The CSC-E consist of 14 items and is an expanded version of the cognitive-consciousness scale of the MCQ-65. It was developed using an adult population (Janeck et al., 2003) but the

Myers et al.

#### TABLE 1 | Study methodology, quality score, psychometrics and main findings relevant to the review.

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MCQ Psychometric Review in Youth

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MCQ Psychometric Review in Youth

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Myers et al.

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MCQ Psychometric Review in Youth

MCQ Psychometric Review in Youth

ADIS-IV-C/P, Anxiety Disorders Interview Schedule-Child/Parents Version; CAWS-Worry, Child and Adolescent Worry Scale; CDI, Children's Depression Inventory-Short Form; CY-BOCS, Children's Yale-Brown Obsessive-Compulsive Scale; LOI-CV, Leyton Obsessional Inventory–Child Version; MASC, Multidimensional Anxiety Scale for Children; MCQ, Metacognitions Questionnaire, -A Adolescent version, -C Child Version, -C30 Child-30; MCQ Subscales; PB, Positive beliefs about worry; NB, Negative beliefs about worry; CC, Cognitive Confidence; NFC, Need for control; CSC, Cognitive self-consciousness; CR, Child Revised; MOCI, Maudsley Obsessive-Compulsive Inventory; Penn State Worry Questionnaire for Children (PSWQ-C); PSS-SR, Post Traumatic Stress Disorder Symptom Scale Self-Report; RCADS, Revised Children's Anxiety and Depression Scale; RCMAS, Revised Children's Manifest Anxiety Scale; SCARED, Screen for Child Anxiety Related Disorders -r: Revised; SCAS, Spence Children's Anxiety Scale; SPQ, Schizotypal Personality Questionnaire (SPQ); SDQ, Strength and Difficulties Questionnaire; SPAI, Social Phobia and Anxiety Inventory; STAI, State Trait Anxiety Inventory, -C Child version, -T Trait version; RIES-C, Revised Impact of Event Scale-Child Version.

English version of the CSC-E was used without adaptation by one study in the review with adolescents, ages 15–17.

# Symptoms Measured

Results extracted for tests of concurrent validity examined relationships between the MCQ measures and worry, anxiety, obsessive-compulsive symptoms, depression, post-traumatic symptoms, general emotional difficulties, psychotic symptoms and dissociation. Symptom measures for individual studies are given in **Table 1**.

# Assessment of Study Quality

Scores on the quality assessment scale (maximum possible 8) ranged from 2 to 7 with a mean of 5.13. All studies had clear research questions and appropriate design. Most studies used validated symptom measures and used appropriate analyses which were described appropriately. Studies varied as to the amount of possible bias in their sampling method with the strongest studies attempting to make their samples representative, by for example using schools in locations evenly spread across a country. Studies were marked down on sampling method if samples were clearly not representative or were at risk of not being representative e.g., using individual schools without discussing how representative these schools were. Few studies carried out power calculations. The adequacy of sample size was assessed by power calculations we made based on parallel adult studies, and studies varied as to whether they had adequate power according to these criteria. Missing data was only reported and addressed in a minority of studies.

# Metacognitions Questionnaire-Adolescent Version (MCQ-A)

# Validity Evidence Based on Content

**Comprehensiveness**

The MCQ-A includes all items of the MCQ-30 with wording slightly simplified.

# **Understandability**

Cartwright-Hatton et al. (2004) report that the MCQ-A has a Flesch-Kincaid Reading Grade Level of 3.6. This means the questionnaire should be understandable to most children aged 9 and up. Beyond this no other data is available regarding its understandability to younger populations.

# Validity Evidence Based on Factor Structure

Three studies examined the factor structure of the MCQ-A. In their validation study, Cartwright-Hatton et al. (2004) carried out an exploratory factor analysis on a non-clinical sample (n = 158). They reported that a five-factor solution was chosen based on the Scree test and including only factors with Eigen values above one. The factors and item loadings corresponded closely with the adult MCQ-30, although goodness of fit indices were not reported. The Confirmatory Factor Analysis (CFA) of the MCQ-A carried out by Ellis and Hudson (2011) using a mixed clinical and nonclinical sample (total n = 114) found an adequate or good fit on four out of five fit indices: GFI = 0.96, AGFI = 0.95, NFI = 0.94, RFI = 0.94, PNFI = 0.86. Wolters et al. (2012) using a nonclinical sample (n = 317) found the five-factor structure had an adequate or good fit on all fit indices GFI = 0.95, AGFI = 0.94, NFI = 0.91, RFI = 0.90. Additionally, Wolters et al. found that a second-order model consisting of a higher-order factor (total score) and five lower-order factors (subscales) had an acceptable or good fit on most criteria. GFI = 0.94, AGFI = 0.93, NFI = 0.90, with the RFI of 0.89 just outside the criteria for acceptable fit. No studies examined measurement invariance across gender or age.

## Internal Consistency

Internal consistency was examined in seven studies without overlapping participants (Cartwright-Hatton et al., 2004; Matthews et al., 2007; Ellis and Hudson, 2011; Wilson et al., 2011; Farrell et al., 2012; Wolters et al., 2012; Mazloom et al., 2016). Five of these studies examined the Cronbach alphas of the total score and subscales and a further two only examined total scores. Cronbach alphas were adequate to excellent for the total score and all subscales apart from NFC (range 0.70– 0.92). Results for the NFC were mixed, in three samples they were below the 0.7 threshold of adequacy (range 0.57–0.66) but Cronbach alphas were adequate in three other samples (range 0.70–0.77).

# Test-Retest Reliability

Test-retest analysis was examined for the total score and subscales in three samples, in two papers (Cartwright-Hatton et al., 2004: 2 weeks test-retest; Wolters et al., 2012-Non-clinical sample, 7–21 weeks test-retest; OCD sample, 6–12 weeks testretest). Results of intraclass correlations were mostly good to excellent (range 0.72–0.95) apart from poor reliability for the NB subscale (0.24) and the total score (0.34) in the former study and NFC (0.35) in the non-clinical sub-sample of the latter study.

# Ranges

Three studies reported ranges for the MCQ-A (Cartwright-Hatton et al., 2004 [total score range only]; Matthews et al., 2007 and Wolters et al., 2012 [for clinicals and non-clinical participants separately]). Across-study ranges for the total score in non-clinical participants were 30–116. For subscales (across two studies) non-clinical ranges were PB 6–24, NB 6–24, CC 6– 22, NFC 6–20, CSC 6–24. In the one study (Wolters et al., 2012) that reported ranges for clinical participants, for the total score, the range was 36–104, for subscales: PB 6–24, NB 6–22, CC 6–22, NFC 6–22, and CSC 7–24. Results suggested the measure picked up a broad range of MCQ scores.

## Validity Evidence Based on Relations With Associated Measures

Nine studies with non-overlapping samples examined correlations between the MCQ-A and a range of psychological symptom measures. Results are shown in **Table 2**.

As shown the Total Score and the NB subscale significantly related to a range of symptoms in all analyses, with effect sizes ranging from medium to high. The other subscales related significantly to symptoms in most but not all analyses. Effect sizes for PB, CC, and CSC ranged from low to medium and for NFC from low to high.

TABLE 2 | Across-study correlations between MCQ-A and symptom measures.

#### \*p < 0.05.

Number of samples with correlations between symptoms and MCQ-A Total Score (TS) and subscales—Obsessive-Compulsive symptoms: TS, five samples (Cartwright-Hatton et al., 2004; Matthews et al., 2007; Crye et al., 2010; Farrell et al., 2012; Wilson and Hall, 2012) subscales, three samples (Cartwright-Hatton et al., 2004; Matthews et al., 2007; Wilson and Hall, 2012); Anxiety: TS, three samples (Cartwright-Hatton et al., 2004; Wolters et al., 2012 - non-clinical group; Wolters et al., 2012 - OCD group) subscales, four samples (Cartwright-Hatton et al., 2004; Wolters et al., 2012 - non-clinical group; Wolters et al., 2012 - OCD group; Wilson and Hall, 2012); Depression: TS and subscales, three samples (Cartwright-Hatton et al., 2004; Wolters et al., 2012 - non-clinical group; Wolters et al., 2012 - OCD group); Worry: one sample (Wilson et al., 2011); Post-traumatic symptoms: one sample (Mazloom et al., 2016); Psychotic symptoms: one sample (Debbané et al., 2009 -controlling for age and IQ).

#### Validity Evidence Based on Relations With a Criterion

Three studies (Cartwright-Hatton et al., 2004; Ellis and Hudson, 2011; Wolters et al., 2012) examined differences between the MCQ-A total score and subscales in clinical and non-clinical groups. The clinical groups consisted of people with "an emotional disorder" not specified (Cartwright-Hatton et al., 2004), anxiety disorders or anxiety disorders with comorbid depression (Ellis and Hudson, 2011) and Obsessive-Compulsive Disorder (Wolters et al., 2012). In all three studies the total score (range d = 1.06 to 1.49) and the NB (range d = 1.54 to 2.41) and NFC (range d = 0.61 to 1.00) subscales were significantly higher in clinical groups than control groups-effect sizes high for total score and NB, medium to high for NFC. PB was higher in two out of three studies (range d = 0.19 to 0.67) while CSC (range d = 0.31 to 0.78) and CC (range d = 0.20 to 1.03) were both higher in one out of three studies.

### Responsiveness

One study (Sanger and Dorjee, 2016) reported on changes in MCQ-A scores following an intervention, which consisted of a course of mindfulness training in non-clinical adolescents. The intervention was successful in leading to significantly increased response inhibition as shown by increased N2 negativity response to an attention task measured by an EEG. However, it did not lead to predicted changes on P300 mean amplitude (measures of attention efficiency). Significant pre to post differences were found on the total score of the MCQ-A (d = 0.64, medium effect size) as well as on NFC (d = 1.15, large effect size) compared to a control group, but not on the other subscales.

### Age

Four articles tested whether there were within-study relationships between age of participants and the MCQ-A total score and subscales: Matthews et al. (2007) in a non-clinical sample, age range 13–16, found that the MCQ-A total score, as well as the NB, NFC, and CSC subscales significantly negatively correlated with age, although correlations were low (range −16 to −19). Wilson et al. (2011) using a non-clinical sample, age range 11–16, and Ellis and Hudson (2011) using a mixed non-clinical and clinical sample, age range 12–17, found no significant correlations between age and the total score or subscales. Wolters et al. (2012), age range 12–18, also found no relationship between the total score or subscales and age in their clinical sample. In their non-clinical sample, there was a small positive relationship between the MCQ-A total scale and age, r = 0.12.

### Differences Between Sexes

Three studies examined differences between sexes in MCQ-A scores. Matthews et al. (2007) and Wilson et al. (2011) using the MCQ-A total score and subscales, Crye et al. (2010) using the MCQ-A total score only. No significant differences were found on any scores.

# Metacognitions Questionnaire-Child Version (MCQ-C)

# Validity Evidence Based on Content

#### **Comprehensiveness**

The MCQ-C does not include the six items designed to assess cognitive confidence in the MCQ-30. Bacow et al. (2009) justified omitting it based on the fact that this scale in adults may be made up of different factors (Hermans et al., 2008) and they argued that it should be omitted until this was clarified. Thus, one factor assessed in the MCQ-30 is not assessed in the MCQ-C.

### **Understandability**

Bacow et al. (2009) report that the MCQ-C has a Flesch-Kincaid Reading Grade Level of two-meaning it should generally be understandable to children ages 7–8. However, Smith and Hudson (2013) tested the understandability of the questionnaire in a sample of fourteen 7–8 year olds and found that a significant proportion of these children did not understand six items on the MCQ-C. Additionally, White and Hudson (2016) reported that six further items were assessed as being above Grade 2 level according to Fry's (1977) criteria.

# Validity Evidence Based on Factor Structure

Three studies (Bacow et al., 2009; Irak, 2012; Stevanovic et al., 2016) examined the factor structure of the MCQ-C. Both Bacow et al. in a combined clinical and non-clinical sample (n = 98) and Irak using a large non-clinical sample (n = 470), carried out a confirmatory factor analysis of the four-factor structure of the MCQ-C. Results of fit indices in Bacow et al.'s were mixed with an RMSEA of 0.077 suggesting an adequate fit but a CFI of 0.85 suggesting a poor fit. Irak's fit indices were good for RMSEA = 0.05 and RMR = 0.08, adequate for GFI = 0.90 and just marginally below adequate for CFI = 0.89 and AGFI = 0.88. Stenanovic et al. split their sample (n = 467) into two, with both of these samples having mixed clinical and non-clinical participants. They first carried out an exploratory factor analysis of the MCQ-C on one part of the sample (n = 233). This resulted in a three rather than four factor structure, made up of 16 items in total described as: (1) Cognitive monitoring, (2) Specific positive worry beliefs, and (3) General positive worry beliefs. In a subsequent CFA using the second part of their sample (n = 234) testing this three-factor structure, an adequate fit was obtained when three items of one of the scales were removed. No studies reported examining measurement invariance based on gender or age.

