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Record W2127443831 · doi:10.1037/pst0000013

WELLFOCUS PPT: Modifying positive psychotherapy for psychosis.

2015· article· en· W2127443831 on OpenAlexaff
Simon Riches, Beate Schrank, Tayyab Rashid, Mike Slade

Bibliographic record

VenuePsychotherapy · 2015
Typearticle
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersNational Institute for Health and Care Research
KeywordsGratitudePsychologyPsychotherapistIntervention (counseling)PsychosisClinical psychologySession (web analytics)ForgivenessPositive psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Positive psychotherapy (PPT) is an established psychological intervention initially validated with people experiencing symptoms of depression. PPT is a positive psychology intervention, an academic discipline that has developed somewhat separately from psychotherapy and focuses on amplifying well-being rather than ameliorating deficit. The processes targeted in PPT (e.g., strengths, forgiveness, gratitude, savoring) are not emphasized in traditional psychotherapy approaches to psychosis. The goal in modifying PPT is to develop a new clinical approach to helping people experiencing psychosis. An evidence-based theoretical framework was therefore used to modify 14-session standard PPT into a manualized intervention, called WELLFOCUS PPT, which aims to improve well-being for people with psychosis. Informed by a systematic review and qualitative research, modification was undertaken in 4 stages: qualitative study, expert consultation, manualization, and stake-holder review. The resulting WELLFOCUS PPT is a theory-based 11-session manualized group therapy.

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)0.005
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.079
GPT teacher head0.387
Teacher spread0.309 · 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 designNot applicable
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

Citations40
Published2015
Admission routes1
Has abstractyes

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