Longitudinal Physical Literacy and Burnout in Chinese University Faculty, Three Waves

A three-wave longitudinal dataset tracks 1,014 Chinese university faculty members over two years. It contains item-level responses and precomputed scores for the Perceived Physical Literacy Instrument and Shirom–Melamed Burnout Measure across baseline, one-year, and two-year follow-ups. The dataset was authored by Ma, Rui Si and is hosted on Harvard Dataverse.

Use Cases

• Identify latent profiles of physical literacy based on the 18-item PPLI scores.
• Model the longitudinal association between physical literacy and burnout using the 14-item SMBM scores.
• Analyze retention and attrition patterns across the three waves of data collection.
• Examine how demographic and professional covariates correlate with burnout trajectories.

Strengths

• Longitudinal design with three waves of data collection over two years.
• Includes 1,014 participants at baseline with retention rates of 86.0% (n=872) and 78.2% (n=793) at follow-ups.
• Provides item-level responses, precomputed subscale scores, and total scores for two validated instruments.
• Contains baseline demographic and professional covariates such as academic rank and years of service.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic and occupational bias inherent to the sample of Chinese university faculty.

Provenance

Source

Harvard Dataverse

Collection Method

Survey responses from university faculty using validated instruments.

Time Range

Longitudinal study covering baseline and two follow-up waves over two years.

Freshness

Last updated 2026-05-12 17:12:23; freshness should be verified.

Geography

China