# Internal Consistency

Eleven articles (Bacow et al., 2009; Irak, 2012; Smith and Hudson, 2013; Benedetto et al., 2014; Holmes et al., 2014; Carr and Szabó, 2015; Donovan et al., 2017; Francis et al., 2017, 2018; Hearn et al., 2017a), representing 10 separate samples reported Cronbach alphas for the MCQ-C (two studies Francis et al., 2017 and Francis et al., 2018 reported Cronbach alphas for different parts of the scale in the same sample). Internal reliability of the MCQ-C total score was adequate to good in the three studies that reported it (range 0.73 to 0.87). Scores on subscales varied depending on the study PB (nine studies) range 0.46 to 0.86, NB (eight studies) range 0.60 to 0.78, NFC (three studies) 0.25 to 0.64, CSC (three studies) 0.61i to 0.75.

# Test-Retest Reliability

Test-retest reliability, over a 3 week period, reported only by Irak was good to excellent for all subscales and the total score (range 0.76 to 0.82).

# Ranges

Two studies with the same sample gave ranges for the MCQ-C (Francis et al., 2017, total score; Francis et al., 2018, PB and NB subscales). Ranges were broad: Total score ranged from 26 to 79, PB 6 to 22 and NB 6 to 24.

# Validity Evidence Based on Relations With Associated Measures

Eleven studies with non-overlapping samples examined correlations between the MCQ-C and a range of psychological symptom measures. Results are shown in **Table 3**.

As shown the Total Score and the NB subscale significantly related to a range of symptoms in all analyses. Effect sizes for the total score ranged from low-medium to high and for NB from medium to high. The other subscales related significantly to symptoms in most but not all analyses with effect sizes ranging from low to medium.

Validity Evidence Based on Relations With a Criterion Four studies examined differences between clinical and nonclinical populations: [Bacow et al., 2009; Smith and Hudson, 2013 using clinical groups with anxiety disorders; Donovan et al. (2016) using a group with Generalized Anxiety Disorder (GAD), and Hearn et al. (2017b) using a group with Social Anxiety Disorder, the GAD comparison in Hearn et al. was not included as the GAD sample overlapped with Donovan et al. (2016)]. Smith and Hudson found significantly higher scores in the clinical than the non-clinical group for the total score (d = 0.69), PB (d = 0.45) (medium effect sizes), and NB (d = 0.87; large effect size). However, NFC and CC did not distinguish the groups. Donovan et al. and Hearn et al. examined only NB and PB, both found that NB (ds of 1.72 and 1.15; both large effects) but not PB (ds of 0.52 and 0.25) was significantly higher in the clinical group than a non-clinical control. Bacow et al. (2009), with worry content controlled, found no significant differences between a clinical and non-clinical group on the total score or subscales beyond significantly higher scores on CSC in the non-clinical group. Of note in this study was that 60% of the non-clinical group had sub-clinical symptoms.

# Responsiveness

Holmes et al. (2014) in a trial treating GAD using Cognitive Behavior Therapy (CBT), in children aged 7–12, examined changes on only the NB and PB subscales of the MCQ-C. Examination of primary outcome measures showed the treatment was successful in reducing diagnostic GAD status and severity of disorder post-treatment compared to a control group, as well as leading a larger increase in overall functioning. They found a significant decrease in NB but not PB from pre-treatment to both post-treatment and 3 month follow up, effect size not reported. However, the decrease in NB was not significantly different from the decrease seen in a wait list control, assessed only at post-treatment.

Hearn et al. (2018) in a trial of CBT with patients with Social Anxiety Disorder (age of participants 8–17) also examined changes on only the NB and PB of the MCQ-C. They examined scores on measures at 12 week assessment when some but not all participants had completed treatment and at 6 month followup. At 12 week assessment there were significant reductions in diagnostic severity and social anxiety symptoms in the treatment group compared to the wait-list control. However, there were no significant difference on diagnostic status. They found no significant reductions at 12 week assessment on NB and PB. However, there were significant reductions from pre-treatment to 6 month follow-up in both NB and PB.

# Age

Three articles examined relationships between scores on the MCQ-C and age. Bacow et al. (2009), age range 7–17, examined age differences in their clinical group only, due to the small sample size of their non-clinical group. Of the four subscales TABLE 3 | Across-study correlations between MCQ-C and symptom measures.

#### \*p < 0.05.

Number of samples with correlations between symptoms and MCQ-C Total Score (TS) and subscales—Obsessive-Compulsive symptoms: TS and subscales, two samples (Irak, 2012; Boysan et al., 2016); Anxiety: TS, three samples (Irak, 2012; Kadak et al., 2013; Smith and Hudson, 2013) PB and NB four samples (Irak, 2012; Smith and Hudson, 2013; Benedetto et al., 2014; Hearn et al., 2017a) NFC and CSC, three samples (Irak, 2012; Smith and Hudson, 2013; Benedetto et al., 2014); Depression: TS, two samples (Bacow et al., 2009; Kadak et al., 2013) subscales, one sample (Bacow et al., 2009); Worry: TS, one sample (Bacow et al., 2009) PB, six samples (Hearn et al., 2017a; Bacow et al., 2009; Kertz and Woodruff-Borden, 2013; Carr and Szabó, 2015; Donovan et al., 2017; Francis et al., 2018, controlling for recruitment site) NB, five samples (Bacow et al., 2009; Kertz and Woodruff-Borden, 2013; Donovan et al., 2017; Hearn et al., 2017a; Francis et al., 2018, controlling for recruitment site) NFC and CSC, one sample (Bacow et al., 2009); Post-traumatic symptoms: one sample (Kadak et al., 2013); Dissociation: one sample (Kadak et al., 2013); Emotional Difficulties: one sample (Smith and Hudson, 2013).

and total score of the MCQ-C the only significant relationship was a positive relationship between CSC and age (only the unstandardized regression coefficient is reported (0.46). Irak (2012) split his sample into children (age 8–12) and adolescents (13–17). There was a significant difference between the groups on PB scores only, with the older group scoring higher. Carr and Szabó (2015) in a non-clinical sample, age range 7–12, examined only PB and found no relationship between this subscale and age.

#### Differences Between Sexes

Three studies examined differences in MCQ-C scores (Benedetto et al. using the MCQ-C subscales, Francis et al., 2018 using just the PB and NB subscales of the MCQ-C, and Irak, 2012, using the MCQ-C total score and subscales). Benedetto et al. and Francis et al. found no differences between scores of males and females. Irak found that females scored significantly higher than males on negative beliefs about worry, and the total score only.

#### Age X Gender Interaction

Two studies examined the interaction between age and gender; both studies used the MCQ-C total score and subscales. bib4 (2009; age range 7–17) found that for younger participants (1 SD below mean age) there were no gender differences on MCQ-C subscales or total score. However, in adolescents (1 SD above mean age) girls scored higher than boys on the MCQ-C total score only. bib44 (2012; age range 8–17) found no interaction effect between age and gender on the total score or subscales.

# Metacognitions Questionnaire-Child 30 (MCQ-C30)

#### Validity Evidence Based on Content

#### **Comprehensiveness**

The MCQ-C30 includes all items of the MCQ-30 with wording simplified to be understandable to children.

#### **Understandability**

No data on reading level or understandability was presented for this measure.

## Validity Evidence Based on Factor Structure

One study (Esbjørn et al., 2013) examined the factor structure of the MCQ-C30. This study carried out a CFA examining the fit of a two-level model with the higher-order factor consisting of the total score and the five subscales making up lower-order factors. They also included gender as a predictor of the total score. In their full non-clinical sample (n = 974) fit indices for the model were acceptable or good: CFI = 0.94, TLI = 0.93, RMSEA = 0.039. They subsequently carried out two CFAs on their sample split by age. This is a test of measurement invariance across age. Results for 13–17 year olds (n = 420) indicated an adequate fit to the two-level model: CFI = 0.90, TLI = 0.90, RMSEA = 0.06, while results for the 9–12 year olds (n = 554) were acceptable on one measure: RMSEA = 0.06, but marginally short on two others: CFI = 0.87, TLI = 0.86. Tests comparing the model fit of the two age groups showed no significant differences between them.

#### Internal Consistency

Five studies with non-overlapping samples (Esbjørn et al., 2013, 2015; Campbell et al., 2018 only results for clinical sample included for this study as non-clinical sample overlapped with another study Esbjørn et al., 2016, 2018) reported Cronbach alphas. Cronbach alphas for the total score ranged from just below the adequate cut-off to excellent: range 0.69–0.91. Subscale scores were somewhat mixed: PB 0.64–0.87, NB 0.65–0.78, CC 0.66–0.82, CSC 0.62–0.75<sup>1</sup> . NFC generally showed the weakest Cronbach alphas, with scores ranging from 0.59 to 0.68.

### Test-Retest Reliability

No studies using this measure reported test-retest results.

#### Ranges

Ranges for the MCQ-C30 were not presented in any study.

<sup>1</sup> In one study (Esbjørn et al., 2016) ranges of Cronbach alphas were given across most subscales including the CSC together rather than separately, this score is the lowest score mentioned in that study.

# Validity Evidence Based on Relations With Associated Measures

Three studies with non-overlapping samples examined correlations between the MCQ-C30 and psychological symptom measures. One of these studies (Campbell et al., 2018) had a very small sample (n = 23) which meant even some medium effect sizes were not significant in this study. Studies using both the Total score and subscales of the MCQ-C30 examined relationships with anxiety, depression and worry.

Results are shown in **Table 4**.

As shown the Total Score significantly related to symptoms in all analyses with effect sized ranging from medium to high. NB and NFC significantly related to anxiety and worry but not depression with all effect sizes ranging from medium to high. PB significantly related to symptoms in three out of four analyses and CC and CSC in two out of four with effect sizes for these subscales ranging from low to medium.

## Validity Evidence Based on Relations With a Criterion

Only one study examined differences between clinical and nonclinical groups with Esbjørn et al. (2015) finding that a group with Generalized Anxiety Disorder scored significantly higher on all subscales apart from CSC: PB (d = 0.70), NB (d = 1.58), CC (d = 0.69), and NFC (d = 1.07; range of effect sizes for significantly different scores medium to large) and that an Anxiety Disorder group scored significantly higher on NB (d = 1.15) and NFC (d = 0.87) than a non-clinical group (both large effect sizes).

# Responsiveness

Two studies examined changes in MCQ-C30 scores following treatment. Esbjørn et al. (2018) in a trial of MCT for GAD in participants aged 7–13 found 86.4% were free of GAD and 72.7% were free of all anxiety disorders post-treatment, at 6 month follow-up figures were 75 and 65.9%, respectively. The total score of the MCQ-C30 and all subscales apart from CC, were significantly reduced from pre to post-treatment, and all reductions remained significant at 6 months follow-up apart from PB. The effect-size, reported for the total score only, was large both from pre to post treatment, d = 0.84, and from pre-treatment to follow up, d = 1.08.

TABLE 4 | Across-study correlations between MCQ-C30 and symptom measures.

\*p < 0.05.

a (Campbell et al., 2018). b (Esbjørn et al., 2013). c (Esbjørn et al., 2016).

### Normann et al. (2016) in a trial of CBT for patients aged 7–12, with several anxiety disorders, examined changes on the total score of the MCQ-C30. The treatment successfully reduced anxiety symptoms from pre-treatment to post-treatment (medium effect) and pre-treatment to follow-up (large effect). The MCQ-C30 Total Score changed significantly from pretreatment to post-treatment d = 0.55 (a medium effect size), and from pre-treatment to follow-up d = 0.87 (large effect size). There was a significant decrease from post-treatment to follow-up.

## Age

One study (Lønfeldt et al., 2017b; age range 9–17) using the MCQ-C30 examined relationships between the total score and subscales and age. They found small but significant negative relationships between the MCQ-Total score (−0.08) as well as NB (−0.08) and NFC (−0.10) and age, for other subscales the relationship was not significant.

## Differences Between Sexes

Two studies examined differences on the MCQ-C30. Esbjørn et al. (2013) found a small but significant correlation between gender and the total score (subscales not examined), with girls scoring higher, but this difference was made non-significant when anxiety was controlled for Lønfeldt et al. (2017a) found that NB but not other scales or the total score were significantly higher in girls than boys.

# Metacognitions Questionnaire-Child Revised (MCQ-CR)

This questionnaire has only been examined in its validation study (White and Hudson, 2016) results are outlined below.

# Validity Evidence Based on Content

# **Comprehensiveness**

The MCQ-CR includes all items of the MCQ-30 with wording simplified to be understandable to children as young as 7–8.

# **Understandability**

The MCQ-CR includes the possibility of indicating "I don't understand" for each item Examination of responses suggested 75% of 7 year olds and 83% of 8 year olds understood all items on the MCQ-CR. However, there was a negative correlation (r = −0.23) between number of items filled in as "I don't understand" and age, indicating that understanding increased with age. A t-test comparing 7–8 year olds with 9–12 year olds found significantly greater lack of understanding in the younger group. For other analyses in the White and Hudson (2016) study items scored as "I don't understand" were treated as missing data. If only one item of a subscale was missing, data was replaced by the mean of that subscale, if more items were missing they were deleted pairwise or listwise depending on whether used in bivariate or multivariate analyses.

