Survey of 119,051 Primary Healthcare Workers in Henan, China on Competencies and Training
by Clifford Silver Tarimo·Updated 3mo ago
165.1 KB1files
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Description
A cross-sectional survey of 119,051 primary healthcare workers across Henan province, China, conducted in August 2023. The data, authored by Clifford Silver Tarimo, examines self-perceived knowledge gaps in basic theory, professional knowledge, and practical skills, as well as preferences for training modalities like case-sharing and skills simulation.
Use Cases
Identify priority areas for competency-based training based on reported knowledge gaps in practical skills and professional knowledge.
Cluster healthcare worker profiles for targeted interventions using the six distinct knowledge gap and preference profiles identified.
Analyze disparities in reported deficiencies between rural and urban clinics or across different staff seniority levels.
Design training programs that align with preferred experiential learning methods like case sharing and skills simulation.
Strengths
Large-scale survey covering 119,051 respondents across an entire province.
Specific quantitative findings reported, such as 40.0% reporting significant knowledge deficiencies and 76.4% preferring case-sharing training.
Analysis includes statistical methods like Generalized Linear Models and K-Means clustering.
Limitations
Row count and column-level documentation are absent; field semantics must be inferred after download.
Data is provided as a PDF (165.1 KB), which may require extraction and structuring for analysis.
The data reflects a specific geographic and temporal context (Henan province, August 2023).
Provenance
Source
Clifford Silver Tarimo via figshare.
Collection Method
Cross-sectional survey of workers from village health clinics, township health centers, community health service centers, and health management institutions.
Time Range
August 2023.
Freshness
Last updated 2026-03-18 07:45:20; freshness should be verified.
Geography
Henan province, China.
Data is in PDF format; conversion to a structured format may be required for computational analysis.