Introduction

Just as we have an immune system to defend against harmful biological agents, our minds also need psychological immunity to remain resilient to the stressors we encounter in everyday life1,2. Previous models of mental health (or well-being more broadly) have explored various conceptualizations, such as (1) multidimensional well-being3,4, (2) mirror opposite to the symptoms of mental disorders5,6, (3) psychosocial flourishing7, (4) “hedo-eudemonic” well-being8, (5) classical models of mental health9, (6) balanced models of mental health10, and (7) the sum of the components of well-being11. These concepts have focused on the components of well-being, and they have not fully captured all aspects of mental health as defined by the World Health Organization (WHO)12 and classical theories of mental health. Therefore, to fully represent mental health, measurement tools should go beyond operationalisations that define the concept in terms of observable characteristics of well-being or as a mirror opposite of mental disorders.

The Maintainable Positive Mental Health Theory (MPMHT)13,14 is the first attempt to treat all theory-based and empirically identified components of well-being as the set of features of mental health that reflect the presence and proper functioning of the psychological capacities needed to maintain and promote a positive psychological status and positive mental health. The suggested definition of positive mental health is a high level of global well-being, which goes together with psychological, social, and spiritual well-functioning, psychological resilience, efficient creative executive functioning, and coping and savoring capacities, all of which are pillars that enable flourishing. Unlike the effects of vaccines, these psychological skills and competencies are deeply ingrained and enduring, developed through time. These pillars of positive mental health can ensure flourishing even when the individual faces negative events, challenges, mental and physical health issues, or possible losses.

To the best of our knowledge, the Mental Health Test (MHT)14, (see Supplementary Table 7 and Table 8) which operationalises the MPMHT, is the first measure that offers a comprehensive, five-dimensional framework designed to cover the wide spectrum of psychological resources connected to mental health, equally including individuals who have mental disorders.

The first factor is Global Well-being, which integrates existing well-being theories and encompasses multi-component subjective well-being in emotional, psychological, social, and spiritual domains of life15,16,17. Savoring is the second factor, referring to the ability to mentally relive joyful memories and experiences, generating mental well-being and extending it to future events18. Savoring is an indispensable component of MPMHT as it enhances attainment and sustainability of positive mental health19. The third factor, Creative and Executive Efficiency, facilitates individuals in dealing with obstacles and hurdles by utilizing their competencies in both personal and social problem-solving15,20. The fourth factor is Self-regulation-the capability to regulate and control temperament, emotions, and negative states while persisting in achieving a goal. This ability plays a crucial role in mental health and represents one of the most adaptive aspects of human behaviour21,22,23. Finally, Resilience is the fifth factor, which refers to an individual’s psychological ability to mobilise their resources and maintain positive mental health when confronted with unexpected, stressful situations. The higher the level of resilience, the quicker the individual can regain their equilibrium from such circumstances24,25,26. The MHT score provides a broad overview of the level of the patient’s mental health capacities. Once the patient’s accessible mental health capacities have been identified, these can be integrated into the recovery phase to improve effectiveness, while more adaptive intervention methods can be used in everyday clinical practice (e.g., psychotherapy). The study by Zábó et al.14, which presents the validation of the measurement on sine morbo samples, provides a more detailed presentation of the advantages of the new concept and measurement.

The present study aims to examine: (1) the reliability and validity of the MHT in a Hungarian adult psychiatric sample; (2) the relationship between the MHT and sociodemographic indicators; (3) the associations between MHT scores and a wide variety of indicators related to organic symptoms and physical health; (4) the relationship between MHT scores and mental disorders and symptoms; (5) the associations between the MHT and its pillars and the type of mental disorder, the severity of the principal diagnosis, psychotherapy during care, pharmacotherapy during care, and the number of self-reported mental disorders, after adjusting for socioeconomic factors; and (6) the relationship between mental health and combinations of psychotherapy and pharmacotherapy.

Methods

Sample and procedure

A cross-sectional, case-control design was employed to measure mental health and mental disorders. Data were gathered between 22 April 2022 and 2 February 2023 from four healthcare facilities under the following conditions. In the Department of Psychiatry and Psychotherapy of Semmelweis University, data collection took place among inpatients after their medication had been adjusted (1.5 to 2 weeks after admission). Patients at the Community Psychiatry Centre of Semmelweis University filled out a self-administered questionnaire during their first medical examination. Data from outpatients at the Psychosomatic Center of the Institute of Behavioural Sciences of Semmelweis University were gathered during the patients’ third therapy session. Data were collected from inpatients at the National Institute of Mental Health, Neurology, and Neurosurgery at the Nyírő Gyula Hospital after the adjustment of their medication (1.5 to 2 weeks after admission), and from outpatients during their third therapy session. Ethical approval (ethical permission number: IV/2423-3/2022/EKU) was obtained from the national Medical Research Council. The study was conducted in accordance with the relevant guidelines and regulations. Informed consent was obtained from all the participants. The sample received the information statement, consent form, and questionnaire in paper format. In a separate document, the patient’s psychiatrist or clinical psychologist provided information about the diagnosis of the patient’s mental disorder(s), the severity of the presenting symptoms, and the patient’s pharmacotherapy. The inclusion criteria were: (1) age: 18–80 years; (2) voluntary participation; and (3) diagnosis with (a) mental disorder(s). The exclusion criterion was a condition that impaired cognitive function and prevented the completion of the questionnaire. A total of 331 patients (140 male, 188 female, and 3 who preferred not to disclose their gender), aged M = 42.5 (SD = 15.9), participated in the study. Further sociodemographic indicators of the sample are presented in Table 1.

