Are Local Governments Ready for Cancer Prevention? Perceived institutional capacity of Polish Local Government Units
DOI:
https://doi.org/10.12775/JEHS.2026.95.76327Keywords
Neoplasms; Local Government; Primary Prevention; Health Promotion; Public Health; Health Policy; PolandAbstract
This study assessed the perceived institutional capacity of Polish local government units (LGUs) to perform tasks related to cancer prevention and examined variation according to LGU type, population size, and voivodeship. A quantitative cross-sectional study was conducted among 407 LGUs representing all 16 Polish voivodeships. Invitations containing a link to an electronic questionnaire were sent to the official email addresses of LGUs, and participating units forwarded the questionnaire to a staff member with sufficient knowledge of the institution’s activities. Data were collected using Computer-Assisted Web Interviewing (CAWI). Perceived institutional capacity was assessed using 20 indicators covering human, financial, organizational, relational, analytical, technological, and evaluation-related components. A composite capacity index was calculated as the arithmetic mean of the 20 items. Descriptive statistics, internal consistency analysis, exploratory factor analysis, between-group comparisons, Spearman’s correlation, and multivariable linear regression with HC3 robust standard errors were used. The mean perceived institutional capacity score was 2.82 (SD = 0.80) on a 1–5 scale. Cooperation with educational institutions and healthcare providers received the most favorable assessments, whereas human resources, technological capacity, financing, locally tailored prevention programmes, and monitoring and evaluation were assessed less favorably. Internal consistency was high (Cronbach’s α = 0.956; McDonald’s ω = 0.957), and exploratory factor analysis indicated two interrelated dimensions. LGU type was associated with capacity, whereas population size and voivodeship were not independently associated with capacity in the multivariable model. The regression model explained 9.3% of the variance.
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