Su, Kuan‐Pin

Background Subjective cognitive decline (SCD) is a preclinical condition associated with an increased risk of dementia and Alzheimer’s disease, with no consensus regarding effective therapeutic interventions to date. As the global burden of aging-related neurodegenerative diseases continues to rise, early intervention has become increasingly critical. Cognitive training has been proposed as a promising behavioral intervention; however, few studies have integrated multimodal assessments to elucidate its underlying neurobiological and psychological mechanisms, particularly within the educational system that shapes cognitive reserve and learning strategies across the lifespan. This pilot study aims to estimate effect sizes for future definitive trials, assess the feasibility and acceptability of the intervention and multimodal evaluations, and generate hypotheses regarding the relationship between recitation practice and clinical biomarkers. Methods A total of 60 individuals with subjective cognitive decline will be enrolled in a randomized, assessor-blinded, controlled pilot study. Participants will be randomly assigned to either an intervention group or a non-active control group prior to baseline assessment. The intervention group will undergo a six-month structured recitation training program. Both groups will undergo short-term follow-up after the intervention, and long-term follow-up annually post-intervention. Multimodal assessments will include neuropsychological testing, functional magnetic resonance imaging (fMRI), electroencephalography (EEG), blood biomarker profiling, gut microbiota analysis, and fecal metabolomics. Discussion This study protocol outlines a randomized, assessor-blinded, controlled pilot study designed to advance understanding of the feasibility of Chinese Classics recitation training on both physiological and psychological outcomes in individuals with subjective cognitive decline. The findings are expected to provide mechanistic insights into non-pharmacological interventions and to address the current underrepresentation of Asian populations in neuroscience research. Clinical trial registration We registered this randomized controlled trial on ClinicalTrials.gov on March 11, 2026, under the identifier NCT07463391.

Objectives Generative artificial intelligence (GAI) tools can enhance the quality and efficiency of medical research, but their improper use may result in plagiarism, academic fraud and unreliable findings. Transparent reporting of GAI use is essential, yet existing guidelines from journals and institutions are inconsistent, with no standardised principles. Design and setting International online Delphi study. Participants International experts in medicine and artificial intelligence. Main outcome measures The primary outcome measure is the consensus level of the Delphi expert panel on the items of inclusion criteria for GAMER (Rreporting guideline for the use of Generative Artificial intelligence tools in MEdical Research). Results The development process included a scoping review, two Delphi rounds and virtual meetings. 51 experts from 26 countries participated in the process (44 in the Delphi survey). The final checklist comprises nine reporting items: general declaration, GAI tool specifications, prompting techniques, tool’s role in the study, declaration of new GAI model(s) developed, artificial intelligence-assisted sections in the manuscript, content verification, data privacy and impact on conclusions. Conclusion GAMER provides universal and standardised guideline for GAI use in medical research, ensuring transparency, integrity and quality.