International Journal of Negative Results invites submissions that report negative, null, or inconclusive results across scientific disciplines. We welcome rigorous studies that challenge assumptions, test replication, or document unexpected outcomes that advance knowledge.

Our editorial focus prioritizes methodological transparency, complete outcome reporting, and clear interpretation of null findings.

• Replication studies and reproducibility assessments
• Null results in clinical trials or observational studies
• Non-confirmatory findings in laboratory research
• Negative outcomes in engineering or computational methods
• Unexpected results in social and behavioral sciences
• Methodological papers reporting failed approaches
• Meta-analyses including unpublished negative findings
• Bias reduction and publication transparency research
• Protocol deviations and learning from null outcomes
• Data-driven reviews of null or inconclusive evidence
• Negative findings in AI, modeling, or algorithm performance
• Inconclusive results with strong methodological rigor

• Replication studies and validation reports
• Short communications of rigorous negative results
• Registered reports and confirmatory protocols
• Policy or perspective pieces on publication bias

Successful submissions provide a clear hypothesis, robust methodology, and transparent reporting of null outcomes. We value studies that explain why negative results are informative and how they refine future research directions.

Authors should document protocols, statistical power, and limitations so results can be interpreted with confidence.

• Clear hypotheses and predefined outcomes
• Transparent statistical analysis and confidence intervals
• Complete reporting of all outcomes and deviations
• Interpretation that links null results to field advancement

Submissions undergo editorial screening for scope fit, methodological rigor, and reporting completeness. Qualified manuscripts move to single blind peer review with subject matter experts.

IJNR operates under an open access model to ensure negative results research is discoverable and reusable. APCs are applied after acceptance and support peer review, production, and archiving services.

Membership options and affordable APC waivers are available for eligible authors. Contact the editorial office at [email protected] for guidance.

• Scope fit confirmed for negative or null results
• Hypotheses and outcomes clearly stated
• Data availability statement included
• Ethics approvals and consent described
• Cover letter explains why negative results matter
• State the original hypothesis and describe how results differed from expectations.
• Report preregistration details or explain why preregistration was not used.
• Provide power calculations and rationale for sample size.
• Include full outcome reporting, including null or secondary findings.
• Describe methods for handling missing data and protocol deviations.
• Report negative or inconclusive results with confidence intervals.
• Clarify whether analyses were exploratory or confirmatory.
• Provide data availability statements and repository links when possible.
• Describe statistical tests and effect size measures used.
• Report any changes to the study protocol after initiation.
• Include transparency about measurement error or instrument limits.
• Describe replication attempts and alignment with prior studies.
• Report quality control steps and data validation checks.
• Include a limitations section with implications for future work.
• Disclose funding sources and potential conflicts of interest.
• Provide ethics approvals and consent documentation where required.
• Explain why negative results are informative for the field.
• Report confidence in null findings and sensitivity analyses.
• Include model assumptions and diagnostic checks for statistical models.
• State inclusion and exclusion criteria clearly.
• Describe stopping rules or interim analyses if used.
• Provide details on instrument calibration and accuracy.
• Document data preprocessing steps and software versions.
• Clarify definitions for primary and secondary outcomes.
• Provide raw data summaries or descriptive statistics.
• Explain decisions to terminate or alter experiments.
• Describe replication materials and protocols for reuse.
• Include null result interpretation without overstating conclusions.
• Report comparison against established benchmarks or baselines.
• Provide metadata on datasets to support reuse.
• Describe environmental or contextual factors affecting outcomes.
• Report adverse events or unintended outcomes if relevant.
• Provide timelines for data collection and analysis.
• Clarify whether findings generalize beyond the study context.
• Provide transparency on data exclusion rules and outlier handling.
• Describe sensitivity analyses for key assumptions.
• Provide access instructions for restricted datasets.
• Explain implications for future replication or meta analysis.
• Include a summary of practical lessons learned.
• Describe randomization or blinding procedures even when results are null.
• Report measurement reliability and inter-rater agreement where relevant.
• Clarify whether analyses were adjusted for multiple comparisons.
• Provide details on data collection instruments and validation.
• Explain how negative results influence future study design.
• Report deviations from preregistered analysis plans.
• Include code availability and reproducibility steps.
• Describe calibration of equipment and control conditions used.
• Provide sensitivity analyses or robustness checks.
• State limitations related to sample heterogeneity.
• Report effect direction even if not statistically significant.
• Discuss implications for theory refinement or model revision.
• Include justification for comparator or control selection.
• Report recruitment or enrollment challenges and impact on results.
• Provide access to materials, stimuli, or questionnaires used.
• Describe data censoring or truncation methods applied.
• Report compliance or adherence rates in interventions.
• Provide reasoning for null effects in the discussion.
• Include negative findings in supplementary tables if needed.
• Describe quality assurance for data entry and cleaning.
• Summarize how null results refine the research question.

IJNR is committed to rigorous, transparent publishing of negative, null, and inconclusive results. We emphasize reproducible methods, full outcome reporting, and ethical compliance across all article types.

The editorial office supports authors, editors, and reviewers with clear guidance and responsive communication. For questions about scope or workflow, contact [email protected].

We encourage complete reporting, data availability, and candid discussion of limitations to strengthen the research record.