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Psychiatry Investig > Volume 23(6); 2026 > Article
Lee, Shahrier, Yoo, and Chung: Validation of the Korean Version of the Meta-Worry Questionnaire Among the General Population

Abstract

Objective

Meta-worry, defined as worry about worrying, plays a central role in the onset and maintenance of generalized anxiety disorder (GAD) within the metacognitive model of anxiety. The Meta-Worry Questionnaire (MWQ) is a self-report scale developed to assess negative metacognitive beliefs about worry. This study aimed to examine the reliability and validity of the Korean version of the MWQ in a general adult population.

Methods

An online survey was conducted with 600 participants, stratified by sex and age. The MWQ was translated using forward and back-translation. The first 300 responses (Group I) were used for exploratory factor analysis (EFA), and the remaining 300 (Group II) were used for confirmatory factor analysis (CFA), item response theory (IRT), and convergent validity. Other measures included the Generalized Anxiety Disorder-7, Metacognition Questionnaire for Insomnia-14, Insomnia Severity Index, and the discrepancy between desired time in bed and desired total sleep time index.

Results

EFA showed a one-factor structure explaining 71.5% of the variance. CFA confirmed good model fit, and measurement invariance was observed across the sexes. The internal consistency was high (α=0.946, ω=0.946), and IRT results indicated strong item discrimination. The MWQ scores were strongly related to anxiety, metacognitive beliefs about insomnia, and insomnia severity.

Conclusion

The Korean version of the MWQ is reliable and valid for assessing meta-worry. These findings support its applicability in evaluating metacognitive aspects of anxiety symptoms in Korean populations.

