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Validation of the english version of the Multidimensional Mentalizing Questionnaire (MMQ)



Mentalizing refers to the ability to understand one’s own and others’ mental states. Mentalizing is considered a key component of social cognition and healthy personality development. A multinational assessment tools able to appraise the multidimensional and multifaceted aspects of this complex construct are needed.


The present study had two aims: (a) validate an English version of the Multidimensional Mentalizing Questionnaire (MMQ, 33 items) which was designed to assess mentalizing based on an integrated and multilevel model of mentalizing; (b) explore the correlational relationships between the six dimensions of the MMQ and a set of sociodemographic, psycho-cognitive, mental health, and socio-functional variables.


Overall, 1823 individuals (age: 19–76 years old [M = 45; SD = 16]; sex: male = 48.51%, female = 50.57%, non-binary = 0.9%) participated in an online survey. While the participants came from 77 different countries, most of them were residents in UK and USA (95%). Data analytics include confirmatory factorial analysis and Pearson correlations.


The CFA results validated the factorial structure of a 28-items MMQ-English version, with acceptable goodness of fit indices. Regarding the psychometric properties, the MMQ-English version showed good internal reliability and significant positive correlation with another scale designed to assess an analogue construct showing a fair convergent validity. The findings indicated that males, individuals with lower levels of education, lower socio-economic status, depressed, and with a higher score of loneliness are significantly more likely to report poor mentalizing compared with females, individuals with higher education level, greater SES, happier, and with lower scores of loneliness.


The present study validated the English version of the MMQ.

Peer Review reports


Mentalizing (also known as mentalization) is “the ability to understand one’s own and others’ mental states, thereby comprehending one’s own and others’ intentions and affects” [1, p.1]. In other words, this ability or mental activity allows a person to interpret the behaviors of others or their own by referring to the mental states (beliefs, feelings, wishes, thoughts, etc.) which could be at the origin of these behaviors [2]. Mentalizing is related to, but distinct from, theory of mind. In fact, both concepts describe metacognitive processes [3]. However, mentalizing mainly concerns the reflection of cognitive and affective mental states in the context of emotional arousal [3, 4]. In contrast, “theory of mind focuses more specifically on epistemic states such as beliefs, intentions, and persuasions.” [3, p.730].

Mentalizing in human cognition, behavior, and health

Mentalizing is considered a key component of social cognition and healthy personality development, playing a significant role in people’s ability to communicate, interpersonal functioning and entertaining relationships, as well as for feeling and expressing empathy, regulating their emotions, impulse control, reflective functioning, and experiencing well-being [2, 5, 6].

Particularly, mentalizing deficiency has been found to be associated with poor mental health [5] and psychopathologies states such as borderline personality disorder (BPD [7, 8]. These findings have led to the development of mentalizing-based therapies (MBT [9, 10]) and mentalizing-based educational interventions (MBEI [11, 12]).

Development of mentalizing measurement instruments

Following the theorization of reflective functioning in the concept of mentalizing in the 1990s, researchers have begun to develop measurement tools [13]. Task-based (e.g., the Affect Task [AT] [13]) and narrative-based (e.g., the Mentalizing Stories for Adolescents [MSA] [14]) mentalizing assessment instruments were specifically developed to be used among children and young adolescents. Interview-based and clinical-report mentalizing screening tools (e.g., Reflective Functioning Scale [RFS] [15] and the Metacognition Assessment Scale [MAS] [16]) were designed to be used among older adolescents (16 + years-old) and adults.

The RFS is a unidimensional screening tool. It assesses individual differences in the ability to mentalize attachment relationships using transcripts of interviews (Adult Attachment Interview). A mentalizing global score is attributed by trained interview codifiers and interpreters on an 11-point scale ranging from anti-reflective to exceptionally reflective [15]. Also based on clinical interviews (Metacognitive Assessment Interview), the MAS overcomes the one-dimensionality problems of the RFS by differentiating metacognitive processes into three dimensions: understanding one’s own mind, understanding others’ minds, and mastery [16]. The first two factors are related to the capacity to reflect upon the self and others’ mental states, while the third factor represents the ability to regulate and control mental states [16]. Albeit highly reliable, the RFS and MAS require time-consuming session transcripts or interviews for assessment and lengthy training to use them correctly [13]. These disadvantages restrict their applicability in large-scale studies involving a relatively large sample of patients, thus limiting their use to highly specialized research and clinical contexts [13].

Mentalizing screening instruments based on self-report measures have been developed to overcome the limitations of tools based on interviews. That is the case of the Reflective Functioning Questionnaire (RFQ [17]) and the Mentalization Questionnaire (MZQ [18]). The RFQ is unidimensional and brief screening measure of reflective functioning, specifically designed to assess severe impairments/imbalances in mentalizing as typically observed in patients presenting features of borderline personality disorder [17]. That is, the RFQ is not suitable to be used among general population, since was not designed to capture the different dimensions of mentalizing, nor to assess the process of mentalizing as it unfolds in social interactions [17].

The MZQ [18] is a multidimensional 15-item self-report measure assessing four dimensions: (a) refusing self-reflection (avoidance of thinking about inner states or a systematic rejection of one’s own feelings combined with the fear of being overwhelmed by them); (b) emotional awareness (lack of perceiving and differentiating one’s own inner states); (c) the psychic equivalence mode (the pre-mentalizing modality of thought in which inner mental states and outer reality are equated and everything appears real, related to an unstable inner representation of relations and a lack of flexibility); and (d) the regulation of affect (the inability to modulate affect, that can produce feelings of helplessness and make people feel threatened by their own feelings). Finally, the Mentalization Imbalances Scale (MIS [19]) is a much more recent clinical-oriented, and multidimensional assessment measure of mentalizing. It has six factors representing different imbalances of mentalizing: cognitive, affective, automatic, external, imbalance toward others, and imbalance toward self.

