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Record W4289835820 · doi:10.1037/int0000290

Open label pilot study on posttrauma health impacts of the Processing of Positive Memories Technique (PPMT).

2022· article· en· W4289835820 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

VenueJournal of Psychotherapy Integration · 2022
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of Calgary
FundersNational Institute of General Medical SciencesNational Institute on Drug AbuseNational Institutes of Health
KeywordsAffect (linguistics)PsychologyClinical psychologyCognitionDepression (economics)Psychological interventionPosttraumatic stressIntervention (counseling)Cognitive processing therapyCognitive reappraisalPsychiatryCognitive therapy

Abstract

fetched live from OpenAlex

=29.25 years; 58.30% women). We used the reliable change indices and clinically significant change score approach. The following number of participants showed statistically reliable changes: 9 participants for PTSD severity (8 recovered/improved); 6 participants for depression severity (5 improved); 5 participants for positive affect levels (2 recovered/improved); 9 participants for negative affect levels (8 recovered); 9 participants for posttrauma cognitions (7 recovered/improved); 5 participants for positive emotion dysregulation (4 recovered); 11 participants for number of retrieved positive memories (3 recovered); and 5 participants for therapeutic alliance (4 recovered). PPMT may impact certain posttrauma targets more effectively (PTSD, depression, negative affect, posttrauma cognitions). PPMT may be more helpful in improving regulation rather than levels of positive affect. PPMT, if supported in further investigations, may add to the clinician tool-box of PTSD interventions.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.453
Threshold uncertainty score0.491

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.160
GPT teacher head0.483
Teacher spread0.323 · 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