INTRODUCTION

Metacognition is the ability of an individual to monitor and control their own cognitive processes, which is “thinking about thinking [1].” Metacognition is divided into three functional components: metacognitive knowledge, an individual’s awareness and understanding of their own cognitive processes and abilities; metacognitive strategies, deliberate actions and techniques that individuals use to monitor, control, and regulate their cognition; and metacognitive experiences, feelings, and judgments that occur during cognitive activities [2]. While most metacognitive processes occur automatically and involuntarily, the capacity to consciously reflect on one’s thoughts provides the advantage of self-regulating cognitive functions [3]. After the introduction of the concept, metacognition became a significant topic of interest in various fields due to its crucial role in psychological processes such as insight, learning, self-regulation, and problem-solving abilities [3,4].
In the context of mental health, metacognition plays two critical roles. First, dysfunctional beliefs about one’s thoughts—such as worry, rumination, and self-blame—can serve as pathological factors that maintain cognitive distortions. These maladaptive metacognitive patterns contribute to the persistence and exacerbation of symptoms by reinforcing negative thought processes. Metacognition is deeply involved in the symptoms of numerous psychiatric disorders, including depression, bi-polar disorder, and obsessive-compulsive disorder [5-7]. Second, developing metacognitive skills offers a therapeutic intervention. By learning to regulate their cognitive processes and strategically intervene in their own thinking patterns, patients can break the vicious cycle of symptoms and negative cognition [8]. This leads to the adoption of more functional coping strategies and improves overall mental health outcomes [9].
Metacognition has been particularly emphasized in relation to pathological worry in anxiety disorders. The metacognitive model of anxiety proposed by Wells [10] has highlighted the significant impact of metacognitive beliefs on the development and maintenance of generalized anxiety disorder (GAD). According to Wells’s [10] metacognitive model, metacognitions about worry are key factors that influence both the initiation and perpetuation of GAD. This model posits that individuals hold two types of beliefs about worry: positive metacognitive beliefs (Type 1) and negative metacognitive beliefs (Type 2) [11]. These beliefs shape how individuals respond to their own thoughts and worries, thereby affecting their emotional and behavioral reactions. Type 1 worry involves positive beliefs about the utility and effectiveness of worry. Individuals with these beliefs view worry as a helpful coping strategy for dealing with potential threats or problematic situations. For example, they might think, “Worrying will help me prepare for the worst,” or “By worrying, I can prevent bad things from happening.” This type of worry is typically situation-specific and ceases once the perceived threat is resolved. It is considered a normal cognitive process that can be adaptive in managing stress and is common in both clinical and non-clinical populations [11].
However, problems arise when worry leads to negative consequences, and individuals begin to perceive worry itself as harmful or uncontrollable [11]. This shift gives rise to negative metacognitive beliefs about worry, constituting Type 2 worry, also known as meta-worry [12]. In this state, individuals start to worry about worry. Predominant thoughts might include, “I cannot control my worry,” “Worrying is dangerous and could harm me,” or “My inability to stop worrying means I’m losing control.” These negative beliefs about worry intensify anxiety and contribute to a vicious cycle where attempts to control or suppress worry fail, further reinforcing the negative metacognition. As individuals engage in ineffective behavioral strategies or thought-control techniques to alleviate their worries, such as avoidance, distraction, or suppression, they may experience temporary relief but ultimately exacerbate their anxiety symptoms. The failure of these strategies reinforces the belief that worry is uncontrollable and dangerous, heightening anxiety and perpetuating the cycle of meta-worry [11]. This process is central to the onset and maintenance of GAD symptoms, as individuals become trapped in a self-perpetuating cycle of worrying about the fact that they are worrying [13]. Empirical evidence supports the significance of negative metacognitive beliefs in GAD. Research indicates that patients with GAD experience higher levels of meta-worry compared to those without anxiety disorders [14]. Moreover, meta-worry is significantly more prevalent in GAD than in other anxiety disorders, such as panic disorder, social phobia, or somatic anxiety [15]. Additionally, meta-worry has been shown to distinguish between individuals with high and low levels of GAD symptoms [16] and plays a significant role in predicting worry severity [17]. These findings suggest that meta-worry is a key feature in GAD and is closely associated with the severity of anxiety symptoms.
While meta-worry can exacerbate psychiatric symptoms, recent research has increasingly focused on the therapeutic potential of metacognition to mitigate these effects. Cultivating an awareness and acceptance of one’s own thoughts and emotions can help interrupt the negative spirals that reinforce maladaptive cognitive patterns [18]. In this context, metacognitive therapy (MCT), developed by Wells [19], has emerged as a key intervention that targets how individuals relate to their internal experiences rather than attempting to eliminate or suppress them. MCT focuses on modifying dysfunctional metacognitions— particularly those related to worry and rumination— rather than directly challenging the specific content of these thoughts. MCT aims to break the cycle of meta-worry by altering negative metacognitive beliefs, thereby reducing anxiety symptoms and improving overall functioning. For example, MCT primarily aims to alter how individuals perceive and manage their own thoughts (e.g., questioning the purpose of worrying about accidents), and even when MCT does involve evaluating the accuracy of certain thoughts, it concentrates on beliefs about cognition (e.g., “I cannot control my worries”) rather than conventional cognitive content (e.g., “the world is dangerous”) [18]. Empirical studies have demonstrated that MCT significantly reduces worry and anxiety symptoms among individuals with conditions such as anxiety and depression, underscoring the importance of addressing metacognitive factors in treatment [8]. Consequently, a validated measure of metaworry is essential to better understand how meta-worry contributes to symptom exacerbation and to assess the effectiveness of interventions that target it.
The Meta-Worry Questionnaire (MWQ) is a self-report rating scale designed to assess negative metacognitions about worry within the framework of Wells’s [11] metacognitive model. Similar tools, such as the Meta-Cognition Questionnaire, assess metacognitive beliefs and processes [20], while the Anxious Thoughts Inventory evaluates social, health, and metaworry [21]. However, these tools do not measure beliefs about the dangerousness of worry, which is a primary component of Type 2 worry. The MWQ measures the beliefs regarding the uncontrollability and danger of worry, and provides a more precise evaluation of meta-worry by quantifying these negative beliefs. Previous studies have validated the reliability and construct validity of MWQ, and high MWQ scores were associated with a diagnosis of GAD [11,22]. Moreover, the MWQ has been used to identify pathological worry status in various contexts, such as posttraumatic stress disorder, childhood development, and during the COVID-19 pandemic [23-25]. Furthermore, the MWQ can be used to evaluate the effectiveness of treatment targeting metacognition and meta-worry [12]. Thus, the MWQ increases our understanding of the metacognitive processes underlying GAD and contributes to the development of more effective, individualized treatment strategies. A Korean version of the MWQ has not been developed, thereby limiting the application of the meta-worry construct within clinical settings, including the assessment of GAD and evaluations of treatment efficacy. In this study, we aimed to explore the reliability and validity of a Korean version of the MWQ among the general population in Korea.

