MétaCan
Menu
Back to cohort
Record W3159498050 · doi:10.1016/s2215-0366(21)00077-8

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data

2021· review· en· W3159498050 on OpenAlexafffund
Toshi A. Furukawa, Aya M Suganuma, Edoardo G. Ostinelli, Gerhard Andersson, Christopher G. Beevers, Jason Shumake, Thomas Berger, Florien Boele, Claudia Buntrock, Per Carlbring, Isabella Choi, Helen Christensen, Andrew Mackinnon, Jennifer Dahne, Marcus J. H. Huibers, David Daniel Ebert, Louise M. Farrer, Nicholas R. Forand, Daniel R. Strunk, Iony D. Ezawa, Erik Forsell, Viktor Kaldo, Anna Geraedts, Simon Gilbody, Elizabeth Littlewood, Sally Brabyn, Heather D. Hadjistavropoulos, Luke H. Schneider, Robert Johansson, Robin Maria Francisca Kenter, Marie Kivi, Cecilia Björkelund, Annet Kleiboer, Heleen Riper, Jan Philipp Klein, Johanna Schröder, Björn Meyer, Steffen Moritz, Lara Bücker, Ove Lintvedt, Peter Johansson, Johan Lundgren, Jeannette Milgrom, Alan W. Gemmill, David C. Mohr, Jesús Montero‐Marín, Javier García‐Campayo, Stephanie Nobis, Anna‐Carlotta Zarski, Kathleen O’Moore, Alishia D. Williams, Jill M. Newby, Sarah Perini, Rachel Phillips, Justine Schneider, Wendy Pots, Nicole E. Pugh, Derek Richards, Isabelle M. Rosso, Scott L. Rauch, Lisa Sheeber, Jessica Smith, Viola Spek, Victor J. Pop, Burçin Ünlü, K.M.P. van Bastelaar, Sanne van Luenen, Nadia Garnefski, Vivian Kraaij, Kristofer Vernmark, Lisanne Warmerdam, Annemieke van Straten, Pavle Zagorscak, Christine Knaevelsrud, Manuel Heinrich, Clara Miguel, Andrea Cipriani, Orestis Efthimiou, Eirini Karyotaki, Pim Cuijpers

Bibliographic record

VenueThe Lancet Psychiatry · 2021
Typereview
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsSt. Joseph’s Healthcare HamiltonUniversity of Regina
FundersNational Institute of Mental HealthNational Institute on Drug AbuseJapan Society for the Promotion of ScienceZonMwCanadian Institutes of Health ResearchNational Institute for Health and Care ResearchWellcome TrustSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsDepression (economics)Component (thermodynamics)Meta-analysisThe InternetCognitionSystematic reviewComputer sciencePsychologyMEDLINEClinical psychologyApplied psychologyData scienceMedicinePsychiatryWorld Wide WebBiologyPathology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.007
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0120.020
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.659
GPT teacher head0.530
Teacher spread0.129 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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

Citations265
Published2021
Admission routes2
Has abstractno

Explore more

Same venueThe Lancet PsychiatrySame topicDigital Mental Health InterventionsFrench-language works237,207