dr. Sci. (Medicine), Associate Professor
Russian Federation, Saint PetersburgViktor V. Mikhaylishin
Albrecht Federal Scientific and Educational Center for Medical and Social Expertise and Rehabilitation
Email: mikhailishin_v@mail.ru
ORCID iD: 0000-0002-9518-1945
SPIN-code: 9225-3365
MD, Cand. Sci. (Medicine)
Russian Federation, Saint PetersburgReferences
- Puzin SN, Shurgaya MA, Memetov SS, et al. Disability in the 21st Century: The State of the Problem of Medical and Social Rehabilitation and Habilitation of Disabled People in Modern Russia. Medical and Social Expertise and Rehabilitation. 2018;21(1–2):10–17. doi: 10.18821/1560-9537-2017-21-1-10-17 EDN: PJHCJH
- Goryainova MV, Karasaeva LA, Nurova AA, et al. Indicators of the Need for Disabled People in Professional Rehabilitation Measures. Medical and Social Expertise and Rehabilitation. 2021;24(2):21–27. doi: 10.17816/MSER65083 EDN: AKWVEP
- Ananyeva TN, Ilyukhina GI, Sazonova YuV. The system of vocational guidance and assistance in employment of disabled people and persons with limited health opportunities within the framework of the international movement “Abilympics”. Medical and Social Expertise and Rehabilitation. 2021;24(2):5–9. doi: 10.17816/MSER71135 EDN: DSKSZI
- Kalashnikov AI, Shamsheva EV, Salikova SI. Professional Rehabilitation of Disabled People in the Omsk Region: Current State and Development Prospects. Physical and Rehabilitation Medicine. 2019;1(4):49–55. doi: 10.26211/2658-4522-2019-1-4-49-55 EDN: YLIACA
- Levack WMM, Fadyl JK. Vocational interventions to help adults with long-term health conditions or disabilities gain and maintain paid work: an overview of systematic reviews. BMJ Open. 2021;11(12):e049522. doi: 10.1136/bmjopen-2021-049522
- Whitworth A, Baxter S, Cullingworth J, Clowes M. Individual Placement and Support (IPS) beyond severe mental health: an overview review and meta-analysis of evidence around vocational outcomes. Preventive Medicine Reports. 2024;43:102786. doi: 10.1016/j.pmedr.2024.102786
- Bond GR, Al-Abdulmunem M, Marbacher J, et al. A systematic review and meta-analysis of IPS supported employment for young adults with mental health conditions. Administration and Policy in Mental Health and Mental Health Services Research. 2023;50(1):160–172. doi: 10.1007/s10488-022-01228-9
- Weld-Blundell I, Shields M, Devine A, et al. Vocational interventions to improve employment participation of people with psychosocial disability, autism and/or intellectual disability: a systematic review. International Journal of Environmental Research and Public Health. 2021;18(22):12083. doi: 10.3390/ijerph182212083
- Nevala N, Pehkonen I, Teittinen A, et al. The effectiveness of rehabilitation interventions on the employment and functioning of people with intellectual disabilities: a systematic review. Journal of Occupational Rehabilitation. 2019;29:773–802. doi: 10.1007/s10926-019-09837-2
- Ponomarenko GN, editor. Rehabilitation of the disabled: a national guide. Moscow: GEOTAR-Media; 2018. 736 p. (In Russ.)
