The reflective function questionnaire for youth: Hungarian adaptation and evaluation of associations with quality of life and psychopathology

Abstract

An important correlate of mental health problems is mentalizing capacity, which appears to be particularly influential during adolescence. However, quality of life has not been studied in relation to mentalizing capacity among adolescents. This study aimed to translate the Reflective Function Questionnaire for Youth (RFQY) into Hungarian, present its psychometric properties, and assess its relationship with demographic characteristics, psychopathology and quality of life. A community sample of 384 youths aged 12–18 years completed the RFQY, the Measure of Quality of Life for Children and Adolescents, and the Strengths and Difficulties Questionnaire. First, we conducted an exploratory factor analysis with direct oblimin rotation on the RFQY items. Next, we assessed the associations between the RFQY and demographics, quality of life, and psychopathology. The EFA resulted in four factors: Internal-self, Internal-other, Self-other, and Strong emotions. The Cronbach’s alpha coefficients of the scales were .81, .82, .67, and .80, respectively. The subscales were uniquely associated with psychopathology and quality of life. Our study provides the first psychometric support for the Hungarian version of the RFQY and indicates that adolescents suffering from internalizing, externalizing symptoms or lower levels of quality of life could benefit from interventions aimed at enhancing mentalizing capacity.

Plain language summary

Keywords

Mentalizing adolescence externalizing problems internalizing problems quality of life

Introduction

Mental health researchers focus on adolescence since many mental disorders first appear during this period (Merikangas et al., 2009). Psychiatric symptoms in youths are often categorized into the Internalizing (anxiety, depression, somatic complaints) and Externalizing (aggressive behavior, attention problems, hyperactivity) categories (Achenbach, 1966). The presence of psychiatric symptoms alone does not necessarily indicate how an individual is functioning, which may, in some cases, be better indicated by quality of life (Weitkamp et al., 2013). Quality of life is a multidimensional concept that involves not only objective indicators such as living conditions, employment, and education but also subjective assessments of physical, emotional, and social functioning (Wallander & Koot, 2016).

The capacity to mentalize plays a prominent role in the psychosocial adaptation of adolescents (Clarke et al., 2020). Mentalizing or reflective function refers to “the mental process by which an individual implicitly and explicitly interprets the actions of himself and others as meaningful based on intentional mental states such as personal desires, needs, feelings, beliefs, and reasons” (Bateman & Fonagy, 2004, p. 21). Several studies have demonstrated significant structural and functional changes in adolescents' brains related to their mentalizing abilities (Blakemore, 2008). During adolescence, there is a shift in the attachment hierarchy as peers' influence increases (Blakemore, 2008). In peer interactions, individuals have the opportunity to engage in more relational exchanges and consider a greater number of perspectives, which require mentalizing abilities (Jewell et al., 2016). Thus, neural development and social experiences are intertwined in a transactional manner. Research suggests that the ability to infer others' mental states improves from early to late adolescence, consistent with the observation that mental state information becomes increasingly relevant to adolescent minds (Dumontheil et al., 2010). In addition to age, gender also plays a role, with females having an advantage when it comes to mentalizing (Poznyak et al., 2019). Previous studies also linked socioeconomic status (SES) to mentalizing abilities, as during the processing of angry facial expressions, adolescents from low SES backgrounds showed greater neural activity in the mentalizing network and the amygdala (Muscatell et al., 2012).

