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Record W2747517649 · doi:10.4088/jcp.16m11329

The THINC-Integrated Tool (THINC-it) Screening Assessment for Cognitive Dysfunction

2017· article· en· W2747517649 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Clinical Psychiatry · 2017
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsUniversity of British ColumbiaCentre for Addiction and Mental HealthUniversity Health NetworkUniversity of TorontoQueen's UniversityBrain and Cognition Discovery Foundation
Fundersnot available
KeywordsCognitionMedicineMajor depressive disorderCognitive testTrail Making TestDepression (economics)Digit symbol substitution testAudiologyPsychologyPsychiatryCognitive impairmentPlacebo

Abstract

fetched live from OpenAlex

OBJECTIVE: To validate the THINC-integrated tool (THINC-it)-a freely available, patient-administered, computerized screening tool integrating subjective and objective measures of cognitive function in adults with major depressive disorder (MDD). METHODS: Subjects aged 18 to 65 years (n = 100) with recurrent MDD experiencing a major depressive episode of at least moderate severity were evaluated and compared to age-, sex-, and education-matched healthy controls (n = 100). Between January and June 2016, subjects completed the THINC-it, which includes variants of the Choice Reaction Time Identification Task (IDN), One-Back Test, Digit Symbol Substitution Test, Trail Making Test-Part B, and the Perceived Deficits Questionnaire for Depression-5-item (PDQ-5-D). RESULTS: The THINC-it required approximately 10 to 15 minutes for administration and was capable of detecting cognitive deficits in adults with MDD. A total of 44.4% of adults with MDD exhibited cognitive performance at ≥ 1.0 SD below that of healthy controls on standardized mean scores of the THINC-it. Concurrent validity of the overall tool, based on a calculated composite score, was acceptable (r = 0.539, P < .001). Concurrent validity of the component tests ranged from -0.083 (IDN) to 0.929 (PDQ-5-D). Qualitative survey results indicated that there was a high level of satisfaction and perceived value in administering the THINC-it regarding its impact on the appropriateness and quality of care being received. CONCLUSIONS: The THINC-it is a valid and sensitive tool for detecting cognitive dysfunction in adults with MDD that is free, easy to use, and rapidly administered. The THINC-it should be incorporated into the assessment and measurement of all patients with MDD, particularly among those with enduring functional impairment. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT02508493.

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.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.103
GPT teacher head0.485
Teacher spread0.382 · 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