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Record W4398237358 · doi:10.1037/ser0000854

Training guidelines and competencies for serious mental illness (SMI) psychology.

2024· article· en· W4398237358 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

VenuePsychological Services · 2024
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsColumbia College
Fundersnot available
KeywordsMental illnessPsychologyClinical psychologyApplied psychologyPsychiatryPsychotherapistMental health

Abstract

fetched live from OpenAlex

Individuals with serious mental illness (SMI) face unique and significant challenges that require evidence-based practices and clinicians who have advanced, comprehensive training to provide them. SMI affects about 5.5% of the U.S. population and results in serious health, social, and economic burdens. Despite advancements in treatment over the past 50 years, training programs for psychologists and other mental health providers have failed to keep up with these advances, underutilizing evidence-based assessments and interventions developed specifically for this population and found to be efficacious. To address this, the SMI Psychology Specialty has developed Training Guidelines to establish consistent, high-quality, and evidence-based training for postdoctoral psychologists. This article highlights selected features of the Training Guidelines for SMI Psychology. Although these were developed for postdoctoral training programs in SMI Psychology, they are applicable to training programs at all levels, and we hope that training programs in psychology and other mental health disciplines will incorporate these advances into their curricula. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.147
GPT teacher head0.453
Teacher spread0.306 · 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