Data and R code for “Within-person feedback among perfectionistic concerns, academic stress, and burnout across the first university year: A four-wave RI-CLPM study”

Description

This repository contains the de-identified longitudinal data, analysis code, documentation, and reproducibility materials supporting the manuscript **“Within-person feedback among perfectionistic concerns, academic stress, and burnout across the first university year: A four-wave RI-CLPM study.”** The study followed 720 first-year undergraduate students across four waves over one academic year, with assessments conducted at approximately 12–13-week intervals. The primary analyses examined reciprocal within-person associations among perfectionistic concerns, academic stress, and academic burnout using random-intercept cross-lagged panel models (RI-CLPMs). Additional analyses evaluated longitudinal measurement invariance, discriminant validity, imposed and enacted academic demand, indirect effects, alternative burnout specifications, conventional CLPMs, demographic and GPA-adjusted robustness models, lag-specific sensitivity, attrition, equivalence testing, and phantom-confounder sensitivity. The repository includes de-identified participant-level data in long and wide formats, pilot-study data, recruitment and attrition information, programme-by-wave academic-demand indicators, codebooks and variable documentation, the complete R/lavaan analysis workflow, derived tables and figures, reproducibility logs, and supplementary documentation. Monte Carlo confidence intervals for the final indirect-effect analyses were generated using 200,000 draws with seed 27092026. Institution, programme, class, and participant identifiers are coded to protect confidentiality. No direct personal identifiers are included in the repository. The data and code are provided to support transparency, reproducibility, secondary verification, and methodological reuse of the analyses reported in the associated manuscript. Researchers reusing these materials should consult the README, codebook, item map, file manifest, and analysis workflow before conducting secondary analyses.

Institutions

• Anhui Polytechnic University

  Anhui, Wuhu

Categories

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