A Structured Workflow for Screening, Scoring, and Visualizing Undergraduate Student Well-Being Questionnaire Data

Questionnaire-based studies are widely used to examine student well-being, but the procedural route from raw responses to analyzable variables, statistical tables, and visual outputs is often insufficiently documented. This protocol demonstrates a structured and auditable workflow for processing anonymized undergraduate well-being questionnaire data collected with multiple Likert-type scale sections. The workflow begins with ethics approval, consent documentation, questionnaire configuration, and raw-data export, and then proceeds through response screening, duplicate-response review, missing-data handling, item coding, reverse scoring, reliability assessment, descriptive analysis, correlation analysis, contrastive group comparison, regression modeling, diagnostic checking, and visualization-source preparation. The example questionnaire uses source-documented and study-adapted scale sections informed by the Depression Anxiety Stress Scales-21, Tuckman Procrastination Scale, Psychological Sense of School Membership Scale, higher-order thinking measurement literature, and subjective well-being scale documentation. Negative emotion, academic procrastination, school belongingness, higher-order thinking, and subjective well-being are used as example scale-level variables to show how item-level responses can be converted into traceable analytic outputs. Representative outputs include a screening-flow table, demographic summary, descriptive and range-verification statistics, internal-consistency estimates, a correlation matrix, contrastive comparison results, regression coefficients, residual and influence diagnostics, and figure-source files. The protocol emphasizes prespecified decision rules, a linked scale map, a pre-analysis screening log, reverse-scoring verification, and numerical-source verification for figures. Rather than proposing a new psychometric scale, validating a measurement model, or establishing causal relationships, this method provides a practical and auditable procedure for researchers who need to screen, score, analyze, and visualize questionnaire-based undergraduate well-being data. The workflow may be adapted to related questionnaire-based studies when the scale map, ethics approval, scoring rules, response-screening thresholds, and visualization-source files are defined before analysis.