# The role of demographic variables in the effectiveness of metacognitive training for psychosis: A meta-analysis

Hanna Gelner, Martyna Krężolek, Adrianna Aleksandrowicz, Justyna Piwińska, Maria Lamarca, Fabrice Berna, Vanessa Acuña, Caroline König, Steffen Moritz, Susana Ochoa, et al.

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## ► To cite this version:

Hanna Gelner, Martyna Krężolek, Adrianna Aleksandrowicz, Justyna Piwińska, Maria Lamarca, et al.. The role of demographic variables in the effectiveness of metacognitive training for psychosis: A meta-analysis. Schizophrenia Research, 2025, 283, pp.85-97. 10.1016/j.schres.2025.06.017. inserm-05515141

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# The role of demographic variables in the effectiveness of metacognitive training for psychosis: A meta-analysis

Hanna Gelner<sup>a,1</sup>, Martyna Krężołek<sup>b,1</sup>, Adrianna Aleksandrowicz<sup>a</sup>, Justyna Piwińska<sup>a</sup>, Maria Lamarca<sup>c,d,e,f</sup>, Fabrice Berna<sup>g</sup>, Vanessa Acuña<sup>h,i</sup>, Caroline König<sup>j</sup>, Steffen Moritz<sup>k</sup>, PERMEPSY Group<sup>a,d,g,h,j,k</sup>, Susana Ochoa<sup>d,e,f,2</sup>, Łukasz Gawęda<sup>a,*,2</sup>

## ARTICLE INFO

**Keywords:**

Psychosis
Schizophrenia

**MCT**

Demographic variables

Meta-analysis

## ABSTRACT

**Background:** Meta-cognitive Training (MCT) is a promising therapeutic approach for schizophrenia. However, the extent to which demographic factors influence its efficacy in reducing psychotic symptoms and cognitive biases, as well as enhancing cognitive insight, needs further examination.

**Methods:** A comprehensive search of databases: PubMed, PsycINFO, Scopus, (2007-November 2024) published only in English was conducted. Thirty-seven studies (81 % randomized, 19 % non-randomized trials) were included. Inclusion criteria were participants with a diagnosis of schizophrenia spectrum or related psychotic disorders, and there were no sex, gender, race, or ethnicity restrictions. We analyzed the influence of demographic factors on the efficacy of MCT, and the meta-regression analyses were conducted for variables including sex, age, duration of illness, and years of education.

**Results:** MCT significantly reduced positive symptoms (d = -0.40; *p* < 0.001), delusions (d = -0.41; *p* < 0.001), and improved cognitive insight (d = 0.28; *p* < 0.05). Women benefit more in cognitive insight in self-reflectiveness scale (d = -0.27; *p* = 0.05). However, no statistically significant gender differences were observed in other domains. Furthermore, no significant results were observed for other sociodemographic variables under study.

**Conclusions:** MCT has been demonstrated to be an effective therapeutic method in the reduction of symptoms associated with schizophrenia, with the impact of demographic factors being limited. The enhancement of cognitive insight, particularly in the domains of self-reflectiveness and self-confidence, has been demonstrated in women. Future research should consider individual differences, particularly in the context of gender to advance personalized therapeutic approaches and optimize psychological interventions.

<footnote><sup>a</sup> Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, Poland, Warsaw</footnote>

<footnote><sup>b</sup> II Department of Psychiatry, Medical University of Warsaw, Poland, Warsaw</footnote>

<footnote><sup>c</sup> Departament de Psicologia Clínica i de la Salut, Facultat de Psicologia, Universitat Autònoma de Barcelona, Barcelona, Spain</footnote>

<footnote><sup>d</sup> Parc Sanitari Sant Joan de Déu, Barcelona, Spain</footnote>

<footnote><sup>e</sup> Consorcio de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain</footnote>

<footnote><sup>f</sup> Grup MERITT, Institut de Recerca Sant Joan de Déu, Barcelona, Spain</footnote>

<footnote><sup>g</sup> University of Strasbourg, University Hospital of Strasbourg, Inserm, Strasbourg, France</footnote>

<footnote><sup>h</sup> Department of Psychiatry, School of Medicine, Faculty of Medicine, Universidad de Valparaíso, Valparaíso, Chile</footnote>

<footnote><sup>i</sup> Unidad de Trastornos Psicóticos, Hospital Del Salvador de Valparaíso, Chile</footnote>

<footnote><sup>j</sup> Soft Computing Research Group at Intelligent Data Science and Artificial Intelligence Research Center Universitat Politècnica de Catalunya, Barcelona, Spain</footnote>

<footnote><sup>k</sup> Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany</footnote>

<footnote>* Corresponding author at: Experimental Psychopathology Lab, Institute of Psychology, Polish Academy of Sciences, ul. Jaracza 1, 00-378 Warsaw, Poland. E-mail address: l.gaweda@psych.pan.pl (Ł. Gawęda).</footnote>

<footnote n="1">¹ H.G. & M.K. Contributed equally to this work and share the first authorship.</footnote>

<footnote n="2">² Ł.G. & S.O. Share the senior authorship.</footnote>
# 1. Introduction

Schizophrenia affects about 1 % of the population (Jongsma et al., 2018). In contrast to disorders such as anxiety or depression, which exhibit pronounced sex differences in terms of prevalence, schizophrenia demonstrates comparatively similar lifetime prevalence between males and females. However, males frequently experience an earlier age of onset and more severe negative symptoms (Ochoa et al., 2012). Furthermore, gender, as well as other sociodemographic factors, may be involved in shaping different courses of the illness (e.g., Castle et al., 1993; Lewine et al., 1998; McGrath et al., 2008; Ochoa et al., 2012; Perälä et al., 2007; Thorup et al., 2007). One of the fundamental distinctions between men and women lies in the average age of schizophrenia onset. Men typically encounter their initial episode between 18 and 25 years old, while women experience it between 25 and 35 (Galderisi et al., 2012; Goldstein and Tsuang, 1990; Gureje, 1991; Ochoa et al., 2012). Notably, women exhibit two critical periods of onset, with the latter occurring after the age of 40 (Ochoa et al., 2006; Ochoa et al., 2012). On the other hand, there are studies (e.g., Murthy et al., 1998; Naqvi et al., 2005; Naqvi et al., 2010) where no gender differences in the age of the first episode of onset were shown. As for the specificity of the disease by gender, here too, we can find some important differences. Men often manifest a higher prevalence of negative symptoms (Riecher-Rössler, 2017), while women tend to exhibit a greater frequency of positive symptoms (Cowell et al., 1996; Ochoa et al., 2012). Interestingly, despite having a more extensive social support system, women may experience lower self-esteem (Thorup et al., 2007; Ferrer-Quintero et al., 2022), lower self-reflectiveness (Espinosa et al., 2024), and diminished cognitive functioning (Karilampi et al., 2011). However, it is essential to note that findings regarding cognitive functioning are inconsistent (Goldberg et al., 1995; Fond et al., 2018; Magdaleno Herrero et al., 2023; Salokangas, 1983).

