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Record W2044174064 · doi:10.1002/da.20566

A comparison of depressed patients in randomized versus nonrandomized trials of antidepressant medication and psychotherapy

2009· article· en· W2044174064 on OpenAlexaff
Shauna C. Kushner, Lena C. Quilty, Carolina McBride, R. Michael Bagby

Bibliographic record

VenueDepression and Anxiety · 2009
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsRandomized controlled trialMedicineMajor depressive disorderPsychiatryPopulationPersonalityClinical psychologyPhysical therapyPsychologyInternal medicineMood

Abstract

fetched live from OpenAlex

BACKGROUND: Clinicians and researchers have questioned whether participants in randomized control trials (RCTs) are representative of patients in the broader clinical population. METHOD: We compared the demographic, clinical, and personality characteristics of patients (N=256) with major depressive disorder (MDD) receiving antidepressant medication or interpersonal therapy as part of an RCT investigation (n=105) versus in a clinic (n=151). The RCT and clinic protocols were identical with the exception of recruitment procedures (advertisement versus physician referral) and assignment to treatment (randomized versus nonrandomized). RESULTS: No significant differences emerged between the RCT participants and clinic patients for sex, age, marital status, and education. Overall, clinic patients were no more severely depressed compared to RCT participants; there was, however, a significant interaction effect. Response rates were significantly higher for RCT participants versus clinic patients. Those participating in the RCT scored significantly higher on a personality scale assessing preference for novel experiences compared to those in the clinic. CONCLUSIONS: Differences in clinical and personality variables between those receiving treatment for MDD as part of an RCT versus in a clinic exist; however, the clinical significance of these differences remains in question, as these variables were unrelated to treatment outcome.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.559

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.382
Teacher spread0.345 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations24
Published2009
Admission routes1
Has abstractyes

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