Spanish College Student Identity and Adjustment Across Two Cohorts (2015 and 2020)
by Paula Domínguez-Alarcón·Updated 9d ago
23.0 KB1files
Available on 1 platform
Sign in to view source links and access this dataset
Description
2,819 college students (38% men, 62% women) surveyed across two cohorts in 2015 (n=1,301) and 2020 (n=1,518). The dataset, authored by Paula Domínguez-Alarcón and shared via figshare, compares identity development and psychological adjustment between these generational groups. It highlights differences in commitment, exploration, wellbeing, and distress, particularly during the COVID-19 pandemic period.
Use Cases
Compare identity commitment levels between generational cohorts based on the described commitment making and identification with commitment dimensions.
Analyze the relationship between ruminative exploration and psychological distress as reported for the 2020 cohort.
Investigate gender differences in the association between identity dimensions and psychological adjustment highlighted in the findings.
Study the impact of socio-historical context (e.g., the COVID-19 pandemic) on wellbeing and distress levels in emerging adults.
Strengths
Total sample size of 2,819 participants provides a substantial basis for analysis.
Direct comparison between two distinct time points (2015 and 2020) allows for generational analysis.
Includes detailed demographic breakdowns by cohort (e.g., 40.9% men in Ch1, 35.6% men in Ch2) and average ages with standard deviations.
Limitations
Column-level documentation is absent; field semantics must be inferred after download.
Row count is unknown, which may limit suitability assessment.
Data is contained in a 23.0 KB DOCX file, suggesting limited raw data scope and potential formatting for analysis.
Provenance
Source
Paula Domínguez-Alarcón via figshare
Collection Method
Survey of college students.
Time Range
2015 and 2020
Freshness
Last updated 2026-05-28 06:18:54; freshness should be verified.
Geography
Spain (implied by 'Spanish college emerging adults')
Data is in a DOCX file format, which may require extraction or conversion for computational analysis.