Importantly, gender and age may be factors that have an impact on the therapeutic protocols (both pharmacological as well as psychosocial interventions) and thus should be considered in the treatment selection. A recent review of the literature revealed an initial benefit for women compared to men in the treatment of schizophrenia, such as a better response to treatment (Thorup et al., 2014). However, higher benefits for women diminish over time, depending on the age of the patient. Furthermore, the social and cultural context of the study impacts observable benefits for women (Seeman, 2019). In general, studies revealed that women demonstrate enhanced overall social functioning both before and during the illness, which is attributed to a broader social support network, including partners and family, whereas men are more likely to live alone or with their parents (Amminger et al., 2006; Canuso and Pandina, 2007; Nordentoft et al., 2006; Thomas et al., 2010; Willhite et al., 2008). Additionally, premenopausal women and post-menopausal women may respond better to antipsychotics compared to men, which may be due to hormonal and psychosocial factors (Canuso and Pandina, 2007). Furthermore, women tend to display a superior response to drug treatments and a more favorable disease prognosis compared to men (Usall et al., 2001; Haro et al., 2008). However, these gender-specific differences necessitate tailored therapeutic approaches, addressing diverse requirements in non-pharmacological therapies. Previous research suggests that responses to psychological treatments are also gender sensitive in CBT (Brabban et al., 2009) but also in MCT (Salas-Sender et al., 2020).

In addition to gender and age, other sociodemographic and clinical characteristics, such as education level and duration of illness, have been demonstrated to affect schizophrenia treatment outcomes significantly (e.g., Ljungdalh, 2017; Perkins et al., 2005; Zhu et al., 2023). Furthermore, educational level plays an important role in a patient's life and is closely related to cognitive function and adherence to medication (Lövdén et al., 2020). A number of studies have indicated that a patient's educational level may be associated with non-adherence to medical advice (e.g., Acosta et al., 2012; Nakonezny and Byerly, 2006), resulting

in relapses and thus limiting further progression among patients with lower education. Furthermore, the duration of untreated psychosis has also been found to be associated with a poorer prognosis and therapeutic resistance (e.g., Brasso et al., 2024; Buoli et al., 2012). Consequently, these factors may also play a significant role in the response to the effectiveness of both pharmacological and psychological interventions.

Given the complexity of schizophrenia and the insufficient effectiveness of antipsychotics (Kart et al., 2021; Lieberman et al., 2005), psychotherapeutic interventions have been developed for positive and negative symptoms. One of the most popular forms of psychotherapy used in the treatment of schizophrenia is Cognitive Behavioral Therapy (CBT), particularly the dedicated CBTp (Cognitive Behavioral Therapy for Psychosis). Meta-analyses have shown that CBTp has low to moderate efficacy (Jauhar et al., 2014; Wykes et al., 2008). The effect size of CBT therapy for positive symptoms was estimated at 0.31 in the Jauhar et al. (2014) meta-analysis, compared to the group receiving standard treatment, and was estimated at 0.37 in the Wykes et al. (2008) meta-analysis. A recent meta-analysis (Berendsen et al., 2024; Sitko et al., 2020) also found that the effectiveness of CBT in treating delusions increased significantly between 1998 and 2024. However, the widespread implementation of psychotherapy is hampered by a number of factors, including the limited availability of therapeutic services in hospital centres, extended waiting periods for individual therapy, and the associated financial costs. Furthermore, patients' frequent withdrawal from pharmacotherapy and non-compliance with medical recommendations have been demonstrated to result in patient dropout from therapy and a reduction in motivation for treatment (Thai et al., 2024; Vega et al., 2021). This poses a significant challenge to the practical implementation of psychotherapy in patients with schizophrenia. Given these accessibility limitations, metacognitive training (MCT; Moritz and Woodward, 2007) emerges as a promising intervention. The standardized structure and capacity for group delivery of MCT facilitate its application in diverse clinical settings, enabling efficient treatment of a larger number of patients in a relatively short period of time. It can increase the availability of psychological interventions and foster greater participant involvement, including through the opportunity to share experiences of illness.

MCT stands out as a well-structured, low-intensity intervention that focuses on cognitive biases, initially tailored for individuals diagnosed with schizophrenia spectrum disorders (Moritz et al., 2023). A recent meta-analysis by Penney et al. (2022), Lopez-Morinigo et al. (2020), Sauvé et al. (2020), and Philipp et al. (2019) on the efficacy of MCT found a moderate effect on general positive symptoms and a moderate to large effect was found on delusions specifically (Penney et al., 2022). MCT is also available as free exercise on the self-help application COGITO (www.uke.de/cogito_app), making it easy to use outside the therapy room and to use MCT therapy techniques independently.

While the effectiveness of MCT in schizophrenia treatment is promising, understanding how demographic factors such as age and gender intersect with treatment outcomes remains a critical, yet often unexplored, aspect of MCT effectiveness research. Despite a limited body of research in this area, a study by Salas-Sender et al. (2020), which examined gender differences in the effectiveness of MCT in patients with first episode psychosis is worth noting. Findings suggest that MCT is more effective in reducing symptoms and improving cognitive insight in women compared to men, highlighting the potential importance of gender-specific approaches in MCT. As a demographic variable, age also can significantly influence an individual's response to therapeutic interventions. Younger individuals' cognitive flexibility and adaptability might render them more receptive to metacognitive strategies, potentially leading to more favorable outcomes (Wykes et al., 2007). In contrast, older individuals might exhibit distinct cognitive patterns, necessitating tailored approaches to address their specific needs within the context of MCT. Similarly, gender plays a role in shaping therapeutic responses (Ochoa et al., 2012). Societal and cultural factors often influence how individuals, especially those with schizophrenia spectrum
disorders, perceive and engage with therapeutic interventions (Degnan et al., 2018). It is therefore important to undertake a detailed examination of the impact of gender and age on the efficacy of therapeutic techniques, such as MCT, for the treatment of schizophrenia. Furthermore, it is important to implement personalized therapeutic techniques that are appropriately tailored to the individual needs of patients in order to optimize the therapy and enhance its effectiveness, thereby accounting for potential differences among patients. Tailoring therapy to the specific needs of patients offers the potential to optimize its effectiveness and take into account the variability observed across demographic groups. This may pave the way for more precise and effective interventions that address the diverse needs of patients. Therefore, the objective of this meta-analysis is to quantitatively synthesise the extant evidence for the efficacy of MCT in schizophrenia, while also examining the impact of key demographic factors, particularly age, gender, education level, and duration of illness, on treatment effectiveness. It is hypothesised that MCT will show significant effects on improving disease symptoms, and that these effects may vary by demographic subgroups.