METHODS

Participants and procedure

The study was conducted as an anonymous online survey. The survey was done via a survey platform of the survey company, EMBRAIN, from October 25 to November 2, 2024. We estimated the sample size as 600 based on the central limit theorem by allocating 60 samples for 10 cells (biological sex ×five age groups) [26]. The company sent 5,640 emails to 1.7 million general population panels; 1,102 accessed the survey form, and 645 responded. The company delivered the first 600 responses after excluding incomplete responses and responses that were too fast or too slow. We divided the responses into two groups: the responses of the first 300 participants (Group I), collected from October 25 to October 29, for exploratory factor analysis (EFA), and the responses of the other 300 participants (Group II), collected from October 31 to November 2, for confirmatory factor analysis (CFA). The protocol of the study was approved by the institutional review board (IRB) of the Asan Medical Center (2024-1229), and the need for written informed consent was waived by the IRB. Participants’ sex, age, marital status, past psychiatric history, current insomnia symptoms, and responses to the rating scales were collected via the survey form.

Measures

MWQ

The MWQ evaluates the frequency of meta-worry through seven items assessing the perceived risk associated with worry [11]. Each item is rated on a frequency scale ranging from 1 (“never”) to 4 (“almost always”). Cronbach’s alpha of 0.95 was reported in the original paper.
The Korean version of the MWQ was developed through translation and back-translation. Two separate native Koreanspeaking experts translated the original version of the MWQ into Korean, and two separate native Korean-speaking experts back-translated the translated Korean version into English. Finally, other experts compared the original version and backtranslated version and completed the final Korean version.

Generalized Anxiety Disorder-7

The Generalized Anxiety Disorder-7 (GAD-7) is a self-administered questionnaire used to evaluate the severity of GAD symptoms, including anxiety, excessive worry, and restlessness [27]. It consists of seven items, each rated from 0 to 3. In this study, we used the Korean version of the scale [28]. Cronbach’s alpha for our sample was 0.934.

Metacognition Questionnaire for Insomnia-14

The Metacognition Questionnaire for Insomnia-14 (MCQI-14) is a brief measure derived from the original 60-item Metacognitions Questionnaire-Insomnia (MCQI), which was developed to assess metacognitive beliefs in primary insomnia [29,30]. This self-report scale focuses on key dimensions of metacognitive beliefs related to insomnia-induced intrusive thoughts and worry. Each item is rated on a four-point Likert scale (0-4), with higher scores indicating stronger maladaptive metacognitive beliefs linked to sleep disturbance. Cronbach’s alpha for our sample was 0.911.

Insomnia Severity Index

The Insomnia Severity Index (ISI) is a widely used self-report measure designed to assess the severity of insomnia symptoms [31,32]. It consists of seven items that evaluate sleep difficulties, and each item is rated on a four-point Likert scale, with higher scores indicating greater insomnia severity. Cronbach’s alpha for our sample was 0.861.

Discrepancy between desired time in bed and desired total sleep time

The discrepancy between desired time in bed and desired total sleep time (DBST) index measures the discrepancy between an individual’s desired time in bed and desired total sleep time [33]. We asked participants, “How many hours do you want to sleep per day?” to assess desired total sleep time and asked “From what time to what time do you want to sleep?” to assess desired time in bed. The DBST was calculated as (desired time in bed)-(desired total sleep time). In previous studies, the DBST index was reported to be correlated with insomnia severity [34-37].

