Introduction
Modern humanities are confronted with a fundamental challenge: how to transform the growing number of psychometric data into reliable knowledge about the factors influencing human mental well-being (Bainbridge, 2024). Two decades ago, collecting and analyzing such data was an extremely labor-intensive process, requiring significant resources. However, the development of information and communication infrastructure, mobile devices, and social media has fundamentally expanded the capabilities of researchers. Today, we have unprecedented access to data on the psychological state of large population samples.
This has led to the emergence of a new research paradigm: instead of classical experiments with strict control of variables, psychology can rely on observations of natural behavior and psychological characteristics of people in their everyday environments (Newson et al., 2024). Big data technologies are specialized tools designed to analyze massive datasets that cannot be handled manually. At the same time, the passive nature of data collection minimizes the influence of the experimenter—a problem that has historically complicated psychological research.
Along with the development of methodological approaches, significant progress has been made in statistical analysis and artificial intelligence. Machine learning and deep learning methods are actively used in healthcare to predict and identify hidden patterns. However, psychological sciences have been slower to adopt these tools, although their potential in this field is particularly significant.
However, mention should be made of the existence of a well-known problem, i.e., the reproducibility crisis in psychology (Open Science Collaboration, 2015). Attempts to replicate classical psychological experiments have yielded similar results in only 39% of cases. This figure indicates systematic problems in psychological methodology. One hypothesis is that the transition to observational methods based on big data, which eliminate the active role of the experimenter, can significantly improve reproducibility.
Finally, the issue of mental health monitoring is becoming critically important in the information age. Personalized information tools (such as social media and algorithmic news feeds) can trigger the formation of biased perceptions and mental disorders, including long-term depression. Therefore, regular diagnostic assessment of both individuals and social groups becomes not merely desirable but essential (Bainbridge, 2024).
The aim of this paper is to examine the challenges and potential applications of big data methods for identifyi statistically significant relationships between various parameters and mental state, to formulate hypotheses for further research, and to provide a basis for practical applications in pedagogy and psychological support.
Practical application: diagnostics and resocialization of teaching staff
Modern Russian education is undergoing a comprehensive process of modernization, which involves the introduction of innovative approaches into educational practices at various levels, as well as the implementation of new trends and transformations aimed at addressing current challenges and priorities.
Effective implementation of educational objectives largely depends on the development of professionally significant characteristics of teaching staff, as well as on the sharpening of competencies and personal psychological traits relevant to their professional activities.
The use of the digital technologies analyzed aligns with state policy objectives (Decree of the President of the Russian Federation of July 21, 2020 No. 474 “On the National Development Goals of the Russian Federation through 2030,” Order of the Government of the Russian Federation of December 31, 2019 No. 3273-r, “Concept for the Training of Teaching Staff for the Education System through 2030,” etc.). According to these objectives, the teaching staff training system must address modern challenges by integrating technology-driven solutions, including digital transformation of the economy and public life. This entails the implementation of educational and diagnostic digital services to support the acquisition of skills in blended learning and design, as well as to master digital educational resources and other digital competencies among both prospective and practicing specialists. Moreover, modern teacher training programs must rely on the increased use of electronic educational environments in educational institutions, including various digital services for students and teachers; actively incorporate digital content and platform-based solutions in modern digital school; utilize big data tools in professional activities; develop and implement new master’s programs aimed at training teachers capable of creating technological and content-driven digital solutions for modern schools; and apply digital diagnostic tools for both pedagogical and psychological purposes. Work in this area involves conducting large-scale research aimed at identifying potential needs of the labor market and education sector, as well as psychological-pedagogical studies focused on identifying patterns in the development of children, adolescents, and young adults, along with the professional and other types of well-being of adults.
Currently, a new social group has emerged in Russian society—participants and veterans of special military operations. This group is of scientific interest from the perspective of psychological, social, and pedagogical research. This research allows for the collection of up-to-date data on significant social phenomena and processes, supports forecasting of social trends and risks, facilitates the effective implementation of social policy objectives, and creates the conditions for the successful adaptation and resocialization of military personnel. Note that psychological research is becoming a key approach to rehabilitating and supporting veterans and combat participants, necessitating the search for effective diagnostic tools to address a wide range of research tasks.