## 2. Methods

The study protocol was registered on the PROSPERO database (CRD42023448858), and the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed (Page et al., 2021).

### 2.1. Search strategy and selection criteria

The search was conducted on material published from 2007 to November 15, 2024, using three electronic databases: PubMed, PsycInfo, and Scopus. Searches were restricted to records published following the first MCT for psychosis publication (2007). The only initial search limitation was the English language. The search strategy used Medical Subjects Headings (MeSH) terms and keywords (Schizophrenia OR Paranoid Disorders OR schizo* OR psychotic* OR psychosis OR psychoses OR "first-episode" OR delusion*, OR schizophrenia/therapy* OR schizophrenia* OR delusions/therapy OR "Psychotic Disorders/ rehabilitation" OR "Schizophrenic Psychology" AND "metacognitive" train* OR "meta-cognitive" train* OR "meta-cognitive" train OR "MCT").

<figure><img src="image_4.png" /><figcaption>Fig. 1. Flowchart.</figcaption></figure>
Fig. 1. presents the report selection flowchart. Two of the authors (M. K. and H.G.) independently evaluated the eligibility of the records, and any discrepancies were resolved through discussion with a third author (L.G.) until a majority agreement was reached. Included reports were published in peer-reviewed journals; books, case studies, review articles, letters to the editor, and conference abstracts were excluded. Studies had to include participants with a diagnosis of schizophrenia spectrum or related psychotic disorder based on standardized criteria (Diagnostic and Statistical Manual of Mental Disorders or International Classification of Diseases). There were no sex, gender, race, ethnicity, medication, comorbid diagnosis or substance restrictions. Exclusion criteria were age under 18 years, participants with a diagnosis of affective psychosis or studies including samples made up of 60 % of patients without a diagnosis of non-affective psychosis. Studies also had to administer the original version of adaptations of MCT for psychosis. Acceptable adaptations included variability in the number of sessions duration. Both individual (MCT+) and group formats were considered. It is worth noting that some studies used the MCT group program for individual training but did not incorporate the MCT+ materials. Eligible studies included randomized controlled trials (RCTs), quasi-experimental studies, and cohort studies published in peer-reviewed journals. If a study included a control group, it had to compare MCT with either a passive control condition (e.g., waitlist) or an active control condition (e.g., treatment as usual, cognitive behavioral therapy, or psycho-education). Articles based on secondary analysis of data from a clinical trial that has been published elsewhere were excluded. Studies were included in the meta-analysis if at least one of the relevant outcomes was measured, the sample size exceeded 10 patients, and no other forms of psychological interventions were provided in addition to MCT. The search was supplemented by relevant papers identified by a manual search of the reference lists of the identified articles. To examine the impact of gender on the effectiveness of the intervention, we contacted the corresponding authors of the included studies via email. Taking into account data provided by co-authors as well as responses to our request, it was possible to analyze the influence of gender on the outcomes based on 22 studies evaluating the effectiveness of MCT. Data extraction was performed by M.K. and H.G.

## 2.2. Outcome measures

### 2.2.1. Positive symptoms

As a measure of positive symptoms, the positive subscale of the Positive and Negative Syndrome Scale (PANSS, Kay et al., 1987), Scale for the Assessment of Positive Symptoms (SAPS, Andreasen, 1986), and Brief Psychiatric Rating Scale (BPRS, Shafer, 2005) were used. The total score of the Psychotic Symptom Rating Sales (PSYRATS) (Haddock et al., 1999) was not used as a measure of positive symptoms because some studies showed that the PSYRATS is not strongly correlated with the positive subscale of the PANSS, such that these instruments may tap into different concepts (Kronmuller et al., 2011).

### 2.2.2. Delusions

The sum of the delusions subscale of the PSYRATS (Haddock et al., 1999) was used as a measure for delusions.

### 2.2.3. Jumping to conclusions

As a measure of cognitive biases, the Fish Task (Moritz et al., 2012; Speechley et al., 2010) and Beads Task (Garety et al., 2005) were used. These computerized probabilistic reasoning tasks were administered to capture jumping to conclusions (JTC), which is a prominent bias targeted by two modules of MCT. In the analyses, only versions with a high discrimination ratio (80:20 or 85:15) and JTC as Draw to Decision (DTD) were considered.

### 2.2.4. Cognitive insight

As a measure of cognitive insight, the Beck Cognitive Insight Scale

(BCIS) (Beck et al., 2004) was used. We analyzed two subscales of the BCIS – “self-reflectiveness” and “self-certainty”. A composite index of the BCIS termed “cognitive insight” was calculated by subtracting the self-certainty subscore from the self-reflectiveness subscore.

## 2.3. Data synthesis procedure

Studies were deemed eligible for quantitative synthesis if they reported the sample sizes, means, and standard deviations for pre- and post-treatment outcome measures. Individual effect sizes (Cohen's d) for each study's control and intervention condition were calculated with reported means and standard deviations using the effect size calculator from the Psychometrica.de website. Subsequently, the effect size of the control condition was subtracted from the effect size of the intervention, resulting in one effect size for each study (Morris and DeShon, 2002). To investigate the influence of demographic factors (i.e., age, duration of illness, and education level) on effect sizes, meta-regression analyses were conducted for variables including age, duration of illness, and years of education.

If data provided by the authors enabled us to compute separate effect sizes for women and men, we subtracted the effect size of women from that of men to assess differences in effect between genders. A positive value indicates a larger effect size in the male group compared to the female group concerning cognitive biases, self-reflectiveness, and the Composite Index. Conversely, a negative value suggests the reverse - a larger effect size in the female group. Similarly, a negative value concerning positive symptoms, delusions, and self-certainty implies a larger effect size in the male group, while a positive value suggests the opposite - a larger effect size in the female group. Selected outcomes were synthesized with separate meta-analyses using JASP Team (2024), (Version 0.18.0). Meta-analyses were not limited to randomized clinical trials (RCTs).

Because of the variance in the type of interventions, a random-effects model was used. The overall effect size was calculated and represented in a forest plot together with the effect size of each study.