Statistical analysis

Continuous variables were expressed as mean±standard deviation (SD). Categorical variables were expressed as numbers and percentages. The normality assumption of the data was checked based on the skewness and kurtosis values within an acceptable range of ±2 [38]. EFA was conducted on the Group I data (n=300). Prior to this, the Kaiser-Meyer-Olkin (KMO) value (>0.60) and Bartlett’s test of sphericity value (p<0.001) were measured to check the data suitability and sampling adequacy [39]. Item-total correlation (accepted value ≥0.30), Cronbach’s alpha, and McDonald’s omega coefficients (accepted values ≥0.70) were used to measure the internal consistency reliabilities of the MWQ [40,41]. Using the Group II data (n=300), CFA, item response theory (IRT) analysis, and convergent validity of the MWQ were determined. In CFA, satisfactory model fit was assessed by standardized root-mean-square residual (SRMR) value and the root mean square error of approximation (RMSEA) value of ≤0.08, and comparative fit index (CFI) and Tucker-Lewis index (TLI) values of ≥0.95 [42,43]. CFA factor loadings were used to calculate the average variance extraction (AVE) and the composite reliability of the MWQ. A multi-group CFA with configural, metric, and scalar invariances was run to assess whether the Korean version of the MWQ can invariably be applied across males and females. A ΔCFI value of ≤0.010 and ΔRMSEA value of ≤0.015 were used as the indicators of measurement invariance recommended by [44].
Under the IRT, we assessed the item-level characteristics using the graded response model (GRM). Before applying the GRM, model fits (i.e., unidimensionality, monotonicity, and local independence of MWQ) were assessed through the IRT assumptions. Loevinger’s H coefficient greater than 0.5 indicates strong unidimensionality, whereas Yen’s Q3 residual coefficient ≤0.2 suggests the local independence of scale items [45,46]. The crit value <40 reflects the monotonicity of items [47]. In the GRM model, we assessed the discrimination and difficulty parameters through slope (α) and threshold (b) coefficients, respectively. For discrimination parameters, cut-off values ranging between 1.35 and 1.69 indicate high, and values greater than 1.70 indicate very high discrimination [48]. Item difficulty parameters indicate the response category of participants with 50% probabilities across varying ability ranges of the latent trait. Moreover, we assessed the item information curves (IICs) and the test information function (TIF) of the MWQ. CFA was run using the lavaan R package (R Foundation for Statistical Computing), and the GRM model was applied using the R package ltm version 1.2.0. The model fits of IRT assumptions were assessed using the R package mokken version 3.1.2 for unidimensionality and monotonicity, and the R package mirt version 1.44.0 for local independence. To explore the convergent validity, we performed a Pearson correlation analysis of the MWQ scale score with the scores of GAD-7, MCQI-14, ISI, and the DBST index. The overall study procedure, including sample allocation and the specific psychometric analyses per-formed for each group, is illustrated in Figure 1.

RESULTS

Demographic information of the study participants is shown in Table 1. The total sample was randomly split into two independent subsamples: Group I (n=300) for EFA and Group II (n=300) for CFA and IRT analysis. Statistical comparisons revealed no significant differences between the two groups regarding age, sex distribution, marital status, or psychiatric history (p>0.05). Furthermore, baseline scores on the MWQ, GAD-7, ISI, MCQI-14, and the DBST index were comparable between the groups, confirming the successful randomization and equivalence of the subsamples. Regarding the data distribution of the MWQ items, mean scores ranged from 1.53 to 1.76 (SD=0.79-0.88). Skewness values ranged from 0.83 to 1.48, and kurtosis values ranged from -0.09 to 1.50, indicating data normality within the acceptable range of ±2.