The five (RFS, MAS, RFQ, MZQ, and MIS [15,16,17,18,19]) mentalizing assessment tools presented above were designed mainly as clinical screening tools to be used among patients with psychopathological states. In the last years, attempts to develop instruments designed to assess the transdiagnostic and continuum components of mentalizing both among a general and clinical population were made. The Mentalization Scale (MentS [20]) assesses mentalizing capacity in three dimensions: self-related mentalization (MentS-S), other-related mentalization (MentS-O), and motivation to mentalize (MentS-M). The Interactive Mentalizing Questionnaire (IMQ [21]) is a 20-item, self-report instrument developed to measure “second order mentalization”, associated with people’s beliefs about how transparent their thoughts are to others, or whether this capacity plays a significant role in social interaction/functioning.

The review above shows that, currently, there is several self-reported instruments designed to assess multiple dimensions of mentalizing. Still, many researchers and clinical practitioners [22,23,24,25] continue to express dissatisfaction with the existing self-report instruments, wondering: (a) What do day exactly assess? Do they measure mentalizing ability or a belief about one’s mentalizing abilities? (b) Do these instruments are able to capture the multifaceted nature of the mentalizing, that is, beyond the multidimensional aspect, its multilevel aspect?

A satisfactory answer to the first set of questions would require the development of a “gold standard” task-based mentalizing assessment tool that could serve as a benchmark measure for a given self-report scale validity. To our knowledge, a consensual “golden standard” task-based assessment tool has not been developed yet. In contrast, Gori et al. [22, 23] developed and validated the Multidimensional Mentalizing Questionnaire (MMQ) among a sample of Italian speaking individuals, in an attempt to respond to this need of an enhanced and versatile framework to assess mentalizing in its multifaceted nature. This instrument has 33 items grouped into six dimensions: reflexivity; ego-strength; relational attunement; relational discomfort; distrust; and emotional dyscontrol. These dimensions can be integrated into a multilevel model of mentalizing (see Fig. 1 in Gori et al. [22, 23]), which comprise two dynamics: (a) in one hand, Good mentalizing (cognitive-affective integration [first level]; internal-external openness [second level]; associated to the flexibility, ego-strength, and relational attunement dimensions [third level]); (b) Bad (poor) mentalizing (cognitive-affective split [first level]; internal-external closure [second level]; associated to relational discomfort, distrust, emotional dyscontrol [third level]).

Fig. 1
figure 1

The CFA path diagram of the first improved model (model-2, 28 items) with the standardized estimates

Confirmatory factor analysis of the questionnaire. The rectangles represent the different items, and the ellipses represent the factors (F1 = reflexivity; F2 = ego-strength; F3 = relational attunement; F4 = relational discomfort; F5 = distrust; F6 = emotional dyscontrol). The values on the arrow linking the six factors between them are the correlations. The values on the arrow linking each of the six factors to the corresponding items are the factors loadings (standardized estimates). The factor loadings indicate how well each item is representative of its unobservable construct (factor). Its values go from 0 to 1. The values on top of each rectangle are the square of the standardized factor loadings; they give the proportion of the explained variance (R2) in each item, which indicates how much of the variance in the item is explained by the unobserved construct. If a standardized factor loading value is greater than 0.70 or explains at least half (0.50 = 50%) of the variance in the item, then the corresponding item is important in explaining the unobserved construct it belongs to. The small rounds are the error terms (measurement errors for each item), and the values on the arrow linking the error terms are the covariances established to improve the model fitting metrics

According to Gori et al. [22, 23], the MMQ showed good psychometric properties such as ability to discriminate between general populations and clinical populations and supports the association between poor mentalizing and psychopathology, underlying the centrality of the mentalizing construct in different forms of psychopathology. Moreover, the six dimensions of the MMQ were significantly correlated with a set of neuro-psychological and socio-functional constructs such as alexithymia (difficulty identifying feelings and distinguishing between feelings and bodily sensations in emotional activation, difficulty in the verbal expression of emotions, externally oriented thinking), impulsiveness (attentional impulsiveness, motor impulsiveness, non-planning impulsiveness), attachment styles (secure attachment, preoccupied attachment, avoidant attachment, unresolved attachment), personality traits (extroversion and agreeableness), and self-esteem. However, this original version of the MMQ [22, 23] was validated in Italian and among a relatively homogenous sample in terms of sex and origin.

The present study purpose

Given the psychometric qualities and the potential utility of the original version of the MMQ [22, 23], the present study had two aims: (a) assess the factor structure and the psychometrics properties of the MMQ-English version among a relatively large sample of multinational participants; (b) explore the correlations between the six dimensions of MMQ and a set of sociodemographic, psycho-cognitive, mental health, and socio-functional variables, namely: (i) the participants’ sociodemographic characteristics, (ii) the participants’ overall score on a theory of mind scale, (iii) the participants score on a happiness-depression scale, and (iiii) the participants score on a loneliness scale.



Overall, 1823 individuals participated in the survey, answering an online questionnaire. The participants were resident in United Kingdom = 1482(77.2%), United States = 342(17.8%), Ireland = 31(1.6%), Australia = 29(1.5%), Sweden = 24(1.3%), New Zealand = 12(0.6%). They had the different nationalities across 27 different European countries = 1466(76.1%), 2 Nord-American countries = 307(16%), 14 Asian countries = 51(2.7%), 8 African countries = 31(2%); 2 Ocean countries = 34(1.8%); 8 Latino-America = 13(0.8%), and 5 Middle east countries = 11(0.8%).

Recruitment and sampling

The recruitment of study participants was conducted anonymously, using the Prolific services [26]. Prolific is private company specialized on research data collection and offering a service that includes a guarantee regarding the quality of the data. They have a “reservoir” of individuals willing to participate on scientific online research surveys. Prolific has been described as possessing some advantages over other similar platforms, including that it is exclusively dedicated to research studies, and its participants are more ethnically and geographically diverse [27]. Following quality checks, we found no missing values and no significant outliers in the data. Thus, there was no need to remove any observation from the datas.

Data collection material

The data was collected via online questionnaire, a task outsourced to Prolific, as explained above. The questionnaire included:

Socio-demographic questions (7 variables)

It included: age, sex (male, female), relationship status (single, in relationship), level of education (measured in terms of years of schooling), and socio-economic status (SES; low, intermediate, high).