Previous research has primarily focused on the relationship between mentalizing and specific mental disorders (Sloover et al., 2022), with only a few studies examining the relationship between mentalizing and global measures of mental health in the context of adolescent psychopathology (Ballespí et al., 2018, 2021). Viewing mentalizing in a global context rather than in relation to specific disorders can be beneficial for several reasons. Firstly, Mentalization-Based Treatment (MBT) was initially developed to treat borderline personality disorder; however, its adaptations have shown efficacy in treating various mental disorders across different settings (Bateman & Fonagy, 2004). Secondly, considering mental disorders as categorical conditions overlooks the high rates of comorbidities (Merikangas et al., 2009). In response to that, psychiatric disorders were initially explained by three higher-order factors (Internalizing, Externalizing, and Thought Disorders) but explained even better with one General Psychopathology dimension (the p factor), and transdiagnostic approaches are recommended (Caspi et al., 2014). Mentalizing has been proposed as a transdiagnostic factor (Ballespí et al., 2018), and it is a key component of many empirically validated treatments (Bateman & Fonagy, 2004). Ballespí et al. (2018, 2021) examined the relationship between mentalizing and mental health from a transdiagnostic perspective and found that mentalizing capacity was not associated with internalizing and externalizing symptoms. However, mentalizing showed robust positive associations with global measures of mental health e.g. happiness, and self-esteem. The authors noted the need for replication using self-reports of psychopathology in adolescents.

Fonagy et al. (2016) developed The Reflective Functioning Questionnaire (RFQ) to measure adult mentalizing capacity, which consists of 46 items. The questionnaire includes two scales, Scale A and Scale B. The items on Scale B are polar-scored, with higher scores indicating a higher level of reflective function, e.g. „I believe that people can see a situation very differently based on their own beliefs and experiences” (1 = strongly disagree – 6 = strongly agree). Scale A is a median scale, with more genuine reflective functions toward the scale’s midpoint, while extremely low or high scores reflect a low reflective function (strongly agree and strongly disagree = 2, disagree and agree = 4, disagree somewhat and agree somewhat = 6). This scale indicates that some uncertainty is healthy in mentalizing while being overly confident or having little confidence are both mentalizing difficulties, e.g. „People’s thoughts are a secret to me”. Perkins (2009) conducted an exploratory factor analysis on the adult RFQ, identifying two conceptually coherent factors: Internal-self (e.g. “I often get confused about what I am feeling”) and Internal-other (e.g. “I usually know exactly what other people are thinking”). The measure was named RFQ-15, consisting of 11 items for Internal-self (Cronbach’s alpha = .75) and four items for Internal-other (Cronbach’s alpha = .63). Further studies with the adult RFQ resulted in an eight-item questionnaire, RFQ-8 (Cronbach’s alpha = .54 - .78), with two subscales: Certainty (RFQ_C, a reversed scored item: „I don’t always know why I do what I do”) and Uncertainty (RFQ_U, e.g. “Sometimes I do things without really knowing why”), which was also replicated in adolescent sample (Badoud et al., 2015).

However, concerns were raised about the RFQ-8: the RFQ may assess a single latent dimension of hypomentalizing, but it is unlikely to be able to identify maladaptive forms of hypermentalizing (Müller et al., 2022). Additionally, some of the RFQ items refer to emotional lability and impulsivity rather than mentalization. As a result of these concerns, Horváth et al. (2023) removed one item of the RFQ-8 and suggested using Likert-type items instead of median scoring to create RFQ-R-7 (McDonald’s ω = .92), which measures hypomentalization, e.g. “People’s thoughts are a mystery to me” (1 = strongly disagree – 7 = strongly agree). Sharp et al. (2009) created the Reflective Function Questionnaire for Youth (RFQY) by rephrasing the RFQ items. Sharp et al. (2021) conducted item response theory analyses to refine RFQY Scale B from a non-clinical sample of adolescents, resulting in a shortened version called RFQY-5 (Cronbach’s alpha = .75).

Overview of the current study

This study aimed to translate the Reflective Function Questionnaire for Youth into Hungarian and present its psychometric properties. In light of the lack of research using exploratory methods regarding the latent structure of the RFQY, exploratory factor analysis was used in this study to determine the best solution. We also aimed to assess the relationship between mentalizing, demographic characteristics (including age, gender, and other variables related to the adolescent’s SES, since these variables have been associated with mentalizing (Dumontheil et al., 2010; Muscatell et al., 2012; Poznyak et al., 2019), psychopathology and quality of life. To our knowledge, quality of life has not been studied in relation to mentalizing capacity among adolescents. However, mentalizing showed robust positive associations with social and role functioning, happiness, self-esteem, resiliency, and transcendence (Ballespí et al., 2018, 2021) so we hypothesized that higher levels of mentalizing would be associated with improved quality of life. We also expected that higher levels of mentalizing are related to lower levels of psychopathology, as much previous research found mentalizing difficulties in specific mental disorders (Sloover et al., 2022).