# Validity Evidence Based on Factor Structure

In a CFA testing the five-factor structure, the RMSEA result 0.06 was acceptable while IFI (0.89) and TLI (0.87) were just under the acceptable criteria.

# Internal Consistency

Cronbach scores for the subscales and total score were adequate to excellent-range 0.76–0.90.

## Test-Retest Reliability

White and Hudson did not explore test-retest and this is currently unknown.

# Ranges

Ranges for the MCQ-CR were broad: Total score 30–104, PB 6–22, NB 6–24, CC 6–23, NFC 6–24, CSC 6–23.

## Validity Evidence Based on Relations With Associated Measures

White and Hudson examined correlations between the MCQ-CR and both anxiety and worry.  The Total score (r = 0.55) and NB (r = 0.65) also were significantly related to worry with large effect sizes, and NFC (r = 0.46) and CSC (r = 0.48) significantly related to worry with medium effect sizes. PB (r = 0.08) and CC (r = 0.13) were not significantly correlated with worry.

Criterion-based validity evidence, and responsiveness were not tested.

## Age

The White and Hudson (2016) study had an age range of 7–12. They found a significant negative correlation between age and CSC (r = −0.36) and NFC (r = −0.15), relationships with other subscales and the total score were not significant.

### Differences Between Sexes

Differences on the total score and subscales were examined and all were non-significant.

# Other MCQ Measures

There was less comprehensive psychometric data available for other MCQ measures used. The two studies that used the MCQ-30 (Gallagher and Cartwright-Hatton, 2008; Welsh et al., 2014) did not report level of understandability, factor-analysis data, internal consistency, test-retest data, range, or analysis of age and gender relationships. Concurrent-based evidence of validity of the MCQ-30 total score came from Gallagher and Cartwright Hatton's finding that it significantly correlated with anxiety, only unstandardized betas were reported. Criterion based evidence for validity of the total score and some subscales came from Welsh et al.'s finding that a group, aged 12–17, at high risk of psychosis, scored significantly higher on the total score (d = 1.16), NB (d = 1.49), CC (d = 0.93) and NFC (d = 0.92) than controls, all effect sizes were large.

The positive beliefs about worry subscale of the MCQ-65 (MCQ-PBR) adapted for children by Meiser-Stedman et al. (2007) had excellent internal consistency (0.90). Concurrent based validity was supported by the fact that it significantly correlated with a measure of trauma symptoms cross-sectionally (r = 0.34). It also significantly correlated prospectively with

trauma symptoms 6 months after the trauma (r = 0.38) but this relationship became non-significant when time 1 trauma symptoms were controlled for (Meiser-Stedman et al., 2009). Criterion based evidence of validity came from the fact that scores on the MCQ-PBR were significantly higher in a group with Acute Stress Disorder than a control group (d = 0.66; a medium effect size) (Meiser-Stedman et al., 2007).

The CSC-E used by Jacobi et al. (2006) had adequate internal consistency (0.77). Concurrent-based evidence for validity was shown by significant relationships between the CSC-E and measures of obsessive-compulsive symptoms, anxiety and depression, individual rs not given. Criterion-based validity evidence was not assessed. The MCQ-PBR and CSC-E are purportedly unidimensional but this was not tested in these studies nor was level of understandability, test-retest data, range, or age and gender differences discussed.

# DISCUSSION

# Overview

Forty-five studies that used MCQ measures or derivatives in children/adolescents were identified in the review reflecting the growth in this research area. Studies used one of seven versions of MCQ measures or derivatives. Of these, one was adapted from the MCQ for use in adolescents-the Metacognitions Questionnaire-Adolescent version (MCQ-A); four for use with children: Metacognitions Questionnaire-Child version (MCQ-C), Metacognitions Questionnaire Children-30 (MCQ-C30), Metacognitions Questionnaire-Child version Revised (MCQ-CR) and the Metacognitions Questionnaire-65 Positive Beliefs scale Revised (MCQ-PBR); and two measures developed for adults were used without adaptation: Metacognitions Questionnaire-30 (MCQ-30), and the Cognitive Self Consciousness-Expanded scale (CSC-E).

The MCQ-A (12 studies) and MCQ-C (19 studies) were the most commonly used and the largest amount of psychometric data is available for these measures. The MCQ-C30 was used in eight studies but these consisted of only five separate samples. Other MCQ measures were each used in two or less studies.

Most studies using the MCQ-A only recruited adolescent participants (aged 12 and older)-the age group that the questionnaire was designed-for, so psychometric data for the MCQ-A largely represents the measure's properties as used with adolescents. Of the four measures designed for use with children, studies examining the MCQ-C, MCQ-C30, and MCQ-PBR used participants with a range of ages spanning children and adolescents (range across measures 7–18), while the one study that examined the MCQ-CR used children aged 7–12. Studies that used adult measures-the MCQ-30 and CSC-Eused adolescent samples and so results reflect their use with this population.

# Factor Structure

The strongest evidence supporting factor structure and latent constructs they represent exists for the MCQ-A as its five-factor structure was supported in the three studies that examined it (Cartwright-Hatton et al., 2004; Ellis and Hudson, 2011; Wolters et al., 2012). However, some caution must be applied when interpreting these results as only one of these studies (Ellis and Hudson, 2011) included clinical populations in their sample and only one of these studies (Wolters et al., 2012) had a sample >300. While all three studies examined a single-order model consisting of the five subscales of the adult versions of the MCQ, only Wolters et al. also examined a second-order model with total score as the higher-order factor and the five-subscales as lower order factors. Results suggested an adequate fit reflecting a recent study in adults which found that the data supported the MCQ-30 as having a second-order or bifactorial model in a large adult population (Fergus and Bardeen, 2017). Initial factor-analysis results of the MCQ-A are promising and were in line with our hypothesis that the factor structure of MCQ in younger populations would be similar to the one found in adults. However, further studies of both single and secondorder models are warranted, particularly using large clinical populations. Studies examining measurement invariance of the MCQ-A factors across gender and age are needed as this has not yet been assessed.

Evidence for the four-factor structure of the MCQ-C, examined in three studies, was mixed. The removal of the cognitive confidence subscale, one of the factors present in earlier versions of the MCQ, from the MCQ-C means that participants were not exposed to the same items as those who completed the full 30 item version in other studies. It is possible that this led to somewhat different responses in the retained items and it is also possible that this could affect item clustering and latent variables emerging from factor-analyses. An additional problem with removing one subscale from the measure is that one important type of metacognition identified in the S-REF model is not assessed. It also prevents comparison of results on this subscale with results from other versions of the MCQ. A strength of other MCQ full-scale measures in contrast is that their structure and items match the MCQ-30, allowing comparison of analyses using all subscales and the total score from children to adolescents to the adult population. The reasoning given by Bacow et al. (2009) for removing the cognitive confidence factor was that results from a study suggested that cognitive confidence may comprise several different elements–confidence in memory, reality monitoring and attention (Hermans et al., 2008) and that they wished to remove this factor until further research clarifies this. However, in our view this does not justify dropping this subscale from the questionnaire.

The five-factor structure of the MCQ-C30, with the total score as a higher-order factor, was supported, particularly in 13–17 year olds, but was only tested in one study and this study used a nonclinical population. Further studies examining the MCQ-C30's factor structure and measurement invariance using clinical and non-clinical populations are needed.

The MCQ-CR was only used in one study (White and Hudson, 2016). The factor-analysis results examining a fivefactor structure was only partially supportive of its latent structure. The MCQ-CR introduced the possibility of responding "I don't understand" to each item and the impact of this on factoranalysis and other results needs to be considered. An advantage of having the possibility of giving this response is that it can help in assessing which items are not well-understood. However, a significant disadvantage is that it introduces a new response to each item, that is not part of the original measure, which might bias interpretation and the desired response to the items. For example, rather than completing items based on the first overall impression, the person is asked to analyze their own understanding or doubts about the meaning of items in this context which may introduce deliberation and bias responses. Additionally, it raises the question as to how to treat items scored as "I don't understand." In the White and Hudson study they were treated as missing data which, depending on the amount of missing items, was replaced by means or deleted. A problem with this is that certain items may have not been generally understood more than others and so the pattern of missing data may not have been random.

The factor structure of the other MCQ measures i.e., the MCQ-30, MCQ-PBR, and CSC-E were not examined in the studies included in the review and remain to be explored in children/adolescent populations.

# Internal Reliability

The internal validity of most subscales and the total score of the MCQ-A were supported by adequate to excellent Cronbach alphas across studies although evidence for the internal reliability of the Need for Control subscale was mixed and needs further exploration. Of note, in the validation study of the MCQ-30 in adults the NFC subscale had the poorest internal reliability (Wells and Cartwright-Hatton, 2004). The internal reliability of the MCQ-C total score was supported in the three studies that examined it. The internal reliability of individual subscales varied between studies, with PB and NFC in particular having weak internal consistency in certain studies but not others. There was a similar pattern with the MCQ-C30 with general support for the total score but variations on subscales, with NFC having the lowest range of Cronbach alphas. Internal validity of the MCQ-CR Total score and subscales, MCQ-PBR and CSC-E were supported but were only examined in one study each and further exploration is needed.

# Validity Evidence Based on Relations With Associated Measures

Concurrent-based evidence for validity was strong across MCQ measures used, with significant relationships demonstrated between the different measures and a range of psychological symptoms. As per our hypothesis, of the subscales, the strongest and most consistent results were for NB. NB correlated significantly with a range of symptoms in almost all analyses across MCQ measures and all correlations represented medium or large effect sizes using Cohen's criteria. Results for NB reflect findings using the MCQ-30 in adults where NB relates strongly to a range of symptoms (e.g., Wells and Cartwright-Hatton, 2004; Spada et al., 2008; Bailey and Wells, 2013). This is consistent with the central role of beliefs concerning the uncontrollability and danger of thoughts in prolonging and intensifying psychological difficulties in the S-REF model (Wells and Matthews, 1994). The total score also emerged as a consistent predictor of symptoms, in fact it significantly related to different symptoms in every analysis that used it across MCQ measures. The strong and consistent findings for the total score may indicate the importance of a general metacognitive factor across disorders, while some of the subscales apart from NB may have more variability as to their levels of importance depending on which type of psychological difficulty.

# Validity Evidence Based on Evidence of Relations With a Criterion

Criterion-based evidence of validity of the total score and NB and NFC subscales of the MCQ-A came from findings in three studies that these scores were consistently higher in clinical than non-clinical groups, all with large or medium effect sizes, results for other subscales were less consistent. NB and NFC also distinguished clinical and non-clinical groups in the one study that tested this using the MCQ-C30 and along with CC in a study using the MCQ-30 (Welsh et al., 2014). Results reflect our hypothesis that, of the subscales, NB and NFC would most consistently and strongly differentiate clinical and non-clinical groups. This parallels findings in adults, with a meta-analysis examining across-study differences on MCQ subscales between clinical and non-clinical groups finding that the negative beliefs and need for control subscales were highest in clinical groups when compared to non-clinical controls, with large effect sizes (Sun et al., 2017). In studies that used the MCQ-C, the NB subscale was significantly higher in clinical than non-clinical groups in three out of four studies. However, the NFC subscale did not emerge as significantly higher in the two studies that examined this although in one of these studies most of the comparison non-clinical group had sub-clinical symptoms which in a fairly small sample was likely to have obscured results. The number of studies comparing clinical and non-clinical children/adolescents across MCQ measures is relatively small and further comparisons are needed particularly as in the metaanalysis of a large number of adult studies, all MCQ subscales emerged as significantly higher in clinical compared to nonclinical groups.

# Responsiveness

Only five studies in the review examined changes in MCQ scores following an intervention or treatment. Studies examining MCQ scores following CBT or Mindfulness interventions using the MCQ-A, MCQ-C, and MCQ-C30 found decreases on at least some subscales and/or total score giving initial support for some responsiveness for these measures. These results were in line with our hypothesis that there should be some change in MCQ scores following any form of treatment that was successful in reducing symptoms. The only study in the review (Esbjørn et al., 2018) that carried out a trial of Metacognitive Therapy (MCT), used the MCQ-C30 as one of their outcome measures. This is a particular test of responsiveness as MCT for GAD, examined in this study, attempts to modify a number of the belief domains measured by the MCQ. The findings of large effects for decreases on the total score, and significant decreases in most subscales at post-treatment is a promising finding for the use of the MCQ-C30 to measure changes in metacognitions following treatment in young populations. Results are consistent with our hypothesis that changes in MCQ scores would be particularly apparent following MCT. The responsiveness of the MCQ-C30 was also supported by a CBT trial which examined changes in the total score of the MCQ-C30 and found medium effects at post-treatment and large effects at follow-up. Further studies of responsiveness of the different MCQ measures, particularly following MCT, are needed.