## 2.4. Methodological quality assessment

Two authors (M.K. and H.G.) independently assessed the study risk of bias using the Mixed Methods Appraisal Tool, version 2018 (Hong et al., 2018). Methodological quality criteria and results are presented in Supplementary Table S1 for randomized controlled trials and S2 for non-randomized controlled trials. Disagreements were resolved between the two authors following examination and discussion of the Mixed Methods Appraisal Tool criteria (MMAT). The heterogeneity of effect sizes across studies was estimated with Cochran's Q test (Cochran, 1950) and the I² statistic (Higgins et al., 2003) for each meta-analysis. By convention, a Q-statistics p-value below 0.1 indicates heterogeneity (Potvin, 2014), while I² values of 25, 50, and 75 are associated with low, moderate, and strong heterogeneity, respectively (Higgins et al., 2003). The risk of publication bias was assessed for each analysis with PET-PEESE. PET-PEESE adjusts for the linear or quadratic relationship between effect sizes and standard errors that are assumed to be unrelated under no publication bias (Stanley and Doucouliagos, 2014; Stanley, 2017). A sensitivity analysis restricted study design to RCTs to verify the impact of study design on our results.

## 3. Results

Based on the aforementioned inclusion and exclusion criteria, 631 papers were identified, and 90 were assessed. Thirty-seven studies were deemed eligible for the meta-analysis. Of these thirty-seven studies, 30 were RCTs (81 %), and 7 were non-RCTs (19 %). Table 1. presents the main characteristics of the included studies.
<table><caption>**Table 1**
Main study characteristics.</caption><thead><tr><th>Source</th><th>Country</th><th>Design</th><th>Group type</th><th>Sample size, No.</th><th>Age, mean (SD)</th><th>DOI, mean (SD)</th><th>Education, mean (SD)</th><th>Gender (F %)</th></tr></thead><tbody><tr><td rowspan="2">Acuna et al., 2022</td><td rowspan="2">Chile</td><td rowspan="2">RCT</td><td>MCT</td><td>25</td><td>27.52 (8.42)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">30.43</td></tr><tr><td>TAU</td><td>21</td><td>25.71 (4.72)</td></tr><tr><td rowspan="2">Aghotor et al., 2010</td><td rowspan="2">Germany</td><td rowspan="2">RCT</td><td>MCT</td><td>14</td><td>28.9 (8.3)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">16.00</td></tr><tr><td>Newspaper discussion group</td><td>12</td><td>32.6 (12.1)</td></tr><tr><td rowspan="2">Ahuir et al., 2018</td><td rowspan="2">Spain</td><td rowspan="2">Crossover RCT</td><td>MCT+ Psychoeducation</td><td>14</td><td>23.0 (4.2)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>Psychoeducation+ MCT</td><td>14</td><td>24.0 (5.0)</td></tr><tr><td rowspan="2">Andreou et al., 2017</td><td rowspan="2">Germany</td><td rowspan="2">RCT</td><td>MCT+</td><td>46</td><td>36.91 (12.5)</td><td rowspan="2">NR</td><td rowspan="2">11.65 (1.7)</td><td rowspan="2">54.35</td></tr><tr><td>CR+</td><td>46</td><td>35.59 (13.1)</td></tr><tr><td>Andreou et al., 2018</td><td>Germany</td><td>Non-RCT</td><td>MCT</td><td>23</td><td>36.84 (12.6)</td><td>NR</td><td>NR</td><td></td></tr><tr><td rowspan="2">Balzan et al., 2019</td><td rowspan="2">Australia</td><td rowspan="2">RCT</td><td>MCT+</td><td>26</td><td>33.37 (9.84)</td><td>9.85 (8.47)</td><td>11.30 (1.96)</td><td>84.44</td></tr><tr><td>CR</td><td>26</td><td>39.04 (7.48)</td><td>12.37 (2.05)</td><td>11.52 (2.05)</td><td>82.47</td></tr><tr><td rowspan="2">Briki et al., 2014</td><td rowspan="2">France</td><td rowspan="2">RCT</td><td>MCT</td><td>25</td><td>41.1 (8.1)</td><td>14.6 (8.4)</td><td>9.00 (2.3)</td><td>36.00</td></tr><tr><td>Supportive therapy</td><td>25</td><td>41.1 (12.4)</td><td>17.8 (10.9)</td><td>8.6 (2.1)</td><td>32.00</td></tr><tr><td rowspan="2">Chen et al., 2021</td><td rowspan="2">China</td><td rowspan="2">RCT</td><td>MCT</td><td>58</td><td>55.28 (9.51)</td><td>22.69 (12.02)</td><td>6.32 (2.87)</td><td>58.62</td></tr><tr><td>Community-based rehabilitation</td><td>62</td><td>52.90 (12.14)</td><td>23.35 (12.70)</td><td>6.74 (2.46)</td><td>61.29</td></tr><tr><td rowspan="2">de Pinho et al., 2021</td><td rowspan="2">Portugal</td><td rowspan="2">RCT</td><td>MCT</td><td>27</td><td>48.30 (9.89)</td><td rowspan="2">NR</td><td rowspan="2">8.07 (2.96)</td><td rowspan="2">48.14</td></tr><tr><td>TAU</td><td>29</td><td>52.66 (7.14)</td></tr><tr><td rowspan="2">Erawati et al., 2014</td><td rowspan="2">Indonesia</td><td rowspan="2">Non-RCT</td><td>MCT+</td><td>26</td><td>37.07 (10.75)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">38.46</td></tr><tr><td>TAU</td><td>26</td><td>42.00 (12.46)</td></tr><tr><td>Favrod et al., 2011</td><td>Switzerland</td><td>Cross-sectional analytic study</td><td>MCT</td><td>18</td><td>41.80 (10.1)</td><td>NR</td><td>NR</td><td>NR</td></tr><tr><td rowspan="2">Favrod et al., 2014</td><td rowspan="2">Switzerland</td><td rowspan="2">RCT</td><td>MCT</td><td>24</td><td>36.85 (10.38)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">34.61</td></tr><tr><td>TAU</td><td>24</td><td>36.58 (9.76)</td></tr><tr><td rowspan="2">Fekete et al., 2022</td><td rowspan="2">Hungary</td><td rowspan="2">RCT</td><td>MCT</td><td>23</td><td>44.22 (10.45)</td><td>16.16 (7.76)</td><td>NR</td><td>52.17</td></tr><tr><td>TAU</td><td>23</td><td>38.39 (10.41)</td><td>11.32 (8.74)</td><td>NR</td><td>52.17</td></tr><tr><td rowspan="2">Fujii et al., 2021</td><td rowspan="2">Japan</td><td rowspan="2">Crossover RCT</td><td>MCT</td><td>9</td><td>54.00 (7.6)</td><td>31.78 (6.16)</td><td>12.17 (1.97)</td><td>33.33</td></tr><tr><td>TAU</td><td>8</td><td>54.50 (8.63)</td><td>33.38 (10.43)</td><td>12.63 (1.80)</td><td>50.00</td></tr><tr><td rowspan="2">Gaweda et al., 2015</td><td rowspan="2">Poland</td><td rowspan="2">RCT</td><td>MCT</td><td>23</td><td>50.41 (10.25)</td><td>22.96 (10.05)</td><td>NR</td><td>52.17</td></tr><tr><td>TAU</td><td>21</td><td>51.65 (10.25)</td><td>20.61 (11.30)</td><td>NR</td><td>47.61</td></tr><tr><td rowspan="2">Haga et al., 2022</td><td rowspan="2">Japan</td><td rowspan="2">RCT</td><td>MCT</td><td>8</td><td>44.25 (8.54)</td><td>21.75 (12.49)</td><td>13.75 (1.85)</td><td>37.5</td></tr><tr><td>Occupational therapy</td><td>8</td><td>43.25 (7.98)</td><td>17.88 (11.11)</td><td>15.25 (2.81)</td><td>62.5</td></tr><tr><td rowspan="2">Ishikawa et al., 2020</td><td rowspan="2">Japan</td><td rowspan="2">RCT</td><td>MCT</td><td>24</td><td>46.04 (8.37)</td><td>19.58 (8.95)</td><td>NR</td><td>45.8</td></tr><tr><td>TAU</td><td>26</td><td>48.96 (8.54)</td><td>22.5 (8.84)</td><td>NR</td><td>53.8</td></tr><tr><td rowspan="2">Kumar et al., 2010</td><td rowspan="2">India</td><td rowspan="2">RCT</td><td>MCT</td><td>8</td><td>31.50 (7.98)</td><td>7.63 (7.74)</td><td>9.37 (2.50)</td><td>NR</td></tr><tr><td>TAU</td><td>8</td><td>34.13 (8.20)</td><td>6.50 (5.21)</td><td>9.25 (4.50)</td><td>NR</td></tr><tr><td rowspan="2">Kuokkanen et al., 2014</td><td rowspan="2">Finland</td><td rowspan="2">RCT</td><td>MCT</td><td>10</td><td>42.0 (10.4)</td><td>16.4 (10.3)</td><td>10.3 (1.6)</td><td>0.00</td></tr><tr><td>TAU</td><td>10</td><td>45.1 (14.3)</td><td>16.5 (9.2)</td><td>10.7 (2.1)</td><td>0.00</td></tr><tr><td rowspan="2">Lam et al., 2015</td><td rowspan="2"></td><td rowspan="2">RCT</td><td>MCT</td><td>38</td><td>41.26 (10.96)</td><td>NR</td><td>NR</td><td>44.73</td></tr><tr><td>TAU</td><td>39</td><td>39.92 (11.29)</td><td>NR</td><td>NR</td><td>33.33</td></tr><tr><td>Lopez-Morinigo et al., 2023</td><td>Spain</td><td>RCT</td><td>MCT</td><td>18</td><td>45.6 (9.9)</td><td>NR</td><td>NR</td><td>46.2</td></tr><tr><td rowspan="2">Moritz et al., 2011a</td><td rowspan="2">Germany</td><td rowspan="2">RCT</td><td>Psychoeducation</td><td>16</td><td>49.8 (9.3)</td><td rowspan="2">NR</td><td rowspan="2">10.83 (1.54)</td><td rowspan="2">47.4</td></tr><tr><td>MCT</td><td>18</td><td>33.6 (8.8)</td></tr></tbody></table>