The Multidimensional Mentalizing Questionnaire (MMQ [22, 23])

It is a 33-item self-report measure covering different core mentalizing constructs on four different axes: (a) cognitive–affective; (b) self–other; (c) outside–inside; and (d) explicit–implicit. The Likert response scale ranges from 1 (Not at all) to 5 (A great deal).

The Four-Items Mentalising Index (FIMI [28])

It is a self-report measure to assess an individual’s mentalizing (or Theory of Mind) ability, which in this particular case means the ability to understand and infer the cognitions of others, including their perceptions, intentions, and beliefs. Item sample: “I find it easy to put myself in somebody else’s shoes”. Items 1, 3, and 4 are scored on a scale from 1 (Strongly disagree) to 4 (Strongly agree). Item 2 is reverse-scored. Total scores range between 4 and 16. Before data analysis, we reversed-coded the relevant items so that the greater the overall FIMI score the greater the theory of mind abilities. The scale internal consistency (Cronbach’s alpha coefficient [α]) was 0.77.

The Short Depression-Happiness Scale (SDHS [29])

The SDHS includes six items assessing depression (e.g., “I feel dissatisfied with my life”) or happiness (e.g., “I feel happy”). For each item, the response ranges from 1 (Never) to 4 (Often). In the current study, the scoring of the happiness items was reversed to ensure that higher scores indicate depressive mood, and lower scores indicate happiness. The scale’s Cronbach α in the current study was 0.90.

The UCLA 3-item loneliness scale [30]

An example item is: “How often do you feel that you lack companionship?”. Participants are required to respond using a 3-point scale: Hardly ever (1); Some of the time (2); Often (3). The scale’s Cronbach α in the current study was 0.85.


The study was carried out in accordance with the Declaration of Helsinki (World Medical Association [WMA] [31]). Participants gave digital informed consent for their survey contribution. That is, for the participants to be allowed to participate in the anonym online survey, they were required to read a written consent form and sign it electronically by clicking a consent button. Participation was voluntary and restricted to those aged ≥ 18 years. All data was anonymously collected. The ethical approval no. KB 390/2022 was obtained from The Bioethics Committee of the Nicolaus Copernicus University functioning at Collegium Medicum in Bydgoszcz, Poland.

Statistical analyses

First, we conducted a descriptive analysis (range, mean [M], standard deviation [SD], skewness, and kurtosis).

Second, to assess the appropriateness of the data for factorial analyses (assumption of adequacy and sphericity, we applied the Kaiser–Meyer–Olkin test [KMO]) and the Bartlett’s test), respectively.

Third, we conducted confirmatory factor analysis (CFA), applying the maximum likelihood estimation (MLE), to test the dimensionality and construct validity of the MMQ. The MLE has proven to be effective even for categorical variables, such as those obtained from our Likert-type scale data, especially in relatively large samples [32, 33]. To evaluate model fit, we used the indices most recommended by statisticians [34], including the Comparative Fit Index (CFI), the Tucker Lewis fit index (TLI), Standardized Root Mean Square Residual (SRMR), and the Root Mean Square Error of Approximation (RMSEA). According to Goretzko et al. [34] and Hu and Bentler [35], cutoff values for CFI and TLI ≥ 0.95 and ≥ 0.90 indicate respectively good and acceptable fit; a SRMR ≤ 0.08, and a RMSEA ≤ 0.06 indicate good model fit. In addition, we conducted a test of factorial structure invariance between the sample of two countries (UK vs. USA) representing 95% of the total sample.

Fourth, we assessed the internal consistency (reliability) of the factorial structure by computing the Cronbach’s alpha coefficient (α) of each dimension, as well as by calculating the Corrected Item-total Correlation. Cronbach’s alpha and Corrected Item-total Correlation were used as measures of reliability. A α ≥ 0.8 (≥ 0.7) indicating good (acceptable) internal consistency [36, 37]. A good Corrected Item-total Correlation is set at r (correlation coefficient) ≥ 0.30 [36, 37].

Fifth, to test the convergent validity, we conducted correlations analysis between the participants total score on MMQ-English version and the participants total score on the FIMI (assessing theory of mind).

Finally, to estimate the relationships between the six dimensions of the MMQ and the sociodemographic, socio-functional, and psycho-cognitive variables, we run correlations (Pearson) analysis. According to Cohen [38], a value of r = 0.10, 0.30, and 0.50 indicates a small, medium, large effect, respectively.

The analyses were conducted using IBM SPSS statistics software (version 29) and AMOS statistical software (version 26).


Descriptive statistics on the participants sociodemographic variables

The socio-demographic characteristics distribution of the all sample was as follow: Number: 1823; Age: 19–65 years-old (M = 31.66, SD = 6.74); Sex: males = 1155(63.4%), females = 636(34.9%); non-binary = 32(1.8%); Relationship status: single = 900(49.4%), in relation, not married = 567(31.1%), in relation, married = 317(17.4%), divorced = 37(2.0%), widow(er) = 2(0.1%); Socio-economic status: low = 483(26.5%), intermediate = 1265(69.4%), high = 75(4.1%); Ethnicity: White = 79.0%, Asian = 9.4%, Mixed = 4.8%, Other = 2.2%; Educational level (years of schooling): min = 4, max = 27, M = 15.94, SD = 3.08.

Descriptive statistics of the MMQ 33 items

Table 1 displays the descriptives statistics related to the MMQ 33 items.

Table 1 Descriptive statistics of the MMQ (33 initial items grouped into 6 factors) and of the other psychological variables

Confirmatory Factorial Analysis (CFA) on the MMQ data

The assumptions of adequacy (KMO = 0.935) and sphericity (Bartlett’s test (ddl = 120) = 18607.60, p < 0.001) were met [39].

First CFA

The first CFA (model-1) tested the theoretical internal validity structure of the MMQ-English version.