# Age

Studies that examined the relationships between age and the MCQ-A total score and subscales (age range across studies 11– 18) found either no or small relationships. This is supportive of the idea that these metacognitions could be fully formed as early as 11 and remain stable across adolescence. However, studies did not break down the distribution of ages within their studies. Findings with other MCQ measures, that included younger participants, were somewhat mixed with individual subscales emerging in only some analyses as being related to age either positively or negatively, using the MCQ-C, MCQ-C30, and MCQ-CR. To fully test if there are any age differences in MCQ scores between children/adolescents of different ages, future studies should consider recruiting participants with an even distribution of age, or directly comparing scores of groups of younger and older children. The one study in the review that did the latter (Irak, 2012) found that 13–17 had higher scores on the positive belief subscale only compared to 8– 12 year olds, further studies are needed to see if this result is replicated. Current findings, together with the fact that ranges of MCQ measures when given were broad, suggest that dysfunctional metacognitions could develop at an early age. This is consistent with findings that suggest there may be childhood factors that lead to vulnerability to the development of these metacognitions, such as early experiences of emotional abuse (e.g., Myers and Wells, 2015; Østefjells et al., 2017) and parenting style (Gallagher and Cartwright-Hatton, 2008; Spada et al., 2012; Lønfeldt et al., 2017b).

# Differences Between Sexes

Most studies that examined differences between males and females on scores of MCQ measures (MCQ-A, MCQ-C, MCQ-C30, MCQ-CR) did not find significant differences which suggest they may, as hypothesized, not be present or may be small. Of note in one of the minority of studies that found differences (Esbjørn et al., 2013; a significantly higher score for girls on the total score) was that controlling for anxiety removed the effect, suggesting it may have been caused by elevated anxiety symptoms in girls. As higher prevalence rates for having an anxiety disorder in females compared to males have been found in children (Anderson et al., 1987); adolescents (Lewinsohn et al., 1998), and adults (Kessler et al., 1994) it may be important for future studies to control for anxiety in analyses of sex differences on MCQ scores in all these groups.

# Test-Retest Reliability

Test-retest reliability was examined in few studies using any of the MCQ measures but results with the MCQ-A and MCQ-C mainly support the stability of the measures over time. More research is needed into this across measures.

# Understandability

The understandability of the measures also needs further investigation. No study, to our knowledge, has examined the understandability of the MCQ-A to adolescents or preadolescents or whether the MCQ-A is more understandable to adolescents than the MCQ-30 and there is a need for these issues to be investigated. The understandability of the MCQ-C30, MCQ-PBR, and CSC-E to children or adolescents has also not been examined, while the one study that examined the understandability of the MCQ-C found that six items were not understandable to most of the small sample of 7–8 year olds tested. Although the MCQ-CR was found to be understandable to most 7–8 year olds in the one study that used it, understanding increased with age.

# CONCLUSIONS

The choice of which version of the MCQ to use in future studies in younger populations may well be influenced by the age group of the population being examined. The MCQ-A has largely good psychometric parameters in adolescents, the population it was designed for, and few studies have used it with younger populations. We suggest future studies using adolescents should certainly consider using the MCQ-A. Studies whose participants include pre-adolescent children and who want to measure the full range of constructs measured by the MCQ-30 should consider using the MCQ-C30 which has initial, although currently relatively limited, psychometric data supporting it. Two studies suggest that the MCQ-C30 is responsive to changes in metacognition following treatment and so the MCQ-C30 may be a particularly appropriate choice for treatment trials that include children.

The youngest age of children included in studies in the review was seven and psychometrics for children younger than this are unknown. The fact that studies only recruited children aged seven and above reflects the traditional view that this is the age where children can report on metacognitive knowledge (Flavell, 1979). However, a recent study (Marulis et al., 2016) suggests that when measured appropriately some younger children-age 3- 5 may be able to report on their metacognitions. Although not using an MCQ measure (Wilson and Hughes, 2011), found that some 6 year olds held both positive and negative metacognitions about worry. Future studies may consider examining children

# REFERENCES

younger than seven on MCQ measures although content and means of administration may well have to be adapted further to accommodate this group.

Strengths of almost all studies reviewed include clearly stated aims/hypotheses, the use of standardized symptom or diagnostic measures and appropriate analyses. Studies varied as to the appropriateness of selection criteria and the adequacy of sample size. Only a minority of studies discussed and corrected for missing data. Although the quality of studies was generally good, the methodological limitations, in particular variable sample sizes, should be born in mind when interpreting psychometric results. A number of studies included younger children and as results from two studies suggest some younger children may have difficulty in understanding some MCQ items, caution must be applied in interpreting some psychometric results of these studies. Although a number of studies included clinical populations most used non-clinical populations thus psychometrics for non-clinical groups are more extensive. No studies carried out analyses of psychometrics based on Item Response Theory (IRT) which has a number of advantages over analyses based on Classic Test Theory. Future studies would be strengthened by carrying out psychometric analyses based on IRT.

Bearing in mind these limitations, this review suggests that several MCQ measures have promising psychometrics in younger populations. The metacognitions assessed by the MCQ appear to be present in children/adolescents and can be assessed by self-report measures. The similarity of a number of results, particularly of concurrent and criterion based tests of validity, in comparison with results in adults, suggest consistent patterns of relationships between the metacognitions assessed by the MCQ and mental health symptoms. Research into metacognitive theory in children and adolescents is growing; research into metacognitive therapy in this population is in its infancy but initial results are promising (Simons et al., 2006; Esbjørn et al., 2018). Further testing and development of metacognitive measures in children and adolescents should help advance this promising area of research and practice.

# AUTHOR CONTRIBUTIONS

SM and AW were involved in study conceptualization. SM and SS were involved with systematic search, article collection and quality assessment, and data analysis. SM carried out data extraction and synthesis. All three authors contributed to the manuscript.

Psychiatry 44, 69–76. doi: 10.1001/archpsyc.1987.018001300 81010

associated with youth social anxiety disorder? J. Affect. Disord. 208, 33–40. doi: 10.1016/j.jad.2016.09.052

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Myers, Solem and Wells. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# APPENDIX

# METHODOLOGICAL QUALITY ASSESSMENT

#### Research question and design

0 Statistical tests not appropriate and/or not appropriately described

# Modeling the Relationships Between Metacognitive Beliefs, Attention Control and Symptoms in Children With and Without Anxiety Disorders: A Test of the S-REF Model

Marie Louise Reinholdt-Dunne<sup>1</sup> \*, Andreas Blicher<sup>1</sup> , Henrik Nordahl<sup>2</sup> , Nicoline Normann<sup>1</sup> , Barbara Hoff Esbjørn<sup>1</sup> and Adrian Wells<sup>3</sup>

<sup>1</sup> Department of Psychology, University of Copenhagen, Copenhagen, Denmark, <sup>2</sup> Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway, <sup>3</sup> School of Psychological Sciences, University of Manchester and Greater Manchester Mental Health NHS Trust, Manchester, United Kingdom

#### Edited by:

Gianluca Castelnuovo, Catholic University of the Sacred Heart, Italy

#### Reviewed by:

Michael Simons, RWTH Aachen University, Germany Łukasz Gawe¸ da, University Medical Center Hamburg-Eppendorf, Germany Sandra Sassaroli, Studi Cognitivi S.p.A, Italy

> \*Correspondence: Marie Louise Reinholdt-Dunne<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Psychology for Clinical Settings, a section of the journal Frontiers in Psychology

> Received: 07 August 2018 Accepted: 07 May 2019 Published: 07 June 2019

#### Citation:

Reinholdt-Dunne ML, Blicher A, Nordahl H, Normann N, Esbjørn BH and Wells A (2019) Modeling the Relationships Between Metacognitive Beliefs, Attention Control and Symptoms in Children With and Without Anxiety Disorders: A Test of the S-REF Model. Front. Psychol. 10:1205. doi: 10.3389/fpsyg.2019.01205 In the metacognitive model, attentional control and metacognitive beliefs are key transdiagnostic mechanisms contributing to psychological disorder. The aim of the current study was to investigate the relative contribution of these mechanisms to symptoms of anxiety and depression in children with anxiety disorders and in nonclinical controls. In a cross-sectional design, 351 children (169 children diagnosed with a primary anxiety disorder and 182 community children) between 7 and 14 years of age completed self-report measures of symptoms, attention control and metacognitive beliefs. Clinically anxious children reported significantly higher levels of anxiety, lower levels of attention control and higher levels of maladaptive metacognitive beliefs than controls. Across groups, lower attention control and higher levels of maladaptive metacognitive beliefs were associated with stronger symptoms, and metacognitions were negatively associated with attention control. Domains of attention control and metacognitions explained unique variance in symptoms when these were entered in the same model within groups, and an interaction effect between metacognitions and attention control was found in the community group that explained additional variance in symptoms. In conclusion, the findings are consistent with predictions of the metacognitive model; metacognitive beliefs and individual differences in selfreport attention control both contributed to psychological dysfunction in children and metacognitive beliefs appeared to be the strongest factor.

Keywords: anxiety disorders, childhood anxiety, metacognition, attention control, prevention, psychological treatment

# INTRODUCTION

Anxiety disorders are the most common psychological problems in children and adolescents with prevalence estimates ranging from 3–20% (Costello et al., 2005; Cartwright-Hatton et al., 2006). They are associated with considerable developmental, psychosocial and psychopathological complications (Beesdo et al., 2009). For example, anxiety has a negative impact on school

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functioning (Mychailyszyn et al., 2010) and is a major risk factor for developing comorbid disorders such as depression (Wittchen et al., 2003). Moreover, childhood anxiety disorders predict psychopathology in adolescence and adulthood (Bittner et al., 2007; Copeland et al., 2009), and are associated with substantial functional impairment in later life (Copeland et al., 2014). Hence, identifying factors underlying anxiety disorders and vulnerability to developing them may inform the development of effective prevention- and treatment interventions that could benefit individuals and society.

Cognitive theories of anxiety implicate biases in information processing in the development and maintenance of anxiety (e.g., Williams et al., 1988). Such biases can be observed in the content of interpretations of experience where the sense of danger and threat predominate (Beck et al., 1985). They are also evident at the level of attentional processes, where anxiety and depression are associated with biased attention for negative emotion-related stimuli (Bar-Haim et al., 2007; Cisler and Koster, 2010). A major challenge is to identify the factors that give rise to bias in psychological disorders. Early models viewed bias as the result of automatic or reflexive processes, but this has been questioned. For example, Wells and Matthews (1994) proposed specific multiple influences on bias including metacognitive beliefs and the individual's goals and strategies for self-regulation of which volitional attention control is a major component. Attention control has been conceptualized as the ability to control attention in inhibiting a dominant response in favor of a less accessible, subdominant response that may be more functional (Rothbart and Bates, 1998; Derryberry and Reed, 2002). Thus, attention control is viewed as a self-regulatory capacity, and it has been shown to moderate the association between attentional bias for threat and anxiety in adults (e.g., Derryberry and Reed, 2002; Bardeen and Orcutt, 2011) and in children (e.g., Lonigan and Vasey, 2009; Susa et al., 2012). Consequently, individual differences in attention control could contribute to resilience or vulnerability to emotional distress (e.g., Lonigan et al., 2004; Muris et al., 2004, 2007, 2008; Susa et al., 2012).

The role of such influences of attention and their link with emotional vulnerability has been captured in detail in the Self-Regulatory Executive Function (S-REF) model (Wells and Matthews, 1994, 1996), which is the basis of the metacognitive model of emotional disorder and treatment (Wells, 2009). In this model, psychological dysfunction is associated with a style of thinking called the cognitive attentional syndrome (CAS). The hallmark of the CAS is perseverative thinking consisting of worry/rumination, threat monitoring and maladaptive coping strategies. The activation and persistence of the CAS is dependent on underlying metacognitive knowledge (i.e., beliefs about cognition). Metacognitive knowledge refers to the information that individuals hold about their own cognition and internal states (e.g., "my worrying thoughts are uncontrollable") and about coping strategies (e.g., "worrying helps me to get things sorted out in my mind") and is implicated across mental disorders (Wells, 2009; Sun et al., 2017). Such metacognitions also contribute to psychological vulnerability when the presence of a mental disorder has been accounted for Nordahl and Wells (2017).

Within the S-REF model, attention control is considered a general resource that facilitates cognitive regulation and the ability to disengage from conceptual processing and perseverative self-focused attention (i.e., the CAS). Whilst this ability is separate from but related to the effects of metacognitive knowledge (Wells and Matthews, 1994) individual differences in attention control (i.e., executive functions) could affect the individual's ability to disengage from the CAS. Attentional control is likely to be comprised at least in part of knowledge or beliefs about attention and studies separating the effects of attention performance (skills) and beliefs about attention in psychological disorder are lacking.

In the metacognitive model in particular, beliefs about poor attention control are of interest as they are likely to be part of a broader dysfunctional metacognitive knowledge base hypothesized to underlie psychological disorder. Furthermore, different dimensions of metacognition may interact and increase the risk or severity of psychological disorder symptoms. In particular, high levels of perceived attention control could help to ameliorate the negative effects of beliefs about the dangerousness of thoughts on anxiety. In contrast, low levels of perceived attention control might enhance the negative effect of metacognitions about the uncontrollability and danger of worrying.

