Literature DB >> 30285277

Predicting the time needed for environmental systematic reviews and systematic maps.

Neal R Haddaway1,2, Martin J Westgate3.   

Abstract

Systematic reviews (SRs) and systematic mapping aim to maximize transparency and comprehensiveness while minimizing subjectivity and bias. These are time-consuming and complex tasks, so SRs are considered resource intensive, but published estimates of systematic-review resource requirements are largely anecdotal. We analyzed all Collaboration for Environmental Evidence (CEE) SRs (n = 66) and maps (n = 20) published from 2012 to 2017 to estimate the average number of articles retained at each review stage. We also surveyed 33 experienced systematic reviewers to collate information on the rate at which those stages could be completed. In combination, these data showed that the average CEE SR takes an estimated 164 d (full-time equivalent) (SD 23), and the average CEE systematic map (SM) (excluding critical appraisal) takes 211 d (SD 53). While screening titles and abstracts is widely considered time-consuming, metadata extraction and critical appraisal took as long or longer to complete, especially for SMs. Given information about the planned methods and evidence base, we created a software tool that predicts time requirements of a SR or map with evidence-based defaults as a starting point. Our results shed light on the most time-consuming stages of the SR and mapping processes, will inform review planning, and can direct innovation to streamline processes. Future predictions of effort required to complete SRs and maps could be improved if authors provide more details on methods and results.
© 2018 Society for Conservation Biology.

Entities:  

Keywords:  carga laboral; compromiso de tiempo; cost; costo; efficiency; eficiencia; evidence synthesis; literature review; revisión de literatura; síntesis de evidencias; time commitment; workload; 工作量; 成本; 投入时间; 效率; 文献综述; 证据综合

Mesh:

Year:  2018        PMID: 30285277     DOI: 10.1111/cobi.13231

Source DB:  PubMed          Journal:  Conserv Biol        ISSN: 0888-8892            Impact factor:   6.560


  9 in total

1.  MMiDaS-AE: Multi-modal Missing Data aware Stacked Autoencoder for Biomedical Abstract Screening.

Authors:  Eric W Lee; Byron C Wallace; Karla I Galaviz; Joyce C Ho
Journal:  Proc ACM Conf Health Inference Learn (2020)       Date:  2020-04-02

2.  Ensuring Prevention Science Research is Synthesis-Ready for Immediate and Lasting Scientific Impact.

Authors:  Emily A Hennessy; Rebecca L Acabchuk; Pieter A Arnold; Adam G Dunn; Yong Zhi Foo; Blair T Johnson; Sonya R Geange; Neal R Haddaway; Shinichi Nakagawa; Witness Mapanga; Kerrie Mengersen; Matthew J Page; Alfredo Sánchez-Tójar; Vivian Welch; Luke A McGuinness
Journal:  Prev Sci       Date:  2021-07-21

3.  Systematic evidence maps as a novel tool to support evidence-based decision-making in chemicals policy and risk management.

Authors:  Taylor A M Wolffe; Paul Whaley; Crispin Halsall; Andrew A Rooney; Vickie R Walker
Journal:  Environ Int       Date:  2019-06-26       Impact factor: 9.621

4.  Research Screener: a machine learning tool to semi-automate abstract screening for systematic reviews.

Authors:  Kevin E K Chai; Robin L J Lines; Daniel F Gucciardi; Leo Ng
Journal:  Syst Rev       Date:  2021-04-01

5.  The REPRISE project: protocol for an evaluation of REProducibility and Replicability In Syntheses of Evidence.

Authors:  Matthew J Page; David Moher; Fiona M Fidler; Julian P T Higgins; Sue E Brennan; Neal R Haddaway; Daniel G Hamilton; Raju Kanukula; Sathya Karunananthan; Lara J Maxwell; Steve McDonald; Shinichi Nakagawa; David Nunan; Peter Tugwell; Vivian A Welch; Joanne E McKenzie
Journal:  Syst Rev       Date:  2021-04-16

Review 6.  Toward Automated Data Extraction According to Tabular Data Structure: Cross-sectional Pilot Survey of the Comparative Clinical Literature.

Authors:  Kevin Kallmes; Karl Holub; Nicole Hardy
Journal:  JMIR Form Res       Date:  2021-11-24

7.  Systematic Mapping Study of AI/Machine Learning in Healthcare and Future Directions.

Authors:  Gaurav Parashar; Alka Chaudhary; Ajay Rana
Journal:  SN Comput Sci       Date:  2021-09-16

8.  Evidence on the impact of Baltic Sea ecosystems on human health and well-being: a systematic map.

Authors:  Joanna Storie; Monika Suškevičs; Fiona Nevzati; Mart Külvik; Tinka Kuhn; Benjamin Burkhard; Suvi Vikström; Virpi Lehtoranta; Simo Riikonen; Soile Oinonen
Journal:  Environ Evid       Date:  2021-11-06

Review 9.  Systematic map of conservation psychology.

Authors:  Kenneth E Wallen; Adam C Landon
Journal:  Conserv Biol       Date:  2020-12       Impact factor: 6.560

  9 in total

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