Methods

Participants

We recruited the sample from schools in different regions of Hungary to reach participants from diverse socioeconomic backgrounds (Table 1). We used convenience sampling as university students carried the questionnaire packets to the schools. This study included a community sample of 384 adolescents between the ages of 12 and 18 years (M = 15.83 years, SD = 1.58); 72.7% of them were females (n = 279), while 105 were males (Table 1). The participant’s location of residence generalizes to the general population of Hungary, as the majority of the children lived in towns (52.3%). In contrast, the adolescent’s current education and the parents’ education levels were less diverse in the current sample, as most of the children participating attended grammar schools 66.2%, as less than 5% of the parents had a low level of education (≤8 years). We aimed to collect data from a minimum of 200 participants to reach the minimum sample size for many factor analytic studies (Kyriazos, 2018). Comrey and Lee (1992) also provided the following guidance in determining the adequacy of sample size for factor analysis: 100 = poor, 200 = fair, and 300 = good.

Table 1.

Demographic Characteristics (N = 384).

Demographics	n (%)
Current education of the adolescent
Grammar-school	254 (66.1)
Secondary technical school	70 (18.2)
Vocational school	9 (2.3)
Primary school	50 (13)
Not receiving education	1 (0.3)
Location of residence
Capital city	98 (25.5)
Town	201 (52.3)
Countryside	85 (22.1)
Education level of the mother
High level (university degree)	234 (60.9)
Medium level (12 years)	134 (34.9)
Low level of education (≤8 years)	16 (4.2)
Education level of the father
High level (university degree)	208 (54.2)
Medium level (12 years)	162 (42.2)
Low level of education (≤8 years)	14 (3.6)

Measures

Two independent authors translated the Reflective Function Questionnaire for Youth into Hungarian, following the guidelines by van Widenfelt et al. (2005). We involved a 12-year-old adolescent in the translation process, asking for his feedback about the wording of the items. An independent psychologist back-translated the final version of the Hungarian RFQY into English. We sent the back-translated English version of the RFQY to the original authors, and they did not suggest any changes. Further characteristics of the scale are described in the Introduction.

We assessed the adolescents' quality of life with the Hungarian self-reported version of the Invertar zur Erfassung der Lebensqualität Kindern und Jugendlichen (ILK; Mattejat et al., 1998). A higher score means a better quality of life, and a lower one reflects worse. Kiss et al. (2007) reported good psychometric properties of the Hungarian version of the ILK (Cronbach’s α = .73). In our study, the ILK had good internal consistency (Cronbach’s α = .77).

The Strengths and Difficulties Questionnaire (SDQ, Goodman et al., 2010) is a brief screening tool for internalizing and externalizing problems. Turi et al. (2013) reported acceptable psychometric properties of the Hungarian version. In the current sample, Cronbach’s alpha of the internalizing problems subscale was .71, while .70 was for the externalizing symptoms subscale.

Statistical analysis

We analyzed data using IBM SPSS 20 (IBM Corp. Released, 2011). We conducted an exploratory factor analysis on the RFQY items following the guidelines of Field (2013). We used the Principal Axis Factoring method with direct oblimin rotation. We assessed correlations among the items, and there was no multicollinearity (r > 0.9) and suppressed factor loading less than 0.3. We considered crossloadings between factors high by the ratio of loadings being greater than 75%. We aimed to find factors with at least three non-cross-loading items and stable loading scores. We also expected the determinant of the correlation matrix to be greater than 0.00001. Parallel analysis with 500 replications was used to determine the number of factors (Hayton et al., 2004). Next, we assessed the relationship between the scales and the demographic characteristics. Subgroups with very low case numbers were merged into new categories. We used parametric tests since the skewness and kurtosis were between ±1 in each case (Bulmer, 1979). The significance level was set at an alpha level of .05, using Bonferroni correction for multiple comparisons.