The fit indices of model-1 were as follow: GFI = 0.89; NFI = 0.83; RFI = 0.82; IFI = 0.85; TLI = 0.84, CFI = 0.84; RMSEA = 0.059; SRMR = 0.072. Except for the RMSEA and the SRMR values, all these indices indicate that the model is not good. The standardized regression weights (factor loadings) were between 0.28 and 0.86, being statistically significant (p < 0.001). Particularly, as it can be seen in Table A (Appendix), five items had factor loading below the acceptable criteria (which stands at 0.50) (Hu & Bentler, 1999): Factor 1 - Reflexivity (Item1 = 0.45, Item8 = 0.49, Item31 = 0.48); Factor 5 - Distrust (Item19 = 0.28); Factor 6 - Emotional dyscontrol (Item2 = 0.40).

Second CFA

To improve the model, we deleted the five items with factor loadings below 0.50 and conducted a second CFA (model-2). The improved model (see path diagram in Fig. 1) metrics were as follow: GFI = 0.90; NFI = 0.86; RFI = 0.85; IFI = 0.88; TLI = 0.86; CFI = 0.88; RMSEA = 0.061; SRMR = 0.072. These indices indicate an improvement of the model-2 comparatively to the model-1. The GFI, RMSEA and the SRMR values suggest that the model-2 is not good but acceptable. The IFI and the CFI are very close to the acceptable threshold. In addition, the standardized regression weights (see Fig. 1) were between 0.50 and 0.87, being statistically significant (p < 0.001), which indicates high correlation between the items and their respective factors.

After examining the modification indices, we tried to improve the model-2 by establishing covariances between the standardized errors. This procedure was not successful: the model-2 did not significantly improve.

Country (UK vs. USA) invariance tests

To find out whether the factor structure of the model-2 is invariant to country, a multi-group analysis was carried out from the model-2.

The configural invariance test showed an acceptable fit for the unconstrained model: GFI = 0.90; NFI = 0.87; RFI = 0.85; IFI = 0.89; TLI = 0.86; CFI = 0.90; RMSEA = 0.063; SRMR = 0.068. The metric invariance test indicated that the meaning of the six modeled constructs (factors) did not change across groups (X2 change = 14.23, p = 0.136).

Internal reliability

Table 2 displays the main results of the internal reliability tests conducted for each subscale of the model-2 factorial structure.

Table 2 Reliability Statistics and Item-total Correlation: Model-2 (28 items*)

Indeed, in model-2, the Cronbach’s alpha coefficient shows that all MMQ subscales had acceptable internal reliability (≥ 70). The Corrected Item-total Correlation had r ≥ 0.30.

Regarding the model-1, see the internal reliability results in Appendix, Table B.

Convergent validity

The correlation between the MMQ-English version total score and the FIMI total score (r = 21; p < 0.001; 95% confidence interval = 0.160 − 0.248; alpha level = 0.01) was significant, indicating good convergence of the two instruments.

Correlations between the MMQ subscales

Table 3 displays the result of the bivariate correlations (Person) analysis between the MMQ subscales of the CFA model-2.

Table 3 Correlation matrix of the MMQ dimensions: Model-2 (28 items)

The relationships are statistically significant, except for the Distrust vs. Relation attunement and Relation discomfort vs. Relation attunement. All significant relationships are positive, except for Relational discomfort vs. Ego-strength, Distrust vs. Ego-strength, and Emotional dyscontrol vs. Ego-strength.

See same results regarding model-1 in Appendix, Table C.

Correlation between MMQ factors (model-2) and the sociodemographic, psycho-cognitive, mental health, and socio-functional variables

Table 4 exhibits the correlations coefficients between the MMQ six factors (model-2) and the set of sociodemographic, psycho-cognitive, mental health, and socio-functioning variables.

Table 4 Correlations between the six MMQ factors (model-2, 28 items) and the sociodemographic, psycho-cognitive, and socio-functional variables

Reflexivity (F1[Factor 1]) was significantly and positively correlated with sex, with education level, with SES, and with loneliness; it was negatively correlated with age. Ego-strength (F2) was significantly and positively associated with age, with SES, and with the theory of mind score; it was negatively associated with sex, with happiness-depression, and with loneliness. Relational attunement (F3) was significantly and positively correlated with sex, with education level, and with SES; it was negatively correlated with happiness-depression score. Relational discomfort (F4) was significantly and positively associated with sex, with happiness-depression score, and with loneliness; it was negatively associated with age, with relationship status, with educational level, with SES, and with the theory of mind score. Distrust (F5) was significantly and positively correlated with happiness-depression scores and with loneliness; it was negatively correlated with education level, with SES, and with the theory of mind score. Emotional dyscontrol (F6) was significantly correlated with none of the demographic and psychological variables. Finally, good mentalizing (calculated by averaging F1, F2, and F3) was significantly and positively associated with sex, with education level, with SES, and with the theory of mind score; it was negatively associated with the happiness-depression score, and with loneliness. Poor mentalizing (calculated by averaging F4, F5, and F6) was significantly and positively correlated with sex, with the happiness-depression score, and with loneliness; it was negatively associated with age, education level, with SES, and with the theory of mind score.


The present study aimed at (a) testing the validity of the MMQ-English version factor structure and its psychometric properties, and (b) to explore the relationships between the six dimensions of the MMQ and a set of sociodemographic, psycho-cognitive, mental health, and socio-functional variables.

