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Record W2058667104 · doi:10.1017/s1041610200006505

Qualitative Analysis of the Clinician Interview-Based Impression of Change (Plus): Methodological Issues and Implications for Clinical Research

2000· article· en· W2058667104 on OpenAlexaff
Christine Joffres, Janice Graham, Kenneth Rockwood

Bibliographic record

VenueInternational Psychogeriatrics · 2000
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsPsychologyQualitative researchClinical psychologySociology

Abstract

fetched live from OpenAlex

The Clinician Interview-Based Impression of Change, plus carer interview (CIBIC-Plus), is widely used in antidementia drug trials. It comprises Likert scales for disease severity and changes, and written accounts summarizing semistructured interviews evaluating behavior, cognition, and function. Studies using the CIBIC-Plus have focused on the numeric scores to the exclusion of the textual data. Our study explored both sets of data to evaluate whether the CIBIC-Plus written data supported (a) the clinicians' global evaluation of patients' changes during treatment, and (b) the emergence of consistent treatment effects. The global (numeric) scales of change were inconsistently supported by the textual data provided in the CIBIC-Plus. No consistent treatment effects were noted. Methodological problems presently limit the retrospective use of the CIBIC-Plus textual data. Improved standardization of note-taking in the CIBIC-Plus textual data may allow for a better understanding of the typical profiles and clinical importance of changes seen in the course of dementia treatment.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.367
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.704
GPT teacher head0.695
Teacher spread0.010 · 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 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

Citations48
Published2000
Admission routes1
Has abstractyes

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