| Testing the Reliability and Validity of the Korean Version of the Pittsburgh Sleep Quality Index Using Fitbit Devices: A Cross-Sectional Analysis |
Si-Yeon Lee1 
, Ja-Eun Choi2
, Ji-Won Lee1
, Yaeji Lee3,4
, Jae-Min Park5,6
, Kyung-Won Hong2
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1Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
2R&D Division, Theragen Health Co. Ltd., Seongnam, Korea
3Department of Biostatistics and Computing, Yonsei University, Seoul, Korea
4Department of Family Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
5Department of Family Medicine, Uijeongbu Eulji Medical Center, Eulji University, Uijeongbu, Korea
6Department of Medicine, Graduate School of Medicine, Yonsei University, Seoul, Korea |
Corresponding author:
Jae-Min Park, Tel: +82-31-951-2339, Fax: +82-31-951-3300,
Email: milkcandy@eulji.ac.kr
Kyung-Won Hong, Tel: +82-31-288-1288, Fax: +82-31-288-1294,
Email: kyungwon.hong@theragenhealth.com
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Received: 30 August 2023 • Revised: 10 December 2023 • Accepted: 12 December 2023 |
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| Abstract |
Background
Sleep disorders and insomnia are prevalent worldwide, with negative health outcomes. The Pittsburgh Sleep Quality Index (PSQI) is a widely used self-report assessment tool for evaluating sleep quality, comprising seven subdomains. The Korean version of the PSQI (PSQI-K) has been tested for reliability and validity in small sample sizes but lacks large-scale validation using objective measures.
Methods
This study was conducted with 268 Korean adults attending health check programs. Participants completed the PSQI-K questionnaire and wore Fitbit devices (Fitbit Inc., USA) to ascertain sleep parameters. Reliability was analyzed using the Cronbach’s α coefficient, and construct validity was determined through factor analysis. Criteria validity was assessed by correlating their index scores with Fitbit sleep parameters. We identified the optimal cutoff for detecting sleep disorders.
Results
The Cronbach’s α coefficient was 0.61, indicating adequate internal consistency. Factor analysis revealed three factors, explaining 48.2% of sleep quality variance. The index scores were negatively correlated with Fitbit sleep efficiency, total sleep time, and number of awakenings (P<0.05). The optimal cutoff point for identifying sleep disorder groups was ≥6.
Conclusion
The PSQI-K demonstrated good reliability and validity when correlated with Fitbit sleep parameters, offering a practical screening tool for identifying sleep disorders among Korean adults. Cutoff scores can help identify patients for sleep interventions. However, further large-scale studies are required to validate these findings. |
| Key Words:
Sleep; Sleep Quality; Reliability; Validity; Insomnia |
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