It should be noted that the work of modern teachers is characterized by a high level of intensity and diverse workloads, which places increased demands on stress tolerance and resilience and increases the risk of psychological well-being and health problems. Timely identification of risks to teachers’ health is a pressing issue requiring optimal solutions, particularly because seeking professional help from psychologists remains relatively uncommon among teaching staff. Conducting psychological diagnostics using digital technologies makes it possible to collect psychologically significant data from respondents in a short period of time and in a respondent-friendly format, process it, and build targeted psychological work. The solution to such problems is especially relevant due to the fact that the ranks of modern teaching staff are replenished with teachers from among veterans of special military operations, many of whom, after returning to civilian life, are at the stage of professional reorientation in new life conditions. Veterans who have no contraindications to teaching and demonstrate an interest in educational work are a valuable resource. This teaching potential requires identification, implementation, and provision of appropriate specialized training programs, in particular in the subject “Fundamentals of Security and Defense of the Homeland,” which involves the competencies possessed by this group of specialists (self-defense skills, survival in natural conditions, first aid, orientation, etc.). A fundamentally significant aspect of this social group’s readiness for teaching is their psychological preparedness and the absence of any mental or psychological impairments. Technologies are needed that allow for the identification of professionally significant characteristics and the absence of contraindications to teaching during the professional selection process. The technologies discussed in this paper make it possible to achieve this goal not only through targeted, individual work but also through large-scale diagnostic procedures, which can be conducted among former military personnel to identify their pedagogical potential and readiness for teaching, educational, and outreach activities with children and youth, including latent ones.
Currently, various studies are actively being conducted on these respondents. Because this understudied social group is characterized by a number of characteristics, professional potential, and specific educational and social needs, it is essential to select, adapt, and develop comprehensive diagnostic materials, tasks, and methodologies. Given that participants and veterans of special military operations represent a large group whose numbers are expected to increase as hostilities continue, research methods based on big data are becoming increasingly important. Since such studies have not yet been conducted for the respondents in question, we present an example of a standard study, which determines the possibilities and prospects for its application to the targeted group and the research subject.
Because the research process is complex, we will consider possible limitations in this area.
Subject-specific and conceptual limitations of the study. In this study, personal and demographic parameters are examined in relation to psychological well-being. These parameters in veterans of special military operations have unique characteristics. Research into personal and demographic parameters is important for any systematic study. However, for example, in the field of education, they are of primary importance for the development of both professional retraining programs and the assessment of readiness for teaching, as a certain percentage of special military operation veterans choose a new career path after completing their military service, including teaching. This social group is differentiated by educational level and personality traits, the impact of combat experience on which requires long-term study.
Thus, with the data presented in the examples, the educational level is shown to influence psychological well-being and stress resilience. Among veterans engaged in teaching, the educational level varies significantly, with differences in age, learning ability, flexibility, emotional, personal, and behavioral adjustment, and readiness to assume the role of a student and a novice professional. Heuristically, we can assume that the results of the study will not differ for this social group. However, this hypothesis requires verification, as statistically significant differences are likely to be identified, which underlies effective utilization of the research methods in question. In particular, as noted, the Big Five model allows for the assessment of significant personality traits, such as agreeableness (i.e., the ability to adaptively respond to situations and avoid conflict) and openness to experience, which is of interest in relation to the veterans’ transition to a new professional field.
In this case, demographic variables are important for assessing personal well-being, because such factors as demographic stability and security—the presence of family, supportive relatives, etc.—help veterans cope with challenging, difficult, and extreme life situations.
In implementing psychological and pedagogical support programs for veterans, research into pronounced and latent negative emotional states is important. These states not only represent potential risks but also may persist and even re-emerge after rehabilitation. However, this does not exclude recurrence, especially in new stressful conditions, and requires long-term observation. For example, possible manifestations of anxiety, associated with a transition to a new professional activity and changes in life in general, require special attention; stress reactions, as the work of a modern teacher is excessively demanding, require collaboration closely within a pair (a person-to-person dyad). From the perspective of the essence approach, this inherently involves stress factors that teachers must be able to constructively overcome and mitigate.
In applying the data and methods discussed, some research limitations should be outlined. These limitations include the possible data incompleteness, the lack of fully developed and targeted diagnostic tools to account for all the characteristics of this social group, and the high variability of individual characteristics, which, although generalizable, still require direct measurement, a targeted approach, and the development of a mechanism for classifying and systematizing the obtained data.
Quantitative indicators may also represent a limitation. For example, during integration into the education system at this stage, it is quite difficult to track the exact proportion of veterans who have chosen a profession related to working with children. This is due to the absence of a unified registry of veteran teaching staff, and their professional retraining in this area is carried out continuously by educational organizations across various regions. As a result, on the one hand, the researcher is dealing with a small sample of respondents, but on the other, he may not be able cover the full diversity of potential respondent in the study.
Qualitative limitations include the following. Since this is the first time attempt to study the social group in question, the researcher must select information and data that are scientifically meaningful. This involves identifying and defining relevant qualitative characteristics and indicators, as well as developing criteria aligned with the research objectives.
