Reporting Randomised Trials of Physical Exercise or Training Interventions in Older Adults
Year: 2026
Type: article
Abstract: This reporting guideline was developed to address the gap in methodological reporting standards for trials investigating physical exercise or training in older adults, aiming to enhance the quality, transparency, and replicability of such research. The aim is to improve the reporting of key elements, including population characteristics, intervention components [e. g., Frequency, Intensity, Time, Type (FITT) principles, tailoring, use of technology], study design and methods (e. g., recruitment, randomization, statistical analysis), as well as study results, including outcomes and adherence measures. A six-stage process was used to develop this guideline. This included a three-round Delphi process involving experts from a large European network (COST Action PhysAgeNet), a comprehensive literature review of existing reporting guidelines, consensus meetings with international experts, and validation with journal editors who evaluated and refined the guideline. The final PETIO guideline includes an expanded checklist of items to report in the context of physical exercise interventions in older adults. Experts and editors agreed on essential items for improving quality, transparency, and replicability, such as intervention components (FITT) and setting, tailoring aspects, adverse events, and control group specifications. Notably, it was also emphasized that standardized reporting is critical for future meta-analyses and the implementation of future research protocols. The guideline is expected to support researchers, peer reviewers, and journal editors in improving the quality and transparency of research on physical exercise interventions in older adults.
Source: physioscience
DOI: 10.1055/a-2820-8550
Institutions: German Sport University Cologne, University of Münster, Universität Hamburg, University of Nicosia, Inserm, COMETE - Mobilités : Vieillissement, pathologie, santé, Centre Hospitalier Universitaire de Caen Normandie, Cyceron, Université de Caen Normandie, University of Ferrara, University of Geneva, Université de Poitiers, Centre de Recherches sur la Cognition et l'Apprentissage, Academic College at Wingate, Levinsky-Wingate Academic College
Language: German
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7204140967