In adults, studies have found support for an association between greater maladaptive metacognitive beliefs and lower perceived attention control (Spada et al., 2010; O'Carroll and Fisher, 2013; Spada and Roarty, 2015; Fernie et al., 2016), and both perceived attention control and metacognitive beliefs have been found to explain unique variance in performance test anxiety (O'Carroll and Fisher, 2013), state anxiety in students before end-of-year examinations (Spada et al., 2010), and decisional procrastination (Fernie et al., 2016). Moreover, Fergus et al. (2012) found that the relationships between activation of the CAS and symptoms became increasingly stronger as self-reported attention control decreased, indicating that activation of the CAS is associated with especially deleterious effects for individuals with low attention control.

In sum, attention control (beliefs) and other metacognitive beliefs may be central to understanding psychological disorder and vulnerability. However, research on the relationship between attention control and metacognitive beliefs and their individual or combined contribution to symptoms is scarce, and to the authors' knowledge has not been investigated in children. The aim of the current study was therefore to investigate the relative contribution of attention control and metacognitive beliefs in children with anxiety disorders and in non-clinical controls. We set out to examine differences between community controls and clinical patients and to explore the unique and interactive effects of metacognitive beliefs and attention control within each group. Our hypotheses were as follows; (1) the clinical group will report greater severity of symptoms, lower attention control and higher levels of maladaptive metacognitive beliefs than the control group; (2) attention control will be negatively associated with symptoms; (3) metacognitive beliefs will be positively associated with symptoms; (4) metacognitive beliefs will be negatively associated with attention control;

(5) attention control and metacognitive beliefs will account for unique variance in symptoms; (6) there should be an interaction between metacognitive beliefs and attention control that contributes to symptoms. Because we cannot predict based on theory whether the interaction occurs in non-patients and/or patients we tested the model in the clinical and non-clinical groups separately.

# MATERIALS AND METHODS

## Participants and Procedure

A child community sample was recruited by sending invitation letters to 1601 families with children aged 8 to 12 years of age living within the catchment area of Center for Anxiety, Department of Psychology, University of Copenhagen. The sample was randomly selected by the Danish Central Office of Civil Registration, and the invitation letter specified that only typically developing children could participate. Families that wished to participate completed a questionnaire booklet online at home, prior to entering the clinic. When entering the clinic, mothers completed the parent version of the Anxiety Disorders Interview Schedule (ADIS; Silverman and Albano, 1996). The interview showed that all participating children were free of psychiatric disorders.

In the clinical sample, families referred their preadolescent children to the clinic, although they had often been recommended to contact the clinic by other professionals, e.g., psychiatrists and school psychologists. Consequently, preadolescents in aged between 7 and 14 that had a primary anxiety disorder, either generalized anxiety disorder, separation anxiety disorder, specific phobia, or social phobia were eligible as participants for the study if they also had an IQ above 70, and one parent native speaker of Danish. The children were assessed with the ADIS (Silverman and Albano, 1996). A combined diagnosis was derived from child and parent ratings, and showed that 110 (65.1%) of the children fulfilled the diagnostic criteria for generalized anxiety disorder, 33 (19.5%) for separation anxiety disorder, 14 (8.3%) for social phobia, and 12 (7.1) for specific phobia. The majority of the children (141; 83.4%) had comorbid anxiety disorders. Sixteen children (9.5%) also had comorbid mood disorder (Dysthymia or Major depressive disorder). A total of 351 children participated in this study, 182 community children (100 girls; 54.9%) between 7 and 12 years of age (M = 10.00, SD = 1.40) and 169 children diagnosed with a primary anxiety disorder (89 girls; 52.7%) between 7 and 14 years of age (M = 9.93, SD = 1.83) were included. Comparison of the community and clinical groups using Chi square and independent t-tests (on categorical and continuous variables, respectively) showed no significant group differences in gender or age distribution between the two groups.

## Ethics Statement

Ethical approval for the study was obtained from the Institutional Review Board at the Department of Psychology, University of Copenhagen. The study complies with ethical standards in the 1964 Helsinki declaration and its later amendments regarding assessment and treatment for children enrolled in psychological research studies. Written informed consent to participate was obtained from all parents of participating youth, and assent was obtained from the youth.

# Measures

The Revised Child Anxiety and Depression Scale – Child version (RCADS, Chorpita et al., 2000) is a 47-item self-report questionnaire measuring child anxiety and depression symptoms. RCADS consists of six subscales: Major depression, social phobia, panic disorder, separation anxiety, generalized anxiety, and obsessive-compulsive disorder. The major depression subscale consists of ten items, the social phobia and the panic disorder subscales consist of nine items, the separation anxiety subscale consists of seven items, and the generalized anxiety and the obsessive-compulsive disorder subscales consist of six items. A total score can be computed by summing the subscales. Validation of the Danish version of RCADS has shown satisfactory psychometric properties (Esbjørn et al., 2012). In the current study, internal consistency was excellent in both the community group (α = 0.94) and the clinical group (α = 0.93).

Attentional Control Scale for Children (ACS-C; Derryberry and Reed, 2002) is a 20-item self-report questionnaire measuring subjective attentional control. ACS-C consists of three subscales: Attention focusing, attention shifting, and flexible control of thought. The attention focusing subscale consists of nine items, the attention shifting subscale consists of six items, and the flexible control of thought subscale consists of five items. Items have to be scored on a 4-point scale with 1 = never, 2 = sometimes, 3 = often, and 4 = always. After recoding inversely formulated items, a total score can be computed by summing the subscales. The ACS-C has shown acceptable psychometric properties (e.g., Muris et al., 2004, 2007, 2008). In this study internal consistency was satisfactory in the clinical group (α = 0.74) and slightly below satisfactory level in the community group (α = 0.57).

Metacognitions Questionnaire for Children (MCQ-C30, Esbjørn et al., 2013) is a 30-item self-report questionnaire measuring metacognitive beliefs and processes in children and is a simplified version of the original adult scale (Wells and Cartwright-Hatton, 2004). MCQ-C<sup>30</sup> consists of five subscales: Positive beliefs about worry, negative beliefs about uncontrollability and danger of worry, cognitive confidence, need for control, and cognitive self-consciousness. All the subscales consist of six items. Items are scored on a 4-point scale with 1 = do not agree, 2 = agree slightly, 3 = agree moderately, and 4 = agree very much. A total score can be computed by summing the subscales. The Danish version of the questionnaire has shown satisfactory psychometric properties (Esbjørn et al., 2013). In the present study internal consistency was satisfactory in both the community group (α = 0.89) and the clinical group (α = 0.86).

# Overview of Data Analyses

Independent samples t-tests were used to compare the community and the clinical group on the RCADS, and on the subscales of the ACS-C and the MCQ-C30. Then we ran

bivariate correlational analyses to investigate the relationship between these variables.

To explore if there was any interaction effect between attention control and metacognitive beliefs on symptoms, we used structural equation modeling (Bentler, 1995). MCQ-C<sup>30</sup> total score, ACS-C total score, and the interaction between these two were used as observed variables, while symptoms (RCADS) was used as a latent variable consisting of all the RCADS subscales. Evaluation of the path coefficient from the interaction variable to the latent construct symptoms was of particular interest, as a significant path coefficient would indicate that moderation occurred.

Hierarchical linear regression analyses were run in each group to test the relative contribution of the attention control domains and metacognitive belief domains. Moreover, if the SEM analysis revealed a moderation effect, we planned to add this interaction variable to the regression models as a means to evaluate its relative contribution over domains of attention control and metacognitive beliefs. RCADS was used as the dependent variable throughout. Gender and age was controlled in the first step. In the second step, we entered the ACS-C subscales, and the MCQ-C<sup>30</sup> subscales were entered in step 3. If the SEM analyses revealed moderation, we planned to enter the interaction variable on the fourth step to test whether the interaction between metacognitive beliefs and attention control explained additional variance in the final equation when unique effects of attention control and metacognitive beliefs were controlled.

# RESULTS

# Group Comparisons

We found significant differences between the groups in symptom severity (RCADS total score), in all three domains of attention control, and in all domains of metacognitive beliefs except for judgments of cognitive confidence; the clinical group scored significantly higher on symptoms and metacognitive beliefs, and significantly lower on attention control compared to the community group. Descriptive statistics and group comparisons are presented in **Table 1**.

# Correlational Analyses

In both groups, there was a significant association between RCADS and ACS-C focusing and shifting, indicating that lower levels of attention control in these two domains are associated with higher levels of symptoms, while there was no association between RCADS and the ACS-C flexible subscale in any of the groups. RCADS was significantly associated with all domains of metacognitive beliefs in the community group, and with all but positive metacognitive beliefs in the clinical group, indicating that higher levels of symptoms are associated with higher maladaptive metacognitive beliefs. Moreover, lower levels of attention control were associated with higher levels of maladaptive metacognitive beliefs; the ACS-C focusing subscale was significantly and negatively associated with all domains of metacognitive beliefs in the community group, while it was significantly negatively associated with all metacognitive belief TABLE 1 | Group comparisons between the community- and the clinical group on age, symptom severity (RCADS), attentional control (ACS-C), and metacognitive beliefs (MCQ-C30); mean score, standard deviation and t-value.

RCADS, revised child anxiety and depression scale – child version; ACS-C, attention control scale for children; focus, attention focusing; shifting, attention shifting; flexible, flexible control of thought; MCQ-C30, metacognitions questionnaire for children; pos, positive metacognitive beliefs; neg, negative metacognitive beliefs; cc, cognitive confidence; nc, need for control; csc, cognitive self-consciousness. ∗∗p < 0.01.

domains except positive metacognitive beliefs in the clinical group. The ACS-C shifting subscales was significantly and negatively associated with negative metacognitive beliefs and judgments of cognitive confidence in both groups, and with need for control in the clinical group, but not with positive metacognitive beliefs or cognitive self-consciousness in any of the groups or need for control in the community group. The ACS-C subscale flexible control of thought was significantly and negatively correlated with negative metacognitive beliefs and cognitive confidence in the clinical group, but was not associated with metacognitions in the community group. The bivariate correlations are presented in **Table 2**.

# Structural Equation Modeling

Structural equation modeling (Bentler, 1995) was used to investigate if there was an interaction effect between attention control and metacognitive beliefs in predicting distress in each group. The total score from the ACS-C and MCQ-C<sup>30</sup> together with their interaction (ACS-C total score × MCQ-C<sup>30</sup> total score) were treated as observed variables, and symptoms were treated as a latent variable consisting of each of the RCADS subscales. The path coefficients were of particular interest, and if the path from the interaction variable to the dependent variable had no predictive value, it was deleted to evaluate a second model without the interaction. Evaluation of overall model fit was conducted according to Hu and Bentler (1999), where the Comparative Fit Index (CFI) and the Tucker-Lewis Index (TLI) should be close to or more than 0.95, the standardized root mean square residual (SRMR) should be less than 0.08, and the root mean square error of approximation (RMSEA) should be less than 0.06, to represent good model fit.

well when the interaction variable was included as the CFI and SRMR were within recommendations, the TLI was borderline of its recommended value, while the RMSEA was above recommended value; χ 2 (24) = 52.315, p = 0.001, CFI = 0.964, TLI = 0.947, RMSEA = 0.081, SRMR = 0.0367. All the standardized regression weights in the model were significant at the 0.001 level, which indicated that there was an additional interaction effect between attention control and metacognitive beliefs in the community sample. In this model, the squared multiple correlation for symptoms (RCADS) was 0.66, indicating that 66% of the variance in symptoms was accounted for by the predictors. We also evaluated the model fit in the community sample without the interaction term, and this model also fitted well, showing slightly better fit indices than the first model: χ 2 (19) = 41.233, p = 0.002, CFI = 0.968, TLI = 0.952, RMSEA = 0.080, SRMR = 0.0365. However, a chi square difference test showed that the model with the interaction variable was significantly better than the model without the interaction term: 1χ <sup>2</sup> = 11.082, 1df = 5, (p < 0.05). The model with the interaction variable in the community sample is presented in **Figure 1**.

In the community group, the data fitted the model reasonably

In the clinical sample, the path from the interaction variable (attention control x metacognitive beliefs) to symptoms was non-significant, indicating that there was no additional contribution of the interaction effect. The interaction variable was therefore deleted before evaluating the model fit. All standardized regression weights in this second model were significant at 0.01 level and the squared multiple correlation for symptoms (RCADS) was 0.52, indicating that 52% of the variance in symptoms was accounted for by the predictors. Still, the model did not provide an optimal fit to the data in the clinical group; χ 2 (19) = 48.644, p < 0.000, CFI = 0.942, TLI = 0.914, RMSEA = 0.096, SRMR = 0.0479. The model without the interaction variable in the clinical group is presented in **Figure 2**.