Procedure

We conducted the research according to the 1964 Helsinki Declaration. We obtained approval from the Research Ethics Committee at the relevant university (reference Nr: 2021/185) and informed the participants about anonymity and confidentiality, and they gave written consent. In the case of underage participants (under 18 years in Hungary), the guardians also gave their written permission. We offered no compensation for the participation. A paper questionnaire packet was completed.

Results

Factor analytic results

The assumptions of factor analysis were met. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy was 0.858 indicating adequate sampling. Bartlett’s Test of Sphericity was significant, χ²(1035, N = 384) = 5281.637, p < .001, so our data set was worthy of factor analysis. The EFA resulted in 13 factors with eigenvalues above one. However, parallel analysis indicated that the four-factor solution fits the current sample the best (Meigenvalues = 1.74, 1.65, 1.60, 0.55; 95% percentile eigenvalues: 1.82, 1.71, 1.65, 1.60). In the next step, an EFA with fixed four factors was conducted. Items with small communalities (<0.02; e.g. „My picture of my parents changes as I change.”) were removed in each step and the EFA resulted in four factors (Table 2). In the final model, the eigenvalues of the four factors were 6.30, 3.59, 2.50, 1.63, respectively, the explained variance was 21.01%, 11.95%, 8.34%, 5.43%, and a total of 46.73%. The first two factors correspond to Perkins’ (2009) Internal-self and Internal-other factors. Our third factor was named Self-other since these items capture the awareness of how one’s behaviour impacts others and how others’ behaviour affects one’s mental states. Strong emotions is the fourth factor, indicating that mentalizing difficulties are associated with strong emotions.

Table 2.

The final factor structure of the Hungarian version of the Reflective Function Questionnaire for Youth (N = 384).

					Factor
	M	SD	Corrected item-total correlation	Cronbach’s α if item Deleted	Internal-self	Internal-other	Self-other	Strong emotions
10. I Often get confused about what I am feeling	3.74	1.51	.67	.78	0.83
8. I Always know what I feel	3.95	1.43	.58	.79	−0.58
17. I don’t always know why I do what I do	3.34	1.47	.58	.79	0.54
36. Sometimes I do things without really knowing why	3.44	1.44	.58	.79	0.51			−0.36
32. I Frequently feel that my mind is empty	3.09	1.57	.49	.80	0.48
23. Those close to me often seem to find it difficult to understand why I do things	3.70	1.56	.49	.80	0.47
18. I Pay attention to my feelings	2.95	1.23	.43	.81	−0.44
13. I Get confused when people talk about their feelings	2.37	1.28	.42	.81	0.44
28. I Trust my feelings	2.99	1.24	.35	.81	−0.41
25. I Usually know exactly what other people are thinking	3.30	1.20	.68	.77		0.79
16. I Am a good mind reader	3.65	1.23	.67	.77		0.75
40. I Can mostly predict what someone else will do	3.44	1.18	.55	.79		0.65
37. I Can tell how someone is feeling by looking at their eyes	3.71	1.31	.57	.79		0.63
30. My feelings about a person is hardly ever wrong	3.72	1.24	.52	.80		0.59
46. I Know exactly what my close friends are thinking	4.04	1.19	.53	.79		0.54
1. People’s thoughts are a secret to me	3.74	1.25	.40	.82		−0.38
45. I Pay attention to the impact of my actions on others’ feelings	4.33	1.13	.51	.60			0.61
20. Understanding the reasons for people’s actions helps me to forgive them	4.69	1.06	.45	.61			0.60
19. In an argument, I keep the other person’s point of view in mind	4.28	1.21	.40	.62			0.47
7. I Often have to force people to do what I want them to do	4.80	1.16	.34	.64			−0.43
14. I Believe other people are too confusing to bother figuring out	4.71	1.20	.37	.63			−0.40
41. I’m often curious about the meaning behind others’ actions	4.82	1.04	.28	.65			0.38
2. I Worry a lot about what people are thinking and feeling	4.03	1.37	.19	.68			0.37
15. I Find it difficult to see other people’s points of view	4.64	1.16	.35	.63			−0.36
29. When I get angry, I say things that I later regret	4.33	1.35	.62	.75				−0.87
22. When I get angry, I say things without really knowing why I am saying them	4.08	1.46	.69	.73				−0.87
38. Sometimes I find myself saying things and I have no idea why I said them	3.42	1.48	.56	.76				−0.49
27. Strong feelings often cloud my thinking	3.71	1.44	.51	.77				−0.45
35. If I feel unsure of myself, I can behave in ways that offend others	3.38	1.51	.52	.77				−0.44
44. How I feel can easily affect how I understand someone else’s behavior	4.03	1.28	.40	.80				−0.31

