Аңдатпа
Aim. To develop, validate, and pilot-test a questionnaire for identifying risk factors for the development of chronic obstructive pulmonary disease (COPD) and associated conditions among healthy coal miners. Materials and methods . The questionnaire consists of 5 sections (71 questions in total): sociodemographic and living conditions (16 questions), harmful habits (5 questions), health status and its changes during occupational activity (19 questions), nature of work and harmful occupational factors (19 questions), and assessment of the severity and intensity of the labor process (12 questions). Additionally, the following standardized instruments were attached: WHOQOL-BREF (quality of life), PHQ-9 (depression), Eysenck Personality Questionnaire (type of nervous system), Vaytenko aging index, and Münsterberg test (cognitive functions). Linguistic adaptation, expert review, and pilot testing were conducted on 102 healthy male coal miners (mean age 37.2±6.0 years). Construct validity was assessed using principal component analysis, and reliability was evaluated by Cronbach’s alpha coefficient. Statistical analysis was performed using IBM SPSS Statistics 13 and STATISTICA 10 software. Results and discussion. The average time to complete the questionnaire was 7–8 minutes. The questions were understandable to the majority of respondents; only 5% required clarification of certain items. Factor loadings across the sections ranged from 0.639 to 0.871. Cronbach’s alpha values by section were as follows: 0.520 (socio-demographic and living conditions), 0.855 (harmful habits), 0.785 (health status), 0.757 (working conditions and occupational hazards), and 0.657 (severity and intensity of labor). These results indicate satisfactory construct validity and acceptable to good internal consistency for most sections. Conclusions. The developed questionnaire demonstrates sufficient reliability and validity for use in scientific and epidemiological studies as well as in practical preventive work among coal miners. The obtained data enable the identification of groups at increased risk of developing COPD and the planning of targeted preventive measures.