Journal of Applied Research in Psychology and Artificial Intelligence (JARPAI) advances applied psychology by publishing research that leverages psychological theories, methods, and evidence to address real-world challenges across diverse contexts. The journal emphasizes research with clear practical relevance, implementation value, and societal impact, while offering a distinct venue for scholarship that extends beyond purely experimental work in academic psychology. It provides a platform for the exchange of ideas, methods, and empirical findings related to the understanding, assessment, and enhancement of psychological processes, behaviors, and interventions in educational, organizational, clinical, social, and community settings. It particularly welcomes contributions that develop or apply innovative theory-driven approaches, rigorously evaluate psychological tools and interventions, and examine their effectiveness, user experience, and practical implications. Submissions that engage with the social, organizational, cultural, and ethical dimensions of psychological applications are also encouraged.
JARPAI considers original empirical research (quantitative, qualitative, and mixed-method designs), applied design and evaluation studies (including project descriptions and evaluations), systematic literature reviews (including meta-analyses) and methodological reviews, as well as theoretical or position papers that build on existing research and offer significant contributions.
Priority is given to longitudinal inquiries and multi-site trials that address the ecological validity of AI in psychology. The journal particularly values research that validates the scalability and generalizability of AI applications across diverse psychological contexts and demographics.
Consequently, manuscripts must demonstrate clear relevance to psychological inquiry and practice, supported by appropriate theoretical grounding and rigorous empirical validation; submissions that do not meet these expectations fall outside the scope of this journal.
Key areas of interest include, but are not limited to, the following:
- AI-Supported Psychological Assessment and Intervention: Research on AI-enabled tools for psychological assessment, screening, monitoring, intervention, and feedback, particularly studies demonstrating effectiveness, validity, and applicability across real-world psychological settings.
- Human–AI Interaction in Psychological Practice: Empirical studies examining how AI systems support decision-making, communication, and service delivery in counseling, clinical, educational, organizational, and community psychology contexts.
- Behavioral, Cognitive, and Affective Analytics: Research using behavioral, cognitive, or emotional data to inform psychological understanding, prediction, and intervention, especially where findings are validated across populations, contexts, or time.
- Generative AI in Psychological Inquiry and Practice: Studies investigating the use of generative AI and large language models in psychologically relevant tasks, provided they are grounded in psychological theory and supported by rigorous empirical evaluation.
- Equity, Inclusion, and Diversity in AI Applications: Research evaluating the fairness, accessibility, cultural responsiveness, and cross-demographic applicability of AI-supported psychological tools and services.
- Ethics, Trust, and Responsible AI in Psychology: Empirically grounded studies on transparency, bias, explainability, privacy, trust, and responsible implementation of AI in psychological research and practice.
- Scalability, Generalizability, and Ecological Validity: Longitudinal, multi-site, and real-world investigations that examine whether AI applications in psychology can be sustained, scaled, and generalized across diverse settings and populations.
- Implementation, Policy, and Professional Practice: Research on adoption, governance, implementation strategies, and system-level integration of AI in applied psychology, particularly where practical impact is demonstrated.