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Interventions Based on Biofeedback Systems to Improve Workers’ Psychological Well-Being, Mental Health, and Safety: Systematic Literature Review

Background: In modern, high-speed work settings, the significance of mental health disorders is increasingly acknowledged as a pressing health issue, with potential adverse consequences for organizations, including reduced productivity and increased absenteeism. Over the past few years, various mental health management solutions, such as biofeedback applications, have surfaced as promising avenues to improve employees’ mental well-being. However, most studies on these interventions have been conducted in controlled laboratory settings. Objective: This review aimed to systematically identify and analyze studies that implemented biofeedback-based interventions in real-world occupational settings, focusing on their effectiveness in improving psychological well-being and mental health. Methods: A systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed and EBSCO databases for studies published between 2012 and 2024. Inclusion criteria were original peer-reviewed studies that focused on employees and used biofeedback interventions to improve mental health or prevent mental illness. Exclusion criteria included nonemployee samples, lack of a description of the intervention, and low methodological quality (assessed using the Physiotherapy Evidence Database [PEDro] checklist). Data were extracted on study characteristics, intervention type, physiological and self-reported outcomes, and follow-up measures. Risk of bias was assessed, and VOSviewer was used to visualize the distribution of research topics. Results: A total of 9 studies met the inclusion criteria. The interventions used a range of delivery methods, including traditional biofeedback, mobile apps, mindfulness techniques, virtual reality, and cerebral blood flow monitoring. Most studies focused on breathing techniques to regulate physiological responses (eg, heart rate variability and respiratory sinus arrhythmia) and showed reductions in stress, anxiety, and depressive symptoms. Mobile and app-directed interventions appeared particularly promising for improving resilience and facilitating recovery after stress. Of the 9 studies, 8 (89%) reported positive outcomes, with 1 (11%) study showing initial increases in stress due to logistical limitations in biofeedback access. Sample sizes were generally small, and long-term follow-up data were limited. Conclusions: Biofeedback interventions in workplace settings show promising short-term results in reducing stress and improving mental health, particularly when incorporating breathing techniques and user-friendly delivery methods such as mobile apps. However, the field remains underexplored in occupational contexts. Future research should address adherence challenges, scalability, cost-effectiveness, and long-term outcomes to support broader implementation of biofeedback as a sustainable workplace mental health strategy.

Single-cell multiome and spatial profiling reveals pancreas cell type-specific gene regulatory programs of type 1 diabetes progression

Sci Adv. 2025 Sep 12;11(37):eady0080. doi: 10.1126/sciadv.ady0080. Epub 2025 Sep 10.

ABSTRACT

Cell type-specific regulatory programs that drive type 1 diabetes (T1D) in the pancreas are poorly understood. Here, we performed single-nucleus multiomics and spatial transcriptomics in up to 32 nondiabetic (ND), autoantibody-positive (AAB+), and T1D pancreas donors. Genomic profiles from 853,005 cells mapped to 12 pancreatic cell types, including multiple exocrine subtypes. β, Acinar, and other cell types, and related cellular niches, had altered abundance and gene activity in T1D progression, including distinct pathways altered in AAB+ compared to T1D. We identified epigenomic drivers of gene activity in T1D and AAB+ which, combined with genetic association, revealed causal pathways of T1D risk including antigen presentation in β cells. Last, single-cell and spatial profiles together revealed widespread changes in cell-cell signaling in T1D including signals affecting β cell regulation. Overall, these results revealed drivers of T1D in the pancreas, which form the basis for therapeutic targets for disease prevention.

PMID:40929272 | PMC:PMC12422192 | DOI:10.1126/sciadv.ady0080

Organoids in Genetic Disorders: from Disease Modeling to Translational Applications

Stem Cell Rev Rep. 2025 Sep 11. doi: 10.1007/s12015-025-10973-x. Online ahead of print.

ABSTRACT

The emergence of organoid models has significantly bridged the gap between traditional cell cultures/animal models and authentic human disease states, particularly for genetic disorders, where their inherent genetic fidelity enables more biologically relevant research directions and enhances translational validity. This review systematically analyzes established organoid models of genetic diseases across organs (e.g., brain, eye, kidney, lung, and heart), highlighting their pivotal roles in identifying novel pathogenic genes, elucidating disease mechanisms, and advancing therapeutic strategies such as drug screening platforms, gene-editing therapies, and organ transplantation strategies. Furthermore, we critically address current limitations-including challenges in recapitulating complex pathologies and scaling production-while underscoring their potential for personalized medicine through multi-omics integration and bioengineering innovations. Although the scope of "genetic diseases" is broad, this synthesis focuses on disorders with well-defined inheritance patterns, such as monogenic disorders, copy number variations (CNVs), and aneuploidies. Despite covering only a subset of these conditions, this review aims to provide researchers with a comprehensive overview of the field, emphasizing how organoid-based approaches could accelerate both mechanistic discoveries and clinical translation in genetic disease research.

PMID:40931310 | DOI:10.1007/s12015-025-10973-x

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