Factor structure and psychometric properties

The MMQ-English version six factorial structure was validated with acceptable/satisfactory goodness of fit, after applying improvement techniques on the initial CFA model. These improvement techniques required the elimination of three, one, and one items respectively from the Factor (F)1 (reflexivity), F5 (distrust), and F6 (emotional dyscontrol) of the initial factor structure. Thus, the validated English version has a total of 28 items, compared to 33 items in the original MMQ [22, 23] factor structure, validated in the Italian sample. Indeed, comparatively to the original MMQ (see Table 1), the items 1 (“I often try to explain what is happening to me”), the item 8 (“I am able to reflect on my behaviors”), and item 31 (“I am a thoughtful person”) were removed from Factor 1; the item 19 (“For me things are either white or black”) was removed from Factor 2, and the item 2 (“I am an impulsive person”) was removed from Factor 6. Regarding the psychometric properties, the current study findings indicated that: (a) all six factors of the MMQ-English version have acceptable internal reliability (Cronbach alpha [α] ≥ 70; corrected item-total correlation [r] ≥ 0.30); (b) the correlations between all items and their respective dimensions are significant (p < 0.001), and the standardized regression weights between the items and their respective dimensions are above the threshold (≥ 0.50); (c) the correlation between the MMQ-English version total score and the FIMI total score was significant, indicating good convergence between the two instruments. The difference between the MMQ-English version and the original MMQ-Italian version may stem from the differences on the sample used. As mentioned in the introduction, the original MMQ version was validated among a relatively homogenous Italian sample, the large majority of whom were female. Comparatively, the validity of the MMQ-English version was tested on a larger sample (1823 participants), diverse in terms of sex, education level, and country of origin. The sample discrepancies might also explain why the original version [22, 23] showed a relatively better goodness of fit (RMSEA = 0.053; SRMR = 0.067; TLI = 0.90; CFI = 0.90) compared with the indices of the present version (RMSEA = 0.061; SRMR = 0.072; TLI = 0.86; CFI = 0.90). While the structure was invariant across two countries (UK vs. USA) representing 95% of the sample, overall, these findings, when compared to the finding of Gori et al. [22, 23], suggest that MMQ is susceptible to socio-cultural and/or cross-cultural differences and that the factor structure need to be improved in future studies, which must have cross-cultural design.

Good vs. bad mentalizing

As stressed in the introduction section, the integrated and multilevel model of mentalizing proposed in the MMQ articulates the idea of good and bad mentalizing throughout four different axes, corresponding to four polarities: explicit-implicit, outside-inside, self-other, and cognitive-affective [22]. These four axes can be assimilated to the four dimensions of mentalizing in the Fonagy’s model [40], also conceived in terms of duel and opposite aspects: automatic-controlled, internal-external, self-other, and cognitive-affective. The main idea of this model is that good mentalizing requires the ability of using these four polarities dynamically, with flexibility, balancing them appropriately as function of the needs of the circumstances, the situation, and the social environment. This perspective might give insight into the findings of the present study, regarding the correlations among the six MMQ factors, and the correlations between the six factors and the sociodemographic, psycho-cognitive, mental health, and socio-functional variables.

Correlations among the six MMQ mentalizing factors

In this study, in general, the three dimensions associated with good mentalizing (reflexibility, ego-strength, relational attunement) are significantly and negatively associated with the three dimensions associated to bad mentalizing (relational discomfort, distrust emotional dyscontrol). This finding further confirms and validated the model of mentalizing proposed in the MMQ. However, there is some exceptions, among them, relational attunement vs. relational discomfort was not significantly correlated; relational attunement vs. distrust was not significantly correlated neither. Results from the original MMQ version validation [22] showed non-significant correlations between reflexibility vs. emotional dyscontrol and between relational attunement vs. emotional dyscontrol. Considering, for instance, that in the MMQ model of bad and good mentalizing the relational attunement and the relational discomfort are opposite poles, it seems anti-hypothetic (counter-intuitive?) that, in the present study and in the study by Gori et al. [22], they are not significantly and negatively correlated. Nevertheless, the overall differences between the two studies suggest that the referred non-significance is probably a result of the variance within and between the samples, rather than indication of a “defect” concerning the conceptual model itself. In any case, this is an issue warranting further investigation in future studies.

Associations with sociodemographic and psychological variables

Significant associations

As for the correlational relationship between the six dimensions of the validated MMQ-English version (model-2) and the set of sociodemographic and psychological variables, generally, the results of the present study are in line with the previous studies.

For instance, the overall findings of the present study suggest that female were significantly more likely to have good mentalizing than their male counterparts. According to the integrative and multilevel model of mentalizing [22, 23] (see Fig. 1) in which the MMQ is based, good mentalizing is achieved when an individual has high scores on the reflexivity, ego-strength, and relational attunement dimensions, which leads to greater internal-external openness abilities and, eventually, to a better cognitive-effective integration. In line with this particular result, findings from magnetic resonance imaging (MRI)-based study [41] suggested that women may have better neuro-cognitive capabilities for mentalizing than men. Furthermore, some research works [42, 43] have indicated that female have better mentalizing performances than their male counterparts and that this difference can be explained as follows: (a) women are generally more motivated to engage in deeper social relationships and tend to socialize more, better, and in much more diverse contexts than men; (b) women, compared to men, are less limited by language abilities in their efforts to mentalize. Thus, it seems that distinct neuro-psychological attributes/functioning and social skills, resulting from specific patterns of socialization, lead to significant sex differences regarding mentalizing performances.

While some studies [42] have shown that, from childhood to adulthood (7–18 years-old), mentalizing gets better as the age advances, in the current study, the overall findings do not indicate that from 19 to 76 years-old, the age has significant effect on participants’ mentalizing performances. There is indication, however, that the reflexivity dimension decline as age advances. This result can be linked with studies [44] indicating that as people aged, they tend to lose cognitive flexibility, because they tend to be more affected by bias through feedback than young individuals, i.e., as their ability to acquire and updating information decline, older people tend to over-rely on their past experiences, instead of giving more weight to the situational indices.

More educated people are more likely to have good mentalizing than less educated people. Individuals with greater SES are more likely to have good mentalizing than those with lower SES. These findings can be explained by the fact that education improves both general and specific cognitive abilities, and greater SES comes with the opportunity to experience diverse social environments and interpersonal/intergroup relationships as well as to have better, diversified, and longer formal and informal education [45].

People higher on theory of mind abilities tend to be also higher on good mentalizing compared to those with lower theory of mind capacities. This result confirms several previous works demonstrating the significant positive relationship between the scores on mentalizing and theory of mind [3]. In fact, as emphasized in the introduction section, these two concepts are highly related which underlines the fair convergent validity of the MMQ in the current study.

