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<p>This study assessed the validity of the ChatGPT in measuring perceived stress and psychological distress in college students by comparing the consistency of the ChatGPT’s scale-based adaptation of the scenario-based interview question scores with the scores of a validated questionnaire. ChatGPT-4 was used to adapt the Perceived Stress Scale (PSS-4) and the 10-item Kessler Psychological Distress Scale (K10) into scenario-based interview questions with automated scoring. A total of 199 college students completed both the ChatGPT-4-generated scenario questions and the corresponding validated questionnaires. Internal consistency, Spearman correlations, intraclass correlation coefficients (ICCs), Bland–Altman analyses, item-level correlations, and K10 threshold-based agreement were evaluated. All participants completed both assessments, with no missing item or total-score data. ChatGPT-4-generated total scores showed moderate correlations with questionnaire scores for both K10 and PSS-4 (Spearman’s ρ = 0.57 for both). The ICC indicated excellent agreement for K10 (ICC = 0.91, 95% CI: 0.89–0.93) and moderate agreement for PSS-4 (ICC = 0.70, 95% CI: 0.63–0.76). Bland–Altman analyses showed small positive mean differences, and item-level correlations were heterogeneous. K10 threshold-based analyses suggested more conservative classification at higher cutoffs. This study provides preliminary feasibility evidence for further validating ChatGPT-4-assisted contextualized scoring as an adjunctive assessment approach. Threshold-based screening performance, reproducibility, criterion validity, and generalizability require further investigation.</p>

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Analysis of the Validity of ChatGPT in the Assessment of Perceived Stress and Psychological Distress Among University Students: A Cross-Sectional Study

  • 期刊论文

  • 发表日期：

    2026年7月9日

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  • MengJie Tong,
  • JiaLi Liu,
  • LiJuan Zeng,
  • Juan Gu,
  • YaKe Yue,
  • YiQing Yu,
  • YuFei Qiu,
  • Fen Yang

摘要

This study assessed the validity of the ChatGPT in measuring perceived stress and psychological distress in college students by comparing the consistency of the ChatGPT’s scale-based adaptation of the scenario-based interview question scores with the scores of a validated questionnaire. ChatGPT-4 was used to adapt the Perceived Stress Scale (PSS-4) and the 10-item Kessler Psychological Distress Scale (K10) into scenario-based interview questions with automated scoring. A total of 199 college students completed both the ChatGPT-4-generated scenario questions and the corresponding validated questionnaires. Internal consistency, Spearman correlations, intraclass correlation coefficients (ICCs), Bland–Altman analyses, item-level correlations, and K10 threshold-based agreement were evaluated. All participants completed both assessments, with no missing item or total-score data. ChatGPT-4-generated total scores showed moderate correlations with questionnaire scores for both K10 and PSS-4 (Spearman’s ρ = 0.57 for both). The ICC indicated excellent agreement for K10 (ICC = 0.91, 95% CI: 0.89–0.93) and moderate agreement for PSS-4 (ICC = 0.70, 95% CI: 0.63–0.76). Bland–Altman analyses showed small positive mean differences, and item-level correlations were heterogeneous. K10 threshold-based analyses suggested more conservative classification at higher cutoffs. This study provides preliminary feasibility evidence for further validating ChatGPT-4-assisted contextualized scoring as an adjunctive assessment approach. Threshold-based screening performance, reproducibility, criterion validity, and generalizability require further investigation.