# Hierarchical Linear Regression Analyses

In the community group, gender and age was not a significant predictor of symptoms in any of the steps in the regression model. On the second step, all domains of attention control made unique contributions to symptoms and together they explained an additional 27% of the variance. In the second step, metacognitive beliefs explained 34% of the variance in symptoms over and above the attention control domains. Need for control was nonsignificant as a predictor, but all other domains of metacognitive beliefs were significant predictors, and negative metacognitive beliefs explained most variance. Adding metacognitive beliefs to the model led the shifting subscale of the ACS-C to be nonsignificant as a predictor, while the two other attention control subscales remained significant indicating that they accounted for unique variance in symptoms. Building on the SEM-analysis, the interaction effect was entered in the model in the fourth step and explained an additional 1 % of the variance. In this final step of the equation, attention control focusing and shifting, negative metacognitive beliefs, cognitive confidence, cognitive self-consciousness and positive metacognitive beliefs together

fpsyg-10-01205 June 7, 2019 Time: 17:5 # 5

with the interaction variable remained significant predictors and explained unique variance in symptoms.

In the clinical group, age was non-significant as a predictor of symptoms, while gender was significant as a predictor in the first step, showing that female gender was associated with higher levels of symptoms. In the second step, the ACS-C focusing subscale was significant as a predictor of symptoms, while the two other ACS-C subscales were not. In sum, attention control accounted for an additional 24 % of the variance in this step. Furthermore, gender remained a significant predictor of symptoms in the second step. In the third step, metacognitive beliefs explained an additional of 22 % of the variance in symptoms over and above age/gender and attention control. Of the MCQ-C<sup>30</sup> subscales, negative metacognitive beliefs and need for control were significant individual predictors. After adding metacognitive beliefs to the model, the ACS-C focusing subscales remained significant as a predictor, while gender became non-significant. The regressions are presented in **Table 3**.

To further explore the interaction effect in the community group, we examined two scatter plots with symptoms (RCADS total score) represented along the Y-axis. In the first scatter plot, attention control (ACS-C total score) were represented along the X-axis. The participants were separated in three group based on their total MCQ-C<sup>30</sup> score; group 1 consisted of the lowest scoring one-third of the sample; group 2 consisted of the one third of the individuals that had a moderate score; group 3 consisted of the one third of the individuals with the highest score. In the second scatter plot, metacognitive beliefs (MCQ-C<sup>30</sup> total score) were represented along the X-axis, and the sample was divided in low, moderate and high attention control groups following the same principle as outlined above. The scatter plots are presented in **Figures 3**, **4**.

Inspection of the plots shows that as dysfunctional metacognitions increase from moderate to high the negative relationship between attention control and symptoms becomes stronger. There is no effect at low levels of metacognitions. Conversely, at higher levels of attention control, the positive

TABLE 3 | Hierarchical regression analysis in the community- and clinical group separately, with RCADS total score as the dependent, gender/age and subscales from the ACS-C and MCQ-C<sup>30</sup> as predictors.

RCADS, revised child anxiety and depression scale – child version; ACS-C, attention control scale for children; focus, attention focusing; shifting, attention shifting; flexible, flexible control of thought; MCQ-C30, metacognitions questionnaire for children; pos, positive metacognitive beliefs; neg, negative metacognitive beliefs; cc, cognitive confidence; nc, need for control; csc, cognitive self-consciousness; β, standardized beta coefficients. <sup>∗</sup>p < 0.05, ∗∗p < 0.01.

relationship between metacognitions and symptoms becomes weaker but there is no effect at low levels of attention control.

# DISCUSSION

Metacognitive beliefs and attention control are two influences on cognitive regulation that have been implicated in the metacognitive model of psychological disorders. This model predicts differences between these factors in clinical and nonpatient individuals, for example that higher endorsements of maladaptive metacognitive beliefs and lower attentional control abilities should be found in clinical compared to non-clinical samples. It also predicts that these factors should be positively associated with symptoms of anxiety and depression in both groups, and that they may interact to moderate the strength of association each of these factors has with anxiety symptoms.

As predicted, the clinical child group showed elevated scores on dysfunctional metacognitive beliefs and lower scores on attention control compared to community controls. Negative metacognitive beliefs about worry differentiated the most between the groups among all predictors, while confidence in memory did not differentiate between the groups. Among the attention control dimensions, the flexible control of thought subscale differentiated the most between groups.

Within each group, we found the expected positive relationship between symptom severity and metacognitive beliefs, with the strongest association with negative metacognitive beliefs about worry. There was no association with positive beliefs in the clinical group, but all other relationships between

metacognitive belief domains and symptoms were significant in both groups and showed relationships of moderate or moderate to low strength. The expected negative relationship between symptoms and attention control was evident as attention focusing and shifting showed a moderate to low association with symptoms, while the relationship with the flexible control of thoughts subscale was non-significant in both groups.

With the exception of positive metacognitive beliefs in the clinical sample, attention focusing was negatively associated with all domains of metacognitive beliefs in both groups. The same relationship was observed between attention shifting, negative metacognitive beliefs and cognitive confidence in both groups, and also between attention shifting and need for control in the clinical group, indicating that maladaptive metacognitive knowledge is related to lower (perceived) ability to control attention.

On testing for interaction effects, the interaction between the total score on the MCQ-C<sup>30</sup> and the ACS-C, was found in the community- but not the clinical sample. This is an interesting finding because it suggests that a multiplicative effect of metacognitions and attention control on symptoms might be most relevant to sub-clinical anxiety and depression symptoms (at least in children). This raises an intriguing but speculative possibility, but one that is nonetheless congruent with the metacognitive model; that strongly held maladaptive metacognitive beliefs can neutralize the emotional benefit conferred by strong attention control beliefs, or conversely that strong attention control can remediate the negative effects of strongly held maladaptive metacognitive beliefs. But these findings point to a possible mechanistic or process-based difference between clinical and non-clinical samples. The interaction was not observed in the clinical group, one explanation might be that the deleterious effects attributed to high metacognitions is not moderated or offset by attentional control in those who have clinical disorder because their dysfunctional metacognitions are so much greater or these individuals use less effective mental regulation strategies. Such effects would be consistent with the S-REF model where attention control and flexibility is considered a general purpose processing resource that is compromised by high dysfunctional metacognitions and strategy selection (i.e., using extended negative thinking to deal with stress) (Wells and Matthews, 1994).

When exploring the relative contribution from the individual ACS-C and MCQ-C<sup>30</sup> subscales in the community sample, attention focusing and shifting, positive metacognitive beliefs, negative metacognitive beliefs, low cognitive confidence, cognitive self-consciousness and the additional interaction effect between metacognitions and attention control explained unique variance in symptoms. In the clinical sample, attention

focusing, negative metacognitive beliefs and beliefs about the need to control thoughts were the only significant independent contributors to symptoms, indicating that greater negative beliefs about the uncontrollability and danger of thoughts, need to control thoughts, and lower levels of attention focusing contribute individually to greater symptoms in clinically anxious children. While positive metacognitive beliefs are suggested to be an important disposition to anxiety disorder specific in metacognitive models of anxiety (Wells, 2009), we found that there was no independent effect of positive metacognitive beliefs on anxiety in the clinical group. One explanation could be that the effects of positive beliefs was masked by the substantial contribution from negative metacognitive beliefs and need for control, that are a more proximal contributor to disorder. Moreover, it could be that different domains of metacognitions may serve as maintenance factors (i.e., negative metacognitive beliefs and need for control) and as causal factors constituting vulnerability (i.e., positive metacognitive beliefs) as reported by others (e.g., Nordahl et al., 2019), but this possibility cannot be tested given the cross-sectional data-set in the present study.

In sum, our findings suggest that the metacognitive model might offer a useful framework to conceptualize psychopathology and psychological vulnerability in children with the implication that metacognitive therapy techniques for the preventionand treatment of disorder could be applicable. Metacognitive therapy (Wells, 2009) interventions aim to modify maladaptive metacognitive knowledge and strengthen flexible control over attention and they should be investigated in this group. While cognitive-behavioral therapy (CBT) is an effective treatment for anxiety in children (e.g., Ewing et al., 2015; James et al., 2015), regulatory processes (i.e., metacognition) and executive function aspects are in large overlooked in these models and treatments, which may account for the fact that a substantial number of patients are non-responders (James et al., 2005). For example, Reinholdt-Dunne et al. (2015) found that attention control did not significantly change in anxious children following CBT. Furthermore, the effect size of anxiety prevention programs for children has been reported as small (e.g., Fisak et al., 2011), indicating a need for further therapeutic developments. Applications of metacognitive therapy and techniques for children have begun and show promising results (Simons et al., 2006; Esbjørn et al., 2015; Murray et al., 2016, 2018; Simons and Kursawe, 2019). However, more studies are needed before any firm conclusions on its effect can be drawn.

The present study has several limitations that should be acknowledged. First, a cross-sectional design was used, and therefore no causal inferences can be made. Second, the clinical sample in this study predominantly consisted of children with primary GAD, and our study should therefore be replicated in a wider clinical context. Furthermore, the clinical sample was

a convenience sample of preadolescents referred for treatment, which resulted in a heterogeneous sample in terms of both primary diagnoses and age. While this is a limitation in some respect, our study has external validity as the sample consisted of patients referred to a clinic setting. Third, selfreport symptom assessment is a limitation of the study. Fourth, an important question concerns the measurement of attention control. In a recent study, the ACS was largely unrelated to behavioral performance measures of attention control (Williams et al., 2017), indicating that the ACS may represent subjective judgments of attention (metacognitive knowledge) rather than actual cognitive ability. However, metacognitive beliefs have been associated with objective shifting ability after controlling for symptoms and general cognitive function (Kraft et al., 2017) and improved neuropsychological functioning has been observed following MCT for depression (Groves et al., 2015) in adults, suggesting that there is a link between metacognitions (including beliefs about attention) and some aspects of objective executive functioning. Further research should utilize longitudinal and experimental designs with objective measures of attention control to better address the relation and direction of relations among metacognitive beliefs, objective attention control and psychopathology symptoms. In addition, testing the contribution of attentional control and metacognitive knowledge to symptoms in more specific clinical groups of children may further enhance our understanding. Further research should take account of potential age differences when exploring the influence of metacognitive knowledge and executive functions on psychological disorder and vulnerability in children.

# REFERENCES

# CONCLUSION

In conclusion, metacognitive beliefs and attention control appear to contribute to emotion disorder symptoms in both clinical and non-clinical children samples. This suggests that prevention strategies and treatment interventions should aim to modify maladaptive metacognitive knowledge and enhance judgments of attention control as recommended in metacognitive therapy. But the nature of the relationship between objective attention performance, beliefs about attention control and disorder symptoms remains to be differentiated.

# ETHICS STATEMENT

Ethical approval for the study was obtained from the Institutional Review Board at the Department of Psychology, University of Copenhagen. The study complies with ethical standards in Denmark regarding assessment and treatment for children enrolled in psychological research studies. Written informed consent to participate was obtained from all parents of participating youth, and assent was obtained from the youth.

# AUTHOR CONTRIBUTIONS

All authors were part of the design of the study. MR-D, AB, NN, and BE were part of data collection and writing the manuscript. HN and AW were part of analyzing the data and writing the manuscript.

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Reinholdt-Dunne, Blicher, Nordahl, Normann, Esbjørn and Wells. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Metacognitive Beliefs Predict Greater Mental Contamination Severity After an Evoking Source

Thomas A. Fergus\*, Kelsi A. Clayson and Sara L. Dolan

Department of Psychology and Neuroscience, Baylor University, Waco, TX, United States

Mental contamination occurs when individuals experience feelings of internal dirtiness and distress in the absence of physical contact with a contaminant.  The self-regulatory executive function (S-REF) model proposes that metacognitive beliefs contribute to the appraisal and regulation of thinking, leading to expectations that metacognitive beliefs would predict greater mental contamination severity following an evoking source. Women who reported directly experiencing sexual trauma (N = 102) completed selfreport measures of metacognitive beliefs and covariates during an online study session, and subsequently completed a task that evoked mental contamination during a followup in-person study session. Metacognitive beliefs surrounding the uncontrollability and danger of thoughts, cognitive confidence, and the need to control thoughts positively correlated with mental contamination severity following the evoking source. Metacognitive beliefs surrounding the uncontrollability and danger of thoughts predicted greater mental contamination severity following the evoking source in multivariate analyses that statistically controlled for baseline mental contamination severity, trait anxiety, and overlap among the metacognitive beliefs. The present results provide preliminary support for the S-REF model as a potential framework for conceptualizing mental contamination.

 Contact contamination occurs when there are concerns of dirtiness, endangerment, infection, or pollution following physical contact with a source. Mental contamination—the focus of the present research—typically arises in the absence of direct physical contact with a source (Rachman, 2004; Rachman et al., 2015). Images, memories, and thoughts are common sources of mental contamination (e.g., Fairbrother et al., 2005; Herba and Rachman, 2007; Elliott and Radomsky, 2009, 2012; Rachman et al., 2012). Mental contamination ranges along a continuum of severity and, thus, typically is best conceptualized dimensionally (Radomsky et al., 2018), with prior investigations using a full range of severity scores (e.g., Elliott and Radomsky, 2009, 2013; Radomsky and Elliott, 2009; Rachman et al., 2012; Brake et al., 2018; Jacoby et al., 2018; Ojserkis et al., 2018).