Item statistics and reliability evidence

Table 2 shows the item-level properties of the Korean version of the MWQ using Group I data (n=300). The corrected item-total correlations (CITC) were between 0.793 and 0.861, and the corrected inter-item discrimination (CID), calculated as the mean inter-item correlation, ranged from 0.680 to 0.751. Internal consistency reliabilities of the Korean version of the MWQ calculated through Cronbach’s alpha and McDonald’s omega were in line with the suggested limits (α=0.946, ω=0.946). Furthermore, the composite reliability of the scale extracted from CFA factor loadings was 0.971, indicating the MWQ is a highly reliable measure to capture the meta-worry of the participants.

EFA

Using Group I data, EFA was run to examine the factor structure of the MWQ using the oblique rotation (geominQ) method. Before conducting factor analysis, sampling adequa-cy and data suitability were checked based on the KMO measures (0.926) and Bartlett’s test of sphericity (p<0.001). A single factor was extracted with eigenvalues over 1, cumulatively explaining 71.5% of the variance. EFA factor loadings ranged from 0.817 (item 1) to 0.891 (item 5) (Table 2).

Convergent validity

To explore the convergent validity of the Korean MWQ using Group II data, we investigated the relationship of the MWQ score with the GAD-7, MCQI-14, and ISI scores (Table 3). We observed a strong positive association between the MWQ score and the GAD-7 (r=0.76; p<0.001; 95% confidence interval, CI [0.70, 0.80]), MCQI-14 (r=0.71, p<0.001, 95% CI [0.65, 0.76]), ISI (r=0.55, p<0.001, 95% CI [0.46, 0.62]), and the DBST index (r=0.12, p<0.05, 95% CI [0.01, 0.23]), indicating that more meta-worry is exhibited in individuals with higher GAD symptoms, high metacognitive beliefs about insomnia, and higher insomnia severity symptoms. This indicates the convergent validity of the Korean MWQ. In addition, the AVE value (0.829) extracted from the CFA factor loadings was in line with the recommended range and further indicates the validity of the MWQ (AVE was calculated from the CFA factor loadings presented below).

CFA

Using Group II data, we performed CFA using the diagonally weighted least square estimation method to determine the structural validity of the Korean version of the MWQ. The single-factor structure had an excellent model fit through the following fit indices: SRMR=0.027, RMSEA=0.084, CFI=0.995, TLI=0.992. CFA factor loadings ranged from 0.859 (item no. 3) to 0.941 (item no. 5), with high factor loadings for other items as well (0.915, 0.936, 0.885, 0.921, and 0.911 for items 1, 2, 4, 6, and 7, respectively). To determine whether the Korean MWQ can invariably be applied across the sexes, a multi-group CFA with configural, metric, and scalar invariances was performed. The values of ΔCFI and ΔRMSEA were within the recommended thresholds, indicating the scale can be applied similarly across males and females (Table 4).

Results from the IRT approach

Using Group II data, while assessing the model fits for IRT assumptions (i.e., unidimensionality, independence, and monotonicity), it was observed that the MWQ was strongly unidimensional (H=0.77), had local independence among scale items with Q3 coefficients ranged from -0.34 to 0.14, and showed no violations of monotonicity in all items with the crit values of 0 for all items. The discrimination and difficulty parameters demonstrated in Table 5 indicate that all MWQ items had discrimination values over 1.70. The α coefficients ranged from 1.96 to 3.78 (mean α=2.551), indicating each item provided enough information and the scale items can effectively differentiate individuals across the latent trait. The IICs in Figure 2A show that item 2 provided the most information (>3) about the latent trait, while other items also con-tributed varying levels of information in the mid-range of the latent trait. The difficulty parameters (b coefficients) in Table 5 and TIF in Figure 2B indicate that the scale provided more information about the participants from -0.75 to 2.0 theta level, indicating item responses of participants are endorsed in each category at varying ability ranges. Furthermore, the item response category characteristics curves represented in Figure 2C indicate that the ability ranges (i.e., thresholds) advanced monotonically for response categories 1 to 4, with lower levels of latent trait participants endorsed for category 1 and gradually endorsed for categories 2, 3, and 4 for the next higher levels of the latent trait.

