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Updated: Sep 17, 2025

Human Circadian Phenotyping and Diurnal Performance Testing in the Real World
Published on: April 7, 2020
Validation of the Norwegian version of the Munich ChronoType Questionnaire for shift workers (MCTQShift)
Line Victoria Moen1, Tarjei L Rysstad2, Jenny-Anne S Lie1
1Work Physiology and Psychology, National Institute of Occupational Health (STAMI), Oslo, Norway.
Abstract:
Chronotype may play a role in the association between shift work and health risks. An important and widely used questionnaire for measuring chronotype is the Munich Chronotype Questionnaire for Shift workers (MCTQShift); however, it has neither been validated nor is it available in Norwegian or any other Scandinavian language. Therefore, we translated the MCTQShift into Norwegian and assessed its validity against subjective and objective sleep measures. We adhered to established methodological guidelines to translate the questionnaire. The final Norwegian version was administered to 60 workers (85% responders) on a three-shift schedule (21.7% women, median age 28 y) at an industrial plant. Sleep duration and mid-sleep from the MCTQShift were compared with sleep diary and a multisensory sleep tracker (the Oura ring). Construct and criterion validity were evaluated. Sleep duration measured by the MCTQShift was highly correlated (r > 0.6) with sleep duration calculated from both the Oura ring and sleep diaries after morning shifts. On free days, the MCTQShift correlated moderately with the sleep diary but weakly with the Oura ring. Mid-sleep correlations from MCTQShift compared to the Oura ring data were high (r > 0.7) for sleep periods after morning and night shifts, and moderate (r = 0.5) sleep periods between free days following morning shift. Bland-Altman analyses indicated that the MCTQShift overestimated sleep duration and underestimated mid-sleep, with the largest discrepancies on free days after morning shifts. Night shifts showed the most pronounced outliers. The Norwegian MCTQShift shows promising validity for assessing sleep habits in shift workers, particularly on workdays. However, reduced accuracy on free days after morning shifts suggests limitations in capturing sleep patterns across all shift types.
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