#### Edited by:

Adrian Wells, The University of Manchester, United Kingdom

#### Reviewed by:

Henrik Nordahl, Norwegian University of Science and Technology, Norway Costas Papageorgiou, Priory Hospital Altrincham, United Kingdom Samuel Myers, Bar-Ilan University, Israel

#### \*Correspondence:

Thomas A. Fergus<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Clinical and Health Psychology, a section of the journal Frontiers in Psychology

Received: 03 July 2018 Accepted: 04 September 2018 Published: 23 October 2018

#### Citation:

Fergus TA, Clayson KA and Dolan SL (2018) Metacognitive Beliefs Predict Greater Mental Contamination Severity After an Evoking Source. Front. Psychol. 9:1784. doi: 10.3389/fpsyg.2018.01784

Much of the extant research has focused on mental contamination in the context of obsessive-compulsive symptoms, in which individuals report experiencing internal dirtiness following ego-dystonic images or thoughts (e.g., Rachman, 2004; Elliott and Radomsky, 2009; Rachman et al., 2015). Cleansing behavior often is reported in such situations; yet, cleansing behavior ultimately contributes to the persistence of perceptions of dirtiness (Rachman et al., 2015). Despite associations with obsessive-compulsive symptoms, mental contamination likely spans across multiple forms of psychopathology (Blakey and Jacoby, 2018).  Mental contamination subsequent to sexual trauma relates to greater posttraumatic stress symptoms (Fairbrother and Rachman, 2004; Olatunji et al., 2008; Badour et al., 2013a,b) and may be particularly relevant to understanding intrusion-related distress associated with traumatic events. For example, feelings of dirtiness may contribute to avoidant coping that maintains mental contamination and distress surrounding images, memories, and thoughts (Coughtrey et al., 2014).

Conceptual models of mental contamination have yet to be fully developed and the purpose of the present research is to provide a preliminary examination as to whether the self-regulatory executive function (S-REF) model (Wells and Matthews, 1994) could serve as a framework for conceptualizing mental contamination. The S-REF model proposes that selfknowledge about coping guides self-regulatory efforts that ultimately maintain and worsen emotional distress (Wells and Matthews, 1994). Metacognitive beliefs (i.e., beliefs about thinking) underlie a particularly deleterious form of selfregulation known as the cognitive attentional syndrome (CAS) within the S-REF model. Threat monitoring and negatively valenced, self-referential thinking (e.g., worry) are hallmark features of the CAS (Wells and Matthews, 1994). The S-REF model has been applied to specific symptomatology, including posttraumatic stress (Wells and Sembi, 2004). The S-REF model proposes that posttraumatic stress symptoms are a normative part of an adaptation process in the acute aftermath of trauma exposure. For example, women commonly experience posttraumatic stress symptoms in the acute aftermath of sexual trauma (Shevlin et al., 2014). Mental contamination commonly is experienced by women following sexual trauma (e.g., Fairbrother and Rachman, 2004) and, thus, could be a relatively normative part of an adaptation process in the acute aftermath of sexual trauma as well.

An important consideration pertains to processes that help maintain mental contamination following sexual trauma, with the S-REF model leading to expectations that metacognitive beliefs contribute to greater mental contamination severity. For example, metacognitive beliefs activate the CAS and, thus, are responsible for "trauma-lock" (Wells and Sembi, 2004; Wells, 2009). Trauma-lock is a byproduct of the CAS that involves trauma perseveration.  Greater mental contamination severity would thus be expected to occur following trauma perseveration, which, according to the S-REF model, occurs because of metacognitive beliefs.

The S-REF model further holds that trauma-lock contributes to negative interpretations of symptoms, which often take the form of metacognitive beliefs (Wells and Sembi, 2004; Wells, 2009). For example, individuals may endorse beliefs such as "It's not normal to keep thinking about the trauma" or "I could lose my mind if I continue to think this way" (Wells, 2009). Such beliefs commonly are termed negative metacognitive beliefs because the beliefs relate to the uncontrollability or danger of thinking (Wells, 2000). Extant research supports negative metacognitive beliefs as being particularly relevant to posttraumatic stress (Bennett and Wells, 2010; Fergus and Bardeen, 2017a), thus highlighting the possible relevance of those specific metacognitive beliefs to mental contamination following trauma exposure. Other researchers have similarly raised the possibility that negative metacognitive beliefs underlie mental contamination (e.g., "If I cannot control my repugnant, repulsive thoughts I will go crazy," Radomsky et al., 2018). The S-REF model posits that negative metacognitive beliefs contribute to negative appraisals of symptomatology, thereby contributing to responses (e.g., worry and other CAS-relevant avoidant coping) that block emotional processing and result in greater threat perception. Underlying metacognitive beliefs are strengthened (e.g., about threat detection, danger of thinking) and traumalock is, thus, maintained (Wells and Sembi, 2004; Wells, 2009). The individual consequently experiences heightened emotional distress, possibly inclusive of mental contamination, because underlying metacognitive beliefs continue to fuel the process (e.g., trauma perseveration, negative interpretation of symptoms).

As noted, conceptual models of mental contamination have yet to be fully developed. Other researchers offered a preliminary cognitive conceptualization of mental contamination, which chiefly focuses on content-based self-appraisals related to responsibility and violation (Rachman et al., 2015; Radomsky et al., 2018). That conceptualization diverges from the S-REF model, as the S-REF model proposes that the impact of such appraisals on emotional distress is the result of metacognitive beliefs and the CAS (Wells, 2000). The present study sought to provide preliminary support for the S-REF model as a framework for conceptualizing mental contamination by examining metacognitive beliefs as a predictor of mental contamination severity following an evoking source among women experiencing sexual trauma. This particular sample

composition was chosen because of the reviewed literature indicating that mental contamination is particularly salient for women experiencing sexual trauma.

It was expected that metacognitive beliefs would positively relate to mental contamination severity following the evoking source. In addition to examining bivariate relations, multivariate analyses examined the robustness of those relations by statistically controlling for the effects of theoretically relevant covariates. Examined covariates included trait anxiety, disgust proneness, and posttraumatic stress symptom severity, each of which has shown relevance to mental contamination in prior research (e.g., Badour et al., 2014; Ojserkis et al., 2018). Including covariates in multivariate analyses allowed for an examination as to the incremental explanatory power of metacognitive beliefs in accounting for mental contamination severity. Multivariate analyses also statistically controlled for mental contamination severity before the evoking source to ensure observed effects captured something beyond baseline severity. Following from extant data that beliefs surrounding the danger and uncontrollability of thinking are metacognitive beliefs particularly relevant to posttraumatic stress (Bennett and Wells, 2010; Fergus and Bardeen, 2017a), as well as other indices of emotional distress (e.g., Spada et al., 2008), those metacognitive beliefs were expected to emerge as particularly relevant to mental contamination severity within multivariate analyses.

# MATERIALS AND METHODS

# Participants

A total of 713 undergraduate women at a private Southern United States university were screened for potential participation. Eligibility criteria were women who reported personally experiencing sexual trauma on the Life Events Checklist for DSM-5 (LEC-5; Weathers et al., 2013a).  A broad definition of sexual trauma was used following findings that women may resist endorsing experiencing sexual trauma when questions contain stigmatized terminology, such as "rape" (e.g., Resnick et al., 1993). A total of 206 women were eligible for participation (28.9% of the total screened sample), a percentage consistent with the lifetime prevalence of sexual trauma found in undergraduate samples of women (Frazier et al., 2009).

Of those 206 eligible participants, 102 participated in the lab-based session (49.5% of eligible participants). The average age of those 102 women was 19.4 years (SD = 3.1, range 18–38), with 56.9% self-identifying as White, 16.7% as Latina, 9.8% as multi-racial, 8.8% as Black, 5.9% as Asian, and 1.9% as "other" ethnicity or race. There were no significant age (t(204) = 0.76, p = 0.451) or ethnoracial (χ 2 (5) = 1.99, p = 0.851) differences between women who were eligible and did versus did not participate. There also were no significant differences on any of the study variable scores reported below between women who were eligible and did versus did not participate (magnitude of t(204) ranged from 0.66 to 1.31, ps > 0.193).

# Measures

## Metacognitions Questionnaire-30 (MCQ-30; Wells and Cartwright-Hatton, 2004)

The MCQ-30 is a 30-item short form of the 65-item MCQ (Cartwright-Hatton and Wells, 1997). Both MCQ versions assess the same five metacognitive beliefs: (a) positive beliefs about worry; (b) negative beliefs about the uncontrollability and danger of thoughts; (c) cognitive confidence; (d) need for control; and (e) cognitive self-consciousness. The distinctiveness of the five metacognitive beliefs of the MCQ-30 has since been replicated (Spada et al., 2008; Fergus and Bardeen, 2017b). MCQ-30 items are rated using a 4-point scale (ranging from 1 to 4). The MCQ-30 scales show approximately 5-week test-retest correlation coefficients ranging from 0.59 to 0.79 (Wells and Cartwright-Hatton, 2004). The MCQ-30 scales showed adequate to good internal consistency in the present study (Cronbach's αs ranging from 0.76 to 0.91).

# State Trait Inventory for Cognitive and Somatic Anxiety (STICSA; Ree et al., 2008)

The STICSA is a 21-item self-report measure of anxiety using separate state and trait versions. In regards to trait anxiety, participants rate the degree to which each item indicates how they "generally feel." STICSA items are rated using a 4-point scale (ranging from 1 to 4). The STICSA assesses cognitive and somatic anxiety, with a total score derived by summing the 21 item scores. Higher scores reflect greater trait anxiety. The STICSA shows approximately 7-week test-retest correlation coefficients of 0.60 and 0.66 (Ree et al., 2008). The STICSA showed good internal consistency in the present study (α = 0.88).

# Disgust Propensity and Sensitivity Scale-Revised (DPSS-R; van Overveld et al., 2006)

The DPSS-R is a 16-item self-report measure of disgust proneness, conceptualized as the propensity to experience disgust and negative appraisals of disgust. DPSS-R items are rated using a 5-point scale (ranging from 1 to 5). A 12-item version that improves upon the factorial validity of the measure was used (Fergus and Valentiner, 2009). Higher scores reflect greater disgust proneness. The DPSS-R shows approximately 8-week test-retest correlation coefficients of 0.69 and 0.67 (van Overveld et al., 2006). The DPSS-R showed good internal consistency in the present study (α = 0.85).

# PTSD Checklist for DSM-5 (PCL-5; Weathers et al., 2013b)

The PCL-5 is a 20-item self-report measure that assesses posttraumatic stress symptoms following PTSD criteria in the DSM-5 (American Psychiatric Association, 2013). PCL-5 items are endorsed using a 5-point scale (ranging from 0 to 4). A total score is derived by summing intrusion, hyperarousal, avoidance, and negative alterations in cognition and mood symptoms over the past month. Higher scores reflect greater

symptom severity. The PCL-5 shows an approximately 1 week test-retest correlation coefficient of 0.82 (Blevins et al., 2015). The PCL-5 showed good internal consistency in the present study (α = 0.93). Participants completed the PCL-5 in relation to the LEC-5 event that currently bothered them the most<sup>1</sup> .

## State Mental Contamination Scale (SMCS; Lorona et al., 2018)

The SMCS is a 15-item self-report measure that assesses state mental contamination and was developed to parallel the items of the trait measure of mental contamination known as the Vancouver Obsessive-Compulsive Inventory-Mental Contamination Scale (VOCI-MC; Radomsky et al., 2014). Lorona et al. (2018) reworded 15, of the 20, items from the VOCI-MC so that the timeframe of the SMCS items reflected the present moment. The remaining five VOCI-MC items were not conducive to rewording to the present moment and were dropped from the item pool. SMCS items are rated using a 5-point scale (ranging from 1 to 5). A total score is derived by summing the 15 item scores. Higher scores indicate greater state mental contamination and the SMCS showed good internal consistency in the present study (α = 0.94).

# Procedure

The local institutional review board approved the study protocol. Separate informed consent processes were completed before the online and lab-based session. The LEC-5 was completed online to determine study eligibility. Participants also completed the MCQ-30, STICSA, DPSS-R, and PCL-5 during the online session. The self-report measures were completed during a separate session to ensure the study activities in the labbased session did not inadvertently influence responses to the self-report measures. Moreover, completing the self-report measures during the separate online session helped reduce the likelihood that responses to those activities influenced responses in the lab-based session. There was an average of 22 days (SD = 16) between the online and the individual lab-based session<sup>2</sup> . Each eligible participant was invited to participate in the lab-based session through an e-mail, of which, as noted, only a subset of eligible participants signedup for the later study session. Eligible participants who attended the lab-based session initially completed an item asking about current feelings of dirtiness rated using a 0 to 100 scale, with 100 representing the greatest severity, to assess baseline mental contamination severity. Participants completed that same item again following the evoking task for purposes of a manipulation check (e.g., Elliott and Radomsky, 2009).