DISCUSSION

This study aimed to examine the factor structure and validate the MWQ in the Korean context. Unlike previous validation studies that focused only on the classical test theory (CTT) approach [11,22], the current study used CTT and IRT approaches to assess the psychometric properties of the scale. Based on two independent subsamples of 300 participants each, the Korean version of the MWQ demonstrated excellent internal consistency (Cronbach’s α=0.946, McDonald’s ω=0.946) and strong model indices in CFA (SRMR=0.027, RMSEA=0.084, CFI=0.995, TLI=0.992). The item-level analysis further revealed strong correlations between individual item scores and the total scale score (CITC range=0.793-0.861) and strong interitem consistency (CID range=0.680-0.751), suggesting that the items contribute meaningfully to the overall measurement of meta-worry. These results indicate that the Korean MWQ is a valid, well-integrated measure for assessing negative metacognitive beliefs about worry.
Our reliability coefficients were highly consistent with those reported for the original English version and the Turkish adaptation [11,22], suggesting that each item in the Korean version retains its internal coherence after translation and cultural adaptation. Consistent with the original conceptualization of meta-worry as a unitary construct, our preliminary analysis indicated that the frequency items alone were sufficient to form a coherent dimension, even without the belief-rating component. This was further supported by a high composite reliability (0.971). The unidimensional structure revealed from EFA accounted for 71.5% of the variance, and CFA supported the single-factor solution with excellent model fit indices, which is in line with the original development and the Turkish adaptation studies [11,22]. All seven items of the MWQ showed strong factor loadings in EFA and CFA, further reinforcing the structural coherence of the scale. Results regarding the measurement invariance across sexes revealed that the Korean MWQ can be applied similarly across males and females.
IRT assumptions of the GRM model suggested the suitability of the data to perform GRM, and accordingly, GRM results revealed that the scale items provided sufficient information and could efficiently differentiate between individuals across the latent trait. The threshold parameters showed that the participants responded to each response category of the scale items at varying ability ranges. Moreover, the IICs and TIF showed that the scale items can provide information across a moderate spectrum of the latent trait, suggesting that the scale is useful in discriminating between individuals with higher and lower levels of meta-worry.
While considering the convergent validity of the scale, we observed that excessive worry about worrying was strongly associated with heightened GAD symptoms, more pronounced metacognitive beliefs related to insomnia and intrusive thoughts, and greater insomnia severity. These associations support the convergent validity of the scale. Interestingly, the correlation with the DBST index, while statistically significant, was relatively modest (r=0.12). This distinction likely arises because the DBST index quantifies a specific discrepancy between desired time in bed and total sleep time [33], which may function more as a trait-like sleep parameter or a behavioral mismatch rather than a direct measure of cognitive distress. In contrast, the ISI and MCQI-14 tap directly into the severity of symptoms and dysfunctional beliefs, constructs that share a closer conceptual overlap with the negative metacognitions assessed by the MWQ. These findings are in line with previous research showing that individuals who meet the criteria for GAD report significantly higher levels of meta-worry compared to non-anxious individuals or those experiencing other anxiety symptoms [15]. In addition, negative metacognitive beliefs such as cognitive self-consciousness, thought suppression, and intrusive thoughts tend to increase in certain situations, particularly at bedtime [49]. Intrusive thoughts before sleep have been linked to the development of primary insomnia, describing the pre-sleep thoughts as intrusive, uncontrollable, and negative [50]. Furthermore, negative metacognitive beliefs during the pre-sleep stage were found to delay the sleep onset and exacerbate the GAD symptoms and other psychopathologies [51]. Altogether, the frequency of meta-worry appears to have a direct influence on the occurrence and recurrence of GAD along with the pre-existing sleep problems, exacerbating the cognitive intrusiveness during pre-sleep conditions.
In this context, the Korean version of the MWQ offers a culturally relevant tool to assess meta-worry, which is an important metacognitive aspect of GAD. By focusing on the negative beliefs that can turn ordinary worry into a persistent and maladaptive process, the scale contributes to expanding the use of the established concept of meta-worry in diverse populations [10]. Clinically, strong item discrimination across the mid-to-upper range of meta-worry may be useful for identifying individuals who are at risk for GAD due to catastrophic beliefs about worry. Previous studies have indicated that a total score of approximately 11 on the original version may help distinguish individuals with GAD from those with other conditions [22]; future research in Korean populations could help confirm an appropriate threshold. In addition to its potential as a screening tool, the scale may aid in treatment planning by identifying individuals who are likely to benefit from interventions such as acceptance-based approaches. Moreover, as the test information curve shows good sensitivity within clinically relevant ranges, the MWQ may be useful for tracking therapeutic progress, serving as a complementary tool alongside broader symptom checklists like the GAD-7.
This study has certain limitations that should be acknowledged. First, participants were recruited through an online panel and self-selected into the study, which may limit the representativeness of the sample and introduce biases such as social desirability. Second, while the Korean version of the MWQ showed good psychometric properties in a non-clinical general population, its applicability to clinical populations remains unclear. Including participants with clinically diagnosed GAD in future studies would help determine the clinical utility of the scale, including optimal cut-off scores. Third, the study used a cross-sectional design, which does not allow for the assessment of test-retest reliability or temporal stability. Longitudinal studies are needed to evaluate the stability of the scale over time. Fourth, while the MCQI-14 was used to assess metacognitive beliefs related to insomnia, insomnia diagnoses were not verified through clinical interviews or treatment history, limiting the interpretation of findings related to insomnia severity. Despite these limitations, the Korean version of the MWQ appears to be a psychometrically sound tool with clinical implications in the field of mental health, addressing appropriate therapeutic interventions for the target individuals.
In conclusion, this study examined the psychometric properties of the Korean version of the MWQ and observed it as a reliable and valid measure of meta-worry in a general adult sample. Analyses based on CTT and IRT confirmed that the MWQ reliably measures a single construct and shows strong internal consistency and validity. These findings indicate the utility of the Korean MWQ as an effective tool for assessing meta-worry.