- De Baets S, Calders P, Schalley N, et al. Updating the evidence on functional capacity evaluation methods: a systematic review. Journal of Occupational Rehabilitation. 2018;28(3):418–428. doi: 10.1007/s10926-017-9734-x
- Safikhani P, Avetisyan H, Föste-Eggers D, Broneske D. Automated occupation coding with hierarchical features: a data-centric approach to classification with pre-trained language models. Discover Artificial Intelligence. 2023;3(1):6. doi: 10.1007/s44163-023-00050-y
- Clavié B, Soulié G. LLM4Jobs: unsupervised occupation extraction and standardization leveraging large language models. Knowledge-Based Systems. 2025;321:113526. doi: 10.1016/j.knosys.2025.113526
- Bethmann A, Schierholz M, Wenzig K, Zielonka M. Machine Learning for Occupation Coding — A Comparison Study. Journal of Survey Statistics and Methodology. 2021;9(5):1013–1034. doi: 10.1093/jssam/smaa033
- Tyao T, Yamazaki N, Otani M, et al. Application of large language models (LLM) for automatic classification of work accident text data: verification of accuracy and practicality. medRxiv. 2025. doi: 10.1101/2025.10.02.25337141
- Barth J, de Boer WEL, Busse JW, et al. Inter-rater agreement in evaluation of disability: systematic review of reproducibility studies. BMJ. 2017;356:j14. doi: 10.1136/bmj.j14
- Spanjer J, Groothoff JW, Brouwer S. Assessing work ability — a cross-sectional study of interrater agreement between disability claimants, treating physicians, and medical experts. Scandinavian Journal of Work, Environment & Health. 2014;40(5):493–501. doi: 10.5271/sjweh.3438
- Durand M-J, Loisel P, Poitras S, et al. The interrater reliability of a functional capacity evaluation: the Physical Work Performance Evaluation. Journal of Occupational Rehabilitation. 2004;14(2):119–129. doi: 10.1023/B:JOOR.0000018328.35521.e8
- Mecham J, Wargo J, Matheson LN. An evaluation of the inter-rater and intra-rater reliability of OccuPro’s functional capacity evaluation. Work. 2018;60(3):465–473. doi: 10.3233/WOR-182754
- Matheson LN. The functional capacity evaluation. In: Demeter SL, Andersson GBJ, editors. Disability evaluation. St. Louis: Mosby; 2003: 746–762.
- Escorpizo R, Reneman MF, Ekholm J, et al. A conceptual definition of vocational rehabilitation based on the ICF: building a shared global model. Journal of Occupational Rehabilitation. 2011;21(2):126–133. doi: 10.1007/s10926-011-9292-6
- Finger ME, Glässel A, Erhart P, et al. Identification of relevant ICF categories in vocational rehabilitation: a cross sectional study evaluating the clinical perspective. Journal of Occupational Rehabilitation. 2011;21(2):156–166. doi: 10.1007/s10926-011-9294-4
- Rigó M, Dragano N, Wahrendorf M, Siegrist J, Lunau T. Work stress on rise? Comparative analysis of trends in work stressors using the European working conditions survey. International Archives of Occupational and Environmental Health. 2021;94(3):459–474. doi: 10.1007/s00420-020-01593-8
- Giorgi G, Lecca LI, Ariza-Montes A, et al. The importance of contextualized psychosocial risk indicators in workplace stress assessment: evidence from the healthcare sector. International Journal of Environmental Research and Public Health. 2021;18(6):3263. doi: 10.3390/ijerph18063263
- Cendales-Ayala B, Useche SA, Gómez-Ortiz V, Bocarejo JP. Psychosocial work factors, job stress and strain at the wheel: validation of the Copenhagen Psychosocial Questionnaire (COPSOQ) in professional drivers. Frontiers in Psychology. 2019;10:1531. doi: 10.3389/fpsyg.2019.01531
- Lunau T, Siegrist J, Dragano N, Wahrendorf M. The association between education and work stress: does the policy context matter? PLoS ONE. 2015;10(3):e0121573. doi: 10.1371/journal.pone.0121573
- Negri L, Spoladore D, Fossati M, et al. Proposal for an ICF-based methodology to foster the return to work of persons with disability. Work. 2023;74(2):649–662. doi: 10.3233/WOR-211226
- Saltychev M, Kinnunen A, Laimi K. Vocational rehabilitation evaluation and the International Classification of Functioning, Disability, and Health (ICF). Journal of Occupational Rehabilitation. 2013;23(1):106–114. doi: 10.1007/s10926-012-9385-x
- Kottner J, Audigé L, Brorson S, et al. Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed. Journal of Clinical Epidemiology. 2011;64(1):96–106. doi: 10.1016/j.jclinepi.2010.03.002
- Hager P, Jungmann F, Holland R, et al. Evaluation and mitigation of the limitations of large language models in clinical decision-making. Nature Medicine. 2024;30:2613–2622. doi: 10.1038/s41591-024-03097-1
- Benkirane K, Kay J, Perez-Ortiz M. How can we diagnose and treat bias in large language models for clinical decision-making? In: Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 2024:12345–12360. doi: 10.48550/arXiv.2410.16574
- Chen IY, Hoffmann J, Dinan E. The evaluation illusion of large language models in medicine. NPJ Digital Medicine. 2025;8(1):512. doi: 10.1038/s41746-025-01963-x
Supplementary files