Despite the fact that item 36 cross-loaded on two factors, the ratio of the loadings was less than 75%, the communality was 0.54, and by omitting this item Cronbach’s alpha coefficient would have been decreased, thus it was decided to keep it (Table 2). The Cronbach’s alpha coefficients of the scales were .81, .82, .67 and .80, respectively. The factor correlations were low (Table 3). For easier interpretation, for the following analysis, we scored the items so that higher scores on the Internal-Self, Internal-other and Self-other factors indicate higher interest and certainty, while higher scores on the Strong emotions reflect greater difficulties. Plus, Horváth et al. (2023) also noted that using Likert-type items instead of median scoring is more appropriate in the case of the RFQ.

Table 3.

Factor correlations (N = 384).

Factor	1	2	3	4
1. Internal-self	—
2. Internal-other	.25	—
3. Self-other	.18	.15	—
4. Strong emotions	.40	.03	.02	—

The bivariate relationships

The Internal-self subscale of the RFQY showed a weak positive association with the Internal-other subscale and with the Self-other subscale and was moderately negatively associated with Strong emotions, internalizing and externalizing symptoms (Table 4). The association between the Internal-self subscale and quality of life was positive and moderate in strength. Furthermore, the Internal-other subscale was weakly associated with the Self-other, internalizing symptoms and quality of life. The Self-other scale and quality of life had a positive relationship with the Internal-Other subscale, while internalizing symptoms were negatively related to the Internal-Other subscale. The Self-other subscale was also weakly, and moderately related to the externalizing symptoms, while the Strong emotions was weakly associated with internalizing symptoms and quality of life, and moderately related to externalizing symptoms. The association with both types of symptoms was positive, while it was negative in the case of the quality of life.

Table 4.

Descriptive Statistics and Bivariate Relationships (Pearson’s Correlation Coefficients) of Study Variables (N = 384).

	M	SD	Skewness	Kurtosis	α	1	2	3	4	5	6
1. Internal-self	3.71	0.75	−0.17	−0.23	.81	—
2. Internal-other	3.66	0.85	0.07	−0.25	.82	.23*	—
3. Self-other	4.54	0.64	−0.54	0.23	.67	.29*	.17*	—
4. Strong emotions	3.82	1	−0.30	−0.38	.80	−.51*	−.11	−.13	—
5. SDQ internalizing	7.26	3.75	0.28	−0.58	.71	−.43*	−.14*	−.03	.22*	—
6. SDQ externalizing	7.22	3.39	0.33	−0.44	.70	−.46*	−.01	−.38*	.40*	.25*	—
7. Quality of life	20.2	4.33	−0.50	−0.15	.77	.50*	.17*	.13	−.24*	−.67*	−.38*

Note. SDQ The Strengths and Difficulties Questionnaire, Quality of life the Erfassung der Lebensqualitat Kindern und Jugendlichen total score.

*p < .007 (α = .05/7, using Bonferroni correction).

Associations with the demographic variables

We found significant gender differences in the Self-other subscale, t(382) = −2.98, p = .003. The effect size was small, Cohen’s d = −.34. Girls had significantly higher scores on the Self-other subscale (M = 4.60, SD = 0.61) than boys (M = 4.38, SD = 0.68). The other demographic characteristics were unrelated to the RFQY subscales.