Notes

Availability of Data and Material

Data will be available from the authors when requested.

Conflicts of Interest

Seockhoon Chung, a contributing editor of the Psychiatry Investigation, was not involved in the editorial evaluation or decision to publish this article. All remaining authors have declared no conflicts of interest.

Author Contributions

Conceptualization: Han-Sung Lee, Seockhoon Chung. Data curation: Seockhoon Chung, Soyoung Yoo. Formal analysis: Han-Sung Lee, Seockhoon Chung. Methodology: Han-Sung Lee, Soyoung Yoo, Seockhoon Chung. Funding: Soyoung Yoo. Writing—original draft: all authors. Writing—review & editing: all authors.

Funding Statement

This research was supported by the K-Brain Project of the National Research Foundation (NRF), funded by the Korean government (MSIT) (RS-2023-00265393).

Acknowledgments

None

Figure 1.
Flowchart of the psychometric validation process. The study sample (N=600) was randomly split into two independent subsamples. Group I (N=300) was used for EFA and reliability testing, while Group II (N=300) was used for CFA, IRT modeling, and validity assessments. SD, standard deviation; CFA, confirmatory factor analysis; CITC, corrected item-total correlation; EFA, exploratory factor analysis; IRT, item response theory; GAD-7, Generalized Anxiety Disorder-7; ISI, Insomnia Severity Index; MCQI-14, Metacognition Questionnaire for Insomnia-14; DBST, discrepancy between desired time in bed and desired total sleep time.
pi-2025-0387f1.jpg
Figure 2.
Item information curves (IICs) (A), test information function (TIF) (B), and the item response category characteristic curves (C) of the Korean version of the Meta-Worry Questionnaire (MWQ).
pi-2025-0387f2.jpg
Table 1.
Clinical characteristics of the study participants
Variable Group I (N=300) Group II (N=300) Test p
Male 150 (50.0) 150 (50.0) χ²=0.000 >0.999
Age (yr) 48.8±16.7 48.8±16.5 t=0.000 >0.999
Marital status χ²=2.014 0.569
 Single 97 (32.3) 87 (29.0)
 Married, with kids 167 (55.7) 171 (57.0)
 Married, without kids 22 (7.3) 21 (7.0)
 Others 14 (4.7) 21 (7.0)
Psychiatric history
 Have you experienced or treated depression, anxiety, or insomnia? (Yes) 55 (18.3) 41 (13.7) χ²=2.096 0.148
Symptoms rating
 Meta-Worry Questionnaire 11.5±5.1 11.3±5.0 t=0.485 0.628
 Generalized Anxiety Disorder-7 4.5±4.9 3.9±4.6 t=1.546 0.123
 Insomnia Severity Index 10.5±5.9 10.0±5.1 t=1.110 0.267
 Metacognition Questionnaire for Insomnia-14 29.7±10.5 29.5±10.3 t=0.236 0.814
 Discrepancy between desired time in bed and desired total sleep time 0.8±1.6 0.9±1.6 t=-0.765 0.444