Depressed individuals are more likely to have poor mentalizing as opposed to happier individuals. According to the integrative and multilevel model of mentalizing [22, 23] in which the MMQ is based, poor mentalizing is achieved when an individual has high scores on the relational discomfort, distrust, and emotional dyscontrol dimensions, which leads to greater internal-external closure and, eventually, to cognitive-effective split. This particular result is backed by previous studies [46], which elaborated that depressed mood leads to increases in arousal and stress levels, resulting in impairments and distortions in mentalizing, which in turn may contribute to the development or persistence of depressive symptoms.

Individuals experiencing higher scores on loneliness were more likely to have poor mentalizing compared to people feeling satisfied with their social relationships. Previous studies have found negative correlation between loneliness and mentalizing only in patients suffering from schizophrenia [47]. The present study, conducted on non-clinical population, suggests that this relationship exists also among individuals from the general population. Lonely persons are significantly more affected by anxiety, depression, and impairments in cognition and social functioning [48], which may explain why they have higher probability of having poor mentalizing.

Overall, the findings discussed above highlight the importance of education and mentalizing training to improve mental health and wellbeing among the general population.

Non-significant associations

In the present study, the relationship between reflexivity (MMQ F1) and happiness/depression was no significant. Reflexivity can be defined as “the fact of someone being able to examine their own feelings, reactions, and motives (reasons for acting) and how these influence what they do or think in a situation” [49]. The concept of reflexivity, as define above, is related to the psychological concept of mindfulness, define as “awareness of one’s internal states and surroundings” which “can help people avoid destructive or automatic habits and responses by learning to observe their thoughts, emotions, and other present-moment experiences without judging or reacting to them” [50]. Several studies have shown that mindfulness is connected to positive outcomes related to mental health and well-being and that this association is mediated by the individual purpose in life and behavioral activation [51]. Thus, it would be interesting, in future studies, to further investigate the relationship between reflexivity and happiness/depression by including possible mediators such as the purpose in life or the behavioral activation.

The association between relational attunement (MMQ F3) and loneliness was also no significant. Relational attunement is “a kinesthetic and emotional sensing of others, knowing their rhythm, affect and experience by metaphorically being in their skin” [52]. As the ability to feel what the other person is feeling by entering their inner world, cognitive and emotional attunement is critical in all relationships while being an essential component of friendships and romantic partnerships [52]. Accordingly, previous studies have shown a significant and negative relationship between relational attunement and loneliness [53]. In the current study, it is possible that some unknown factors moderate/mediate this association. Thus, it is an issue that must be investigated thoroughly in future studies.

Finally, based in previous studies [52, 53], it could have been hypothesize an statistical significant association between emotional dyscontrol (MMQ F6), happiness/depression, and loneliness. The finding of the present study indicated, however, that it was not the case; the relationship was not significant. As mention above, one of the best ways to address this “contradiction” in future studies is to design a methodology that includes possible moderators/mediators and/or conduct cluster analyses to group participants into different categories as function of given variables (sociodemographic characteristics, personality traits, social experiences, etc.) and run association analyses between the chosen variables (e.g., emotional dyscontrol and happiness) within each cluster to see what can come out.


The present study involves a cross sectional assessment. Overall, 95% of the participants come from just two countries, the UK and the USA. Furthermore, the sample included is not a representative sample of the population. Further studies may assess mentalizing across different clinical and representative samples within longitudinal design. The study however included a sex-balanced large sample from different countries. Finally, this study does not give a response to the question discussed in the introduction, which can be reformulated here as follow: to what extent MMQ assesses people’s mentalizing abilities (and not only their beliefs about their mentalizing abilities)? As discussed recently by Wendt et al. [25, p. 9–10], to validated a “mindreading” instrument in terms of assessing “abilities” and not just “beliefs about one’s own abilities”, future studies must go behind the classic tests of internal consistency, structural validity, or convergent validity (with another self-reported measurement instrument), and create task-based assessment tool to be used as “gold standard” to validate a given self-report instrument capacity to assess a set of “real” abilities. In this case, a “gold standard” to validated the MMQ capacity to assess “real” mentalizing abilities must contain tasks in line with the functionalist reconceptualization of mentalizing abilities, that is, mentalizing abilities viewed “in terms of its ecological utility in everyday life, such as the ability to achieve favorable outcomes in interpersonal situations” in which mentalizing is required; appropriated tasks must be designed specifically to go behind inference “of mental states from static information to a broader perspective encompassing interpersonal communication” [25, p. 11–12].


The present study allowed the validation of the 28-items MMQ-English version. The current study results indicated that male, less educated, lower SES, depressed, and lonely individuals are significantly more likely to have poor mentalizing compared with female, highly educated, greater SES, happier, non-lonely individuals. Finally, these findings emphasize the need to consider mentalizing as a multifaceted and multilevel psychological construct centrally involved in a variety of human psycho-cognitive expressions, behavior, and mental health conditions.

Data availability

The data used in this study are available at:



Borderline personality disorder


Mentalization-based therapy


Affect Task


Mentalizing Stories for Adolescents


Reflective Functioning Scale


Metacognition Assessment Scale


Adult Attachment Interview


Reflective Functioning Questionnaire


Mentalization Questionnaire


Mentalization Imbalances Scale


Mentalization Scale


Interactive Mentalizing Questionnaire


Multidimensional Mentalizing Questionnaire


Four-Items Mentalisation Index


Short Depression-Happiness Scale

UCLA 3-Item:

University of California Los Angeles Short Form Loneliness Scale


Confirmatory Factorial Analysis


Kaiser–Meyer–Olkin test


Comparative Fit Index


Tucker Lewis Fit Index


Standardized Root Mean Square Residual


Root Mean Square Error of Approximation




Relationship status


Education level


Socio-economic status


Theory of mind score


Happiness-depression score


Loneliness score


  1. American Psychological Association. (APA, 2018). APA Dictionary of Psychology. APA.

  2. Fonagy P, Allison E. What is mentalization? The concept and its foundations in developmental research. In: Midgley N, Vrouva I, editors. Minding the child: Mentalization-based interventions with children, young people and their families. Routledge/Taylor & Francis Group; 2012. pp. 11–34.

