Original empirical research is submitted through a primary-data or secondary-data route according to the principal evidentiary basis of the study.
JMNS considers experimental, observational, clinical, biomechanical, physiological, performance and neurophysiological studies relevant to its scope. Primary- and secondary-data studies are evaluated according to the same standards of scientific quality, methodological rigor, ethical integrity and relevance.
Use this route when the reported study is based principally on data newly collected for the research. Describe the study design, setting, participants, eligibility criteria, procedures, outcomes, instrumentation and acquisition protocol with enough detail for critical appraisal and, where feasible, reproduction.
Use this route when the reported study is based principally on analysis of an existing dataset. Identify the authoritative repository or data source, persistent identifier when available, exact dataset version or release, access date when relevant, applicable licence or access model and any Data Use Agreement governing the data used.
Distinguish the existing data from the new research question, preprocessing, analyses, models and interpretation. Explain record selection, exclusions, missingness, provenance limitations and how the available variables and sample support the stated question. Datasets may be identified through the JMNS Verified Dataset Library or independently; use of a JMNS-listed dataset is optional and gives no editorial advantage.
Methods should allow a qualified reader to understand and, where feasible, reproduce the work. Report study design, setting, participants or sample, eligibility criteria, procedures, outcomes and analytical plan. Provide a sample-size rationale appropriate to the design; do not use retrospective power as a substitute for design rationale.
For electromyography, motion analysis, force platforms, wearables, video, neurophysiology and related quantitative methods, report relevant manufacturer/model information, sensor/electrode/marker placement, sampling settings, synchronization, calibration, filtering, preprocessing, normalization, event or phase definitions, derived variables, quality-control procedures and software/firmware/package versions when material to reproducibility.
Define primary and secondary outcomes when applicable, the statistical unit, handling of repeated observations or clustering, missing-data handling and how model assumptions were evaluated. Report effect estimates with appropriate measures of uncertainty and distinguish confirmatory, exploratory and post hoc analyses.
For machine-learning or predictive studies, separate development, validation and test data appropriately; describe participant-level or sample-level splitting, class imbalance, tuning, calibration, overfitting safeguards, data leakage prevention and external validation when applicable. Use TRIPOD+AI or a more specific reporting guideline when relevant.
Clinical trials must be registered in an appropriate public registry at or before the time of first participant consent for enrollment. Report the registry name and identifier, and include the registration number at the end of the abstract. Trials should follow CONSORT 2025 and relevant extensions.
Manuscripts reporting clinical-trial results must include a data-sharing statement describing whether individual deidentified participant data and related materials will be shared, what will be available, when and for how long, and the applicable access criteria. Intervention descriptions should use TIDieR and, for exercise programmes when applicable, CERT.
Every Original Research article requires a Data Availability Statement. A Code Availability Statement is required when custom analytical or processing code materially supports the work. Reused datasets and software with persistent identifiers should be formally cited, including the exact version or release when available.
Report ethics approval, consent and privacy protections where applicable. General funding, competing-interest, CRediT, ORCID, AI-use, image-integrity and language-support requirements are stated in the main Author Guidelines.