Table 1 Sociodemographic characteristics of the participants (n = 331).
Full size table

Measures

Participants received a printed, 226-item self-report questionnaire. Fourteen questions referred to sociodemographic data. Twenty-seven questions measured general mental and physical health with single items. One question assessed the proportion of the respondent’s recent positive experiences. Participants reported: (1) if they thought they had (a) mental disorder(s); (2) what symptoms they experienced and how intensely; and (3) whether they had ever been diagnosed with a mental disorder. The instruments used were the Mental Health Test13,14; the Global Well-being Scale15; the PERMA-profiler27; the Psychological Well-being Scale3; the Satisfaction with Life Scale28; the Positivity Scale6; and the Symptom Checklist-90, revised29. Details of the measures are given in Supplementary Table 1. Each respondent’s psychiatrist or clinical psychologist was asked to provide a paper-based report on the patient, including: (1) the name of the patient’s mental disorder(s) according to DSM-530 or ICD31, depending on the institution’s protocol; (2) the severity of the symptoms; and (3) the patient’s pharmacotherapy.

Statistical processing

Regarding our analytical strategy, we rely on several commonly employed methods. First, for analyses related to structural validity, we employed confirmatory factor analysis (CFA) consistent with the analyses described in the original article introducing the MHT14. We chose a robust method for model fitting (maximum likelihood mean variance, MLMV) in CFA, which provides a good alternative to the traditional ML method requiring multidimensional normality32. Furthermore, we calculated two reliability measures for the proposed subscales, namely, Cronbach’s alpha and McDonald’s Omega33. Second, to assess intercorrelations between the subscales or between the scales and other variables, we calculated both Pearson’s product-moment and Spearman’s rank-based correlation coefficients. If normality is violated (noted under the tables) which results in large differences between the two measures34 then Spearman coefficients are used, otherwise all results are based on the former. To examine differences between sociodemographic groups, we employ robust t-tests (which account for unequal variances, see the study by Derrick, Toher and White35 if normality is confirmed (noted under tables), and one-way ANOVAs36. Finally, we conclude our examinations with multivariate ordinary least squares linear regression models37, where the dependent variables are the MHT scales. We check for the violation of the OLS linear regression assumptions using visual methods37. All calculations and results are available from the authors.

Results

Structural validity

Confirmatory factor analysis (CFA) was performed with R and ROP-R38. The values obtained indicated a good fit for all indicators. The most important results are summarized in Table 2.

Table 2 The main model fit indices in confirmatory factor analysis of the five-factor model of the MHT on a clinical sample.
Full size table

Table 3 shows the alpha and omega values with 95% confidence intervals, with all subscales showing acceptable internal consistency.

Table 3 Measures of reliability for the subscales of the MHT.
Full size table

The intercorrelations of the subscales (see Table 4) indicate that in the clinical sample, the MHT subscales have a strong positive relationship with very large effect size (r = 0.43–0.61, p < 0.001), with two weaker but still significant correlations with small and medium effect sizes (r = 0.19 and 0.26, p < 0.001)39. In two instances, the scores for the subscales were not associated with each other: our data suggest that savoring and creative and executive efficiency are not related to self-regulation in the clinical sample. Descriptive statistics of the MHT subscales are shown in Supplementary Table 4, descriptive statistics of the single items of the MHT are shown in Supplementary Table 5. Density plots for MHT subscales are shown in Supplementary Figure 1.

Table 4 Intercorrelations of the MHT subscales.
Full size table

External and content validity

For the analysis of content validity, we estimated the (Pearson) correlation between the five MHT subscales and the previously described instruments (see Table 5; descriptive statitistics of the other instruments used in the study are shown in Supplementary Table 2; measures of reliability for the other instruments used are shown in Supplementary Table 3). A statistically significant relationship was observed between the subscales of the MHT with the mentioned well-being, mental health, and mental disorder symptoms measures. The absolute values of the correlations ranged between 0.19 and 0.79, with most showing a moderate to very strong level of association. One exception was the correlation between positive experience (%) and self-regulation (r = 0.10), where the relationship was not significant (p > 0.05). Overall, it can be concluded that the MHT subscales perform well with other indicators related to mental health and mental disorders in a clinical sample.