  3. Wyl A. Mentalisierung Und Theory of mind [Mentalization and theory of mind]. Prax Kinderpsychol Kinderpsychiatr. 2014;63(9):730–7.

    Article  PubMed  Google Scholar 

  4. Choi-Kain LW, Gunderson JG. Mentalization: ontogeny, assessment, and application in the treatment of borderline personality disorder. Am J Psychiatry. 2008;165(9):1127–35.

    Article  PubMed  Google Scholar 

  5. Ballespí S, Vives J, Sharp C, Chanes L, Barrantes-Vidal N. Self and other mentalizing polarities and dimensions of mental health: Association with types of symptoms, functioning and well-being. Front Psychol. 2021;12.

  6. Cooper B, Anderson JL, Sharp C, et al. Attachment, mentalization, and criterion B of the Alternative DSM-5 Model for Personality disorders (AMPD). BMC Borderline Personal Disord Emot Dysregul. 2021;8:23.

    Article  Google Scholar 

  7. Bateman A, Fonagy P. Mentalization-based treatment for borderline personality disorder: a practical guide. Oxford: Oxford University Press; 2006.

    Book  Google Scholar 

  8. Fonagy P, Luyten P. A developmental, mentalization-based approach to the understanding and treatment of borderline personality disorder. Dev Psychopathol. 2009;21(4):1355–81.

    Article  PubMed  Google Scholar 

  9. Bateman A, Fonagy P. Mentalization based treatment for borderline personality disorder. World Psychiatry. 2010;9(1):11–5.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Bateman A. Cambridge guide to mentalization-based treatment (MBT). Combridge, UK: Cambridge University Press; 2023.

    Book  Google Scholar 

  11. Cerciello F, Ricci MC, Lombardi A. Effects on mentalization through educational intervention using Virtual Reality. Proceedings of the International Day of Persons with Disabilities. Inclusion, Autonomy, Technology, December 2–3, 2022, Rome, Italy.

  12. Schaarsberg REK, Ribberink AZ, Osinga B, et al. Treatment responsivity in adolescents with disruptive behavior problems: co-creation of a virtual reality–based add-on intervention. JMIR Formative Res. 2023;7(1):e46592.

    Article  Google Scholar 

  13. Vrouva I, Target M, Ensink K. Measuring mentalization in children and young people. In: Midgley N, Vrouva I, editors. Minding the child: Mentalization-based interventions with children, young people and their families. Routledge/Taylor & Francis Group; 2012. pp. 54–76.

  14. Vrouva I, Fonagy P. Development of the mentalizing stories for adolescents (MSA). J Am Psychoanal Assoc. 2009;57:1174–9.

    Google Scholar 

  15. Fonagy P, Target M, Steele H, Steele M. (1998). Reflective Functioning Scale (RF) APA PsycTests.

  16. Semerari A, Carcione A, Dimaggio G, et al. How to evaluate metacognitive functioning in psychotherapy? The Metacognition Assessment Scale and its applications. Clin Psychol Psychother. 2003;10(4):238–61.

    Article  Google Scholar 

  17. Fonagy P, Luyten P, Moulton-Perkins A, et al. Development and validation of a self-report measure of mentalizing: the reflective functioning questionnaire. PLoS ONE. 2016;11(7):e0158678.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Hausberg MC, Schulz H, Piegler T, Happach CG, Klöpper M, Brütt AL, Sammet I, Andreas S. Is a self-rated instrument appropriate to assess mentalization in patients with mental disorders? Development and first validation of the mentalization questionnaire (MZQ). Psychother Res. 2012;22(6):699–709.

    Article  PubMed  Google Scholar 

  19. Gagliardini G, Gullo S, Caverzasi E, Boldrini A, Blasi S, Colli A. Assessing mentalization in psychotherapy: first validation of the mentalization imbalances Scale. Res Psychother. 2018;21(3):339.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Dimitrijević A, Hanak N, Altaras Dimitrijević A, Jolić Marjanović Z. (2018). The Mentalization Scale (MentS): A self-report measure for the assessment of mentalizing capacity. J. Pers. Assess. 2018;100(3),268–280.

  21. Wu H, Fung BJ, Mobbs D. Mentalizing uuring social interaction: the development and validation of the interactive Mentalizing Questionnaire. Front Psychol. 2022;17(12):791835.

    Article  Google Scholar 

  22. Gori A, Arcioni A, Topino E, Craparo G, Grotto RL. Development of a new measure for assessing mentalizing: the Multidimensional Mentalizing Questionnaire (MMQ). J Pers Med. 2021;11(4):305.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Gori A, Topino E. Exploring and deepening the facets of mentalizing: the integration of network and factorial analysis approaches to verify the psychometric properties of the multidimensional mentalizing questionnaire (MMQ). Int J Environ Res Public Health. 2023;20:4744.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Olga JM. What’s on your mind? A guide for mentalization assessment in adults. Poznań; 2021.

  25. Wendt LP, Zimmermann J, Spitzer C, Müller S. Mindreading measures misread? A multimethod investigation into the validity of self-report and task-based approaches. Psychol Assess. 2024;36(5):365–78.

    Article  PubMed  Google Scholar 

  26. Pacific.

  27. Peer E, Samat S, Brandimarte L, Acquisti A. Beyond the Turk: alternative platforms for crowdsourcing behavioral research. J Exp Soc Psychol. 2017;70:153–63.

    Article  Google Scholar 

  28. Clutterbuck RA, Callan MJ, Taylor EC, Livingston LA, Shah P. Development and validation of the four-item Mentalising Index. Psychol Assess. 2021;33(7):629–36.

    Article  PubMed  Google Scholar 

  29. Joseph S, Linley PA, Harwood J, Lewis CA, McCollam P. Rapid assessment of well-being: the short depression-happiness scale (SDHS). Psychol Psychother: Theory Res Pract. 2004;77(4):463–78.

