Table 1_Predictor and subgroup analysis of somatic symptoms and emotional exhaustion among

Katharina Wörle's dataset contains survey results from a longitudinal study of university students in Germany during the SARS-CoV-2 pandemic. It includes responses from 3,066 students in 2020 and 1,438 in 2021, with a longitudinal sample of 264 participants tracked across both years. The data was collected to assess the prevalence and development of emotional exhaustion and somatic symptoms, examining subgroup differences and predictors of change.

Use Cases

• Predicting changes in emotional exhaustion based on perceived work complexity, as indicated by the longitudinal analysis.
• Analyzing subgroup differences in somatic symptoms based on study field, comparing medical and non-medical students.
• Investigating demographic predictors of mental health outcomes, focusing on gender and academic year.
• Modeling the longitudinal trajectory of somatic symptom scores over a one-year period.

Strengths

• Includes a longitudinal sample of 264 students tracked over one year.
• Provides cross-sectional data from a large sample of 3,066 students in 2020.
• Examines multiple predictor variables including demographics, study field, and perceived work complexity.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the full dataset is unknown, which may limit suitability assessment.
• Data is from a single large university in Germany, which may limit generalizability.

Provenance

Source

Katharina Wörle via figshare.

Collection Method

Data were collected from students from a large university in Germany, using two surveys conducted 1 year apart.

Time Range

Surveys conducted in 2020 and 2021.

Freshness

Last updated 2026-05-13 04:37:35; freshness should be verified.

Geography

A large university in Germany.