Noteworthy are also the moral and ethical limitations. Given the life, personal, and professional experience of participants and veterans of special military operations, there are a number of questions that cannot be asked, or that respondents have the right not to answer, because these questions may inadvertently violate ethical principles or fall either inside or outside the boundaries of moral assumptions.
The main limitation is that the study presupposes a complete and honest response from the respondent, which in real-life situations may not coincide with expectations, thereby qualitatively and quantitatively affecting the data obtained. This situation can arise either intentionally or unintentionally, for example, when a respondent expresses a subjective assessment or opinion. A larger sample size and a longer research period will help overcome these limitations.
Given the limitations and missing information, the use of heuristics based on the researchers’ scientific and practical experience, their ability to apply it effectively, and their deep knowledge of the subject matter can be a useful tool. Thus, several hypotheses can be formulated simultaneously, which can be verified or refuted using objective research methods. In this case, the researcher can act in one of two predetermined ways: when the problem is unknown and yet to be identified; or when the researcher recognizes the problem but cannot claim it without evidence that requiring validation with scientifically supported data. These opportunities allow one to overcome stereotypical perceptions of a given situation and tap into its resources and potential.
We should note another feature that arises in this context. A person’s psychological and mental state is a dynamically changing process, requiring prolonged observation and periodic assessment.
Given that the analysis of statistically significant data using big data technologies reveals the influence of components such as educational level, family status, and others on psychological well-being, it is of interest to determine the status of future or current teachers who are veterans of special military operations. Note that, in terms of the parameters significant for psychological well-being, this social group is at risk due to the specific nature of their previous professional activities, the presence of high risks to life and health, infrequent communication with family, limited time spent at home, etc. Education also appears to be unstable in these respects. Most of the specialists in this group with bachelor’s degrees in non-educational fields can become teachers through advanced training or postgraduate certificates. Under these conditions, future teachers experience certain professional deficiencies, the presence of which can cause anxiety, generate professional insecurity, serve as a prerequisite for conflict, lead to professional failure, reduce motivation, and so on. Combined with other negative factors, these deficiencies can adversely affect the psychological health of specialists and influence their decisions, including those related to leaving their new profession. Early identification of potential problems using modern technologies, including big data, will facilitate the study of current issues and create conditions for the successful resocialization of this group of teachers.
Given the novelty and relevance of this issue, we emphasize once again the urgent need for specialized research into the development of various types of readiness for teaching among veterans of special military operations. In this case, important factors include cognitive and personal characteristics, analysis of professional predisposition, communication skills, goal-setting and life prospects, the development of social expectations, parameters of the need-motivational sphere, emotional stability, and the well-being of the emotional, volitional, and other spheres. The technologies under consideration will be in high demand for obtaining both individually oriented data and mass statistical data, enabling significant personnel, organizational, and managerial decisions, including at the national level. The insufficient representation and predominant absence of data on the relevant characteristics of the job descriptions of teachers among veterans of special military operations in scientific theory determine the high level of relevance of these technologies, which allow for the collection and processing of large volumes of scientifically significant information and data, as well as their scientific specification and visualization. Note that such technologies not only allow for statistical analysis but also provide information on significant relationships when analyzing massive psychometric datasets.
Modern school education is becoming increasingly technologically advanced: digital technologies are used in teaching lessons, assessing children’s performance, and interacting with parents. Each teacher is tasked with conducting psychological, pedagogical, and educational assessments before and after teaching children. This procedure is labor-intensive, as the scope of competencies, such as those in the field of security, is multifaceted, encompassing knowledge of social, domestic, road, military, psychological, and other areas of security, and is associated with significant time expenditures. These technologies allow one to optimize data processing and collection, to collect accurate diagnostic information, and to integrate this information into both pedagogical and psychological work.
Thus, the active use of these resources, including big data, is relevant both for solving scientific problems in education and psychology and for everyday practical activities. Moreover, when working with children and young people of various age groups during the educational process, these resources may help realize and develop the teaching staff’s potential and provide their psychological and pedagogical support. It is essential that all researchers are proficient in modern technologies for collecting, processing, and visualizing data; in fact, they must be adequately informed about variations and types of these methods and be able to combine traditional and innovative technological approaches to solving scientific and practical problems.
Conclusions
The professional sphere has a differentiated impact on mental health, including in the field of education, where there is a poorly studied social group of teaching staff undergoing a stage of resocialization.
The passive collection of psychometric data represents a new paradigm in psychological research, promising more reliable and valid results compared to traditional experiments.
The practical application of these methods is critically important for organizing psychological and pedagogical support for teaching staff, including veterans of special military operations, who are transitioning to civilian activities.