WCP 2025

Introduction: Contemporary psychological practice is facing an increasing number of requests related to psychospiritual and psychoreligious problems, which arise from various factors including inadequate spiritual practices and sociocultural changes. In this context, religiously-oriented psychocorrection (ROP) emerges as an innovative method capable of addressing the specific needs of religious individuals whose problems are often linked to altered states of consciousness (ASCs) and a departure from traditional moral and spiritual values.
Objective: To reintegrate believers into their spiritual community, restore their connection with religious values, and facilitate a renewed understanding of their faith. ROP is effective in addressing spiritual crises caused by both negative ASCs and violations of moral principles.
The ROP concept is part of I.E. Sokolovskaya’s psychological dissertation research on "The Social Psychology of Religious Identity in Contemporary Russian Youth" (2015).
ROP, a method of spiritual healing, includes recommendations for constructive problem-solving in the spheres of interethnic, intercultural, and interfaith relations, the prevention of religious extremism, and facilitating the socio-psychological adaptation of young people in their personal and professional lives.
Methodology: ROP is aimed at harmonizing the bodily, mental, and spiritual resources of the individual, based on the concept of spiritual healing described in I.E. Sokolovskaya's dissertation research, as well as on the transpersonal concepts of W. James, R. Assagioli, C. Jung, S. and C. Grof, A. Maslow, V.V. Kozlov, and S.A. Belousov.
Psychospiritual (PSP) and psychoreligious (PRP) problems often arise from a conflict between religious beliefs and the modern world, as well as from a misunderstanding of spiritual practices. A departure from ethical principles, moral norms, and spiritual laws frequently leads to maladjustment and psychological distress, manifesting in ASCs.
Results: The uniqueness of religiously-oriented psychocorrection differentiates this method from general psychotherapy by considering the confessional affiliation of clients and integrating spiritual practices.
ROP is already being implemented in educational institutions, demonstrating its recognition and promise, for example, within some practical disciplines in the training of clinical psychologists in Higher Education Institutions in Moscow, as well as in the training of students at the Academy of Innovative Psychocorrection and Scientific Research.
Conclusion: The presented analysis of the ROP method shows its significance for the psychological correction and spiritual development of religious individuals. The multi-level approach enables the resolution of complex issues related to the harmonization of an individual’s inner world and their adaptation to modern society.

In essence, politicians are employees of the citizens who have to pay for their services and in democracies are enabled to elect them in elections. This is why politicians should keep an eye on the well-being of their employers.
The identification of essential human psychological needs makes it possible to define the desirable core goals of politics. These include human relationships, active conduct, sense of coherence, and healthy stress levels. A political system should guarantee its people freedom and support in these four basic needs.
In addition, understanding psychodynamics makes it possible to prevent spirals of regression, which tend to lead to violence and catastrophe, in times of heightened stress in society.
Education in basic psychodynamics on all levels of society is required to enable progress towards a world of psychologically mature, responsive, and self-determined citizens.

Introduction This research aims to integrate artificial intelligence technology, particularly automated machine learning methods, into psychological research to address the limitations of traditional frequentist statistical approaches in handling nonlinear relationships of psychological characteristics. Current psychological research predominantly relies on regression-based methods, which often fall short in capturing the complex nonlinear relationships between psychological features. We propose an innovative semi-automated workflow that empowers psychology researchers to leverage machine learning algorithms for intelligent model selection, facilitating the construction of more precise and insightful theoretical frameworks.

Methodology We designed a low-code workflow based on AutoGluon, specifically tailored for psychological research methodologies with high accessibility. This approach encompasses three primary research objectives:
1. Automated hyperparameter tuning to attain optimal models.
2. Identification of important features through interpretability techniques, facilitating feature selection based on calculated importance.
3. Theoretical reconstruction based on important features by integrating exploratory factor analysis with machine learning interpretability.
Using psychological resilience research as an example, we provide a detailed annotated code workflow along with raw data to demonstrate the application of this method.

Results The workflow successfully implements automated machine learning model selection and optimization, effectively identifying key features in psychological resilience research. Through interpretability techniques, we quantify the relative importance of different features, providing a data-driven basis for feature selection. Combined with exploratory factor analysis, we reconstruct theoretical frameworks that more accurately reflect the nonlinear relationships among psychological characteristics.

Conclusion The semi-automated workflow proposed in this study provides psychological researchers with a practical tool to better understand nonlinear relationships between psychological characteristics. This low-code approach lowers the barrier for psychological researchers to utilize advanced machine learning techniques, offering new possibilities for data-driven psychological theory construction. Future research can extend this methodology to additional psychological research domains and integrate more types of data, such as text, audio, and images.