Discussion

This study aimed to translate the Reflective Function Questionnaire for Youth into Hungarian and present its psychometric properties. We also aimed to assess the relationship between mentalizing, demographic characteristics, psychopathology and quality of life, with the latter association being of particular interest as we are not aware of other studies that have examined this relationship among adolescents. The exploratory factor analysis resulted in four factors: Internal-self, Internal-other, Self-other and Strong emotions, which showed adequate psychometric properties with stable factor loadings and acceptable Cronbach’s alpha coefficients. The first two factors correspond to Perkins’ (2009) Internal-self and Internal-other factors, the third factor captures the awareness of how one’s behaviour impacts others and how others' behaviour affects one’s mental states. The fourth factor is Strong emotions, which comes as no surprise, as the literature indicates strong associations between emotion regulation and mentalizing skills (Schwarzer et al., 2021). Overall, most previous research supported the two-factor (Certainty and Uncertainty) solution of the RFQ (Fonagy et al., 2016), however, the new Hungarian RFQY captures the certainty and interest in the self-other dimensions of mentalizing per scale, therefore a more complex measurement of mentalizing is possible.

We expected that higher levels of mentalizing would be associated with improved quality of life, since in previous pieces of research mentalizing showed robust positive associations with social and role functioning, happiness, self-esteem, resiliency, and transcendence (Ballespí et al., 2018, 2021). Quality of life was positively associated with the Internal-self and the Internal-other subscales, which is in agreement with the studies by Ballespí et al. (2018, 2021). The Strong emotions subscale was also negatively related to the adolescents’ quality of life. The relationship between quality of life and Strong emotions is also in line with prior studies, which indicated a strong relationship between emotion regulation and quality of life (Chervonsky & Hunt, 2019). The Internal-self’s relationship with quality of life evidenced the largest effect size, while the Internal-other’ association had the smallest effect size. However, the Self-other mentalizing was unrelated to quality of life. It is worth noting that the majority of the ILK items relate to aspects of quality of life that are independent of others, such as being alone, physical health, and educational achievement, whereas only two items relate to quality of life within relationships, such as relationships with peers and family members.

Previous research regarding the associations between psychopathology and mentalizing is controversial. Ballespí et al. (2018, 2021) found no significant association between the Self-other mentalizing polarities and proxy-reported internalizing or externalizing symptoms of adolescents, while many pieces of research indicated that specific mental disorders symptoms are related to mentalizing difficulties (Sloover et al., 2022). Our results are in line with previous research, which indicated that internalizing problems are related to both self-mentalizing (Ballespí et al., 2022) and other-mentalizing (Ballespí et al., 2018) difficulties. Chevalier et al.’s metanalysis (Chevalier et al., 2023) showed that mentalizing assessed in a relational context is unrelated to internalizing problems. In line with this result, we also found that the Self-other mentalizing subscale, reflecting the relationship between an individual’s internal mental state and that of others, was unrelated to internalizing symptoms.

Furthermore, our results regarding externalizing symptoms are also in agreement with previous research, as youth with externalizing disorders have difficulties identifying their own emotions (Roberton et al., 2012). In line with this, we found a negative relationship between Internal-self mentalizing and externalizing symptoms. Furthermore, we also identified a negative relationship between the Self-other mentalizing and externalizing symptoms, which also comes as no surprise, as externalizing symptoms primarily affect the individual’s connection to others (Achenbach, 1966).

Both externalizing and internalising symptoms were related to the Strong emotions scale, which is in line with the strong association between psychiatric symptoms and emotional regulation difficulties (Schäfer et al., 2017). Similar to the study conducted by Bizzi et al. (2019), the effect sizes between psychopathology and mentalizing were larger in the case of externalizing symptoms than in the case of internalizing symptoms.

