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Record W1974131713 · doi:10.5920/mhldrp.2005.2111

Rewiring efficacy studies to increase their relevance to routine practice

2005· article· en· W1974131713 on OpenAlexfundno aff
Michael Barkham, Chris Leach, David A. Shapiro, Gillian E. Hardy, Mike Lucock, Anne Rees

Bibliographic record

VenueMental Health and Learning Disabilities Research and Practice · 2005
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsnot available
FundersPetroleum Technology Research Centre
KeywordsRelevance (law)PsychologyBeck Depression InventoryReplication (statistics)PropositionPsychotherapistBridging (networking)Core (optical fiber)Clinical psychologyComputer sciencePsychiatryMedicineEpistemologyPolitical science

Abstract

fetched live from OpenAlex

Current efficacy literature relies heavily on the Beck Depression Inventory (BDI) as the gold standard patient self-report measure. In contrast, the evaluation of psychological therapies in routine practice relies heavily on the CORE-OM. Although the two measures are conceptually distinct, they have been shown to be highly correlated. This suggests the possibility of replacing one measure with the other - a procedure we refer to as rewiring - in service of making the results of efficacy studies using the BDI have greater relevance of practitioners who routinely use the CORE-OM. We tested this proposition using transformation tables (Leach et al., in press) to convert BDI-I scores into CORE-OM scores and reran the analysis of a major efficacy study of depression - the Second Sheffield Psychotherapy Project (Shapiro et al., 1994). Results showed a near perfect replication of the original results and examples of benchmarks concerning the overall effects of treatment as well as differences between treatments are provided against which outcomes in routine practice can be contrasted. The implications for bridging efficacy and effectiveness research are discussed.

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)0.006
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.173
GPT teacher head0.558
Teacher spread0.385 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2005
Admission routes1
Has abstractyes

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