(continued on next page)
<table><caption>**Table 1 (continued)**</caption><thead><tr><th>Source</th><th>Country</th><th>Design</th><th>Group type</th><th>Sample size, No.</th><th>Age, mean (SD)</th><th>DOI, mean (SD)</th><th>Education, mean (SD)</th><th>Gender (F %)</th></tr></thead><tbody><tr><td rowspan="3">Moritz et al., 2011b</td><td rowspan="3">Germany</td><td rowspan="3">RCT</td><td>TAU</td><td>18</td><td>31.9 (7.0)</td><td rowspan="3">NR</td><td>10.44 (1.50)</td><td>27.77</td></tr><tr><td>MCT</td><td>24</td><td>32.63 (12.48)</td><td>11.25 (1.48)</td><td>29.16</td></tr><tr><td>CR</td><td>24</td><td>35.46 (9.10)</td><td>11.35 (1.53)</td><td>41.66</td></tr><tr><td rowspan="2">Moritz et al., 2013</td><td rowspan="2">Germany</td><td rowspan="2">RCT</td><td>MCT</td><td>76</td><td>36.82 (11.12)</td><td rowspan="2">NR</td><td>11.34 (1.65)</td><td>40.78</td></tr><tr><td>CR</td><td>63</td><td>32.68 (9.54)</td><td>11.59 (1.67)</td><td>33.78</td></tr><tr><td rowspan="2">Naughton et al., 2012</td><td rowspan="2">Ireland</td><td rowspan="2">Cohort</td><td>MCT</td><td>11</td><td>37.5 (10.6)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">NR</td></tr><tr><td>Waiting list</td><td>8</td><td>35.62 (11.2)</td></tr><tr><td rowspan="2">Ochoa et al., 2017</td><td rowspan="2">Spain</td><td rowspan="2">RCT</td><td>MCT</td><td>65</td><td>27.05 (7.94)</td><td rowspan="2">2.15 (20.1)</td><td rowspan="2">NR</td><td rowspan="2">32.3</td></tr><tr><td>Psychoeducation</td><td>57</td><td>28.21 (6.73)</td></tr><tr><td rowspan="2">Park et al., 2020</td><td rowspan="2">South Korea</td><td rowspan="2">RCT</td><td>MCT</td><td>30</td><td>38.37 (9.07)</td><td rowspan="2">13.70 (8.50)</td><td>12.80 (1.73)</td><td>40.0</td></tr><tr><td>Psychoeducation</td><td>29</td><td>40.86 (7.34)</td><td>14.90 (8.67)</td><td>13.38 (2.56)</td><td>34.5</td></tr><tr><td rowspan="2">Pos et al., 2018</td><td rowspan="2">Netherlands</td><td rowspan="2">RCT</td><td>MCT</td><td>20</td><td>23.59 (3.03)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">28.0</td></tr><tr><td>Occupational therapy</td><td>18</td><td>23.08 (4.16)</td></tr><tr><td rowspan="2">Shan et al., 2020</td><td rowspan="2">China</td><td rowspan="2">RCT</td><td>MCT</td><td>19</td><td>26.05 (5.81)</td><td rowspan="2">NR</td><td>11.63 (3.75)</td><td>36.84</td></tr><tr><td>Recreational activities</td><td>20</td><td>22.75 (4.38)</td><td>10.65 (2.50)</td><td>25.00</td></tr><tr><td rowspan="2">Simón-Expósito and Felipe-Castaño, 2019</td><td rowspan="2">Spain</td><td rowspan="2">Non-RCT</td><td>MCT</td><td>11</td><td>42.82 (7.5)</td><td>21.55 (8.26)</td><td>10.36 (4.01)</td><td>27.27</td></tr><tr><td>TAU</td><td>11</td><td>47.27 (12.63)</td><td>24.36 (11.48)</td><td>11.82 (3.14)</td><td></td></tr><tr><td rowspan="2">So et al., 2015</td><td rowspan="2">Hong Kong</td><td rowspan="2">Crossover RCT</td><td>MCT+</td><td>23</td><td>32.35 (12.87)</td><td rowspan="2">NR</td><td>11.67 (2.78)</td><td>47.82</td></tr><tr><td>Waiting list</td><td>21</td><td>35.62 (10.89)</td><td>12.81 (3.19)</td><td>42.85</td></tr><tr><td rowspan="2">Ho-Wai So et al., 2020</td><td rowspan="2">Hong Kong</td><td rowspan="2">RCT</td><td>MCT</td><td>27</td><td>42.78 (14.54)</td><td rowspan="2">NR</td><td>10.81 (3.03)</td><td>55.55</td></tr><tr><td>TAU</td><td>29</td><td>40.21 (13.27)</td><td>12.45 (3.49)</td><td>37.93</td></tr><tr><td>Tanoue et al., 2021</td><td>Japan</td><td>Cross-sectional analytic study</td><td>MCT</td><td>22</td><td>52.7 (12.4)</td><td>NR</td><td>NR</td><td>58.82</td></tr><tr><td rowspan="2">Ussorio et al., 2016</td><td rowspan="2">Italy</td><td rowspan="2">Cross-sectional analytic study</td><td>MCT</td><td>56</td><td>22.02 (4.54)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td rowspan="2">26.78</td></tr><tr><td>TAU</td><td>75</td><td>38.3 (11.1)</td><td>NR</td><td>NR</td></tr><tr><td rowspan="2">van Oosterhout et al., 2014</td><td rowspan="2">Netherlands</td><td rowspan="2">RCT</td><td>MCT</td><td>79</td><td>36.8 (8.7)</td><td rowspan="2">NR</td><td rowspan="2">NR</td><td>28.00</td></tr><tr><td>PSST</td><td>10</td><td>33.1 (10.7)</td><td>13.6 (6.1)</td><td>11.7 (3.2)</td></tr><tr><td rowspan="2">Yildiz et al., 2018</td><td rowspan="2">Turkey</td><td rowspan="2">RCT</td><td>MCT</td><td>10</td><td>37.4 (4.6)</td><td rowspan="2">13.2 (8.4)</td><td>11.4 (1.6)</td><td>40.00</td></tr><tr><td>PSST</td><td>10</td><td>31.50 (6.06)</td><td>10.85 (5.71)</td><td>12.56 (2.23)</td><td>30.00</td></tr><tr><td rowspan="2">Zalzala et al., 2022</td><td rowspan="2">United States</td><td rowspan="2">RCT</td><td>MCT</td><td>16</td><td>32.27 (6.28)</td><td rowspan="2">9.13 (7.80)</td><td>12.04 (2.28)</td><td>47.00</td></tr><tr><td>Healthy living group</td><td>16</td><td></td><td></td><td></td></tr></tbody></table>

