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Record W2336078844 · doi:10.1002/jclp.22296

A Competency Framework for the Practice of Psychology: Procedures and Implications

2016· article· en· W2336078844 on OpenAlexaffabout
John Hunsley, Howard Spivak, Jack B. Schaffer, Darcy Cox, Carla Caro, Emil Rodolfa, Sandra Greenberg

Bibliographic record

VenueJournal of Clinical Psychology · 2016
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of British ColumbiaUniversity of Ottawa
Fundersnot available
KeywordsLicensurePracticumInternshipPsychologyMedical educationApplied psychologyCredentialingSurvey data collectionCompetence (human resources)Social psychologyPedagogyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Several competency models for training and practice in professional psychology have been proposed in the United States and Canada. Typically, the procedures used in developing and finalizing these models have involved both expert working groups and opportunities for input from interested parties. What has been missing, however, are empirical data to determine the degree to which the model reflects the views of members of the profession as a whole. METHOD: Using survey data from 466 licensed or registered psychologists (approximately half of whom completed one of two versions of the survey), we examined the degree to which psychologists, both those engaged primarily in practice and those involved in doctoral training, agreed with the competency framework developed by the Association of State and Provincial Psychology Boards' Practice Analysis Task Force (Rodolfa et al., 2013). RESULTS: When distinct time points in training and licensure or registration were considered (i.e., entry-level supervised practice in practicum settings, advanced-level supervised practice during internship, entry level independent practice, and advanced practice), there was limited agreement by survey respondents with the competency framework's proposal about when specific competencies should be attained. In contrast, greater agreement was evident by respondents with the competency framework when the reference point was focused on entry to independent practice (i.e., the competencies necessary for licensure or registration). CONCLUSION: We discuss the implications of these findings for the development of competency models, as well as for the implementation of competency requirements in both licensure or registration and training contexts.

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)0.005
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.827
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.177
GPT teacher head0.578
Teacher spread0.401 · 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 designOther design
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

Citations12
Published2016
Admission routes2
Has abstractyes

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