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Record W2998499817 · doi:10.1186/s12961-019-0498-y

Stakeholders’ experiences with the evidence aid website to support ‘real-time’ use of research evidence to inform decision-making in crisis zones: a user testing study

2019· article· en· W2998499817 on OpenAlexaff
Ahmad Firas Khalid, John N. Lavis, Fadi El‐Jardali, Meredith Vanstone

Bibliographic record

VenueHealth Research Policy and Systems · 2019
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsMcMaster UniversityImpactMcMaster University Medical Centre
Fundersnot available
KeywordsCredibilityUsabilityEvidence-based practicePublic relationsHealth carePsychologyMedicineMedical educationPolitical scienceComputer scienceAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Humanitarian action in crisis zones is fraught with many challenges, including lack of timely and accessible research evidence to inform decision-making about humanitarian interventions. Evidence websites have the potential to address this challenge. Evidence Aid is the only evidence website designed for crisis zones that focuses on providing research evidence in the form of systematic reviews. The objective of this study is to explore stakeholders' views of Evidence Aid, contributing further to our understanding of the use of research evidence in decision-making in crisis zones. METHODS: We designed a qualitative user-testing study to collect interview data from stakeholders about their impressions of Evidence Aid. Eligible stakeholders included those with and without previous experience of Evidence Aid. All participants were either currently working or have worked within the last year in a crisis zone. Participants were asked to perform the same user experience-related tasks and answer questions about this experience and their knowledge needs. Data were analysed using a deductive framework analysis approach drawing on Morville's seven facets of the user experience - findability, usability, usefulness, desirability, accessibility, credibility and value. RESULTS: A total of 31 interviews were completed with senior decision-makers (n = 8), advisors (n = 7), field managers (n = 7), analysts/researchers (n = 5) and healthcare providers (n = 4). Participant self-reported knowledge needs varied depending on their role. Overall, participants did not identify any 'major' problems (highest order) and identified only two 'big' problems (second highest order) with using the Evidence Aid website, namely the lack of a search engine on the home page and that some full-text articles linked to/from the site require a payment. Participants identified seven specific suggestions about how to improve Evidence Aid, many of which can also be applied to other evidence websites. CONCLUSIONS: Stakeholders in crisis zones found Evidence Aid to be useful, accessible and credible. However, they experienced some problems with the lack of a search engine on the home page and the requirement for payment for some full-text articles linked to/from the site.

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)0.052
metaresearch head score (Gemma)0.106
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.275

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0520.106
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0020.006
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.781
GPT teacher head0.637
Teacher spread0.144 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations7
Published2019
Admission routes1
Has abstractyes

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