Note. MMAT = Mixed Methods Appraisal Tool; DOI = Duration of illness; MCT = Metacognitive Training; MCT+ = Individual Metacognitive Training; CR = Cognitive Remediation; CR+ = Individual Cognitive Remediation; PSST = Psychosocial Skills Training; RCT = Randomized Clinical Trial; TAU = Treatment as Usual; NR = Not Recorded; No. = Number; SD = Standard Deviation.

### 3.1. Effect of demographic variables on positive symptoms

Thirty studies (n MCT = 732, n control = 613) reporting positive symptoms outcome measures were included. Sample sizes ranged from n = 16 (Haga et al., 2022) to n = 135 (Moritz et al., 2013), totaling N = 1345 participants. Thirty studies reported age, thirteen studies reported duration of illness, and seventeen studies reported years of education. The overall effect on positive symptoms (d = -0.40; 95 % CI, -0.55, -0.24; P < 0.001) favored MCT compared with controls. The overall effect was not moderated by age (Z = 0.762, P = 0.446), duration of illness (Z = -1.164, P = 0.244), or education (Z = -0.234, P = 0.815). Fourteen studies only reported gender (n women = 302, n men = 511). As illustrated in Fig. 2, there was no gender effect on positive symptoms (d = -0.02; 95 % CI, -0.34, 0.29; P = 0.883).

### 3.2. Effect of demographic variables on delusions

Fifteen studies (n MCT = 447, n control = 438) reporting delusion outcome measures were included. Sample sizes ranged from n = 18 (Favrod et al., 2014) to n = 135 (Moritz et al., 2023), totaling N = 885 participants. Fifteen studies reported age, five studies reported duration of illness, and ten studies reported years of education. The overall effect on delusions (d = -0.41; 95 % CI, -0.62, -0.19; P < 0.001) favored MCT compared with controls. The overall effect was not moderated by age (Z = -0.503, P = 0.615), duration of illness (Z = 0.103, P = 0.918), or education (Z = 0.808, P = 0.419). For gender effects, we meta-analyzed ten studies (n women = 273, n men = 431). As illustrated in Fig. 3, a greater reduction in the intensity of delusions was observed in men. However, the result was not significant (d = -0.39; 95 % CI, -0.85, 0.08; P = 0.108).
<figure><img src="image_5.png" /><figcaption>Fig. 2. Forrest plot for meta-analysis of gender in positive symptoms (positive values favoring women and negative values favoring men).</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 3. Forrest plot meta-analysis of gender in delusions (positive values favoring women and negative values favoring men).</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 4. Forrest plot for meta-analysis of gender in cognitive biases (positive values favoring men and negative values favoring women).</figcaption></figure>
### 3.3. Effect of demographic variables on cognitive biases

Seven studies (n MCT = 208, n control = 210) reporting cognitive bias outcome measures were included. Sample sizes ranged from n = 20 (Kuokkanen et al., 2014) to n = 135 (Moritz et al., 2013), totaling N = 418 participants. Seven studies reported age, two studies reported duration of illness (the factor could not be analyzed due to the insufficient number of reported variables), and five studies reported years of education. The overall effect on cognitive biases (d = 0.13; 95 % CI, -0.09, 0.36; P = 0.241) non-favored MCT compared with controls. The overall effect was not moderated by age (Z = 0.433, P = 0.665) or education (Z = -1.465, P = 0.143). For gender effect, we meta-analyzed eight studies (n women = 229, n men = 367). As illustrated in Fig. 4, there was no gender effect on cognitive biases (d = 0.04; 95 % CI, -0.56, 0.63; P = 0.906).

