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Record W3009865029 · doi:10.1002/capr.12306

Understanding supervisee nondisclosures in supervision with videorecording review and interpersonal process recall

2020· article· en· W3009865029 on OpenAlexaffabout
Allison J. Foskett, K. Jessica Van Vliet

Bibliographic record

VenueCounselling and Psychotherapy Research · 2020
Typearticle
Languageen
FieldPsychology
TopicCounseling Practices and Supervision
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologyDyadRecallPracticumThematic analysisInterpersonal communicationQualitative researchAnxietySession (web analytics)Clinical psychologyApplied psychologySocial psychologyPsychotherapistMedical educationPedagogyMedicinePsychiatryCognitive psychology

Abstract

fetched live from OpenAlex

Abstract The purpose of this qualitative multiple case study was to obtain an in‐depth understanding of supervisees' in‐the‐moment nondisclosure experiences, perceptions and internal processes as they occurred in clinical supervision involving videorecording review. The supervisees who participated in the study were students in their first year of a master's‐level counselling practicum in Western Canada. Utilising interpersonal process recall (IPR) interview methods, supervisees were asked to share their moment‐by‐moment nondisclosures that occurred during a recent videorecorded supervision session in which the supervisory dyad reviewed a videorecording of the supervisee's clinical work. Thematic analysis across cases yielded five overarching themes: (a) validation; (b) safety; (c) growth and accomplishment; (d) performance anxiety; and (e) avoidance. The findings revealed a broad range of positive and negative supervisee nondisclosures that were influenced by the supervision modality of videorecording review and the IPR interview. Implications for clinical supervision, limitations of the study and suggestions for future research are discussed.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.305
GPT teacher head0.443
Teacher spread0.138 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations1
Published2020
Admission routes2
Has abstractyes

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