Table 5 Correlation of subscales with other well-being scales and measures.
Full size table

Results with sociodemographic indicators

Turning to the practical use of the MHT, we first conducted tests to examine whether the MHT is related to any sociodemographic indicators (see Table 6). Our results suggest that in the clinical sample, the overall MHT score, defined by the average of the scores for the five MHT subscales, is not related to the patient’s gender, age, relationship status, number of children, religiosity, or work-related absence. A difference is present in the case of employment (p = 0.03), as employed individuals have a higher mean MHT score (3.41) compared to those not in employment (3.21). In terms of educational level, the mean difference between individuals with primary (2.97) and tertiary (3.45) education is significant (p = 0.001).

Table 6 Difference in MHT scores by sociodemographic indicator.
Full size table

In contrast to sociodemographic indicators, the MHT score is associated with a wide variety of indicators related to bodily symptoms and physical health (see Table 7). The correlations imply that a higher MHT score is significantly related to the lower prevalence of weakness (r =  − 0.33), dizziness (r =  − 0.19), tiredness (r =  − 0.33), nausea (r =  − 0.20), headaches (r =  − 0.14), fainting (r =  − 0.14), muteness (r =  − 0.16), loss of sensation (r =  − 0.19), and amnesia (r =  − 0.29), and higher subjective health (r = 0.39), general physical health (r = 0.44), and well-being (r = 0.44).

Table 7 Correlations of MHT score with reported bodily symptoms and physical well-being.
Full size table

The MHT scores also perform well in association with mental disorders and symptoms (see Table 8). The average MHT score among those with a self-reported (3.14 compared to 3.76) or diagnosed (3.18 versus 3.54) mental disorder is significantly lower, and a higher number (r =  − 0.34, p < 0.001) and greater severity (r =  − 0.15, p = 0.025) of self-reported mental disorders are related to lower overall mental health. Additionally, significant correlations imply that those with higher MHT scores in the clinical sample experienced a lower prevalence of worrying (r =  − 0.32), nervousness (r =  − 0.41), stress (r =  − 0.37), and restlessness (r =  − 0.32), and enjoyed better general mental health (r = 0.58).

Table 8 Association between MHT score and mental disorders and symptoms.
Full size table

Relationship between psychopathological characteristics and mental health capacities

In the final part of our analysis, we departed from bivariate analyses and fitted multivariate linear (OLS) regressions to investigate the relationship of disorder type, severity of principal diagnosis, psychotherapy during patient care, pharmacotherapy during patient care, and number of self-reported mental disorders with the MHT and its subscales in the presence of socioeconomic controls (see Table 9; the intercorrelations of the SCL-90-R subscales are shown in Supplementary Table 6). Significant associations were found between overall MHT score and unipolar depression and number of mental disorders. Compared to patients with addictive disorders, the MHT score of patients with unipolar depression was 0.44 points lower. Moreover, each additional self-reported mental disorder lowered the MHT score by 0.17 points.

Table 9 Linear regression model of MHT score and subscales (base models).
Full size table

Models for the subscales yielded additional insights. Compared to the reference group (addictive disorders), those with personality disorders (b =  − 0.62) and unipolar depression (b =  − 0.56) had lower global well-being scores. Severity was also a key factor for global well-being, compared to a mild principal diagnosis: those with moderate (b =  − 0.52) and severe (b =  − 0.89) diagnoses had lower scores. The effect of the number of self-reported mental disorders (b =  − 0.23) was similar to that of the overall MHT. In the case of savoring, the only significant association was found with unipolar depression (b =  − 0.78), which is connected with reduced savoring capacity. Similarly, only one variable—number of self-reported mental disorders—was significantly negatively associated with self-regulation (b =  − 0.17). Finally, the psychological resilience score was negatively associated with anxiety and somatization disorders (b =  − 0.57), unipolar depression (b =  − 0.84), and number of self-reported mental disorders (b =  − 0.27), but positively related to pharmacotherapy (b = 0.59). The model for creative and executive efficiency did not fit our data.

In addition to the main models presented above, we fitted additional models with an alternative psychotherapy and pharmacotherapy specification (see Table 10). As other effects were unchanged, they are not presented again. The results show that combinations of psychotherapy and pharmacotherapy are positively related to the overall MHT, and to the creative and executive efficiency and psychological resilience subscales. Compared to patients receiving neither psychotherapy nor pharmacotherapy during their care, those receiving psychotherapy but not pharmacotherapy had a significantly higher MHT score (b = 0.87). For the creative and executive efficiency subscale, the combinations are especially important: receiving therapy without medication (b = 1.96), medication only (b = 1.81), or a combination (b = 1.59) significantly improved score. For psychological resilience, only therapy without medication was found to be a significantly positive factor (b = 1.46).

