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Record W2281959534 · doi:10.1186/1745-6215-16-s2-o81

Do pragmatic trials trade-off internal validity for external validity?

2015· article· en· W2281959534 on OpenAlexaff
Kirsty Loudon, Merrick Zwarenstein, Frank Sullivan, Peter T. Donnan, Shaun Treweek

Bibliographic record

VenueTrials · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsExternal validityInternal validityMedicinePsychologySocial psychologyPathology

Abstract

fetched live from OpenAlex

Trials can be described as being on a design spectrum between highly explanatory (roughly, ‘Can the intervention work?’) to highly pragmatic (‘Does the intervention work in routine care?’). A criticism levelled at trials that take a pragmatic approach is that they sacrifice internal validity for external validity, i.e. there is a trade-off to be made. Proponents of pragmatic trials argue that there is no trade-off. However, both critics and defenders of the pragmatic approach have made their arguments in the absence of empirical evidence one way or the other. As part of our work developing the PRECIS-2 trial design tool, we looked for evidence of the validity trade-off in two ways. Firstly, a sample of 14 cardiovascular explanatory trials was matched to trials of the same intervention but which took a more pragmatic design approach. Secondly, 23 trials included in a Cochrane review of first-line treatment for hypertension were compared. The Cochrane Risk of Bias tool was used to assess internal validity; PRECIS-2 was used to assess design approach. We found no clear difference in Cochrane Risk of Bias assessments between trials taking explanatory and pragmatic approaches. Work with a larger sample of trials is required before we can be completely confident in this result but this represents the first evidence that the suggested trade-off between internal and external validity in trials may be false. This work is part of the Trial Forge initiative to improve trial efficiency.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
gptMetaresearch
Domain: Methods · Genre: Methods
About the Canadian research system: no · About a Canadian topic: no
Theoretical or conceptuallow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.338
metaresearch head score (Gemma)0.199
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.533
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.3380.199
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.851
GPT teacher head0.557
Teacher spread0.295 · 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

Labeled directly by 2 models reading the full record.

Study designTheoretical or conceptual
DomainMethods
GenreEmpirical · Methods

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

Citations5
Published2015
Admission routes1
Has abstractyes

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