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Record W2974443830 · doi:10.1097/xeb.0000000000000202

Evaluation of the JBI scoping reviews methodology by current users

2019· article· en· W2974443830 on OpenAlexaff
Hanan Khalil, Marsha Bennett, Christina Godfrey, Patricia McInerney, Zac Munn, Micah D.J. Peters

Bibliographic record

VenueInternational Journal of Evidence-Based Healthcare · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsQueen's University
Fundersnot available
KeywordsSystematic reviewDescriptive statisticsMedical educationWork (physics)PsychologyMEDLINEMedicineEngineeringPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: In 2014, JBI Database of Systematic Reviews and Implementation Reports published a comprehensive methodology for the conduct and reporting of scoping reviews based on previous frameworks and guidance. Further work on scoping review methodology and particularly reporting is needed. To assist with refinements to the methodology, this survey was undertaken to evaluate users' experiences of following the process methodology. An electronic survey was generated to explore authors' experiences with the methodology and to seek feedback on the stages of scoping review development. METHOD: An online survey administered using Qualtrics - a secure survey platform - was distributed through invitations to a total of 51 registered users in the Joanna Briggs Database of Systematic reviews and Implementation reports. We analysed the questionnaire data using descriptive statistics. The qualitative data were grouped together, and free text comments were inductively themed and coded by the authors. RESULTS: Thirty-one participants completed the survey (response rate of 61%). The majority of the participants identified themselves as researchers (55%) followed by educators (25%). Most participants were university employees (77%) and only 10% were based in hospitals. Forty-two percent of the participants reported that the scoping review they had been involved with had taken between 6 and 12 months, and 32% of participants spent over a year completing their reviews. Eighty-seven percent of participants stated that their scoping reviews led to further work such as developing a systematic review, a basis for a grant application, formation of a part of students' doctoral studies, and informing further work in a research project. Some of the limitations listed by the participants were the lack of examples in each section of the methodology, especially in the inclusion criteria, and presentation of the results sections. CONCLUSION: The overall evaluation by the participants of the JBI scoping review methodology highlighted the need for additional detailed guidance for inclusion criteria and presentation of the results. Provision of clear examples for each step was also requested for future improvement.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.321
metaresearch head score (Gemma)0.140
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3210.140
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.964
GPT teacher head0.697
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations86
Published2019
Admission routes1
Has abstractyes

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