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Record W2900189521 · doi:10.1016/j.jad.2018.11.034

Validation of the University of California San Diego Performance-based Skills Assessment (UPSA) in major depressive disorder: Replication and extension of initial findings

2018· article· en· W2900189521 on OpenAlexaff
Michael Cronquist Christensen, Lasse B. Sluth, Roger S. McIntyre

Bibliographic record

VenueJournal of Affective Disorders · 2018
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of TorontoUniversity Health Network
FundersH. Lundbeck A/S
KeywordsReplication (statistics)Extension (predicate logic)PsychologyMajor depressive disorderClinical psychologyPsychiatryGerontologyMedicineComputer scienceVirology

Abstract

fetched live from OpenAlex

BACKGROUND: The University of California San Diego Performance-based Skills Assessment (UPSA) has been validated as a functional measure in patients with major depressive disorder (MDD). The study herein aims to both replicate and extend the initial validation incorporating data sets from two additional studies. METHODS: NCT02279966 and NCT02272517 were multinational, double-blind, placebo-controlled studies in adult outpatients with moderate-to-severe MDD and a current major depressive episode of ≥3 months and less than 1 year, respectively. Subjects were randomized to vortioxetine (10 or 20 mg), placebo or active reference drug (paroxetine [20 mg], or escitalopram [10 or 20 mg]) for 8 weeks. Pearson correlation coefficients were estimated for baseline UPSA-Brief (UPSA-B), demographic/disease characteristics, Montgomery-Åsberg Depression Rating Scale (MADRS), Perceived Deficit Questionnaire-20 items (PDQ-20), and Digit Symbol Substitution Test (DSST), to examine construct validity. Distribution- and anchor-based methods examined clinically important difference (CID) threshold. A pooled analysis with data from NCT01564862 (initial validation study) was performed to increase the statistical power of the estimations. RESULTS: In pooled analysis of the two new studies, UPSA-B score correlated with the DSST (r = 0.32, P < 0.0001), but not the MADRS (r = -0.07, p = 0.302) or the PDQ-20 (r = -0.10, p = 0.109), replicating initial validation results. Estimated CID range was 7.1-11.2 and 5.5-6.1 points for anchor- and distribution-based methods, respectively. In pooled analyses of all three studies, the CID was 7.0 and 6.4 for anchor- and distribution-based methods, respectively. CONCLUSIONS: These results confirm the construct validity of UPSA for assessing functional capacity in patients with MDD. Estimated CID using UPSA is approximately 6-7 points. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01564862; NCT02272517; NCT02279966.

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)0.064
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.341

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0640.071
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.283
Teacher spread0.275 · 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 designObservational
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

Citations9
Published2018
Admission routes1
Has abstractyes

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