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Record W2505670894 · doi:10.1080/02109395.2016.1189205

Forward thinking: correlates of posttreatment outcome expectation among depressed outpatients / <i>Pensamiento prospectivo: correlatos de las expectativas de resultados post-tratamiento de pacientes ambulatorios que sufren depresión</i>

2016· article· en· W2505670894 on OpenAlexaff
Michael J. Constantino, Andreea Vîslă, John S. Ogrodniczuk, Alice E. Coyne, Ingrid Söchting

Bibliographic record

VenueStudies in Psychology Estudios de Psicología · 2016
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyExpectancy theoryOutcome (game theory)Clinical psychologyDepression (economics)Cognitive therapyCognitionPsychotherapistPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Although patients’ expectation about a treatment’s efficacy correlate with beneficial therapy processes and outcomes, scant research addresses patients’ expectation for lasting improvement at treatment’s end. Given the influence of beliefs on psychological functioning, posttreatment outcome expectation reflects an important acute treatment outcome. In this study, we examined patient characteristics, treatment processes and clinical change factors in relation to the posttreatment outcome expectation of 65 depressed outpatients completing group cognitive-behavioural therapy. Less than 1% of variability in posttreatment outcome expectation was due to group effects; thus, we conducted single-level regressions. Patients with less severe baseline depression, higher session 3 outcome expectation, more during-treatment hope and a greater reduction in interpersonal problems reported greater posttreatment outcome expectancy. Various patient characteristics and change factors can help clinicians forecast, and respond to, those patients who will possess stronger or weaker belief in their ability to maintain therapy gains at treatment’s end.

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)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.049
GPT teacher head0.390
Teacher spread0.341 · 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.

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

Citations4
Published2016
Admission routes1
Has abstractyes

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