For the evoking task, participants completed the "dirty-kiss" task (Elliott et al., 2008) in which they listened to an audio recording through headphones that instructed them to imagine attending a party with a friend.  The recording ends with the friend asking, "How did you end up kissing that guy?" and participants then take off the headphones. This task has been used in prior research to evoke mental contamination (e.g., Elliott and Radomsky, 2012). Immediately following task completion, participants completed the SMCS. Participants then completed items related to the ease of imagining, vividness, and realism of the scenario using a 0 to 100 scale, with higher scores indicating greater ease imagining, vividness, and realism. Ratings indicated a high degree of ease imagining (M = 84.25, SD = 22.09), vividness (M = 82.41, SD = 19.22), and realism (M = 75.74, SD = 25.41) in the present study. Participants were then debriefed. Participants received partial course credit for their participation in both the online and labbased session.

# RESULTS

# Preliminary Analyses

A paired-samples t-test was used to examine the effectiveness of the dirty-kiss task by comparing feelings of dirtiness from before, M = 18.32, SD = 22.14, and after, M = 65.95, SD = 28.82, the task. That analysis indicated a significant increase in dirtiness ratings, t(101) = 15.03, p < 0.001, and the effect was large in magnitude, Cohen's d = 1.86. The task had its intended effect.

Descriptive statistics and zero-order correlations among the study variables are presented in **Table 1**. The maximum magnitude values for skewness (baseline feelings of dirtiness: 1.09) and kurtosis (PCL-5: 0.94) of the study variables were below levels typically considered elevated (i.e., | 2| ; Bandalos, 2018). As such, the distributions of scores did not appear to substantively deviate from normality. The metacognitive beliefs generally significantly intercorrelated with the covariates, save for baseline feelings of dirtiness only correlating with cognitive confidence. As predicted, metacognitive beliefs generally positively correlated with mental contamination severity following the evoking source (i.e., SMCS scores). Those correlations were small-tomoderate in magnitude. Associations with mental contamination severity following the evoking source were found in relation to negative metacognitive beliefs, cognitive confidence, and the need for control. Because positive metacognitive beliefs and cognitive self-consciousness did not correlate with mental contamination severity following the evoking source, the positive metacognitive beliefs and cognitive self-consciousness scales of the MCQ-30 were dropped from multivariate analyses (e.g., Thielsch et al., 2015). In addition, among the covariates,

<sup>1</sup>Approximately half of the sample (i.e., 48%) indicated that sexual trauma was the most bothersome LEC-5 event and no other LEC-5 event was endorsed as the most bothersome by more than 10% of the sample. SMCS scores following the evoking task did not significantly differ based upon whether sexual trauma was the most distressing LEC-5 event (t(100) = 1.32, p = 0.192). Negative metacognitive beliefs continued to share an association with SMCS scores when including the most distressing LEC-5 event (sexual trauma versus non-sexual trauma) as a covariate (β = 0.34, p = 0.015, in final block of regression analysis). The most distressing LEC-5 event (sexual trauma versus non-sexual trauma) did not moderate the association between negative metacognitive beliefs and SMCS scores (β = -0.18, p = 0.590, for the interaction term).

<sup>2</sup>Days between study sessions did not correlate with any of the study variables (magnitude of rs ranging from 0.01 to 0.12, ps > 0.252).

#### TABLE 1 | Descriptive statistics and zero-order correlations.

fpsyg-09-01784 October 22, 2018 Time: 17:26 # 5

N = 102. ∗∗p < 0.01, <sup>∗</sup>p < 0.05 (two-tailed). MCQ, Metacognitions Questionnaire (P, Positive; N, Negative; CC, Cognitive Confidence; NC, Need for Control; CSC, Cognitive Self-Consciousness); STICSA, State-Trait Inventory of Cognitive and Somatic Anxiety; DPSS-R, Disgust Propensity and Sensitivity Scale-Revised; PCL-5, PTSD Checklist for DSM-5; SMCS, State Mental Contamination Scale.

only trait anxiety and baseline feelings of dirtiness correlated with mental contamination severity following the evoking source. As such, disgust proneness and posttraumatic stress symptoms were dropped as covariates from multivariate analyses.

## Block 4, baseline feelings of dirtiness and negative metacognitive beliefs were the only significant statistical predictors.

# DISCUSSION

# Regression Analyses

A hierarchical multiple linear regression was used to examine the unique variance accounted for by metacognitive beliefs in mental contamination severity following the evoking source (i.e., SMCS scores). The retained covariates (trait STICSA, baseline feelings of dirtiness) were entered into Block 1 of the model. The retained metacognitive variables were entered into subsequent blocks in descending order based upon the magnitude of zeroorder correlations with mental contamination severity following the evoking source. As such, negative metacognitive beliefs from the MCQ-30 were entered into Block 2, need for control from the MCQ-30 was entered into Block 3, and cognitive confidence from the MCQ-30 was entered into Block 4. The maximum variance inflation factor (VIF) among the predictors in the regression analysis was 2.31, well below conventional guidelines for indicating problems with multicollinearity (>10; Cohen et al., 2003). The maximum Cook's D value was 0.08, well below conventional guidelines for indicating the presence of an overly influential case on the regression model (>1.0; Cohen et al., 2003). The maximum Mahalanobis distance value was 14.95 and, thus, there were no values at or above the respective critical value for indicating multivariate outliers (χ 2 (5) = 20.52, p < 0.001; Mertler and Vannatta, 2005).

The variance accounted for in mental contamination severity following the evoking source and standardized beta weights from the regression analysis are presented in **Table 2**. As shown, the covariates collectively accounted for 14% of variance in mental contamination severity in Block 1. Adding negative metacognitive beliefs to the model in Block 2 accounted for an additional 8% of variance in mental contamination severity. Adding metacognitive beliefs related to need for control and cognitive confidence in Block 3 and Block 4, respectively, did not explain additional variance in mental contamination severity. In The present study sought to provide a preliminary examination of the S-REF model (Wells and Matthews, 1994) as a framework for conceptualizing mental contamination by investigating metacognitive beliefs as predictors of mental contamination severity. An S-REF model applied to posttraumatic stress (Wells and Sembi, 2004) was the selected framework for the present study given the frequent occurrence of mental contamination following sexual trauma. Women who experienced sexual trauma completed a self-report measure of metacognitive beliefs and later completed a task that evoked mental contamination. Consistent with study predictions, metacognitive beliefs generally positively correlated with mental contamination severity following the evoking task. In bivariate analysis, metacognitive beliefs related to the uncontrollability and danger of thoughts, cognitive confidence, and need for control shared small-to-moderate correlations with mental contamination severity. However, only negative metacognitive beliefs (i.e., uncontrollability and danger of thoughts) related to mental contamination severity in multivariate analyses, suggesting, as predicted, that those metacognitive beliefs are particularly relevant to mental contamination.

The association between negative metacognitive beliefs and mental contamination severity is notable because it was found even while statistically controlling for baseline mental contamination severity, trait anxiety, and interrelations among other metacognitive beliefs. Disgust proneness and posttraumatic stress symptom severity were not included as covariates in multivariate analyses, as those two variables unexpectedly did not correlate with mental contamination severity following the evoking source in the present study. That pattern of findings stands in contrast to prior findings that disgust and posttraumatic stress symptoms are associated with changes in feelings of dirtiness from before to after an evoking source among women experiencing sexual trauma (Badour et al., 2014). Sample

N = 102. ∗∗p < 0.01, <sup>∗</sup>p < 0.05 (two-tailed). STICSA, State-Trait Inventory of Cognitive and Somatic Anxiety; MCQ, Metacognitions Questionnaire (N, Negative; NC, Need for Control; CC, Cognitive Confidence).

composition could be one reason for the discrepant findings, as Badour et al. (2014) used a narrower group of respondents experiencing sexual trauma (i.e., women reporting sexual trauma exposure and denied history of physical assault) than the present study. Assessment method could be another reason for discrepant findings, as Badour et al. assessed mental contamination via feelings of dirtiness alone. Although that assessment method is common (e.g., Elliott and Radomsky, 2009), and was included as a manipulation check in the present study, Radomsky et al. (2014) contend that mental contamination is more fully represented through aspects other than feelings of dirtiness. The state measure of mental contamination used in the present study follows Radomsky et al.'s contention via conceptualizing mental contamination as broader than feelings of dirtiness alone (Lorona et al., 2018). Although tenable possibilities, future research examining the contribution of disgust proneness and posttraumatic stress symptoms to in-vivo experiences of mental contamination appears warranted before firmer conclusions about those interrelations are drawn.

Negative metacognitive beliefs were expected to be the metacognitive beliefs particularly relevant to mental contamination following from extant findings linking those metacognitive beliefs to posttraumatic stress (Bennett and Wells, 2010; Fergus and Bardeen, 2017a). In the context of posttraumatic stress, beliefs about the uncontrollability and danger of thoughts putatively lead to threatening interpretations of symptoms that contribute to emotional distress (Wells and Sembi, 2004; Wells, 2009). Images, memories, and thoughts are common sources of mental contamination (e.g., Fairbrother et al., 2005; Herba and Rachman, 2007; Elliott and Radomsky, 2009, 2013; Rachman et al., 2012). Following from the S-REF model, negative interpretations of symptoms would be expected to increase the likelihood of unwanted images, memories, and thoughts occurring (Wells and Sembi, 2004; Wells, 2009) and, thereby, re-evoke mental contamination. Prior research indicates that re-evoking mental contamination contributes to its persistence (Coughtrey et al., 2014). Additionally, negative metacognitive beliefs could contribute to the engagement in avoidant behavior in an attempt to regulate thoughts, with that behavior ultimately blocking emotional processing and maintaining distress (Wells, 2000). Cleansing behavior is a common type of avoidant behavior reported in the context of mental contamination (Rachman et al., 2015) and future research should seek to examine whether negative metacognitive beliefs are associated with cleansing behavior following a mental contamination provocation.

Conceptual models of mental contamination have yet to be fully developed, with existing cognitive conceptualizations emphasizing the role of negative appraisals in relation to mental contamination (Rachman et al., 2015; Radomsky et al., 2018). Whereas such conceptualizations do not preclude the consideration of metacognitive beliefs, existing examinations of the relevance of cognitive variables to mental contamination have tended to focus on content-based self-appraisals related to responsibility and violation (e.g., Radomsky and Elliott, 2009; Elliott and Radomsky, 2013). The S-REF model would lead to predictions that mental contamination is not the result of such content-based self-appraisals (e.g., "I am pathetic, weak, hopeless," Radomsky et al., 2018), but is the result of metacognitive beliefs and the CAS (Wells, 2000). Content-based self-appraisals, unfortunately, were unexamined. Future research that concurrently examines content-based self-appraisals and metacognitive beliefs will aid in elucidating the degree to which those variables incrementally contribute to our understanding of mental contamination.

Additional support for the S-REF model as a tenable framework for conceptualizing mental contamination could come from future research findings that content-based selfappraisals do not account for unique variance in mental contamination severity once statistically controlling for metacognitive beliefs, such as the uncontrollability and danger of thoughts, or the CAS. Such patterns of findings have emerged in prior studies examining obsessive-compulsive symptoms (e.g., Myers et al., 2009; Solem et al., 2010). It is important to note that content-based self-appraisals can initiate self-regulatory efforts in the form of the CAS (Wells, 2000). It is thus possible that the

relationship between content-based self-appraisals and mental contamination depends upon metacognitive beliefs or the CAS serving as moderators. Indeed, extant research supports that possibility when considering the relation between content-based self-appraisals and the frequency of ego-dystonic intrusive thoughts (Fergus and Wu, 2010). Another possibility is that the impact of the types of beliefs on mental contamination differs across time, which could be examined in future longitudinal research.

Future research supporting the relevance of metacognitive beliefs to mental contamination would point to potential treatment strategies when seeking to reduce mental contamination. For example, such patterns of findings may point to a focus on the metacognitive mode in which intervention strategies chiefly target how one relates to cognitive events (Wells, 2000). A greater focus on the metacognitive mode, rather than the object mode, in which the content of appraisals are evaluated for their accuracy, could be preferred when seeking to reduce mental contamination. The present results indicate the relevance of negative metacognitive beliefs to mental contamination. Intervention strategies relevant to mitigating negative metacognitive beliefs about the uncontrollability and danger of thoughts include verbal reattribution, behavioral experiments, and detached mindfulness (Wells, 2009). Detached mindfulness seeks to promote the metacognitive mode by having individuals consider themselves as an observer separate from their thoughts to facilitate suspension of conceptual processing and the alteration of metacognitive beliefs (Wells, 2009). Current treatment efforts for mental contamination are in their relative infancy (Coughtrey et al., 2013) and future research may seek to examine the usefulness of metacognitive intervention strategies in the reduction of mental contamination severity.