Skip to content
DraconiticResearch
Search Sources API
181,716 studies31 sourcesUpdated 38 min ago
Peer-reviewedCC BY-NC 4.0BMJ Open

Reproducible study identification and selection in systematic reviews: barriers and paths forward

  • Lifeng Lin1
  • Xing Xing1,2
  • Chong Wu3
  • Yiqun Chen2
  • Jiayi Tong2
  • Deborah Jean McClelland4
  • Zhao Chen1
4 affiliations
  1. 1Department of Epidemiology and Biostatistics, The University of Arizona, Tucson, Arizona, USA
  2. 2Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
  3. 3Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
  4. 4Health Science Library, The University of Arizona, Tucson, Arizona, USA
Open at sourcePDFDOICite

Abstract

Systematic reviews are foundational to evidence-based practice, but the reproducibility and auditability of study identification and selection remain persistent challenges. Existing reporting standards, such as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and PRISMA-Search extension, have improved transparency, yet important gaps remain in documenting search strategies, retrieved records, screening decisions and supplementary identification methods. In this article, we discuss key barriers to reproducibility, including incomplete or inconsistent search documentation, limitations in date filter precision, restricted access to databases and platforms, non-repeatable supplementary search methods and variability in applying eligibility criteria. We suggest a minimum documentation set specifying the search histories, source-specific exports, record-management information, screening decisions and artificial intelligence (AI)-related records that review teams should preserve and share. We also recommend information-specialist involvement and carefully documented human-in-the-loop AI use. These strategies may not guarantee perfect reproducibility, but they can improve auditability, reduce research waste and strengthen trust in systematic reviews.

Related

  1. Common barriers and facilitators to the implementation of digital medicine in chronic respiratory diseases: a systematic review of reviews
    Julia Korel, Sebastian Kuhn, Rainer Gloeckl +16
    Frontiers in Digital HealthPeer-reviewedCC BYFull textEpidemiology & public healthDOAJ
  2. School-based mindfulness interventions in children and adolescents: an umbrella review of systematic reviews, with implications for physical education
    Claudia Arreza-Roca, Noelia González-Gálvez
    BMC Public HealthPeer-reviewedCC BY 4.0Epidemiology & public healthCrossref
  3. Structured medication reviews for adults with multimorbidity and polypharmacy in primary care: a systematic review
    Elena Lammila-Escalera, Geva Greenfield, Reham Aldakhil +6
    BMJ OpenPeer-reviewedCC BY 4.0Full textGeneral medicineCrossref
  4. Spin and Methodological Quality in Systematic Reviews of Decompression Timing for Central Cord Syndrome
    Marco Napolitano, Aidan Lindgren, Daniel Rusu +6
    Global Spine JournalPeer-reviewedCC BY-NC-NDFull textSurgery & anaesthesiaEurope PMC
  5. Risk factors for renal cell carcinoma: An umbrella review of systematic reviews and meta-analyses
    Sihan Chen, Yin Huang, Bo Chen +9
    BMC MedicinePeer-reviewedCC BY 4.0General medicineCrossref

Cite

BibTeXRIS
BibTeX
@article{lin2026reproducible,
  title = {{Reproducible study identification and selection in systematic reviews: barriers and paths forward}},
  author = {Lifeng Lin and Xing Xing and Chong Wu and Yiqun Chen and Jiayi Tong and Deborah Jean McClelland and Zhao Chen},
  journal = {BMJ Open},
  year = {2026},
  month = sep,
  doi = {10.1136/bmjopen-2026-123460},
  url = {https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-123460},
  note = {CC BY-NC 4.0},
}
RIS
TY  - JOUR
TI  - Reproducible study identification and selection in systematic reviews: barriers and paths forward
AU  - Lifeng Lin
AU  - Xing Xing
AU  - Chong Wu
AU  - Yiqun Chen
AU  - Jiayi Tong
AU  - Deborah Jean McClelland
AU  - Zhao Chen
PY  - 2026
DA  - 2026/09/30
JO  - BMJ Open
DO  - 10.1136/bmjopen-2026-123460
UR  - https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2026-123460
AB  - Systematic reviews are foundational to evidence-based practice, but the reproducibility and auditability of study identification and selection remain persistent challenges. Existing reporting standards, such as Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 and PRISMA-Search extension, have improved transparency, yet important gaps remain in documenting search strategies, retrieved records, screening decisions and supplementary identification methods. In this article, we discuss key barriers to reproducibility, including incomplete or inconsistent search documentation, limitations in date filter precision, restricted access to databases and platforms, non-repeatable supplementary search methods and variability in applying eligibility criteria. We suggest a minimum documentation set specifying the search histories, source-specific exports, record-management information, screening decisions and artificial intelligence (AI)-related records that review teams should preserve and share. We also recommend information-specialist involvement and carefully documented human-in-the-loop AI use. These strategies may not guarantee perfect reproducibility, but they can improve auditability, reduce research waste and strengthen trust in systematic reviews.
SN  - 2044-6055
SN  - 2044-6055
ER  -