    Article  Google Scholar 

  30. Hughes ME, Waite LJ, Hawkley LC, Cacioppo JT. A short scale for measuring loneliness in large surveys: results from two population-based studies. Res Aging. 2004;26(6):655–72.

    Article  PubMed  PubMed Central  Google Scholar 

  31. World Medical Association (WMA) Declaration of Helsinki - Ethical Principles for Medical Research Involving Human Subjects. WMA. 1964.

  32. Asún RA, Rdz-Navarro K, Alvarado JM. Developing multidimensional likert scales using item factor analysis: the case of four-point items. Sociol Methods Res. 2016;45(1):109–33.

    Article  Google Scholar 

  33. Rhemtulla M, Brosseau-Liard PÉ, Savalei V. When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychol Methods. 2012;17(3):354–73.

    Article  PubMed  Google Scholar 

  34. Goretzko D, Siemund K, Sterner P. Evaluating model fit of measurement models in confirmatory factor analysis. Educ Psychol Meas. 2024;84(1):123–44.

    Article  PubMed  Google Scholar 

  35. Hu LT, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1998;6(1):1–55.

    Article  Google Scholar 

  36. Bland JM, Altman DG. Statistic notes: Cronbach’s alpha. BMJ. 1997;314(7080):572.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Zijlmans EAO, Tijmstra J, van der Ark LA, Sijtsma K. Item-score reliability in empirical-data sets and its relationship with other item indices. Educ Psychol Meas. 2018;78(6):998–1020.

    Article  PubMed  Google Scholar 

  38. Cohen J. Statistical Power Analysis for the behavioral sciences. 2nd ed. New York: Routledge; 1988.

    Google Scholar 

  39. Cerny CA, Kaiser HF. A study of a measure of sampling adequacy for factor-analysis correlation matrices. Multivar Behav Res. 1977;12(1):43–7.

    Article  Google Scholar 

  40. Fonagy P, Gergely G, Jurist EL, Target M. Affect regulation, mentalization and the development of the self. New York: Other; 2002.

    Google Scholar 

  41. Krach S, Blümel I, Marjoram D, et al. Are women better mindreaders? Sex differences in neural correlates of mentalizing detected with functional MRI. BMC Neurosci. 2009;10:9.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Poznyak E, Morosan L, Perroud N, Speranza M, Badoud D, Debbané M. Roles of age, gender and psychological difficulties in adolescent mentalizing. J Adolesc. 2019;74:120–9.

    Article  PubMed  Google Scholar 

  43. Rutherford HJV, Wareham JD, Vrouva I, Mayes LC, Fonagy P, Potenza MN. Sex differences moderate the relationship between adolescent language and mentalization. Pers Disord: Theory Res Treat. 2012;3(4):393–405.

    Article  Google Scholar 

  44. Wilson CG, Nusbaum AT, Whitney P, Hinson JM. Age-differences in cognitive flexibility when overcoming a preexisting bias through feedback. J Clin Exp Neuropsychol. 2018;40(6):586–94.

    Article  PubMed  Google Scholar 

  45. American Psychological Association. (APA, 2024). Education and Socioeconomic Status. APA. (Assessed February 06, 2024).

  46. Langenbach BP, Koelkebeck K, Knoch D. Mentalising and depression: a mini-review on behavior, neural substrates, and treatment options. Front Psych. 2023;14.

  47. Okruszek Ł, Jarkiewicz M, Piejka A, Chrustowicz M, Krawczyk M, Schudy A, Harvey PD, Penn DL, Ludwig K, Green MF, Pinkham AE. Loneliness is associated with mentalizing and emotion recognition abilities in schizophrenia, but only in a cluster of patients with social cognitive deficits. J Int Neuropsychol Soc. 2024;30(1):27–34.

    Article  PubMed  Google Scholar 

  48. Finley AJ, Schaefer SM. Affective neuroscience of loneliness: potential mechanisms underlying the Association between Perceived Social isolation, Health, and well-being. J Psychiatr Brain Sci. 2022;7(6):e220011.

    Article  PubMed  PubMed Central  Google Scholar 

  49. The Cambridge Dictionary. Reflexivity. The Cambridge Dictionary. 2024.

  50. American Psychological Association (APA), Mindfulness. APA; 2024.

  51. Crego A, Yela JR, Gómez-Martínez MÁ et al. Relationships between mindfulness, purpose in life, happiness, anxiety, and depression: Testing a mediation model in a sample of women. Int J Environ Res Public Health. 2021; 21;18(3):925.

  52. Erksine RG. Attunement and involvement: therapeutic responses to relational needs. Int J Psychother. 1998;3(3).

  53. Di Tella M, Adenzato M, Castelli L, Ghiggia A, Loneliness. Association with individual differences in socioemotional skills. Pers Individ Differ. 2023;203:111991.

    Article  Google Scholar 

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The authors wish to acknowledge the study participants for their contribution.


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Authors and Affiliations



GVC and YK conceived the study. YK, LR, ML-D and MW-D, GVC conceived the survey and prepared the questionnaires. GVC conducted data analyses. GVC wrote the first draft. All authors read, reviewed and approved the manuscript.

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Correspondence to Germano Vera Cruz or Yasser Khazaal.

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The study was carried out in accordance with the Declaration of Helsinki (World Medical Association [WMA] [31]). Participants gave digital informed consent for their survey contribution. That is, for the participants to be allowed to participate in the anonym online survey, they were required to read a written consent form and sign it electronically by clicking a consent button. Participation was voluntary and restricted to those aged ≥ 18 years. All data was anonymously collected. The ethical approval no. KB 390/2022 was obtained from The Bioethics Committee of the Nicolaus Copernicus University functioning at Collegium Medicum in Bydgoszcz, Poland.

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Vera Cruz, G., Rochat, L., Liberacka-Dwojak, M. et al. Validation of the english version of the Multidimensional Mentalizing Questionnaire (MMQ). BMC Psychol 12, 344 (2024).

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