We also found a significant gender difference in the Self-other subscale, as girls had significantly higher scores than boys. The Self-other subscale consists of items measuring perspective taking e.g. „In an argument, I keep the other person’s point of view in mind.” and empathic understanding „I pay attention to the impact of my actions on others’ feelings”. The results of our study are similar to previous research since females often score higher on tests of empathy, perspective-taking and social sensitivity than males (Rueckert & Naybar, 2008). Furthermore, men are more likely to suffer from psychiatric disorders such as autism spectrum disorder, conduct disorder, and antisocial personality disorder, which are characterized by a lack of empathy and perspective-taking (Chakrabarti & Baron-Cohen, 2006). In the study by Van der Graaff et al. (2014), adolescent girls also demonstrated higher levels of empathic concern than boys, and while girls' empathic concern remained stable throughout adolescence, boys' empathic concern decreased from early to middle adolescence with a rebound to the initial level thereafter. Additionally, a gender difference in perspective-taking also emerged during adolescence, with girls' increases being steeper than boys'.

The current study has several limitations that should be acknowledged. Firstly, its cross-sectional design limits the ability to establish causal relationships. Future longitudinal studies are needed to provide more robust conclusions about the relationships examined. Secondly, the use of self-report measures introduces potential biases, including the influence of contextual factors, memory, and socially desirable responses. Additionally, the limitations of the RFQ should be considered. Firstly, filling out a self-report measure assumes a certain level of reflective capacity, which may not be uniform across all participants. Incorporating alternative measures, such as observational measures, other informant measures, experimental measures, and qualitative research designs, could be useful. Furthermore, since the original RFQ was initially developed for adults, the process of adapting it for adolescents might not fully account for developmental differences. The information that parents and teachers provide besides the self-report measures might also play a critical role, so using multi-informant methods could provide more reliable information about the complex relationships between the measured constructs. Further research is required to replicate our findings in clinical samples.

Despite these limitations, our study provides the first psychometric support for the Hungarian version of the RFQY.

According to previous studies, MBT has been shown to be effective in improving the quality of life of adolescents suffering from severe personality disorders by reducing symptom severity and improving personality functioning (Laurenssen et al., 2014). Our preliminary results regarding the correlation between the RFQY and global mental health measures indicate that MBT could be beneficial to a community sample of adolescents with internalizing, externalizing symptoms or lower quality of life. Through MBT (Bateman & Fonagy, 2004), one gains a greater understanding of one’s own mental state, thus increasing the ability to self-mentalize. Apart from self-mentalization, other mentalization also improves, as the interest in others' mental states grows, while the level of certainty in others' mental becomes more genuine (Fonagy et al., 2016). By improving and integrating self, other, and self-other mentalizing into a coherent process, effective mentalizing protects against metacognitive disorganization as well as improves emotion regulation that contributes to more stable self-experiences, improved social cognitive functioning and communication.

Footnotes

Author contributions

Brigitta Szabó corresponded to the introduction. Brigitta Szabó, Márton Boda and Laura Losonczy collected the data. Brigitta Szabó, Mónika Miklósi, Carla Sharp and Judit Futó contributed equally to the statistical analysis. Brigitta Szabó, Mónika Miklósi and Judit Futó corresponded to the discussion part of the article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Ethical statement

ORCID iD

Brigitta Szabo

Data availability Statement

The dataset generated during and/or analyzed during the current study is available upon reasonable request from the corresponding author.*

Author biographies

Brigitta Szabó, PhD student in the Eötvös Loránd University, Budapest, Hungary.

Carla Sharp PhD, clinical psychologist. Professor in the Clinical Psychology Doctoral Program and Associate Dean for Faculty and Research at the University of Houston.

Judit Futó PhD, clinical psychologist and neuropsychologist. Researcher in Eötvös Loránd University, Budapest, Hungary.

Márton Boda, psychologist. Outpatient setting in Hungary.

Laura Losonczy, psychology student at Eötvös Loránd University, Budapest, Hungary.

Mónika Miklósi PhD, clinical psychologist, certified CBT and Schema therapist, assistant professor at Eötvös Loránd University, Budapest, Hungary.

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