# Digital Inclusion and Equitable Public Services for People with Disabilities in Thailand ## 📌 Project OverviewThis repository contains datasets, SEM model files, and documentation supporting the research article:“Overcoming Data Barriers: Digital Inclusion and Equitable Public Services for People with Disabilities in Thailand.” The study examines disparities between government officials (service providers) and people with disabilities (service recipients) in relation to public service delivery (S), audit data governance (A), and data-driven culture (C). Multi-Group Structural Equation Modeling (MG-SEM) is used to assess whether key structural relationships differ between groups. --- ## 📂 Project Structure ### 📁 Dataset/- Dataset.csv → De-identified dataset (CSV) ### 📁 AMOS_Models/- AMOS_Models.amw → AMOS file for MG-SEM analysis (AMOS v24.0) ### 📁 Documentation/- README.txt → This file (project structure and data usage) --- ## 📎 Extended dataThe repository also contains the following extended data used in the study: ### Survey questionnaire- Survey_TH.pdf — Original Thai version of the survey questionnaire used in the study- Survey_EN.pdf — English translation of the survey questionnaire (for reference) ### Figures- Figure 1.TIFF — Figure 1: Data Governance Factors for Auditing Public Services for People with Disabilities in Thailand Model- Figure 2.TIFF — Figure 2: Multi-Group Causal Models Influencing Audit Data Governance in Public Service Delivery ### Tables (main manuscript)- Table 1.xlsx — Table 1: Number and Percentage Classified by Characteristics of the Sample Group- Table 2.xlsx — Table 2: Standards and Thresholds for Multi-group MG-SEM- Table 3.xlsx — Table 3: Comparison of Path Coefficients and Model Fit for Structural Weights in MG-SEM- Table 4.xlsx — Table 4: Model Comparison- Table 5.xlsx — Table 5: Policy Recommendations and Practical Guidelines ### Supplementary tables- Table S1.xlsx — Table S1: Factors influencing audit data governance in public services for people with disabilities- Table S2.xlsx — Table S2: Regression weights for SEM model by public service provider and public service recipient --- ## 📊 How to Use the Data1) The dataset (.csv) can be opened in IBM SPSS Statistics, jamovi, JASP, R, Python, or other software that supports CSV. 2) AMOS model file (.amw) can be opened in IBM SPSS AMOS (Version 24.0) for MG-SEM analysis. 3) Tables and supplementary tables:- Tables 1–5 summarize the main manuscript results.- Supplementary Tables S1–S2 provide item-level and parameter-estimate details that support verification of the measurement and structural models. --- ## 🔐 Ethical Considerations and Data AccessTo ensure compliance with research ethics, all personally identifiable information has been removed from the shared dataset. Direct identifiers and sensitive attributes that could increase re-identification risk have been removed or generalized. For example:- demographic and contextual variables (e.g., age, gender, disability type, occupational category, experience level) are not shared in identifiable form; and- geographic information is provided only at an aggregated level where applicable. Openly available materials:This repository includes de-identified data (.csv), model files (.amw), extended data, and supplementary tables (S1–S2). Restricted data and controlled access:Due to privacy and ethical concerns, certain sensitive data that could lead to re-identification are not publicly available. Researchers who require access to restricted data must:1) Submit a formal request via email to the corresponding author;2) Provide details on research purpose and intended data usage; and3) Sign a Data Use Agreement (DUA). Requests will be reviewed on a case-by-case basis to ensure compliance with research integrity standards. --- ## 📞 Contact InformationFor inquiries about the project or data access, please contact:- ch.sitt@gmail.com- Mahidol University