Table 10 Linear regression model of MHT score and subscales with psychotherapy–pharmacotherapy combinations.
Full size table

Discussion

The present study aims to examine the reliability and validity of the MHT in a Hungarian adult psychiatric sample and the relationship between mental health competencies and various indicators (sociodemographic characteristics, physical health, mental disorders, psychotherapy and/or pharmacotherapy during care). Confirmatory factor analysis showed a good fit of the five-factor model to the data for the clinical version of the Mental Health Test. High internal consistency coefficients and excellent external and content validity were reported. The test is not sensitive to sociodemographic indicators but is sensitive to the correlates of well-being and to the symptoms of different types of mental disorders. Our findings suggest that the Mental Health Test is a suitable measure for assessing mental health capacities in psychiatric samples.

The test is innovative in several ways, particularly in the clinical setting, compared to previous tests. First, it is based on the Maintainable Positive Mental Health Theory (MPMHT). One of the key messages of this concept is that there are various competencies behind the different components of mental health unlike previous measures which define mental health in terms of observable characteristics of well-being or as a mirror opposite of mental disorders. The MPMHT captures not just one (e.g. resilience9, social well-being40, coping41, but all of the essential aspects of mental health as defined by the World Health Organization12 and classical mental health theories. The identified main pillars of positive mental health—global well-being, creative and efficient coping, savoring capacity, resilience, and dynamic self-regulation—are competencies that can be trained, improved, and strengthened by their nature. This multidimensional approach, that channels five scales into a comprehensive framework shows conceptual similarities with recent transformative mental health models e.g. pivotal mental states model42. The MHT covers a wide spectrum of mental health measures and suitable for the comprehensive assessment of the individual's mental health competencies. The short completion time, the self-test design can provide the opportunity for a quick-and-easy assessment even in time-pressured clinical settings.

Furthermore, on the basis of this assessment, with precisely targeted interventions or even with self-help activity, people living with mental disorder(s) can establish a balance between their own physical and mental status and their social environment, and they can also create a sustainable optimization of personal and social functioning (self-regulation) and an equilibrium of positive and negative emotions (coping, savoring). It may also increase the level of spiritual connectedness, sense of coherence43, and ultimately global functioning14. This shift in perspective aligns with the growing recognition of the importance of promoting positive mental health and well-being (Supplementary Fig. 1).

Limitations

Firstly, the validation was carried out on a convenience sample, thus the resulting sample is not representative of patients in the participating healthcare facilities. Furthermore, measurement invariance could not be tested due to the small sample size in the subsamples. Like all self-report questionnaires, the MHT is, to a certain extent, liable to the conscious and unconscious response tendencies of the respondents. In addition, since participation was voluntary, more severe cases were not represented, while various factors related to personality, illness, and attitude, as well as factors related to mental well-being, are likely to have influenced willingness to participate. Additionally, the intercorrelations of the MHT subscales are very high, which is due to the fact that the scales of the MHT are inspired by previous measures (e.g. the Global Well-being subscale was derived from the Global Well-being Scale15). Despite that, the advantage of the instrument is the comprehensiveness that results from its multidimensionality. It measures five mental health competencies and an average indicator which provides a more individualistic insight into the functioning of a person’s mental health competencies. Another limitation is that the measure shows strong positive correlation with other well-being and mental health scales and instrument. This may result from the fact that quantitative scales cannot capture such subtle differences in a person’s mental health characteristics, which can be crucial in therapeutic practice, for example. Finally, in the analysis of the interrelationships between combinations of psychotherapy and pharmacotherapy and mental health, it would be worth filtering out the covariate effect of type of care.

Conclusion and consequences

In summary, our preliminary results suggest that the MHT is a suitable measure for assessing mental health competencies and resources in psychiatric samples. Exploring the positive dimensions of people living with mental disorders is not only of theoretical importance but also has purposeful practical consequences. Firstly, it reveals the foundations on which a rehabilitation professional group can build in order to achieve positive life goals (including destigmatization and reducing self-stigma), where the goal is not necessarily symptom reduction but improving quality of life and the restoration of everyday functionality to the fullest extent possible. Secondly, and as a result of the above, it can propose a new paradigm for therapy which not only focuses on treating symptoms and maximizing adaptation level, but also puts a huge emphasis on the empowerment of the patients. Thirdly, it may have health-related and economic significance, since people living with mental disorders may be helped to recover their functions more quickly, enabling them to return to social productivity sooner. It can also provide an opportunity to embrace disability as part of human experience and to support patients based on their existing psychological competencies.