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Record W2045696982 · doi:10.1080/10503307.2014.963729

The therapeutic factor inventory-8: Using item response theory to create a brief scale for continuous process monitoring for group psychotherapy

2014· article· en· W2045696982 on OpenAlexafffund
Giorgio A. Tasca, Christine Cabrera, Elizabeth Kristjansson, Rebecca MacNair-Semands, Anthony S. Joyce, John S. Ogrodniczuk

Bibliographic record

VenuePsychotherapy Research · 2014
Typearticle
Languageen
FieldPsychology
TopicPsychotherapy Techniques and Applications
Canadian institutionsUniversity of AlbertaUniversity of OttawaUniversity of British ColumbiaOttawa Hospital
FundersCanadian Institutes of Health Research
KeywordsPsychologyPsychotherapistItem response theoryScale (ratio)Group psychotherapyPredictive validityClinical psychologyPsychometrics

Abstract

fetched live from OpenAlex

OBJECTIVE: We tested a very brief version of the 23-item Therapeutic Factors Inventory-Short Form (TFI-S), and describe the use of Item Response Theory (IRT) for the purpose of developing short and reliable scales for group psychotherapy. METHOD: Group therapy patients (N = 578) completed the TFI-S on one occasion, and their data were used for the IRT analysis. Of those, 304 completed the TFI-S and other measures on more than one occasion to assess sensitivity to change, concurrent, and predictive validity of the brief version. RESULTS: Results suggest that the new TFI-8 is a brief, reliable, and valid measure of a higher-order group therapeutic factor. CONCLUSION: The TFI-8 may be used for continuous process measurement and feedback to improve the functioning of therapy groups.

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)0.009
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.030
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.145
GPT teacher head0.502
Teacher spread0.357 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations30
Published2014
Admission routes2
Has abstractyes

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