Values are presented as number (%) or mean±standard deviation.

Table 2.
Item properties of the Korean version of Meta-Worry Questionnaire (Group I, N=300)
Items Mean SD Skewness Kurtosis CITC CID Factor loading
Item 1 1.76 0.81 0.83 -0.09 0.793 0.684 0.817
Item 2 1.75 0.84 0.91 0.04 0.806 0.680 0.830
Item 3 1.53 0.80 1.48 1.50 0.795 0.727 0.819
Item 4 1.57 0.79 1.24 0.66 0.810 0.720 0.836
Item 5 1.59 0.83 1.27 0.72 0.861 0.751 0.891
Item 6 1.65 0.88 1.20 0.45 0.838 0.733 0.866
Item 7 1.56 0.84 1.36 0.86 0.829 0.732 0.858

SD, standard deviation; CITC, corrected item-total correlation; CID, corrected inter‑item discrimination.

Table 3.
Correlation coefficients of each variable in all participants (Group II, N=300)
Variables Age MWQ GAD-7 ISI MCQI-14
MWQ -0.20**
GAD-7 -0.28** 0.76**
ISI -0.12* 0.55** 0.61**
MCQI-14 -0.08 0.71** 0.59** 0.62**
DBST index 0.07 0.12* 0.13* 0.19** 0.14*

* p<0.05;

** p<0.01.

MWQ, Meta-Worry Questionnaire; GAD-7, Generalized Anxiety Disorder-7; ISI, Insomnia Severity Index; MCQI-14, Metacognition Questionnaire for Insomnia-14; DBST, discrepancy between desired time in bed and desired total sleep time.

Table 4.
Measurement invariance of the Korean version of the MWQ across sex
Sex (male/female) Model fit
Model comparison
χ2 df p CFI TLI RMSEA ∆CFI ∆RMSEA
Configural 85.95 28 - 0.995 0.992 0.090 - -
Metric 72.50 34 <0.01 0.996 0.996 0.087 -0.001 0.003
Scalar 98.09 47 <0.01 0.995 0.996 0.085 0.001 0.002

MWQ, Meta-Worry Questionnaire; χ², chi-square; df, degrees of freedom; CFI, comparative fit index; TLI, Tucker-Lewis index; RMSEA, root mean square error of approximation; -, not applicable.

Table 5.
Discrimination (α) and difficulty (b) parameters of the Korean version of the MWQ
α b1 b2 b3
MWQ 1 2.97 -0.06 1.10 2.21
MWQ 2 3.78 -0.13 0.81 1.87
MWQ 3 1.96 0.54 1.47 2.52
MWQ 4 2.04 0.39 1.56 3.07
MWQ 5 2.44 0.30 1.25 2.42
MWQ 6 2.53 0.19 1.12 2.20
MWQ 7 2.14 0.33 1.29 2.47

MWQ, Meta-Worry Questionnaire; α, discrimination power with slope coefficients; b, difficulty parameters with threshold coefficients.

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