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Record W2147978070 · doi:10.1136/bmjopen-2014-005919

A usability study of two formats of a shortened systematic review for clinicians

2014· article· en· W2147978070 on OpenAlexafffund
Laure Perrier, M. Ryan Kealey, Sharon E. Straus

Bibliographic record

VenueBMJ Open · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicMeta-analysis and systematic reviews
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsUsabilityThink aloud protocolMedicineSystem usability scaleSystematic reviewWeb usabilityComputer scienceMEDLINEApplied psychologyHuman–computer interactionMedical educationPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to evaluate the usability of two formats of a shortened systematic review for clinicians. MATERIALS AND METHODS: Usability of the prototypes was assessed using three cycles of iterative testing. 10 participants were asked to complete tasks of locating information or items within two prototypes and 'think aloud' while being audio taped. Interviews were also audio recorded and participants completed a systematic usability scale. RESULTS: Revisions were made between each iteration in order to address issues identified by participants. Finding information relating to the number of studies in the meta-analysis, and locating the number of studies in the entire systematic review were revealed as areas needing attention during the usability evaluation. CONCLUSIONS: Iterative testing combined with a multifaceted approach to usability testing offered essential insight into aspects of the prototypes that required modifications. Alterations were made in order to create finalised versions of the two shortened systematic review formats.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.390
metaresearch head score (Gemma)0.750
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.752

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3900.750
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0080.006
Science and technology studies0.0020.003
Scholarly communication0.0070.008
Open science0.0030.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.872
GPT teacher head0.671
Teacher spread0.201 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations19
Published2014
Admission routes2
Has abstractyes

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