### 3.4. Effect of demographic variables on cognitive insight

Fifteen studies (n MCT = 401, n control = 340) reporting cognitive insight outcome measures were included. Sample sizes ranged from n = 16 (Haga et al., 2022) to n = 128 (van Oosterhout et al., 2014), totaling N = 757 participants. All studies reported age, six studies reported duration of illness, and seven studies reported years of education. The overall effect on self-reflectiveness (d = 0.13; 95 % CI, -0.11, 0.37; P = 0.278) did not favor MCT compared with controls. The overall effect was not moderated by age (Z = 1.402, P = 0.161), duration of illness (Z = -0.058, P = 0.954), or education (Z = 1.026, P = 0.305). Regarding self-certainty, the overall effect (d = -0.15; 95 % CI, -0.31, 0.02; P = 0.080) non-favored MCT compared with controls. The overall effect was not moderated by age (Z = -0.187, P = 0.852) or duration of illness (Z = 0.964, P = 0.335) but was moderated by education (Z = 2.738, P = 0.006). The overall effect on Composite Index (d = 0.28; 95 % CI, 0.05, 0.52; P = 0.018) favored MCT compared with controls. The overall effect was not moderated by age (Z = -1.094, P = 0.274), duration of illness (Z = -0.498, P = 0.619), or education (Z = -0.506, P = 0.613). For gender effect, we meta-analyzed nine studies (n women = 170, n men = 278). The results are illustrated in Fig. 5. There was a gender effect on self-reflectiveness, indicating greater improvement in women (d = -0.27; 95 % CI, -0.54, 0.01; P = 0.055). The sensitivity analysis restricting study design to RCTs included five studies that were additionally made. The results of this sensitivity analysis were no longer significant (d = -0.10; 95 % CI, -0.49, 0.30; P = 0.630). In terms of self-

certainty (see Supplementary Fig. S1) (d = -0.02; 95 % CI, -0.46, 0.43; P = 0.946) and Composite Index (see Supplementary Fig. S2), there was no gender effect (d = -0.17; 95 % CI, -0.43, 0.09; P = 0.208).

### 3.5. Estimation of evidence

The I² values suggest the presence of strong heterogeneity for positive symptoms, delusions, cognitive biases, and insight. The risk of publication bias was assessed via visual examination of the funnel plots (see Supplementary Tables S3 and S4 and Supplementary Figs. S3-S14) by using the PET/PEESE method in JASP to detect an assessment of potential publication bias. The analysis for variables such as PSYRATS, JTC, BCIS SC, SR, INDEX, and PANSS was conducted. Based on the analysis for each variable, there was no significance, indicating a publication bias.

## 4. Discussion

The present meta-analysis provides new insights into the effectiveness of Metacognitive Training (MCT) as a therapeutic intervention for the treatment of schizophrenia symptoms. In particular, the influence of demographic factors such as gender, age, duration of illness, and educational level has been investigated. The demonstrated efficacy of MCT in reducing positive symptoms is consistent with previous studies (e.g., Moritz et al., 2013; Penney et al., 2022), which indicated a moderate effect of MCT on symptoms such as hallucinations and delusions. Furthermore, MCT appears to be a universally applicable and moderately effective intervention for patients across diverse demographic characteristics. Our meta-analysis confirms the efficacy of MCT in improving cognitive insight, particularly in the female group and in the group with higher education.

Considering specific symptoms, our analysis revealed that MCT demonstrated a moderate reduction in delusion severity. A trend towards greater improvement in delusions was observed in male patients in some studies, however, these differences were not statistically significant. Our meta-analysis indicated no significant efficacy of MCTs in reducing cognitive biases, which is consistent with previous findings suggesting that MCT may be less effective for deep-seated cognitive biases than for reducing positive symptoms (Penney et al., 2022). It is worth emphasizing that in our study, we included only the jumping to conclusions index as a measure of cognitive biases, which may have influenced the obtained results. Moreover, schizophrenia patients

<figure><img src="image_8.png" /><figcaption>**Fig. 5.** Forrest plot for meta-analysis of gender in cognitive insight in a self-reflectiveness subscale (positive values favoring men and negative values favoring women).</figcaption></figure>
exhibit not only cognitive biases but also enhanced confidence for erroneous judgments (Moritz et al., 2004), which was not the subject of analysis. In future research, it would be valuable to examine whether, under the influence of MCT, patients not only reduce cognitive biases but also decrease their confidence in the responses they provide. Attenuated response confidence may open the minds of patients to alternative scenarios, delay decision-making, and decrease behavioral consequences for momentous decisions. Reducing overconfidence seems to be the core aim of the MCT rather than eliminating cognitive biases as “to err is human” (Moritz et al., 2013). Furthermore, we did not observe an impact of demographic variables as well as illness duration on the effectiveness of the MCT.

The results regarding the impact of MCT on cognitive insight offer a more complex picture. While the overall impact of MCT on domains such as self-reflectiveness and self-certainty did not reach statistical significance when compared to the control groups, the composite index of cognitive insight demonstrated a notable effect in favor of MCT. It is noteworthy that the impact of self-certainty was significantly influenced by educational attainment. This observation suggests that individuals with higher levels of education may have derived greater benefits from them in terms of cognitive insight. These results are coherent with previous studies that reported the effect of better IQ as a variable related with higher improvement in self-certainty cognitive insight (Birulés et al., 2020).

A study conducted by Barbalat et al. (2024) documented a reduction in quality of life in patients with better clinical insight, including lower self-esteem. However, a higher level of education (>12 years of education) was found to reduce the impact of increased insight and enhance patients' subjective quality of life. A similar conclusion can be drawn from the results obtained in our meta-analysis, where patients with higher levels of education appeared to benefit more from training in improving cognitive insight. Despite the distinction between cognitive and clinical insight as separate domains, they are closely related (Nair et al., 2014). Cognitive insight, which includes the ability to self-reflect and critically evaluate the patient's own beliefs, can provide the foundation for developing clinical insight, enabling the patient to better understand their own symptoms in the context of the illness. Consequently, the findings suggest that a higher level of education, which fosters superior information processing abilities and the utilisation of cognitive insight, is associated with greater benefits from MCT. This underscores the importance of personalising therapeutic interventions to align with patients' educational levels to ensure optimal efficacy and the maximisation of therapeutic benefits.

