Nausea and vomiting of pregnancy (NVP) is a common health issue among pregnant women. NVP involves any degree or duration of nausea with or without vomiting or retching and which is not associated with other known causal factors. Almost 70% of women worldwide experience NVP, with higher rates reported in East Asian countries [1]. Medical treatment is needed in severe cases. Nutritional disturbances, weight loss, dehydration, and ketonuria may lead to hospitalisation [2]. Hyperemesis gravidarum (HG) is considered the most severe form of NVP. Einarson et al. [1] reported that the prevalence of HG was 1.1%. In addition to the emergence of somatic symptoms, a woman’s quality of life (QOL) and ability to function are also impaired among those who suffered from severe NVP [3, 4]. A significant correlation between NVP and pregnancy complications was also reported. Women with NVP also have significant correlation with high blood pressure having had no prior history and preeclampsia [5]. Women with HG have a risk of having a low birth weight infant, an infant small for gestational age, or a preterm delivery [6, 7]. Women with HG also exhibited depression, post-traumatic stress disorder, and anxiety disorders [8, 9]. For clinical and research use, a reliable and valid, as well as simple, measure for quantification of NVP severity is required.
The Pregnancy-Unique Quantification of Emesis and Nausea (PUQE) [10] is a severity measure used in studies to determine the burden or treatment outcome of NVP. The PUQE is a scoring system for nausea and vomiting during pregnancy, which consists of three items. The PUQE was developed for pregnant women on the basis of the Rhodes Index of Nausea and Vomiting (INV) [11] and focuses on three symptoms: nausea, vomiting, and retching. The original PUQE entailed rating the daily number of vomiting episodes, the length of nausea in hours per day, and the number of retching episodes per 12 hours. Its validation was confirmed by Koren et al [12]. To capture more comprehensive NVP severity, the PUQE was modified by Lacasse et al [13]. The Modified-PUQE (PUQE-24) is a scoring system per 24 hours with the same scoring calculation and interpretation as for the original PUQE. The PUQE is widely used as a scoring system to assess NVP severity in many countries [14, 15, 16, 17]. Its use as the validated tool should be applied more frequently in better defining the severe end of HG [18].
The present study shows the psychometric properties of the PUQE-24 among pregnant women including confirmatory factor analysis (CFA) and configural, measurement, and structural invariance of the factor structure. We focused on the invariance of the factor structure between nulliparas and multiparas and between the test and retest occasions. When a psychological instrument is used in different populations or used at more than one measurement occasion, both selection of the best fit model of factor structure and confirmation of the postulation that the psychological instrument in question measures the same phenomena is needed. If this confirmation is not achieved, the instrument does not reflect the same phenomenon and the results may be biased. Invariance tests take several steps [19]. First, each group (e.g., nulliparas vs. multiparas) has the same pattern of the indicators and factors (configural invariance). Second, factor loadings for like indicators are invariant across groups (metric invariance; also known as weak factorial invariance). Third, intercepts of like items are invariant across groups (scalar invariance; also known as strong factorial invariance). Fourth, residuals (errors) of like items are invariant across groups (residual invariance; also known as strict factorial invariance). Fifth, variances of like factors are invariant across groups (factor variance invariance). Sixth, means of factors are invariant across groups (factor mean invariance). The second to fourth steps are called measurement invariance. The fifth and sixth steps are called structural invariance [19]. If one step is rejected, the next steps cannot be performed. We conducted tests for our hypotheses using this algorithm.
On the procedure of the data analysis and explanation, we followed the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) Study Design checklist [20]. It is recommended for designing studies and evaluating measurement properties, including content validity, structural validity, internal consistency, cross-cultural validity/measurement invariance, reliability, measurement error, criterion validity, hypotheses testing for construct validity, and responsiveness [21, 22]. The PUQE-24 has been evaluated its content validity [10, 12, 13, 23], hypothesis testing for construct validity [13, 24, 25] and criterion validity [12]. To the best our knowledge, its validity including the measurement invariance has not been examined.