Moreover, with regard to the gender-specific efficacy of the training, the analysis revealed that women exhibited significantly greater improvements in the domain of “self-reflectiveness” than men, which is consistent with the findings of some previous studies (Salas-Sender et al., 2020). Nevertheless, a sensitivity analysis that was limited to randomized controlled trials (RCTs) demonstrated that this difference was no longer statistically significant. Concurrently, no significant discrepancy was observed in the effects on “self-certainty” and the composite index of cognitive insight between the two genders. Therefore, our findings may indicate that there are differences in the mechanisms by which men and women engage in metacognitive processes, with women demonstrating a greater tendency to benefit more from MCT for cognitive insight.

Interestingly, a comprehensive meta-analysis (Vita et al., 2021) identified that cognitive remediation (CR) was an effective treatment for cognitive functioning in patients with schizophrenia, with no significant demographic variables moderating outcomes. However, a more recent meta-analysis (Vita et al., 2024) examined the durability of CR effects and identified that female gender was associated with greater functional improvement during the follow-up period. This finding aligns with the results of the present meta-analysis, in which female patients exhibited significantly improved in self-reflectiveness, suggesting that gender may have a more extensive impact on the response to psychosocial

interventions, not only in MCT, but also in other techniques such as CR interventions. These findings highlight the significance of gender as a moderator of treatment efficacy and underscore the necessity for more personalized intervention strategies that take into account the demographic profiles of patients diagnosed with schizophrenia.

## 5. Strengths and limitations

While the current meta-analysis provides valuable insights into the effectiveness of MCT in the context of demographics and cognitive insight, it also presents several limitations that should be addressed. A principal limitation of this meta-analysis was the methodological heterogeneity of the included studies. The analysis incorporated both RCTs and quasi-experimental studies, in addition to diverse intervention formats, including individual and group sessions, which may have affected the outcomes. Although the use of a random effects model allowed for the consideration of heterogeneity, it did not fully eliminate it. The analysis of intervention-related factors that may influence treatment effectiveness could provide valuable insights and enhance the interpretation of our findings. However, such analyses were not conducted in the present study, as Penney et al. (2022) demonstrated that, aside from the year of publication, none of the investigated variables were statistically significant moderators of treatment outcomes. The limitation in the current literature on the effectiveness of Metacognitive Therapy (MCT) is the infrequent and inconsistent reporting of intervention characteristics. It is therefore recommended that future research should seek to achieve greater consistency in the design and reporting of studies conducted, including the standardization of the number of sessions, treatment formats, and measurement tools (such as PANSS or PSYRATS) in order to increase the comparability of results and reliability of conclusions. Moreover, an additional limitation is observed in the exclusion of studies published in languages other than English. While this criterion was employed to ensure consistency in the evaluation of studies and to avoid misinterpretation due to inaccurate translation, it limits access to all current studies.

Notwithstanding the aforementioned limitations, the present meta-analysis is characterized by a number of significant strengths. The inclusion of a wide range of studies and variables permitted the comprehensive examination of the efficacy of MCT. Secondly, the results obtained in this meta-analysis are consistent with those of previous meta-analyses (e.g., Philipp et al., 2019; Penney et al., 2022), thereby increasing their reliability and relevance to clinical practice. Thirdly, MCT has been demonstrated to be an efficacious intervention for the reduction of positive symptoms and delusions, irrespective of the patient's age, gender, or educational attainment. This makes it an extremely versatile tool for the management of schizophrenia symptoms and for the benefit of patients at any stage of their illness.

## 6. Conclusions

In conclusion, the results of this study demonstrate the efficacy of MCT as a universal and effective therapeutic method for schizophrenia patients. In light of the current global healthcare crisis, MCT appears to be a valuable intervention that is readily available (already available in 39 language variants). Our results support the conclusion that MCT is a valuable, effective, and multifaceted intervention.

A key finding of this meta-analysis is the observed improvement in cognitive insight, particularly among female patients and patients with higher educational level. Although the effect size was modest, the pronounced benefit of MCT in these demographic groups suggests a potential role for gender and educational level in the efficacy of metacognitive interventions. This provides a promising avenue for further research into how diverse demographic characteristics, including gender, may influence the outcomes of MCT, particularly in terms of cognitive insight.

It is therefore recommended that future studies consider a more
personalized approach to MCT, including the specific advantages of different training modules in relation to demographic variables such as age, gender, and educational level. This would allow for a more targeted and effective application of MCT, ensuring that it can be tailored to maximize its benefits for individual patients. Furthermore, we suggest that future studies should endeavor to achieve greater standardization in the tools used and the methodology for selecting the study group. This would ensure consistency and comparability of results between studies on the effectiveness of MCT.

### CRediT authorship contribution statement

**Hanna Gelner:** Visualization, Conceptualization, Writing – original draft, Data curation, Writing – review & editing, Formal analysis, Methodology. **Martyna Krężółek:** Visualization, Data curation, Writing – original draft, Formal analysis, Writing – review & editing, Methodology, Resources, Conceptualization. **Adrianna Aleksandrowicz:** Writing – review & editing. **Justyna Piwinska:** Writing – review & editing. **Maria Lamarca:** Writing – review & editing. **Fabrice Berna:** Writing – review & editing, Project administration. **Vanessa Acuña:** Project administration, Writing – review & editing. **Caroline König:** Writing – review & editing, Project administration. **Steffen Moritz:** Project administration, Writing – review & editing. **Susana Ochoa:** Writing – review & editing, Project administration. **Łukasz Gawędź:** Project administration, Supervision, Conceptualization, Writing – review & editing, Formal analysis, Methodology.

### Funding/support

The PERMEPSY project was supported under the frame of ERA PerMed by: Instituto de Salud Carlos III (ISCIII), Spain; German Federal Ministry of Education and Research (BMBF), Germany; Agencia Nacional de la Recherche (ANR), France; National Centre for Research and Development (NCBR), Poland; Agencia Nacional de Investigación y Desarrollo (ANID), Chile.

### Declaration of competing interest

Dr. Moritz is a codeveloper of metacognitive training for psychosis.

### Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.schres.2025.06.017.

### Data availability

Information about certified meta-cognitive clinical e-training for facilitators is available in English and German from the Clinical Neuropsychology Unit at the UKE, Hamburg. Certified Online Training: Metacognitive Training at https://www.uke.de/e-mct.

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